From 2966c2c3adf0cb1499284a43ddc69d611d72c604 Mon Sep 17 00:00:00 2001 From: ekmb Date: Thu, 9 Feb 2023 22:13:49 -0800 Subject: [PATCH 01/19] remove TN Signed-off-by: ekmb --- Dockerfile | 7 +- Jenkinsfile | 92 +- .../tts/aligner_heteronym_disambiguation.py | 12 +- .../{text_processing => tts}/g2p/README.md | 0 .../g2p/conf/g2p_conformer_ctc.yaml | 8 +- .../g2p/conf/heteronym_classification.yaml | 6 +- .../g2p/conf/t5_g2p.yaml | 6 +- .../g2p/g2p_inference.py | 2 +- .../g2p/g2p_train_and_evaluate.py | 4 +- .../g2p/heteronym_classification_inference.py | 2 +- ...ronym_classification_train_and_evaluate.py | 2 +- .../{text_processing => tts}/g2p/utils.py | 4 +- .../text_to_speech/tokenizer_wrapper.py | 2 +- .../text_to_speech/tts_tokenizers.py | 24 +- .../collections/tts/g2p/data}/__init__.py | 4 +- .../collections/tts}/g2p/data/ctc_g2p.py | 2 +- .../collections/tts}/g2p/data/data_utils.py | 0 .../g2p/data/heteronym_classification_data.py | 0 .../collections/tts}/g2p/data/t5_g2p.py | 2 +- 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RUN for f in $(ls requirements*.txt); do pip3 install --disable-pip-version-check --no-cache-dir -r $f; done -# install pynini -COPY nemo_text_processing/install_pynini.sh /tmp/nemo/ -RUN /bin/bash /tmp/nemo/install_pynini.sh - # install k2, skip if installation fails COPY scripts /tmp/nemo/scripts/ RUN /bin/bash /tmp/nemo/scripts/speech_recognition/k2/setup.sh || exit 0 @@ -81,8 +77,7 @@ RUN --mount=from=nemo-src,target=/tmp/nemo cd /tmp/nemo && pip install ".[all]" # Check install RUN python -c "import nemo.collections.nlp as nemo_nlp" && \ - python -c "import nemo.collections.tts as nemo_tts" && \ - python -c "import nemo_text_processing.text_normalization as text_normalization" + python -c "import nemo.collections.tts as nemo_tts" # TODO: Update to newer numba 0.56.0RC1 for 22.03 container if possible # install pinned numba version diff --git a/Jenkinsfile b/Jenkinsfile index f36839598941..bd8cbd78e906 100644 --- a/Jenkinsfile +++ b/Jenkinsfile @@ -102,92 +102,6 @@ pipeline { } } - - stage('L0: TN/ITN Tests CPU') { - when { - anyOf { - branch 'main' - changeRequest target: 'main' - } - } - failFast true - parallel { - stage('En TN grammars') { - steps { - sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/text_normalization/normalize.py --text="1" --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22' - } - } - stage('En ITN grammars') { - steps { - sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/inverse_text_normalization/inverse_normalize.py --language en --text="twenty" --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22' - } - } - stage('Test En non-deterministic TN & Run all En TN/ITN tests (restore grammars from cache)') { - steps { - sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/text_normalization/normalize_with_audio.py --text "\$.01" --n_tagged 2 --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22' - sh 'CUDA_VISIBLE_DEVICES="" pytest tests/nemo_text_processing/en/ -m "not pleasefixme" --cpu --tn_cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22' - } - } - stage('Test En Hybrid TN') { - steps { - sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/hybrid/wfst_lm_rescoring.py --data /home/TestData/nlp/text_norm/hybrid_tn/test.txt --regenerate_pkl --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22 | grep "all_correct: True" || exit 1' - } - } - } - } - - stage('L2: NeMo text processing') { - when { - anyOf { - branch 'main' - changeRequest target: 'main' - } - } - failFast true - parallel { - stage('L2: Eng TN') { - steps { - sh 'cd tools/text_processing_deployment && python pynini_export.py --output=/home/TestData/nlp/text_norm/output/ --grammars=tn_grammars --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22 --language=en && ls -R /home/TestData/nlp/text_norm/output/ && echo ".far files created "|| exit 1' - sh 'cd nemo_text_processing/text_normalization/ && python normalize.py --input_file=/home/TestData/nlp/text_norm/ci/test.txt --input_case="lower_cased" --language=en --output_file=/home/TestData/nlp/text_norm/output/test.pynini.txt --verbose' - sh 'cat /home/TestData/nlp/text_norm/output/test.pynini.txt' - sh 'cmp --silent /home/TestData/nlp/text_norm/output/test.pynini.txt /home/TestData/nlp/text_norm/ci/test_goal_py_05-25.txt || exit 1' - sh 'rm -rf /home/TestData/nlp/text_norm/output/*' - } - } - - stage('L2: Eng ITN export') { - steps { - sh 'cd tools/text_processing_deployment && python pynini_export.py --output=/home/TestData/nlp/text_denorm/output/ --grammars=itn_grammars --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22 --language=en && ls -R /home/TestData/nlp/text_denorm/output/ && echo ".far files created "|| exit 1' - sh 'cd nemo_text_processing/inverse_text_normalization/ && python inverse_normalize.py --input_file=/home/TestData/nlp/text_denorm/ci/test.txt --language=en --output_file=/home/TestData/nlp/text_denorm/output/test.pynini.txt --verbose' - sh 'cmp --silent /home/TestData/nlp/text_denorm/output/test.pynini.txt /home/TestData/nlp/text_denorm/ci/test_goal_py.txt || exit 1' - sh 'rm -rf /home/TestData/nlp/text_denorm/output/*' - } - } - stage('L2: TN with Audio (audio and raw text)') { - steps { - sh 'cd nemo_text_processing/text_normalization && \ - python normalize_with_audio.py --language=en --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22 --text "The total amounts to \\$4.76." \ - --audio_data /home/TestData/nlp/text_norm/audio_based/audio.wav | tail -n2 | head -n1 > /tmp/out_raw.txt 2>&1 && \ - cmp --silent /tmp/out_raw.txt /home/TestData/nlp/text_norm/audio_based/result.txt || exit 1' - } - } - stage('L2: TN with Audio (audio and text file)') { - steps { - sh 'cd nemo_text_processing/text_normalization && \ - python normalize_with_audio.py --language=en --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22 --text /home/TestData/nlp/text_norm/audio_based/text.txt \ - --audio_data /home/TestData/nlp/text_norm/audio_based/audio.wav | tail -n2 | head -n1 > /tmp/out_file.txt 2>&1 && \ - cmp --silent /tmp/out_file.txt /home/TestData/nlp/text_norm/audio_based/result.txt || exit 1' - } - } - stage('L2: TN with Audio (manifest)') { - steps { - sh 'cd nemo_text_processing/text_normalization && \ - python normalize_with_audio.py --language=en --audio_data /home/TestData/nlp/text_norm/audio_based/manifest.json --n_tagged=120 --cache_dir /home/TestData/nlp/text_norm/ci/grammars/11-16-22' - } - } - } - } - stage('L2: ASR dev run') { when { anyOf { @@ -1073,7 +987,7 @@ pipeline { parallel { stage('G2P Conformer training, evaluation and inference') { steps { - sh 'cd examples/text_processing/g2p && \ + sh 'cd examples/tts/g2p && \ TIME=`date +"%Y-%m-%d-%T"` && OUTPUT_DIR_CONFORMER=output_ctc_${TIME} && \ python g2p_train_and_evaluate.py \ train_manifest=/home/TestData/g2p/g2p.json \ @@ -1097,7 +1011,7 @@ pipeline { } stage('ByT5G2P training, evaluation and inference') { steps { - sh 'TRANSFORMERS_OFFLINE=0 && cd examples/text_processing/g2p && \ + sh 'TRANSFORMERS_OFFLINE=0 && cd examples/tts/g2p && \ TIME=`date +"%Y-%m-%d-%T"` && OUTPUT_DIR_T5=output_byt5_${TIME} && \ python g2p_train_and_evaluate.py \ train_manifest=/home/TestData/g2p/g2p.json \ @@ -1119,7 +1033,7 @@ pipeline { } stage('HeteronymClassificationModel training, evaluation and inference') { steps { - sh 'cd examples/text_processing/g2p && \ + sh 'cd examples/tts/g2p && \ TIME=`date +"%Y-%m-%d-%T"` && OUTPUT_DIR=output_${TIME} && \ python heteronym_classification_train_and_evaluate.py \ train_manifest=/home/TestData/g2p/manifest.json \ diff --git a/examples/tts/aligner_heteronym_disambiguation.py b/examples/tts/aligner_heteronym_disambiguation.py index fe5d89747a2b..ad6b1ac13eee 100644 --- a/examples/tts/aligner_heteronym_disambiguation.py +++ b/examples/tts/aligner_heteronym_disambiguation.py @@ -26,7 +26,7 @@ """ -G2P disambiguation using an Aligner model's input embedding distances. +G2P_paper disambiguation using an Aligner model's input embedding distances. Does not handle OOV and leaves them as graphemes. @@ -46,7 +46,7 @@ def get_args(): """Retrieve arguments for disambiguation. """ - parser = argparse.ArgumentParser("G2P disambiguation using Aligner input embedding distances.") + parser = argparse.ArgumentParser("G2P_paper disambiguation using Aligner input embedding distances.") # TODO(jocelynh): Make this required=False with default download from NGC once ckpt uploaded parser.add_argument('--model', required=True, type=str, help="Path to Aligner model checkpoint (.nemo file).") parser.add_argument( @@ -108,7 +108,7 @@ def disambiguate_candidates(aligner, text, spec, spec_len, confidence, device, h Note: This could be sped up if multiple words' candidates were batched, but this is conceptually easier. """ - # Grab original G2P result + # Grab original G2P_paper result aligner_g2p = aligner.tokenizer.g2p base_g2p = aligner_g2p(text) @@ -122,7 +122,7 @@ def disambiguate_candidates(aligner, text, spec, spec_len, confidence, device, h has_heteronym = False for word in words: - # Retrieve the length of the word in the default G2P conversion + # Retrieve the length of the word in the default G2P_paper conversion g2p_default_len = len(aligner_g2p(word)) # Check if word needs to be disambiguated @@ -134,7 +134,7 @@ def disambiguate_candidates(aligner, text, spec, spec_len, confidence, device, h candidate_prons_and_lengths = [] for pron in aligner_g2p.phoneme_dict[word]: - # Replace graphemes in the base G2P result with the current variant + # Replace graphemes in the base G2P_paper result with the current variant candidate = base_g2p[:word_start_idx] + pron + base_g2p[word_start_idx + g2p_default_len :] candidate_tokens = aligner.tokenizer.encode_from_g2p(candidate) @@ -247,7 +247,7 @@ def disambiguate_dataset( count = 0 for line in f_in: - # Retrieve entry and base G2P conversion for full text + # Retrieve entry and base G2P_paper conversion for full text entry = json.loads(line) # Set punct_post_process=True in order to preserve words with apostrophes text = aligner.normalizer.normalize(entry['text'], punct_post_process=True) diff --git a/examples/text_processing/g2p/README.md b/examples/tts/g2p/README.md similarity index 100% rename from examples/text_processing/g2p/README.md rename to examples/tts/g2p/README.md diff --git a/examples/text_processing/g2p/conf/g2p_conformer_ctc.yaml b/examples/tts/g2p/conf/g2p_conformer_ctc.yaml similarity index 95% rename from examples/text_processing/g2p/conf/g2p_conformer_ctc.yaml rename to examples/tts/g2p/conf/g2p_conformer_ctc.yaml index a20259b197c2..aa94405747fb 100644 --- a/examples/text_processing/g2p/conf/g2p_conformer_ctc.yaml +++ b/examples/tts/g2p/conf/g2p_conformer_ctc.yaml @@ -1,4 +1,4 @@ -name: G2P-Conformer-CTC +name: G2P_paper-Conformer-CTC # Dataset info train_manifest: ??? @@ -69,7 +69,7 @@ model: train_ds: manifest_filepath: ${train_manifest} dataset: - _target_: "nemo_text_processing.g2p.data.ctc_g2p.CTCG2PBPEDataset" + _target_: "nemo.tts.g2p.data.ctc_g2p.CTCG2PBPEDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: @@ -81,7 +81,7 @@ model: validation_ds: manifest_filepath: ${validation_manifest} dataset: - _target_: "nemo_text_processing.g2p.data.ctc_g2p.CTCG2PBPEDataset" + _target_: "nemo.tts.g2p.data.ctc_g2p.CTCG2PBPEDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: @@ -93,7 +93,7 @@ model: test_ds: manifest_filepath: ${test_manifest} dataset: - _target_: "nemo_text_processing.g2p.data.ctc_g2p.CTCG2PBPEDataset" + _target_: "nemo.collections.tts.g2p.data.ctc_g2p.CTCG2PBPEDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: diff --git a/examples/text_processing/g2p/conf/heteronym_classification.yaml b/examples/tts/g2p/conf/heteronym_classification.yaml similarity index 89% rename from examples/text_processing/g2p/conf/heteronym_classification.yaml rename to examples/tts/g2p/conf/heteronym_classification.yaml index ef6b65a69cf0..89c2899230de 100644 --- a/examples/text_processing/g2p/conf/heteronym_classification.yaml +++ b/examples/tts/g2p/conf/heteronym_classification.yaml @@ -35,7 +35,7 @@ model: train_ds: dataset: - _target_: "nemo_text_processing.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" + _target_: "nemo.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" manifest: ${train_manifest} grapheme_field: "text_graphemes" # name of the field in manifest for input grapheme text dataloader_params: @@ -46,7 +46,7 @@ model: validation_ds: dataset: - _target_: "nemo_text_processing.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" + _target_: "nemo.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" manifest: ${validation_manifest} grapheme_field: "text_graphemes" # name of the field in manifest for input grapheme text dataloader_params: @@ -57,7 +57,7 @@ model: test_ds: dataset: - _target_: "nemo_text_processing.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" + _target_: "nemo.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" manifest: ${test_manifest} grapheme_field: "text_graphemes" # name of the field in manifest for input grapheme text dataloader_params: diff --git a/examples/text_processing/g2p/conf/t5_g2p.yaml b/examples/tts/g2p/conf/t5_g2p.yaml similarity index 92% rename from examples/text_processing/g2p/conf/t5_g2p.yaml rename to examples/tts/g2p/conf/t5_g2p.yaml index 0ee46d1e61ac..24eca43ce12f 100644 --- a/examples/text_processing/g2p/conf/t5_g2p.yaml +++ b/examples/tts/g2p/conf/t5_g2p.yaml @@ -17,7 +17,7 @@ model: train_ds: manifest_filepath: ${train_manifest} dataset: - _target_: "nemo_text_processing.g2p.data.t5_g2p.T5G2PDataset" + _target_: "nemo.tts.g2p.data.t5_g2p.T5G2PDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: @@ -29,7 +29,7 @@ model: validation_ds: manifest_filepath: ${validation_manifest} dataset: - _target_: "nemo_text_processing.g2p.data.t5_g2p.T5G2PDataset" + _target_: "nemo.tts.g2p.data.t5_g2p.T5G2PDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: @@ -41,7 +41,7 @@ model: test_ds: manifest_filepath: ${test_manifest} dataset: - _target_: "nemo_text_processing.g2p.data.t5_g2p.T5G2PDataset" + _target_: "nemo.tts.g2p.data.t5_g2p.T5G2PDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: diff --git a/examples/text_processing/g2p/g2p_inference.py b/examples/tts/g2p/g2p_inference.py similarity index 98% rename from examples/text_processing/g2p/g2p_inference.py rename to examples/tts/g2p/g2p_inference.py index fe73ddbcbfde..ec32c29c4a95 100644 --- a/examples/text_processing/g2p/g2p_inference.py +++ b/examples/tts/g2p/g2p_inference.py @@ -18,7 +18,7 @@ import pytorch_lightning as pl import torch -from nemo_text_processing.g2p.models.g2p_model import G2PModel +from nemo.collections.tts.g2p.models import G2PModel from omegaconf import OmegaConf from utils import get_metrics diff --git a/examples/text_processing/g2p/g2p_train_and_evaluate.py b/examples/tts/g2p/g2p_train_and_evaluate.py similarity index 97% rename from examples/text_processing/g2p/g2p_train_and_evaluate.py rename to examples/tts/g2p/g2p_train_and_evaluate.py index 395b82c3f073..1770bd28f87d 100644 --- a/examples/text_processing/g2p/g2p_train_and_evaluate.py +++ b/examples/tts/g2p/g2p_train_and_evaluate.py @@ -16,7 +16,7 @@ import pytorch_lightning as pl import torch -from nemo_text_processing.g2p.models.g2p_model import G2PModel +from nemo.collections.tts.g2p.models import G2PModel from utils import get_model from nemo.collections.common.callbacks import LogEpochTimeCallback @@ -41,7 +41,7 @@ Example of the config file: NeMo/examples/text_processing/g2p/conf/t5_g2p.yaml -# Training Conformer-G2P Model and evaluation at the end of training: +# Training Conformer-G2P_paper Model and evaluation at the end of training: python examples/text_processing/g2p/g2p_train_and_evaluate.py \ # (Optional: --config-path= --config-name=) \ model.train_ds.manifest_filepath="" \ diff --git a/examples/text_processing/g2p/heteronym_classification_inference.py b/examples/tts/g2p/heteronym_classification_inference.py similarity index 99% rename from examples/text_processing/g2p/heteronym_classification_inference.py rename to examples/tts/g2p/heteronym_classification_inference.py index f587a12c3317..a4621422a8f4 100644 --- a/examples/text_processing/g2p/heteronym_classification_inference.py +++ b/examples/tts/g2p/heteronym_classification_inference.py @@ -20,7 +20,7 @@ import pytorch_lightning as pl import torch -from nemo_text_processing.g2p.models.heteronym_classification import HeteronymClassificationModel +from nemo.collections.tts.g2p.models.heteronym_classification import HeteronymClassificationModel from omegaconf import OmegaConf from nemo.core.config import hydra_runner diff --git a/examples/text_processing/g2p/heteronym_classification_train_and_evaluate.py b/examples/tts/g2p/heteronym_classification_train_and_evaluate.py similarity index 98% rename from examples/text_processing/g2p/heteronym_classification_train_and_evaluate.py rename to examples/tts/g2p/heteronym_classification_train_and_evaluate.py index e6a3cd17ade6..012e7a894958 100644 --- a/examples/text_processing/g2p/heteronym_classification_train_and_evaluate.py +++ b/examples/tts/g2p/heteronym_classification_train_and_evaluate.py @@ -16,7 +16,7 @@ import pytorch_lightning as pl import torch -from nemo_text_processing.g2p.models.heteronym_classification import HeteronymClassificationModel +from nemo.collections.tts.g2p.models.heteronym_classification import HeteronymClassificationModel from nemo.collections.common.callbacks import LogEpochTimeCallback from nemo.core.config import hydra_runner diff --git a/examples/text_processing/g2p/utils.py b/examples/tts/g2p/utils.py similarity index 96% rename from examples/text_processing/g2p/utils.py rename to examples/tts/g2p/utils.py index 1f022e49cab3..c91be04f2ae3 100644 --- a/examples/text_processing/g2p/utils.py +++ b/examples/tts/g2p/utils.py @@ -14,8 +14,8 @@ import json -from nemo_text_processing.g2p.models.ctc_g2p import CTCG2PModel -from nemo_text_processing.g2p.models.t5_g2p import T5G2PModel +from nemo.collections.tts.g2p.models import CTCG2PModel +from nemo.collections.tts.g2p.models.t5_g2p import T5G2PModel from nemo.collections.asr.metrics.wer import word_error_rate from nemo.utils import logging diff --git a/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py b/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py index be73e80a1b3c..539c9d85a829 100644 --- a/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py +++ b/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -from nemo_text_processing.g2p.modules import EnglishG2p +from nemo.collections.tts.g2p.modules import EnglishG2p from nemo.collections.common.tokenizers import TokenizerSpec from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import EnglishPhonemesTokenizer diff --git a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py index 1b478653d62a..ac9cb45a2724 100644 --- a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py +++ b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py @@ -19,7 +19,7 @@ from contextlib import contextmanager from typing import List, Optional -from nemo_text_processing.g2p.data.data_utils import ( +from nemo.collections.tts.g2p.data.data_utils import ( any_locale_text_preprocessing, chinese_text_preprocessing, english_text_preprocessing, @@ -447,11 +447,11 @@ def encode(self, text): def encode_from_g2p(self, g2p_text: List[str], raw_text: Optional[str] = None): """ - Encodes text that has already been run through G2P. - Called for encoding to tokens after text preprocessing and G2P. + Encodes text that has already been run through G2P_paper. + Called for encoding to tokens after text preprocessing and G2P_paper. Args: - g2p_text: G2P's output, could be a mixture of phonemes and graphemes, + g2p_text: G2P_paper's output, could be a mixture of phonemes and graphemes, e.g. "see OOV" -> ['S', 'IY1', ' ', 'O', 'O', 'V'] raw_text: original raw input """ @@ -534,11 +534,11 @@ def __init__( """ if not hasattr(g2p, "symbols"): logging.error( - f"Please make sure the G2P module passed into the IPATokenizer has a `symbols` attribute. " + f"Please make sure the G2P_paper module passed into the IPATokenizer has a `symbols` attribute. " f"This is required in order to build the tokenizer vocabulary.\n" f"Expected e.g. IPAG2P, found {type(g2p)}" ) - raise ValueError("G2P modules passed into the IPATokenizer must have `symbols` defined.") + raise ValueError("G2P_paper modules passed into the IPATokenizer must have `symbols` defined.") if locale is not None: validate_locale(locale) @@ -596,14 +596,14 @@ def encode(self, text: str) -> List[int]: def encode_from_g2p(self, g2p_text: List[str], raw_text: Optional[str] = None) -> List[int]: """ - Tokenize the `g2p_text` that has been already run through G2P. Each item in the `g2p_text` would be encoded as + Tokenize the `g2p_text` that has been already run through G2P_paper. Each item in the `g2p_text` would be encoded as one of the integer IDs predefined in `self._token2id`. Note that this function should be called after `self.text_preprocessing_func` and `self.g2p` functions Args: - g2p_text (List[str]): a sequence of tokens from G2P's output. It could be a sequence of phonemes, a sequence + g2p_text (List[str]): a sequence of tokens from G2P_paper's output. It could be a sequence of phonemes, a sequence of graphemes, or a mixture of both. For example, `['ˈ', 's', 'i', ' ', '#O', '#O', '#V']`, which is the - G2P's output of the text "see OOV", where '#' is prepended to each grapheme in order to distinguish + G2P_paper's output of the text "see OOV", where '#' is prepended to each grapheme in order to distinguish graphemes from phonemes if there are overlaps in between. The prefix '#' can be customized in `nemo_text_processing.g2p.modules.IPAG2P.grapheme_prefix`. raw_text (str): the original text after calling `self.text_preprocessing_func`. It is optional. It is only @@ -732,11 +732,11 @@ def encode(self, text): def encode_from_g2p(self, g2p_text: List[str], raw_text: Optional[str] = None): """ - Encodes text that has already been run through G2P. - Called for encoding to tokens after text preprocessing and G2P. + Encodes text that has already been run through G2P_paper. + Called for encoding to tokens after text preprocessing and G2P_paper. Args: - g2p_text: G2P's output, could be a mixture of Chinese phonemes and English letters. + g2p_text: G2P_paper's output, could be a mixture of Chinese phonemes and English letters. raw_text: original raw input """ ps, space, tokens = [], self.tokens[self.space], set(self.tokens) diff --git a/nemo_text_processing/text_normalization/es/__init__.py b/nemo/collections/tts/g2p/data/__init__.py similarity index 85% rename from nemo_text_processing/text_normalization/es/__init__.py rename to nemo/collections/tts/g2p/data/__init__.py index bd1fc7d433ef..5857cda3f17b 100644 --- a/nemo_text_processing/text_normalization/es/__init__.py +++ b/nemo/collections/tts/g2p/data/__init__.py @@ -12,4 +12,6 @@ # See the License for the specific language governing permissions and # limitations under the License. -LOCALIZATION = "eu" # Set to am for alternate formatting +from nemo.collections.tts.g2p.data.t5_g2p import T5G2PDataset + +__all__ = ["T5G2PDataset", "CTCG2PBPEDataset"] diff --git a/nemo_text_processing/g2p/data/ctc_g2p.py b/nemo/collections/tts/g2p/data/ctc_g2p.py similarity index 99% rename from nemo_text_processing/g2p/data/ctc_g2p.py rename to nemo/collections/tts/g2p/data/ctc_g2p.py index 792a92a10fa6..6b0052db6996 100644 --- a/nemo_text_processing/g2p/data/ctc_g2p.py +++ b/nemo/collections/tts/g2p/data/ctc_g2p.py @@ -37,7 +37,7 @@ def __init__( with_labels: bool = True, ): """ - Creates a dataset to train a CTC-based G2P models. + Creates a dataset to train a CTC-based G2P_paper models. Args: manifest_filepath: path to a .json manifest that contains "phoneme_field" and "grapheme_field" diff --git a/nemo_text_processing/g2p/data/data_utils.py b/nemo/collections/tts/g2p/data/data_utils.py similarity index 100% rename from nemo_text_processing/g2p/data/data_utils.py rename to nemo/collections/tts/g2p/data/data_utils.py diff --git a/nemo_text_processing/g2p/data/heteronym_classification_data.py b/nemo/collections/tts/g2p/data/heteronym_classification_data.py similarity index 100% rename from nemo_text_processing/g2p/data/heteronym_classification_data.py rename to nemo/collections/tts/g2p/data/heteronym_classification_data.py diff --git a/nemo_text_processing/g2p/data/t5_g2p.py b/nemo/collections/tts/g2p/data/t5_g2p.py similarity index 98% rename from nemo_text_processing/g2p/data/t5_g2p.py rename to nemo/collections/tts/g2p/data/t5_g2p.py index 0e4c5f2697b6..200d057fb0ab 100644 --- a/nemo_text_processing/g2p/data/t5_g2p.py +++ b/nemo/collections/tts/g2p/data/t5_g2p.py @@ -40,7 +40,7 @@ def __init__( with_labels: bool = True, ): """ - Dataset to train T5-based G2P generative model. + Dataset to train T5-based G2P_paper generative model. Args: manifest_filepath: path to a .json manifest that contains "phoneme_field" and "grapheme_field" diff --git a/nemo_text_processing/g2p/models/__init__.py b/nemo/collections/tts/g2p/models/__init__.py similarity index 84% rename from nemo_text_processing/g2p/models/__init__.py rename to nemo/collections/tts/g2p/models/__init__.py index 5f35864a4fd9..46c89fc49a6e 100644 --- a/nemo_text_processing/g2p/models/__init__.py +++ b/nemo/collections/tts/g2p/models/__init__.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -from nemo_text_processing.g2p.models.ctc_g2p import CTCG2PModel -from nemo_text_processing.g2p.models.t5_g2p import T5G2PModel +from nemo.collections.tts.g2p.models.t5_g2p import T5G2PModel +from nemo.collections.tts.g2p.models.ctc_g2p import CTCG2PModel __all__ = ["T5G2PModel", "CTCG2PModel"] diff --git a/nemo_text_processing/g2p/models/ctc_g2p.py b/nemo/collections/tts/g2p/models/ctc_g2p.py similarity index 99% rename from nemo_text_processing/g2p/models/ctc_g2p.py rename to nemo/collections/tts/g2p/models/ctc_g2p.py index a456942c1ad8..2a7ad7965c02 100644 --- a/nemo_text_processing/g2p/models/ctc_g2p.py +++ b/nemo/collections/tts/g2p/models/ctc_g2p.py @@ -19,8 +19,8 @@ import torch from hydra.utils import instantiate -from nemo_text_processing.g2p.data.ctc_g2p import CTCG2PBPEDataset -from nemo_text_processing.g2p.models.g2p_model import G2PModel +from nemo.collections.tts.g2p.data.ctc_g2p import CTCG2PBPEDataset +from nemo.collections.tts.g2p.models.g2p_model import G2PModel from omegaconf import DictConfig, ListConfig, OmegaConf, open_dict from pytorch_lightning import Trainer from torch import nn diff --git a/nemo_text_processing/g2p/models/g2p_model.py b/nemo/collections/tts/g2p/models/g2p_model.py similarity index 100% rename from nemo_text_processing/g2p/models/g2p_model.py rename to nemo/collections/tts/g2p/models/g2p_model.py diff --git a/nemo_text_processing/g2p/models/heteronym_classification.py b/nemo/collections/tts/g2p/models/heteronym_classification.py similarity index 99% rename from nemo_text_processing/g2p/models/heteronym_classification.py rename to nemo/collections/tts/g2p/models/heteronym_classification.py index 2cb19ac8bd6e..ddfac56ef93a 100644 --- a/nemo_text_processing/g2p/models/heteronym_classification.py +++ b/nemo/collections/tts/g2p/models/heteronym_classification.py @@ -19,8 +19,8 @@ import torch from hydra.utils import instantiate -from nemo_text_processing.g2p.data.data_utils import get_heteronym_spans, get_wordid_to_phonemes, read_wordids -from nemo_text_processing.g2p.data.heteronym_classification_data import HeteronymClassificationDataset +from nemo.collections.tts.g2p.data.data_utils import get_heteronym_spans, get_wordid_to_phonemes, read_wordids +from nemo.collections.tts.g2p.data.heteronym_classification_data import HeteronymClassificationDataset from omegaconf import DictConfig from pytorch_lightning import Trainer diff --git a/nemo_text_processing/g2p/models/t5_g2p.py b/nemo/collections/tts/g2p/models/t5_g2p.py similarity index 98% rename from nemo_text_processing/g2p/models/t5_g2p.py rename to nemo/collections/tts/g2p/models/t5_g2p.py index ee919ffa6643..bc1ba7e88ab9 100644 --- a/nemo_text_processing/g2p/models/t5_g2p.py +++ b/nemo/collections/tts/g2p/models/t5_g2p.py @@ -17,8 +17,8 @@ import torch from hydra.utils import instantiate -from nemo_text_processing.g2p.data.t5_g2p import T5G2PDataset -from nemo_text_processing.g2p.models.g2p_model import G2PModel +from nemo.collections.tts.g2p.data.t5_g2p import T5G2PDataset +from nemo.collections.tts.g2p.models.g2p_model import G2PModel from omegaconf import DictConfig, OmegaConf from pytorch_lightning import Trainer from transformers import AutoTokenizer, T5ForConditionalGeneration diff --git a/nemo_text_processing/g2p/modules.py b/nemo/collections/tts/g2p/modules.py similarity index 98% rename from nemo_text_processing/g2p/modules.py rename to nemo/collections/tts/g2p/modules.py index 91141ac729e1..6108098cfa74 100644 --- a/nemo_text_processing/g2p/modules.py +++ b/nemo/collections/tts/g2p/modules.py @@ -23,7 +23,7 @@ import nltk import torch -from nemo_text_processing.g2p.data.data_utils import ( +from nemo.collections.tts.g2p.data.data_utils import ( GRAPHEME_CASE_MIXED, GRAPHEME_CASE_UPPER, LATIN_CHARS_ALL, @@ -81,7 +81,7 @@ def setup_heteronym_model( """ try: - from nemo_text_processing.g2p.models.heteronym_classification import HeteronymClassificationModel + from nemo.collections.tts.g2p.models.heteronym_classification import HeteronymClassificationModel self.heteronym_model = heteronym_model self.heteronym_model.set_wordid_to_phonemes(wordid_to_phonemes_file) @@ -102,7 +102,7 @@ def __init__( phoneme_probability: Optional[float] = None, mapping_file: Optional[str] = None, ): - """English G2P module. This module converts words from grapheme to phoneme representation using phoneme_dict in CMU dict format. + """English G2P_paper module. This module converts words from grapheme to phoneme representation using phoneme_dict in CMU dict format. Optionally, it can ignore words which are heteronyms, ambiguous or marked as unchangeable by word_tokenize_func (see code for details). Ignored words are left unchanged or passed through apply_to_oov_word for handling. Args: @@ -310,7 +310,7 @@ def __init__( mapping_file: Optional[str] = None, ) -> None: """ - Generic IPA G2P module. This module converts words from graphemes to International Phonetic Alphabet + Generic IPA G2P_paper module. This module converts words from graphemes to International Phonetic Alphabet representations. Optionally, it can ignore heteronyms, ambiguous words, or words marked as unchangeable by `word_tokenize_func` (see code for details). Ignored words are left unchanged or passed through `apply_to_oov_word` for handling. @@ -683,7 +683,7 @@ def __init__( mapping_file: Optional[str] = None, word_segmenter: Optional[str] = None, ): - """Chinese G2P module. This module first converts Chinese characters into pinyin sequences using pypinyin, then pinyin sequences would + """Chinese G2P_paper module. This module first converts Chinese characters into pinyin sequences using pypinyin, then pinyin sequences would be further converted into phoneme sequences using pinyin_dict_nv_22.10.txt dict file. For Chinese and English bilingual sentences, the English words would be converted into letters. Args: diff --git a/nemo/collections/tts/models/aligner.py b/nemo/collections/tts/models/aligner.py index 66705d516e0d..ce1eeba309ef 100644 --- a/nemo/collections/tts/models/aligner.py +++ b/nemo/collections/tts/models/aligner.py @@ -82,11 +82,13 @@ def _setup_normalizer(self, cfg): ) try: + import nemo_text_processing + self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) except Exception as e: logging.error(e) raise ImportError( - "`pynini` not installed, please install via NeMo/nemo_text_processing/pynini_install.sh" + "`nemo_text_processing` not installed, see https://github.com/NVIDIA/NeMo-text-processing for more details" ) self.text_normalizer_call = self.normalizer.normalize @@ -96,6 +98,12 @@ def _setup_normalizer(self, cfg): def _setup_tokenizer(self, cfg): text_tokenizer_kwargs = {} if "g2p" in cfg.text_tokenizer: + # for backward compatibility + if self._is_model_being_restored() and cfg.text_tokenizer.g2p.get('_target_', None): + cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( + "nemo_text_processing.g2p", "nemo.collections.tts.g2p" + ) + g2p_kwargs = {} if "phoneme_dict" in cfg.text_tokenizer.g2p: diff --git a/nemo/collections/tts/models/fastpitch.py b/nemo/collections/tts/models/fastpitch.py index 67d55cb70e88..2e3593e76115 100644 --- a/nemo/collections/tts/models/fastpitch.py +++ b/nemo/collections/tts/models/fastpitch.py @@ -170,13 +170,14 @@ def _setup_normalizer(self, cfg): normalizer_kwargs["whitelist"] = self.register_artifact( 'text_normalizer.whitelist', cfg.text_normalizer.whitelist ) - try: + import nemo_text_processing + self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) except Exception as e: logging.error(e) raise ImportError( - "`pynini` not installed, please install via NeMo/nemo_text_processing/pynini_install.sh" + "`nemo_text_processing` not installed, see https://github.com/NVIDIA/NeMo-text-processing for more details" ) self.text_normalizer_call = self.normalizer.normalize @@ -187,6 +188,13 @@ def _setup_tokenizer(self, cfg): text_tokenizer_kwargs = {} if "g2p" in cfg.text_tokenizer: + + # for backward compatibility + if self._is_model_being_restored() and cfg.text_tokenizer.g2p.get('_target_', None): + cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( + "nemo_text_processing.g2p", "nemo.collections.tts.g2p" + ) + g2p_kwargs = {} if "phoneme_dict" in cfg.text_tokenizer.g2p: @@ -199,6 +207,7 @@ def _setup_tokenizer(self, cfg): 'text_tokenizer.g2p.heteronyms', cfg.text_tokenizer.g2p.heteronyms, ) + # for backward compatability text_tokenizer_kwargs["g2p"] = instantiate(cfg.text_tokenizer.g2p, **g2p_kwargs) # TODO @xueyang: rename the instance of tokenizer because vocab is misleading. diff --git a/nemo/collections/tts/models/mixer_tts.py b/nemo/collections/tts/models/mixer_tts.py index fffaf82d5a06..5f59e93554c5 100644 --- a/nemo/collections/tts/models/mixer_tts.py +++ b/nemo/collections/tts/models/mixer_tts.py @@ -132,11 +132,13 @@ def _setup_normalizer(self, cfg): ) try: + import nemo_text_processing + self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) except Exception as e: logging.error(e) raise ImportError( - "`pynini` not installed, please install via NeMo/nemo_text_processing/pynini_install.sh" + "`nemo_text_processing` not installed, see https://github.com/NVIDIA/NeMo-text-processing for more details" ) self.text_normalizer_call = self.normalizer.normalize @@ -146,6 +148,12 @@ def _setup_normalizer(self, cfg): def _setup_tokenizer(self, cfg): text_tokenizer_kwargs = {} if "g2p" in cfg.text_tokenizer: + # for backward compatibility + if self._is_model_being_restored() and cfg.text_tokenizer.g2p.get('_target_', None): + cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( + "nemo_text_processing.g2p", "nemo.collections.tts.g2p" + ) + g2p_kwargs = {} if "phoneme_dict" in cfg.text_tokenizer.g2p: diff --git a/nemo/collections/tts/models/radtts.py b/nemo/collections/tts/models/radtts.py index e303c924f4b2..ea08346c8b9f 100644 --- a/nemo/collections/tts/models/radtts.py +++ b/nemo/collections/tts/models/radtts.py @@ -326,6 +326,12 @@ def parser(self): def _setup_tokenizer(self, cfg): text_tokenizer_kwargs = {} if "g2p" in cfg.text_tokenizer: + # for backward compatibility + if self._is_model_being_restored() and cfg.text_tokenizer.g2p.get('_target_', None): + cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( + "nemo_text_processing.g2p", "nemo.collections.tts.g2p" + ) + g2p_kwargs = {} if "phoneme_dict" in cfg.text_tokenizer.g2p: @@ -363,7 +369,16 @@ def _setup_normalizer(self, cfg): 'text_normalizer.whitelist', cfg.text_normalizer.whitelist ) - self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) + try: + import nemo_text_processing + + self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) + self.text_normalizer_call = self.normalizer.normalize + except Exception as e: + logging.error(e) + raise ImportError( + "`nemo_text_processing` not installed, see https://github.com/NVIDIA/NeMo-text-processing for more details" + ) self.text_normalizer_call = self.normalizer.normalize if "text_normalizer_call_kwargs" in cfg: self.text_normalizer_call_kwargs = cfg.text_normalizer_call_kwargs diff --git a/nemo/collections/tts/models/tacotron2.py b/nemo/collections/tts/models/tacotron2.py index 311677ba7eb6..20fee29a7c31 100644 --- a/nemo/collections/tts/models/tacotron2.py +++ b/nemo/collections/tts/models/tacotron2.py @@ -307,11 +307,13 @@ def _setup_normalizer(self, cfg): ) try: + import nemo_text_processing + self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) except Exception as e: logging.error(e) raise ImportError( - "`pynini` not installed, please install via NeMo/nemo_text_processing/pynini_install.sh" + "`nemo_text_processing` not installed, see https://github.com/NVIDIA/NeMo-text-processing for more details" ) self.text_normalizer_call = self.normalizer.normalize @@ -321,6 +323,12 @@ def _setup_normalizer(self, cfg): def _setup_tokenizer(self, cfg): text_tokenizer_kwargs = {} if "g2p" in cfg.text_tokenizer and cfg.text_tokenizer.g2p is not None: + # for backward compatibility + if self._is_model_being_restored() and cfg.text_tokenizer.g2p.get('_target_', None): + cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( + "nemo_text_processing.g2p", "nemo.collections.tts.g2p" + ) + g2p_kwargs = {} if "phoneme_dict" in cfg.text_tokenizer.g2p: diff --git a/nemo/collections/tts/models/vits.py b/nemo/collections/tts/models/vits.py index a18c762803e2..832197195742 100644 --- a/nemo/collections/tts/models/vits.py +++ b/nemo/collections/tts/models/vits.py @@ -97,14 +97,28 @@ def _setup_normalizer(self, cfg): 'text_normalizer.whitelist', cfg.text_normalizer.whitelist ) - self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) - self.text_normalizer_call = self.normalizer.normalize + try: + import nemo_text_processing + + self.normalizer = instantiate(cfg.text_normalizer, **normalizer_kwargs) + self.text_normalizer_call = self.normalizer.normalize + except Exception as e: + logging.error(e) + raise ImportError( + "`nemo_text_processing` not installed, see https://github.com/NVIDIA/NeMo-text-processing for more details" + ) if "text_normalizer_call_kwargs" in cfg: self.text_normalizer_call_kwargs = cfg.text_normalizer_call_kwargs def _setup_tokenizer(self, cfg): text_tokenizer_kwargs = {} if "g2p" in cfg.text_tokenizer and cfg.text_tokenizer.g2p is not None: + # for backward compatibility + if self._is_model_being_restored() and cfg.text_tokenizer.g2p.get('_target_', None): + cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( + "nemo_text_processing.g2p", "nemo.collections.tts.g2p" + ) + g2p_kwargs = {} if "phoneme_dict" in cfg.text_tokenizer.g2p: diff --git a/nemo/collections/tts/torch/g2ps.py b/nemo/collections/tts/torch/g2ps.py index d66af6f82da7..e6347a0657a9 100644 --- a/nemo/collections/tts/torch/g2ps.py +++ b/nemo/collections/tts/torch/g2ps.py @@ -14,4 +14,3 @@ # TODO @xueyang: deprecate this file since no other places import modules from here anymore. However, # all checkpoints uploaded in ngc used this path. So it requires to update all ngc checkpoints g2p path as well. -from nemo_text_processing.g2p.modules import IPAG2P, BaseG2p, EnglishG2p diff --git a/nemo_text_processing/README.md b/nemo_text_processing/README.md deleted file mode 100644 index 181d6ddc8e3b..000000000000 --- a/nemo_text_processing/README.md +++ /dev/null @@ -1,8 +0,0 @@ -**nemo_text_processing** -========================== - -Introduction ------------- - -NeMo's `nemo_text_processing` is a Python package that is installed with the `nemo_toolkit`. -See [documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/wfst_text_normalization.html) for details. \ No newline at end of file diff --git a/nemo_text_processing/__init__.py b/nemo_text_processing/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/fst_alignment/README.md b/nemo_text_processing/fst_alignment/README.md deleted file mode 100644 index 99ae457db5c7..000000000000 --- a/nemo_text_processing/fst_alignment/README.md +++ /dev/null @@ -1,27 +0,0 @@ -This folder contains Python and C++ scripts that generate input output mappings from a specified FST graph and input string. -The required input FST graph needs to be provided as OpenFst FAR file. - -Requirements: -- Python: Pynini -- C++: Thrax, OpenFst - -Example Usage: - - -```python -python alignment.py --fst=fst.far --text="2615 Forest Av, 1 Aug 2016" --rule="tokenize_and_classify" --start=22 --end=26 - -Output: \ -inp string: |2615 Forest Av, 1 Aug 2016| \ -out string: |twenty six fifteen Forest Avenue , the first of august twenty sixteen| \ -inp indices: [22:26] -out indices: [55:69] \ -in: |2016| out: |twenty sixteen| -``` - - - -Disclaimer: - -The heuristic algorithm relies on monotonous alignment and can fail in certain situations, -e.g. when word pieces are reordered by the fst. \ No newline at end of file diff --git a/nemo_text_processing/fst_alignment/alignment.cpp b/nemo_text_processing/fst_alignment/alignment.cpp deleted file mode 100644 index aba2c3bab328..000000000000 --- a/nemo_text_processing/fst_alignment/alignment.cpp +++ /dev/null @@ -1,194 +0,0 @@ -//Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -//Licensed under the Apache License, Version 2.0 (the "License"); -//you may not use this file except in compliance with the License. -//You may obtain a copy of the License at -// http://www.apache.org/licenses/LICENSE-2.0 -//Unless required by applicable law or agreed to in writing, software -//distributed under the License is distributed on an "AS IS" BASIS, -//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -//See the License for the specific language governing permissions and -//limitations under the License. - - -#include -#include -#include -#include -#include - -using fst::StdArcLookAheadFst; -using thrax::GrmManager; -using fst::StdArc; -using fst::StdFst; -using namespace std; -typedef StdArcLookAheadFst LookaheadFst; - - -// This file takes 1. FST path 2. entire string 3. start position of substring 4. end (exclusive) position of substring -// and prints 1. mapped output string 2. start and end indices of mapped substring - -// Usage: - -// g++ -std=gnu++11 -I/include/ alignment.cpp -lfst -lthrax -ldl -L/lib -// ./a.out "tokenize_and_classify" "2615 Forest Av, 1 Aug 2016" 22 26 - -// Output: -// inp string: |2615 Forest Av, 1 Aug 2016| -// out string: |twenty six fifteen Forest Avenue , the first of august twenty sixteen| -// inp indices: [22:26] -// out indices: [55:69] -// in: |2016| out: |twenty sixteen| - -// Disclaimer: The heuristic algorithm relies on monotonous alignment and can fail in certain situations, -// e.g. when word pieces are reordered by the fst, e.g. - -// ./a.out "tokenize_and_classify" "$1" 0 1 -// inp string: |$1| -// out string: |one dollar| -// inp indices: [0:1] out indices: [0:3] -// in: |$| out: |one| - -// to prevent compiler error, not actually called -namespace fst { - #include - #include - #include - #include - - bool IsSTList(const std::string &source) { - std::ifstream strm(source, std::ios_base::in | std::ios_base::binary); - if (!strm) return false; - int32_t magic_number = 0; - ReadType(strm, &magic_number); - return magic_number == kSTListMagicNumber; - } - - bool IsSTTable(const std::string &source) { - std::ifstream strm(source); - if (!strm.good()) return false; - - int32_t magic_number = 0; - ReadType(strm, &magic_number); - return magic_number == kSTTableMagicNumber; - } -} - -char EPS = '\0'; -char WS= ' '; - - -int _get_aligned_index(const vector> &alignment, int index){ - int aligned_index = 0; - - int idx = 0; - while (idx < index){ - if (get<0>(alignment[aligned_index]) != EPS) {idx += 1;} - aligned_index += 1; - } - while (get<0>(alignment[aligned_index]) == EPS){ - aligned_index += 1; - } - return aligned_index; -} - -int _get_original_index(const vector> &alignment, int aligned_index){ - int og_index = 0; - int idx = 0; - while (idx < aligned_index) { - if (get<1>(alignment[idx]) != EPS) {og_index += 1;} - idx += 1; - } - return og_index; -} - - -tuple indexed_map_to_output(const vector> &alignment, int start, int end) { - - int aligned_start = _get_aligned_index(alignment, start); - int aligned_end = _get_aligned_index(alignment, end-1); - - string output_str = ""; - string input_str = ""; - for (const auto &i: alignment){ - output_str += get<1>(i); - input_str += get<0>(i); - } - - - while ((aligned_start -1 > 0) && (get<0>(alignment[aligned_start-1]) == EPS) && (isalpha(get<1>(alignment[aligned_start-1])) || (get<1>(alignment[aligned_start-1]) == EPS))) {aligned_start -= 1;} - - while (((aligned_end + 1) < alignment.size()) && (get<0>(alignment[aligned_end + 1]) == EPS) && (isalpha(get<1>(alignment[aligned_end + 1])) || (get<1>(alignment[aligned_end + 1]) == EPS))) {aligned_end += 1;} - - while (((aligned_end + 1) < alignment.size()) && (isalpha(get<1>(alignment[aligned_end + 1])) || get<1>(alignment[aligned_end + 1]) == EPS)) {aligned_end += 1;} - - int output_og_start_index = _get_original_index(alignment, aligned_start); - int output_og_end_index = _get_original_index(alignment, aligned_end+1); - - return make_tuple(output_og_start_index, output_og_end_index); - - -} - -int main(int argc, char * argv[]) { - if (argc != 6) - { - printf("\n Please provide 4 input arguments, 1st is the path to fst, 2nd the fst rule name, " - "3rd the full string in quotes, 4th is start index of word, 5th is exclusive end index of word."); - return 1; - } - unique_ptr grm_; - grm_.reset(new GrmManager); - string grm_file=argv[1]; - string grm_rule=argv[2]; - grm_->LoadArchive(grm_file); - LookaheadFst fst_(*(grm_->GetFst(grm_rule))); - - - string input = argv[3]; - typedef fst::StringCompiler Compiler; - typedef StdArc::StateId StateId; - typedef fst::StringPrinter Printer; - Compiler compiler; - thrax::GrmManager::MutableTransducer input_fst; - compiler(input, &input_fst); - - fst::ComposeFst output(input_fst,fst_); - thrax::GrmManager::MutableTransducer shortest_path; - fst::ShortestPath(output, &shortest_path); - - auto siter = shortest_path.Start(); - vector> alignment; - - while (shortest_path.Final(siter) == StdArc::Weight::Zero()) { - fst::ArcIterator aiter(shortest_path, siter); - if (aiter.Done()) { - cerr << "Unexpected format: Does not reach final state" << endl; - return 1; - } - const auto &arc = aiter.Value(); - alignment.push_back({(char)arc.ilabel, (char)arc.olabel }); - siter = arc.nextstate; - aiter.Next(); - if (!aiter.Done()) { - cerr << "Unexpected format: State has multiple outgoing arcs" << endl; - return 1; - } - } - - string output_str = ""; - int idx = 0; - for (const auto &i: alignment){ - if (get<1>(i) == EPS) continue; - output_str += get<1>(i); - } - - int start_index = atoi(argv[4]); - int end_index = atoi(argv[5]); - - tuple out_indices = indexed_map_to_output(alignment, start_index, end_index); - cout << "inp string: |" << argv[3] << "|" << endl; - cout << "out string: |" << output_str << "|" << endl; - cout << "inp indices: [" << start_index << ":" << end_index << "]" << endl; - cout << "out indices: [" << get<0>(out_indices) << ":" << get<1>(out_indices) << "]" << endl; - cout << "in: |" << input.substr(start_index, end_index - start_index) << "| out: |" << output_str.substr(get<0>(out_indices), (get<1>(out_indices)-get<0>(out_indices))) << "|" << endl; -} \ No newline at end of file diff --git a/nemo_text_processing/fst_alignment/alignment.py b/nemo_text_processing/fst_alignment/alignment.py deleted file mode 100644 index dbf2897d8fa0..000000000000 --- a/nemo_text_processing/fst_alignment/alignment.py +++ /dev/null @@ -1,254 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -from argparse import ArgumentParser -from typing import List - -import pynini -from pynini import Far - -from nemo.utils import logging - - -""" -This files takes 1. Far file containing a fst graph created by TN or ITN 2. entire string. -Optionally: 3. start position of substring 4. end (exclusive) position of substring -and returns input output mapping of all words in the string bounded by whitespace. -If start and end position specified returns -1. mapped output string 2. start and end indices of mapped substring - -Usage: - -python alignment.py --fst= --text=\"2615 Forest Av, 1 Aug 2016\" --rule=\"tokenize_and_classify\" --start=22 --end=26 - -Output: -inp string: |2615 Forest Av, 1 Aug 2016| -out string: |twenty six fifteen Forest Avenue , the first of august twenty sixteen| -inp indices: [22:26] -out indices: [55:69] -in: |2016| out: |twenty sixteen| - - -python alignment.py --fst= --text=\"2615 Forest Av, 1 Aug 2016\" --rule=\"tokenize_and_classify\" - -Output: -inp string: |2615 Forest Av, 1 Aug 2016| -out string: |twenty six fifteen Forest Avenue , the first of august twenty sixteen| -inp indices: [0:4] out indices: [0:18] -in: |2615| out: |twenty six fifteen| -inp indices: [5:11] out indices: [19:25] -in: |Forest| out: |Forest| -inp indices: [12:15] out indices: [26:34] -in: |Av,| out: |Avenue ,| -inp indices: [16:17] out indices: [39:44] -in: |1| out: |first| -inp indices: [18:21] out indices: [48:54] -in: |Aug| out: |august| -inp indices: [22:26] out indices: [55:69] -in: |2016| out: |twenty sixteen| - - -Disclaimer: The heuristic algorithm relies on monotonous alignment and can fail in certain situations, -e.g. when word pieces are reordered by the fst: - - -python alignment.py --fst= --text=\"$1\" --rule=\"tokenize_and_classify\" --start=0 --end=1 -inp string: |$1| -out string: |one dollar| -inp indices: [0:1] out indices: [0:3] -in: |$| out: |one| -""" - - -def parse_args(): - args = ArgumentParser("map substring to output with FST") - args.add_argument("--fst", help="FAR file containing FST", type=str, required=True) - args.add_argument( - "--rule", - help="rule name in FAR file containing FST", - type=str, - default='tokenize_and_classify', - required=False, - ) - args.add_argument( - "--text", - help="input string", - type=str, - default="2615 Forest Av, 90601 CA, Santa Clara. 10kg, 12/16/2018, $123.25. 1 Aug 2016.", - ) - args.add_argument("--start", help="start index of substring to be mapped", type=int, required=False) - args.add_argument("--end", help="end index of substring to be mapped", type=int, required=False) - return args.parse_args() - - -EPS = "" -WHITE_SPACE = "\u23B5" - - -def get_word_segments(text: str) -> List[List[int]]: - """ - Returns word segments from given text based on white space in form of list of index spans. - """ - spans = [] - cur_span = [0] - for idx, ch in enumerate(text): - if len(cur_span) == 0 and ch != " ": - cur_span.append(idx) - elif ch == " ": - cur_span.append(idx) - assert len(cur_span) == 2 - spans.append(cur_span) - cur_span = [] - elif idx == len(text) - 1: - idx += 1 - cur_span.append(idx) - assert len(cur_span) == 2 - spans.append(cur_span) - return spans - - -def create_symbol_table() -> pynini.SymbolTable: - """ - Creates and returns Pynini SymbolTable used to label alignment with ascii instead of integers - """ - table = pynini.SymbolTable() - for num in range(34, 200): # ascii alphanum + letter range - table.add_symbol(chr(num), num) - table.add_symbol(EPS, 0) - table.add_symbol(WHITE_SPACE, 32) - return table - - -def get_string_alignment(fst: pynini.Fst, input_text: str, symbol_table: pynini.SymbolTable): - """ - create alignment of input text based on shortest path in FST. Symbols used for alignment are from symbol_table - - Returns: - output: list of tuples, each mapping input character to output - """ - lattice = pynini.shortestpath(input_text @ fst) - paths = lattice.paths(input_token_type=symbol_table, output_token_type=symbol_table) - - ilabels = paths.ilabels() - olabels = paths.olabels() - logging.debug(paths.istring()) - logging.debug(paths.ostring()) - output = list(zip([symbol_table.find(x) for x in ilabels], [symbol_table.find(x) for x in olabels])) - paths.next() - assert paths.done() - output_str = "".join(map(remove, [x[1] for x in output])) - return output, output_str - - -def _get_aligned_index(alignment: List[tuple], index: int): - """ - Given index in contracted input string computes corresponding index in alignment (which has EPS) - """ - aligned_index = 0 - idx = 0 - - while idx < index: - if alignment[aligned_index][0] != EPS: - idx += 1 - aligned_index += 1 - while alignment[aligned_index][0] == EPS: - aligned_index += 1 - return aligned_index - - -def _get_original_index(alignment, aligned_index): - """ - Given index in aligned output, returns corresponding index in contracted output string - """ - - og_index = 0 - idx = 0 - while idx < aligned_index: - if alignment[idx][1] != EPS: - og_index += 1 - idx += 1 - return og_index - - -remove = lambda x: "" if x == EPS else " " if x == WHITE_SPACE else x - - -def indexed_map_to_output(alignment: List[tuple], start: int, end: int): - """ - Given input start and end index of contracted substring return corresponding output start and end index - - Args: - alignment: alignment generated by FST with shortestpath, is longer than original string since including eps transitions - start: inclusive start position in input string - end: exclusive end position in input string - - Returns: - output_og_start_index: inclusive start position in output string - output_og_end_index: exclusive end position in output string - """ - # get aligned start and end of input substring - aligned_start = _get_aligned_index(alignment, start) - aligned_end = _get_aligned_index(alignment, end - 1) # inclusive - - logging.debug(f"0: |{list(map(remove, [x[0] for x in alignment[aligned_start:aligned_end+1]]))}|") - - # extend aligned_start to left - while ( - aligned_start - 1 > 0 - and alignment[aligned_start - 1][0] == EPS - and (alignment[aligned_start - 1][1].isalpha() or alignment[aligned_start - 1][1] == EPS) - ): - aligned_start -= 1 - - while ( - aligned_end + 1 < len(alignment) - and alignment[aligned_end + 1][0] == EPS - and (alignment[aligned_end + 1][1].isalpha() or alignment[aligned_end + 1][1] == EPS) - ): - aligned_end += 1 - - while (aligned_end + 1) < len(alignment) and ( - alignment[aligned_end + 1][1].isalpha() or alignment[aligned_end + 1][1] == EPS - ): - aligned_end += 1 - - output_og_start_index = _get_original_index(alignment=alignment, aligned_index=aligned_start) - output_og_end_index = _get_original_index(alignment=alignment, aligned_index=aligned_end + 1) - return output_og_start_index, output_og_end_index - - -if __name__ == '__main__': - logging.setLevel(logging.INFO) - args = parse_args() - fst = Far(args.fst, mode='r') - try: - fst = fst[args.rule] - except: - raise ValueError(f"{args.rule} not found. Please specify valid --rule argument.") - input_text = args.text - - table = create_symbol_table() - alignment, output_text = get_string_alignment(fst=fst, input_text=input_text, symbol_table=table) - print(f"inp string: |{args.text}|") - print(f"out string: |{output_text}|") - - if args.start is None: - indices = get_word_segments(input_text) - else: - indices = [(args.start, args.end)] - for x in indices: - start, end = indexed_map_to_output(start=x[0], end=x[1], alignment=alignment) - print(f"inp indices: [{x[0]}:{x[1]}] out indices: [{start}:{end}]") - print(f"in: |{input_text[x[0]:x[1]]}| out: |{output_text[start:end]}|") diff --git a/nemo_text_processing/g2p/__init__.py b/nemo_text_processing/g2p/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/g2p/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/g2p/data/__init__.py b/nemo_text_processing/g2p/data/__init__.py deleted file mode 100644 index d218266f08a0..000000000000 --- a/nemo_text_processing/g2p/data/__init__.py +++ /dev/null @@ -1,18 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.g2p.data.ctc_g2p import CTCG2PBPEDataset -from nemo_text_processing.g2p.data.t5_g2p import T5G2PDataset - -__all__ = ["T5G2PDataset", "CTCG2PBPEDataset"] diff --git a/nemo_text_processing/hybrid/model_utils.py b/nemo_text_processing/hybrid/model_utils.py deleted file mode 100644 index 174ed6737704..000000000000 --- a/nemo_text_processing/hybrid/model_utils.py +++ /dev/null @@ -1,158 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import math -import re -from typing import List, Union - -import torch -from tqdm import tqdm - -from nemo.collections.common.parts import MLMScorer -from nemo.utils import logging - - -def init_models(model_name_list: str): - """ - returns dictionary of Masked Language Models by their HuggingFace name. - """ - model_names = model_name_list.split(",") - models = {} - for model_name in model_names: - device = 'cuda' if torch.cuda.is_available() else 'cpu' - models[model_name] = MLMScorer(model_name=model_name, device=device) - return models - - -def get_score(texts: Union[List[str], str], model: MLMScorer): - """Computes MLM score for list of text using model""" - try: - if isinstance(texts, str): - texts = [texts] - score = -1 * sum(model.score_sentences(texts)) / len(texts) - except Exception as e: - print(e) - print(f"Scoring error: {texts}") - score = math.inf - return score - - -def get_masked_score(text, model, do_lower=True): - """text is normalized prediction which contains <> around semiotic tokens. - If multiple tokens are present, multiple variants of the text are created where all but one ambiguous semiotic tokens are masked - to avoid unwanted reinforcement of neighboring semiotic tokens.""" - text = text.lower() if do_lower else text - spans = re.findall("<\s.+?\s>", text) - if len(spans) > 0: - text_with_mask = [] - - for match in re.finditer("<\s.+?\s>", text): - new_text = ( - text[: match.span()[0]] + match.group().replace("< ", "").replace(" >", "") + text[match.span()[1] :] - ) - new_text = re.sub("<\s.+?\s>", model.MASK_LABEL, new_text) - text_with_mask.append(new_text) - text = text_with_mask - - return get_score(text, model) - - -def _get_ambiguous_positions(sentences: List[str]): - """returns None or index list of ambigous semiotic tokens for list of sentences. - E.g. if sentences = ["< street > < three > A", "< saint > < three > A"], it returns [1, 0] since only - the first semiotic span / is ambiguous.""" - l_sets = [set([x]) for x in re.findall("<\s.+?\s>", sentences[0])] - for sentence in sentences[1:]: - spans = re.findall("<\s.+?\s>", sentence) - if len(spans) != len(l_sets): - return None - for i in range(len(spans)): - l_sets[i].add(spans[i]) - - ambiguous = [] - for span in l_sets: - ambiguous.append(len(span) > 1) - return ambiguous - - -def score_options(sentences: List[str], context_len, model, do_lower=True): - """return list of scores for each sentence in list where model is used for MLM Scoring.""" - scores = [] - if context_len is not None: - diffs = [find_diff(s, context_len) for s in sentences] - if len(set([len(d) for d in diffs])) == 1: - sentences = diffs - - ambiguous_positions = None - if sentences and isinstance(sentences[0], str): - ambiguous_positions = _get_ambiguous_positions(sentences) - - for sent in tqdm(sentences): - if isinstance(sent, list): # in case of set context len - option_scores = [get_masked_score(s, model, do_lower) for s in sent] - logging.debug(sent) - logging.debug(option_scores) - logging.debug("=" * 50) - if any(math.isnan(x) for x in option_scores): - av_score = math.inf - else: - av_score = round(sum(option_scores) / len(option_scores), 4) - scores.append(av_score) - elif isinstance(sent, str): # in case of full context - if ambiguous_positions: - matches = list(re.finditer("<\s.+?\s>", sent)) - for match, pos in zip(matches[::-1], ambiguous_positions[::-1]): - if not pos: - sent = ( - sent[: match.span()[0]] - + match.group().replace("< ", "").replace(" >", "") - + sent[match.span()[1] :] - ) - scores.append(round(get_masked_score(sent, model, do_lower=do_lower))) - else: - raise ValueError() - return scores - - -def find_diff(text, context_len=3): - """Finds parts of text normalized by WFST and returns them in list with a context of context_len""" - diffs = [] - pattern_start = "< " - pattern_end = " >" - - def __clean(s): - return s.replace(pattern_start, "").replace(pattern_end, "").replace(" ", " ") - - index_start = 0 - while pattern_start in text[index_start:]: - index_start = index_start + text[index_start:].index(pattern_start) - offset = index_start - if pattern_end in text[offset:]: - index_end = offset + text[offset:].index(pattern_end) + len(pattern_end) - center = __clean(text[index_start:index_end]) - - left_context = " ".join(__clean(text[:index_start]).split()[-context_len:]) - if len(left_context) > 0 and text[:index_start][-1].isspace(): - left_context = left_context + " " - right_context = " ".join(__clean(text[index_end:]).split()[:context_len]) - if len(right_context) > 0 and text[index_end][0].isspace(): - right_context = " " + right_context - diffs.append(left_context + center + right_context) - index_end += 1 - index_start = index_end + 1 - else: - break - if len(diffs) == 0: - diffs = [text] - return diffs diff --git a/nemo_text_processing/hybrid/utils.py b/nemo_text_processing/hybrid/utils.py deleted file mode 100644 index 84c892679354..000000000000 --- a/nemo_text_processing/hybrid/utils.py +++ /dev/null @@ -1,696 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import copy -import difflib -import json -import re -import string -from typing import List, Optional, Tuple, Union - -import pandas as pd -import pynini -from nemo_text_processing.inverse_text_normalization.en.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer -from pynini.lib.rewrite import top_rewrite -from tqdm import tqdm - -from nemo.utils import logging - -DELIMITER = '~~' - -cardinal_graph = CardinalFst().graph_no_exception -cardinal_graph = ( - pynini.closure(pynini.union("In ", "in ")) + cardinal_graph + pynini.closure(pynini.accep(" ") + cardinal_graph) -) - -inverse_normalizer = InverseNormalizer() - - -def load_data(input_fs: List[str]): - """ - loads data from list of abs file paths - Returns: - inputs: List[str] list of abs file paths - targets: List[List[str]] list of targets, can contain multiple options for each target - sentences: List[List[str]] list of sentence options - labels: List[List[int]] list of labels (1,0) - """ - inputs = [] - sentences = [] - cur_sentences = [] - labels = [] - cur_labels = [] - for input_f in input_fs: - if input_f.endswith(".json"): - with open(input_f, "r") as f: - for line in f: - line = json.loads(line) - try: - inputs.append(line['text'].strip()) - sentences.append([line['gt_normalized'].strip()]) - labels.append([1]) - except Exception as e: - print(e) - raise ValueError(f"Check format for line {line}") - else: - with open(input_f, "r") as f: - for line in f: - if line != "\n": - try: - sent, label = line.strip().split(DELIMITER) - except Exception as e: - if line.startswith("#"): - continue - print(e) - raise ValueError(f"Check format for line {line}") - if label == "RAW": - inputs.append(sent) - elif label == "1": - cur_sentences.append(sent) - cur_labels.append(1) - elif label == "0": - cur_sentences.append(sent) - cur_labels.append(0) - else: - sentences.append(cur_sentences) - cur_sentences = [] - labels.append(cur_labels) - cur_labels = [] - - if len(cur_sentences) > 0: - sentences.append(cur_sentences) - labels.append(cur_labels) - assert len(inputs) == len(sentences) - targets = [[x for i, x in enumerate(sents) if ls[i]] for (sents, ls) in zip(sentences, labels)] - return inputs, targets, sentences, labels - - -def remove_whitelist_boudaries(x): - # remove raw whitelist - x = re.sub(r"\|raw_start\|[^|]+\|raw_end\|", "", x) - # remove norm text boundaries - x = x.replace("|norm_start|", "").replace("|norm_end|", "") - return x - - -def _clean_pre_norm_libritts(inputs: List[str], targets: List[List[str]]): - """ - standardizes format of inputs and targets before being normalized, so more rules apply. - This is specific for libritts. - """ - for i in range(len(targets)): - for j in range(len(targets[i])): - targets[i][j] = clean_libri_tts(targets[i][j]) - - for i in range(len(inputs)): - for target in targets[i]: - diffs = get_diff(a=inputs[i].lower(), b=target.lower()) - for diff in diffs[::-1]: - in_diff = inputs[i][diff[0][0] : diff[0][1]].lower() - tg_diff = target[diff[1][0] : diff[1][1]].lower() - replacement = inputs[i][: diff[0][0]] + tg_diff + inputs[i][diff[0][1] :] - if (in_diff == "s" and tg_diff == "z") or (in_diff == "z" and tg_diff == "s"): - inputs[i] = replacement - elif (in_diff == "re" and tg_diff == "er") or (in_diff == "er" and tg_diff == "re"): - inputs[i] = replacement - elif (in_diff == "me" and tg_diff == "") or (in_diff == "" and tg_diff == "me"): - inputs[i] = replacement - elif (in_diff == "ue" and tg_diff == "") or (in_diff == "" and tg_diff == "ue"): - inputs[i] = replacement - return inputs, targets - - -def _clean_pre_norm_google(inputs: List[str], targets: List[List[str]]): - """ - standardizes format of inputs and targets before being normalized, so more rules apply. - This is specific for google dataset. - """ - for i in range(len(inputs)): - - inputs[i] = re.sub(r"\$\s([0-9]{1,})", r"$\1", inputs[i]) - inputs[i] = re.sub(r"\bmr ", r"Mr. ", inputs[i]) - inputs[i] = re.sub(r"\bdr ", r"Dr. ", inputs[i]) - inputs[i] = re.sub(r"\bdr$", r"Dr.", inputs[i]) - inputs[i] = re.sub(r"\bmrs ", r"Mrs. ", inputs[i]) - inputs[i] = re.sub(r"\bjr ", r"Jr. ", inputs[i]) - inputs[i] = re.sub(r"\bjr$", r"Jr.", inputs[i]) - inputs[i] = re.sub(r"\dsr ", r"Sr. ", inputs[i]) - inputs[i] = re.sub(r"\dsr$", r"Sr.", inputs[i]) - for target in targets[i]: - diffs = get_diff(a=inputs[i].lower(), b=target.lower()) - for diff in diffs[::-1]: - in_diff = inputs[i][diff[0][0] : diff[0][1]].lower() - tg_diff = target[diff[1][0] : diff[1][1]].lower() - replacement = inputs[i][: diff[0][0]] + tg_diff + inputs[i][diff[0][1] :] - if (in_diff == "s" and tg_diff == "z") or (in_diff == "z" and tg_diff == "s"): - inputs[i] = replacement - elif (in_diff == "re" and tg_diff == "er") or (in_diff == "er" and tg_diff == "re"): - inputs[i] = replacement - elif (in_diff == "me" and tg_diff == "") or (in_diff == "" and tg_diff == "me"): - inputs[i] = replacement - elif (in_diff == "" and tg_diff == "u") or (in_diff == "u" and tg_diff == ""): - inputs[i] = replacement - elif (in_diff == "ue" and tg_diff == "") or (in_diff == "" and tg_diff == "ue"): - inputs[i] = replacement - elif re.sub(r"\.", "", in_diff) == re.sub(r"( |\.)", "", tg_diff): - inputs[i] = replacement - - return inputs, targets - - -def clean_pre_norm(inputs: List[str], targets: List[List[str]], dataset: Optional[str] = None): - """ - standardizes format of inputs and targets before being normalized, so more rules apply. - """ - # deep copy - pre_inputs = copy.deepcopy(inputs) - pre_targets = copy.deepcopy(targets) - - # --- data specific pre cleaning --- - if dataset == "libritts": - pre_inputs, pre_targets = _clean_pre_norm_libritts(inputs=pre_inputs, targets=pre_targets) - elif dataset == "google": - pre_inputs, pre_targets = _clean_pre_norm_google(inputs=pre_inputs, targets=pre_targets) - else: - pass - - # --- general pre cleaning --- - for i in range(len(pre_inputs)): - pre_inputs[i] = re.sub("librivox.org", "librivox dot org", pre_inputs[i]) - pre_inputs[i] = re.sub( - rf"([0-9]?[0-9](\.|:)[0-9][0-9]\s?)(a|A|p|P)(\.?)\s(M|m)(\.?)", rf"\1\3\4\5\6", pre_inputs[i] - ) - # pre_inputs[i] =re.sub(rf"\b(S|s)t\.", rf"saint", pre_inputs[i]) - return pre_inputs, pre_targets - - -def _clean_post_norm_libritts(inputs: List[str], targets: List[List[str]], norm_texts): - return targets, norm_texts - - -def _clean_post_norm_google(inputs: List[str], targets: List[List[str]], norm_texts): - """ - standardizes format of inputs and targets, and predicted normalizations for easier evaluation. - This is specific for google dataset. - """ - for i in range(len(targets)): - for target in targets[i]: - for j, norm in enumerate(norm_texts[i][0]): - diffs = get_diff(a=norm.lower(), b=target.lower()) - for diff in diffs[::-1]: - norm_diff = norm[diff[0][0] : diff[0][1]].lower() - tg_diff = target[diff[1][0] : diff[1][1]].lower() - replacement = norm[: diff[0][0]] + tg_diff + norm[diff[0][1] :] - if norm_diff == re.sub(r" ", "", tg_diff): - norm_texts[i][0][j] = replacement - - return targets, norm_texts - - -def _clean_post_general(str) -> str: - """ - standardizes format of inputs and targets, and predicted normalizations for easier evaluation. - """ - str = re.sub(rf" oh ", " zero ", str) - str = re.sub(rf" oh$", " zero", str) - str = re.sub(rf"^oh ", "zero ", str) - # str = re.sub(rf" o ", " zero ", str) - str = re.sub(rf"\sO\b", "zero", str) - str = re.sub(rf" o$", " zero", str) - str = re.sub(rf"^o ", "zero ", str) - str = re.sub(rf"'o ", "'zero ", str) - str = str.replace("mountain", "mount") - return str - - -def _clean_targets(str) -> str: - """Clean ground truth options.""" - str = re.sub(rf" o ", " zero ", str) - return str - - -def adjust_pred(pred: str, gt: str, dataset: str, delim_present=True): - """Standardize prediction format to make evaluation easier""" - orig_pred = pred - orig_gt = gt - if delim_present and not re.search(rf"< (.*?) >", pred): - return pred - pred = re.sub(rf"< ", "", pred) - pred = re.sub(rf" >", "", pred) - pred = pred.lower().strip() - gt = gt.lower().strip() - can_be_adjusted = False - - if dataset in ["google", "libritts"] and pred != gt: - if is_date(pred=pred, gt=gt, cardinal_graph=cardinal_graph): - pred = gt - elif contains_month(pred, gt): - pred = re.sub(r",", "", pred) - gt = re.sub(r",", "", gt) - pred = re.sub(r" zero ", " o ", pred) - gt = re.sub(r" zero ", " o ", gt) - gt = re.sub(rf" +", " ", gt) - pred = re.sub(rf" +", " ", pred) - - if pred != gt: - gt_itn = inverse_normalizer.normalize(gt, verbose=False) - pred_itn = inverse_normalizer.normalize(pred, verbose=False) - if len(gt_itn) == len(pred_itn) and set(gt_itn) == set(pred_itn): - can_be_adjusted = True - pred = gt - elif " of " in gt: - gt = re.sub(r"(^the | of)", "", gt) - idx = gt.index(" ") - idx2 = (gt[idx + 1 :].index(" ") if " " in gt[idx + 1 :] else len(gt[idx + 1 :])) + idx + 1 - gt = gt[idx + 1 : idx2] + " " + gt[:idx] + gt[idx2:] - if dataset == "libritts" and pred != gt: - if "dollar" in gt: - gt = re.sub(rf"\band\b", "", gt) - pred = re.sub(rf"\band\b", "", pred) - if re.search(r"\bus dollar", pred) and not re.search(r"\bus dollar", gt): - pred = re.sub(rf"\bus dollar", "dollar", pred) - else: - gt = re.sub(rf"(\bthe\b|\.)", "", gt) - pred = re.sub(rf"\bone\b", "a", pred) - gt = re.sub(rf"\bmr\b", "mister", gt) - gt = re.sub(rf"\bmrs\b", "misses", gt) - gt = re.sub(rf"\bdr\b", "doctor", gt) - gt = re.sub(rf"\bco\b", "company", gt) - if gt != pd and dataset in ["google", "libritts"]: - if gt.replace("/", "").replace(" ", " ") == pred.replace("slash", "").replace(" ", " "): - pred = gt - elif gt in ["s", "z"] and pred in ["s", "z"]: - pred = gt - elif gt == "hash tag" and pred == "hash": - pred = "hash tag" - elif gt[:-2] == pred[:-2] and gt[-2:] in ["er", "re"] and pred[-2:] in ["er", "re"]: - pred = gt - # elif gt.replace("-", " ").replace(" ", " ") == pred.replace("minus", "").replace(" ", " "): - # pred = gt - elif gt.replace("to", "").replace("-", "") == pred.replace("to", "").replace("-", ""): - pred = gt - - gt = re.sub(rf" +", " ", gt) - pred = re.sub(rf"(\.)", "", pred) - pred = re.sub(rf" +", " ", pred) - if gt == pred: - can_be_adjusted = True - if can_be_adjusted: - if delim_present: - res = f" < {orig_gt} > " - else: - res = orig_gt - return res - else: - return orig_pred - - -def clean_post_norm( - inputs: List[str], - targets: List[List[str]], - norm_texts, - dataset: Optional[str] = None, - delim_present: Optional[bool] = True, -): - """ - Args: - inputs (List[str]): inputs - targets (List[List[str]]): targets - norm_texts (List[(List[str], List[float])]): List of normalization options, weights - dataset (Optional[str], optional): _description_. Defaults to None. - delim_present (Optional[str], optional): The flag indicates whether normalization output contain delimiters "<>". - Set to False for NN baseline. - """ - # deep copy - post_norm_texts = copy.deepcopy(norm_texts) - post_targets = copy.deepcopy(targets) - - # --- data specific pre cleaning --- - if dataset == "libritts": - post_targets, post_norm_texts = _clean_post_norm_libritts( - inputs=inputs, targets=post_targets, norm_texts=post_norm_texts - ) - elif dataset == "google": - post_targets, post_norm_texts = _clean_post_norm_google( - inputs=inputs, targets=post_targets, norm_texts=post_norm_texts - ) - - else: - pass - - # --- general pre cleaning --- - - for i in range(len(targets)): - for j, x in enumerate(post_targets[i]): - post_targets[i][j] = _clean_post_general(x) - for j, x in enumerate(post_norm_texts[i][0]): - if x.count("< ") != x.count(" >"): - x = x.replace("<", "< ").replace(">", " >").replace(" ", " ") - post_norm_texts[i][0][j] = _clean_post_general(x) - if dataset in ["libritts", "google"]: - for i, _targets in enumerate(post_targets): - for jj, option in enumerate(post_norm_texts[i][0]): - for _, _target in enumerate(_targets): - - if not delim_present: - # nn doesn't have punctuation marks that leads for diff_pred_gt mismatch - _target = remove_punctuation(_target, remove_spaces=False, do_lower=True) - option = remove_punctuation(option, remove_spaces=False, do_lower=True) - - diffs = diff_pred_gt(pred=option, gt=_target) - for diff in diffs[::-1]: - if diff[0][1] - diff[0][0] == 0 and diff[1][1] - diff[1][0] == 0: - continue - pred = option[diff[0][0] : diff[0][1]] - gt = _target[diff[1][0] : diff[1][1]] - logging.debug(f"pred: |{pred}|\tgt: |{gt}|") - new_pred = adjust_pred(pred=pred, gt=gt, dataset=dataset, delim_present=delim_present) - new_pred = ( - post_norm_texts[i][0][jj][: diff[0][0]] - + new_pred - + post_norm_texts[i][0][jj][diff[0][1] :] - ) - logging.debug(f"|{post_norm_texts[i][0][jj]}| -> |{new_pred}|") - post_norm_texts[i][0][jj] = new_pred - return post_targets, post_norm_texts - - -def clean_libri_tts(target: str): - """ - Replace abbreviations in LibriTTS dataset - """ - - # Normalized text in LibriTTS by Google which contains abbreviations from `libri_sometimes_converts_abbrs` sometimes wasn't converted. - libri_sometimes_converts_abbrs = {"St.": "saint", "Rev.": "reverend"} - - # Normalized text in LibriTTS by Google which contains abbreviations from `libri_wo_changes_abbrs` wasn't converted. - libri_wo_changes_abbrs = {"vs.": "versus"} - - google_abbr2expand = { - "mr": "mister", - "Mr": "Mister", - "mrs": "misses", - "Mrs": "Misses", - "dr": "doctor", - "Dr": "Doctor", - "drs": "doctors", - "Drs": "Doctors", - "lt": "lieutenant", - "Lt": "Lieutenant", - "sgt": "sergeant", - "Sgt": "Sergeant", - "st": "saint", - "St": "Saint", - "jr": "junior", - "Jr": "Junior", - "maj": "major", - "Maj": "Major", - "hon": "honorable", - "Hon": "Honorable", - "gov": "governor", - "Gov": "Governor", - "capt": "captain", - "Capt": "Captain", - "esq": "esquire", - "Esq": "Esquire", - "gen": "general", - "Gen": "General", - "ltd": "limited", - "Ltd": "Limited", - "rev": "reverend", - "Rev": "Reverend", - "col": "colonel", - "Col": "Colonel", - "and co": "and Company", - "and Co": "and Company", - "mt": "mount", - "Mt": "Mount", - "ft": "fort", - "Ft": "Fort", - "tenn": "tennessee", - "Tenn": "Tennessee", - "vs": "versus", - "Vs": "Versus", - "&": "and", - "§": "section", - "#": "hash", - "=": "equals", - } - - # let's normalize `libri_only_remove_dot_abbrs` abbreviations, because google doesn't do it well - for abbr in google_abbr2expand.keys(): - if abbr in target: - # replace abbr in google text via regex and using \b to match only whole words, keep original 1 and 2 groups - target = re.sub(rf'(^|\s|\W){abbr}($|\s)', rf"\1{google_abbr2expand[abbr]}\2", target) - - # let's normalize `libri_sometimes_converts_abbrs` abbreviations manually, google sometimes forgets to expand them - for abbr, t in libri_sometimes_converts_abbrs.items(): - target = target.replace(abbr, t) - - # let's normalize `libri_wo_changes_abbrs` abbreviations manually, google doesn't change, but they should be - for abbr, t in libri_wo_changes_abbrs.items(): - target = target.replace(abbr, t) - - return target - - -def remove_punctuation(text: str, remove_spaces=True, do_lower=True, lang="en", exclude=None): - """Removes punctuation (and optionally spaces) in text for better evaluation""" - all_punct_marks = string.punctuation - - if exclude is not None: - for p in exclude: - all_punct_marks = all_punct_marks.replace(p, "") - text = re.sub("[" + all_punct_marks + "]", " ", text) - - if lang == "en": - # remove things like \x94 and \x93 - text = re.sub(r"[^\x00-\x7f]", r" ", text) - - text = re.sub(r" +", " ", text) - if remove_spaces: - text = text.replace(" ", "").replace("\u00A0", "").strip() - - if do_lower: - text = text.lower() - return text.strip() - - -def get_alternative_label(pred: str, targets: List[str]) -> bool: - """Returns true if prediction matches target options""" - - def _relax_diff(text): - text = text.replace("us dollars", "dollars") - text = text.replace("etcetera", "").replace("etc", "") - text = text.replace("one half ounce", "").replace("half an ounce", "") - text = text.replace("television", "").replace("t v ", " ").replace("tv", "") - text = text.replace("hundred", "") - text = text.replace("forty two", "").replace("four two", "") - text = text.replace("re", "").replace("er", "") - text = text.replace("ou", "").replace("o", "") - text = text.replace(" ", " ").strip() - return text - - acceptable = False - pred = remove_punctuation(pred, remove_spaces=False, do_lower=True) - for target in targets: - target = _clean_post_general(remove_punctuation(target, remove_spaces=False, do_lower=True)) - target = _clean_targets(remove_punctuation(target, remove_spaces=False, do_lower=True)) - if _relax_diff(target) == _relax_diff(pred): - acceptable = True - break - return acceptable - - -def get_labels(targets: List[str], norm_texts_weights: List[Tuple[str, str]], lang="en",) -> List[List[str]]: - """ - Assign labels to generated normalization options (1 - for ground truth, 0 - other options) - Args: - targets: ground truth normalization sentences - norm_texts_weights: List of tuples: (normalization options, weights of normalization options) - returns: - List of labels [1, 0] for every normalization option - """ - print("Assign labels to generated normalization options...") - labels = [] - for i, cur_targets in tqdm(enumerate(targets)): - curr_labels = [] - cur_targets = [_clean_targets(t) for t in cur_targets] - for norm_option in norm_texts_weights[i][0]: - norm_option = _clean_targets(norm_option) - norm_option = remove_whitelist_boudaries(norm_option) - - if is_correct(pred=norm_option, targets=cur_targets, lang=lang): - curr_labels.append(1) - elif get_alternative_label(pred=norm_option, targets=cur_targets): - curr_labels.append(1) - else: - curr_labels.append(0) - labels.append(curr_labels) - return labels - - -def contains_month(pred, gt): - """Check is the pred/gt contain month in the span""" - months = [ - "january", - "february", - "march", - "april", - "may", - "june", - "july", - "august", - "september", - "october", - "november", - "december", - ] - - for mon in months: - if mon in gt and mon in pred: - return True - return False - - -def is_date(pred, gt, cardinal_graph): - """Returns True is pred and gt are date format modifications and are equal.""" - is_date_case = False - - # for cases "1890" -> "one thousand eight hundred ninety" vs "eighteen ninety" - if "thousand" in pred and "hundred" in pred and pred.strip().split()[-2:] == gt.strip().split()[-2:]: - is_date_case = True - elif "thousand" in gt and "hundred" in gt and gt.strip().split()[-2:] == pred.strip().split()[-2:]: - is_date_case = True - else: - try: - if top_rewrite(gt.replace(" oh ", " zero ").replace(" o ", " zero "), cardinal_graph).replace( - " ", "" - ) == top_rewrite(pred.replace(" oh ", " zero ").replace(" o ", " zero "), cardinal_graph).replace(" ", ""): - is_date_case = True - except: - pass - - return is_date_case - - -def is_correct(pred: str, targets: Union[List[str], str], lang: str) -> bool: - """ - returns True if prediction matches targets for language lang. - """ - if isinstance(targets, List): - targets = [remove_punctuation(x, remove_spaces=True, do_lower=True, lang=lang) for x in targets] - else: - targets = [remove_punctuation(targets, remove_spaces=True, do_lower=True, lang=lang)] - - pred = remove_punctuation(pred, remove_spaces=True, do_lower=True) - return pred in targets - - -def print_df(df): - """ - prints data frame - """ - with pd.option_context( - "display.max_rows", None, "display.max_columns", None, "display.width", 1000, "display.max_colwidth", 400, - ): - print(df) - - -def get_diff(a: str, b: str): - """returns list of different substrings between and b - - Returns: - list of Tuple(pred start and end, gt start and end) subsections - """ - s = difflib.SequenceMatcher(None, a, b, autojunk=False) - - # s contains a list of triples. Each triple is of the form (i, j, n), and means that a[i:i+n] == b[j:j+n]. - # The triples are monotonically increasing in i and in j. - s = s.get_matching_blocks() - s = [x for x in s if x[2] != 1] - # get not matching blocks - matches = [[0, 0, 0]] + s - unmatches_l = [] - unmatches_r = [] - for l, r in zip(matches[:-1], matches[1:]): - unmatches_l.append([l[0] + l[2], r[0]]) - unmatches_r.append([l[1] + l[2], r[1]]) - - result = list(zip(unmatches_l, unmatches_r)) - - for item in list(zip(unmatches_l, unmatches_r)): - logging.debug(f"a: {a[item[0][0]:item[0][1]]}") - logging.debug(f"b: {b[item[1][0]:item[1][1]]}") - logging.debug("=" * 20) - return result[1:] - - -def diff_pred_gt(pred: str, gt: str): - """returns list of different substrings between prediction and gt - relies on that prediction uses '< ' ' >' - - Args: - pred (str): prediction - gt (str): ground truth - - Returns: - list of Tuple(pred start and end, gt start and end) subsections - - e.g. pred="< Edward third >., king Our own . loss had been < two thousand two hundred >" - gt ="Edward III., king Our own loss had been twenty two hundred" - --> [([0, 16], [0, 10]), ([32, 34], [26, 26]), ([48, 76], [40, 58])] - """ - s = difflib.SequenceMatcher(None, pred, gt, autojunk=False) - - # s contains a list of triples. Each triple is of the form (i, j, n), and means that a[i:i+n] == b[j:j+n]. - # The triples are monotonically increasing in i and in j. - s = s.get_matching_blocks() - - left = list(re.finditer("< ", pred)) - left = [x.start() for x in left] - right = list(re.finditer(" >", pred)) - right = [x.end() for x in right] - left = [-1] + left + [len(pred)] - right = [0] + right + [len(pred)] - - matches = [] - assert len(left) == len(right) - idx = 1 - for i, seq in enumerate(s): - if i == len(s) - 1 and seq[2] == 0: - break - while idx < len(left) - 1 and (seq[0] >= right[idx]): - idx += 1 - - if right[idx - 1] <= seq[0] < left[idx] and (seq[0] + seq[2]) <= left[idx]: - matches.append(seq) - - # get not matching blocks - matches = [[0, 0, 0]] + matches + [[len(pred), len(gt), 0]] - unmatches_l = [] - unmatches_r = [] - for l, r in zip(matches[:-1], matches[1:]): - unmatches_l.append([l[0] + l[2], r[0]]) - unmatches_r.append([l[1] + l[2], r[1]]) - - result = list(zip(unmatches_l, unmatches_r)) - - for item in list(zip(unmatches_l, unmatches_r)): - logging.debug(f"pred: {pred[item[0][0]:item[0][1]]}") - logging.debug(f"gt : {gt[item[1][0]:item[1][1]]}") - logging.debug("=" * 20) - return result diff --git a/nemo_text_processing/hybrid/wfst_lm_rescoring.py b/nemo_text_processing/hybrid/wfst_lm_rescoring.py deleted file mode 100644 index 72b3b59bb62a..000000000000 --- a/nemo_text_processing/hybrid/wfst_lm_rescoring.py +++ /dev/null @@ -1,335 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import argparse -import os -import pickle -import re -import shutil -from typing import Dict, List - -import model_utils -import pandas as pd -import utils -from joblib import Parallel, delayed -from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio -from tqdm import tqdm - -from nemo.utils import logging - -parser = argparse.ArgumentParser(description="Re-scoring") -parser.add_argument("--lang", default="en", type=str, choices=["en"]) -parser.add_argument("--n_tagged", default=100, type=int, help="Number WFST options") -parser.add_argument("--context_len", default=-1, type=int, help="Context length, -1 to use full context") -parser.add_argument("--threshold", default=0.2, type=float, help="delta threshold value") -parser.add_argument("--overwrite_cache", action="store_true", help="overwrite cache") -parser.add_argument("--model_name", type=str, default="bert-base-uncased") -parser.add_argument("--cache_dir", default='cache', type=str, help="use cache dir") -parser.add_argument( - "--data", - default="text_normalization_dataset_files/EngConf.txt", - help="For En only. Path to a file for evaluation.", -) -parser.add_argument("--n_jobs", default=-2, type=int, help="The maximum number of concurrently running jobs") -parser.add_argument( - "--models", default="mlm_bert-base-uncased", type=str, help="Comma separated string of model names" -) -parser.add_argument( - "--regenerate_pkl", - action="store_true", - help="Set to True to re-create pickle file with WFST normalization options", -) -parser.add_argument("--batch_size", default=200, type=int, help="Batch size for parallel processing") - - -def rank(sentences: List[str], labels: List[int], models: Dict[str, 'Model'], context_len=None, do_lower=True): - """ - computes scores for each sentences using all provided models and returns summary in data frame - """ - df = pd.DataFrame({"sent": sentences, "labels": labels}) - for model_name, model in models.items(): - scores = model_utils.score_options( - sentences=sentences, context_len=context_len, model=model, do_lower=do_lower - ) - df[model_name] = scores - return df - - -def threshold_weights(norm_texts_weights, delta: float = 0.2): - """ - norm_texts_weights: list of [ List[normalized options of input], list[weights] ] - delta: delta to add to minimum weight in options to compose upper limit for threshhold - - returns: - filter list of same format as input - """ - # threshold value is factor applied to lowest/first weight of all normalization options for every input - res = [] - for i, options_weights in enumerate(norm_texts_weights): - thresh = options_weights[1][0] + delta # minimum weight plus delta - item = [x for x in zip(*options_weights)] - # filters out all options for every input that is larger than threshold - res.append(list(filter(lambda x: x[1] < thresh, item))) - - return [list(map(list, zip(*item))) for item in res] - - -def _get_unchanged_count(text): - """ - returns number of unchanged words in text - """ - exclude = '#$%&<>' - - # remove normalized whitelist - text = re.sub(r"\|norm_start\|[^|]+\|norm_end\|", "", text) - # remove raw text boundaries - text = text.replace("|raw_start|", "").replace("|raw_end|", "") - - start_pattern = "<" - end_pattern = ">" - - text = utils.remove_punctuation(text, remove_spaces=False, do_lower=False, exclude=exclude) - text_clean = "" - for ch in text: - if ch.isalpha() or ch.isspace() or ch in [start_pattern, end_pattern]: - text_clean += ch - else: - text_clean += " " + ch + " " - - text = text_clean - unchanged_count = 0 - skip = False - - for word in text.split(): - if start_pattern == word: - skip = True - elif end_pattern == word: - skip = False - elif not skip: - unchanged_count += 1 - return unchanged_count - - -def _get_replacement_count(text): - """ - returns number of token replacements - """ - start_pattern = "<" - end_pattern = ">" - return min(text.count(start_pattern), text.count(end_pattern)) - - -def threshold(norm_texts_weights, unchanged=True, replacement=True): - """ - Reduces the number of WFST options based for LM rescoring. - - Args: - :param norm_texts_weights: WFST options with associated weight - :param unchanged: set to True to filter out examples based on number of words left unchanged - (punct is not taken into account) - :param replacement: set to True to filter out examples based on number of replacements made - (Given A and B are WFST options, if the number of unchanged for A and B are the same, - the option with a smaller number of replacements is preferable (i.e., larger span)). - - :return: WFST options with associated weight (reduced) - """ - - def __apply(norm_texts_weights, f, use_min=True): - inputs_filtered = [] - for example in norm_texts_weights: - texts = example[0] - counts = [f(t) for t in texts] - [logging.debug(f"{c} -- {t}") for t, c in zip(texts, counts)] - target_count = min(counts) if use_min else max(counts) - filtered_texts = [] - filtered_weights = [] - for i, c in enumerate(counts): - if c == target_count: - filtered_texts.append(example[0][i]) - filtered_weights.append(example[1][i]) - inputs_filtered.append([filtered_texts, filtered_weights]) - return inputs_filtered - - logging.debug("BASIC THRESHOLDING INPUT:") - [logging.debug(x) for x in norm_texts_weights[0][0]] - if unchanged: - norm_texts_weights = __apply(norm_texts_weights, _get_unchanged_count) - logging.debug("AFTER UNCHANGED FILTER:") - [logging.debug(x) for x in norm_texts_weights[0][0]] - - if replacement: - norm_texts_weights = __apply(norm_texts_weights, _get_replacement_count) - logging.debug("AFTER REPLACEMENT FILTER:") - [logging.debug(x) for x in norm_texts_weights[0][0]] - - return norm_texts_weights - - -def main(): - args = parser.parse_args() - - logging.setLevel(logging.INFO) - lang = args.lang - input_f = args.data - - if args.data == "text_normalization_dataset_files/LibriTTS.json": - args.dataset = "libritts" - elif args.data == "text_normalization_dataset_files/GoogleTN.json": - args.dataset = "google" - else: - args.dataset = None - if not os.path.exists(args.data): - raise FileNotFoundError(f"{args.data} file not found") - - print("Create Masked Language Model...") - models = model_utils.init_models(model_name_list=args.model_name) - input_fs = input_f.split(",") - print("LOAD DATA...") - inputs, targets, _, _ = utils.load_data(input_fs) - pre_inputs, pre_targets = utils.clean_pre_norm(dataset=args.dataset, inputs=inputs, targets=targets) - - print("INIT WFST...") - normalizer = NormalizerWithAudio( - input_case="cased", lang=lang, cache_dir=args.cache_dir, lm=True, overwrite_cache=args.overwrite_cache - ) - - print("APPLYING NORMALIZATION RULES...") - p_file = ( - f"norm_texts_weights_{args.n_tagged}_{os.path.basename(args.data)}_{args.context_len}_{args.threshold}.pkl" - ) - - if not os.path.exists(p_file) or args.regenerate_pkl: - print(f"Creating WFST and saving to {p_file}") - - def __process_batch(batch_idx, batch, dir_name): - normalized = [] - for x in tqdm(batch): - ns, ws = normalizer.normalize(x, n_tagged=args.n_tagged, punct_post_process=False) - ns = [re.sub(r"<(.+?)>", r"< \1 >", x) for x in ns] - normalized.append((ns, ws)) - with open(f"{dir_name}/{batch_idx}.p", "wb") as handle: - pickle.dump(normalized, handle, protocol=pickle.HIGHEST_PROTOCOL) - - print(f"Batch -- {batch_idx} -- is complete") - return batch_idx - - # to save intermediate results to a file - batch = min(len(pre_inputs), args.batch_size) - - tmp_dir = f"/tmp/{os.path.basename(args.data)}" - if os.path.exists(tmp_dir): - shutil.rmtree(tmp_dir) - os.makedirs(tmp_dir, exist_ok=True) - - batch_ids = Parallel(n_jobs=args.n_jobs)( - delayed(__process_batch)(idx, pre_inputs[i : i + batch], tmp_dir) - for idx, i in enumerate(range(0, len(pre_inputs), batch)) - ) - - # aggregate all intermediate results - norm_texts_weights = [] - for batch_id in batch_ids: - batch_f = f"{tmp_dir}/{batch_id}.p" - norm_texts_weights.extend(pickle.load(open(batch_f, "rb"))) - - with open(p_file, "wb") as handle: - pickle.dump(norm_texts_weights, handle, protocol=pickle.HIGHEST_PROTOCOL) - else: - print(f"Loading WFST from {p_file}") - norm_texts_weights = pickle.load(open(p_file, "rb")) - - print("THRESHOLDING...") - # apply weights threshold to reduce number of options - - if args.threshold > 0: - norm_texts_weights = threshold_weights(norm_texts_weights, delta=args.threshold) - logging.debug("AFTER WEIGHTS THRESHOLDING:") - [logging.debug(x) for x in norm_texts_weights[0][0]] - - # reduce number of options by selecting options with the smallest number of unchanged words - norm_texts_weights = threshold(norm_texts_weights) - - print("POST PROCESSING...") - post_targets, post_norm_texts_weights = utils.clean_post_norm( - dataset=args.dataset, inputs=pre_inputs, targets=pre_targets, norm_texts=norm_texts_weights - ) - - print("GETTING LABELS...") - labels = utils.get_labels(targets=post_targets, norm_texts_weights=post_norm_texts_weights) - - examples_with_no_labels_among_wfst = [i for i, x in enumerate(labels) if 1 not in x] - - print("GATHERING STATS...") - model_stats = {m: 0 for m in models} - gt_in_options = 0 - for i, example in tqdm(enumerate(zip(post_norm_texts_weights, labels))): - data, curr_labels = example - assert len(data[0]) == len(curr_labels) - df = rank( - sentences=data[0], - labels=curr_labels, - models=models, - context_len=args.context_len if args.context_len is not None and args.context_len >= 0 else None, - do_lower=True, - ) - df['sent'] = df['sent'].apply(lambda x: utils.remove_whitelist_boudaries(x)) - df["weights"] = data[1] - - do_print = False - - for model in models: - # one hot vector for predictions, 1 for the best score option - df[f"{model}_pred"] = (df[model] == min(df[model])).astype(int) - # add constrain when multiple correct labels per example - pred_is_correct = min(sum((df["labels"] == df[f"{model}_pred"]) & df["labels"] == 1), 1) - - if not pred_is_correct or logging.getEffectiveLevel() <= logging.DEBUG: - do_print = True - - if do_print: - print(f"{model} prediction is correct: {pred_is_correct == 1}") - model_stats[model] += pred_is_correct - gt_in_options += 1 in curr_labels - - if do_print: - print(f"INPUT: {pre_inputs[i]}") - print(f"GT : {post_targets[i]}\n") - utils.print_df(df) - print("-" * 80 + "\n") - - if gt_in_options != len(post_norm_texts_weights): - print("WFST options for some examples don't contain the ground truth:") - for i in examples_with_no_labels_among_wfst: - print(f"INPUT: {pre_inputs[i]}") - print(f"GT : {post_targets[i]}\n") - print(f"WFST:") - for x in post_norm_texts_weights[i]: - print(x) - print("=" * 40) - - all_correct = True - for model, correct in model_stats.items(): - print( - f"{model} -- correct: {correct}/{len(post_norm_texts_weights)} or ({round(correct/len(post_norm_texts_weights) * 100, 2)}%)" - ) - all_correct = all_correct and (correct == len(post_norm_texts_weights)) - - print(f"examples_with_no_labels_among_wfst: {len(examples_with_no_labels_among_wfst)}") - return all_correct - - -if __name__ == "__main__": - all_correct = main() - print(f"all_correct: {all_correct}") diff --git a/nemo_text_processing/install_pynini.sh b/nemo_text_processing/install_pynini.sh deleted file mode 100644 index 301df87c223d..000000000000 --- a/nemo_text_processing/install_pynini.sh +++ /dev/null @@ -1,2 +0,0 @@ -#!/bin/bash -pip install pynini==2.1.5 diff --git a/nemo_text_processing/inverse_text_normalization/README.md b/nemo_text_processing/inverse_text_normalization/README.md deleted file mode 100644 index 8bf5a0fcf929..000000000000 --- a/nemo_text_processing/inverse_text_normalization/README.md +++ /dev/null @@ -1,11 +0,0 @@ -# Inverse Text Normalization - -Inverse Text Normalization is part of NeMo's `nemo_text_processing` - a Python package that is installed with the `nemo_toolkit`. -It converts text from spoken form into written form, e.g. "one hundred twenty three" -> "123". - -See [NeMo documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/wfst_text_normalization.html) for details. - -Tutorial with overview of the package capabilities: [Text_(Inverse)_Normalization.ipynb](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/Text_(Inverse)_Normalization.ipynb) - -Tutorial on how to customize the underlying gramamrs: [WFST_Tutorial.ipynb](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/WFST_Tutorial.ipynb) - diff --git a/nemo_text_processing/inverse_text_normalization/__init__.py b/nemo_text_processing/inverse_text_normalization/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/de/__init__.py b/nemo_text_processing/inverse_text_normalization/de/__init__.py deleted file mode 100644 index a1ed7385c85c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/__init__.py b/nemo_text_processing/inverse_text_normalization/de/taggers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/cardinal.py b/nemo_text_processing/inverse_text_normalization/de/taggers/cardinal.py deleted file mode 100644 index e0b066173814..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/cardinal.py +++ /dev/null @@ -1,67 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, GraphFst -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals. Numbers below ten are not converted. - Allows both compound numeral strings or separated by whitespace. - "und" (en: "and") can be inserted between "hundert" and following number or "tausend" and following single or double digit number. - - e.g. minus drei und zwanzig -> cardinal { negative: "-" integer: "23" } } - e.g. minus dreiundzwanzig -> cardinal { integer: "23" } } - e.g. dreizehn -> cardinal { integer: "13" } } - e.g. ein hundert -> cardinal { integer: "100" } } - e.g. einhundert -> cardinal { integer: "100" } } - e.g. ein tausend -> cardinal { integer: "1000" } } - e.g. eintausend -> cardinal { integer: "1000" } } - e.g. ein tausend zwanzig -> cardinal { integer: "1020" } } - - Args: - tn_cardinal_tagger: TN cardinal tagger - """ - - def __init__(self, tn_cardinal_tagger: GraphFst, deterministic: bool = True): - super().__init__(name="cardinal", kind="classify", deterministic=deterministic) - - # add_space_between_chars = pynini.cdrewrite(pynini.closure(insert_space, 0, 1), NEMO_CHAR, NEMO_CHAR, NEMO_SIGMA) - optional_delete_space = pynini.closure(NEMO_SIGMA | pynutil.delete(" ")) - - graph = (tn_cardinal_tagger.graph @ optional_delete_space).invert().optimize() - self.graph_hundred_component_at_least_one_none_zero_digit = ( - (tn_cardinal_tagger.graph_hundred_component_at_least_one_none_zero_digit @ optional_delete_space) - .invert() - .optimize() - ) - - self.graph_ties = (tn_cardinal_tagger.two_digit_non_zero @ optional_delete_space).invert().optimize() - # this is to make sure if there is an ambiguity with decimal, decimal is chosen, e.g. 1000000 vs. 1 million - graph = pynutil.add_weight(graph, weight=0.001) - self.graph_no_exception = graph - self.digit = pynini.arcmap(tn_cardinal_tagger.digit, map_type="rmweight").invert().optimize() - graph_exception = pynini.project(self.digit, 'input') - self.graph = (pynini.project(graph, "input") - graph_exception.arcsort()) @ graph - - self.optional_minus_graph = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("minus ", "\"-\" "), 0, 1 - ) - - final_graph = self.optional_minus_graph + pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/date.py b/nemo_text_processing/inverse_text_normalization/de/taggers/date.py deleted file mode 100644 index b65be41e4e1b..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/date.py +++ /dev/null @@ -1,90 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - convert_space, -) -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, in the form of (day) month (year) or year - e.g. vierundzwanzigster juli zwei tausend dreizehn -> tokens { name: "24. Jul. 2013" } - e.g. neunzehnachtzig -> tokens { name: "1980" } - e.g. vierzehnter januar -> tokens { name: "14. Jan." } - e.g. zweiter dritter -> tokens { name: "02.03." } - e.g. januar neunzehnachtzig -> tokens { name: "Jan. 1980" } - e.g. zwanzigzwanzig -> tokens { name: "2020" } - - Args: - itn_cardinal_tagger: ITN cardinal tagger - tn_date_tagger: TN date tagger - tn_date_verbalizer: TN date verbalizer - """ - - def __init__( - self, - itn_cardinal_tagger: GraphFst, - tn_date_tagger: GraphFst, - tn_date_verbalizer: GraphFst, - deterministic: bool = True, - ): - super().__init__(name="date", kind="classify", deterministic=deterministic) - - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - optional_delete_space = pynini.closure(NEMO_SIGMA | pynutil.delete(" ", weight=0.0001)) - tagger = tn_date_verbalizer.graph.invert().optimize() - - delete_day_marker = ( - pynutil.delete("day: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) @ itn_cardinal_tagger.graph_no_exception - - month_as_number = pynutil.delete("month: \"") + itn_cardinal_tagger.graph_no_exception + pynutil.delete("\"") - month_as_string = pynutil.delete("month: \"") + tn_date_tagger.month_abbr.invert() + pynutil.delete("\"") - - convert_year = (tn_date_tagger.year @ optional_delete_space).invert().optimize() - delete_year_marker = ( - pynutil.delete("year: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) @ convert_year - - # day. month as string (year) - verbalizer = ( - pynini.closure(delete_day_marker + pynutil.insert(".") + pynini.accep(" "), 0, 1) - + month_as_string - + pynini.closure(pynini.accep(" ") + delete_year_marker, 0, 1) - ) - - # day. month as number (year) - verbalizer |= ( - delete_day_marker @ add_leading_zero_to_double_digit - + pynutil.insert(".") - + pynutil.delete(" ") - + month_as_number @ add_leading_zero_to_double_digit - + pynutil.insert(".") - + pynini.closure(pynutil.delete(" ") + delete_year_marker, 0, 1) - ) - - # year - verbalizer |= delete_year_marker - - final_graph = tagger @ verbalizer - - graph = pynutil.insert("name: \"") + convert_space(final_graph) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/decimal.py b/nemo_text_processing/inverse_text_normalization/de/taggers/decimal.py deleted file mode 100644 index e6d562d4b43e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/decimal.py +++ /dev/null @@ -1,59 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.taggers.decimal import get_quantity, quantities -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, GraphFst -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal - e.g. minus elf komma zwei null null sechs billionen -> decimal { negative: "true" integer_part: "11" fractional_part: "2006" quantity: "billionen" } - e.g. eine billion -> decimal { integer_part: "1" quantity: "billion" } - Args: - itn_cardinal_tagger: ITN Cardinal tagger - tn_decimal_tagger: TN decimal tagger - """ - - def __init__(self, itn_cardinal_tagger: GraphFst, tn_decimal_tagger: GraphFst, deterministic: bool = True): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - - self.graph = tn_decimal_tagger.graph.invert().optimize() - - delete_point = pynutil.delete(" komma") - - allow_spelling = pynini.cdrewrite(pynini.cross("eine ", "eins ") + quantities, "[BOS]", "[EOS]", NEMO_SIGMA) - - graph_fractional = pynutil.insert("fractional_part: \"") + self.graph + pynutil.insert("\"") - graph_integer = ( - pynutil.insert("integer_part: \"") + itn_cardinal_tagger.graph_no_exception + pynutil.insert("\"") - ) - final_graph_wo_sign = graph_integer + delete_point + pynini.accep(" ") + graph_fractional - - self.final_graph_wo_negative = ( - allow_spelling - @ ( - final_graph_wo_sign - | get_quantity( - final_graph_wo_sign, itn_cardinal_tagger.graph_hundred_component_at_least_one_none_zero_digit - ) - ).optimize() - ) - - final_graph = itn_cardinal_tagger.optional_minus_graph + self.final_graph_wo_negative - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/electronic.py b/nemo_text_processing/inverse_text_normalization/de/taggers/electronic.py deleted file mode 100644 index 849d6c8435ef..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/electronic.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic: email addresses, etc. - e.g. c d f eins at a b c punkt e d u -> tokens { name: "cdf1.abc.edu" } - - Args: - tn_electronic_tagger: TN eletronic tagger - tn_electronic_verbalizer: TN eletronic verbalizer - """ - - def __init__(self, tn_electronic_tagger: GraphFst, tn_electronic_verbalizer: GraphFst, deterministic: bool = True): - super().__init__(name="electronic", kind="classify", deterministic=deterministic) - - tagger = pynini.invert(tn_electronic_verbalizer.graph).optimize() - verbalizer = pynini.invert(tn_electronic_tagger.graph).optimize() - final_graph = tagger @ verbalizer - - graph = pynutil.insert("name: \"") + final_graph + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/fraction.py b/nemo_text_processing/inverse_text_normalization/de/taggers/fraction.py deleted file mode 100644 index 6960a666343a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/fraction.py +++ /dev/null @@ -1,67 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - convert_space, - delete_space, -) -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for classifying fraction - e.g. ein halb -> tokens { name: "1/2" } - e.g. ein ein halb -> tokens { name: "1 1/2" } - e.g. drei zwei ein hundertstel -> tokens { name: "3 2/100" } - - Args: - itn_cardinal_tagger: ITN cardinal tagger - tn_fraction_verbalizer: TN fraction verbalizer - """ - - def __init__(self, itn_cardinal_tagger: GraphFst, tn_fraction_verbalizer: GraphFst, deterministic: bool = True): - super().__init__(name="fraction", kind="classify", deterministic=deterministic) - tagger = tn_fraction_verbalizer.graph.invert().optimize() - - delete_optional_sign = pynini.closure(pynutil.delete("negative: ") + pynini.cross("\"true\" ", "-"), 0, 1) - delete_integer_marker = ( - pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) @ itn_cardinal_tagger.graph_no_exception - - delete_numerator_marker = ( - pynutil.delete("numerator: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) @ itn_cardinal_tagger.graph_no_exception - - delete_denominator_marker = ( - pynutil.insert('/') - + (pynutil.delete("denominator: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"")) - @ itn_cardinal_tagger.graph_no_exception - ) - - graph = ( - pynini.closure(delete_integer_marker + pynini.accep(" "), 0, 1) - + delete_numerator_marker - + delete_space - + delete_denominator_marker - ).optimize() - verbalizer = delete_optional_sign + graph - - self.graph = tagger @ verbalizer - - graph = pynutil.insert("name: \"") + convert_space(self.graph) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/measure.py b/nemo_text_processing/inverse_text_normalization/de/taggers/measure.py deleted file mode 100644 index 86eff3ff29da..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/measure.py +++ /dev/null @@ -1,103 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.taggers.measure import singular_to_plural, unit_singular -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure. Allows for plural form for unit. - e.g. minus elf kilogramm -> measure { cardinal { negative: "true" integer: "11" } units: "kg" } - e.g. drei stunden -> measure { cardinal { integer: "3" } units: "h" } - e.g. ein halb kilogramm -> measure { decimal { integer_part: "1/2" } units: "kg" } - e.g. eins komma zwei kilogramm -> measure { decimal { integer_part: "1" fractional_part: "2" } units: "kg" } - - Args: - itn_cardinal_tagger: ITN Cardinal tagger - itn_decimal_tagger: ITN Decimal tagger - itn_fraction_tagger: ITN Fraction tagger - """ - - def __init__( - self, - itn_cardinal_tagger: GraphFst, - itn_decimal_tagger: GraphFst, - itn_fraction_tagger: GraphFst, - deterministic: bool = True, - ): - super().__init__(name="measure", kind="classify", deterministic=deterministic) - - cardinal_graph = ( - pynini.cdrewrite(pynini.cross(pynini.union("ein", "eine"), "eins"), "[BOS]", "[EOS]", NEMO_SIGMA) - @ itn_cardinal_tagger.graph_no_exception - ) - - graph_unit_singular = pynini.invert(unit_singular) # singular -> abbr - unit = (pynini.invert(singular_to_plural()) @ graph_unit_singular) | graph_unit_singular # plural -> abbr - unit = convert_space(unit) - graph_unit_singular = convert_space(graph_unit_singular) - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("minus", "\"true\"") + delete_extra_space, 0, 1 - ) - - unit_misc = pynutil.insert("/") + pynutil.delete("pro") + delete_space + graph_unit_singular - - unit = ( - pynutil.insert("units: \"") - + (unit | unit_misc | pynutil.add_weight(unit + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - - subgraph_decimal = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + itn_decimal_tagger.final_graph_wo_negative - + pynutil.insert(" }") - + delete_extra_space - + unit - ) - - subgraph_fraction = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + pynutil.insert("integer_part: \"") - + itn_fraction_tagger.graph - + pynutil.insert("\" }") - + delete_extra_space - + unit - ) - - subgraph_cardinal = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + cardinal_graph - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit - ) - final_graph = subgraph_cardinal | subgraph_decimal | subgraph_fraction - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/money.py b/nemo_text_processing/inverse_text_normalization/de/taggers/money.py deleted file mode 100644 index dad06de1c1c5..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/money.py +++ /dev/null @@ -1,91 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.taggers.money import maj_singular, min_plural, min_singular -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money - e.g. elf euro und vier cent -> money { integer_part: "11" fractional_part: 04 currency: "€" } - - Args: - itn_cardinal_tagger: ITN Cardinal Tagger - itn_decimal_tagger: ITN Decimal Tagger - """ - - def __init__(self, itn_cardinal_tagger: GraphFst, itn_decimal_tagger: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="classify", deterministic=deterministic) - cardinal_graph = ( - pynini.cdrewrite(pynini.cross(pynini.union("ein", "eine"), "eins"), "[BOS]", "[EOS]", NEMO_SIGMA) - @ itn_cardinal_tagger.graph_no_exception - ) - graph_decimal_final = itn_decimal_tagger.final_graph_wo_negative - - graph_unit = pynini.invert(maj_singular) - graph_unit = pynutil.insert("currency: \"") + convert_space(graph_unit) + pynutil.insert("\"") - - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - min_unit = pynini.project(min_singular | min_plural, "output") - # elf euro (und) vier cent, vier cent - cents_standalone = ( - pynutil.insert("fractional_part: \"") - + cardinal_graph @ add_leading_zero_to_double_digit - + delete_space - + pynutil.delete(min_unit) - + pynutil.insert("\"") - ) - - optional_cents_standalone = pynini.closure( - delete_space - + pynini.closure(pynutil.delete("und") + delete_space, 0, 1) - + insert_space - + cents_standalone, - 0, - 1, - ) - # elf euro vierzig, only after integer - optional_cents_suffix = pynini.closure( - delete_extra_space - + pynutil.insert("fractional_part: \"") - + pynutil.add_weight(cardinal_graph @ add_leading_zero_to_double_digit, -0.7) - + pynutil.insert("\""), - 0, - 1, - ) - - graph_integer = ( - pynutil.insert("integer_part: \"") - + cardinal_graph - + pynutil.insert("\"") - + delete_extra_space - + graph_unit - + (optional_cents_standalone | optional_cents_suffix) - ) - graph_decimal = graph_decimal_final + delete_extra_space + graph_unit - graph_decimal |= pynutil.insert("currency: \"€\" integer_part: \"0\" ") + cents_standalone - final_graph = graph_integer | graph_decimal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/ordinal.py b/nemo_text_processing/inverse_text_normalization/de/taggers/ordinal.py deleted file mode 100644 index 300dd901032c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/ordinal.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal - e.g. dreizehnter -> tokens { name: "13." } - - Args: - itn_cardinal_tagger: ITN Cardinal Tagger - tn_ordinal_verbalizer: TN Ordinal Verbalizer - """ - - def __init__(self, itn_cardinal_tagger: GraphFst, tn_ordinal_verbalizer: GraphFst, deterministic: bool = True): - super().__init__(name="ordinal", kind="classify", deterministic=deterministic) - - tagger = tn_ordinal_verbalizer.graph.invert().optimize() - - graph = ( - pynutil.delete("integer: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) @ itn_cardinal_tagger.graph - - final_graph = tagger @ graph + pynutil.insert(".") - - graph = pynutil.insert("name: \"") + final_graph + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/telephone.py b/nemo_text_processing/inverse_text_normalization/de/taggers/telephone.py deleted file mode 100644 index ddc3391d4b95..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/telephone.py +++ /dev/null @@ -1,53 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space, insert_space -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone numbers, e.g. - null vier eins eins eins zwei drei vier eins zwei drei vier -> tokens { name: "(0411) 1234-1234" } - - Args: - tn_cardinal_tagger: TN Cardinal Tagger - """ - - def __init__(self, tn_cardinal_tagger: GraphFst, deterministic: bool = True): - super().__init__(name="telephone", kind="classify", deterministic=deterministic) - separator = pynini.accep(" ") # between components - digit = pynini.union(*list(map(str, range(1, 10)))) @ tn_cardinal_tagger.two_digit_non_zero - zero = pynini.cross("0", "null") - - number_part = ( - pynutil.delete("(") - + zero - + insert_space - + pynini.closure(digit + insert_space, 2, 2) - + digit - + pynutil.delete(")") - + separator - + pynini.closure(digit + insert_space, 3, 3) - + digit - + pynutil.delete("-") - + insert_space - + pynini.closure(digit + insert_space, 3, 3) - + digit - ) - graph = convert_space(pynini.invert(number_part)) - final_graph = pynutil.insert("name: \"") + graph + pynutil.insert("\"") - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/time.py b/nemo_text_processing/inverse_text_normalization/de/taggers/time.py deleted file mode 100644 index c747202b923d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/time.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, GraphFst -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time - e.g. acht uhr e s t-> time { hours: "8" zone: "e s t" } - e.g. dreizehn uhr -> time { hours: "13" } - e.g. dreizehn uhr zehn -> time { hours: "13" minutes: "10" } - e.g. viertel vor zwölf -> time { minutes: "45" hours: "11" } - e.g. viertel nach zwölf -> time { minutes: "15" hours: "12" } - e.g. halb zwölf -> time { minutes: "30" hours: "11" } - e.g. drei vor zwölf -> time { minutes: "57" hours: "11" } - e.g. drei nach zwölf -> time { minutes: "3" hours: "12" } - e.g. drei uhr zehn minuten zehn sekunden -> time { hours: "3" hours: "10" sekunden: "10"} - - Args: - tn_time_verbalizer: TN time verbalizer - """ - - def __init__(self, tn_time_verbalizer: GraphFst, deterministic: bool = True): - super().__init__(name="time", kind="classify", deterministic=deterministic) - # lazy way to make sure compounds work - optional_delete_space = pynini.closure(NEMO_SIGMA | pynutil.delete(" ", weight=0.0001)) - graph = (tn_time_verbalizer.graph @ optional_delete_space).invert().optimize() - self.fst = self.add_tokens(graph).optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/tokenize_and_classify.py b/nemo_text_processing/inverse_text_normalization/de/taggers/tokenize_and_classify.py deleted file mode 100644 index 487fcd71effd..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,141 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.inverse_text_normalization.de.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.de.taggers.date import DateFst -from nemo_text_processing.inverse_text_normalization.de.taggers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.de.taggers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.de.taggers.fraction import FractionFst -from nemo_text_processing.inverse_text_normalization.de.taggers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.de.taggers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.de.taggers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.de.taggers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.de.taggers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.de.taggers.whitelist import WhiteListFst -from nemo_text_processing.inverse_text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.inverse_text_normalization.en.taggers.word import WordFst -from nemo_text_processing.text_normalization.de.taggers.cardinal import CardinalFst as TNCardinalTagger -from nemo_text_processing.text_normalization.de.taggers.date import DateFst as TNDateTagger -from nemo_text_processing.text_normalization.de.taggers.decimal import DecimalFst as TNDecimalTagger -from nemo_text_processing.text_normalization.de.taggers.electronic import ElectronicFst as TNElectronicTagger -from nemo_text_processing.text_normalization.de.taggers.whitelist import WhiteListFst as TNWhitelistTagger -from nemo_text_processing.text_normalization.de.verbalizers.date import DateFst as TNDateVerbalizer -from nemo_text_processing.text_normalization.de.verbalizers.electronic import ElectronicFst as TNElectronicVerbalizer -from nemo_text_processing.text_normalization.de.verbalizers.fraction import FractionFst as TNFractionVerbalizer -from nemo_text_processing.text_normalization.de.verbalizers.ordinal import OrdinalFst as TNOrdinalVerbalizer -from nemo_text_processing.text_normalization.de.verbalizers.time import TimeFst as TNTimeVerbalizer -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False, deterministic: bool = True): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != 'None': - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "_de_itn.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars.") - tn_cardinal_tagger = TNCardinalTagger(deterministic=False) - tn_date_tagger = TNDateTagger(cardinal=tn_cardinal_tagger, deterministic=False) - tn_decimal_tagger = TNDecimalTagger(cardinal=tn_cardinal_tagger, deterministic=False) - tn_ordinal_verbalizer = TNOrdinalVerbalizer(deterministic=False) - tn_fraction_verbalizer = TNFractionVerbalizer(ordinal=tn_ordinal_verbalizer, deterministic=False) - tn_time_verbalizer = TNTimeVerbalizer(cardinal_tagger=tn_cardinal_tagger, deterministic=False) - tn_date_verbalizer = TNDateVerbalizer(ordinal=tn_ordinal_verbalizer, deterministic=False) - tn_electronic_tagger = TNElectronicTagger(deterministic=False) - tn_electronic_verbalizer = TNElectronicVerbalizer(deterministic=False) - tn_whitelist_tagger = TNWhitelistTagger(input_case="cased", deterministic=False) - - cardinal = CardinalFst(tn_cardinal_tagger=tn_cardinal_tagger) - cardinal_graph = cardinal.fst - - ordinal = OrdinalFst(itn_cardinal_tagger=cardinal, tn_ordinal_verbalizer=tn_ordinal_verbalizer) - ordinal_graph = ordinal.fst - decimal = DecimalFst(itn_cardinal_tagger=cardinal, tn_decimal_tagger=tn_decimal_tagger) - decimal_graph = decimal.fst - - fraction = FractionFst(itn_cardinal_tagger=cardinal, tn_fraction_verbalizer=tn_fraction_verbalizer) - fraction_graph = fraction.fst - - measure_graph = MeasureFst( - itn_cardinal_tagger=cardinal, itn_decimal_tagger=decimal, itn_fraction_tagger=fraction - ).fst - date_graph = DateFst( - itn_cardinal_tagger=cardinal, tn_date_verbalizer=tn_date_verbalizer, tn_date_tagger=tn_date_tagger - ).fst - word_graph = WordFst().fst - time_graph = TimeFst(tn_time_verbalizer=tn_time_verbalizer).fst - money_graph = MoneyFst(itn_cardinal_tagger=cardinal, itn_decimal_tagger=decimal).fst - whitelist_graph = WhiteListFst(tn_whitelist_tagger=tn_whitelist_tagger).fst - punct_graph = PunctuationFst().fst - electronic_graph = ElectronicFst( - tn_electronic_tagger=tn_electronic_tagger, tn_electronic_verbalizer=tn_electronic_verbalizer - ).fst - telephone_graph = TelephoneFst(tn_cardinal_tagger=tn_cardinal_tagger).fst - - classify = ( - pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(whitelist_graph, 1.0) - | pynutil.add_weight(time_graph, 1.1) - | pynutil.add_weight(date_graph, 1.1) - | pynutil.add_weight(decimal_graph, 1.1) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(fraction_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/inverse_text_normalization/de/taggers/whitelist.py b/nemo_text_processing/inverse_text_normalization/de/taggers/whitelist.py deleted file mode 100644 index 5d52e3a37ca1..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/taggers/whitelist.py +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelisted tokens - e.g. misses -> tokens { name: "Mrs." } - Args: - tn_whitelist_tagger: TN whitelist tagger - """ - - def __init__(self, tn_whitelist_tagger: GraphFst, deterministic: bool = True): - super().__init__(name="whitelist", kind="classify", deterministic=deterministic) - - whitelist = pynini.invert(tn_whitelist_tagger.graph) - graph = pynutil.insert("name: \"") + convert_space(whitelist) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/__init__.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/cardinal.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/cardinal.py deleted file mode 100644 index 92a83625a5f2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/cardinal.py +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinal - e.g. cardinal { integer: "23" negative: "-" } -> -23 - - Args: - tn_cardinal_verbalizer: TN cardinal verbalizer - """ - - def __init__(self, tn_cardinal_verbalizer: GraphFst, deterministic: bool = True): - super().__init__(name="cardinal", kind="verbalize", deterministic=deterministic) - self.numbers = tn_cardinal_verbalizer.numbers - optional_sign = pynini.closure(pynutil.delete("negative: \"") + NEMO_NOT_QUOTE + pynutil.delete("\" "), 0, 1) - graph = optional_sign + self.numbers - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/decimal.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/decimal.py deleted file mode 100644 index ff3839533d72..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/decimal.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_preserve_order -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, e.g. - decimal { negative: "true" integer_part: "12" fractional_part: "5006" quantity: "billion" } -> -12.5006 billion - - Args: - tn_decimal_verbalizer: TN decimal verbalizer - """ - - def __init__(self, tn_decimal_verbalizer: GraphFst, deterministic: bool = True): - super().__init__(name="decimal", kind="verbalize", deterministic=deterministic) - delete_space = pynutil.delete(" ") - optional_sign = pynini.closure( - pynutil.delete("negative: \"") + NEMO_NOT_QUOTE + pynutil.delete("\"") + delete_space, 0, 1 - ) - optional_integer = pynini.closure(tn_decimal_verbalizer.integer, 0, 1) - optional_fractional = pynini.closure( - delete_space + pynutil.insert(",") + tn_decimal_verbalizer.fractional_default, 0, 1 - ) - graph = (optional_integer + optional_fractional + tn_decimal_verbalizer.optional_quantity).optimize() - self.numbers = optional_sign + graph - graph = self.numbers + delete_preserve_order - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/measure.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/measure.py deleted file mode 100644 index 90f43e7e6f40..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/measure.py +++ /dev/null @@ -1,64 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { cardinal { negative: "true" integer: "12" } units: "kg" } -> -12 kg - measure { decimal { integer_part: "1/2" } units: "kg" } -> 1/2 kg - measure { decimal { integer_part: "1" fractional_part: "2" quantity: "million" } units: "kg" } -> 1,2 million kg - - Args: - decimal: ITN Decimal verbalizer - cardinal: ITN Cardinal verbalizer - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="measure", kind="verbalize", deterministic=deterministic) - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "-"), 0, 1) - unit = ( - pynutil.delete("units:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - + delete_space - ) - graph_decimal = ( - pynutil.delete("decimal {") - + delete_space - + optional_sign - + delete_space - + decimal.numbers - + delete_space - + pynutil.delete("}") - ) - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + delete_space - + cardinal.numbers - + delete_space - + pynutil.delete("}") - ) - - graph = (graph_cardinal | graph_decimal) + delete_space + pynutil.insert(" ") + unit - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/money.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/money.py deleted file mode 100644 index f0377d4fac4e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/money.py +++ /dev/null @@ -1,40 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { integer_part: "12" fractional_part: "05" currency: "$" } -> $12.05 - - Args: - decimal: ITN Decimal verbalizer - """ - - def __init__(self, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="verbalize", deterministic=deterministic) - unit = ( - pynutil.delete("currency:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = unit + delete_space + decimal.numbers - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/time.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/time.py deleted file mode 100644 index 13a013db57ed..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/time.py +++ /dev/null @@ -1,52 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_ALPHA, NEMO_DIGIT, GraphFst, delete_space -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, e.g. - time { hours: "8" minutes: "30" zone: "e s t" } -> 08:30 Uhr est - time { hours: "8" } -> 8 Uhr - time { hours: "8" minutes: "30" seconds: "10" } -> 08:30:10 Uhr - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="time", kind="verbalize", deterministic=deterministic) - - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - hour = pynutil.delete("hours: \"") + pynini.closure(NEMO_DIGIT, 1) + pynutil.delete("\"") - minute = pynutil.delete("minutes: \"") + pynini.closure(NEMO_DIGIT, 1) + pynutil.delete("\"") - - second = pynutil.delete("seconds: \"") + pynini.closure(NEMO_DIGIT, 1) + pynutil.delete("\"") - zone = ( - pynutil.delete("zone: \"") + pynini.closure(NEMO_ALPHA + delete_space) + NEMO_ALPHA + pynutil.delete("\"") - ) - optional_zone = pynini.closure(pynini.accep(" ") + zone, 0, 1) - graph = ( - delete_space - + pynutil.insert(":") - + (minute @ add_leading_zero_to_double_digit) - + pynini.closure(delete_space + pynutil.insert(":") + (second @ add_leading_zero_to_double_digit), 0, 1) - + pynutil.insert(" Uhr") - + optional_zone - ) - graph_h = hour + pynutil.insert(" Uhr") + optional_zone - graph_hm = hour @ add_leading_zero_to_double_digit + graph - graph_hms = hour @ add_leading_zero_to_double_digit + graph - final_graph = graph_hm | graph_hms | graph_h - self.fst = self.delete_tokens(final_graph).optimize() diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/verbalize.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/verbalize.py deleted file mode 100644 index 80bafd1978d6..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/verbalize.py +++ /dev/null @@ -1,45 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.de.verbalizers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.de.verbalizers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.de.verbalizers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.de.verbalizers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.de.verbalizers.time import TimeFst -from nemo_text_processing.text_normalization.de.verbalizers.cardinal import CardinalFst as TNCardinalVerbalizer -from nemo_text_processing.text_normalization.de.verbalizers.decimal import DecimalFst as TNDecimalVerbalizer -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="verbalize", kind="verbalize", deterministic=deterministic) - tn_cardinal_verbalizer = TNCardinalVerbalizer(deterministic=False) - tn_decimal_verbalizer = TNDecimalVerbalizer(deterministic=False) - - cardinal = CardinalFst(tn_cardinal_verbalizer=tn_cardinal_verbalizer) - cardinal_graph = cardinal.fst - decimal = DecimalFst(tn_decimal_verbalizer=tn_decimal_verbalizer) - decimal_graph = decimal.fst - measure_graph = MeasureFst(decimal=decimal, cardinal=cardinal).fst - money_graph = MoneyFst(decimal=decimal).fst - time_graph = TimeFst().fst - graph = time_graph | money_graph | measure_graph | decimal_graph | cardinal_graph - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/de/verbalizers/verbalize_final.py b/nemo_text_processing/inverse_text_normalization/de/verbalizers/verbalize_final.py deleted file mode 100644 index 779a00a4234e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/de/verbalizers/verbalize_final.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.de.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "jetzt" } tokens { name: "ist" } tokens { time { hours: "12" minutes: "30" } } -> jetzt ist 12:30 Uhr - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="verbalize_final", kind="verbalize", deterministic=deterministic) - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/en/__init__.py b/nemo_text_processing/inverse_text_normalization/en/__init__.py deleted file mode 100644 index a1ed7385c85c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst diff --git a/nemo_text_processing/inverse_text_normalization/en/clean_eval_data.py b/nemo_text_processing/inverse_text_normalization/en/clean_eval_data.py deleted file mode 100644 index d9bc2fccb685..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/clean_eval_data.py +++ /dev/null @@ -1,342 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from argparse import ArgumentParser -from typing import List - -import regex as re -from nemo_text_processing.text_normalization.data_loader_utils import ( - EOS_TYPE, - Instance, - load_files, - training_data_to_sentences, -) - - -""" -This file is for evaluation purposes. -filter_loaded_data() cleans data (list of instances) for inverse text normalization. Filters and cleaners can be specified for each semiotic class individually. -For example, normalized text should only include characters and whitespace characters but no punctuation. - Cardinal unnormalized instances should contain at least one integer and all other characters are removed. -""" - - -class Filter: - """ - Filter class - - Args: - class_type: semiotic class used in dataset - process_func: function to transform text - filter_func: function to filter text - - """ - - def __init__(self, class_type: str, process_func: object, filter_func: object): - self.class_type = class_type - self.process_func = process_func - self.filter_func = filter_func - - def filter(self, instance: Instance) -> bool: - """ - filter function - - Args: - filters given instance with filter function - - Returns: True if given instance fulfills criteria or does not belong to class type - """ - if instance.token_type != self.class_type: - return True - return self.filter_func(instance) - - def process(self, instance: Instance) -> Instance: - """ - process function - - Args: - processes given instance with process function - - Returns: processed instance if instance belongs to expected class type or original instance - """ - if instance.token_type != self.class_type: - return instance - return self.process_func(instance) - - -def filter_cardinal_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_cardinal_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r"[^0-9]", "", un_normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_ordinal_1(instance: Instance) -> bool: - ok = re.search(r"(st|nd|rd|th)\s*$", instance.un_normalized) - return ok - - -def process_ordinal_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r"[,\s]", "", un_normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_decimal_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_decimal_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - un_normalized = re.sub(r",", "", un_normalized) - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_measure_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_measure_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r",", "", un_normalized) - un_normalized = re.sub(r"m2", "m²", un_normalized) - un_normalized = re.sub(r"(\d)([^\d.\s])", r"\1 \2", un_normalized) - normalized = re.sub(r"[^a-z\s]", "", normalized) - normalized = re.sub(r"per ([a-z\s]*)s$", r"per \1", normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_money_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_money_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r",", "", un_normalized) - un_normalized = re.sub(r"a\$", r"$", un_normalized) - un_normalized = re.sub(r"us\$", r"$", un_normalized) - un_normalized = re.sub(r"(\d)m\s*$", r"\1 million", un_normalized) - un_normalized = re.sub(r"(\d)bn?\s*$", r"\1 billion", un_normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_time_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_time_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - un_normalized = re.sub(r": ", ":", un_normalized) - un_normalized = re.sub(r"(\d)\s?a\s?m\s?", r"\1 a.m.", un_normalized) - un_normalized = re.sub(r"(\d)\s?p\s?m\s?", r"\1 p.m.", un_normalized) - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_plain_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_plain_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_punct_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_punct_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_date_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_date_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - un_normalized = re.sub(r",", "", un_normalized) - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_letters_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_letters_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_verbatim_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_verbatim_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_digit_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_digit_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_telephone_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_telephone_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_electronic_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_electronic_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_fraction_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_fraction_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_address_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_address_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -filters = [] -filters.append(Filter(class_type="CARDINAL", process_func=process_cardinal_1, filter_func=filter_cardinal_1)) -filters.append(Filter(class_type="ORDINAL", process_func=process_ordinal_1, filter_func=filter_ordinal_1)) -filters.append(Filter(class_type="DECIMAL", process_func=process_decimal_1, filter_func=filter_decimal_1)) -filters.append(Filter(class_type="MEASURE", process_func=process_measure_1, filter_func=filter_measure_1)) -filters.append(Filter(class_type="MONEY", process_func=process_money_1, filter_func=filter_money_1)) -filters.append(Filter(class_type="TIME", process_func=process_time_1, filter_func=filter_time_1)) - -filters.append(Filter(class_type="DATE", process_func=process_date_1, filter_func=filter_date_1)) -filters.append(Filter(class_type="PLAIN", process_func=process_plain_1, filter_func=filter_plain_1)) -filters.append(Filter(class_type="PUNCT", process_func=process_punct_1, filter_func=filter_punct_1)) -filters.append(Filter(class_type="LETTERS", process_func=process_letters_1, filter_func=filter_letters_1)) -filters.append(Filter(class_type="VERBATIM", process_func=process_verbatim_1, filter_func=filter_verbatim_1)) -filters.append(Filter(class_type="DIGIT", process_func=process_digit_1, filter_func=filter_digit_1)) -filters.append(Filter(class_type="TELEPHONE", process_func=process_telephone_1, filter_func=filter_telephone_1)) -filters.append(Filter(class_type="ELECTRONIC", process_func=process_electronic_1, filter_func=filter_electronic_1)) -filters.append(Filter(class_type="FRACTION", process_func=process_fraction_1, filter_func=filter_fraction_1)) -filters.append(Filter(class_type="ADDRESS", process_func=process_address_1, filter_func=filter_address_1)) -filters.append(Filter(class_type=EOS_TYPE, process_func=lambda x: x, filter_func=lambda x: True)) - - -def filter_loaded_data(data: List[Instance], verbose: bool = False) -> List[Instance]: - """ - Filters list of instances - - Args: - data: list of instances - - Returns: filtered and transformed list of instances - """ - updates_instances = [] - for instance in data: - updated_instance = False - for fil in filters: - if fil.class_type == instance.token_type and fil.filter(instance): - instance = fil.process(instance) - updated_instance = True - if updated_instance: - if verbose: - print(instance) - updates_instances.append(instance) - return updates_instances - - -def parse_args(): - parser = ArgumentParser() - parser.add_argument("--input", help="input file path", type=str, default='./en_with_types/output-00001-of-00100') - parser.add_argument("--verbose", help="print filtered instances", action='store_true') - return parser.parse_args() - - -if __name__ == "__main__": - args = parse_args() - file_path = args.input - - print("Loading training data: " + file_path) - instance_list = load_files([file_path]) # List of instances - filtered_instance_list = filter_loaded_data(instance_list, args.verbose) - training_data_to_sentences(filtered_instance_list) diff --git a/nemo_text_processing/inverse_text_normalization/en/data/__init__.py b/nemo_text_processing/inverse_text_normalization/en/data/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/en/data/currency.tsv b/nemo_text_processing/inverse_text_normalization/en/data/currency.tsv deleted file mode 100644 index c3712552dc72..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/currency.tsv +++ /dev/null @@ -1,35 +0,0 @@ -$ dollar -$ us dollar -$ united states dollar -£ british pound -€ euro -₩ won -nzd new zealand dollar -rs rupee -chf swiss franc -dkk danish kroner -fim finnish markka -aed arab emirates dirham -¥ yen -czk czech koruna -mro mauritanian ouguiya -pkr pakistani rupee -crc costa rican colon -hk$ hong kong dollar -npr nepalese rupee -awg aruban florin -nok norwegian kroner -tzs tanzanian shilling -sek swedish kronor -cyp cypriot pound -r real -sar saudi riyal -cve cape verde escudo -rsd serbian dinar -dm german mark -shp saint helena pounds -php philippine peso -cad canadian dollar -ssp south sudanese pound -scr seychelles rupee -mvr maldivian rufiyaa \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/electronic/__init__.py b/nemo_text_processing/inverse_text_normalization/en/data/electronic/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/en/data/electronic/domain.tsv b/nemo_text_processing/inverse_text_normalization/en/data/electronic/domain.tsv deleted file mode 100644 index 207a14ae1c2d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/electronic/domain.tsv +++ /dev/null @@ -1,10 +0,0 @@ -com -uk -fr -net -br -in -ru -de -it -ai diff --git a/nemo_text_processing/inverse_text_normalization/en/data/electronic/server_name.tsv b/nemo_text_processing/inverse_text_normalization/en/data/electronic/server_name.tsv deleted file mode 100644 index ca7f97bc9f69..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/electronic/server_name.tsv +++ /dev/null @@ -1,17 +0,0 @@ -g mail gmail -gmail -n vidia nvidia -nvidia -outlook -hotmail -yahoo -aol -gmx -msn -live -yandex -orange -wanadoo -web -comcast -google diff --git a/nemo_text_processing/inverse_text_normalization/en/data/electronic/symbols.tsv b/nemo_text_processing/inverse_text_normalization/en/data/electronic/symbols.tsv deleted file mode 100644 index 5be8da870eae..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/electronic/symbols.tsv +++ /dev/null @@ -1,22 +0,0 @@ -. dot -- dash -- hyphen -_ underscore -! exclamation mark -# number sign -$ dollar sign -% percent sign -& ampersand -' quote -* asterisk -+ plus -/ slash -= equal sign -? question mark -^ circumflex -` right single quote -{ left brace -| vertical bar -} right brace -~ tilde -, comma \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/magnitudes.tsv b/nemo_text_processing/inverse_text_normalization/en/data/magnitudes.tsv deleted file mode 100644 index 3bfa4849e869..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/magnitudes.tsv +++ /dev/null @@ -1,4 +0,0 @@ -k thousand -m million -b billion -t trillion \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/measurements.tsv b/nemo_text_processing/inverse_text_normalization/en/data/measurements.tsv deleted file mode 100644 index 6801b7b427b8..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/measurements.tsv +++ /dev/null @@ -1,109 +0,0 @@ -f fahrenheit -c celsius -km kilometer -m meter -cm centimeter -mm millimeter -ha hectare -mi mile -m² square meter -km² square kilometer -ft foot -% percent -hz hertz -kw kilowatt -hp horsepower -mg milligram -kg kilogram -ghz gigahertz -khz kilohertz -mhz megahertz -v volt -h hour -mc mega coulomb -s second -nm nanometer -rpm revolution per minute -min minute -mA milli ampere -% per cent -kwh kilo watt hour -m³ cubic meter -mph mile per hour -tw tera watt -mv milli volt -mw megawatt -μm micrometer -" inch -tb terabyte -cc c c -g gram -da dalton -atm atmosphere -ω ohm -db decibel -ps peta second -oz ounce -hl hecto liter -μg microgram -pg petagram -gb gigabyte -kb kilobit -ev electron volt -mb megabyte -kb kilobyte -kbps kilobit per second -mbps megabit per second -st stone -kl kilo liter -tj tera joule -kv kilo volt -mv mega volt -kn kilonewton -mm megameter -au astronomical unit -yd yard -rad radian -lm lumen -hs hecto second -mol mole -gpa giga pascal -ml milliliter -gw gigawatt -ma mega ampere -kt knot -kgf kilogram force -ng nano gram -ns nanosecond -ms mega siemens -bar bar -gl giga liter -μs microsecond -da deci ampere -pa pascal -ds deci second -ms milli second -dm deci meter -dm³ cubic deci meter -amu atomic mass unit -mb megabit -mf mega farad -bq becquerel -pb petabit -mm² square millimeter -cm² square centimeter -sq mi square mile -sq ft square foot -kpa kilopascal -cd candela -tl tera liter -ms mega second -mpa megapascal -pm peta meter -pb peta byte -gwh giga watt hour -kcal kilo calory -gy gray -sv sievert -cwt hundredweight -cc c c diff --git a/nemo_text_processing/inverse_text_normalization/en/data/months.tsv b/nemo_text_processing/inverse_text_normalization/en/data/months.tsv deleted file mode 100644 index 6e7903c0ba26..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/months.tsv +++ /dev/null @@ -1,12 +0,0 @@ -january -february -march -april -may -june -july -august -september -october -november -december \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/numbers/__init__.py b/nemo_text_processing/inverse_text_normalization/en/data/numbers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/en/data/numbers/digit.tsv b/nemo_text_processing/inverse_text_normalization/en/data/numbers/digit.tsv deleted file mode 100644 index fa329799db6f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/numbers/digit.tsv +++ /dev/null @@ -1,9 +0,0 @@ -one 1 -two 2 -three 3 -four 4 -five 5 -six 6 -seven 7 -eight 8 -nine 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/numbers/hundred.tsv b/nemo_text_processing/inverse_text_normalization/en/data/numbers/hundred.tsv deleted file mode 100644 index 10e2b9645a53..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/numbers/hundred.tsv +++ /dev/null @@ -1 +0,0 @@ -hundred \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/numbers/teen.tsv b/nemo_text_processing/inverse_text_normalization/en/data/numbers/teen.tsv deleted file mode 100644 index 8e60fa1d3cb3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/numbers/teen.tsv +++ /dev/null @@ -1,10 +0,0 @@ -ten 10 -eleven 11 -twelve 12 -thirteen 13 -fourteen 14 -fifteen 15 -sixteen 16 -seventeen 17 -eighteen 18 -nineteen 19 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/numbers/thousands.tsv b/nemo_text_processing/inverse_text_normalization/en/data/numbers/thousands.tsv deleted file mode 100644 index bf30542bb6bc..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/numbers/thousands.tsv +++ /dev/null @@ -1,22 +0,0 @@ -thousand -million -billion -trillion -quadrillion -quintillion -sextillion -septillion -octillion -nonillion -decillion -undecillion -duodecillion -tredecillion -quattuordecillion -quindecillion -sexdecillion -septendecillion -octodecillion -novemdecillion -vigintillion -centillion \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/numbers/ties.tsv b/nemo_text_processing/inverse_text_normalization/en/data/numbers/ties.tsv deleted file mode 100644 index d7ec82e11478..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/numbers/ties.tsv +++ /dev/null @@ -1,9 +0,0 @@ -twenty 2 -thirty 3 -forty 4 -fourty 4 -fifty 5 -sixty 6 -seventy 7 -eighty 8 -ninety 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/numbers/zero.tsv b/nemo_text_processing/inverse_text_normalization/en/data/numbers/zero.tsv deleted file mode 100644 index c479272d4039..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/numbers/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -zero 0 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/ordinals/__init__.py b/nemo_text_processing/inverse_text_normalization/en/data/ordinals/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/ordinals/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/en/data/ordinals/digit.tsv b/nemo_text_processing/inverse_text_normalization/en/data/ordinals/digit.tsv deleted file mode 100644 index 4b7fc24f1606..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/ordinals/digit.tsv +++ /dev/null @@ -1,9 +0,0 @@ -first one -second two -third three -fourth four -fifth five -sixth sixth -seventh seven -eighth eight -ninth nine \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/ordinals/teen.tsv b/nemo_text_processing/inverse_text_normalization/en/data/ordinals/teen.tsv deleted file mode 100644 index 496fefc086d1..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/ordinals/teen.tsv +++ /dev/null @@ -1 +0,0 @@ -twelfth twelve \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/time/__init__.py b/nemo_text_processing/inverse_text_normalization/en/data/time/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/en/data/time/minute_to.tsv b/nemo_text_processing/inverse_text_normalization/en/data/time/minute_to.tsv deleted file mode 100644 index edab4d5b03d6..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/time/minute_to.tsv +++ /dev/null @@ -1,59 +0,0 @@ -1 59 -2 58 -3 57 -4 56 -5 55 -6 54 -7 53 -8 52 -9 51 -10 50 -11 49 -12 48 -13 47 -14 46 -15 45 -16 44 -17 43 -18 42 -19 41 -20 40 -21 39 -22 38 -23 37 -24 36 -25 35 -26 34 -27 33 -28 32 -29 31 -30 30 -31 29 -32 28 -33 27 -34 26 -35 25 -36 24 -37 23 -38 22 -39 21 -40 20 -41 19 -42 18 -43 17 -44 16 -45 15 -46 14 -47 13 -48 12 -49 11 -50 10 -51 9 -52 8 -53 7 -54 6 -55 5 -56 4 -57 3 -58 2 -59 1 diff --git a/nemo_text_processing/inverse_text_normalization/en/data/time/time_suffix.tsv b/nemo_text_processing/inverse_text_normalization/en/data/time/time_suffix.tsv deleted file mode 100644 index b39a9ef9a92c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/time/time_suffix.tsv +++ /dev/null @@ -1,8 +0,0 @@ -p m p.m. -pm p.m. -p.m. -p.m p.m. -am a.m. -a.m. -a.m a.m. -a m a.m. \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/time/time_zone.tsv b/nemo_text_processing/inverse_text_normalization/en/data/time/time_zone.tsv deleted file mode 100644 index 3e0ade467a84..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/time/time_zone.tsv +++ /dev/null @@ -1,7 +0,0 @@ -cst c s t -cet c e t -pst p s t -est e s t -pt p t -et e t -gmt g m t diff --git a/nemo_text_processing/inverse_text_normalization/en/data/time/to_hour.tsv b/nemo_text_processing/inverse_text_normalization/en/data/time/to_hour.tsv deleted file mode 100644 index 1b006ea3ea0f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/time/to_hour.tsv +++ /dev/null @@ -1,12 +0,0 @@ -one 12 -two 1 -three 2 -four 3 -five 4 -six 5 -seven 6 -eigh 7 -nine 8 -ten 9 -eleven 10 -twelve 11 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/en/data/whitelist.tsv b/nemo_text_processing/inverse_text_normalization/en/data/whitelist.tsv deleted file mode 100644 index 7eed41ecf2ee..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/data/whitelist.tsv +++ /dev/null @@ -1,12 +0,0 @@ -e.g. for example -dr. doctor -mr. mister -mrs. misses -st. saint -7-eleven seven eleven -es3 e s three -s&p s and p -ASAP a s a p -AT&T a t and t -LLP l l p -ATM a t m diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/__init__.py b/nemo_text_processing/inverse_text_normalization/en/taggers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/cardinal.py b/nemo_text_processing/inverse_text_normalization/en/taggers/cardinal.py deleted file mode 100644 index ac72a2bf0e9a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/cardinal.py +++ /dev/null @@ -1,143 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path, num_to_word -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals - e.g. minus twenty three -> cardinal { integer: "23" negative: "-" } } - Numbers below thirteen are not converted. - """ - - def __init__(self): - super().__init__(name="cardinal", kind="classify") - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - - graph_hundred = pynini.cross("hundred", "") - - graph_hundred_component = pynini.union(graph_digit + delete_space + graph_hundred, pynutil.insert("0")) - graph_hundred_component += delete_space - graph_hundred_component += pynini.union( - graph_teen | pynutil.insert("00"), - (graph_ties | pynutil.insert("0")) + delete_space + (graph_digit | pynutil.insert("0")), - ) - - graph_hundred_component_at_least_one_none_zero_digit = graph_hundred_component @ ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT) - ) - self.graph_hundred_component_at_least_one_none_zero_digit = ( - graph_hundred_component_at_least_one_none_zero_digit - ) - - # Transducer for eleven hundred -> 1100 or twenty one hundred eleven -> 2111 - graph_hundred_as_thousand = pynini.union(graph_teen, graph_ties + delete_space + graph_digit) - graph_hundred_as_thousand += delete_space + graph_hundred - graph_hundred_as_thousand += delete_space + pynini.union( - graph_teen | pynutil.insert("00"), - (graph_ties | pynutil.insert("0")) + delete_space + (graph_digit | pynutil.insert("0")), - ) - - graph_hundreds = graph_hundred_component | graph_hundred_as_thousand - - graph_thousands = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("thousand"), - pynutil.insert("000", weight=0.1), - ) - - graph_million = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("million"), - pynutil.insert("000", weight=0.1), - ) - graph_billion = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("billion"), - pynutil.insert("000", weight=0.1), - ) - graph_trillion = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("trillion"), - pynutil.insert("000", weight=0.1), - ) - graph_quadrillion = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("quadrillion"), - pynutil.insert("000", weight=0.1), - ) - graph_quintillion = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("quintillion"), - pynutil.insert("000", weight=0.1), - ) - graph_sextillion = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("sextillion"), - pynutil.insert("000", weight=0.1), - ) - - graph = pynini.union( - graph_sextillion - + delete_space - + graph_quintillion - + delete_space - + graph_quadrillion - + delete_space - + graph_trillion - + delete_space - + graph_billion - + delete_space - + graph_million - + delete_space - + graph_thousands - + delete_space - + graph_hundreds, - graph_zero, - ) - - graph = graph @ pynini.union( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT), "0" - ) - - labels_exception = [num_to_word(x) for x in range(0, 13)] - graph_exception = pynini.union(*labels_exception) - - graph = ( - pynini.cdrewrite(pynutil.delete("and"), NEMO_SPACE, NEMO_SPACE, NEMO_SIGMA) - @ (NEMO_ALPHA + NEMO_SIGMA) - @ graph - ) - - self.graph_no_exception = graph - - self.graph = (pynini.project(graph, "input") - graph_exception.arcsort()) @ graph - - optional_minus_graph = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("minus", "\"-\"") + NEMO_SPACE, 0, 1 - ) - - final_graph = optional_minus_graph + pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/date.py b/nemo_text_processing/inverse_text_normalization/en/taggers/date.py deleted file mode 100644 index 43fe65f3e2e8..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/date.py +++ /dev/null @@ -1,154 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - -graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")).optimize() -graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")).optimize() -ties_graph = pynini.string_file(get_abs_path("data/numbers/ties.tsv")).optimize() - - -def _get_month_graph(): - """ - Transducer for month, e.g. march -> march - """ - month_graph = pynini.string_file(get_abs_path("data/months.tsv")) - return month_graph - - -def _get_ties_graph(): - """ - Transducer for 20-99 e.g - twenty three -> 23 - """ - graph = ties_graph + (delete_space + graph_digit | pynutil.insert("0")) - return graph - - -def _get_range_graph(): - """ - Transducer for decades (1**0s, 2**0s), centuries (2*00s, 1*00s), millennia (2000s) - """ - graph_ties = _get_ties_graph() - graph = (graph_ties | graph_teen) + delete_space + pynini.cross("hundreds", "00s") - graph |= pynini.cross("two", "2") + delete_space + pynini.cross("thousands", "000s") - graph |= ( - (graph_ties | graph_teen) - + delete_space - + (pynini.closure(NEMO_ALPHA, 1) + (pynini.cross("ies", "y") | pynutil.delete("s"))) - @ (graph_ties | pynini.cross("ten", "10")) - + pynutil.insert("s") - ) - graph @= pynini.union("1", "2") + NEMO_DIGIT + NEMO_DIGIT + NEMO_DIGIT + "s" - return graph - - -def _get_year_graph(): - """ - Transducer for year, e.g. twenty twenty -> 2020 - """ - - def _get_digits_graph(): - zero = pynini.cross((pynini.accep("oh") | pynini.accep("o")), "0") - graph = zero + delete_space + graph_digit - graph.optimize() - return graph - - def _get_thousands_graph(): - graph_ties = _get_ties_graph() - graph_hundred_component = (graph_digit + delete_space + pynutil.delete("hundred")) | pynutil.insert("0") - optional_end = pynini.closure(pynutil.delete("and "), 0, 1) - graph = ( - graph_digit - + delete_space - + pynutil.delete("thousand") - + delete_space - + graph_hundred_component - + delete_space - + (graph_teen | graph_ties | (optional_end + pynutil.insert("0") + graph_digit)) - ) - return graph - - graph_ties = _get_ties_graph() - graph_digits = _get_digits_graph() - graph_thousands = _get_thousands_graph() - year_graph = ( - # 20 19, 40 12, 2012 - assuming no limit on the year - (graph_teen + delete_space + (graph_ties | graph_digits | graph_teen)) - | (graph_ties + delete_space + (graph_ties | graph_digits | graph_teen)) - | graph_thousands - ) - year_graph.optimize() - return year_graph - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, - e.g. january fifth twenty twelve -> date { month: "january" day: "5" year: "2012" preserve_order: true } - e.g. the fifth of january twenty twelve -> date { day: "5" month: "january" year: "2012" preserve_order: true } - e.g. twenty twenty -> date { year: "2012" preserve_order: true } - - Args: - ordinal: OrdinalFst - """ - - def __init__(self, ordinal: GraphFst): - super().__init__(name="date", kind="classify") - - ordinal_graph = ordinal.graph - year_graph = _get_year_graph() - YEAR_WEIGHT = 0.001 - year_graph = pynutil.add_weight(year_graph, YEAR_WEIGHT) - month_graph = _get_month_graph() - - month_graph = pynutil.insert("month: \"") + month_graph + pynutil.insert("\"") - - day_graph = pynutil.insert("day: \"") + pynutil.add_weight(ordinal_graph, -0.7) + pynutil.insert("\"") - graph_year = ( - delete_extra_space - + pynutil.insert("year: \"") - + pynutil.add_weight(year_graph, -YEAR_WEIGHT) - + pynutil.insert("\"") - ) - optional_graph_year = pynini.closure(graph_year, 0, 1,) - graph_mdy = month_graph + ( - (delete_extra_space + day_graph) | graph_year | (delete_extra_space + day_graph + graph_year) - ) - graph_dmy = ( - pynutil.delete("the") - + delete_space - + day_graph - + delete_space - + pynutil.delete("of") - + delete_extra_space - + month_graph - + optional_graph_year - ) - graph_year = pynutil.insert("year: \"") + (year_graph | _get_range_graph()) + pynutil.insert("\"") - - final_graph = graph_mdy | graph_dmy | graph_year - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/decimal.py b/nemo_text_processing/inverse_text_normalization/en/taggers/decimal.py deleted file mode 100644 index 0112cdc81b09..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/decimal.py +++ /dev/null @@ -1,94 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -def get_quantity(decimal: 'pynini.FstLike', cardinal_up_to_hundred: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. one million -> integer_part: "1" quantity: "million" - e.g. one point five million -> integer_part: "1" fractional_part: "5" quantity: "million" - - Args: - decimal: decimal FST - cardinal_up_to_hundred: cardinal FST - """ - numbers = cardinal_up_to_hundred @ ( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT) - ) - suffix = pynini.union("million", "billion", "trillion", "quadrillion", "quintillion", "sextillion") - res = ( - pynutil.insert("integer_part: \"") - + numbers - + pynutil.insert("\"") - + delete_extra_space - + pynutil.insert("quantity: \"") - + suffix - + pynutil.insert("\"") - ) - res |= decimal + delete_extra_space + pynutil.insert("quantity: \"") + (suffix | "thousand") + pynutil.insert("\"") - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal - e.g. minus twelve point five o o six billion -> decimal { negative: "true" integer_part: "12" fractional_part: "5006" quantity: "billion" } - e.g. one billion -> decimal { integer_part: "1" quantity: "billion" } - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="decimal", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - - graph_decimal = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_decimal |= pynini.string_file(get_abs_path("data/numbers/zero.tsv")) | pynini.cross("o", "0") - - graph_decimal = pynini.closure(graph_decimal + delete_space) + graph_decimal - self.graph = graph_decimal - - point = pynutil.delete("point") - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("minus", "\"true\"") + delete_extra_space, 0, 1 - ) - - graph_fractional = pynutil.insert("fractional_part: \"") + graph_decimal + pynutil.insert("\"") - graph_integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - final_graph_wo_sign = ( - pynini.closure(graph_integer + delete_extra_space, 0, 1) + point + delete_extra_space + graph_fractional - ) - final_graph = optional_graph_negative + final_graph_wo_sign - - self.final_graph_wo_negative = final_graph_wo_sign | get_quantity( - final_graph_wo_sign, cardinal.graph_hundred_component_at_least_one_none_zero_digit - ) - final_graph |= optional_graph_negative + get_quantity( - final_graph_wo_sign, cardinal.graph_hundred_component_at_least_one_none_zero_digit - ) - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/electronic.py b/nemo_text_processing/inverse_text_normalization/en/taggers/electronic.py deleted file mode 100644 index 5a2ef1a023bc..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/electronic.py +++ /dev/null @@ -1,91 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_ALPHA, GraphFst, insert_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic: as URLs, email addresses, etc. - e.g. c d f one at a b c dot e d u -> tokens { electronic { username: "cdf1" domain: "abc.edu" } } - """ - - def __init__(self): - super().__init__(name="electronic", kind="classify") - - delete_extra_space = pynutil.delete(" ") - alpha_num = ( - NEMO_ALPHA - | pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - ) - - symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")).invert() - - accepted_username = alpha_num | symbols - process_dot = pynini.cross("dot", ".") - username = (alpha_num + pynini.closure(delete_extra_space + accepted_username)) | pynutil.add_weight( - pynini.closure(NEMO_ALPHA, 1), weight=0.0001 - ) - username = pynutil.insert("username: \"") + username + pynutil.insert("\"") - single_alphanum = pynini.closure(alpha_num + delete_extra_space) + alpha_num - server = single_alphanum | pynini.string_file(get_abs_path("data/electronic/server_name.tsv")) - domain = single_alphanum | pynini.string_file(get_abs_path("data/electronic/domain.tsv")) - domain_graph = ( - pynutil.insert("domain: \"") - + server - + delete_extra_space - + process_dot - + delete_extra_space - + domain - + pynutil.insert("\"") - ) - graph = username + delete_extra_space + pynutil.delete("at") + insert_space + delete_extra_space + domain_graph - - ############# url ### - protocol_end = pynini.cross(pynini.union("w w w", "www"), "www") - protocol_start = (pynini.cross("h t t p", "http") | pynini.cross("h t t p s", "https")) + pynini.cross( - " colon slash slash ", "://" - ) - # .com, - ending = ( - delete_extra_space - + symbols - + delete_extra_space - + (domain | pynini.closure(accepted_username + delete_extra_space,) + accepted_username) - ) - - protocol_default = ( - ( - (pynini.closure(delete_extra_space + accepted_username, 1) | server) - | pynutil.add_weight(pynini.closure(NEMO_ALPHA, 1), weight=0.0001) - ) - + pynini.closure(ending, 1) - ).optimize() - protocol = ( - pynini.closure(protocol_start, 0, 1) + protocol_end + delete_extra_space + process_dot + protocol_default - ).optimize() - - protocol |= pynini.closure(protocol_end + delete_extra_space + process_dot, 0, 1) + protocol_default - - protocol = pynutil.insert("protocol: \"") + protocol.optimize() + pynutil.insert("\"") - graph |= protocol - ######## - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/fraction.py b/nemo_text_processing/inverse_text_normalization/en/taggers/fraction.py deleted file mode 100644 index 5e7fd7dad848..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/fraction.py +++ /dev/null @@ -1,26 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst - - -class FractionFst(GraphFst): - """ - Finite state transducer for classifying fraction - """ - - def __init__(self): - super().__init__(name="fraction", kind="classify") - # integer_part # numerator # denominator diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/measure.py b/nemo_text_processing/inverse_text_normalization/en/taggers/measure.py deleted file mode 100644 index c050bc759379..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/measure.py +++ /dev/null @@ -1,97 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, - get_singulars, -) -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure - e.g. minus twelve kilograms -> measure { negative: "true" cardinal { integer: "12" } units: "kg" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="measure", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - - graph_unit = pynini.string_file(get_abs_path("data/measurements.tsv")) - graph_unit_singular = pynini.invert(graph_unit) # singular -> abbr - graph_unit_plural = get_singulars(graph_unit_singular) # plural -> abbr - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("minus", "\"true\"") + delete_extra_space, 0, 1 - ) - - unit_singular = convert_space(graph_unit_singular) - unit_plural = convert_space(graph_unit_plural) - unit_misc = pynutil.insert("/") + pynutil.delete("per") + delete_space + convert_space(graph_unit_singular) - - unit_singular = ( - pynutil.insert("units: \"") - + (unit_singular | unit_misc | pynutil.add_weight(unit_singular + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - unit_plural = ( - pynutil.insert("units: \"") - + (unit_plural | unit_misc | pynutil.add_weight(unit_plural + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - - subgraph_decimal = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + decimal.final_graph_wo_negative - + pynutil.insert(" }") - + delete_extra_space - + unit_plural - ) - subgraph_cardinal = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + ((NEMO_SIGMA - "one") @ cardinal_graph) - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit_plural - ) - subgraph_cardinal |= ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + pynini.cross("one", "1") - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit_singular - ) - final_graph = subgraph_decimal | subgraph_cardinal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/money.py b/nemo_text_processing/inverse_text_normalization/en/taggers/money.py deleted file mode 100644 index c6227b7efd20..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/money.py +++ /dev/null @@ -1,115 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_NOT_SPACE, - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, - get_singulars, - insert_space, -) -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money - e.g. twelve dollars and five cents -> money { integer_part: "12" fractional_part: 05 currency: "$" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="money", kind="classify") - # quantity, integer_part, fractional_part, currency - - cardinal_graph = cardinal.graph_no_exception - # add support for missing hundred (only for 3 digit numbers) - # "one fifty" -> "one hundred fifty" - with_hundred = pynini.compose( - pynini.closure(NEMO_NOT_SPACE) + pynini.accep(" ") + pynutil.insert("hundred ") + NEMO_SIGMA, - pynini.compose(cardinal_graph, NEMO_DIGIT ** 3), - ) - cardinal_graph |= with_hundred - graph_decimal_final = decimal.final_graph_wo_negative - - unit = pynini.string_file(get_abs_path("data/currency.tsv")) - unit_singular = pynini.invert(unit) - unit_plural = get_singulars(unit_singular) - - graph_unit_singular = pynutil.insert("currency: \"") + convert_space(unit_singular) + pynutil.insert("\"") - graph_unit_plural = pynutil.insert("currency: \"") + convert_space(unit_plural) + pynutil.insert("\"") - - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - # twelve dollars (and) fifty cents, zero cents - cents_standalone = ( - pynutil.insert("fractional_part: \"") - + pynini.union( - pynutil.add_weight(((NEMO_SIGMA - "one") @ cardinal_graph), -0.7) @ add_leading_zero_to_double_digit - + delete_space - + pynutil.delete("cents"), - pynini.cross("one", "01") + delete_space + pynutil.delete("cent"), - ) - + pynutil.insert("\"") - ) - - optional_cents_standalone = pynini.closure( - delete_space - + pynini.closure(pynutil.delete("and") + delete_space, 0, 1) - + insert_space - + cents_standalone, - 0, - 1, - ) - # twelve dollars fifty, only after integer - optional_cents_suffix = pynini.closure( - delete_extra_space - + pynutil.insert("fractional_part: \"") - + pynutil.add_weight(cardinal_graph @ add_leading_zero_to_double_digit, -0.7) - + pynutil.insert("\""), - 0, - 1, - ) - - graph_integer = ( - pynutil.insert("integer_part: \"") - + ((NEMO_SIGMA - "one") @ cardinal_graph) - + pynutil.insert("\"") - + delete_extra_space - + graph_unit_plural - + (optional_cents_standalone | optional_cents_suffix) - ) - graph_integer |= ( - pynutil.insert("integer_part: \"") - + pynini.cross("one", "1") - + pynutil.insert("\"") - + delete_extra_space - + graph_unit_singular - + (optional_cents_standalone | optional_cents_suffix) - ) - graph_decimal = graph_decimal_final + delete_extra_space + graph_unit_plural - graph_decimal |= pynutil.insert("currency: \"$\" integer_part: \"0\" ") + cents_standalone - final_graph = graph_integer | graph_decimal - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/ordinal.py b/nemo_text_processing/inverse_text_normalization/en/taggers/ordinal.py deleted file mode 100644 index ea80bc7b512d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/ordinal.py +++ /dev/null @@ -1,44 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal - e.g. thirteenth -> ordinal { integer: "13" } - - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="ordinal", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - graph_digit = pynini.string_file(get_abs_path("data/ordinals/digit.tsv")) - graph_teens = pynini.string_file(get_abs_path("data/ordinals/teen.tsv")) - graph = pynini.closure(NEMO_CHAR) + pynini.union( - graph_digit, graph_teens, pynini.cross("tieth", "ty"), pynini.cross("th", "") - ) - - self.graph = graph @ cardinal_graph - final_graph = pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/punctuation.py b/nemo_text_processing/inverse_text_normalization/en/taggers/punctuation.py deleted file mode 100644 index 10de67cdb08e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/punctuation.py +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class PunctuationFst(GraphFst): - """ - Finite state transducer for classifying punctuation - e.g. a, -> tokens { name: "a" } tokens { name: "," } - """ - - def __init__(self): - super().__init__(name="punctuation", kind="classify") - - s = "!#$%&\'()*+,-./:;<=>?@^_`{|}~" - punct = pynini.union(*s) - - graph = pynutil.insert("name: \"") + punct + pynutil.insert("\"") - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/telephone.py b/nemo_text_processing/inverse_text_normalization/en/taggers/telephone.py deleted file mode 100644 index b230db216250..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/telephone.py +++ /dev/null @@ -1,136 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALNUM, - NEMO_ALPHA, - NEMO_DIGIT, - GraphFst, - insert_space, -) -from pynini.lib import pynutil - - -def get_serial_number(cardinal): - """ - any alphanumerical character sequence with at least one number with length greater equal to 3 - """ - digit = pynini.compose(cardinal.graph_no_exception, NEMO_DIGIT) - character = digit | NEMO_ALPHA - sequence = character + pynini.closure(pynutil.delete(" ") + character, 2) - sequence = sequence @ (pynini.closure(NEMO_ALNUM) + NEMO_DIGIT + pynini.closure(NEMO_ALNUM)) - return sequence.optimize() - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone numbers, e.g. - one two three one two three five six seven eight -> { number_part: "123-123-5678" } - - This class also support card number and IP format. - "one two three dot one double three dot o dot four o" -> { number_part: "123.133.0.40"} - - "three two double seven three two one four three two one four three double zero five" -> - { number_part: 3277 3214 3214 3005} - - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="telephone", kind="classify") - # country code, number_part, extension - digit_to_str = ( - pynini.invert(pynini.string_file(get_abs_path("data/numbers/digit.tsv")).optimize()) - | pynini.cross("0", pynini.union("o", "oh", "zero")).optimize() - ) - - str_to_digit = pynini.invert(digit_to_str) - - double_digit = pynini.union( - *[ - pynini.cross( - pynini.project(str(i) @ digit_to_str, "output") - + pynini.accep(" ") - + pynini.project(str(i) @ digit_to_str, "output"), - pynutil.insert("double ") + pynini.project(str(i) @ digit_to_str, "output"), - ) - for i in range(10) - ] - ) - double_digit.invert() - - # to handle cases like "one twenty three" - two_digit_cardinal = pynini.compose(cardinal.graph_no_exception, NEMO_DIGIT ** 2) - double_digit_to_digit = ( - pynini.compose(double_digit, str_to_digit + pynutil.delete(" ") + str_to_digit) | two_digit_cardinal - ) - - single_or_double_digit = (pynutil.add_weight(double_digit_to_digit, -0.0001) | str_to_digit).optimize() - single_or_double_digit |= ( - single_or_double_digit - + pynini.closure(pynutil.add_weight(pynutil.delete(" ") + single_or_double_digit, 0.0001)) - ).optimize() - - number_part = pynini.compose( - single_or_double_digit, - NEMO_DIGIT ** 3 + pynutil.insert("-") + NEMO_DIGIT ** 3 + pynutil.insert("-") + NEMO_DIGIT ** 4, - ).optimize() - number_part = pynutil.insert("number_part: \"") + number_part.optimize() + pynutil.insert("\"") - - cardinal_option = pynini.compose(single_or_double_digit, NEMO_DIGIT ** (2, 3)) - - country_code = ( - pynutil.insert("country_code: \"") - + pynini.closure(pynini.cross("plus ", "+"), 0, 1) - + ((pynini.closure(str_to_digit + pynutil.delete(" "), 0, 2) + str_to_digit) | cardinal_option) - + pynutil.insert("\"") - ) - - optional_country_code = pynini.closure(country_code + pynutil.delete(" ") + insert_space, 0, 1).optimize() - graph = optional_country_code + number_part - - # credit card number - space_four_digits = insert_space + NEMO_DIGIT ** 4 - credit_card_graph = pynini.compose(single_or_double_digit, NEMO_DIGIT ** 4 + space_four_digits ** 3).optimize() - graph |= pynutil.insert("number_part: \"") + credit_card_graph.optimize() + pynutil.insert("\"") - - # SSN - ssn_graph = pynini.compose( - single_or_double_digit, - NEMO_DIGIT ** 3 + pynutil.insert("-") + NEMO_DIGIT ** 2 + pynutil.insert("-") + NEMO_DIGIT ** 4, - ).optimize() - graph |= pynutil.insert("number_part: \"") + ssn_graph.optimize() + pynutil.insert("\"") - - # ip - digit_or_double = pynini.closure(str_to_digit + pynutil.delete(" "), 0, 1) + double_digit_to_digit - digit_or_double |= double_digit_to_digit + pynini.closure(pynutil.delete(" ") + str_to_digit, 0, 1) - digit_or_double |= str_to_digit + (pynutil.delete(" ") + str_to_digit) ** (0, 2) - digit_or_double |= cardinal_option - digit_or_double = digit_or_double.optimize() - - ip_graph = digit_or_double + (pynini.cross(" dot ", ".") + digit_or_double) ** 3 - - graph |= pynutil.insert("number_part: \"") + ip_graph.optimize() + pynutil.insert("\"") - graph |= ( - pynutil.insert("number_part: \"") - + pynutil.add_weight(get_serial_number(cardinal=cardinal), weight=0.0001) - + pynutil.insert("\"") - ) - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/time.py b/nemo_text_processing/inverse_text_normalization/en/taggers/time.py deleted file mode 100644 index aceb50799239..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/time.py +++ /dev/null @@ -1,143 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.en.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path, num_to_word -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - convert_space, - delete_extra_space, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time - e.g. twelve thirty -> time { hours: "12" minutes: "30" } - e.g. twelve past one -> time { minutes: "12" hours: "1" } - e.g. two o clock a m -> time { hours: "2" suffix: "a.m." } - e.g. quarter to two -> time { hours: "1" minutes: "45" } - e.g. quarter past two -> time { hours: "2" minutes: "15" } - e.g. half past two -> time { hours: "2" minutes: "30" } - """ - - def __init__(self): - super().__init__(name="time", kind="classify") - # hours, minutes, seconds, suffix, zone, style, speak_period - - suffix_graph = pynini.string_file(get_abs_path("data/time/time_suffix.tsv")) - time_zone_graph = pynini.invert(pynini.string_file(get_abs_path("data/time/time_zone.tsv"))) - to_hour_graph = pynini.string_file(get_abs_path("data/time/to_hour.tsv")) - minute_to_graph = pynini.string_file(get_abs_path("data/time/minute_to.tsv")) - - # only used for < 1000 thousand -> 0 weight - cardinal = pynutil.add_weight(CardinalFst().graph_no_exception, weight=-0.7) - - labels_hour = [num_to_word(x) for x in range(0, 24)] - labels_minute_single = [num_to_word(x) for x in range(1, 10)] - labels_minute_double = [num_to_word(x) for x in range(10, 60)] - - graph_hour = pynini.union(*labels_hour) @ cardinal - - graph_minute_single = pynini.union(*labels_minute_single) @ cardinal - graph_minute_double = pynini.union(*labels_minute_double) @ cardinal - graph_minute_verbose = pynini.cross("half", "30") | pynini.cross("quarter", "15") - oclock = pynini.cross(pynini.union("o' clock", "o clock", "o'clock", "oclock"), "") - - final_graph_hour = pynutil.insert("hours: \"") + graph_hour + pynutil.insert("\"") - graph_minute = ( - oclock + pynutil.insert("00") - | pynutil.delete("o") + delete_space + graph_minute_single - | graph_minute_double - ) - final_suffix = pynutil.insert("suffix: \"") + convert_space(suffix_graph) + pynutil.insert("\"") - final_suffix = delete_space + insert_space + final_suffix - final_suffix_optional = pynini.closure(final_suffix, 0, 1) - final_time_zone_optional = pynini.closure( - delete_space - + insert_space - + pynutil.insert("zone: \"") - + convert_space(time_zone_graph) - + pynutil.insert("\""), - 0, - 1, - ) - - # five o' clock - # two o eight, two thirty five (am/pm) - # two pm/am - graph_hm = ( - final_graph_hour + delete_extra_space + pynutil.insert("minutes: \"") + graph_minute + pynutil.insert("\"") - ) - # 10 past four, quarter past four, half past four - graph_m_past_h = ( - pynutil.insert("minutes: \"") - + pynini.union(graph_minute_single, graph_minute_double, graph_minute_verbose) - + pynutil.insert("\"") - + delete_space - + pynutil.delete("past") - + delete_extra_space - + final_graph_hour - ) - - graph_quarter_time = ( - pynutil.insert("minutes: \"") - + pynini.cross("quarter", "45") - + pynutil.insert("\"") - + delete_space - + pynutil.delete(pynini.union("to", "till")) - + delete_extra_space - + pynutil.insert("hours: \"") - + to_hour_graph - + pynutil.insert("\"") - ) - - graph_m_to_h_suffix_time = ( - pynutil.insert("minutes: \"") - + ((graph_minute_single | graph_minute_double).optimize() @ minute_to_graph) - + pynutil.insert("\"") - + pynini.closure(delete_space + pynutil.delete(pynini.union("min", "mins", "minute", "minutes")), 0, 1) - + delete_space - + pynutil.delete(pynini.union("to", "till")) - + delete_extra_space - + pynutil.insert("hours: \"") - + to_hour_graph - + pynutil.insert("\"") - + final_suffix - ) - - graph_h = ( - final_graph_hour - + delete_extra_space - + pynutil.insert("minutes: \"") - + (pynutil.insert("00") | graph_minute) - + pynutil.insert("\"") - + final_suffix - + final_time_zone_optional - ) - final_graph = ( - (graph_hm | graph_m_past_h | graph_quarter_time) + final_suffix_optional + final_time_zone_optional - ) - final_graph |= graph_h - final_graph |= graph_m_to_h_suffix_time - - final_graph = self.add_tokens(final_graph.optimize()) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/tokenize_and_classify.py b/nemo_text_processing/inverse_text_normalization/en/taggers/tokenize_and_classify.py deleted file mode 100644 index 9130ffc9ba08..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,111 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.inverse_text_normalization.en.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.en.taggers.date import DateFst -from nemo_text_processing.inverse_text_normalization.en.taggers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.en.taggers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.en.taggers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.en.taggers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.en.taggers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.inverse_text_normalization.en.taggers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.en.taggers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.en.taggers.whitelist import WhiteListFst -from nemo_text_processing.inverse_text_normalization.en.taggers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="tokenize_and_classify", kind="classify") - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "_en_itn.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars.") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - - ordinal = OrdinalFst(cardinal) - ordinal_graph = ordinal.fst - - decimal = DecimalFst(cardinal) - decimal_graph = decimal.fst - - measure_graph = MeasureFst(cardinal=cardinal, decimal=decimal).fst - date_graph = DateFst(ordinal=ordinal).fst - word_graph = WordFst().fst - time_graph = TimeFst().fst - money_graph = MoneyFst(cardinal=cardinal, decimal=decimal).fst - whitelist_graph = WhiteListFst().fst - punct_graph = PunctuationFst().fst - electronic_graph = ElectronicFst().fst - telephone_graph = TelephoneFst(cardinal).fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.1) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.1) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/whitelist.py b/nemo_text_processing/inverse_text_normalization/en/taggers/whitelist.py deleted file mode 100644 index dced4d4faf62..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/whitelist.py +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelisted tokens - e.g. misses -> tokens { name: "mrs." } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - """ - - def __init__(self): - super().__init__(name="whitelist", kind="classify") - - whitelist = pynini.string_file(get_abs_path("data/whitelist.tsv")).invert() - graph = pynutil.insert("name: \"") + convert_space(whitelist) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/taggers/word.py b/nemo_text_processing/inverse_text_normalization/en/taggers/word.py deleted file mode 100644 index 714e68efeb3d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/taggers/word.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying plain tokens, that do not belong to any special class. This can be considered as the default class. - e.g. sleep -> tokens { name: "sleep" } - """ - - def __init__(self): - super().__init__(name="word", kind="classify") - word = pynutil.insert("name: \"") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert("\"") - self.fst = word.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/utils.py b/nemo_text_processing/inverse_text_normalization/en/utils.py deleted file mode 100644 index 6a8bd48cda5e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/utils.py +++ /dev/null @@ -1,47 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os -from typing import Union - -import inflect - -_inflect = inflect.engine() - - -def num_to_word(x: Union[str, int]): - """ - converts integer to spoken representation - - Args - x: integer - - Returns: spoken representation - """ - if isinstance(x, int): - x = str(x) - x = _inflect.number_to_words(str(x)).replace("-", " ").replace(",", "") - return x - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + '/' + rel_path diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/__init__.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/cardinal.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/cardinal.py deleted file mode 100644 index 8d9c3a621b78..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/cardinal.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinal - e.g. cardinal { integer: "23" negative: "-" } -> -23 - """ - - def __init__(self): - super().__init__(name="cardinal", kind="verbalize") - optional_sign = pynini.closure( - pynutil.delete("negative:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space, - 0, - 1, - ) - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - self.numbers = graph - graph = optional_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/date.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/date.py deleted file mode 100644 index 276223bb5cf4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/date.py +++ /dev/null @@ -1,80 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { month: "january" day: "5" year: "2012" preserve_order: true } -> february 5 2012 - date { day: "5" month: "january" year: "2012" preserve_order: true } -> 5 february 2012 - """ - - def __init__(self): - super().__init__(name="date", kind="verbalize") - month = ( - pynutil.delete("month:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - day = ( - pynutil.delete("day:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - year = ( - pynutil.delete("year:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + delete_space - + pynutil.delete("\"") - ) - - # month (day) year - graph_mdy = ( - month + pynini.closure(delete_extra_space + day, 0, 1) + pynini.closure(delete_extra_space + year, 0, 1) - ) - - # (day) month year - graph_dmy = ( - pynini.closure(day + delete_extra_space, 0, 1) + month + pynini.closure(delete_extra_space + year, 0, 1) - ) - - optional_preserve_order = pynini.closure( - pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - | pynutil.delete("field_order:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space - ) - - final_graph = (graph_mdy | year | graph_dmy) + delete_space + optional_preserve_order - - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/decimal.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/decimal.py deleted file mode 100644 index 41b3a281afd4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/decimal.py +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, e.g. - decimal { negative: "true" integer_part: "12" fractional_part: "5006" quantity: "billion" } -> -12.5006 billion - """ - - def __init__(self): - super().__init__(name="decimal", kind="verbalize") - optionl_sign = pynini.closure(pynini.cross("negative: \"true\"", "-") + delete_space, 0, 1) - integer = ( - pynutil.delete("integer_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_integer = pynini.closure(integer + delete_space, 0, 1) - fractional = ( - pynutil.insert(".") - + pynutil.delete("fractional_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_fractional = pynini.closure(fractional + delete_space, 0, 1) - quantity = ( - pynutil.delete("quantity:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_quantity = pynini.closure(pynutil.insert(" ") + quantity + delete_space, 0, 1) - graph = optional_integer + optional_fractional + optional_quantity - self.numbers = graph - graph = optionl_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/electronic.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/electronic.py deleted file mode 100644 index 4c9951c95360..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/electronic.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. tokens { electronic { username: "cdf1" domain: "abc.edu" } } -> cdf1@abc.edu - """ - - def __init__(self): - super().__init__(name="electronic", kind="verbalize") - user_name = ( - pynutil.delete("username:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - domain = ( - pynutil.delete("domain:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - protocol = ( - pynutil.delete("protocol:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - graph = user_name + delete_space + pynutil.insert("@") + domain - graph |= protocol - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/fraction.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/fraction.py deleted file mode 100644 index ca2bdcee2da5..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/fraction.py +++ /dev/null @@ -1,25 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst - - -class FractionFst(GraphFst): - """ - Finite state transducer for verbalizing fraction, - """ - - def __init__(self): - super().__init__(name="fraction", kind="verbalize") diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/measure.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/measure.py deleted file mode 100644 index c5a7617610c6..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/measure.py +++ /dev/null @@ -1,62 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { negative: "true" cardinal { integer: "12" } units: "kg" } -> -12 kg - - Args: - decimal: DecimalFst - cardinal: CardinalFst - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst): - super().__init__(name="measure", kind="verbalize") - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "-"), 0, 1) - unit = ( - pynutil.delete("units:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - + delete_space - ) - graph_decimal = ( - pynutil.delete("decimal {") - + delete_space - + optional_sign - + delete_space - + decimal.numbers - + delete_space - + pynutil.delete("}") - ) - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + delete_space - + cardinal.numbers - + delete_space - + pynutil.delete("}") - ) - graph = (graph_cardinal | graph_decimal) + delete_space + pynutil.insert(" ") + unit - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/money.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/money.py deleted file mode 100644 index 7218257f7ff7..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/money.py +++ /dev/null @@ -1,41 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { integer_part: "12" fractional_part: "05" currency: "$" } -> $12.05 - - Args: - decimal: DecimalFst - """ - - def __init__(self, decimal: GraphFst): - super().__init__(name="money", kind="verbalize") - unit = ( - pynutil.delete("currency:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = unit + delete_space + decimal.numbers - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/ordinal.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/ordinal.py deleted file mode 100644 index 378939812fc2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/ordinal.py +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinal, e.g. - ordinal { integer: "13" } -> 13th - """ - - def __init__(self): - super().__init__(name="ordinal", kind="verbalize") - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - convert_eleven = pynini.cross("11", "11th") - convert_twelve = pynini.cross("12", "12th") - convert_thirteen = pynini.cross("13", "13th") - convert_one = pynini.cross("1", "1st") - convert_two = pynini.cross("2", "2nd") - convert_three = pynini.cross("3", "3rd") - convert_rest = pynutil.insert("th", weight=0.01) - - suffix = pynini.cdrewrite( - convert_eleven - | convert_twelve - | convert_thirteen - | convert_one - | convert_two - | convert_three - | convert_rest, - "", - "[EOS]", - NEMO_SIGMA, - ) - graph = graph @ suffix - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/telephone.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/telephone.py deleted file mode 100644 index 6c37ba468af6..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/telephone.py +++ /dev/null @@ -1,41 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { number_part: "123-123-5678" } - -> 123-123-5678 - """ - - def __init__(self): - super().__init__(name="telephone", kind="verbalize") - - number_part = pynutil.delete("number_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - optional_country_code = pynini.closure( - pynutil.delete("country_code: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + pynini.accep(" "), - 0, - 1, - ) - delete_tokens = self.delete_tokens(optional_country_code + number_part) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/time.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/time.py deleted file mode 100644 index 5a2c8709345e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/time.py +++ /dev/null @@ -1,81 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - GraphFst, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, e.g. - time { hours: "12" minutes: "30" } -> 12:30 - time { hours: "1" minutes: "12" } -> 01:12 - time { hours: "2" suffix: "a.m." } -> 02:00 a.m. - """ - - def __init__(self): - super().__init__(name="time", kind="verbalize") - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete("\"") - ) - minute = ( - pynutil.delete("minutes:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete("\"") - ) - suffix = ( - delete_space - + insert_space - + pynutil.delete("suffix:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - optional_suffix = pynini.closure(suffix, 0, 1) - zone = ( - delete_space - + insert_space - + pynutil.delete("zone:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - optional_zone = pynini.closure(zone, 0, 1) - graph = ( - hour @ add_leading_zero_to_double_digit - + delete_space - + pynutil.insert(":") - + (minute @ add_leading_zero_to_double_digit) - + optional_suffix - + optional_zone - ) - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/verbalize.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/verbalize.py deleted file mode 100644 index 48d052ea7a62..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/verbalize.py +++ /dev/null @@ -1,62 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.en.verbalizers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.date import DateFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - """ - - def __init__(self): - super().__init__(name="verbalize", kind="verbalize") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - ordinal_graph = OrdinalFst().fst - decimal = DecimalFst() - decimal_graph = decimal.fst - measure_graph = MeasureFst(decimal=decimal, cardinal=cardinal).fst - money_graph = MoneyFst(decimal=decimal).fst - time_graph = TimeFst().fst - date_graph = DateFst().fst - whitelist_graph = WhiteListFst().fst - telephone_graph = TelephoneFst().fst - electronic_graph = ElectronicFst().fst - graph = ( - time_graph - | date_graph - | money_graph - | measure_graph - | ordinal_graph - | decimal_graph - | cardinal_graph - | whitelist_graph - | telephone_graph - | electronic_graph - ) - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/verbalize_final.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/verbalize_final.py deleted file mode 100644 index a8ea187009db..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/verbalize_final.py +++ /dev/null @@ -1,44 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.en.verbalizers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now - """ - - def __init__(self): - super().__init__(name="verbalize_final", kind="verbalize") - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/whitelist.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/whitelist.py deleted file mode 100644 index 67ffe4c76826..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/whitelist.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for verbalizing whitelist - e.g. tokens { name: "mrs." } -> mrs. - """ - - def __init__(self): - super().__init__(name="whitelist", kind="verbalize") - graph = ( - pynutil.delete("name:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = graph @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/en/verbalizers/word.py b/nemo_text_processing/inverse_text_normalization/en/verbalizers/word.py deleted file mode 100644 index 6e94ac8c892c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/en/verbalizers/word.py +++ /dev/null @@ -1,33 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for verbalizing plain tokens - e.g. tokens { name: "sleep" } -> sleep - """ - - def __init__(self): - super().__init__(name="word", kind="verbalize") - chars = pynini.closure(NEMO_CHAR - " ", 1) - char = pynutil.delete("name:") + delete_space + pynutil.delete("\"") + chars + pynutil.delete("\"") - graph = char @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/__init__.py b/nemo_text_processing/inverse_text_normalization/es/__init__.py deleted file mode 100644 index bbc86ae98762..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.es.taggers.tokenize_and_classify import ClassifyFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.verbalize_final import VerbalizeFinalFst diff --git a/nemo_text_processing/inverse_text_normalization/es/data/__init__.py b/nemo_text_processing/inverse_text_normalization/es/data/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/es/data/currency_plural.tsv b/nemo_text_processing/inverse_text_normalization/es/data/currency_plural.tsv deleted file mode 100644 index b222ff77a263..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/currency_plural.tsv +++ /dev/null @@ -1,6 +0,0 @@ -€ euros -US$ dólares estadounidenses -US$ dólares americanos -$ dólares -$ pesos -¥ yenes \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/currency_singular.tsv b/nemo_text_processing/inverse_text_normalization/es/data/currency_singular.tsv deleted file mode 100644 index f3977eaf936a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/currency_singular.tsv +++ /dev/null @@ -1,6 +0,0 @@ -€ euro -US$ dólar estadounidense -US$ dólar americano -$ dólar -$ peso -¥ yen \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/electronic/__init__.py b/nemo_text_processing/inverse_text_normalization/es/data/electronic/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/es/data/electronic/domain.tsv b/nemo_text_processing/inverse_text_normalization/es/data/electronic/domain.tsv deleted file mode 100644 index 8053757321a0..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/electronic/domain.tsv +++ /dev/null @@ -1,25 +0,0 @@ -com -es -uk -fr -net -br -in -ru -de -it -edu -co -ar -bo -cl -co -ec -fk -gf -fy -pe -py -sr -ve -uy \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/electronic/server_name.tsv b/nemo_text_processing/inverse_text_normalization/es/data/electronic/server_name.tsv deleted file mode 100644 index 711073d5d88d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/electronic/server_name.tsv +++ /dev/null @@ -1,17 +0,0 @@ -gmail g mail -gmail -nvidia n vidia -nvidia -outlook -hotmail -yahoo -aol -gmx -msn -live -yandex -orange -wanadoo -web -comcast -bbc \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/electronic/symbols.tsv b/nemo_text_processing/inverse_text_normalization/es/data/electronic/symbols.tsv deleted file mode 100644 index 9835226f9c25..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/electronic/symbols.tsv +++ /dev/null @@ -1,4 +0,0 @@ -. punto -- guion -_ guion bajo -/ barra \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/measurements_plural.tsv b/nemo_text_processing/inverse_text_normalization/es/data/measurements_plural.tsv deleted file mode 100644 index a27d890228a4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/measurements_plural.tsv +++ /dev/null @@ -1,19 +0,0 @@ -cm centímetros -g gramos -h horas -kg kilos -kg kilogramos -km kilómetros -km² kilómetros cuadrados -l litros -m metros -m² metros cuadrados -m³ metros cubicos -mph millas por hora -ml mililitros -mm milímetros -ms milisegundos -min minutos -% por ciento -% porciento -s segundos diff --git a/nemo_text_processing/inverse_text_normalization/es/data/measurements_singular.tsv b/nemo_text_processing/inverse_text_normalization/es/data/measurements_singular.tsv deleted file mode 100644 index 7c892b5d06d4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/measurements_singular.tsv +++ /dev/null @@ -1,19 +0,0 @@ -cm centímetro -g gramo -h hora -kg kilo -kg kilogramo -km kilómetro -km² kilómetro cuadrado -l litro -m metro -m² metro cuadrado -m³ metro cubico -mph milla por hora -ml mililitro -mm milímetro -ms milisegundo -min minuto -% por ciento -% porciento -s segundo diff --git a/nemo_text_processing/inverse_text_normalization/es/data/months.tsv b/nemo_text_processing/inverse_text_normalization/es/data/months.tsv deleted file mode 100644 index 55ada228937a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/months.tsv +++ /dev/null @@ -1,12 +0,0 @@ -enero -febrero -marzo -abril -mayo -junio -julio -agosto -septiembre -octubre -noviembre -diciembre \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/numbers/__init__.py b/nemo_text_processing/inverse_text_normalization/es/data/numbers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/es/data/numbers/digit.tsv b/nemo_text_processing/inverse_text_normalization/es/data/numbers/digit.tsv deleted file mode 100644 index 639fe1c73579..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/numbers/digit.tsv +++ /dev/null @@ -1,12 +0,0 @@ -uno 1 -un 1 -ún 1 -una 1 -dos 2 -tres 3 -cuatro 4 -cinco 5 -seis 6 -siete 7 -ocho 8 -nueve 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/numbers/hundreds.tsv b/nemo_text_processing/inverse_text_normalization/es/data/numbers/hundreds.tsv deleted file mode 100644 index 972e687760b3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/numbers/hundreds.tsv +++ /dev/null @@ -1,18 +0,0 @@ -ciento 1 -cien 1 -doscientos 2 -doscientas 2 -trescientos 3 -trescientas 3 -cuatrocientos 4 -cuatrocientas 4 -quinientos 5 -quinientas 5 -seiscientos 6 -seiscientas 6 -setecientos 7 -setecientas 7 -ochocientos 8 -ochocientas 8 -novecientos 9 -novecientas 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/numbers/teen.tsv b/nemo_text_processing/inverse_text_normalization/es/data/numbers/teen.tsv deleted file mode 100644 index 370526ea57c3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/numbers/teen.tsv +++ /dev/null @@ -1,10 +0,0 @@ -diez 10 -once 11 -doce 12 -trece 13 -catorce 14 -quince 15 -dieciséis 16 -diecisiete 17 -dieciocho 18 -diecinueve 19 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/numbers/ties.tsv b/nemo_text_processing/inverse_text_normalization/es/data/numbers/ties.tsv deleted file mode 100644 index 30f0d43f25ad..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/numbers/ties.tsv +++ /dev/null @@ -1,9 +0,0 @@ -veinte 2 -treinta 3 -cuarenta 4 -cincuenta 5 -cinquenta 5 -sesenta 6 -setenta 7 -ochenta 8 -noventa 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/numbers/twenties.tsv b/nemo_text_processing/inverse_text_normalization/es/data/numbers/twenties.tsv deleted file mode 100644 index e586cfa432a0..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/numbers/twenties.tsv +++ /dev/null @@ -1,14 +0,0 @@ -veintiuno 21 -veintiún 21 -veintiuna 21 -veintidós 22 -veintitrés 23 -veintitres 23 -veinticuatro 24 -veinticuátro 24 -veintiacuátro 24 -veinticinco 25 -veintiséis 26 -veintisiete 27 -veintiocho 28 -veintinueve 29 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/numbers/zero.tsv b/nemo_text_processing/inverse_text_normalization/es/data/numbers/zero.tsv deleted file mode 100644 index 945785283a51..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/numbers/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -cero 0 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/__init__.py b/nemo_text_processing/inverse_text_normalization/es/data/ordinals/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/digit.tsv b/nemo_text_processing/inverse_text_normalization/es/data/ordinals/digit.tsv deleted file mode 100644 index a478659f09aa..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/digit.tsv +++ /dev/null @@ -1,22 +0,0 @@ -primero uno -primera uno -primer uno -segundo dos -segunda dos -tercero tres -tercera tres -tercer tres -cuarto cuatro -cuarta cuatro -quinto cinco -quinta cinco -sexto seis -sexta seis -séptimo siete -séptima siete -sétimo siete -sétima siete -octavo ocho -octava ocho -noveno nueve -novena nueve \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/hundreds.tsv b/nemo_text_processing/inverse_text_normalization/es/data/ordinals/hundreds.tsv deleted file mode 100644 index 488730618f19..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/hundreds.tsv +++ /dev/null @@ -1,18 +0,0 @@ -centésimo ciento -centésima ciento -ducentésimo doscientos -ducentésima doscientos -tricentésimo trescientos -tricentésima trescientos -cuadringentésimo cuatrocientos -cuadringentésima cuatrocientos -quingentésimo quinientos -quingentésima quinientos -sexcentésimo seiscientos -sexcentésima seiscientos -septingentésimo setecientos -septingentésima setecientos -octingentésimo ochocientos -octingentésima ochocientos -noningentésimo novecientos -noningentésima novecientos \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/teen.tsv b/nemo_text_processing/inverse_text_normalization/es/data/ordinals/teen.tsv deleted file mode 100644 index 946398825d24..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/teen.tsv +++ /dev/null @@ -1,55 +0,0 @@ -décimo diez -décima diez -decimoprimero once -decimoprimera once -decimoprimer once -décimo primero once -décima primera once -décimo primera once -décimo primer once -undécimo once -undécima once -decimosegundo doce -decimosegunda doce -décimo segundo doce -décima segunda doce -décimo segunda doce -duodécimo doce -duodécima doce -decimotercero trece -decimotercera trece -decimotercer trece -décimo tercero trece -décima tercera trece -décimo tercera trece -décimo tercer trece -decimocuarto catorce -decimocuarta catorce -décimo cuarto catorce -décima cuarta catorce -décimo cuarta catorce -decimoquinto quince -decimoquinta quince -décimo quinto quince -décima quinta quince -décimo quinta quince -decimosexto dieciséis -decimosexta dieciséis -décimo sexto dieciséis -décima sexta dieciséis -décimo sexta dieciséis -decimoséptimo diecisiete -decimoséptima diecisiete -décimo séptimo diecisiete -décima séptima diecisiete -décimo séptima diecisiete -decimoctavo dieciocho -decimoctava dieciocho -décimo octavo dieciocho -décima octava dieciocho -décimo octava dieciocho -decimonoveno diecinueve -decimonovena diecinueve -décimo noveno diecinueve -décima novena diecinueve -décimo novena diecinueve \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/ties.tsv b/nemo_text_processing/inverse_text_normalization/es/data/ordinals/ties.tsv deleted file mode 100644 index 5c22d5520e3f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/ties.tsv +++ /dev/null @@ -1,15 +0,0 @@ -vigésimo veinte -vigésima veinte -trigésimo treinta -cuadragésimo cuarenta -cuadragésima cuarenta -quincuagésimo cincuenta -quincuagésima cincuenta -sexagésimo sesenta -sexagésima sesenta -septuagésimo setenta -septuagésima setenta -octogésimo ochenta -octogésima ochenta -nonagésimo noventa -nonagésima noventa \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/twenties.tsv b/nemo_text_processing/inverse_text_normalization/es/data/ordinals/twenties.tsv deleted file mode 100644 index 4c1b1770c823..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/ordinals/twenties.tsv +++ /dev/null @@ -1,20 +0,0 @@ -vigesimoprimero veintiuno -vigesimoprimera veintiuno -vigesimoprimer veintiuno -vigésimosegundo veintidós -vigésimosegunda veintidós -vigésimotercero veintitrés -vigésimotercera veintitrés -vigésimotercer veintitrés -vigésimocuarto veinticuatro -vigésimocuarta veinticuatro -vigésimoquinto veinticinco -vigésimoquinta veinticinco -vigésimosexto veintiséis -vigésimosexta veintiséis -vigésimoséptimo veintisiete -vigésimoséptima veintisiete -vigésimooctavo veintiocho -vigésimooctava veintiocho -vigésimonoveno veintinueve -vigésimonovena veintinueve \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/time/__init__.py b/nemo_text_processing/inverse_text_normalization/es/data/time/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/es/data/time/time_suffix.tsv b/nemo_text_processing/inverse_text_normalization/es/data/time/time_suffix.tsv deleted file mode 100644 index 00604d9003ee..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/time/time_suffix.tsv +++ /dev/null @@ -1,12 +0,0 @@ -peme p.m. -pe eme p.m. -p m p.m. -pm p.m. -p.m. -p.m p.m. -ame a.m. -a eme a.m. -am a.m. -a.m. -a.m a.m. -a m a.m. \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/time/time_to.tsv b/nemo_text_processing/inverse_text_normalization/es/data/time/time_to.tsv deleted file mode 100644 index 71d4bcd0802e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/time/time_to.tsv +++ /dev/null @@ -1,24 +0,0 @@ -la una las 12 -las dos la 1 -las tres las 2 -las cuatro las 3 -las cinco las 4 -las seis las 5 -las siete las 6 -las ocho las 7 -las nueve las 8 -las diez las 9 -las once las 10 -las doce las 11 -las trece las 12 -las catorce las 13 -las quince las 14 -las dieciséis las 15 -las diecisiete las 16 -las diecieocho las 17 -las diecinueve las 18 -las veinte las 19 -las veintiuna las 20 -las veintidos las 21 -las veintitres las 22 -las cero las 23 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/es/data/whitelist.tsv b/nemo_text_processing/inverse_text_normalization/es/data/whitelist.tsv deleted file mode 100644 index e1816d9768dd..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/data/whitelist.tsv +++ /dev/null @@ -1,2 +0,0 @@ -ud. usted -uds. ustedes diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/__init__.py b/nemo_text_processing/inverse_text_normalization/es/taggers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/cardinal.py b/nemo_text_processing/inverse_text_normalization/es/taggers/cardinal.py deleted file mode 100644 index 2afce51ef24f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/cardinal.py +++ /dev/null @@ -1,188 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals - e.g. menos veintitrés -> cardinal { negative: "-" integer: "23"} - This class converts cardinals up to (but not including) "un cuatrillón", - i.e up to "one septillion" in English (10^{24}). - Cardinals below ten are not converted (in order to avoid - "vivo en una casa" --> "vivo en 1 casa" and any other odd conversions.) - - Although technically Spanish grammar requires that "y" only comes after - "10s" numbers (ie. "treinta", ..., "noventa"), these rules will convert - numbers even with "y" in an ungrammatical place (because "y" is ignored - inside cardinal numbers). - e.g. "mil y una" -> cardinal { integer: "1001"} - e.g. "ciento y una" -> cardinal { integer: "101"} - """ - - def __init__(self): - super().__init__(name="cardinal", kind="classify") - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - graph_hundreds = pynini.string_file(get_abs_path("data/numbers/hundreds.tsv")) - - graph_hundred_component = graph_hundreds | pynutil.insert("0") - graph_hundred_component += delete_space - graph_hundred_component += pynini.union( - graph_twenties | graph_teen | pynutil.insert("00"), - (graph_ties | pynutil.insert("0")) + delete_space + (graph_digit | pynutil.insert("0")), - ) - - graph_hundred_component_at_least_one_none_zero_digit = graph_hundred_component @ ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT) - ) - self.graph_hundred_component_at_least_one_none_zero_digit = ( - graph_hundred_component_at_least_one_none_zero_digit - ) - - graph_thousands = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("mil"), - pynutil.insert("001") + pynutil.delete("mil"), # because we say 'mil', not 'un mil' - pynutil.insert("000", weight=0.1), - ) - - graph_millones = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("millones") | pynutil.delete("millón")), - pynutil.insert("000") + pynutil.delete("millones"), # to allow for 'mil millones' - ) - - graph_mil_millones = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("mil"), - pynutil.insert("001") + pynutil.delete("mil"), # because we say 'mil', not 'un mil' - ) - graph_mil_millones += delete_space + ( - graph_millones | pynutil.insert("000") + pynutil.delete("millones") - ) # allow for 'mil millones' - graph_mil_millones |= pynutil.insert("000000", weight=0.1) - - # also allow 'millardo' instead of 'mil millones' - graph_millardo = ( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("millardo") | pynutil.delete("millardos")) - ) - - graph_billones = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("billones") | pynutil.delete("billón")), - ) - - graph_mil_billones = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("mil"), - pynutil.insert("001") + pynutil.delete("mil"), # because we say 'mil', not 'un mil' - ) - graph_mil_billones += delete_space + ( - graph_billones | pynutil.insert("000") + pynutil.delete("billones") - ) # allow for 'mil billones' - graph_mil_billones |= pynutil.insert("000000", weight=0.1) - - graph_trillones = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("trillones") | pynutil.delete("trillón")), - ) - - graph_mil_trillones = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("mil"), - pynutil.insert("001") + pynutil.delete("mil"), # because we say 'mil', not 'un mil' - ) - graph_mil_trillones += delete_space + ( - graph_trillones | pynutil.insert("000") + pynutil.delete("trillones") - ) # allow for 'mil trillones' - graph_mil_trillones |= pynutil.insert("000000", weight=0.1) - - graph = pynini.union( - (graph_mil_trillones | pynutil.insert("000", weight=0.1) + graph_trillones) - + delete_space - + (graph_mil_billones | pynutil.insert("000", weight=0.1) + graph_billones) - + delete_space - + pynini.union( - graph_mil_millones, - pynutil.insert("000", weight=0.1) + graph_millones, - graph_millardo + graph_millones, - graph_millardo + pynutil.insert("000", weight=0.1), - ) - + delete_space - + graph_thousands - + delete_space - + graph_hundred_component, - graph_zero, - ) - - graph = graph @ pynini.union( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT), "0" - ) - - # ignore "y" inside cardinal numbers - graph = ( - pynini.cdrewrite(pynutil.delete("y"), NEMO_SPACE, NEMO_SPACE, NEMO_SIGMA) - @ (NEMO_ALPHA + NEMO_SIGMA) - @ graph - ) - - self.graph_no_exception = graph - - # save self.numbers_up_to_thousand for use in DecimalFst - digits_up_to_thousand = NEMO_DIGIT | (NEMO_DIGIT ** 2) | (NEMO_DIGIT ** 3) - numbers_up_to_thousand = pynini.compose(graph, digits_up_to_thousand).optimize() - self.numbers_up_to_thousand = numbers_up_to_thousand - - # save self.numbers_up_to_million for use in DecimalFst - digits_up_to_million = ( - NEMO_DIGIT - | (NEMO_DIGIT ** 2) - | (NEMO_DIGIT ** 3) - | (NEMO_DIGIT ** 4) - | (NEMO_DIGIT ** 5) - | (NEMO_DIGIT ** 6) - ) - numbers_up_to_million = pynini.compose(graph, digits_up_to_million).optimize() - self.numbers_up_to_million = numbers_up_to_million - - # don't convert cardinals from zero to nine inclusive - graph_exception = pynini.project(pynini.union(graph_digit, graph_zero), 'input') - - self.graph = (pynini.project(graph, "input") - graph_exception.arcsort()) @ graph - - optional_minus_graph = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("menos", "\"-\"") + NEMO_SPACE, 0, 1 - ) - - final_graph = optional_minus_graph + pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/date.py b/nemo_text_processing/inverse_text_normalization/es/taggers/date.py deleted file mode 100644 index 4eda33129787..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/date.py +++ /dev/null @@ -1,59 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, - e.g. primero de enero -> date { day: "1" month: "enero" } - e.g. uno de enero -> date { day: "1" month: "enero" } - """ - - def __init__(self): - super().__init__(name="date", kind="classify") - - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - - graph_1_to_100 = pynini.union( - graph_digit, - graph_twenties, - graph_teen, - (graph_ties + pynutil.insert("0")), - (graph_ties + pynutil.delete(" y ") + graph_digit), - ) - - digits_1_to_31 = [str(digits) for digits in range(1, 32)] - graph_1_to_31 = graph_1_to_100 @ pynini.union(*digits_1_to_31) - # can use "primero" for 1st day of the month - graph_1_to_31 = pynini.union(graph_1_to_31, pynini.cross("primero", "1")) - - day_graph = pynutil.insert("day: \"") + graph_1_to_31 + pynutil.insert("\"") - - month_graph = pynini.string_file(get_abs_path("data/months.tsv")) - month_graph = pynutil.insert("month: \"") + month_graph + pynutil.insert("\"") - - graph_dm = day_graph + delete_space + pynutil.delete("de") + delete_extra_space + month_graph - - final_graph = graph_dm - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/decimal.py b/nemo_text_processing/inverse_text_normalization/es/taggers/decimal.py deleted file mode 100644 index bdbf180495de..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/decimal.py +++ /dev/null @@ -1,117 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -def get_quantity(decimal: 'pynini.FstLike', cardinal_up_to_million: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. one million -> integer_part: "1" quantity: "million" - e.g. one point five million -> integer_part: "1" fractional_part: "5" quantity: "million" - - Args: - decimal: decimal FST - cardinal_up_to_million: cardinal FST - """ - numbers = cardinal_up_to_million @ ( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT) - ) - - suffix = pynini.union( - "millón", - "millones", - "millardo", - "millardos", - "billón", - "billones", - "trillón", - "trillones", - "cuatrillón", - "cuatrillones", - ) - res = ( - pynutil.insert("integer_part: \"") - + numbers - + pynutil.insert("\"") - + delete_extra_space - + pynutil.insert("quantity: \"") - + suffix - + pynutil.insert("\"") - ) - res |= decimal + delete_extra_space + pynutil.insert("quantity: \"") + suffix + pynutil.insert("\"") - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal - Decimal point is either "." or ",", determined by whether "punto" or "coma" is spoken. - e.g. menos uno coma dos seis -> decimal { negative: "true" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" } - e.g. menos uno punto dos seis -> decimal { negative: "true" integer_part: "1" morphosyntactic_features: "." fractional_part: "26" } - - This decimal rule assumes that decimals can be pronounced as: - (a cardinal) + ('coma' or 'punto') plus (any sequence of cardinals <1000, including 'zero') - - Also writes large numbers in shortened form, e.g. - e.g. uno coma dos seis millón -> decimal { negative: "false" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" quantity: "millón" } - e.g. dos millones -> decimal { negative: "false" integer_part: "2" quantity: "millones" } - e.g. mil ochocientos veinticuatro millones -> decimal { negative: "false" integer_part: "1824" quantity: "millones" } - Args: - cardinal: CardinalFst - - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="decimal", kind="classify") - - # number after decimal point can be any series of cardinals <1000, including 'zero' - graph_decimal = cardinal.numbers_up_to_thousand - graph_decimal = pynini.closure(graph_decimal + delete_space) + graph_decimal - self.graph = graph_decimal - - # decimal point can be denoted by 'coma' or 'punto' - decimal_point = pynini.cross("coma", "morphosyntactic_features: \",\"") - decimal_point |= pynini.cross("punto", "morphosyntactic_features: \".\"") - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("menos", "\"true\"") + delete_extra_space, 0, 1 - ) - - graph_fractional = pynutil.insert("fractional_part: \"") + graph_decimal + pynutil.insert("\"") - - cardinal_graph = cardinal.graph_no_exception | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - final_graph_wo_sign = ( - pynini.closure(graph_integer + delete_extra_space, 0, 1) - + decimal_point - + delete_extra_space - + graph_fractional - ) - final_graph = optional_graph_negative + final_graph_wo_sign - - self.final_graph_wo_negative = final_graph_wo_sign | get_quantity( - final_graph_wo_sign, cardinal.numbers_up_to_million - ) - final_graph |= optional_graph_negative + get_quantity(final_graph_wo_sign, cardinal.numbers_up_to_million) - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/electronic.py b/nemo_text_processing/inverse_text_normalization/es/taggers/electronic.py deleted file mode 100644 index 53b6b4d090cf..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/electronic.py +++ /dev/null @@ -1,96 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_ALPHA, GraphFst, insert_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying 'electronic' semiotic classes, i.e. - email address (which get converted to "username" and "domain" fields), - and URLS (which get converted to a "protocol" field). - e.g. c d f uno arroba a b c punto e d u -> tokens { electronic { username: "cdf1" domain: "abc.edu" } } - e.g. doble ve doble ve doble ve a b c punto e d u -> tokens { electronic { protocol: "www.abc.edu" } } - """ - - def __init__(self): - super().__init__(name="electronic", kind="classify") - - delete_extra_space = pynutil.delete(" ") - alpha_num = ( - NEMO_ALPHA - | pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - ) - - symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")).invert() - - accepted_username = alpha_num | symbols - process_dot = pynini.cross("punto", ".") - username = ( - pynutil.insert("username: \"") - + alpha_num - + delete_extra_space - + pynini.closure(accepted_username + delete_extra_space) - + alpha_num - + pynutil.insert("\"") - ) - single_alphanum = pynini.closure(alpha_num + delete_extra_space) + alpha_num - server = single_alphanum | pynini.string_file(get_abs_path("data/electronic/server_name.tsv")).invert() - domain = single_alphanum | pynini.string_file(get_abs_path("data/electronic/domain.tsv")).invert() - domain_graph = ( - pynutil.insert("domain: \"") - + server - + delete_extra_space - + process_dot - + delete_extra_space - + domain - + pynutil.insert("\"") - ) - graph = ( - username + delete_extra_space + pynutil.delete("arroba") + insert_space + delete_extra_space + domain_graph - ) - - ############# url ### - protocol_end = pynini.cross(pynini.union("www", "w w w", "doble ve doble ve doble ve"), "www") - protocol_start = pynini.cross(pynini.union("http", "h t t p", "hache te te pe"), "http") - protocol_start |= pynini.cross(pynini.union("https", "h t t p s", "hache te te pe ese"), "https") - protocol_start += pynini.cross(" dos puntos barra barra ", "://") - - # e.g. .com, .es - ending = ( - delete_extra_space - + symbols - + delete_extra_space - + (domain | pynini.closure(accepted_username + delete_extra_space,) + accepted_username) - ) - - protocol = ( - pynini.closure(protocol_start, 0, 1) - + protocol_end - + delete_extra_space - + process_dot - + delete_extra_space - + (pynini.closure(delete_extra_space + accepted_username, 1) | server) - + pynini.closure(ending, 1) - ) - protocol = pynutil.insert("protocol: \"") + protocol + pynutil.insert("\"") - graph |= protocol - ######## - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/measure.py b/nemo_text_processing/inverse_text_normalization/es/taggers/measure.py deleted file mode 100644 index a660da140040..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/measure.py +++ /dev/null @@ -1,96 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure - e.g. menos doce kilogramos -> measure { cardinal { negative: "true" integer: "12" } units: "kg" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="measure", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - - graph_unit_singular = pynini.string_file(get_abs_path("data/measurements_singular.tsv")) - graph_unit_singular = pynini.invert(graph_unit_singular) # singular -> abbr - graph_unit_plural = pynini.string_file(get_abs_path("data/measurements_plural.tsv")) - graph_unit_plural = pynini.invert(graph_unit_plural) # plural -> abbr - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("menos", "\"true\"") + delete_extra_space, 0, 1 - ) - - unit_singular = convert_space(graph_unit_singular) - unit_plural = convert_space(graph_unit_plural) - unit_misc = pynutil.insert("/") + pynutil.delete("por") + delete_space + convert_space(graph_unit_singular) - - unit_singular = ( - pynutil.insert("units: \"") - + (unit_singular | unit_misc | pynutil.add_weight(unit_singular + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - unit_plural = ( - pynutil.insert("units: \"") - + (unit_plural | unit_misc | pynutil.add_weight(unit_plural + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - - subgraph_decimal = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + decimal.final_graph_wo_negative - + pynutil.insert(" }") - + delete_extra_space - + unit_plural - ) - subgraph_cardinal = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + ((NEMO_SIGMA - "un" - "una" - "uno") @ cardinal_graph) - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit_plural - ) - subgraph_cardinal |= ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + (pynini.cross("un", "1") | pynini.cross("una", "1") | pynini.cross("uno", "1")) - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit_singular - ) - final_graph = subgraph_decimal | subgraph_cardinal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/money.py b/nemo_text_processing/inverse_text_normalization/es/taggers/money.py deleted file mode 100644 index 754afdd36b65..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/money.py +++ /dev/null @@ -1,111 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money - e.g. doce dólares y cinco céntimos -> money { integer_part: "12" fractional_part: 05 currency: "$" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="money", kind="classify") - # quantity, integer_part, fractional_part, currency - - cardinal_graph = cardinal.graph_no_exception - graph_decimal_final = decimal.final_graph_wo_negative - - unit_singular = pynini.string_file(get_abs_path("data/currency_singular.tsv")) - unit_singular = pynini.invert(unit_singular) - unit_plural = pynini.string_file(get_abs_path("data/currency_plural.tsv")) - unit_plural = pynini.invert(unit_plural) - - graph_unit_singular = pynutil.insert("currency: \"") + convert_space(unit_singular) + pynutil.insert("\"") - graph_unit_plural = pynutil.insert("currency: \"") + convert_space(unit_plural) + pynutil.insert("\"") - - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - # twelve dollars (and) fifty cents, zero cents - cents_standalone = ( - pynutil.insert("morphosyntactic_features: \",\"") # always use a comma in the decimal - + insert_space - + pynutil.insert("fractional_part: \"") - + pynini.union( - pynutil.add_weight(((NEMO_SIGMA - "un") @ cardinal_graph), -0.7) @ add_leading_zero_to_double_digit - + delete_space - + pynutil.delete(pynini.union("centavos", "céntimos")), - pynini.cross("un", "01") + delete_space + pynutil.delete(pynini.union("centavo", "céntimo")), - ) - + pynutil.insert("\"") - ) - - optional_cents_standalone = pynini.closure( - delete_space - + pynini.closure((pynutil.delete("con") | pynutil.delete('y')) + delete_space, 0, 1) - + insert_space - + cents_standalone, - 0, - 1, - ) - # twelve dollars fifty, only after integer - # setenta y cinco dólares con sesenta y tres~$75,63 - optional_cents_suffix = pynini.closure( - delete_extra_space - + pynutil.insert("morphosyntactic_features: \",\"") # always use a comma in the decimal - + insert_space - + pynutil.insert("fractional_part: \"") - + pynini.closure((pynutil.delete("con") | pynutil.delete('y')) + delete_space, 0, 1) - + pynutil.add_weight(cardinal_graph @ add_leading_zero_to_double_digit, -0.7) - + pynutil.insert("\""), - 0, - 1, - ) - - graph_integer = ( - pynutil.insert("integer_part: \"") - + ((NEMO_SIGMA - "un" - "una") @ cardinal_graph) - + pynutil.insert("\"") - + delete_extra_space - + graph_unit_plural - + (optional_cents_standalone | optional_cents_suffix) - ) - graph_integer |= ( - pynutil.insert("integer_part: \"") - + (pynini.cross("un", "1") | pynini.cross("una", "1")) - + pynutil.insert("\"") - + delete_extra_space - + graph_unit_singular - + (optional_cents_standalone | optional_cents_suffix) - ) - graph_decimal = graph_decimal_final + delete_extra_space + graph_unit_plural - graph_decimal |= pynutil.insert("currency: \"$\" integer_part: \"0\" ") + cents_standalone - final_graph = graph_integer | graph_decimal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/ordinal.py b/nemo_text_processing/inverse_text_normalization/es/taggers/ordinal.py deleted file mode 100644 index fdb04a504bfa..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/ordinal.py +++ /dev/null @@ -1,91 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal - vigésimo primero -> ordinal { integer: "21" morphosyntactic_features: "o" } - This class converts ordinal up to "millesímo" (one thousandth) exclusive. - - Cardinals below ten are not converted (in order to avoid - e.g. "primero hice ..." -> "1.º hice...", "segunda guerra mundial" -> "2.ª guerra mundial" - and any other odd conversions.) - - This FST also records the ending of the ordinal (called "morphosyntactic_features"): - either "o", "a", or "er". - - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="ordinal", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - graph_digit = pynini.string_file(get_abs_path("data/ordinals/digit.tsv")) - graph_teens = pynini.string_file(get_abs_path("data/ordinals/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/ordinals/twenties.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/ordinals/ties.tsv")) - graph_hundreds = pynini.string_file(get_abs_path("data/ordinals/hundreds.tsv")) - - ordinal_graph_union = pynini.union(graph_digit, graph_teens, graph_twenties, graph_ties, graph_hundreds,) - - accept_o_endings = NEMO_SIGMA + pynini.accep("o") - accept_a_endings = NEMO_SIGMA + pynini.accep("a") - accept_er_endings = NEMO_SIGMA.closure() + pynini.accep("er") - - ordinal_graph_o = accept_o_endings @ ordinal_graph_union - ordinal_graph_a = accept_a_endings @ ordinal_graph_union - ordinal_graph_er = accept_er_endings @ ordinal_graph_union - - # 'optional_numbers_in_front' have negative weight so we always - # include them if they're there - optional_numbers_in_front = (pynutil.add_weight(ordinal_graph_union, -0.1) + delete_space.closure()).closure() - graph_o_suffix = (optional_numbers_in_front + ordinal_graph_o) @ cardinal_graph - graph_a_suffix = (optional_numbers_in_front + ordinal_graph_a) @ cardinal_graph - graph_er_suffix = (optional_numbers_in_front + ordinal_graph_er) @ cardinal_graph - - # don't convert ordinals from one to nine inclusive - graph_exception = pynini.project(pynini.union(graph_digit), 'input') - graph_o_suffix = (pynini.project(graph_o_suffix, "input") - graph_exception.arcsort()) @ graph_o_suffix - graph_a_suffix = (pynini.project(graph_a_suffix, "input") - graph_exception.arcsort()) @ graph_a_suffix - graph_er_suffix = (pynini.project(graph_er_suffix, "input") - graph_exception.arcsort()) @ graph_er_suffix - - graph = ( - pynutil.insert("integer: \"") - + graph_o_suffix - + pynutil.insert("\"") - + pynutil.insert(" morphosyntactic_features: \"o\"") - ) - graph |= ( - pynutil.insert("integer: \"") - + graph_a_suffix - + pynutil.insert("\"") - + pynutil.insert(" morphosyntactic_features: \"a\"") - ) - graph |= ( - pynutil.insert("integer: \"") - + graph_er_suffix - + pynutil.insert("\"") - + pynutil.insert(" morphosyntactic_features: \"er\"") - ) - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/punctuation.py b/nemo_text_processing/inverse_text_normalization/es/taggers/punctuation.py deleted file mode 100644 index 12405d5c5cb2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/punctuation.py +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class PunctuationFst(GraphFst): - """ - Finite state transducer for classifying punctuation - e.g. a, -> tokens { name: "a" } tokens { name: "," } - """ - - def __init__(self): - super().__init__(name="punctuation", kind="classify") - - s = "!#$%&\'()*+,-./:;<=>?@^_`{|}~" - punct = pynini.union(*s) - - graph = pynutil.insert("name: \"") + punct + pynutil.insert("\"") - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/telephone.py b/nemo_text_processing/inverse_text_normalization/es/taggers/telephone.py deleted file mode 100644 index 0e3a47c903b9..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/telephone.py +++ /dev/null @@ -1,138 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone numbers, e.g. - uno dos tres uno dos tres cinco seis siete ocho -> { number_part: "123-123-5678" }. - If 10 digits are spoken, they are grouped as 3+3+4 (eg. 123-456-7890). - If 9 digits are spoken, they are grouped as 3+3+3 (eg. 123-456-789). - If 8 digits are spoken, they are grouped as 4+4 (eg. 1234-5678). - In Spanish, digits are generally spoken individually, or as 2-digit numbers, - eg. "one twenty three" = "123", - "twelve thirty four" = "1234". - - (we ignore more complicated cases such as "three hundred and two" or "three nines"). - """ - - def __init__(self): - super().__init__(name="telephone", kind="classify") - - # create `single_digits` and `double_digits` graphs as these will be - # the building blocks of possible telephone numbers - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - - single_digits = pynini.invert(graph_digit).optimize() | pynini.cross("0", "cero") - - double_digits = pynini.union( - graph_twenties, - graph_teen, - (graph_ties + pynutil.insert("0")), - (graph_ties + delete_space + pynutil.delete("y") + delete_space + graph_digit), - ).invert() - - # define `ten_digit_graph`, `nine_digit_graph`, `eight_digit_graph` - # which accept telephone numbers spoken (1) only with single digits, - # or (2) spoken with double digits (and sometimes single digits) - - # 10-digit option (1): all single digits - ten_digit_graph = ( - pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + single_digits - ) - - # 10-digit option (2): (1+2) + (1+2) + (2+2) digits - ten_digit_graph |= ( - single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - # 9-digit option (1): all single digits - nine_digit_graph = ( - pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 2, 2) - + single_digits - ) - - # 9-digit option (2): (1+2) + (1+2) + (1+2) digits - nine_digit_graph |= ( - single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + single_digits - + insert_space - + double_digits - ) - - # 8-digit option (1): all single digits - eight_digit_graph = ( - pynini.closure(single_digits + insert_space, 4, 4) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + single_digits - ) - - # 8-digit option (2): (2+2) + (2+2) digits - eight_digit_graph |= ( - double_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - number_part = pynini.union(ten_digit_graph, nine_digit_graph, eight_digit_graph,) - - number_part = pynutil.insert("number_part: \"") + pynini.invert(number_part) + pynutil.insert("\"") - - graph = number_part - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/time.py b/nemo_text_processing/inverse_text_normalization/es/taggers/time.py deleted file mode 100644 index 2eb8b4f681bf..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/time.py +++ /dev/null @@ -1,143 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - convert_space, - delete_extra_space, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time - Time formats that it converts: - - + - e.g. la una diez -> time { hours: "la 1" minutes: "10" } - - + " y " + - e.g. la una y diez -> time { hours: "la 1" minutes: "10" } - - + " con " + - e.g. la una con diez -> time { hours: "la 1" minutes: "10" } - - + " menos " + - e.g. las dos menos cuarto -> time { hours: "la 1" minutes: "45" } - - "(un) cuarto para " + - e.g. cuarto para las dos -> time { minutes: "45" hours: "la 1" } - - Note that times on the hour (e.g. "las dos" i.e. "two o'clock") do not get - converted into a time format. This is to avoid converting phrases that are - not part of a time phrase (e.g. "las dos personas" i.e. "the two people") - e.g. las dos -> tokens { name: "las" } tokens { name: "dos" } - However, if a time on the hour is followed by a suffix (indicating 'a.m.' - or 'p.m.'), it will be converted. - e.g. las dos pe eme -> time { hours: "las 2" minutes: "00" suffix: "p.m." } - - Note that although the TimeFst verbalizer can accept 'zone' (timezone) fields, - so far the rules have not been added to the TimeFst tagger to process - timezones (to keep the rules simple, and because timezones are not very - often specified in Spanish.) - """ - - def __init__(self): - super().__init__(name="time", kind="classify") - - suffix_graph = pynini.string_file(get_abs_path("data/time/time_suffix.tsv")) - time_to_graph = pynini.string_file(get_abs_path("data/time/time_to.tsv")) - - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - - graph_1_to_100 = pynini.union( - graph_digit, - graph_twenties, - graph_teen, - (graph_ties + pynutil.insert("0")), - (graph_ties + pynutil.delete(" y ") + graph_digit), - ) - - # note that graph_hour will start from 2 hours - # "1 o'clock" will be treated differently because it - # is singular - digits_2_to_23 = [str(digits) for digits in range(2, 24)] - digits_1_to_59 = [str(digits) for digits in range(1, 60)] - - graph_1oclock = pynini.cross("la una", "la 1") - graph_hour = pynini.cross("las ", "las ") + graph_1_to_100 @ pynini.union(*digits_2_to_23) - graph_minute = graph_1_to_100 @ pynini.union(*digits_1_to_59) - graph_minute_verbose = pynini.cross("media", "30") | pynini.cross("cuarto", "15") - - final_graph_hour = pynutil.insert("hours: \"") + (graph_1oclock | graph_hour) + pynutil.insert("\"") - - final_graph_minute = ( - pynutil.insert("minutes: \"") - + pynini.closure((pynutil.delete("y") | pynutil.delete("con")) + delete_space, 0, 1) - + (graph_minute | graph_minute_verbose) - + pynutil.insert("\"") - ) - - final_suffix = pynutil.insert("suffix: \"") + convert_space(suffix_graph) + pynutil.insert("\"") - final_suffix_optional = pynini.closure(delete_space + insert_space + final_suffix, 0, 1) - - # las nueve a eme (only convert on-the-hour times if they are followed by a suffix) - graph_hsuffix = ( - final_graph_hour + delete_extra_space + pynutil.insert("minutes: \"00\"") + insert_space + final_suffix - ) - - # las nueve y veinticinco - graph_hm = final_graph_hour + delete_extra_space + final_graph_minute - - # un cuarto para las cinco - graph_mh = ( - pynutil.insert("minutes: \"") - + pynini.union(pynini.cross("un cuarto para", "45"), pynini.cross("cuarto para", "45"),) - + pynutil.insert("\"") - + delete_extra_space - + pynutil.insert("hours: \"") - + time_to_graph - + pynutil.insert("\"") - ) - - # las diez menos diez - graph_time_to = ( - pynutil.insert("hours: \"") - + time_to_graph - + pynutil.insert("\"") - + delete_extra_space - + pynutil.insert("minutes: \"") - + delete_space - + pynutil.delete("menos") - + delete_space - + pynini.union( - pynini.cross("cinco", "55"), - pynini.cross("diez", "50"), - pynini.cross("cuarto", "45"), - pynini.cross("veinte", "40"), - pynini.cross("veinticinco", "30"), - ) - + pynutil.insert("\"") - ) - final_graph = pynini.union( - (graph_hm | graph_mh | graph_time_to) + final_suffix_optional, graph_hsuffix - ).optimize() - - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/tokenize_and_classify.py b/nemo_text_processing/inverse_text_normalization/es/taggers/tokenize_and_classify.py deleted file mode 100644 index 730fe023653c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,111 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.inverse_text_normalization.es.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.es.taggers.date import DateFst -from nemo_text_processing.inverse_text_normalization.es.taggers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.es.taggers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.es.taggers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.es.taggers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.es.taggers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.es.taggers.punctuation import PunctuationFst -from nemo_text_processing.inverse_text_normalization.es.taggers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.es.taggers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.es.taggers.whitelist import WhiteListFst -from nemo_text_processing.inverse_text_normalization.es.taggers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="tokenize_and_classify", kind="classify") - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "_es_itn.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars.") - - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - - ordinal = OrdinalFst(cardinal) - ordinal_graph = ordinal.fst - - decimal = DecimalFst(cardinal) - decimal_graph = decimal.fst - - measure_graph = MeasureFst(cardinal=cardinal, decimal=decimal).fst - date_graph = DateFst().fst - word_graph = WordFst().fst - time_graph = TimeFst().fst - money_graph = MoneyFst(cardinal=cardinal, decimal=decimal).fst - whitelist_graph = WhiteListFst().fst - punct_graph = PunctuationFst().fst - electronic_graph = ElectronicFst().fst - telephone_graph = TelephoneFst().fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.1) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.09) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/whitelist.py b/nemo_text_processing/inverse_text_normalization/es/taggers/whitelist.py deleted file mode 100644 index 4cad1d70ee9d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/whitelist.py +++ /dev/null @@ -1,33 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelisted tokens - e.g. usted -> tokens { name: "ud." } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - """ - - def __init__(self): - super().__init__(name="whitelist", kind="classify") - - whitelist = pynini.string_file(get_abs_path("data/whitelist.tsv")).invert() - graph = pynutil.insert("name: \"") + convert_space(whitelist) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/taggers/word.py b/nemo_text_processing/inverse_text_normalization/es/taggers/word.py deleted file mode 100644 index 57f143d0d458..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/taggers/word.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying plain tokens, that do not belong to any special class. This can be considered as the default class. - e.g. sleep -> tokens { name: "sleep" } - """ - - def __init__(self): - super().__init__(name="word", kind="classify") - word = pynutil.insert("name: \"") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert("\"") - self.fst = word.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/utils.py b/nemo_text_processing/inverse_text_normalization/es/utils.py deleted file mode 100644 index f6e06f793c07..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/utils.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + '/' + rel_path diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/__init__.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/cardinal.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/cardinal.py deleted file mode 100644 index e6737be6e864..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/cardinal.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinal - e.g. cardinal { negative: "-" integer: "23" } -> -23 - """ - - def __init__(self): - super().__init__(name="cardinal", kind="verbalize") - optional_sign = pynini.closure( - pynutil.delete("negative:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space, - 0, - 1, - ) - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - self.numbers = graph - graph = optional_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/date.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/date.py deleted file mode 100644 index a6e9df0d26c6..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/date.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_extra_space, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { day: "1" month: "enero" preserve_order: true } -> 1 de enero - """ - - def __init__(self): - super().__init__(name="date", kind="verbalize") - month = ( - pynutil.delete("month:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - day = ( - pynutil.delete("day:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - # day month - graph_dm = day + delete_extra_space + pynutil.insert("de") + insert_space + month - - optional_preserve_order = pynini.closure( - pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - | pynutil.delete("field_order:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space - ) - - final_graph = graph_dm + delete_space + optional_preserve_order - - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/decimal.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/decimal.py deleted file mode 100644 index b443733a2f5e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/decimal.py +++ /dev/null @@ -1,66 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, - e.g. decimal { negative: "true" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" } -> -1,26 - e.g. decimal { negative: "true" integer_part: "1" morphosyntactic_features: "." fractional_part: "26" } -> -1.26 - e.g. decimal { negative: "false" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" quantity: "millón" } -> 1,26 millón - e.g. decimal { negative: "false" integer_part: "2" quantity: "millones" } -> 2 millones - """ - - def __init__(self): - super().__init__(name="decimal", kind="verbalize") - optionl_sign = pynini.closure(pynini.cross("negative: \"true\"", "-") + delete_space, 0, 1) - integer = ( - pynutil.delete("integer_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_integer = pynini.closure(integer + delete_space, 0, 1) - - decimal_point = pynini.cross("morphosyntactic_features: \",\"", ",") - decimal_point |= pynini.cross("morphosyntactic_features: \".\"", ".") - - fractional = ( - decimal_point - + delete_space - + pynutil.delete("fractional_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_fractional = pynini.closure(fractional + delete_space, 0, 1) - quantity = ( - pynutil.delete("quantity:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_quantity = pynini.closure(pynutil.insert(" ") + quantity + delete_space, 0, 1) - graph = optional_integer + optional_fractional + optional_quantity - self.numbers = graph - graph = optionl_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/electronic.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/electronic.py deleted file mode 100644 index cf6bdc779f0e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/electronic.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. tokens { electronic { username: "cdf1" domain: "abc.edu" } } -> cdf1@abc.edu - e.g. tokens { electronic { protocol: "www.abc.edu" } } -> www.abc.edu - """ - - def __init__(self): - super().__init__(name="electronic", kind="verbalize") - user_name = ( - pynutil.delete("username:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - domain = ( - pynutil.delete("domain:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - protocol = ( - pynutil.delete("protocol:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - graph = user_name + delete_space + pynutil.insert("@") + domain - graph |= protocol - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/measure.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/measure.py deleted file mode 100644 index c25a3fd9e3ae..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/measure.py +++ /dev/null @@ -1,61 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { cardinal { negative: "true" integer: "12" } units: "kg" } -> -12 kg - - Args: - decimal: DecimalFst - cardinal: CardinalFst - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst): - super().__init__(name="measure", kind="verbalize") - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "-"), 0, 1) - unit = ( - pynutil.delete("units:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - + delete_space - ) - graph_decimal = ( - pynutil.delete("decimal {") - + delete_space - + optional_sign - + delete_space - + decimal.numbers - + delete_space - + pynutil.delete("}") - ) - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + delete_space - + cardinal.numbers - + delete_space - + pynutil.delete("}") - ) - graph = (graph_cardinal | graph_decimal) + delete_space + pynutil.insert(" ") + unit - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/money.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/money.py deleted file mode 100644 index a52371f1e756..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/money.py +++ /dev/null @@ -1,40 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { integer_part: "12" morphosyntactic_features: "," fractional_part: "05" currency: "$" } -> $12,05 - - Args: - decimal: DecimalFst - """ - - def __init__(self, decimal: GraphFst): - super().__init__(name="money", kind="verbalize") - unit = ( - pynutil.delete("currency:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = unit + delete_space + decimal.numbers - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/ordinal.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/ordinal.py deleted file mode 100644 index 8cfb15095367..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/ordinal.py +++ /dev/null @@ -1,45 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinal, e.g. - ordinal { integer: "13" morphosyntactic_features: "o" } -> 13.º - """ - - def __init__(self): - super().__init__(name="ordinal", kind="verbalize") - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - replace_suffix = pynini.union( - pynini.cross(" morphosyntactic_features: \"o\"", ".º"), - pynini.cross(" morphosyntactic_features: \"a\"", ".ª"), - pynini.cross(" morphosyntactic_features: \"er\"", ".ᵉʳ"), - ) - - graph = graph + replace_suffix - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/telephone.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/telephone.py deleted file mode 100644 index bc32f62fe474..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/telephone.py +++ /dev/null @@ -1,32 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { number_part: "123-123-5678" } - -> 123-123-5678 - """ - - def __init__(self): - super().__init__(name="telephone", kind="verbalize") - - number_part = pynutil.delete("number_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(number_part) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/time.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/time.py deleted file mode 100644 index 1cb725099891..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/time.py +++ /dev/null @@ -1,82 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - GraphFst, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, - e.g. time { hours: "la 1" minutes: "10" } -> la 1:10 - e.g. time { hours: "la 1" minutes: "45" } -> la 1:45 - """ - - def __init__(self): - super().__init__(name="time", kind="verbalize") - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - - # hour includes preposition ("la" or "las") - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete("\"") - + pynini.union("la ", "las ") - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete("\"") - ) - minute = ( - pynutil.delete("minutes:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete("\"") - ) - suffix = ( - delete_space - + insert_space - + pynutil.delete("suffix:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - optional_suffix = pynini.closure(suffix, 0, 1) - zone = ( - delete_space - + insert_space - + pynutil.delete("zone:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - optional_zone = pynini.closure(zone, 0, 1) - graph = ( - hour - + delete_space - + pynutil.insert(":") - + (minute @ add_leading_zero_to_double_digit) - + optional_suffix - + optional_zone - ) - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/verbalize.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/verbalize.py deleted file mode 100644 index 4cbb140a7179..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/verbalize.py +++ /dev/null @@ -1,62 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.es.verbalizers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.date import DateFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - """ - - def __init__(self): - super().__init__(name="verbalize", kind="verbalize") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - ordinal_graph = OrdinalFst().fst - decimal = DecimalFst() - decimal_graph = decimal.fst - measure_graph = MeasureFst(decimal=decimal, cardinal=cardinal).fst - money_graph = MoneyFst(decimal=decimal).fst - time_graph = TimeFst().fst - date_graph = DateFst().fst - whitelist_graph = WhiteListFst().fst - telephone_graph = TelephoneFst().fst - electronic_graph = ElectronicFst().fst - - graph = ( - time_graph - | date_graph - | money_graph - | measure_graph - | ordinal_graph - | decimal_graph - | cardinal_graph - | whitelist_graph - | telephone_graph - | electronic_graph - ) - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/verbalize_final.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/verbalize_final.py deleted file mode 100644 index 26d09996b67d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/verbalize_final.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.es.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.es.verbalizers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now - """ - - def __init__(self): - super().__init__(name="verbalize_final", kind="verbalize") - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/whitelist.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/whitelist.py deleted file mode 100644 index cc231a46b655..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/whitelist.py +++ /dev/null @@ -1,37 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for verbalizing whitelist - e.g. tokens { name: "uds." } -> uds. - """ - - def __init__(self): - super().__init__(name="whitelist", kind="verbalize") - graph = ( - pynutil.delete("name:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = graph @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/es/verbalizers/word.py b/nemo_text_processing/inverse_text_normalization/es/verbalizers/word.py deleted file mode 100644 index 3a5ba96b95d5..000000000000 --- a/nemo_text_processing/inverse_text_normalization/es/verbalizers/word.py +++ /dev/null @@ -1,32 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for verbalizing plain tokens - e.g. tokens { name: "sleep" } -> sleep - """ - - def __init__(self): - super().__init__(name="word", kind="verbalize") - chars = pynini.closure(NEMO_CHAR - " ", 1) - char = pynutil.delete("name:") + delete_space + pynutil.delete("\"") + chars + pynutil.delete("\"") - graph = char @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/README.md b/nemo_text_processing/inverse_text_normalization/fr/README.md deleted file mode 100644 index 049f7182c9af..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/README.md +++ /dev/null @@ -1,30 +0,0 @@ -# Note on French spelling - -Due to a 1990 orthographic reform, there are currently two conventions for written French numbers: - -1. **Reformed** All composite words are joined by a hyphen: -e.g. `1122 -> mille-cent-vingt-deux` - -2. **Traditional** Hyphenation only occurs (with exception) for numbers from 17 to 99 (inclusive): -e.g. `1122 -> mille cent vingt-deux` - -As available training data for upstream ASR will vary in use of convention, NeMo's French ITN accomodates either style for normalization e.g. - -``` - python inverse_normalize.py "mille-cent-vingt-deux" --language="fr" --> 1122 - python inverse_normalize.py "mille cent vingt-deux" --language="fr" --> 1122 -``` - -As a result, there exists some ambiguity in the case of currency conversions, namely minor denominations of the dollar e.g. - -``` - 300 -> "trois-cents" # Reformed spelling - 300 -> "trois cents" # Traditional spelling - 3 ¢ -> "trois cents" # Valid for both -``` - -Cardinals take priority in such cases. - -``` -python inverse_normalize.py "trois cents" --language="fr" -> 300 -``` diff --git a/nemo_text_processing/inverse_text_normalization/fr/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/__init__.py deleted file mode 100644 index 37e27e0e968c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.fr.taggers.tokenize_and_classify import ClassifyFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.verbalize_final import VerbalizeFinalFst diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/electronic/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/domain.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/electronic/domain.tsv deleted file mode 100644 index 8053757321a0..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/domain.tsv +++ /dev/null @@ -1,25 +0,0 @@ -com -es -uk -fr -net -br -in -ru -de -it -edu -co -ar -bo -cl -co -ec -fk -gf -fy -pe -py -sr -ve -uy \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/server_name.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/electronic/server_name.tsv deleted file mode 100644 index cf6bbf44d524..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/server_name.tsv +++ /dev/null @@ -1,17 +0,0 @@ -g mail gmail -gmail -n vidia nvidia -nvidia -outlook -hotmail -yahoo -aol -gmx -msn -live -yandex -orange -wanadoo -web -google -comcast \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/symbols.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/electronic/symbols.tsv deleted file mode 100644 index 198f13c3ca8e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/electronic/symbols.tsv +++ /dev/null @@ -1,12 +0,0 @@ -chez @ -at @ -à @ -arobase @ -point . -barre oblique / -tiret - -tiret bas _ -souligné _ -sous-tiret _ -blanc souligné _ -underscore _ \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/fractions.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/fractions.tsv deleted file mode 100644 index 5f18ea20aad0..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/fractions.tsv +++ /dev/null @@ -1,41 +0,0 @@ -demie deux -demies deux -demi deux -demis deux -tiers trois -quart quatre -quarts quatre -quatrièmes quatre -quatrième quatre -cinquième cinq -cinquièmes cinq -neuvième neuf -neuvièmes neuf -onzième onze -onzièmes onze -douzième douze -douzièmes douze -treizième treize -treizièmes treize -quatorzième quatorze -quatorzièmes quatorze -quinzième quinze -quinzièmes quinze -seizième seize -seizièmes seize -trentième trente -trentièmes trente -quarantième quarante -quarantièmes quarante -cinquantième cinquante -cinquantièmes cinquante -soixantième soixante -soixantièmes soixante -septantième septante -septantièmes septante -huitantième huitante -huitantièmes huitante -nonantième nonante -nonantièmes nonante -millième mille -millièmes mille \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/measurements/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/measurements/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/measurements/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/measurements/magnitudes.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/measurements/magnitudes.tsv deleted file mode 100644 index ded57b90a31d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/measurements/magnitudes.tsv +++ /dev/null @@ -1,16 +0,0 @@ -exa E -péta P -téra T -giga G -méga M -kilo k -hecto h -déca da -déci d -centi c -milli m -micro µ -nano n -pico p -femto f -atto a \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/measurements/measurements.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/measurements/measurements.tsv deleted file mode 100644 index 91ca880c4aef..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/measurements/measurements.tsv +++ /dev/null @@ -1,27 +0,0 @@ -mètre m -mètre carré m² -mètres carrés m² -mètre cube m³ -mètres cubes m³ -seconde s -minute min -heure h -degré ° -degrés ° -degré celsius °C -degrés celsius °C -gramme g -litre l -kilo kg -pouce '' -livre lb -poid lb -mile ml -pour cent % -pour mille ‰ -mètre heure km/h -mètres heure m/h -mètre à l’heure m/h -mètres à l’heure m/h -mètre par l’heure m/h -mètres par l’heure m/h \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/money/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/money/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/money/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/money/currency_major.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/money/currency_major.tsv deleted file mode 100644 index 3f9e1cec2c3d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/money/currency_major.tsv +++ /dev/null @@ -1,40 +0,0 @@ -dollar $ -dollars $ -dollar américain $ US -dollars américains $ US -dollar des États-Unis $ US -dollars des États-Unis $ US -dollar canadien $ CA -dollars canadiens $ CA -dollar australien $ AU -dollars australien $ AU -dollar néo-zélandais $ NZ -dollars néo-zélandais $ NZ -dollar de Hong Kong $ HK -dollars de Hong Kong $ HK -euro € -euros € -livre sterling £ -livre £ -livres £ -livre britannique £ -livres britanniques £ -sterling £ -won ₩ -won sud-coréen ₩ -yen japonais ¥ -yens japonais ¥ -yen ¥ -yens ¥ -yuan ¥ -yuans ¥ -franc CHF -franc suisse CHF -dinar algérien DA -dinars algériens DA -dinar DA -dinars DA -dirham marocain DH -dirhams marocains DH -dirham DH -dirhams DH \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/money/currency_minor.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/money/currency_minor.tsv deleted file mode 100644 index f5622c2d23b0..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/money/currency_minor.tsv +++ /dev/null @@ -1,5 +0,0 @@ -centime € -centimes € -eurocent € -eurocents € -pence £ \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/months.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/months.tsv deleted file mode 100644 index 5051c6835098..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/months.tsv +++ /dev/null @@ -1,12 +0,0 @@ -janvier -février -mars -avril -mai -juin -juillet -août -septembre -octobre -novembre -décembre \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/digit.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/digit.tsv deleted file mode 100644 index 1cb49929aaf7..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/digit.tsv +++ /dev/null @@ -1,10 +0,0 @@ -un 1 -une 1 -deux 2 -trois 3 -quatre 4 -cinq 5 -six 6 -sept 7 -huit 8 -neuf 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/hundreds.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/hundreds.tsv deleted file mode 100644 index f23060a2b6a7..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/hundreds.tsv +++ /dev/null @@ -1,2 +0,0 @@ -cent -cents \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/teen.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/teen.tsv deleted file mode 100644 index 0229696e9a72..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/teen.tsv +++ /dev/null @@ -1,6 +0,0 @@ -onze 11 -douze 12 -treize 13 -quatorze 14 -quinze 15 -seize 16 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/thousands.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/thousands.tsv deleted file mode 100644 index f77e5142656d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/thousands.tsv +++ /dev/null @@ -1,23 +0,0 @@ -mille -million -millions -milliard -milliards -billion -billions -trillion -trillions -quadrillion -quadrillions -quintillion -quintillions -sextillion -sextillions -septillion -septillions -octillion -octillions -nonillion -nonillions -decillion -decillions \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/ties.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/ties.tsv deleted file mode 100644 index b4dc2d6def67..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/ties.tsv +++ /dev/null @@ -1,13 +0,0 @@ -dix 1 -vingt 2 -vingts 2 -trente 3 -quarante 4 -cinquante 5 -soixante 6 -soixante-dix 7 -septante 7 -huitante 8 -quatre-vingt 8 -quatre-vingt-dix 9 -nonante 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/ties_unique.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/ties_unique.tsv deleted file mode 100644 index 2729167c192c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/ties_unique.tsv +++ /dev/null @@ -1,25 +0,0 @@ -vingts 20 -vingt-et-un 21 -vingt-et-une 21 -trente-et-un 31 -trente-et-une 31 -quarante-et-un 41 -quarante-et-une 41 -cinquante-et-un 51 -cinquante-et-une 51 -soixante-et-un 61 -soixante-et-une 61 -soixante-et-onze 71 -soixante-douze 72 -soixante-treize 73 -soixante-quatorze 74 -soixante-quinze 75 -soixante-seize 76 -quatre-vingts 80 -quatre-vingt 80 -quatre-vingt-onze 91 -quatre-vingt-douze 92 -quatre-vingt-treize 93 -quatre-vingt-quatorze 94 -quatre-vingt-quinze 95 -quatre-vingt-seize 96 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/zero.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/numbers/zero.tsv deleted file mode 100644 index 3ee7c2afa353..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/numbers/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -zéro 0 diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/digits_root_change.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/digits_root_change.tsv deleted file mode 100644 index ab7c43859d19..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/digits_root_change.tsv +++ /dev/null @@ -1,17 +0,0 @@ -quatrième quatre -cinquième cinq -neuvième neuf -onzième onze -douzième douze -treizième treize -quatorzième quatorze -quinzième quinze -seizième seize -trentième trente -quarantième quarante -cinquantième cinquante -soixantième soixante -septantième septante -huitantième huitante -nonantième nonante -millième mille \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/firsts.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/firsts.tsv deleted file mode 100644 index d648b34b1e69..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/firsts.tsv +++ /dev/null @@ -1,4 +0,0 @@ -premier er -premiers ers -première re -premières res \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/key_nouns.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/key_nouns.tsv deleted file mode 100644 index 543e4f051280..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/key_nouns.tsv +++ /dev/null @@ -1 +0,0 @@ -siècle \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/second.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/second.tsv deleted file mode 100644 index 2eaead50b4e9..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/ordinals/second.tsv +++ /dev/null @@ -1,4 +0,0 @@ -second d -seconde de -seconds ds -secondes des \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/roman/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/roman/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/roman/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/roman/digits_large.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/roman/digits_large.tsv deleted file mode 100644 index e5fde2cc6722..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/roman/digits_large.tsv +++ /dev/null @@ -1,9 +0,0 @@ -I 1 -II 2 -III 3 -IV 4 -V 5 -VI 6 -VII 7 -VIII 8 -IX 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/roman/hundreds_large.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/roman/hundreds_large.tsv deleted file mode 100644 index 5e04779be5ea..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/roman/hundreds_large.tsv +++ /dev/null @@ -1,9 +0,0 @@ -C 1 -CC 2 -CCC 3 -CD 4 -D 5 -DC 6 -DCC 7 -DCCC 8 -CM 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/roman/ties_large.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/roman/ties_large.tsv deleted file mode 100644 index 445773d91f0c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/roman/ties_large.tsv +++ /dev/null @@ -1,9 +0,0 @@ -X 1 -XX 2 -XXX 3 -XL 4 -L 5 -LX 6 -LXX 7 -LXXX 8 -XC 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/suppletive.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/suppletive.tsv deleted file mode 100644 index e69de29bb2d1..000000000000 diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/data/time/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/hour_to_night.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/time/hour_to_night.tsv deleted file mode 100644 index 1374f45c0f5b..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/hour_to_night.tsv +++ /dev/null @@ -1,12 +0,0 @@ -1 13 -2 14 -3 15 -4 16 -5 17 -6 18 -7 19 -8 20 -9 21 -10 22 -11 23 -12 0 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/hours.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/time/hours.tsv deleted file mode 100644 index 732b2b0096fa..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/hours.tsv +++ /dev/null @@ -1,26 +0,0 @@ -zéro 0 -une 1 -deux 2 -trois 3 -quatre 4 -cinq 5 -six 6 -sept 7 -huit 8 -neuf 9 -dix 10 -onze 11 -douze 12 -treize 13 -quatorze 14 -quinze 15 -seize 16 -dix-sept 17 -dix-huit 18 -dix-neuf 19 -vingt 20 -vingt-et-une 21 -vingt et une -vingt-deux 22 -vingt-trois 23 -vingt-quatre 24 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/hours_to.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/time/hours_to.tsv deleted file mode 100644 index a56219579975..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/hours_to.tsv +++ /dev/null @@ -1,25 +0,0 @@ -1 0 -2 1 -3 2 -4 3 -5 4 -6 5 -7 6 -8 7 -9 8 -10 9 -11 10 -12 11 -13 12 -14 13 -15 14 -16 15 -17 16 -18 17 -19 18 -20 19 -21 20 -22 21 -23 22 -24 23 -0 23 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/minutes.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/time/minutes.tsv deleted file mode 100644 index c0a555475902..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/minutes.tsv +++ /dev/null @@ -1,63 +0,0 @@ -une 01 -deux 02 -trois 03 -quatre 04 -cinq 05 -six 06 -sept 07 -huit 08 -neuf 09 -dix 10 -onze 11 -douze 12 -treize 13 -quatorze 14 -quinze 15 -seize 16 -dix-sept 17 -dix-huit 18 -dix-neuf 19 -vingt 20 -vingt-et-une 21 -vingt et une 21 -vingt-deux 22 -vingt-trois 23 -vingt-quatre 27 -vingt-cinq 25 -vingt-six 26 -vingt-sept 27 -vingt-huit 28 -vingt-neuf 29 -trente 30 -trente-et-une 31 -trente et une 31 -trente-deux 32 -trente-trois 33 -trente-quatre 34 -trente-cinq 35 -trente-six 36 -trente-sept 37 -trente-huit 38 -trente-neuf 39 -quarante 40 -quarante-et-une 41 -quarante et une 41 -quarante-deux 42 -quarante-trois 43 -quarante-quatre 44 -quarante-cinq 45 -quarante-six 46 -quarante-sept 47 -quarante-huit 48 -quarante-neuf 49 -cinquante 50 -cinquante-et-une 51 -cinquante et une 51 -cinquante-deux 52 -cinquante-trois 53 -cinquante-quatre 54 -cinquante-cinq 55 -cinquante-six 56 -cinquante-sept 57 -cinquante-huit 58 -cinquante-neuf 59 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/minutes_to.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/time/minutes_to.tsv deleted file mode 100644 index d8516a9f83ce..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/minutes_to.tsv +++ /dev/null @@ -1,59 +0,0 @@ -01 59 -02 58 -03 57 -04 56 -05 55 -06 54 -07 53 -08 52 -09 51 -10 50 -11 49 -12 48 -13 47 -14 46 -15 45 -16 44 -17 43 -18 42 -19 41 -20 40 -21 39 -22 38 -23 37 -24 36 -25 35 -26 34 -27 33 -28 32 -29 31 -30 30 -31 29 -32 28 -33 27 -34 26 -35 25 -36 24 -37 23 -38 22 -39 21 -40 20 -41 19 -42 18 -43 17 -44 16 -45 15 -46 14 -47 13 -48 12 -49 11 -50 10 -51 09 -52 08 -53 07 -54 06 -55 05 -56 04 -57 03 -58 02 -59 01 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/time_suffix_am.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/time/time_suffix_am.tsv deleted file mode 100644 index 7ae369317bc9..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/time_suffix_am.tsv +++ /dev/null @@ -1 +0,0 @@ -du matin \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/time/time_suffix_pm.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/time/time_suffix_pm.tsv deleted file mode 100644 index 3cad151dca4e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/time/time_suffix_pm.tsv +++ /dev/null @@ -1,2 +0,0 @@ -de l'après-midi -du soir \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/data/whitelist.tsv b/nemo_text_processing/inverse_text_normalization/fr/data/whitelist.tsv deleted file mode 100644 index 1a09a2ece8e4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/data/whitelist.tsv +++ /dev/null @@ -1,16 +0,0 @@ -monsieur M. -messieurs MM. -madame Mᵐᵉ -mesdames Mᵐᵉˢ -mademoiselle Mˡˡᵉ -mademoiselles Mˡˡᵉˢ -docteur Dʳ -docteurs Dʳˢ -docteure Dʳᵉ -docteures Dʳᵉˢ -après jésus-christ apr. J.-C. -avant Jésus-Christ av. J.-C. -ca v. -vers v. -l’honorable le hon. -le très hononrable le très hon. \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/fr/graph_utils.py b/nemo_text_processing/inverse_text_normalization/fr/graph_utils.py deleted file mode 100644 index 1ca29ee113ba..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/graph_utils.py +++ /dev/null @@ -1,189 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os -import string -from pathlib import Path -from typing import Dict - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini import Far -from pynini.examples import plurals -from pynini.export import export -from pynini.lib import byte, pynutil, utf8 - -NEMO_CHAR = utf8.VALID_UTF8_CHAR - -NEMO_DIGIT = byte.DIGIT -NEMO_LOWER = pynini.union(*string.ascii_lowercase).optimize() -NEMO_UPPER = pynini.union(*string.ascii_uppercase).optimize() -NEMO_ALPHA = pynini.union(NEMO_LOWER, NEMO_UPPER).optimize() -NEMO_ALNUM = pynini.union(NEMO_DIGIT, NEMO_ALPHA).optimize() -NEMO_HEX = pynini.union(*string.hexdigits).optimize() -NEMO_NON_BREAKING_SPACE = u"\u00A0" -NEMO_SPACE = " " -NEMO_WHITE_SPACE = pynini.union(" ", "\t", "\n", "\r", u"\u00A0").optimize() -NEMO_NOT_SPACE = pynini.difference(NEMO_CHAR, NEMO_WHITE_SPACE).optimize() -NEMO_NOT_QUOTE = pynini.difference(NEMO_CHAR, r'"').optimize() - -NEMO_PUNCT = pynini.union(*map(pynini.escape, string.punctuation)).optimize() -NEMO_GRAPH = pynini.union(NEMO_ALNUM, NEMO_PUNCT).optimize() - -NEMO_SIGMA = pynini.closure(NEMO_CHAR) - -delete_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE)) -insert_space = pynutil.insert(" ") -delete_extra_space = pynini.cross(pynini.closure(NEMO_WHITE_SPACE, 1), " ") - -# French frequently compounds numbers with hyphen. -delete_hyphen = pynutil.delete(pynini.closure("-", 0, 1)) -insert_hyphen = pynutil.insert("-") -suppletive = pynini.string_file(get_abs_path("data/suppletive.tsv")) - -_s = NEMO_SIGMA + pynutil.insert("s") -_x = NEMO_SIGMA + pynini.string_map([("eau"), ("eu"), ("ou")]) + pynutil.insert("x") -_aux = NEMO_SIGMA + pynini.string_map([("al", "aux"), ("ail", "aux")]) - -graph_plural = plurals._priority_union( - suppletive, plurals._priority_union(_s, pynini.union(_x, _aux), NEMO_SIGMA), NEMO_SIGMA -).optimize() - -SINGULAR_TO_PLURAL = graph_plural -PLURAL_TO_SINGULAR = pynini.invert(graph_plural) -TO_LOWER = pynini.union(*[pynini.cross(x, y) for x, y in zip(string.ascii_uppercase, string.ascii_lowercase)]) -TO_UPPER = pynini.invert(TO_LOWER) - - -def generator_main(file_name: str, graphs: Dict[str, pynini.FstLike]): - """ - Exports graph as OpenFst finite state archive (FAR) file with given file name and rule name. - - Args: - file_name: exported file name - graphs: Mapping of a rule name and Pynini WFST graph to be exported - """ - exporter = export.Exporter(file_name) - for rule, graph in graphs.items(): - exporter[rule] = graph.optimize() - exporter.close() - print(f'Created {file_name}') - - -def get_plurals(fst): - """ - Given singular returns plurals - - Args: - fst: Fst - - Returns plurals to given singular forms - """ - return SINGULAR_TO_PLURAL @ fst - - -def get_singulars(fst): - """ - Given plural returns singulars - - Args: - fst: Fst - - Returns singulars to given plural forms - """ - return PLURAL_TO_SINGULAR @ fst - - -def convert_space(fst) -> 'pynini.FstLike': - """ - Converts space to nonbreaking space. - Used only in tagger grammars for transducing token values within quotes, e.g. name: "hello kitty" - This is making transducer significantly slower, so only use when there could be potential spaces within quotes, otherwise leave it. - - Args: - fst: input fst - - Returns output fst where breaking spaces are converted to non breaking spaces - """ - return fst @ pynini.cdrewrite(pynini.cross(NEMO_SPACE, NEMO_NON_BREAKING_SPACE), "", "", NEMO_SIGMA) - - -class GraphFst: - """ - Base class for all grammar fsts. - - Args: - name: name of grammar class - kind: either 'classify' or 'verbalize' - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, name: str, kind: str, deterministic: bool = True): - self.name = name - self.kind = kind - self._fst = None - self.deterministic = deterministic - - self.far_path = Path(os.path.dirname(__file__) + '/grammars/' + kind + '/' + name + '.far') - if self.far_exist(): - self._fst = Far(self.far_path, mode="r", arc_type="standard", far_type="default").get_fst() - - def far_exist(self) -> bool: - """ - Returns true if FAR can be loaded - """ - return self.far_path.exists() - - @property - def fst(self) -> 'pynini.FstLike': - return self._fst - - @fst.setter - def fst(self, fst): - self._fst = fst - - def add_tokens(self, fst) -> 'pynini.FstLike': - """ - Wraps class name around to given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - return pynutil.insert(f"{self.name} {{ ") + fst + pynutil.insert(" }") - - def delete_tokens(self, fst) -> 'pynini.FstLike': - """ - Deletes class name wrap around output of given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - res = ( - pynutil.delete(f"{self.name}") - + delete_space - + pynutil.delete("{") - + delete_space - + fst - + delete_space - + pynutil.delete("}") - ) - return res @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/cardinal.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/cardinal.py deleted file mode 100644 index 2c8fd6c0c16f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/cardinal.py +++ /dev/null @@ -1,278 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - NEMO_NOT_SPACE, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_hyphen, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -def rewrite(cardinal: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Function to rewrite cardinals written in traditional orthograph (no '-' for numbers >100) - to current orthography ('-' between all words in number string) - e.g. deux mille cent vingt-trois -> deux-mille-cent-vingt-trois. - In cases where original orthography is current, or string is mixture of two orthographies, - will render invalid form that will not pass through CardinalFst - e.g. deux-mille cent-vingt-trois -> "deux##vingt-trois" ('#' is not accepted in cardinal FST and will fail to convert.) - e.g. deux - - Args: - cardinal: cardinal FST - """ - - # Traditional orthography does not hyphenate numbers > 100, this will insert hyphens in - # those contexts. - targets = pynini.string_map( - [ - "et", # for 'et un/onze' - "cent", - "mille", - "million", - "milliard", - "billion", - "billiard", - "trillion", - "trilliard", - ] - ) - targets += pynini.accep("s").ques - - no_spaces = pynini.closure(NEMO_NOT_SPACE) - - # Valid numbers in reformed orthography will have no spaces. - new_orthography_sigma = no_spaces - - # Old orthography will not have these strings. Replacing with character to mark. - targets_for_filtering = ("-" + targets) | ("-" + targets + "-") | (targets + "-") - - filter = pynini.cdrewrite(pynini.cross(targets_for_filtering, "#"), "", "", NEMO_SIGMA) # Invalid for cardinal - - old_orthography_sigma = pynini.difference(NEMO_CHAR, "#") # Marked character removed from sigma_star. - old_orthography_sigma.closure() - - # Only accept strings that occur in old orthography. (This avoids tying two non-related numbers together.) - # e.g. mille cent-une -> mille-cent-une - filter @= old_orthography_sigma - - # Now know replacements will only work around targets - replace_left = pynini.cdrewrite(pynini.cross(" ", "-"), "", targets, NEMO_SIGMA) - - replace_right = pynini.cdrewrite(pynini.cross(" ", "-"), targets, "", NEMO_SIGMA) - - replace = replace_left @ replace_right - - graph = new_orthography_sigma | (filter @ replace) - - return graph @ cardinal - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals - e.g. mois vingt-trois -> cardinal { negative: "-" integer: "23"} - This class converts cardinals up to (but not including) "un-quatrillion", - i.e up to "one septillion" in English (10^{24}). - Cardinals below nine are not converted (in order to avoid - "j'ai un pomme." --> "j'ai 1 pomme" and any other odd conversions.) - This transducer accomodates both traditional hyphenation of numbers ('-' for most numbers <100) - and current hyphenation (all elements of number are hyphenated), prioritizing the latter. - e.g cent cinquante et un -> cardinal { integer: "151"} - cent-cinquante-et-un -> cardinal { integer: "151"} - This is done through a context dependent rewrite that attempts to map old spelling to new. - e.g. cent cinquante et un -> cent-cinquante-et-un - """ - - def __init__(self): - super().__init__(name="cardinal", kind="classify") - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_teens = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_ties_unique = pynini.string_file(get_abs_path("data/numbers/ties_unique.tsv")) - - # Tens components - graph_tens_component = graph_ties + ((delete_hyphen + graph_digit) | pynutil.insert("0")) - graph_tens_component = pynini.union(graph_tens_component, graph_teens, graph_ties_unique) - - graph_tens_component_with_leading_zeros = pynini.union( - graph_tens_component, (pynutil.insert("0") + (graph_digit | pynutil.insert("0", weight=0.01))) - ) - - # Hundreds components - graph_cent_singular = pynutil.delete("cent") # Used in hundreds place - graph_cent_plural = pynini.cross( - "cents", "00" - ) # Only used as terminus of hundred sequence. deux cents -> 200, deux cent un -> 201 - - graph_digit_no_one = pynini.project(pynini.union("un", "une"), 'input') - graph_digit_no_one = (pynini.project(graph_digit, "input") - graph_digit_no_one.arcsort()) @ graph_digit - - graph_hundreds_component_singular = ( - graph_digit_no_one + delete_hyphen + graph_cent_singular - ) # Regular way: [1-9] * 100 - - graph_hundreds_component_singular = pynini.union(graph_hundreds_component_singular, pynini.cross("cent", "1")) - graph_hundreds_component_singular += delete_hyphen - graph_hundreds_component_singular += graph_tens_component_with_leading_zeros - - graph_hundreds_component_plural = graph_digit_no_one + delete_hyphen + graph_cent_plural - - graph_hundreds_component = pynini.union( - graph_hundreds_component_singular, - graph_hundreds_component_plural, - pynutil.insert("0") + graph_tens_component_with_leading_zeros, - ) - - graph_hundreds_component_at_least_one_none_zero_digit = graph_hundreds_component @ ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT) - ) - self.graph_hundreds_component_at_least_one_none_zero_digit = rewrite( - graph_hundreds_component_at_least_one_none_zero_digit - ).optimize() - - # Graph thousands (we'll need this for cases of mille millions, mille milliards...) - graph_tens_of_hundreds_component_singular = ( - graph_tens_component + delete_hyphen + graph_cent_singular - ) # Tens of hundreds. e.g. 1900 = nineteen hundred/ 'dix neuf cents" - graph_tens_of_hundreds_component_singular += delete_hyphen + graph_tens_component_with_leading_zeros - graph_tens_of_hundreds_component_plural = graph_tens_component + delete_hyphen + graph_cent_plural - graph_tens_of_hundred_component = ( - graph_tens_of_hundreds_component_plural | graph_tens_of_hundreds_component_singular - ) - - graph_thousands = pynini.union( - graph_hundreds_component_at_least_one_none_zero_digit + delete_hyphen + pynutil.delete("mille"), - pynutil.insert("001") + pynutil.delete("mille"), # because 'mille', not 'un mille' - pynutil.insert("000", weight=0.1), - ) - - # All other large amounts - graph_millions = pynini.union( - graph_hundreds_component_at_least_one_none_zero_digit - + delete_hyphen - + (pynutil.delete("million") | pynutil.delete("millions")), - pynutil.insert("000", weight=0.1), - ) - - graph_milliards = pynini.union( # French for English 'billion' - graph_hundreds_component_at_least_one_none_zero_digit - + delete_hyphen - + (pynutil.delete("milliard") | pynutil.delete("milliards")), - pynutil.insert("000", weight=0.1), - ) - - graph_billions = pynini.union( # NOTE: this is English 'trillion.' - graph_hundreds_component_at_least_one_none_zero_digit - + delete_hyphen - + (pynutil.delete("billions") | pynutil.delete("billion")), - pynutil.insert("000", weight=0.1), - ) - - graph_mille_billion = pynini.union( - graph_hundreds_component_at_least_one_none_zero_digit + delete_hyphen + pynutil.delete("mille"), - pynutil.insert("001") + pynutil.delete("mille"), # because we say 'mille', not 'un mille' - ) - graph_mille_billion += delete_hyphen + ( - graph_millions | pynutil.insert("000") + pynutil.delete("billions") - ) # allow for 'mil millones' - graph_mille_billion |= pynutil.insert("000000", weight=0.1) - - graph_billiards = pynini.union( - graph_hundreds_component_at_least_one_none_zero_digit - + delete_hyphen - + (pynutil.delete("billiards") | pynutil.delete("billiard")), - pynutil.insert("000", weight=0.1), - ) - - graph_trillions = pynini.union( # One thousand English trillions. - graph_hundreds_component_at_least_one_none_zero_digit - + delete_hyphen - + (pynutil.delete("trillions") | pynutil.delete("trillion")), - pynutil.insert("000", weight=0.1), - ) - - graph_trilliards = pynini.union( - graph_hundreds_component_at_least_one_none_zero_digit - + delete_hyphen - + (pynutil.delete("trilliards") | pynutil.delete("trilliard")), - pynutil.insert("000", weight=0.1), - ) - - graph = pynini.union( - graph_trilliards - + delete_hyphen - + graph_trillions - + delete_hyphen - + graph_billiards - + delete_hyphen - + graph_billions - + delete_hyphen - + graph_milliards - + delete_hyphen - + graph_millions - + delete_hyphen - + graph_thousands - + delete_hyphen - + graph_hundreds_component, - graph_tens_of_hundred_component, - graph_zero, - ) - - graph = graph @ pynini.union( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT), "0" - ) - - graph = rewrite(graph) - - self.graph_no_exception = graph.optimize() - - # save self.numbers_up_to_thousand for use in DecimalFst - digits_up_to_thousand = NEMO_DIGIT | (NEMO_DIGIT ** 2) | (NEMO_DIGIT ** 3) - numbers_up_to_thousand = pynini.compose(graph, digits_up_to_thousand).optimize() - self.numbers_up_to_thousand = numbers_up_to_thousand - - # save self.numbers_up_to_million for use in DecimalFst - digits_up_to_million = ( - NEMO_DIGIT - | (NEMO_DIGIT ** 2) - | (NEMO_DIGIT ** 3) - | (NEMO_DIGIT ** 4) - | (NEMO_DIGIT ** 5) - | (NEMO_DIGIT ** 6) - ) - numbers_up_to_million = pynini.compose(graph, digits_up_to_million).optimize() - self.numbers_up_to_million = numbers_up_to_million - - # don't convert cardinals from zero to nine inclusive - graph_exception = pynini.project(pynini.union(graph_digit, graph_zero), 'input') - - self.graph = (pynini.project(graph, "input") - graph_exception.arcsort()) @ graph - - optional_minus_graph = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("moins", "\"-\"") + NEMO_SPACE, 0, 1 - ) - - final_graph = optional_minus_graph + pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/date.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/date.py deleted file mode 100644 index 1412111b42b2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/date.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import GraphFst, delete_extra_space -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, in the form of (day) month (year) or year - e.g. le vingt-quatre juillet deux-mille-treize -> date { day: "24" month: "juli" year: "2013" preserve_order: true } - e.g. le vingt-quatre juillet deux-mille-treize -> date { day: "24" month: "juli" year: "2013" preserve_order: true } - e.g. le premier janvier -> date { day: "1" month: "janvier" preserve_order: true } - - Also will convert colloquialism of spelling in which tens of hundreds are used to express date. (e.g. nineteen hundred and four) - e.g. le vingt mais dix-neuf-cent-quatre -> date { day: "20" month: "mais" year: "1904" preserve_order: true } - - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="date", kind="classify") - - self.cardinal = cardinal.graph_no_exception - - year_graph = self.cardinal - - month_graph = pynini.string_file(get_abs_path("data/months.tsv")) - month_graph = pynutil.insert("month: \"") + month_graph + pynutil.insert("\"") - - day_graph = self.cardinal | pynini.cross("premier", "1") # Premier is only ordinal used for dates - day_graph = pynutil.insert("day: \"") + day_graph + pynutil.insert("\"") - optional_graph_year = pynini.closure( - delete_extra_space + pynutil.insert("year: \"") + year_graph + pynutil.insert("\""), 0, 1, - ) - graph_dmy = day_graph + delete_extra_space + month_graph + optional_graph_year - - final_graph = graph_dmy - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/decimal.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/decimal.py deleted file mode 100644 index 035d70fab857..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/decimal.py +++ /dev/null @@ -1,128 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_hyphen, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -def get_quantity(decimal: 'pynini.FstLike', cardinal_up_to_thousand: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. one million -> integer_part: "1" quantity: "million" - e.g. one point five million -> integer_part: "1" fractional_part: "5" quantity: "million" - - Will tag cases up to denominations of tens of hundreds of thousand. 'douze cent mille millions' -> 1 200 000 millions - - Args: - decimal: decimal FST - cardinal_up_to_million: cardinal FST - """ - numbers = cardinal_up_to_thousand @ ( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT) - ) - - suffix = pynini.union( - "million", - "millions", - "milliard", - "milliards", - "billion", - "billions", - "billiard", - "billiards", - "trillion", - "trillions", - "trilliard", - "trilliards", - ) - res = ( - pynutil.insert("integer_part: \"") - + numbers - + pynutil.insert("\"") - + ( - pynini.union(delete_hyphen, delete_extra_space) - ) # Can be written either as 'deux-millions' or 'deux millions' depending on whether it registers as a noun or part of cardinal. - + pynutil.insert(" quantity: \"") - + suffix - + pynutil.insert("\"") - ) - res |= decimal + delete_extra_space + pynutil.insert(" quantity: \"") + suffix + pynutil.insert("\"") - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal - Decimal point is "," (virgule). - e.g. moins un virgule deux six -> decimal { negative: "true" integer_part: "1" fractional_part: "26" } - - This decimal rule assumes that decimals can be pronounced as: - (a cardinal) + ('virgule') plus (any sequence of cardinals <1 million, including 'zero') - - Also writes large numbers in shortened form, e.g. - e.g. un virgule deux-six-million -> decimal { negative: "false" integer_part: "1" fractional_part: "26" quantity: "million" } - e.g. deux-million -> decimal { negative: "false" integer_part: "2" quantity: "millions" } - e.g. moins cent-vingt-quatre-millions -> decimal { negative: "true" integer_part: "124" quantity: "millions" } - Args: - cardinal: CardinalFst - - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="decimal", kind="classify") - - # number after decimal point can be any series of cardinals <1 million, including 'zero' - graph_decimal = cardinal.numbers_up_to_million - graph_decimal = pynini.closure(graph_decimal + delete_space) + graph_decimal - self.graph = graph_decimal - - # decimal point is denote by virgule - graph_fractional_separator = pynutil.delete("virgule") - - # Possible negatives - optional_graph_negative = pynutil.insert("negative: ") + pynini.cross("moins", "\"true\"") + delete_extra_space - optional_graph_negative = optional_graph_negative.ques - - # Fractional portion - graph_fractional = pynutil.insert("fractional_part: \"") + graph_decimal + pynutil.insert("\"") - - # Integers - cardinal_graph = cardinal.graph_no_exception | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - - # Final graphs - final_graph_wo_sign = ( - pynini.closure(graph_integer + delete_extra_space, 0, 1) - + graph_fractional_separator - + delete_extra_space - + graph_fractional - ) - final_graph = optional_graph_negative + final_graph_wo_sign - - self.final_graph_wo_negative = final_graph_wo_sign | get_quantity( - final_graph_wo_sign, cardinal.graph_hundreds_component_at_least_one_none_zero_digit - ) - final_graph |= optional_graph_negative + get_quantity( - final_graph_wo_sign, cardinal.graph_hundreds_component_at_least_one_none_zero_digit - ) - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/electronic.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/electronic.py deleted file mode 100644 index 15d82665001a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/electronic.py +++ /dev/null @@ -1,110 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import NEMO_ALPHA, GraphFst, insert_space -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying 'electronic' semiotic classes, i.e. - email address (which get converted to "username" and "domain" fields), - and URLS (which get converted to a "protocol" field). - e.g. c d f une arobase a b c point e d u -> tokens { electronic { username: "cdf1" domain: "abc.edu" } } - e.g. double vé double vé double vé a b c point e d u -> tokens { electronic { protocol: "www.abc.edu" } } - """ - - def __init__(self): - super().__init__(name="electronic", kind="classify") - - delete_extra_space = pynutil.delete(" ") - alpha_num = ( - NEMO_ALPHA - | pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - ) - - symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")) - ampersand = pynini.string_map([("arobase"), ("chez"), ("at"), ("à")]) - - accepted_username = alpha_num | symbols - process_dot = pynini.cross("point", ".") - username = ( - pynutil.insert("username: \"") - + alpha_num - + delete_extra_space - + pynini.closure(accepted_username + delete_extra_space) - + alpha_num - + pynutil.insert("\"") - ) - single_alphanum = pynini.closure(alpha_num + delete_extra_space) + alpha_num - server = single_alphanum | pynini.string_file(get_abs_path("data/electronic/server_name.tsv")) - domain = single_alphanum | pynini.string_file(get_abs_path("data/electronic/domain.tsv")) - domain_graph = ( - pynutil.insert("domain: \"") - + server - + delete_extra_space - + process_dot - + delete_extra_space - + domain - + pynutil.insert("\"") - ) - graph = ( - username - + delete_extra_space - + pynutil.delete(ampersand) - + insert_space - + delete_extra_space - + domain_graph - ) - - ############# url ### - protocol_end = pynini.cross(pynini.union("www", "w w w", "double vé double vé double vé"), "www") - protocol_start = pynini.cross(pynini.union("http", "h t t p", "ache té té pé"), "http") - protocol_start |= pynini.cross(pynini.union("https", "h t t p s", "ache té té pé esse"), "https") - protocol_start += pynini.cross( - pynini.union( - " deux-points barre oblique barre oblique ", - " deux-points barre barre ", - " deux-points double barre ", - " deux-points slash slash ", - ), - "://", - ) - - # e.g. .com, .es - ending = ( - delete_extra_space - + symbols - + delete_extra_space - + (domain | pynini.closure(accepted_username + delete_extra_space) + accepted_username) - ) - - protocol = ( - pynini.closure(protocol_start, 0, 1) - + protocol_end - + delete_extra_space - + process_dot - + delete_extra_space - + (pynini.closure(delete_extra_space + accepted_username, 1) | server) - + pynini.closure(ending, 1) - ) - protocol = pynutil.insert("protocol: \"") + protocol + pynutil.insert("\"") - graph |= protocol - ######## - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/fraction.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/fraction.py deleted file mode 100644 index e053237246ce..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/fraction.py +++ /dev/null @@ -1,75 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_CHAR, - GraphFst, - delete_extra_space, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for classifying fraction - e.g. demi -> tokens { fraction { numerator: "1" denominator: "2" } } - e.g. un et demi -> tokens { fraction { integer_part: "1" numerator: "1" denominator: "2" } } - e.g. trois et deux centième -> tokens { fraction { integer_part: "3" numerator: "2" denominator: "100" } } - - Args: - cardinal: OrdinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="fraction", kind="classify") - # integer_part # numerator # denominator - - graph_cardinal = cardinal.graph_no_exception - graph_strip_undo_root_change = pynini.string_file(get_abs_path("data/fractions.tsv")) # add in absolute path - - graph_strip_no_root_change = pynutil.delete("ième") # For no change to root - graph_strip_no_root_change += pynutil.delete("s").ques # for plurals - - graph_strip = graph_strip_no_root_change | graph_strip_undo_root_change - - self.fractional = ((pynini.closure(NEMO_CHAR) + graph_strip) @ graph_cardinal).optimize() - - integer = pynutil.insert("integer_part: \"") + graph_cardinal + pynutil.insert("\" ") - integer += delete_space - integer += pynutil.delete("et") # used to demarcate integer and fractional parts - - numerator = pynutil.insert("numerator: \"") + graph_cardinal + pynutil.insert("\"") - denominator = pynutil.insert(" denominator: \"") + self.fractional + pynutil.insert("\"") - - # Demi (half) can occur alone without explicit numerator. - graph_demi_component = pynutil.delete("demi") + pynutil.delete("e").ques + pynutil.delete("s").ques - graph_demi_component += pynutil.insert("numerator: \"1\" denominator: \"2\"") - - graph_fraction_component = numerator + delete_space + denominator - graph_fraction_component |= graph_demi_component - self.graph_fraction_component = graph_fraction_component - - graph = pynini.closure(integer + delete_space, 0, 1) + graph_fraction_component - graph = graph.optimize() - self.final_graph_wo_negative = graph - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("moins", "\"true\"") + delete_extra_space, 0, 1 - ) - graph = optional_graph_negative + graph - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/measure.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/measure.py deleted file mode 100644 index d9636286c6fa..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/measure.py +++ /dev/null @@ -1,92 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - get_singulars, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure. Allows for plural form for unit. - e.g. moins onze kilogramme -> measure { negative: "true" cardinal { integer: "11" } units: "kg" } - e.g. trois heures -> measure { cardinal { integer: "3" } units: "h" } - e.g. demi gramme -> measure { fraction { numerator: "1" denominator: "2" } units: "g" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - fraction: FractionFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, fraction: GraphFst): - super().__init__(name="measure", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - - graph_prefix = pynini.string_file(get_abs_path("data/measurements/magnitudes.tsv")) - graph_unit_singular = pynini.string_file(get_abs_path("data/measurements/measurements.tsv")) - - unit = get_singulars(graph_unit_singular) | graph_unit_singular - unit = graph_prefix.ques + unit - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("moins", "\"true\"") + delete_extra_space, 0, 1 - ) - - unit_misc = pynutil.insert("/") + (pynutil.delete("par") | pynutil.delete("à")) + delete_space + unit - - unit = ( - pynutil.insert("units: \"") - + (unit | unit_misc | pynutil.add_weight(unit + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - - subgraph_decimal = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + decimal.final_graph_wo_negative - + pynutil.insert(" }") - + delete_extra_space - + unit - ) - - subgraph_fraction = ( - pynutil.insert("fraction { ") - + optional_graph_negative - + fraction.final_graph_wo_negative - + pynutil.insert(" }") - + delete_extra_space - + unit - ) - - subgraph_cardinal = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + cardinal_graph - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit - ) - final_graph = subgraph_decimal | subgraph_cardinal | subgraph_fraction - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/money.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/money.py deleted file mode 100644 index 17f473aa2bb9..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/money.py +++ /dev/null @@ -1,134 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money - e.g. douze euro cinq -> money { integer_part: "12" currency: "€" fractional_part: 05} - e.g. zéro euro cinq -> money { integer_part: "0" currency: "€" fractional_part: 05} - e.g. cinq centimes -> money { integer_part: "0" currency: "€" fractional_part: 05} - - Note, the currency symbol seems more common for exact amounts and quantities less than 'un million' - For 'round' quantities of >=million (milliard, billion), the symbol is dropped. This allows - use of the 'de' preposition. - e.g. cinq millions d'euros -> money { integer_part: "5" currency: "d'euros" fractional_part: 00} - e.g. un milliard d'euro -> money { integer_part: "5" currency: "d'euro" fractional_part: 00} - e.g. trois virgule trois millions d'euros -> money { integer_part: "3" currency: "d'euros" fractional_part: 3} - - Currency is included for uniform tagging. - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="money", kind="classify") - # quantity, integer_part, fractional_part, currency - - # quantities - cardinal_graph = cardinal.graph_no_exception - graph_decimal = decimal.final_graph_wo_negative - - # Converts currency names to symbols - convert_currency_major = pynini.string_file( - get_abs_path("data/money/currency_major.tsv") - ) # major denominations - convert_currency_minor = pynini.string_file( - get_abs_path("data/money/currency_minor.tsv") - ) # minor denominations to major symbol. (e.g. 5 cents -> 0.05 $ ) - - accept_all_currency = (convert_currency_major | convert_currency_minor).project( - "input" - ) # recognizes all currencies - - # Graphs for large round amounts ('deux billiards d'euros', 'un milliard de dollars') - graph_de = pynini.union("de ", "des ", "d'") # the use of de/d'only occurs with round amounts - graph_currency_component_large_round_amounts = graph_de + accept_all_currency - graph_currency_component_large_round_amounts = ( - pynutil.insert(" currency: \"") + graph_currency_component_large_round_amounts + pynutil.insert("\"") - ) - - graph_money_large_round_amounts = ( - graph_decimal + delete_space - ) # graph_decimal includes tags and quantities already - graph_money_large_round_amounts += graph_currency_component_large_round_amounts - - # For standard currency - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - - # Graphs integer denomination for large denominations (e.g. $) - graph_integer_component_major = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - graph_integer_component_major += delete_space - - graph_currency_component_major = ( - pynutil.insert(" currency: \"") + convert_currency_major + pynutil.insert("\"") - ) - - graph_decimal_component_major = ( - delete_space - + pynutil.insert(" fractional_part: \"") - + (cardinal_graph @ add_leading_zero_to_double_digit) - + pynutil.insert("\"") - ) - - # Rare cases where 'et' will separate major and minor denominations. - delete_minor_currency = pynini.project(convert_currency_minor, "input") - delete_minor_currency = delete_extra_space + pynutil.delete(delete_minor_currency) - - delete_et = delete_extra_space + pynutil.delete("et") - - graph_money_major = ( - graph_integer_component_major - + graph_currency_component_major - + delete_et.ques - + graph_decimal_component_major.ques - + delete_minor_currency.ques - ) - - # For cases when only small denominations are used. - graph_integer_component_minor = pynutil.insert("integer_part: \"0\"") - - graph_decimal_component_minor = ( - pynutil.insert(" fractional_part: \"") - + (cardinal_graph @ add_leading_zero_to_double_digit) - + pynutil.insert("\"") - ) - graph_decimal_component_minor += delete_extra_space - - graph_currency_component_minor = ( - pynutil.insert(" currency: \"") + convert_currency_minor + pynutil.insert("\"") - ) - - graph_money_minor = ( - graph_integer_component_minor + graph_decimal_component_minor + graph_currency_component_minor - ) - - graph_money_standard_amounts = graph_money_major | graph_money_minor - - final_graph = graph_money_large_round_amounts | graph_money_standard_amounts - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/ordinal.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/ordinal.py deleted file mode 100644 index 29da19b85c0a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/ordinal.py +++ /dev/null @@ -1,77 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import NEMO_SIGMA, GraphFst, delete_space -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal - vingt-deuxième -> ordinal { integer: "22" morphosyntactic_features: "e" } - - Also notes specific nouns that have unique normalization conventions. - For instance, 'siècles' are rendered in roman numerals when given an ordinal adjective. - e.g. dix-neuvième siècle -> XIXe - - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="ordinal", kind="classify") - - graph_cardinal = cardinal.graph_no_exception - graph_undo_root_change = pynini.string_file( - get_abs_path("data/ordinals/digits_root_change.tsv") - ) # Returns base number to normal after root change. - graph_firsts = pynini.string_file(get_abs_path("data/ordinals/firsts.tsv")) - graph_second = pynini.string_file(get_abs_path("data/ordinals/second.tsv")) - graph_special_ordinals = pynini.string_file(get_abs_path("data/ordinals/key_nouns.tsv")) - - # Removes morpheme - graph_no_root_change = pynutil.delete("ième") # For no change to root - - graph_strip_morpheme = pynini.union(graph_no_root_change, graph_undo_root_change) - graph_strip_morpheme = NEMO_SIGMA + graph_strip_morpheme - - graph_integer_component = graph_strip_morpheme @ graph_cardinal - - graph_morpheme_component = pynutil.insert("e") # Put the superscript in. - graph_morpheme_component += pynini.accep("s").ques # In case of plurals. - - # Concatenate with cardinal graph. - graph_ordinal = pynutil.insert("integer: \"") + graph_integer_component + pynutil.insert("\"") - graph_ordinal += ( - pynutil.insert(" morphosyntactic_features: \"") + graph_morpheme_component - ) # Leave open in case further morphems occur - - # Primer has a different subscript depending on gender, need to take note if - # 'premier' or 'première' - graph_firsts = pynutil.insert("integer: \"1\" morphosyntactic_features: \"") + graph_firsts - - # Second used 'd' as a superscript. - graph_second = pynutil.insert("integer: \"2\" morphosyntactic_features: \"") + graph_second - - graph = graph_firsts | graph_second | graph_ordinal - - # For roman numerals. Carries over designation to verbalizer - graph_special_ordinals = pynutil.insert("/") + delete_space + graph_special_ordinals - - graph += graph_special_ordinals.ques + pynutil.insert("\"") - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/punctuation.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/punctuation.py deleted file mode 100644 index 458497aa6064..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/punctuation.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import GraphFst -from pynini.lib import pynutil - - -class PunctuationFst(GraphFst): - """ - Finite state transducer for classifying punctuation - e.g. a, -> tokens { name: "a" } tokens { name: "," } - """ - - def __init__(self): - super().__init__(name="punctuation", kind="classify") - - s = "!#$%&\'()*+,-./:;<=>?@^_`{|}~" - guillemets = "\u00AB" + "\u00BB" # quotation marks in French. - s += guillemets - punct = pynini.union(*s) - - graph = pynutil.insert("name: \"") + punct + pynutil.insert("\"") - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/telephone.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/telephone.py deleted file mode 100644 index 9d18fb71f1f3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/telephone.py +++ /dev/null @@ -1,82 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - GraphFst, - delete_hyphen, - delete_space, - insert_space, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone numbers. Assumes conventional grouping for Metropolitan France (and overseas departments) - (two number sequences are grouped as individual cardinals) or digit by digit (chiffre-par-chiffre) e.g. - "zero un quatre-vingt-deux zero deux vingt-deux cinquante" -> { number_part: "01 42 02 22 50" } - "zero un quatre deux zero deux deux deux cinq zero" -> { number_part: "01 42 02 22 50" } - - In cases where only one digit of the first pairing is admitted, assumes that the 0 was skipped. - "une vingt-trois quatre-vingt zero six dix-sept" -> { number_part: "01 23 40 06 17" } - """ - - def __init__(self): - super().__init__(name="telephone", kind="classify") - - # create `single_digits` and `double_digits` graphs as these will be - # the building blocks of possible telephone numbers - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_ties_unique = pynini.string_file((get_abs_path("data/numbers/ties_unique.tsv"))) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - - double_digits = pynini.union( - graph_teen, - graph_ties_unique, - (graph_ties + pynutil.insert("0")), - (graph_ties + delete_hyphen + graph_digit), - ) - - graph_first_pair = graph_zero + delete_space + graph_digit - graph_first_pair |= pynutil.insert("0") + graph_digit # if zero is omitted - graph_first_pair += ( - delete_space + insert_space - ) # delete_space since closure allows possible gaps to be removed - - # All digits - single_digits = graph_digit | graph_zero - - graph_pair_all_digits = single_digits + delete_space - graph_pair_all_digits += single_digits - - graph_all_digits = pynini.closure(graph_pair_all_digits + delete_space + insert_space, 3, 3) - graph_all_digits = graph_first_pair + graph_all_digits + graph_pair_all_digits - - # Paired digits - graph_pair_digits_and_ties = double_digits | graph_pair_all_digits - - graph_digits_and_ties = pynini.closure(graph_pair_digits_and_ties + delete_space + insert_space, 3, 3) - graph_digits_and_ties = graph_first_pair + graph_digits_and_ties + graph_pair_digits_and_ties - - number_part = pynini.union(graph_all_digits, graph_digits_and_ties) - - number_part = pynutil.insert("number_part: \"") + number_part + pynutil.insert("\"") - - graph = number_part - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/time.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/time.py deleted file mode 100644 index 499701a1ea8e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/time.py +++ /dev/null @@ -1,115 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import GraphFst, delete_space -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time - e.g. huit heures -> time { hours: "8" minutes: "00" } - e.g. treize heures -> time { hours: "13" minutes: "00" } - e.g. treize heures dix -> time { hours: "13" minutes: "10" } - e.g. huit heures du matin -> time { hours: "8" minutes: "00" suffix: "avant mid"} - e.g. huite heures du après midi -> time { hours: "8" minutes: "00" suffix: "après-midi"} - e.g. douze heures moins qart -> time { hours: "11" minutes: "45" } - e.g. douze heures et qart -> time { hours: "12" minutes: "15" } - e.g. midi et qart -> time { hours: "12" minutes: "15" } - e.g. minuit et medi -> time { hours: "0" minutes: "30" } - e.g. douze heures moins medi -> time { hours: "11" minutes: "30" } - e.g. douze heures moins trois -> time { hours: "11" minutes: "57" } - """ - - def __init__(self): - super().__init__(name="time", kind="classify") - # hours, minutes, seconds, suffix, zone, style, speak_period - - # time_zone = pynini.invert(pynini.string_file(get_abs_path("data/time/time_zone.tsv"))) - graph_hours_to = pynini.string_file(get_abs_path("data/time/hours_to.tsv")) - graph_minutes_to = pynini.string_file(get_abs_path("data/time/minutes_to.tsv")) - graph_hours = pynini.string_file(get_abs_path("data/time/hours.tsv")) - graph_minutes = pynini.string_file(get_abs_path("data/time/minutes.tsv")) - graph_suffix_am = pynini.string_file(get_abs_path("data/time/time_suffix_am.tsv")) - graph_suffix_pm = pynini.string_file(get_abs_path("data/time/time_suffix_pm.tsv")) - - graph_suffix = pynini.cross(graph_suffix_am, "am") | pynini.cross(graph_suffix_pm, "pm") - - # Mapping 'heures' - graph_heures = pynini.accep("heure") + pynini.accep("s").ques - graph_heures = pynutil.delete(graph_heures) - - graph_hours += delete_space + graph_heures - - # Midi and minuit - graph_midi = pynini.cross("midi", "12") - graph_minuit = pynini.cross("minuit", "0") - - # Mapping 'et demi' and 'et qart' - graph_et = pynutil.delete("et") + delete_space - - graph_demi = pynini.accep("demi") - graph_demi += pynini.accep("e").ques # people vary on feminine or masculine form - graph_demi = pynini.cross(graph_demi, "30") - - graph_quart = pynini.accep('quart') - graph_quart = pynini.accep("le ").ques + graph_quart # sometimes used - graph_quart = pynini.cross(graph_quart, '15') - graph_trois_quart = pynini.cross("trois quarts", "45") - - graph_fractions = pynini.union(graph_demi, graph_quart, graph_trois_quart) - - graph_et_fractions = graph_et + graph_fractions - - # Hours component is usually just a cardinal + 'heures' (ignored in case of 'midi/minuit'). - graph_hours_component = pynini.union(graph_hours, graph_midi, graph_minuit) - graph_hours_component = pynutil.insert("hours: \"") + graph_hours_component + pynutil.insert("\"") - graph_hours_component += delete_space - - # Minutes component - graph_minutes_component = ( - pynutil.insert(" minutes: \"") + pynini.union(graph_minutes, graph_et_fractions) + pynutil.insert("\"") - ) - - # Hour and minutes together. For 'demi' and 'qart', 'et' is used as a conjunction. - graph_time_standard = graph_hours_component + graph_minutes_component.ques - - # For time until hour. "quatre heures moins qart" -> 4 h 00 - 0 h 15 = 3 h 45 - graph_moins = pynutil.delete("moins") - graph_moins += delete_space - - graph_hours_to_component = graph_hours | graph_midi | graph_minuit - graph_hours_to_component @= graph_hours_to - graph_hours_to_component = pynutil.insert("hours: \"") + graph_hours_to_component + pynutil.insert("\"") - graph_hours_to_component += delete_space - - graph_minutes_to_component = pynini.union(graph_minutes, graph_fractions) - graph_minutes_to_component @= graph_minutes_to - graph_minutes_to_component = pynutil.insert(" minutes: \"") + graph_minutes_to_component + pynutil.insert("\"") - - graph_time_to = graph_hours_to_component + graph_moins + graph_minutes_to_component - - graph_time_no_suffix = graph_time_standard | graph_time_to - - graph_suffix_component = pynutil.insert(" suffix: \"") + graph_suffix + pynutil.insert("\"") - graph_suffix_component = delete_space + graph_suffix_component - graph_suffix_component = graph_suffix_component.ques - - final_graph = graph_time_no_suffix + graph_suffix_component - - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/tokenize_and_classify.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/tokenize_and_classify.py deleted file mode 100644 index 16b8f56f8d94..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,116 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.inverse_text_normalization.fr.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.date import DateFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.fraction import FractionFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.punctuation import PunctuationFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.whitelist import WhiteListFst -from nemo_text_processing.inverse_text_normalization.fr.taggers.word import WordFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="tokenize_and_classify", kind="classify") - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "_fr_itn.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars.") - - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - - fraction = FractionFst(cardinal) - fraction_graph = fraction.fst - - ordinal = OrdinalFst(cardinal) - ordinal_graph = ordinal.fst - - decimal = DecimalFst(cardinal) - decimal_graph = decimal.fst - - measure_graph = MeasureFst(cardinal=cardinal, decimal=decimal, fraction=fraction).fst - date_graph = DateFst(cardinal).fst - word_graph = WordFst().fst - time_graph = TimeFst().fst - money_graph = MoneyFst(cardinal, decimal).fst - whitelist_graph = WhiteListFst().fst - punct_graph = PunctuationFst().fst - electronic_graph = ElectronicFst().fst - telephone_graph = TelephoneFst().fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.05) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.08) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(fraction_graph, 1.09) - | pynutil.add_weight(money_graph, 1.07) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/whitelist.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/whitelist.py deleted file mode 100644 index 54826162c07a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/whitelist.py +++ /dev/null @@ -1,33 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import GraphFst, convert_space -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelisted tokens - e.g. misses -> tokens { name: "mrs." } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - """ - - def __init__(self): - super().__init__(name="whitelist", kind="classify") - - whitelist = pynini.string_file(get_abs_path("data/whitelist.tsv")) - graph = pynutil.insert("name: \"") + convert_space(whitelist) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/taggers/word.py b/nemo_text_processing/inverse_text_normalization/fr/taggers/word.py deleted file mode 100644 index 95d05ce6aa7a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/taggers/word.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying plain tokens, that do not belong to any special class. This can be considered as the default class. - e.g. sleep -> tokens { name: "sleep" } - """ - - def __init__(self): - super().__init__(name="word", kind="classify") - word = pynutil.insert("name: \"") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert("\"") - self.fst = word.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/utils.py b/nemo_text_processing/inverse_text_normalization/fr/utils.py deleted file mode 100644 index f6e06f793c07..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/utils.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + '/' + rel_path diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/__init__.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/cardinal.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/cardinal.py deleted file mode 100644 index 4aca2bac2c9f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/cardinal.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinal - e.g. cardinal { negative: "-" integer: "23" } -> -23 - """ - - def __init__(self): - super().__init__(name="cardinal", kind="verbalize") - optional_sign = pynini.closure( - pynutil.delete("negative:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space, - 0, - 1, - ) - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - self.numbers = graph - graph = optional_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/date.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/date.py deleted file mode 100644 index 47304c1e1be0..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/date.py +++ /dev/null @@ -1,76 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { day: "1" month: "janvier" preserve_order: true } -> 1 de enero - """ - - def __init__(self): - super().__init__(name="date", kind="verbalize") - - convert_primer = pynini.cross('1', '1ᵉʳ') - day = ( - pynutil.delete("day:") - + delete_space - + pynutil.delete("\"") - + ( - pynini.closure(NEMO_NOT_QUOTE, 1) | pynutil.add_weight(convert_primer, -1) - ) # first of the month is ordinal - + pynutil.delete("\"") - ) - month = ( - pynutil.delete("month:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - year = ( - pynutil.delete("year:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - # day month - graph_dm = day + delete_extra_space + month - graph_dmy = graph_dm + delete_extra_space + year - - optional_preserve_order = pynini.closure( - pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - | pynutil.delete("field_order:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space - ) - - final_graph = (graph_dm | graph_dmy) + delete_space + optional_preserve_order - - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/decimal.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/decimal.py deleted file mode 100644 index dc00842cd1c7..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/decimal.py +++ /dev/null @@ -1,94 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_DIGIT, - NEMO_NON_BREAKING_SPACE, - NEMO_NOT_QUOTE, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class NumberParser(GraphFst): - """ - Finite state transducer for parsing strings of digis. Breaks up digit strings into groups of three for - strings of digits of four or more (inclusive). Groupings are separated by non-breaking space. - e.g. '1000' -> '1 000' - e.g. '1000,33333' -> '1 000,333 33 - """ - - def __init__(self): - super().__init__(name="parser", kind="verbalize") - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, e.g. - decimal { negative: "true" integer_part: "12" fractional_part: "5006" quantity: "billion" } -> -12.5006 billion - """ - - def __init__(self): - super().__init__(name="decimal", kind="verbalize") - - # Need parser to group digits by threes - exactly_three_digits = NEMO_DIGIT ** 3 - at_most_three_digits = pynini.closure(NEMO_DIGIT, 1, 3) - - space_every_three_integer = ( - at_most_three_digits + (pynutil.insert(NEMO_NON_BREAKING_SPACE) + exactly_three_digits).closure() - ) - space_every_three_decimal = ( - pynini.accep(",") - + (exactly_three_digits + pynutil.insert(NEMO_NON_BREAKING_SPACE)).closure() - + at_most_three_digits - ) - group_by_threes = space_every_three_integer | space_every_three_decimal - self.group_by_threes = group_by_threes - - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "-") + delete_space, 0, 1) - integer = ( - pynutil.delete("integer_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - integer = integer @ group_by_threes - optional_integer = pynini.closure(integer + delete_space, 0, 1) - fractional = ( - pynutil.insert(",") - + pynutil.delete("fractional_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - fractional = fractional @ group_by_threes - optional_fractional = pynini.closure(fractional + delete_space, 0, 1) - quantity = ( - pynutil.delete("quantity:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_quantity = pynini.closure(pynutil.insert(" ") + quantity + delete_space, 0, 1) - graph = (optional_integer + optional_fractional + optional_quantity).optimize() - self.numbers = graph - graph = optional_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/electronic.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/electronic.py deleted file mode 100644 index e4cc75cbd6ef..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/electronic.py +++ /dev/null @@ -1,45 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. tokens { electronic { username: "cdf1" domain: "abc.edu" } } -> cdf1@abc.edu - """ - - def __init__(self): - super().__init__(name="electronic", kind="verbalize") - user_name = ( - pynutil.delete("username:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - domain = ( - pynutil.delete("domain:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - graph = user_name + delete_space + pynutil.insert("@") + domain - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/fraction.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/fraction.py deleted file mode 100644 index dce25d9497c8..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/fraction.py +++ /dev/null @@ -1,53 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for verbalizing fraction - e.g. fraction { integer_part: "1" numerator: "2" denominator: "3" } } -> 1 2/3 - - """ - - def __init__(self): - super().__init__(name="fraction", kind="verbalize") - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "-") + delete_space, 0, 1) - integer = ( - pynutil.delete("integer_part: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + insert_space - ) - numerator = pynutil.delete("numerator: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - denominator = ( - pynutil.insert('/') - + pynutil.delete("denominator: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - graph = (pynini.closure(integer + delete_space, 0, 1) + numerator + delete_space + denominator).optimize() - self.numbers = graph - delete_tokens = self.delete_tokens(optional_sign + graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/measure.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/measure.py deleted file mode 100644 index ad0f2f98c1b0..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/measure.py +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { negative: "true" cardinal { integer: "12" } units: "kg" } -> -12 kg - - Args: - decimal: DecimalFst - cardinal: CardinalFst - fraction: FractionFst - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst, fraction: GraphFst): - super().__init__(name="measure", kind="verbalize") - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "-"), 0, 1) - unit = ( - pynutil.delete("units:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - + delete_space - ) - graph_decimal = ( - pynutil.delete("decimal {") - + delete_space - + optional_sign - + delete_space - + decimal.numbers - + delete_space - + pynutil.delete("}") - ) - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + delete_space - + cardinal.numbers @ decimal.group_by_threes # measurements most obey three by three spacing - + delete_space - + pynutil.delete("}") - ) - graph_fraction = ( - pynutil.delete("fraction {") - + delete_space - + optional_sign - + delete_space - + fraction.numbers - + delete_space - + pynutil.delete("}") - ) - - graph = (graph_cardinal | graph_decimal | graph_fraction) + delete_space + pynutil.insert(" ") + unit - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/money.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/money.py deleted file mode 100644 index db47256841a7..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/money.py +++ /dev/null @@ -1,45 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { integer_part: "12" fractional_part: "05" currency: "$" } -> 12.05 $ - - Args: - decimal: DecimalFst - """ - - def __init__(self, decimal: GraphFst): - super().__init__(name="money", kind="verbalize") - unit = ( - pynutil.delete("currency:") - + delete_extra_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - graph = decimal.numbers + delete_space + unit - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/ordinal.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/ordinal.py deleted file mode 100644 index 96d8c24030d2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/ordinal.py +++ /dev/null @@ -1,81 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_DIGIT, - NEMO_NOT_QUOTE, - GraphFst, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinal, e.g. - ordinal { integer: "13" morphosyntactic_features: "e" } -> 13ᵉ - - Given 'special' terms for ordinals (e.g. siècle), renders - amount in conventional format. e.g. - - ordinal { integer: "13" morphosyntactic_features: "e/siècle" } -> XIIIᵉ - """ - - def __init__(self): - super().__init__(name="ordinal", kind="verbalize") - graph_integer = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - replace_suffix = pynini.union( - pynini.cross("e", "ᵉ"), # only delete first quote since there may be more features - pynini.cross("d", "ᵈ"), - pynini.cross("r", "ʳ"), - pynini.cross("s", "ˢ"), - ) - replace_suffix = pynutil.delete(" morphosyntactic_features: \"") + replace_suffix.plus - - graph_arabic = graph_integer + replace_suffix.plus - - # For roman. - graph_roman_digits = pynini.string_file(get_abs_path("data/roman/digits_large.tsv")).invert() - graph_roman_ties = pynini.string_file(get_abs_path("data/roman/ties_large.tsv")).invert() - graph_roman_hundreds = pynini.string_file(get_abs_path("data/roman/hundreds_large.tsv")).invert() - graph_roman_zero_digit = pynutil.delete("0") - - graph_roman_hundreds = NEMO_DIGIT ** 3 @ ( - graph_roman_hundreds - + pynini.union(graph_roman_ties, graph_roman_zero_digit) - + pynini.union(graph_roman_digits, graph_roman_zero_digit) - ) - graph_roman_ties = NEMO_DIGIT ** 2 @ ( - graph_roman_ties + pynini.union(graph_roman_digits, graph_roman_zero_digit) - ) - graph_roman_digits = NEMO_DIGIT @ graph_roman_digits - - graph_roman_integers = graph_roman_hundreds | graph_roman_ties | graph_roman_digits - - graph_roman = (graph_integer @ graph_roman_integers) + replace_suffix - graph_roman += pynini.cross("/", " ") + "siècle" - - graph = (graph_roman | graph_arabic) + pynutil.delete("\"") - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/telephone.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/telephone.py deleted file mode 100644 index c204bcc3897d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/telephone.py +++ /dev/null @@ -1,32 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { number_part: "02 33 43 53 22" } - -> 02 33 43 53 22 - """ - - def __init__(self): - super().__init__(name="telephone", kind="verbalize") - - number_part = pynutil.delete("number_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(number_part) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/time.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/time.py deleted file mode 100644 index 93e4886e58ed..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/time.py +++ /dev/null @@ -1,68 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.fr.utils import get_abs_path -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, e.g. - time { hours: "8" minutes: "30" suffix: "du matin"} -> 8 h 30 - time { hours: "8" minutes: "30" } -> 8 h 30 - time { hours: "8" minutes: "30" suffix: "du soir"} -> 20 h 30 - """ - - def __init__(self): - super().__init__(name="time", kind="verbalize") - - hour_to_night = pynini.string_file(get_abs_path("data/time/hour_to_night.tsv")) - - day_suffixes = pynutil.delete("suffix: \"am\"") - night_suffixes = pynutil.delete("suffix: \"pm\"") - - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_DIGIT, 1, 2) - + pynutil.delete("\"") - ) - minute = ( - pynutil.delete("minutes:") - + delete_extra_space - + pynutil.delete("\"") - + pynini.closure(NEMO_DIGIT, 1, 2) - + pynutil.delete("\"") - ) - - graph = hour + delete_extra_space + pynutil.insert("h") + minute.ques + delete_space + day_suffixes.ques - - graph |= ( - hour @ hour_to_night - + delete_extra_space - + pynutil.insert("h") - + minute.ques - + delete_space - + night_suffixes - ) - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/verbalize.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/verbalize.py deleted file mode 100644 index 9eec8eff90b8..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/verbalize.py +++ /dev/null @@ -1,64 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import GraphFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.date import DateFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.fraction import FractionFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.whitelist import WhiteListFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - """ - - def __init__(self): - super().__init__(name="verbalize", kind="verbalize") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - ordinal_graph = OrdinalFst().fst - decimal = DecimalFst() - decimal_graph = decimal.fst - fraction = FractionFst() - fraction_graph = fraction.fst - measure_graph = MeasureFst(decimal=decimal, cardinal=cardinal, fraction=fraction).fst - money_graph = MoneyFst(decimal=decimal).fst - time_graph = TimeFst().fst - date_graph = DateFst().fst - whitelist_graph = WhiteListFst().fst - telephone_graph = TelephoneFst().fst - electronic_graph = ElectronicFst().fst - graph = ( - time_graph - | date_graph - | money_graph - | measure_graph - | fraction_graph - | ordinal_graph - | decimal_graph - | cardinal_graph - | whitelist_graph - | telephone_graph - | electronic_graph - ) - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/verbalize_final.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/verbalize_final.py deleted file mode 100644 index 9753b785561b..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/verbalize_final.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import GraphFst, delete_extra_space, delete_space -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.fr.verbalizers.word import WordFst -from pynini.lib import pynutil - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now - """ - - def __init__(self): - super().__init__(name="verbalize_final", kind="verbalize") - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/whitelist.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/whitelist.py deleted file mode 100644 index 6b350062d8d5..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/whitelist.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_CHAR, - NEMO_SIGMA, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for verbalizing whitelist - e.g. tokens { name: "mrs." } -> mrs. - """ - - def __init__(self): - super().__init__(name="whitelist", kind="verbalize") - graph = ( - pynutil.delete("name:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = graph @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/word.py b/nemo_text_processing/inverse_text_normalization/fr/verbalizers/word.py deleted file mode 100644 index fa8f0f39d3d4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/fr/verbalizers/word.py +++ /dev/null @@ -1,37 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.fr.graph_utils import ( - NEMO_CHAR, - NEMO_SIGMA, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for verbalizing plain tokens - e.g. tokens { name: "sleep" } -> sleep - """ - - def __init__(self): - super().__init__(name="word", kind="verbalize") - chars = pynini.closure(NEMO_CHAR - " ", 1) - char = pynutil.delete("name:") + delete_space + pynutil.delete("\"") + chars + pynutil.delete("\"") - graph = char @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/inverse_normalize.py b/nemo_text_processing/inverse_text_normalization/inverse_normalize.py deleted file mode 100644 index a39131440cec..000000000000 --- a/nemo_text_processing/inverse_text_normalization/inverse_normalize.py +++ /dev/null @@ -1,148 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from argparse import ArgumentParser -from time import perf_counter -from typing import List - -from nemo_text_processing.text_normalization.data_loader_utils import load_file, write_file -from nemo_text_processing.text_normalization.normalize import Normalizer -from nemo_text_processing.text_normalization.token_parser import TokenParser - - -class InverseNormalizer(Normalizer): - """ - Inverse normalizer that converts text from spoken to written form. Useful for ASR postprocessing. - Input is expected to have no punctuation outside of approstrophe (') and dash (-) and be lower cased. - - Args: - lang: language specifying the ITN - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, lang: str = 'en', cache_dir: str = None, overwrite_cache: bool = False): - - if lang == 'en': - from nemo_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import ( - VerbalizeFinalFst, - ) - - elif lang == 'es': - from nemo_text_processing.inverse_text_normalization.es.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.inverse_text_normalization.es.verbalizers.verbalize_final import ( - VerbalizeFinalFst, - ) - - elif lang == 'pt': - from nemo_text_processing.inverse_text_normalization.pt.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.inverse_text_normalization.pt.verbalizers.verbalize_final import ( - VerbalizeFinalFst, - ) - - elif lang == 'ru': - from nemo_text_processing.inverse_text_normalization.ru.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.inverse_text_normalization.ru.verbalizers.verbalize_final import ( - VerbalizeFinalFst, - ) - - elif lang == 'de': - from nemo_text_processing.inverse_text_normalization.de.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.inverse_text_normalization.de.verbalizers.verbalize_final import ( - VerbalizeFinalFst, - ) - elif lang == 'fr': - from nemo_text_processing.inverse_text_normalization.fr.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.inverse_text_normalization.fr.verbalizers.verbalize_final import ( - VerbalizeFinalFst, - ) - elif lang == 'vi': - from nemo_text_processing.inverse_text_normalization.vi.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.inverse_text_normalization.vi.verbalizers.verbalize_final import ( - VerbalizeFinalFst, - ) - - self.tagger = ClassifyFst(cache_dir=cache_dir, overwrite_cache=overwrite_cache) - self.verbalizer = VerbalizeFinalFst() - self.parser = TokenParser() - self.lang = lang - - def inverse_normalize_list(self, texts: List[str], verbose=False) -> List[str]: - """ - NeMo inverse text normalizer - - Args: - texts: list of input strings - verbose: whether to print intermediate meta information - - Returns converted list of input strings - """ - return self.normalize_list(texts=texts, verbose=verbose) - - def inverse_normalize(self, text: str, verbose: bool) -> str: - """ - Main function. Inverse normalizes tokens from spoken to written form - e.g. twelve kilograms -> 12 kg - - Args: - text: string that may include semiotic classes - verbose: whether to print intermediate meta information - - Returns: written form - """ - return self.normalize(text=text, verbose=verbose) - - -def parse_args(): - parser = ArgumentParser() - input = parser.add_mutually_exclusive_group() - input.add_argument("--text", dest="input_string", help="input string", type=str) - input.add_argument("--input_file", dest="input_file", help="input file path", type=str) - parser.add_argument('--output_file', dest="output_file", help="output file path", type=str) - parser.add_argument( - "--language", help="language", choices=['en', 'de', 'es', 'pt', 'ru', 'fr', 'vi'], default="en", type=str - ) - parser.add_argument("--verbose", help="print info for debugging", action='store_true') - parser.add_argument("--overwrite_cache", help="set to True to re-create .far grammar files", action="store_true") - parser.add_argument( - "--cache_dir", - help="path to a dir with .far grammar file. Set to None to avoid using cache", - default=None, - type=str, - ) - return parser.parse_args() - - -if __name__ == "__main__": - args = parse_args() - start_time = perf_counter() - inverse_normalizer = InverseNormalizer( - lang=args.language, cache_dir=args.cache_dir, overwrite_cache=args.overwrite_cache - ) - print(f'Time to generate graph: {round(perf_counter() - start_time, 2)} sec') - - if args.input_string: - print(inverse_normalizer.inverse_normalize(args.input_string, verbose=args.verbose)) - elif args.input_file: - print("Loading data: " + args.input_file) - data = load_file(args.input_file) - - print("- Data: " + str(len(data)) + " sentences") - prediction = inverse_normalizer.inverse_normalize_list(data, verbose=args.verbose) - if args.output_file: - write_file(args.output_file, prediction) - print(f"- Denormalized. Writing out to {args.output_file}") - else: - print(prediction) diff --git a/nemo_text_processing/inverse_text_normalization/pt/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/__init__.py deleted file mode 100644 index c1586debd25f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.pt.taggers.tokenize_and_classify import ClassifyFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.verbalize_final import VerbalizeFinalFst diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/data/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/currency_plural.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/currency_plural.tsv deleted file mode 100644 index a89a763093ea..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/currency_plural.tsv +++ /dev/null @@ -1,5 +0,0 @@ -€ euros -£ libras esterlinas -US$ dólares americanos -$ dólares -R$ reais \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/currency_singular.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/currency_singular.tsv deleted file mode 100644 index 9ec77dc35654..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/currency_singular.tsv +++ /dev/null @@ -1,5 +0,0 @@ -€ euro -£ libra esterlina -US$ dólar americano -$ dólar -R$ real \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/data/electronic/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/domain.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/electronic/domain.tsv deleted file mode 100644 index ea547b890119..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/domain.tsv +++ /dev/null @@ -1,26 +0,0 @@ -com -es -uk -fr -net -br -in -ru -de -it -edu -co -ar -bo -cl -co -ec -fk -gf -fy -pe -py -sr -ve -uy -pt \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/server_name.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/electronic/server_name.tsv deleted file mode 100644 index 34ab709bb308..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/server_name.tsv +++ /dev/null @@ -1,11 +0,0 @@ -gmail g mail -gmail -nvidia n vidia -nvidia -outlook -hotmail -yahoo -aol -live -msn -live \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/symbols.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/electronic/symbols.tsv deleted file mode 100644 index 690a9ca427f1..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/electronic/symbols.tsv +++ /dev/null @@ -1,6 +0,0 @@ -. ponto -- traço -- hífen -_ traço baixo -_ underscore -/ barra \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/measurements_plural.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/measurements_plural.tsv deleted file mode 100755 index 6d2684afdf8b..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/measurements_plural.tsv +++ /dev/null @@ -1,56 +0,0 @@ -h horas -min minutos -s segundos -ms milissegundos -ns nanossegundos -μs microssegundos -t toneladas -kg quilos -kg quilogramas -g gramas -mg miligramas -μm micrômetros -nm nanômetros -mm milímetros -cm centímetros -cm² centímetros quadrado -cm³ centímetros cúbico -m metros -m² metros quadrados -m³ metros cúbicos -km quilômetros -km² quilômetros quadrados -ha hectares -kph quilômetros por hora -mph milhas por hora -m/s metros por segundo -l litros -ml mililitros -kgf quilogramas forças -kgf quilogramas força -% por cento -°F fahrenheit -°C celsius -°F graus fahrenheit -°C graus celsius -Hz hertz -kHz quilo hertz -MHz mega hertz -GHz giga hertz -W watts -kW quilowatts -MW megawatts -GW gigawatts -Wh watts hora -kWh quilowatts hora -MWh megawatts hora -GWh gigawatts hora -kV quilovolts -V volts -mV milivolts -A amperes -mA miliamperes -rpm rotações por minuto -db decibéis -cal calorias -kcal quilocalorias diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/measurements_singular.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/measurements_singular.tsv deleted file mode 100755 index bf7320e6242c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/measurements_singular.tsv +++ /dev/null @@ -1,55 +0,0 @@ -h hora -min minuto -s segundo -ms milissegundo -ns nanossegundo -μs microssegundo -t tonelada -kg quilo -kg quilograma -g grama -mg miligrama -μm micrômetro -nm nanômetro -mm milímetro -cm centímetro -cm² centímetro quadrado -cm³ centímetro cúbico -m metro -m² metro quadrado -m³ metro cúbico -km quilômetro -km² quilômetro quadrado -ha hectare -kph quilômetro por hora -mph milha por hora -m/s metro por segundo -l litro -ml mililitro -kgf quilograma força -% por cento -°F fahrenheit -°C celsius -°F grau fahrenheit -°C grau celsius -Hz hertz -kHz quilo hertz -MHz mega hertz -GHz giga hertz -W watt -kW quilowatt -MW megawatt -GW gigawatt -Wh watt hora -kWh quilowatt hora -MWh megawatt hora -GWh gigawatt hora -kV quilovolt -V volt -mV milivolt -A ampere -mA miliampere -rpm rotação por minuto -db decibel -cal caloria -kcal quilocaloria diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/months.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/months.tsv deleted file mode 100644 index ed1cf8d4f78c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/months.tsv +++ /dev/null @@ -1,12 +0,0 @@ -janeiro -fevereiro -março -abril -maio -junho -julho -agosto -setembro -outubro -novembro -dezembro diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/digit.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/digit.tsv deleted file mode 100644 index fda1b633b2fb..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/digit.tsv +++ /dev/null @@ -1,11 +0,0 @@ -um 1 -uma 1 -dois 2 -duas 2 -três 3 -quatro 4 -cinco 5 -seis 6 -sete 7 -oito 8 -nove 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/hundreds.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/hundreds.tsv deleted file mode 100644 index ff06089d3e67..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/hundreds.tsv +++ /dev/null @@ -1,17 +0,0 @@ -cento 1 -duzentos 2 -duzentas 2 -trezentos 3 -trezentas 3 -quatrocentos 4 -quatrocentas 4 -quinhentos 5 -quinhentas 5 -seiscentos 6 -seiscentas 6 -setecentos 7 -setecentas 7 -oitocentos 8 -oitocentas 8 -novecentos 9 -novecentas 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/onehundred.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/onehundred.tsv deleted file mode 100644 index 1b5f9fa05302..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/onehundred.tsv +++ /dev/null @@ -1 +0,0 @@ -cem 100 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/teen.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/teen.tsv deleted file mode 100644 index 6bc21cccfc30..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/teen.tsv +++ /dev/null @@ -1,11 +0,0 @@ -dez 10 -onze 11 -doze 12 -treze 13 -catorze 14 -quatorze 14 -quinze 15 -dezesseis 16 -dezessete 17 -dezoito 18 -dezenove 19 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/ties.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/ties.tsv deleted file mode 100644 index 63ff93c83220..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/ties.tsv +++ /dev/null @@ -1,8 +0,0 @@ -vinte 2 -trinta 3 -quarenta 4 -cinquenta 5 -sessenta 6 -setenta 7 -oitenta 8 -noventa 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/twenties.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/twenties.tsv deleted file mode 100644 index c72178c15ed1..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/twenties.tsv +++ /dev/null @@ -1,9 +0,0 @@ -vinte um 21 -vinte dois 22 -vinte três 23 -vinte quatro 24 -vinte cinco 25 -vinte seis 26 -vinte sete 27 -vinte oito 28 -vinte nove 29 diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/zero.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/numbers/zero.tsv deleted file mode 100644 index c479272d4039..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/numbers/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -zero 0 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/digit.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/digit.tsv deleted file mode 100644 index ad97cc411414..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/digit.tsv +++ /dev/null @@ -1,18 +0,0 @@ -primeiro 1 -primeira 1 -segundo 2 -segunda 2 -terceiro 3 -terceira 3 -quarto 4 -quarta 4 -quinto 5 -quinta 5 -sexto 6 -sexta 6 -sétimo 7 -sétima 7 -oitavo 8 -oitava 8 -nono 9 -nona 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/hundreds.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/hundreds.tsv deleted file mode 100644 index b7b15ee92488..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/hundreds.tsv +++ /dev/null @@ -1,28 +0,0 @@ -centésimo 1 -centésima 1 -ducentésimo 2 -ducentésima 2 -tricentésimo 3 -tricentésima 3 -trecentésimo 3 -trecentésima 3 -quadringentésimo 4 -quadringentésima 4 -quingentésimo 5 -quingentésima 5 -sexcentésimo 6 -sexcentésima 6 -seiscentésimo 6 -seiscentésima 6 -septingentésimo 7 -septingentésima 7 -setingentésimo 7 -setingentésima 7 -octingentésimo 8 -octingentésima 8 -octogentésimo 8 -octogentésima 8 -noningentésimo 9 -noningentésima 9 -nongentésimo 9 -nongentésima 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/ties.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/ties.tsv deleted file mode 100644 index 55c4c4ee2fa3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/ordinals/ties.tsv +++ /dev/null @@ -1,20 +0,0 @@ -décimo 1 -décima 1 -vigésimo 2 -vigésima 2 -trigésimo 3 -trigésima 3 -quadragésimo 4 -quadragésima 4 -quinquagésimo 5 -quinquagésima 5 -sexagésimo 6 -sexagésima 6 -septuagésimo 7 -septuagésima 7 -setuagésimo 7 -setuagésima 7 -octogésimo 8 -octogésima 8 -nonagésimo 9 -nonagésima 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/time/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/data/time/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/time/hour_to_am.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/time/hour_to_am.tsv deleted file mode 100644 index c22366ba8665..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/time/hour_to_am.tsv +++ /dev/null @@ -1 +0,0 @@ -1 0 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/time/hour_to_pm.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/time/hour_to_pm.tsv deleted file mode 100644 index 548045d94c60..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/time/hour_to_pm.tsv +++ /dev/null @@ -1 +0,0 @@ -1 12 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/time/hours_to.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/time/hours_to.tsv deleted file mode 100644 index 5742d596b64d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/time/hours_to.tsv +++ /dev/null @@ -1,23 +0,0 @@ -0 23 -2 1 -3 2 -4 3 -5 4 -6 5 -7 6 -8 7 -9 8 -10 9 -11 10 -12 11 -13 12 -14 13 -15 14 -16 15 -17 16 -18 17 -19 18 -20 19 -21 20 -22 21 -23 22 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/time/minutes_to.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/time/minutes_to.tsv deleted file mode 100644 index d8516a9f83ce..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/time/minutes_to.tsv +++ /dev/null @@ -1,59 +0,0 @@ -01 59 -02 58 -03 57 -04 56 -05 55 -06 54 -07 53 -08 52 -09 51 -10 50 -11 49 -12 48 -13 47 -14 46 -15 45 -16 44 -17 43 -18 42 -19 41 -20 40 -21 39 -22 38 -23 37 -24 36 -25 35 -26 34 -27 33 -28 32 -29 31 -30 30 -31 29 -32 28 -33 27 -34 26 -35 25 -36 24 -37 23 -38 22 -39 21 -40 20 -41 19 -42 18 -43 17 -44 16 -45 15 -46 14 -47 13 -48 12 -49 11 -50 10 -51 09 -52 08 -53 07 -54 06 -55 05 -56 04 -57 03 -58 02 -59 01 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/time/time_suffix_am.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/time/time_suffix_am.tsv deleted file mode 100644 index 95394d7a6145..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/time/time_suffix_am.tsv +++ /dev/null @@ -1,2 +0,0 @@ -da madrugada da madrugada -da manhã da manhã \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/time/time_suffix_pm.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/time/time_suffix_pm.tsv deleted file mode 100644 index 18c7c994b020..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/time/time_suffix_pm.tsv +++ /dev/null @@ -1,2 +0,0 @@ -da tarde da tarde -da noite da noite \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/data/whitelist.tsv b/nemo_text_processing/inverse_text_normalization/pt/data/whitelist.tsv deleted file mode 100644 index bd82088f7990..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/data/whitelist.tsv +++ /dev/null @@ -1,5 +0,0 @@ -segunda-feira segunda feira -terça-feira terça feira -quarta-feira quarta feira -quinta-feira quinta feira -sexta-feira sexta feira \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/cardinal.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/cardinal.py deleted file mode 100644 index 5ff16a6e0f46..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/cardinal.py +++ /dev/null @@ -1,385 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - NEMO_SPACE, - NEMO_WHITE_SPACE, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals - e.g. menos veintitrés -> cardinal { negative: "-" integer: "23"} - This class converts cardinals up to (but not including) "un cuatrillón", - i.e up to "one septillion" in English (10^{24}). - Cardinals below ten are not converted (in order to avoid - "vivo em uma casa" --> "vivo em 1 casa" and any other odd conversions.) - - Although technically Portuguese grammar requires that "e" only comes after - "10s" numbers (ie. "trinta", ..., "noventa"), these rules will convert - numbers even with "e" in an ungrammatical place (because "e" is ignored - inside cardinal numbers). - e.g. "mil e uma" -> cardinal { integer: "1001"} - e.g. "cento e uma" -> cardinal { integer: "101"} - """ - - def __init__(self, use_strict_e=False): - """ - :param use_strict_e: When True forces to have the separator "e" in the right places - """ - super().__init__(name="cardinal", kind="classify") - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - graph_one_hundred = pynini.string_file(get_abs_path("data/numbers/onehundred.tsv")) - graph_hundreds = pynini.string_file(get_abs_path("data/numbers/hundreds.tsv")) - - graph = None - - if not use_strict_e: - graph_hundred_component = graph_hundreds | pynutil.insert("0") - graph_hundred_component += delete_space - graph_hundred_component += pynini.union( - graph_twenties | graph_teen | pynutil.insert("00"), - (graph_ties | pynutil.insert("0")) + delete_space + (graph_digit | pynutil.insert("0")), - ) - graph_hundred_component = pynini.union(graph_hundred_component, graph_one_hundred) - - graph_hundred_component_at_least_one_none_zero_digit = graph_hundred_component @ ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT) - ) - - graph_thousands = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("mil"), - pynutil.insert("001") + pynutil.delete("mil"), # because we say 'mil', not 'hum mil' - pynutil.insert("000", weight=0.01), - ) - - graph_milhoes = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("milhão") | pynutil.delete("milhões")), - pynutil.insert("000", weight=0.01), - ) - - graph_bilhoes = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("bilhão") | pynutil.delete("bilhões")), - pynutil.insert("000", weight=0.01), - ) - - graph_trilhoes = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("trilhão") | pynutil.delete("trilhões")), - pynutil.insert("000", weight=0.01), - ) - - graph_quatrilhoes = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("quatrilhão") | pynutil.delete("quatrilhões")), - pynutil.insert("000", weight=0.01), - ) - - graph_quintilhoes = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("quintilhão") | pynutil.delete("quintilhões")), - pynutil.insert("000", weight=0.01), - ) - - graph_sextilhoes = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + (pynutil.delete("sextilhão") | pynutil.delete("sextilhões")), - pynutil.insert("000", weight=0.01), - ) - - graph = pynini.union( - graph_sextilhoes - + delete_space - + graph_quintilhoes - + delete_space - + graph_quatrilhoes - + delete_space - + graph_trilhoes - + delete_space - + graph_bilhoes - + delete_space - + graph_milhoes - + delete_space - + graph_thousands - + delete_space - + graph_hundred_component, - graph_zero, - ) - - graph = graph @ pynini.union( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT), - "0", - ) - - graph = ( - pynini.cdrewrite(pynutil.delete("e"), NEMO_SPACE, NEMO_SPACE, NEMO_SIGMA) - @ (NEMO_ALPHA + NEMO_SIGMA) - @ graph - ) - - else: - graph_e = ( - pynutil.delete(NEMO_WHITE_SPACE.plus) + pynutil.delete("e") + pynutil.delete(NEMO_WHITE_SPACE.plus) - ) - - graph_ties_component = pynini.union( - graph_teen | graph_twenties, - graph_ties + ((graph_e + graph_digit) | pynutil.insert("0")), - pynutil.add_weight(pynutil.insert("0") + graph_digit, 0.1), - ) @ (pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT)) - - graph_hundreds_except_hundred = (pynini.project(graph_hundreds, "input") - "cento") @ graph_hundreds - - graph_hundred_component_prefix_e = pynini.union( - graph_one_hundred, - pynutil.add_weight(graph_hundreds_except_hundred + pynutil.insert("00"), 0.1), - pynutil.insert("0") + graph_ties_component, - ) @ (pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT)) - graph_hundred_component_prefix_e = graph_hundred_component_prefix_e.optimize() - - graph_hundred_component_no_prefix = pynini.union(graph_hundreds + graph_e + graph_ties_component,) @ ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT) - ) - graph_hundred_component_no_prefix = graph_hundred_component_no_prefix.optimize() - - graph_mil_prefix_e = pynini.union( - # because we say 'mil', not 'hum mil' - ( - (graph_hundred_component_prefix_e + delete_space + pynutil.delete("mil")) - | (pynutil.insert("001", weight=0.1) + pynutil.delete("mil")) - ) - + ( - (graph_e + graph_hundred_component_prefix_e) - | (delete_space + graph_hundred_component_no_prefix) - | pynutil.insert("000", weight=0.1) - ) - ) - - graph_mil_no_prefix = pynini.union( - ( - (graph_hundred_component_no_prefix + delete_space + pynutil.delete("mil")) - | pynutil.insert("000", weight=0.1) - ) - + ( - (graph_e + graph_hundred_component_prefix_e) - | (delete_space + graph_hundred_component_no_prefix) - | pynutil.insert("000", weight=0.1) - ) - ) - - graph_milhao_prefix_e = pynini.union( - ( - graph_hundred_component_prefix_e - + delete_space - + (pynutil.delete("milhão") | pynutil.delete("milhões")) - ) - + ((graph_e + graph_mil_prefix_e) | (delete_space + graph_mil_no_prefix)) - ) - - graph_milhao_no_prefix = pynini.union( - ( - ( - graph_hundred_component_no_prefix - + delete_space - + (pynutil.delete("milhão") | pynutil.delete("milhões")) - ) - | pynutil.insert("000", weight=0.1) - ) - + ((graph_e + graph_mil_prefix_e) | (delete_space + graph_mil_no_prefix)) - ) - - graph_bilhao_prefix_e = pynini.union( - ( - graph_hundred_component_prefix_e - + delete_space - + (pynutil.delete("bilhão") | pynutil.delete("bilhões")) - ) - + ((graph_e + graph_milhao_prefix_e) | (delete_space + graph_milhao_no_prefix)) - ) - - graph_bilhao_no_prefix = pynini.union( - ( - ( - graph_hundred_component_no_prefix - + delete_space - + (pynutil.delete("bilhão") | pynutil.delete("bilhões")) - ) - | pynutil.insert("000", weight=0.1) - ) - + ((graph_e + graph_milhao_prefix_e) | (delete_space + graph_milhao_no_prefix)) - ) - - graph_trilhao_prefix_e = pynini.union( - ( - graph_hundred_component_prefix_e - + delete_space - + (pynutil.delete("trilhão") | pynutil.delete("trilhões")) - ) - + ((graph_e + graph_bilhao_prefix_e) | (delete_space + graph_bilhao_no_prefix)) - ) - - graph_trilhao_no_prefix = pynini.union( - ( - ( - graph_hundred_component_no_prefix - + delete_space - + (pynutil.delete("trilhão") | pynutil.delete("trilhões")) - ) - | pynutil.insert("000", weight=0.1) - ) - + ((graph_e + graph_bilhao_prefix_e) | (delete_space + graph_bilhao_no_prefix)) - ) - - graph_quatrilhao_prefix_e = pynini.union( - ( - graph_hundred_component_prefix_e - + delete_space - + (pynutil.delete("quatrilhão") | pynutil.delete("quatrilhões")) - ) - + ((graph_e + graph_trilhao_prefix_e) | (delete_space + graph_trilhao_no_prefix)) - ) - - graph_quatrilhao_no_prefix = pynini.union( - ( - ( - graph_hundred_component_no_prefix - + delete_space - + (pynutil.delete("quatrilhão") | pynutil.delete("quatrilhões")) - ) - | pynutil.insert("000", weight=0.1) - ) - + ((graph_e + graph_trilhao_prefix_e) | (delete_space + graph_trilhao_no_prefix)) - ) - - graph_quintilhao_prefix_e = pynini.union( - ( - graph_hundred_component_prefix_e - + delete_space - + (pynutil.delete("quintilhão") | pynutil.delete("quintilhões")) - ) - + ((graph_e + graph_quatrilhao_prefix_e) | (delete_space + graph_quatrilhao_no_prefix)) - ) - - graph_quintilhao_no_prefix = pynini.union( - ( - ( - graph_hundred_component_no_prefix - + delete_space - + (pynutil.delete("quintilhão") | pynutil.delete("quintilhões")) - ) - | pynutil.insert("000", weight=0.1) - ) - + ((graph_e + graph_quatrilhao_prefix_e) | (delete_space + graph_quatrilhao_no_prefix)) - ) - - graph_sextilhao_prefix_e = pynini.union( - ( - graph_hundred_component_prefix_e - + delete_space - + (pynutil.delete("sextilhão") | pynutil.delete("sextilhões")) - ) - + ((graph_e + graph_quintilhao_prefix_e) | (delete_space + graph_quintilhao_no_prefix)) - ) - - graph_sextilhao_no_prefix = pynini.union( - ( - ( - graph_hundred_component_no_prefix - + delete_space - + (pynutil.delete("sextilhão") | pynutil.delete("sextilhões")) - ) - | pynutil.insert("000", weight=0.1) - ) - + ((graph_e + graph_quintilhao_prefix_e) | (delete_space + graph_quintilhao_no_prefix)) - ) - - graph = pynini.union( - graph_sextilhao_no_prefix, - graph_sextilhao_prefix_e, - graph_quintilhao_prefix_e, - graph_quatrilhao_prefix_e, - graph_trilhao_prefix_e, - graph_bilhao_prefix_e, - graph_milhao_prefix_e, - graph_mil_prefix_e, - graph_hundred_component_prefix_e, - graph_ties_component, - graph_zero, - ).optimize() - - graph = graph @ pynini.union( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT), - "0", - ) - - graph = graph.optimize() - self.graph_no_exception = graph - - # save self.numbers_up_to_thousand for use in DecimalFst - digits_up_to_thousand = NEMO_DIGIT | (NEMO_DIGIT ** 2) | (NEMO_DIGIT ** 3) - numbers_up_to_thousand = pynini.compose(graph, digits_up_to_thousand).optimize() - self.numbers_up_to_thousand = numbers_up_to_thousand - - # save self.numbers_up_to_million for use in DecimalFst - digits_up_to_million = ( - NEMO_DIGIT - | (NEMO_DIGIT ** 2) - | (NEMO_DIGIT ** 3) - | (NEMO_DIGIT ** 4) - | (NEMO_DIGIT ** 5) - | (NEMO_DIGIT ** 6) - ) - numbers_up_to_million = pynini.compose(graph, digits_up_to_million).optimize() - self.numbers_up_to_million = numbers_up_to_million - - # save self.digits_from_year for use in DateFst - digits_1_2099 = [str(digits) for digits in range(1, 2100)] - digits_from_year = (numbers_up_to_million @ pynini.union(*digits_1_2099)).optimize() - self.digits_from_year = digits_from_year - - # don't convert cardinals from zero to nine inclusive - graph_exception = pynini.project(pynini.union(graph_digit, graph_zero), 'input') - - self.graph = (pynini.project(graph, "input") - graph_exception.arcsort()) @ graph - - optional_minus_graph = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("menos", "\"-\"") + NEMO_SPACE, 0, 1 - ) - - final_graph = optional_minus_graph + pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/date.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/date.py deleted file mode 100644 index 4b891ea98a42..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/date.py +++ /dev/null @@ -1,85 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, - e.g. primeiro de janeiro -> date { day: "1" month: "janeiro" } - e.g. um de janeiro -> date { day: "1" month: "janeiro" } - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="date", kind="classify") - - digits_from_year = cardinal.digits_from_year - - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - - graph_1_to_100 = pynini.union( - pynutil.insert("0") + graph_digit, - graph_twenties, - graph_teen, - (graph_ties + pynutil.insert("0")), - (graph_ties + pynutil.delete(" e ") + graph_digit), - ) - - digits_1_to_31 = [str("{:0>2d}").format(digits) for digits in range(1, 32)] - graph_1_to_31 = graph_1_to_100 @ pynini.union(*digits_1_to_31) - # can use "primeiro" for 1st day of the month - graph_1_to_31 = pynini.union(graph_1_to_31, pynini.cross("primeiro", "01")) - - day_graph = pynutil.insert("day: \"") + graph_1_to_31 + pynutil.insert("\"") - - month_name_graph = pynini.string_file(get_abs_path("data/months.tsv")) - month_name_graph = pynutil.insert("month: \"") + month_name_graph + pynutil.insert("\"") - - # vinte do oito -> 20/08 - digits_1_to_12 = [str("{:0>2d}").format(digits) for digits in range(1, 13)] - graph_1_to_12 = graph_1_to_100 @ pynini.union(*digits_1_to_12) - month_number_graph = pynutil.insert("month: \"") + graph_1_to_12 + pynutil.insert("\"") - - graph_dm = day_graph + delete_space + pynutil.delete("de") + delete_extra_space + month_name_graph - - graph_dm |= ( - day_graph - + delete_space - + pynutil.delete("do") - + delete_extra_space - + month_number_graph - + pynutil.insert(" morphosyntactic_features: \"/\"") - ) - - graph_year = ( - delete_space - + pynutil.delete("de") - + delete_extra_space - + pynutil.insert("year: \"") - + digits_from_year - + pynutil.insert("\"") - ) - graph_dmy = graph_dm + graph_year.ques - - final_graph = graph_dmy - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/decimal.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/decimal.py deleted file mode 100644 index dab779965ed3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/decimal.py +++ /dev/null @@ -1,119 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -def get_quantity(decimal: 'pynini.FstLike', cardinal_up_to_million: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. one million -> integer_part: "1" quantity: "million" - e.g. one point five million -> integer_part: "1" fractional_part: "5" quantity: "million" - - Args: - decimal: decimal FST - cardinal_up_to_million: cardinal FST - """ - numbers = cardinal_up_to_million @ ( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT) - ) - - suffix = pynini.union( - "milhão", - "milhões", - "bilhão", - "bilhões", - "trilhão", - "trilhões", - "quatrilhão", - "quatrilhões", - "quintilhão", - "quintilhões", - "sextilhão", - "sextilhões", - ) - res = ( - pynutil.insert("integer_part: \"") - + numbers - + pynutil.insert("\"") - + delete_extra_space - + pynutil.insert("quantity: \"") - + suffix - + pynutil.insert("\"") - ) - res |= decimal + delete_extra_space + pynutil.insert("quantity: \"") + suffix + pynutil.insert("\"") - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal - Decimal point is either "." or ",", determined by whether "ponto" or "vírgula" is spoken. - e.g. menos um vírgula dois seis -> decimal { negative: "true" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" } - e.g. menos um ponto dois seis -> decimal { negative: "true" integer_part: "1" morphosyntactic_features: "." fractional_part: "26" } - - This decimal rule assumes that decimals can be pronounced as: - (a cardinal) + ('vírgula' or 'ponto') plus (any sequence of cardinals <1000, including 'zero') - - Also writes large numbers in shortened form, e.g. - e.g. um vírgula dois seis milhões -> decimal { negative: "false" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" quantity: "milhões" } - e.g. dois milhões -> decimal { negative: "false" integer_part: "2" quantity: "milhões" } - e.g. mil oitcentos e vinte e quatro milhões -> decimal { negative: "false" integer_part: "1824" quantity: "milhões" } - Args: - cardinal: CardinalFst - - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="decimal", kind="classify") - - # number after decimal point can be any series of cardinals <1000, including 'zero' - graph_decimal = cardinal.numbers_up_to_thousand - graph_decimal = pynini.closure(graph_decimal + delete_space) + graph_decimal - self.graph = graph_decimal - - # decimal point can be denoted by 'vírgula' or 'ponto' - decimal_point = pynini.cross("vírgula", "morphosyntactic_features: \",\"") - decimal_point |= pynini.cross("ponto", "morphosyntactic_features: \".\"") - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("menos", "\"true\"") + delete_extra_space, 0, 1 - ) - - graph_fractional = pynutil.insert("fractional_part: \"") + graph_decimal + pynutil.insert("\"") - - cardinal_graph = cardinal.graph_no_exception | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - final_graph_wo_sign = ( - pynini.closure(graph_integer + delete_extra_space, 0, 1) - + decimal_point - + delete_extra_space - + graph_fractional - ) - final_graph = optional_graph_negative + final_graph_wo_sign - - self.final_graph_wo_negative = final_graph_wo_sign | get_quantity( - final_graph_wo_sign, cardinal.numbers_up_to_million - ) - final_graph |= optional_graph_negative + get_quantity(final_graph_wo_sign, cardinal.numbers_up_to_million) - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/electronic.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/electronic.py deleted file mode 100644 index aa152b116a20..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/electronic.py +++ /dev/null @@ -1,96 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_ALPHA, GraphFst, insert_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying 'electronic' semiotic classes, i.e. - email address (which get converted to "username" and "domain" fields), - and URLS (which get converted to a "protocol" field). - e.g. c d f um arroba a b c ponto e d u -> tokens { electronic { username: "cdf1" domain: "abc.edu" } } - e.g. dáblio dáblio dáblio a b c ponto e d u -> tokens { electronic { protocol: "www.abc.edu" } } - """ - - def __init__(self): - super().__init__(name="electronic", kind="classify") - - delete_extra_space = pynutil.delete(" ") - alpha_num = ( - NEMO_ALPHA - | pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - ) - - symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")).invert() - - accepted_username = alpha_num | symbols - process_dot = pynini.cross("ponto", ".") - username = ( - pynutil.insert("username: \"") - + alpha_num - + delete_extra_space - + pynini.closure(accepted_username + delete_extra_space) - + alpha_num - + pynutil.insert("\"") - ) - single_alphanum = pynini.closure(alpha_num + delete_extra_space) + alpha_num - server = single_alphanum | pynini.string_file(get_abs_path("data/electronic/server_name.tsv")).invert() - domain = single_alphanum | pynini.string_file(get_abs_path("data/electronic/domain.tsv")).invert() - domain_graph = ( - pynutil.insert("domain: \"") - + server - + delete_extra_space - + process_dot - + delete_extra_space - + domain - + pynutil.insert("\"") - ) - graph = ( - username + delete_extra_space + pynutil.delete("arroba") + insert_space + delete_extra_space + domain_graph - ) - - ############# url ### - protocol_end = pynini.cross(pynini.union("www", "w w w", "dáblio dáblio dáblio"), "www") - protocol_start = pynini.cross(pynini.union("http", "h t t p", "agá tê tê pê"), "http") - protocol_start |= pynini.cross(pynini.union("https", "h t t p s", "agá tê tê pê ésse"), "https") - protocol_start += pynini.cross(" dois pontos barra barra ", "://") - - # e.g. .com, .es - ending = ( - delete_extra_space - + symbols - + delete_extra_space - + (domain | pynini.closure(accepted_username + delete_extra_space) + accepted_username) - ) - - protocol = ( - pynini.closure(protocol_start, 0, 1) - + protocol_end - + delete_extra_space - + process_dot - + delete_extra_space - + (pynini.closure(delete_extra_space + accepted_username, 1) | server) - + pynini.closure(ending, 1) - ) - protocol = pynutil.insert("protocol: \"") + protocol + pynutil.insert("\"") - graph |= protocol - ######## - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/measure.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/measure.py deleted file mode 100644 index 7b6f1015ad79..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/measure.py +++ /dev/null @@ -1,95 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, -) -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure - e.g. menos doze quilogramas -> measure { cardinal { negative: "true" integer: "12" } units: "kg" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="measure", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - - graph_unit_singular = pynini.string_file(get_abs_path("data/measurements_singular.tsv")).invert() - graph_unit_plural = pynini.string_file(get_abs_path("data/measurements_plural.tsv")).invert() - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("menos", "\"true\"") + delete_extra_space, 0, 1 - ) - - unit_singular = convert_space(graph_unit_singular) - unit_plural = convert_space(graph_unit_plural) - unit_misc = pynutil.insert("/") + pynutil.delete("por") + delete_space + convert_space(graph_unit_singular) - - unit_singular = ( - pynutil.insert("units: \"") - + (unit_singular | unit_misc | pynutil.add_weight(unit_singular + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - unit_plural = ( - pynutil.insert("units: \"") - + (unit_plural | unit_misc | pynutil.add_weight(unit_plural + delete_space + unit_misc, 0.01)) - + pynutil.insert("\"") - ) - - subgraph_decimal = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + decimal.final_graph_wo_negative - + pynutil.insert(" }") - + delete_extra_space - + unit_plural - ) - subgraph_cardinal = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + ((NEMO_SIGMA - "um" - "uma") @ cardinal_graph) - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit_plural - ) - subgraph_cardinal |= ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + (pynini.cross("um", "1") | pynini.cross("uma", "1")) - + pynutil.insert("\"") - + pynutil.insert(" }") - + delete_extra_space - + unit_singular - ) - - final_graph = subgraph_decimal | subgraph_cardinal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/money.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/money.py deleted file mode 100644 index cc3639438b83..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/money.py +++ /dev/null @@ -1,127 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - convert_space, - delete_extra_space, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money - e.g. doze dólares e cinco centavos -> money { integer_part: "12" fractional_part: "05" currency: "$" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="money", kind="classify") - # quantity, integer_part, fractional_part, currency - - cardinal_graph = cardinal.graph_no_exception - graph_decimal_final = decimal.final_graph_wo_negative - - unit_singular = pynini.string_file(get_abs_path("data/currency_singular.tsv")).invert() - unit_plural = pynini.string_file(get_abs_path("data/currency_plural.tsv")).invert() - - graph_unit_singular = pynutil.insert("currency: \"") + convert_space(unit_singular) + pynutil.insert("\"") - graph_unit_plural = pynutil.insert("currency: \"") + convert_space(unit_plural) + pynutil.insert("\"") - - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - # twelve dollars (and) fifty cents, zero cents - cents_standalone = ( - pynutil.insert("morphosyntactic_features: \",\"") # always use a comma in the decimal - + insert_space - + pynutil.insert("fractional_part: \"") - + pynini.union( - pynutil.add_weight(((NEMO_SIGMA - "um" - "uma") @ cardinal_graph), -0.7) - @ add_leading_zero_to_double_digit - + delete_space - + pynutil.delete(pynini.union("centavos")), - pynini.cross("um", "01") + delete_space + pynutil.delete(pynini.union("centavo")), - ) - + pynutil.insert("\"") - ) - - optional_cents_standalone = pynini.closure( - delete_space - + pynini.closure((pynutil.delete("com") | pynutil.delete('e')) + delete_space, 0, 1) - + insert_space - + cents_standalone, - 0, - 1, - ) - - # twelve dollars fifty, only after integer - # setenta e cinco dólares com sessenta e três ~ $75,63 - optional_cents_suffix = pynini.closure( - delete_extra_space - + pynutil.insert("morphosyntactic_features: \",\"") # always use a comma in the decimal - + insert_space - + pynutil.insert("fractional_part: \"") - + pynini.closure((pynutil.delete("com") | pynutil.delete('e')) + delete_space, 0, 1) - + pynutil.add_weight(cardinal_graph @ add_leading_zero_to_double_digit, -0.7) - + pynutil.insert("\""), - 0, - 1, - ) - - graph_integer = ( - pynutil.insert("integer_part: \"") - + ((NEMO_SIGMA - "um" - "uma") @ cardinal_graph) - + pynutil.insert("\"") - + delete_extra_space - + graph_unit_plural - + (optional_cents_standalone | optional_cents_suffix) - ) - graph_integer |= ( - pynutil.insert("integer_part: \"") - + (pynini.cross("um", "1") | pynini.cross("uma", "1")) - + pynutil.insert("\"") - + delete_extra_space - + graph_unit_singular - + (optional_cents_standalone | optional_cents_suffix) - ) - - graph_cents_standalone = pynini.union( - pynutil.insert("currency: \"R$\" integer_part: \"0\" ") + cents_standalone, - pynutil.add_weight( - pynutil.insert("integer_part: \"0\" ") - + cents_standalone - + delete_extra_space - + pynutil.delete("de") - + delete_space - + graph_unit_singular, - -0.1, - ), - ) - - graph_decimal = ( - graph_decimal_final + delete_extra_space + (pynutil.delete("de") + delete_space).ques + graph_unit_plural - ) - graph_decimal |= graph_cents_standalone - final_graph = graph_integer | graph_decimal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/ordinal.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/ordinal.py deleted file mode 100644 index ff7f3fbf02fa..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/ordinal.py +++ /dev/null @@ -1,84 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal - vigésimo primeiro -> ordinal { integer: "21" morphosyntactic_features: "o" } - This class converts ordinal up to "milésimo" (one thousandth) exclusive. - - Cardinals below ten are not converted (in order to avoid - e.g. "primero fez ..." -> "1º fez...", "segunda guerra mundial" -> "2ª guerra mundial" - and any other odd conversions.) - - This FST also records the ending of the ordinal (called "morphosyntactic_features"): - either "o" or "a". - - Args: - cardinal: CardinalFst - """ - - def __init__(self): - super().__init__(name="ordinal", kind="classify") - - graph_digit = pynini.string_file(get_abs_path("data/ordinals/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/ordinals/ties.tsv")) - graph_hundreds = pynini.string_file(get_abs_path("data/ordinals/hundreds.tsv")) - - ordinal_graph_union = pynini.union( - pynutil.add_weight(graph_digit, 0.4), - pynutil.add_weight(graph_ties + ((delete_space + graph_digit) | pynutil.insert("0")), 0.2), - graph_hundreds - + ((delete_space + graph_ties) | pynutil.insert("0")) - + ((delete_space + graph_digit) | pynutil.insert("0")), - ) - - accept_o_endings = NEMO_SIGMA + pynini.accep("o") - accept_a_endings = NEMO_SIGMA + pynini.accep("a") - - ordinal_graph_o = accept_o_endings @ ordinal_graph_union - ordinal_graph_a = accept_a_endings @ ordinal_graph_union - - # 'optional_numbers_in_front' have negative weight so we always - # include them if they're there - optional_in_front = (pynutil.add_weight(ordinal_graph_union, -0.1) + delete_space.closure()).closure() - graph_o_suffix = optional_in_front + ordinal_graph_o - graph_a_suffix = optional_in_front + ordinal_graph_a - - # don't convert ordinals from one to nine inclusive - graph_exception = pynini.project(pynini.union(graph_digit), 'input') - graph_o_suffix = (pynini.project(graph_o_suffix, "input") - graph_exception.arcsort()) @ graph_o_suffix - graph_a_suffix = (pynini.project(graph_a_suffix, "input") - graph_exception.arcsort()) @ graph_a_suffix - - graph = ( - pynutil.insert("integer: \"") - + graph_o_suffix - + pynutil.insert("\"") - + pynutil.insert(" morphosyntactic_features: \"o\"") - ) - graph |= ( - pynutil.insert("integer: \"") - + graph_a_suffix - + pynutil.insert("\"") - + pynutil.insert(" morphosyntactic_features: \"a\"") - ) - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/punctuation.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/punctuation.py deleted file mode 100644 index cb5285452954..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/punctuation.py +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class PunctuationFst(GraphFst): - """ - Finite state transducer for classifying punctuation - e.g. a, -> tokens { name: "a" } tokens { name: "," } - """ - - def __init__(self): - super().__init__(name="punctuation", kind="classify") - - s = "!#$%&\'()*+,-./:;<=>?@^_`{|}~" - punct = pynini.union(*s) - - graph = pynutil.insert("name: \"") + punct + pynutil.insert("\"") - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/telephone.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/telephone.py deleted file mode 100755 index a1ad2d07585d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/telephone.py +++ /dev/null @@ -1,131 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone numbers, e.g. - um dois um dois três quatro cinco seis sete oito nove -> { number_part: "(12) 12345-6789" }. - If 11 digits are spoken, they are grouped as 2+5+4 (eg. (12) 34567-8901). - If 10 digits are spoken, they are grouped as 2+4+4 (eg. (12) 3456-7890). - If 9 digits are spoken, they are grouped as 5+4 (eg. 12345-6789). - If 8 digits are spoken, they are grouped as 4+4 (eg. 1234-5678). - In portuguese, digits are generally spoken individually, or as 2-digit numbers, - eg. "trinta e quatro oitenta e dois" = "3482", - "meia sete vinte" = "6720". - """ - - def __init__(self): - super().__init__(name="telephone", kind="classify") - - # create `single_digits` and `double_digits` graphs as these will be - # the building blocks of possible telephone numbers - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_half = pynini.cross("meia", "6") - - graph_all_digits = pynini.union(graph_digit, graph_half, graph_zero) - - single_digits = pynini.invert(graph_all_digits).optimize() - - double_digits = ( - pynini.union( - graph_teen | graph_twenties, - (graph_ties + pynutil.insert("0")), - (graph_ties + delete_space + pynutil.delete("e") + delete_space + graph_digit), - (graph_all_digits + delete_space + graph_all_digits), - ) - .invert() - .optimize() - ) - - # define `eleven_digit_graph`, `ten_digit_graph`, `nine_digit_graph`, `eight_digit_graph` - # which accept telephone numbers spoken (1) only with single digits, - # or (2) spoken with double digits (and sometimes single digits) - - # 11-digit option (2): (2) + (1+2+2) + (2+2) digits - eleven_digit_graph = ( - pynutil.delete("(") - + double_digits - + insert_space - + pynutil.delete(") ") - + single_digits - + insert_space - + double_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - # 10-digit option (2): (2) + (2+2) + (2+2) digits - ten_digit_graph = ( - pynutil.delete("(") - + double_digits - + insert_space - + pynutil.delete(") ") - + double_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - # 9-digit option (2): (1+2+2) + (2+2) digits - nine_digit_graph = ( - single_digits - + insert_space - + double_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - # 8-digit option (2): (2+2) + (2+2) digits - eight_digit_graph = ( - double_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - number_part = pynini.union(eleven_digit_graph, ten_digit_graph, nine_digit_graph, eight_digit_graph) - - number_part = pynutil.insert("number_part: \"") + pynini.invert(number_part) + pynutil.insert("\"") - - graph = number_part - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/time.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/time.py deleted file mode 100755 index 1e209ec963ee..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/time.py +++ /dev/null @@ -1,214 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time - e.g. quinze pro meio dia -> time { hours: "11" minutes: "45" } - e.g. quinze pra meia noite -> time { hours: "23" minutes: "45" } - e.g. quinze pra uma -> time { hours: "12" minutes: "45" } - e.g. dez pras duas -> time { hours: "1" minutes: "50" } - e.g. quinze pras duas -> time { hours: "1" minutes: "45" } - e.g. ao meio dia -> time { hours: "12" minutes: "00" morphosyntactic_features: "ao" } - e.g. ao meio dia e meia -> time { hours: "12" minutes: "30" morphosyntactic_features: "ao" } - e.g. ao meio dia e meio -> time { hours: "12" minutes: "30" morphosyntactic_features: "ao" } - e.g. à meia noite e quinze -> time { hours: "0" minutes: "15" morphosyntactic_features: "à" } - e.g. à meia noite e meia -> time { hours: "0" minutes: "30" morphosyntactic_features: "à" } - e.g. à uma e trinta -> time { hours: "1" minutes: "30" morphosyntactic_features: "à" } - e.g. às onze e trinta -> time { hours: "11" minutes: "30" morphosyntactic_features: "às" } - e.g. às três horas e trinta minutos -> time { hours: "3" minutes: "30" morphosyntactic_features: "às" } - """ - - def __init__(self): - super().__init__(name="time", kind="classify") - - # graph_hour_to_am = pynini.string_file(get_abs_path("data/time/hour_to_am.tsv")) - # graph_hour_to_pm = pynini.string_file(get_abs_path("data/time/hour_to_pm.tsv")) - graph_hours_to = pynini.string_file(get_abs_path("data/time/hours_to.tsv")) - graph_minutes_to = pynini.string_file(get_abs_path("data/time/minutes_to.tsv")) - graph_suffix_am = pynini.string_file(get_abs_path("data/time/time_suffix_am.tsv")) - graph_suffix_pm = pynini.string_file(get_abs_path("data/time/time_suffix_pm.tsv")) - - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - - graph_1_to_100 = pynini.union( - graph_digit, - graph_twenties, - graph_teen, - (graph_ties + pynutil.insert("0")), - (graph_ties + pynutil.delete(" e ") + graph_digit), - ) - - # note that graph_hour will start from 2 hours - # "1 o'clock" will be treated differently because it - # is singular - digits_2_to_23 = [str(digits) for digits in range(2, 24)] - digits_1_to_59 = [str(digits) for digits in range(1, 60)] - - graph_2_to_23 = graph_1_to_100 @ pynini.union(*digits_2_to_23) - graph_1_to_59 = graph_1_to_100 @ pynini.union(*digits_1_to_59) - graph_uma = pynini.cross("uma", "1") - - # Mapping 'horas' - graph_hour = pynutil.delete(pynini.accep("hora") + pynini.accep("s").ques) - graph_minute = pynutil.delete(pynini.accep("minuto") + pynini.accep("s").ques) - - # Mapping 'meio dia' and 'meia noite' - graph_meio_dia = pynini.cross("meio dia", "12") - graph_meia_noite = pynini.cross("meia noite", "0") - - # Mapping 'e meia' - graph_e = delete_space + pynutil.delete(" e ") + delete_space - graph_e_meia = graph_e + pynini.cross("meia", "30") - graph_e_meio = graph_e + pynini.cross("meio", "30") - - # à uma e meia -> 1:30 - # às três e meia -> 3:30 - graph_hours_at_prefix_singular = ( - pynutil.insert("morphosyntactic_features: \"") - + (pynini.cross("à", "à") | pynini.cross("a", "à")) - + pynutil.insert("\" ") - + delete_space - ) - graph_hours_at_singular = ( - graph_hours_at_prefix_singular - + pynutil.insert("hours: \"") - + graph_uma - + pynutil.insert("\"") - + (delete_space + graph_hour).ques - ) - graph_hours_at_prefix_plural = ( - pynutil.insert("morphosyntactic_features: \"") - + (pynini.cross("às", "às") | pynini.cross("as", "às")) - + pynutil.insert("\" ") - + delete_space - ) - graph_hours_at_plural = ( - graph_hours_at_prefix_plural - + pynutil.insert("hours: \"") - + graph_2_to_23 - + pynutil.insert("\"") - + (delete_space + graph_hour).ques - ) - final_graph_hour_at = graph_hours_at_singular | graph_hours_at_plural - - graph_minutes_component_without_zero = graph_e + graph_1_to_59 + (delete_space + graph_minute).ques - graph_minutes_component_without_zero |= graph_e_meia + pynutil.delete(delete_space + pynini.accep("hora")).ques - final_graph_minute = ( - pynutil.insert(" minutes: \"") + graph_minutes_component_without_zero + pynutil.insert("\"") - ) - - graph_hm = final_graph_hour_at + final_graph_minute - - # à uma hora -> 1:00 - graph_hours_at_singular_with_hour = ( - graph_hours_at_prefix_singular - + pynutil.insert("hours: \"") - + graph_uma - + pynutil.insert("\"") - + delete_space - + graph_hour - ) - - graph_hours_at_plural_with_hour = ( - graph_hours_at_prefix_plural - + pynutil.insert("hours: \"") - + graph_2_to_23 - + pynutil.insert("\"") - + delete_space - + graph_hour - ) - - graph_hm |= (graph_hours_at_singular_with_hour | graph_hours_at_plural_with_hour) + pynutil.insert( - " minutes: \"00\"", weight=0.2 - ) - - # meio dia e meia -> 12:30 - # meia noite e meia -> 0:30 - graph_minutes_without_zero = ( - pynutil.insert(" minutes: \"") + graph_minutes_component_without_zero + pynutil.insert("\"") - ) - graph_meio_min = ( - pynutil.insert("hours: \"") - + (graph_meio_dia | graph_meia_noite) - + pynutil.insert("\"") - + graph_minutes_without_zero - ) - graph_meio_min |= ( - pynutil.insert("hours: \"") - + graph_meio_dia - + pynutil.insert("\" minutes: \"") - + graph_e_meio - + pynutil.insert("\"") - ) - graph_hm |= graph_meio_min - - # às quinze para as quatro -> às 3:45 - # NOTE: case 'para à uma' ('to one') could be either 0:XX or 12:XX - # leading to wrong reading ('meio dia e ...' or 'meia noite e ...') - graph_para_a = ( - pynutil.delete("para") - | pynutil.delete("para a") - | pynutil.delete("para as") - | pynutil.delete("pra") - | pynutil.delete("pras") - ) - graph_para_o = pynutil.delete("para") | pynutil.delete("para o") | pynutil.delete("pro") - - graph_pra_min = ( - pynutil.insert("morphosyntactic_features: \"") - + (pynini.cross("à", "à") | pynini.cross("às", "às") | pynini.cross("a", "à") | pynini.cross("as", "às")) - + pynutil.insert("\" ") - + delete_space - ) - graph_pra_min += ( - pynutil.insert("minutes: \"") - + (graph_1_to_59 @ graph_minutes_to) - + pynutil.insert("\" ") - + (delete_space + graph_minute).ques - ) - graph_pra_hour = ( - pynutil.insert("hours: \"") - + (graph_2_to_23 @ graph_hours_to) - + pynutil.insert("\"") - + (delete_space + graph_hour).ques - ) - graph_pra_hour |= pynutil.insert("hours: \"") + (graph_meia_noite @ graph_hours_to) + pynutil.insert("\"") - - graph_pra = graph_pra_min + delete_space + graph_para_a + delete_space + graph_pra_hour - - # às quinze pro meio dia -> às 11:45 - graph_pro = graph_pra_min + delete_space + graph_para_o + delete_space - graph_pro += pynutil.insert(" hours: \"") + (graph_meio_dia @ graph_hours_to) + pynutil.insert("\"") - - graph_mh = graph_pra | graph_pro - - # optional suffix - final_suffix = pynutil.insert("suffix: \"") + (graph_suffix_am | graph_suffix_pm) + pynutil.insert("\"") - final_suffix_optional = pynini.closure(delete_space + insert_space + final_suffix, 0, 1) - - final_graph = pynini.union((graph_hm | graph_mh) + final_suffix_optional).optimize() - - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/tokenize_and_classify.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/tokenize_and_classify.py deleted file mode 100644 index a7a3fd6a3244..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,110 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.date import DateFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.punctuation import PunctuationFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.whitelist import WhiteListFst -from nemo_text_processing.inverse_text_normalization.pt.taggers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="tokenize_and_classify", kind="classify") - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "_pt_itn.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars.") - - cardinal = CardinalFst(use_strict_e=True) - cardinal_graph = cardinal.fst - - ordinal_graph = OrdinalFst().fst - - decimal = DecimalFst(cardinal) - decimal_graph = decimal.fst - - measure_graph = MeasureFst(cardinal=cardinal, decimal=decimal).fst - date_graph = DateFst(cardinal=cardinal).fst - word_graph = WordFst().fst - time_graph = TimeFst().fst - money_graph = MoneyFst(cardinal=cardinal, decimal=decimal).fst - whitelist_graph = WhiteListFst().fst - punct_graph = PunctuationFst().fst - electronic_graph = ElectronicFst().fst - telephone_graph = TelephoneFst().fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.09) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.09) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/whitelist.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/whitelist.py deleted file mode 100644 index 6965ccbb8e70..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/whitelist.py +++ /dev/null @@ -1,33 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelisted tokens - e.g. usted -> tokens { name: "ud." } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - """ - - def __init__(self): - super().__init__(name="whitelist", kind="classify") - - whitelist = pynini.string_file(get_abs_path("data/whitelist.tsv")).invert() - graph = pynutil.insert("name: \"") + convert_space(whitelist) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/taggers/word.py b/nemo_text_processing/inverse_text_normalization/pt/taggers/word.py deleted file mode 100644 index 7908397d52ad..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/taggers/word.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying plain tokens, that do not belong to any special class. This can be considered as the default class. - e.g. sleep -> tokens { name: "sleep" } - """ - - def __init__(self): - super().__init__(name="word", kind="classify") - word = pynutil.insert("name: \"") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert("\"") - self.fst = word.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/utils.py b/nemo_text_processing/inverse_text_normalization/pt/utils.py deleted file mode 100644 index a73b7d9ddb39..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/utils.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + '/' + rel_path diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/__init__.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/cardinal.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/cardinal.py deleted file mode 100644 index 928a259d3897..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/cardinal.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinal - e.g. cardinal { negative: "-" integer: "23" } -> -23 - """ - - def __init__(self): - super().__init__(name="cardinal", kind="verbalize") - optional_sign = pynini.closure( - pynutil.delete("negative:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space, - 0, - 1, - ) - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - self.numbers = graph - graph = optional_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/date.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/date.py deleted file mode 100644 index 7c0034099ba2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/date.py +++ /dev/null @@ -1,87 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_extra_space, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { day: "1" month: "enero" preserve_order: true } -> 1 de enero - """ - - def __init__(self): - super().__init__(name="date", kind="verbalize") - month = ( - pynutil.delete("month:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - day = ( - pynutil.delete("day:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - year = ( - pynutil.delete("year:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - # day month - graph_dmy = ( - day - + delete_extra_space - + pynutil.insert("de") - + insert_space - + month - + (delete_extra_space + pynutil.insert("de") + insert_space + year).ques - ) - graph_dmy |= ( - day - + delete_space - + pynutil.insert("/") - + month - + pynutil.delete(" morphosyntactic_features: \"/\"") - + (delete_space + pynutil.insert("/") + year).ques - ) - - optional_preserve_order = pynini.closure( - pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - | pynutil.delete("field_order:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space - ) - - final_graph = graph_dmy + delete_space + optional_preserve_order - - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/decimal.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/decimal.py deleted file mode 100644 index 58fc76ea63e6..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/decimal.py +++ /dev/null @@ -1,66 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, - e.g. decimal { negative: "true" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" } -> -1,26 - e.g. decimal { negative: "true" integer_part: "1" morphosyntactic_features: "." fractional_part: "26" } -> -1.26 - e.g. decimal { negative: "false" integer_part: "1" morphosyntactic_features: "," fractional_part: "26" quantity: "millón" } -> 1,26 millón - e.g. decimal { negative: "false" integer_part: "2" quantity: "millones" } -> 2 millones - """ - - def __init__(self): - super().__init__(name="decimal", kind="verbalize") - optionl_sign = pynini.closure(pynini.cross("negative: \"true\"", "-") + delete_space, 0, 1) - integer = ( - pynutil.delete("integer_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_integer = pynini.closure(integer + delete_space, 0, 1) - - decimal_point = pynini.cross("morphosyntactic_features: \",\"", ",") - decimal_point |= pynini.cross("morphosyntactic_features: \".\"", ".") - - fractional = ( - decimal_point - + delete_space - + pynutil.delete("fractional_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_fractional = pynini.closure(fractional + delete_space, 0, 1) - quantity = ( - pynutil.delete("quantity:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_quantity = pynini.closure(pynutil.insert(" ") + quantity + delete_space, 0, 1) - graph = optional_integer + optional_fractional + optional_quantity - self.numbers = graph - graph = optionl_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/electronic.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/electronic.py deleted file mode 100644 index 11b2706a3562..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/electronic.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. tokens { electronic { username: "cdf1" domain: "abc.edu" } } -> cdf1@abc.edu - e.g. tokens { electronic { protocol: "www.abc.edu" } } -> www.abc.edu - """ - - def __init__(self): - super().__init__(name="electronic", kind="verbalize") - user_name = ( - pynutil.delete("username:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - domain = ( - pynutil.delete("domain:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - protocol = ( - pynutil.delete("protocol:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - graph = user_name + delete_space + pynutil.insert("@") + domain - graph |= protocol - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/measure.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/measure.py deleted file mode 100644 index 057ade696d11..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/measure.py +++ /dev/null @@ -1,61 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { cardinal { negative: "true" integer: "12" } units: "kg" } -> -12 kg - - Args: - decimal: DecimalFst - cardinal: CardinalFst - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst): - super().__init__(name="measure", kind="verbalize") - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "-"), 0, 1) - unit = ( - pynutil.delete("units:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - + delete_space - ) - graph_decimal = ( - pynutil.delete("decimal {") - + delete_space - + optional_sign - + delete_space - + decimal.numbers - + delete_space - + pynutil.delete("}") - ) - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + delete_space - + cardinal.numbers - + delete_space - + pynutil.delete("}") - ) - graph = (graph_cardinal | graph_decimal) + delete_space + pynutil.insert(" ") + unit - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/money.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/money.py deleted file mode 100644 index 54a9b1038337..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/money.py +++ /dev/null @@ -1,40 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { integer_part: "12" morphosyntactic_features: "," fractional_part: "05" currency: "$" } -> $12,05 - - Args: - decimal: DecimalFst - """ - - def __init__(self, decimal: GraphFst): - super().__init__(name="money", kind="verbalize") - unit = ( - pynutil.delete("currency:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = unit + delete_space + insert_space + decimal.numbers - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/ordinal.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/ordinal.py deleted file mode 100644 index fe3454e15e71..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/ordinal.py +++ /dev/null @@ -1,44 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinal, e.g. - ordinal { integer: "13" morphosyntactic_features: "o" } -> 13º - """ - - def __init__(self): - super().__init__(name="ordinal", kind="verbalize") - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - replace_suffix = pynini.union( - pynini.cross(" morphosyntactic_features: \"o\"", "º"), - pynini.cross(" morphosyntactic_features: \"a\"", "ª"), - ) - - graph = graph + replace_suffix - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/telephone.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/telephone.py deleted file mode 100644 index 4dd0d7079889..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/telephone.py +++ /dev/null @@ -1,32 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { number_part: "123-123-5678" } - -> 123-123-5678 - """ - - def __init__(self): - super().__init__(name="telephone", kind="verbalize") - - number_part = pynutil.delete("number_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(number_part) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/time.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/time.py deleted file mode 100755 index b1a04c673752..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/time.py +++ /dev/null @@ -1,82 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_NOT_QUOTE, - GraphFst, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, - e.g. time { hours: "à 1" minutes: "10" } -> à 1:10 - e.g. time { hours: "às 2" minutes: "45" } -> às 2:45 - """ - - def __init__(self): - super().__init__(name="time", kind="verbalize") - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - - prefix = ( - pynutil.delete("morphosyntactic_features:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + delete_space - + insert_space - ) - optional_prefix = pynini.closure(prefix, 0, 1) - - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete("\"") - ) - minute = ( - pynutil.delete("minutes:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete("\"") - ) - suffix = ( - delete_space - + insert_space - + pynutil.delete("suffix:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_suffix = pynini.closure(suffix, 0, 1) - - graph = ( - optional_prefix - + hour - + delete_space - + pynutil.insert(":") - + (minute @ add_leading_zero_to_double_digit) - + optional_suffix - ) - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/verbalize.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/verbalize.py deleted file mode 100644 index 88c04991b5f4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/verbalize.py +++ /dev/null @@ -1,62 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.date import DateFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - """ - - def __init__(self): - super().__init__(name="verbalize", kind="verbalize") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - ordinal_graph = OrdinalFst().fst - decimal = DecimalFst() - decimal_graph = decimal.fst - measure_graph = MeasureFst(decimal=decimal, cardinal=cardinal).fst - money_graph = MoneyFst(decimal=decimal).fst - time_graph = TimeFst().fst - date_graph = DateFst().fst - whitelist_graph = WhiteListFst().fst - telephone_graph = TelephoneFst().fst - electronic_graph = ElectronicFst().fst - - graph = ( - time_graph - | date_graph - | money_graph - | measure_graph - | ordinal_graph - | decimal_graph - | cardinal_graph - | whitelist_graph - | telephone_graph - | electronic_graph - ) - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/verbalize_final.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/verbalize_final.py deleted file mode 100644 index cc2e65aed46d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/verbalize_final.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.pt.verbalizers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now - """ - - def __init__(self): - super().__init__(name="verbalize_final", kind="verbalize") - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/whitelist.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/whitelist.py deleted file mode 100644 index f54aaea65b0a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/whitelist.py +++ /dev/null @@ -1,37 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for verbalizing whitelist - e.g. tokens { name: "sexta feira" } -> "sexta-feira" - """ - - def __init__(self): - super().__init__(name="whitelist", kind="verbalize") - graph = ( - pynutil.delete("name:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = graph @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/word.py b/nemo_text_processing/inverse_text_normalization/pt/verbalizers/word.py deleted file mode 100644 index 4417d8f0020c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/pt/verbalizers/word.py +++ /dev/null @@ -1,32 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for verbalizing plain tokens - e.g. tokens { name: "sleep" } -> sleep - """ - - def __init__(self): - super().__init__(name="word", kind="verbalize") - chars = pynini.closure(NEMO_CHAR - " ", 1) - char = pynutil.delete("name:") + delete_space + pynutil.delete("\"") + chars + pynutil.delete("\"") - graph = char @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/__init__.py b/nemo_text_processing/inverse_text_normalization/ru/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/__init__.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/cardinal.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/cardinal.py deleted file mode 100644 index e812be117d5d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/cardinal.py +++ /dev/null @@ -1,46 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst, insert_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals, e.g. - "тысяча один" -> cardinal { integer: "1 001" } - - Args: - tn_cardinal: Text normalization Cardinal graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="cardinal", kind="classify", deterministic=deterministic) - - graph = tn_cardinal.cardinal_numbers_default - self.graph = graph.invert().optimize() - - optional_sign = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("минус ", "\"-\"") + insert_space, 0, 1 - ) - - # do not invert numbers less than 10 - graph = pynini.compose(graph, NEMO_DIGIT ** (2, ...)) - graph = optional_sign + pynutil.insert("integer: \"") + graph + pynutil.insert("\"") - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/date.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/date.py deleted file mode 100644 index 9727626c8924..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/date.py +++ /dev/null @@ -1,37 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, e.g. - восемнадцатое июня две тысячи второго -> tokens { date { day: "18.06.2002" } } - - Args: - tn_date: Text normalization Date graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_date: GraphFst, deterministic: bool = True): - super().__init__(name="date", kind="classify", deterministic=deterministic) - - graph = pynini.invert(tn_date.final_graph).optimize() - graph = self.add_tokens(pynutil.insert("day: \"") + graph + pynutil.insert("\"")) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/decimals.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/decimals.py deleted file mode 100644 index 66e8f5f7354b..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/decimals.py +++ /dev/null @@ -1,54 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SPACE, GraphFst, delete_extra_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal - e.g. "минус три целых две десятых" -> decimal { negative: "true" integer_part: "3," fractional_part: "2" } - - Args: - tn_decimal: Text normalization Decimal graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_decimal, deterministic: bool = False): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("минус", "\"true\"") + delete_extra_space, 0, 1 - ) - - graph_fractional_part = pynini.invert(tn_decimal.graph_fractional).optimize() - graph_integer_part = pynini.invert(tn_decimal.integer_part).optimize() - optional_graph_quantity = pynini.invert(tn_decimal.optional_quantity).optimize() - - graph_fractional = pynutil.insert("fractional_part: \"") + graph_fractional_part + pynutil.insert("\"") - graph_integer = pynutil.insert("integer_part: \"") + graph_integer_part + pynutil.insert("\"") - optional_graph_quantity = pynutil.insert("quantity: \"") + optional_graph_quantity + pynutil.insert("\"") - optional_graph_quantity = pynini.closure(pynini.accep(NEMO_SPACE) + optional_graph_quantity, 0, 1) - - self.final_graph_wo_sign = ( - graph_integer + pynini.accep(NEMO_SPACE) + graph_fractional + optional_graph_quantity - ) - final_graph = optional_graph_negative + self.final_graph_wo_sign - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/electronic.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/electronic.py deleted file mode 100644 index f73c8f1b8780..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/electronic.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic, e.g. - "эй би собака эн ди точка ру" -> electronic { username: "ab@nd.ru" } - - Args: - tn_electronic: Text normalization Electronic graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_electronic, deterministic: bool = True): - super().__init__(name="electronic", kind="classify", deterministic=deterministic) - - graph = tn_electronic.final_graph - graph = graph.invert().optimize() - graph = pynutil.insert("username: \"") + graph + pynutil.insert("\"") - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/measure.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/measure.py deleted file mode 100644 index ef15a61e20ce..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/measure.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure, e.g. - "два килограма" -> measure { cardinal { integer: "2 кг" } } - - Args: - tn_measure: Text normalization Cardinal graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_measure, deterministic: bool = True): - super().__init__(name="measure", kind="classify", deterministic=deterministic) - - tn_measure = tn_measure.tagger_graph_default @ tn_measure.verbalizer_graph - graph = tn_measure.invert().optimize() - graph = pynutil.insert("cardinal { integer: \"") + graph + pynutil.insert("\" }") - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/money.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/money.py deleted file mode 100644 index 7477350ec1cc..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/money.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money, e.g. - "два рубля" -> money { integer_part: "2 руб." } - - Args: - tn_money: Text normalization Money graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_money, deterministic: bool = True): - super().__init__(name="money", kind="classify", deterministic=deterministic) - - graph = tn_money.final_graph - graph = graph.invert().optimize() - graph = pynutil.insert("integer_part: \"") + graph + pynutil.insert("\"") - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/ordinal.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/ordinal.py deleted file mode 100644 index 306054d63d37..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/ordinal.py +++ /dev/null @@ -1,44 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinals, e.g. - "второе" -> ordinal { integer: "2" } } - - Args: - tn_ordinal: Text normalization Ordinal graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_ordinal: GraphFst, deterministic: bool = True): - super().__init__(name="ordinal", kind="classify", deterministic=deterministic) - - tn_ordinal = tn_ordinal.ordinal_numbers - - graph = tn_ordinal.invert().optimize() - self.graph = graph - - # do not invert numbers less than 10 - graph = pynini.compose(graph, NEMO_DIGIT ** (2, ...)) - graph = pynutil.insert("integer: \"") + graph + pynutil.insert("\"") - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/telephone.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/telephone.py deleted file mode 100644 index 7b54ddc7e443..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/telephone.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone, e.g. - "восемь девятьсот тринадцать девятьсот восемьдесят три пятьдесят шесть ноль один" -> telephone { number_part: "8-913-983-56-01" } - - Args: - tn_telephone: Text normalization telephone graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_telephone: GraphFst, deterministic: bool = True): - super().__init__(name="telephone", kind="classify", deterministic=deterministic) - - tn_telephone = tn_telephone.final_graph - graph = tn_telephone.invert().optimize() - graph = pynutil.insert("number_part: \"") + graph + pynutil.insert("\"") - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/time.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/time.py deleted file mode 100644 index 50e12c09abb2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/time.py +++ /dev/null @@ -1,69 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SPACE, GraphFst -from nemo_text_processing.text_normalization.ru.verbalizers.time import TimeFst as TNTimeVerbalizer -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time, e.g. - "два часа пятнадцать минут" -> time { hours: "02:15" } - - Args: - tn_time: Text Normalization Time graph - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, tn_time: GraphFst, deterministic: bool = True): - super().__init__(name="time", kind="classify", deterministic=deterministic) - - tn_time_tagger = tn_time.graph_preserve_order - tn_time_verbalizer = TNTimeVerbalizer().graph - tn_time_graph_preserve_order = pynini.compose(tn_time_tagger, tn_time_verbalizer).optimize() - graph_preserve_order = pynini.invert(tn_time_graph_preserve_order).optimize() - graph_preserve_order = pynutil.insert("hours: \"") + graph_preserve_order + pynutil.insert("\"") - - # "пятнадцать минут шестого" -> 17:15 - # Requires permutations for the correct verbalization - m_next_h = ( - pynutil.insert("minutes: \"") - + pynini.invert(tn_time.minutes).optimize() - + pynutil.insert("\"") - + pynini.accep(NEMO_SPACE) - + pynutil.insert("hours: \"") - + pynini.invert(tn_time.increment_hour_ordinal).optimize() - + pynutil.insert("\"") - ).optimize() - - # "без пятнадцати минут шесть" -> 17:45 - # Requires permutation for the correct verbalization - m_to_h = ( - pynini.cross("без ", "minutes: \"") - + pynini.invert(tn_time.mins_to_h) - + pynutil.insert("\"") - + pynini.accep(NEMO_SPACE) - + pynutil.insert("hours: \"") - + pynini.invert(tn_time.increment_hour_cardinal).optimize() - + pynutil.insert("\"") - ) - - graph_reserve_order = m_next_h | m_to_h - graph = graph_preserve_order | graph_reserve_order - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/tokenize_and_classify.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/tokenize_and_classify.py deleted file mode 100644 index 7f2a833b5230..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,114 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.inverse_text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.inverse_text_normalization.en.taggers.word import WordFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.date import DateFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.decimals import DecimalFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.ru.taggers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.ru.taggers.tokenize_and_classify import ClassifyFst as TNClassifyFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="tokenize_and_classify", kind="classify") - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "_ru_itn.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars. This might take some time...") - tn_classify = TNClassifyFst( - input_case='cased', deterministic=False, cache_dir=cache_dir, overwrite_cache=True - ) - cardinal = CardinalFst(tn_cardinal=tn_classify.cardinal) - cardinal_graph = cardinal.fst - - ordinal = OrdinalFst(tn_ordinal=tn_classify.ordinal) - ordinal_graph = ordinal.fst - - decimal = DecimalFst(tn_decimal=tn_classify.decimal) - decimal_graph = decimal.fst - - measure_graph = MeasureFst(tn_measure=tn_classify.measure).fst - date_graph = DateFst(tn_date=tn_classify.date).fst - word_graph = WordFst().fst - time_graph = TimeFst(tn_time=tn_classify.time).fst - money_graph = MoneyFst(tn_money=tn_classify.money).fst - whitelist_graph = WhiteListFst().fst - punct_graph = PunctuationFst().fst - electronic_graph = ElectronicFst(tn_electronic=tn_classify.electronic).fst - telephone_graph = TelephoneFst(tn_telephone=tn_classify.telephone).fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.1) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.1) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(pynutil.add_weight(delete_extra_space, 1.1) + token_plus_punct) - - graph = delete_space + graph + delete_space - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/inverse_text_normalization/ru/taggers/whitelist.py b/nemo_text_processing/inverse_text_normalization/ru/taggers/whitelist.py deleted file mode 100644 index def15e5e56cd..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/taggers/whitelist.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelist, e.g. - "квартира" -> telephone { number_part: "кв." } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="whitelist", kind="classify", deterministic=deterministic) - whitelist = pynini.string_file(get_abs_path("data/whitelist.tsv")).invert() - graph = pynutil.insert("name: \"") + convert_space(whitelist) + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/__init__.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/cardinal.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/cardinal.py deleted file mode 100644 index 12e2451f7044..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/cardinal.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing roman numerals - e.g. cardinal { integer: "1 001" } -> 1 001 - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="cardinal", kind="verbalize", deterministic=deterministic) - - optional_sign = pynini.closure( - pynutil.delete("negative:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space, - 0, - 1, - ) - - graph = ( - optional_sign + pynutil.delete("integer: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/date.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/date.py deleted file mode 100644 index 02cce48dae10..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/date.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { day: "02.03.89" } -> "02.03.89" - """ - - def __init__(self): - super().__init__(name="date", kind="verbalize") - graph = pynutil.delete("day: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph.optimize()) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/decimal.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/decimal.py deleted file mode 100644 index cf8cefc5d50d..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/decimal.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, NEMO_SPACE, GraphFst, delete_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, e.g. - decimal { negative: "true" integer_part: "3," fractional_part: "2" } -> -3,2 - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="decimal", kind="verbalize", deterministic=deterministic) - - optional_sign = pynini.closure(pynini.cross("negative: \"true\" ", "-"), 0, 1) - - integer = pynutil.delete(" \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - integer_part = pynutil.delete("integer_part:") + integer - fractional_part = pynutil.delete("fractional_part:") + integer - optional_quantity = pynini.closure(pynini.accep(NEMO_SPACE) + pynutil.delete("quantity:") + integer, 0, 1) - - graph = optional_sign + integer_part + delete_space + fractional_part + optional_quantity - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/electronic.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/electronic.py deleted file mode 100644 index 158cd9893b87..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/electronic.py +++ /dev/null @@ -1,31 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. electronic { username: "ab@nd.ru" } -> "ab@nd.ru" - """ - - def __init__(self): - super().__init__(name="electronic", kind="verbalize") - - graph = pynutil.delete("username: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/measure.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/measure.py deleted file mode 100644 index 3cae67bac289..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/measure.py +++ /dev/null @@ -1,37 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure - e.g. measure { cardinal { integer: "2 кг" } } -> "2 кг" - """ - - def __init__(self): - super().__init__(name="measure", kind="verbalize") - - graph = ( - pynutil.delete(" cardinal { integer: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + delete_space - + pynutil.delete("}") - ) - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/money.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/money.py deleted file mode 100644 index af59d33db5d9..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/money.py +++ /dev/null @@ -1,31 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. money { integer_part: "2 руб." } -> "2 руб." - """ - - def __init__(self): - super().__init__(name="money", kind="verbalize") - - graph = pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/ordinal.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/ordinal.py deleted file mode 100644 index 31ff9b3c6063..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/ordinal.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinal numbers - e.g. ordinal { integer: "2" } -> "2" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="ordinal", kind="verbalize", deterministic=deterministic) - - value = pynini.closure(NEMO_NOT_QUOTE) - graph = pynutil.delete("integer: \"") + value + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/telephone.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/telephone.py deleted file mode 100644 index 06c705dc4b61..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/telephone.py +++ /dev/null @@ -1,31 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone - e.g. telephone { number_part: "8-913-983-56-01" } -> "8-913-983-56-01" - """ - - def __init__(self): - super().__init__(name="telephone", kind="verbalize") - - graph = pynutil.delete("number_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/time.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/time.py deleted file mode 100644 index edfe7b8988ec..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/time.py +++ /dev/null @@ -1,45 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time - e.g. time { hours: "02:15" } -> "02:15" - """ - - def __init__(self): - super().__init__(name="time", kind="verbalize") - hour = ( - pynutil.delete("hours: ") + pynutil.delete("\"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) - minutes = ( - pynutil.delete("minutes: ") - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - graph_preserve_order = pynutil.delete("hours: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - # for cases that require permutations for the correct verbalization - graph_reverse_order = hour + delete_space + pynutil.insert(":") + minutes + delete_space - - graph = graph_preserve_order | graph_reverse_order - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/verbalize.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/verbalize.py deleted file mode 100644 index 39a2bebe7474..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/verbalize.py +++ /dev/null @@ -1,64 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.en.verbalizers.whitelist import WhiteListFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.date import DateFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.time import TimeFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - """ - - def __init__(self): - super().__init__(name="verbalize", kind="verbalize") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - ordinal = OrdinalFst() - ordinal_graph = ordinal.fst - decimal = DecimalFst() - decimal_graph = decimal.fst - whitelist_graph = WhiteListFst().fst - electronic_graph = ElectronicFst().fst - money_graph = MoneyFst().fst - date_graph = DateFst().fst - measure_graph = MeasureFst().fst - telephone_graph = TelephoneFst().fst - time_graph = TimeFst().fst - - graph = ( - whitelist_graph - | cardinal_graph - | ordinal_graph - | decimal_graph - | electronic_graph - | date_graph - | money_graph - | measure_graph - | telephone_graph - | time_graph - ) - - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/verbalize_final.py b/nemo_text_processing/inverse_text_normalization/ru/verbalizers/verbalize_final.py deleted file mode 100644 index f409537d2d41..000000000000 --- a/nemo_text_processing/inverse_text_normalization/ru/verbalizers/verbalize_final.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.en.verbalizers.word import WordFst -from nemo_text_processing.inverse_text_normalization.ru.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now - """ - - def __init__(self): - super().__init__(name="verbalize_final", kind="verbalize") - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/run_evaluate.py b/nemo_text_processing/inverse_text_normalization/run_evaluate.py deleted file mode 100644 index d2b3b63305ad..000000000000 --- a/nemo_text_processing/inverse_text_normalization/run_evaluate.py +++ /dev/null @@ -1,113 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from argparse import ArgumentParser - -from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer -from nemo_text_processing.text_normalization.data_loader_utils import ( - evaluate, - known_types, - load_files, - training_data_to_sentences, - training_data_to_tokens, -) - - -''' -Runs Evaluation on data in the format of : \t\t<`self` if trivial class or normalized text> -like the Google text normalization data https://www.kaggle.com/richardwilliamsproat/text-normalization-for-english-russian-and-polish -''' - - -def parse_args(): - parser = ArgumentParser() - parser.add_argument("--input", help="input file path", type=str) - parser.add_argument( - "--lang", help="language", choices=['en', 'de', 'es', 'pt', 'ru', 'fr', 'vi'], default="en", type=str - ) - parser.add_argument( - "--cat", - dest="category", - help="focus on class only (" + ", ".join(known_types) + ")", - type=str, - default=None, - choices=known_types, - ) - parser.add_argument("--filter", action='store_true', help="clean data for inverse normalization purposes") - return parser.parse_args() - - -if __name__ == "__main__": - # Example usage: - # python run_evaluate.py --input= --cat= --filter - args = parse_args() - if args.lang == 'en': - from nemo_text_processing.inverse_text_normalization.en.clean_eval_data import filter_loaded_data - file_path = args.input - inverse_normalizer = InverseNormalizer() - - print("Loading training data: " + file_path) - training_data = load_files([file_path]) - - if args.filter: - training_data = filter_loaded_data(training_data) - - if args.category is None: - print("Sentence level evaluation...") - sentences_un_normalized, sentences_normalized, _ = training_data_to_sentences(training_data) - print("- Data: " + str(len(sentences_normalized)) + " sentences") - sentences_prediction = inverse_normalizer.inverse_normalize_list(sentences_normalized) - print("- Denormalized. Evaluating...") - sentences_accuracy = evaluate( - preds=sentences_prediction, labels=sentences_un_normalized, input=sentences_normalized - ) - print("- Accuracy: " + str(sentences_accuracy)) - - print("Token level evaluation...") - tokens_per_type = training_data_to_tokens(training_data, category=args.category) - token_accuracy = {} - for token_type in tokens_per_type: - print("- Token type: " + token_type) - tokens_un_normalized, tokens_normalized = tokens_per_type[token_type] - print(" - Data: " + str(len(tokens_normalized)) + " tokens") - tokens_prediction = inverse_normalizer.inverse_normalize_list(tokens_normalized) - print(" - Denormalized. Evaluating...") - token_accuracy[token_type] = evaluate(tokens_prediction, tokens_un_normalized, input=tokens_normalized) - print(" - Accuracy: " + str(token_accuracy[token_type])) - token_count_per_type = {token_type: len(tokens_per_type[token_type][0]) for token_type in tokens_per_type} - token_weighted_accuracy = [ - token_count_per_type[token_type] * accuracy for token_type, accuracy in token_accuracy.items() - ] - print("- Accuracy: " + str(sum(token_weighted_accuracy) / sum(token_count_per_type.values()))) - - print(" - Total: " + str(sum(token_count_per_type.values())), '\n') - - for token_type in token_accuracy: - if token_type not in known_types: - raise ValueError("Unexpected token type: " + token_type) - - if args.category is None: - c1 = ['Class', 'sent level'] + known_types - c2 = ['Num Tokens', len(sentences_normalized)] + [ - token_count_per_type[known_type] if known_type in tokens_per_type else '0' for known_type in known_types - ] - c3 = ["Denormalization", sentences_accuracy] + [ - token_accuracy[known_type] if known_type in token_accuracy else '0' for known_type in known_types - ] - - for i in range(len(c1)): - print(f'{str(c1[i]):10s} | {str(c2[i]):10s} | {str(c3[i]):5s}') - else: - print(f'numbers\t{token_count_per_type[args.category]}') - print(f'Denormalization\t{token_accuracy[args.category]}') diff --git a/nemo_text_processing/inverse_text_normalization/vi/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/__init__.py deleted file mode 100644 index 9af8257c226e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.vi.taggers.tokenize_and_classify import ClassifyFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.verbalize_final import VerbalizeFinalFst diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/data/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/currency.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/currency.tsv deleted file mode 100644 index ce65d4420cb6..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/currency.tsv +++ /dev/null @@ -1,11 +0,0 @@ -$ đô -$ usd -$ đô la -$ đô la mỹ -€ euro -€ ơ rô -¥ yên -₩ won -₩ uôn -RM ringgit -₫ đồng \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/data/electronic/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/domain.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/electronic/domain.tsv deleted file mode 100644 index c56c252adbea..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/domain.tsv +++ /dev/null @@ -1,11 +0,0 @@ -com -uk -fr -net -br -in -ru -de -it -vn -edu \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/server_name.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/electronic/server_name.tsv deleted file mode 100644 index 4eadcaf5915a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/server_name.tsv +++ /dev/null @@ -1,16 +0,0 @@ -g mail gmail -gmail -n vidia nvidia -nvidia -outlook -hotmail -yahoo -aol -gmx -msn -live -yandex -orange -wanadoo -web -comcast \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/symbols.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/electronic/symbols.tsv deleted file mode 100644 index eccbe3d47512..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/electronic/symbols.tsv +++ /dev/null @@ -1,20 +0,0 @@ -. chấm -- gạch -_ gạch dưới -_ shift gạch -_ síp gạch -! chấm than -# thăng -$ đô -% phần trăm -& và -* sao -: hai chấm -+ cộng -/ sẹc -= bằng -? chấm hỏi -? hỏi chấm -^ mũ -| hoặc -, phẩy \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/magnitudes.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/magnitudes.tsv deleted file mode 100644 index 727dc567011c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/magnitudes.tsv +++ /dev/null @@ -1,5 +0,0 @@ -k nghìn -k ngàn -m triệu -b tỉ -b tỷ \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/math/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/data/math/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/math/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/math/symbols.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/math/symbols.tsv deleted file mode 100644 index 2475c6ec39b8..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/math/symbols.tsv +++ /dev/null @@ -1,10 +0,0 @@ -% phần trăm -& và -* nhân -* sao -+ cộng -- trừ -/ chia -= bằng -^ mũ -| hoặc \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/measurements.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/measurements.tsv deleted file mode 100644 index fa28177c8239..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/measurements.tsv +++ /dev/null @@ -1,185 +0,0 @@ -°f fahrenheit -°f độ f -°c celsius -°c độ c -km kilomet -km ki lô met -km ki lô mét -km kilô mét -km kilo mét -m met -m mét -cm centimet -cm cen ti mét -cm xen ti mét -cm xăng ti mét -mm millimet -mm mi li mét -mm mili mét -ha hecta -ha héc ta -mi mile -m² met vuông -m² mét vuông -km² kilomet vuông -km² ki lô met vuông -km² kilo mét vuông -km² ki lô mét vuông -ft foot -% phần trăm -hz héc -hz hẹc -kw kilowatt -kw kilo watt -kw ki lô watt -kw ki lô oát -kw ki lô goát -hp mã lực -mg milligram -mg milli gram -mg mi li gram -mg mi li gam -mg mili gam -kg kilogram -kg kilo gram -kg ki lô gram -kg kilo gam -kg ki lô gam -kg kí lô -kg kí -ghz giga hẹc -ghz giga héc -ghz gi ga héc -ghz gi ga hẹc -khz kilo hẹc -khz kilo héc -khz ki lô héc -khz ki lô hẹc -mhz mega héc -mhz mega hẹc -mhz mê ga hẹc -mhz mê ga héc -v vôn -h giờ -phút phút -s giây -nm nanomet -nm nano mét -nm na nô mét -mA milli ampe -mA mi li ampe -mA mi li am pe -kwh kilowatt giờ -kwh kilo watt giờ -kwh ki lô oát giờ -kwh ki lô goát giờ -m³ met khối -m³ mét khối -cm³ centimet khối -cm³ cen ti mét khối -cm³ xen ti mét khối -cm³ xăng ti mét khối -tw tera watt -tw terawatt -tw te ra watt -tw tê ra watt -tw tê ra oát -tw tê ra goát -mv milli vôn -mv mi li vôn -mw megawatt -mw mega watt -mw mê ga watt -mw mê ga oát -mw mê ga goát -μm micromet -μm micro mét -μm muy crô mét -μm mi crô mét -μm muy cờ rô mét -μm mi cờ rô mét -inch inch -tb terabyte -tb tera byte -tb te ra byte -tb te ra bai -tb tê ra byte -tb tê ra bai -g gram -g gam -ω ohm -ω ôm -db decibel -db deci ben -db đề xi ben -μg microgram -μg micro gram -μg muy crô gram -μg micro gam -μg muy crô gam -μg muy cờ rô gam -pg petagram -pg peta gam -pg pê ta gam -gb gigabyte -gb giga byte -gb giga bai -gb gi ga byte -gb gi ga bai -mb megabyte -mb mega byte -mb mega bai -mb me ga byte -mb me ga bai -mb mê ga byte -mb mê ga bai -kb kilobyte -kb kilo byte -kb kilo bai -kb ki lô byte -kb ki lô bai -kbps kilobit trên giây -mbps megabit trên giây -kv kilovolt -kv kilo vôn -kv ki lô vôn -mv megavolt -mv mega vôn -mv me ga vôn -mv mê ga vôn -yd yard -rad radian -gpa giga pascal -gpa gi ga pascal -gw gigawatt -gw giga watt -gw gi ga watt -gw gi ga oát -ns nano giây -ns na nô giây -μs micro giây -μs muy crô giây -μs muy cờ rô giây -pa pascal -ms milli giây -ms mi li giây -dm decimet -dm đề xi mét -dm³ đề xi mét khối -dm³ decimet khối -mm² millimet vuông -mm² mi li mét vuông -cm² centimet vuông -cm² centi mét vuông -cm² xăng ti mét vuông -cm² xen ti mét vuông -pb peta byte -pb petabyte -pb pê ta byte -kcal kilocalories -kcal kilocalo -kcal ki lô calo -l lít -ml millilit -ml mili lít -ml mi li lít \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/months.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/months.tsv deleted file mode 100644 index 93da6892e2ba..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/months.tsv +++ /dev/null @@ -1,14 +0,0 @@ -một 1 -hai 2 -ba 3 -tư 4 -bốn 4 -năm 5 -sáu 6 -bảy 7 -bẩy 7 -tám 8 -chín 9 -mười 10 -mười một 11 -mười hai 12 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/data/numbers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/digit.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/numbers/digit.tsv deleted file mode 100644 index bdac5ded18ff..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/digit.tsv +++ /dev/null @@ -1,10 +0,0 @@ -một 1 -hai 2 -ba 3 -bốn 4 -năm 5 -sáu 6 -bảy 7 -bẩy 7 -tám 8 -chín 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/hundred.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/numbers/hundred.tsv deleted file mode 100644 index b2f35ae9fbf3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/hundred.tsv +++ /dev/null @@ -1 +0,0 @@ -trăm \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/teen.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/numbers/teen.tsv deleted file mode 100644 index 722dc678d4eb..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/teen.tsv +++ /dev/null @@ -1,11 +0,0 @@ -mười 10 -mười một 11 -mười hai 12 -mười ba 13 -mười bốn 14 -mười lăm 15 -mười sáu 16 -mười bảy 17 -mười bẩy 17 -mười tám 18 -mười chín 19 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/thousands.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/numbers/thousands.tsv deleted file mode 100644 index d2ca259e8be8..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/thousands.tsv +++ /dev/null @@ -1,6 +0,0 @@ -nghìn -triệu -tỉ -nghìn tỉ -triệu tỉ -tỉ tỉ \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/ties.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/numbers/ties.tsv deleted file mode 100644 index cca1f8008036..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/ties.tsv +++ /dev/null @@ -1,9 +0,0 @@ -hai 2 -ba 3 -bốn 4 -năm 5 -sáu 6 -bảy 7 -bẩy 7 -tám 8 -chín 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/zero.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/numbers/zero.tsv deleted file mode 100644 index 70d6dcf26ae2..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/numbers/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -không 0 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/ordinals/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/data/ordinals/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/ordinals/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/ordinals/digit.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/ordinals/digit.tsv deleted file mode 100644 index a1403b7ceb4b..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/ordinals/digit.tsv +++ /dev/null @@ -1,12 +0,0 @@ -nhất 1 -nhì 2 -hai 2 -ba 3 -bốn 4 -tư 4 -năm 5 -sáu 6 -bảy 7 -bẩy 7 -tám 8 -chín 9 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/data/time/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/hours.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/time/hours.tsv deleted file mode 100644 index 48e35fc90130..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/hours.tsv +++ /dev/null @@ -1,29 +0,0 @@ -không 0 -một 1 -hai 2 -ba 3 -bốn 4 -năm 5 -sáu 6 -bảy 7 -bẩy 7 -tám 8 -chín 9 -mười 10 -mười một 11 -mười hai 12 -mười ba 13 -mười bốn 14 -mười lăm 15 -mười sáu 16 -mười bảy 17 -mười bẩy 17 -mười tám 18 -mười chín 19 -hai mươi 20 -hai mươi mốt 21 -hai mốt 21 -hai mươi hai 22 -hai hai 22 -hai mươi ba 23 -hai ba 23 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/hours_to.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/time/hours_to.tsv deleted file mode 100644 index a56219579975..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/hours_to.tsv +++ /dev/null @@ -1,25 +0,0 @@ -1 0 -2 1 -3 2 -4 3 -5 4 -6 5 -7 6 -8 7 -9 8 -10 9 -11 10 -12 11 -13 12 -14 13 -15 14 -16 15 -17 16 -18 17 -19 18 -20 19 -21 20 -22 21 -23 22 -24 23 -0 23 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/hours_to_night.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/time/hours_to_night.tsv deleted file mode 100644 index 1374f45c0f5b..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/hours_to_night.tsv +++ /dev/null @@ -1,12 +0,0 @@ -1 13 -2 14 -3 15 -4 16 -5 17 -6 18 -7 19 -8 20 -9 21 -10 22 -11 23 -12 0 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/minutes.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/time/minutes.tsv deleted file mode 100644 index 0d7872b948f4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/minutes.tsv +++ /dev/null @@ -1,118 +0,0 @@ -không 0 -một 1 -hai 2 -ba 3 -bốn 4 -năm 5 -sáu 6 -bảy 7 -bẩy 7 -tám 8 -chín 9 -mười 10 -mười một 11 -mười hai 12 -mười ba 13 -mười bốn 14 -mười lăm 15 -mười sáu 16 -mười bảy 17 -mười bẩy 17 -mười tám 18 -mười chín 19 -hai mươi 20 -hai mươi mốt 21 -hai mươi hai 22 -hai mươi ba 23 -hai mươi tư 24 -hai mươi bốn 24 -hai mươi lăm 25 -hai mươi sáu 26 -hai mươi bảy 27 -hai mươi bẩy 27 -hai mươi tám 28 -hai mươi chín 29 -ba mươi 30 -ba mươi mốt 21 -ba mươi hai 22 -ba mươi ba 33 -ba mươi tư 34 -ba mươi bốn 34 -ba mươi lăm 35 -ba mươi sáu 36 -ba mươi bảy 37 -ba mươi bẩy 37 -ba mươi tám 38 -ba mươi chín 39 -bốn mươi 40 -bốn mươi mốt 41 -bốn mươi hai 42 -bốn mươi ba 43 -bốn mươi tư 44 -bốn mươi bốn 44 -bốn mươi lăm 45 -bốn mươi sáu 46 -bốn mươi bảy 47 -bốn mươi bẩy 47 -bốn mươi tám 48 -bốn mươi chín 49 -năm mươi 50 -năm mươi mốt 51 -năm mươi hai 52 -năm mươi ba 53 -năm mươi tư 54 -năm mươi bốn 54 -năm mươi lăm 55 -năm mươi sáu 56 -năm mươi bảy 57 -năm mươi bẩy 57 -năm mươi tám 58 -năm mươi chín 59 -hai mốt 21 -hai hai 22 -hai ba 23 -hai tư 24 -hai bốn 24 -hai lăm 25 -hai năm 25 -hai sáu 26 -hai bảy 27 -hai bẩy 27 -hai tám 28 -hai chín 29 -ba mốt 21 -ba hai 22 -ba ba 33 -ba tư 34 -ba bốn 34 -ba lăm 35 -ba năm 35 -ba sáu 36 -ba bảy 37 -ba bẩy 37 -ba tám 38 -ba chín 39 -bốn mốt 41 -bốn hai 42 -bốn ba 43 -bốn tư 44 -bốn bốn 44 -bốn lăm 45 -bốn năm 45 -bốn sáu 46 -bốn bảy 47 -bốn bẩy 47 -bốn tám 48 -bốn chín 49 -năm mốt 51 -năm hai 52 -năm ba 53 -năm tư 54 -năm bốn 54 -năm lăm 55 -năm năm 55 -năm sáu 56 -năm bảy 57 -năm bẩy 57 -năm tám 58 -năm chín 59 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/minutes_to.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/time/minutes_to.tsv deleted file mode 100644 index bcb3283651c4..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/minutes_to.tsv +++ /dev/null @@ -1,59 +0,0 @@ -1 59 -2 58 -3 57 -4 56 -5 55 -6 54 -7 53 -8 52 -9 51 -10 50 -11 49 -12 48 -13 47 -14 46 -15 45 -16 44 -17 43 -18 42 -19 41 -20 40 -21 39 -22 38 -23 37 -24 36 -25 35 -26 34 -27 33 -28 32 -29 31 -30 30 -31 29 -32 28 -33 27 -34 26 -35 25 -36 24 -37 23 -38 22 -39 21 -40 20 -41 19 -42 18 -43 17 -44 16 -45 15 -46 14 -47 13 -48 12 -49 11 -50 10 -51 9 -52 8 -53 7 -54 6 -55 5 -56 4 -57 3 -58 2 -59 1 \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/time_suffix.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/time/time_suffix.tsv deleted file mode 100644 index b39a9ef9a92c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/time_suffix.tsv +++ /dev/null @@ -1,8 +0,0 @@ -p m p.m. -pm p.m. -p.m. -p.m p.m. -am a.m. -a.m. -a.m a.m. -a m a.m. \ No newline at end of file diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/time/time_zone.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/time/time_zone.tsv deleted file mode 100644 index 3e0ade467a84..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/data/time/time_zone.tsv +++ /dev/null @@ -1,7 +0,0 @@ -cst c s t -cet c e t -pst p s t -est e s t -pt p t -et e t -gmt g m t diff --git a/nemo_text_processing/inverse_text_normalization/vi/data/whitelist.tsv b/nemo_text_processing/inverse_text_normalization/vi/data/whitelist.tsv deleted file mode 100644 index e69de29bb2d1..000000000000 diff --git a/nemo_text_processing/inverse_text_normalization/vi/graph_utils.py b/nemo_text_processing/inverse_text_normalization/vi/graph_utils.py deleted file mode 100644 index adf1077fc08a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/graph_utils.py +++ /dev/null @@ -1,152 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os -import string -from pathlib import Path -from typing import Dict - -import pynini -from pynini import Far -from pynini.export import export -from pynini.lib import byte, pynutil, utf8 - -NEMO_CHAR = utf8.VALID_UTF8_CHAR - -NEMO_DIGIT = byte.DIGIT -NEMO_LOWER = pynini.union(*string.ascii_lowercase).optimize() -NEMO_UPPER = pynini.union(*string.ascii_uppercase).optimize() -NEMO_ALPHA = pynini.union(NEMO_LOWER, NEMO_UPPER).optimize() -NEMO_ALNUM = pynini.union(NEMO_DIGIT, NEMO_ALPHA).optimize() -NEMO_HEX = pynini.union(*string.hexdigits).optimize() -NEMO_NON_BREAKING_SPACE = "\u00A0" -NEMO_SPACE = " " -NEMO_WHITE_SPACE = pynini.union(" ", "\t", "\n", "\r", "\u00A0").optimize() -NEMO_NOT_SPACE = pynini.difference(NEMO_CHAR, NEMO_WHITE_SPACE).optimize() -NEMO_NOT_QUOTE = pynini.difference(NEMO_CHAR, r'"').optimize() - -NEMO_PUNCT = pynini.union(*map(pynini.escape, string.punctuation)).optimize() -NEMO_GRAPH = pynini.union(NEMO_ALNUM, NEMO_PUNCT).optimize() - -NEMO_SIGMA = pynini.closure(NEMO_CHAR) - -delete_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE)) -insert_space = pynutil.insert(" ") -delete_extra_space = pynini.cross(pynini.closure(NEMO_WHITE_SPACE, 1), " ") - -# French frequently compounds numbers with hyphen. -delete_hyphen = pynutil.delete(pynini.closure("-", 0, 1)) -insert_hyphen = pynutil.insert("-") - -TO_LOWER = pynini.union(*[pynini.cross(x, y) for x, y in zip(string.ascii_uppercase, string.ascii_lowercase)]) -TO_UPPER = pynini.invert(TO_LOWER) - - -def generator_main(file_name: str, graphs: Dict[str, pynini.FstLike]): - """ - Exports graph as OpenFst finite state archive (FAR) file with given file name and rule name. - - Args: - file_name: exported file name - graphs: Mapping of a rule name and Pynini WFST graph to be exported - """ - exporter = export.Exporter(file_name) - for rule, graph in graphs.items(): - exporter[rule] = graph.optimize() - exporter.close() - print(f"Created {file_name}") - - -def convert_space(fst) -> "pynini.FstLike": - """ - Converts space to nonbreaking space. - Used only in tagger grammars for transducing token values within quotes, e.g. name: "hello kitty" - This is making transducer significantly slower, so only use when there could be potential spaces within quotes, otherwise leave it. - - Args: - fst: input fst - - Returns output fst where breaking spaces are converted to non breaking spaces - """ - return fst @ pynini.cdrewrite(pynini.cross(NEMO_SPACE, NEMO_NON_BREAKING_SPACE), "", "", NEMO_SIGMA) - - -class GraphFst: - """ - Base class for all grammar fsts. - - Args: - name: name of grammar class - kind: either 'classify' or 'verbalize' - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, name: str, kind: str, deterministic: bool = True): - self.name = name - self.kind = kind - self._fst = None - self.deterministic = deterministic - - self.far_path = Path(os.path.dirname(__file__) + "/grammars/" + kind + "/" + name + ".far") - if self.far_exist(): - self._fst = Far(self.far_path, mode="r", arc_type="standard", far_type="default").get_fst() - - def far_exist(self) -> bool: - """ - Returns true if FAR can be loaded - """ - return self.far_path.exists() - - @property - def fst(self) -> "pynini.FstLike": - return self._fst - - @fst.setter - def fst(self, fst): - self._fst = fst - - def add_tokens(self, fst) -> "pynini.FstLike": - """ - Wraps class name around to given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - return pynutil.insert(f"{self.name} {{ ") + fst + pynutil.insert(" }") - - def delete_tokens(self, fst) -> "pynini.FstLike": - """ - Deletes class name wrap around output of given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - res = ( - pynutil.delete(f"{self.name}") - + delete_space - + pynutil.delete("{") - + delete_space - + fst - + delete_space - + pynutil.delete("}") - ) - return res @ pynini.cdrewrite(pynini.cross("\u00A0", " "), "", "", NEMO_SIGMA) diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/cardinal.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/cardinal.py deleted file mode 100644 index d25c96071477..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/cardinal.py +++ /dev/null @@ -1,153 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - NEMO_DIGIT, - NEMO_SPACE, - GraphFst, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals - e.g. trừ hai mươi ba -> cardinal { integer: "23" negative: "-" } } - e.g. hai nghìn lẻ chín -> cardinal { integer: "2009"} } - Numbers below ten are not converted. - """ - - def __init__(self): - super().__init__(name="cardinal", kind="classify") - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) - - graph_one = pynini.cross("mốt", "1") - graph_four = pynini.cross("tư", "4") - graph_five = pynini.cross("lăm", "5") - graph_half = pynini.cross("rưỡi", "5") - graph_hundred = pynini.cross("trăm", "") - graph_ten = pynini.cross("mươi", "") - zero = pynini.cross(pynini.union("linh", "lẻ"), "0") - - optional_ten = pynini.closure(delete_space + graph_ten, 0, 1) - last_digit_exception = pynini.project(pynini.cross("năm", "5"), "input") - last_digit = pynini.union( - (pynini.project(graph_digit, "input") - last_digit_exception.arcsort()) @ graph_digit, - graph_one, - graph_four, - graph_five, - ) - - graph_hundred_ties_component = (graph_digit | graph_zero) + delete_space + graph_hundred - graph_hundred_ties_component += delete_space - graph_hundred_ties_component += pynini.union( - graph_teen, - (graph_half | graph_four | graph_one) + pynutil.insert("0"), - graph_ties + optional_ten + ((delete_space + last_digit) | pynutil.insert("0")), - zero + delete_space + (graph_digit | graph_four), - pynutil.insert("00"), - ) - graph_hundred_ties_component |= ( - pynutil.insert("0") - + delete_space - + pynini.union( - graph_teen, - graph_ties + optional_ten + delete_space + last_digit, - graph_ties + delete_space + graph_ten + pynutil.insert("0"), - zero + delete_space + (graph_digit | graph_four), - ) - ) - graph_hundred_component = graph_hundred_ties_component | (pynutil.insert("00") + delete_space + graph_digit) - - graph_hundred_component_at_least_one_none_zero_digit = graph_hundred_component @ ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT) - ) - self.graph_hundred_component_at_least_one_none_zero_digit = ( - graph_hundred_component_at_least_one_none_zero_digit - ) - graph_hundred_ties_zero = graph_hundred_ties_component | pynutil.insert("000") - - graph_thousands = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + pynutil.delete(pynini.union("nghìn", "ngàn")), - pynutil.insert("000", weight=0.1), - ) - - graph_ten_thousand = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("vạn"), - pynutil.insert("0000", weight=0.1), - ) - - graph_ten_thousand_suffix = pynini.union( - graph_digit + delete_space + pynutil.delete(pynini.union("nghìn", "ngàn")), - pynutil.insert("0", weight=0.1), - ) - - graph_million = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("triệu"), - pynutil.insert("000", weight=0.1), - ) - graph_billion = pynini.union( - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + pynutil.delete(pynini.union("tỉ", "tỷ")), - pynutil.insert("000", weight=0.1), - ) - - graph = pynini.union( - graph_billion - + delete_space - + graph_million - + delete_space - + graph_thousands - + delete_space - + graph_hundred_ties_zero, - graph_ten_thousand + delete_space + graph_ten_thousand_suffix + delete_space + graph_hundred_ties_zero, - graph_hundred_component_at_least_one_none_zero_digit - + delete_space - + pynutil.delete(pynini.union("nghìn", "ngàn")) - + delete_space - + (((last_digit | graph_half) + pynutil.insert("00")) | graph_hundred_ties_zero), - graph_digit, - graph_zero, - ) - - graph = graph @ pynini.union( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT), "0", - ) - - # don't convert cardinals from zero to nine inclusive - graph_exception = pynini.project(pynini.union(graph_digit, graph_zero), "input") - - self.graph_no_exception = graph - - self.graph = (pynini.project(graph, "input") - graph_exception.arcsort()) @ graph - - optional_minus_graph = pynini.closure( - pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"-"') + NEMO_SPACE, 0, 1, - ) - - final_graph = optional_minus_graph + pynutil.insert('integer: "') + self.graph + pynutil.insert('"') - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/date.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/date.py deleted file mode 100644 index e1986f69c144..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/date.py +++ /dev/null @@ -1,157 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst, delete_extra_space, delete_space -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - -graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")).optimize() -graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")).optimize() -graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")).optimize() -ties_graph = pynini.string_file(get_abs_path("data/numbers/ties.tsv")).optimize() - - -def _get_month_graph(): - """ - Transducer for month, e.g. march -> march - """ - month_graph = pynini.string_file(get_abs_path("data/months.tsv")).optimize() - return month_graph - - -def _get_ties_graph(): - """ - Transducer for 20-99 e.g - hai ba -> 23 - """ - graph_one = pynini.cross("mốt", "1") - graph_four = pynini.cross("tư", "4") - graph_five = pynini.cross("lăm", "5") - graph_ten = pynini.cross("mươi", "") - optional_ten = pynini.closure(delete_space + graph_ten, 0, 1) - - graph = pynini.union( - ties_graph + optional_ten + delete_space + (graph_digit | graph_one | graph_four | graph_five), - ties_graph + delete_space + graph_ten + pynutil.insert("0"), - ) - return graph - - -def _get_year_graph(): - """ - Transducer for year, e.g. hai không hai mươi -> 2020 - """ - - def _get_digits_graph(): - zero = pynini.cross((pynini.union("linh", "lẻ")), "0") - four = pynini.cross("tư", "4") - graph = pynini.union(zero + delete_space + (graph_digit | four), graph_zero + delete_space + graph_digit,) - graph.optimize() - return graph - - def _get_hundreds_graph(graph_ties, graph_digits): - graph = ( - graph_digit - + delete_space - + pynutil.delete("trăm") - + delete_space - + (graph_teen | graph_ties | graph_digits) - ) - return graph - - def _get_thousands_graph(graph_ties, graph_digits): - graph_hundred_component = ( - (graph_digit | graph_zero) + delete_space + pynutil.delete("trăm") - ) | pynutil.insert("0") - graph = ( - graph_digit - + delete_space - + pynutil.delete(pynini.union("nghìn", "ngàn")) - + delete_space - + graph_hundred_component - + delete_space - + (graph_teen | graph_ties | graph_digits) - ) - return graph - - graph_ties = _get_ties_graph() - graph_digits = _get_digits_graph() - graph_hundreds = _get_hundreds_graph(graph_ties, graph_digits) - graph_thousands = _get_thousands_graph(graph_ties, graph_digits) - year_graph = ( - # 20 19, 40 12, 2012, 2 0 0 5, 2 0 17, 938 - assuming no limit on the year - graph_digit - + delete_space - + (graph_digit | graph_zero) - + delete_space - + (graph_teen | graph_ties | graph_digits) - | graph_thousands - | graph_hundreds - | (graph_digit + pynutil.insert("0") + delete_space + (graph_ties | graph_digits | graph_teen)) - ) - year_graph.optimize() - return year_graph - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, - e.g. mười lăm tháng một năm hai nghìn mười hai -> date { day: "15" month: "1" year: "2012" preserve_order: true } - e.g. ngày ba mốt tháng mười hai năm một chín chín chín -> date { day: "31" month: "12" year: "2012" preserve_order: true } - e.g. năm hai không hai mốt -> date { year: "2021" preserve_order: true } - - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="date", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - year_graph = _get_year_graph() - YEAR_WEIGHT = 0.001 - year_graph = pynutil.add_weight(year_graph, YEAR_WEIGHT) - month_graph = _get_month_graph() - - month_graph = pynutil.insert('month: "') + month_graph + pynutil.insert('"') - month_exception = pynini.project(pynini.cross("năm", "5"), "input") - month_graph_exception = (pynini.project(month_graph, "input") - month_exception.arcsort()) @ month_graph - - day_graph = pynutil.insert('day: "') + cardinal_graph + pynutil.insert('"') - # day_suffix = pynini.union("ngày", "mùng") - # optional_day = pynini.closure(day_suffix + delete_space, 0, 1) - - graph_month = pynutil.delete("tháng") + delete_space + month_graph_exception - graph_year = ( - delete_extra_space - + pynutil.delete("năm") - + delete_extra_space - + pynutil.insert('year: "') - + pynutil.add_weight(year_graph, -YEAR_WEIGHT) - + pynutil.insert('"') - ) - optional_graph_year = pynini.closure(graph_year, 0, 1) - graph_my = pynutil.delete("tháng") + delete_space + month_graph + graph_year - graph_dmy = ( - day_graph + delete_space + pynutil.delete("tháng") + delete_extra_space + month_graph + optional_graph_year - ) - graph_year = ( - pynutil.delete("năm") + delete_extra_space + pynutil.insert('year: "') + year_graph + pynutil.insert('"') - ) - - final_graph = (graph_dmy | graph_my | graph_month | graph_year) + pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/decimal.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/decimal.py deleted file mode 100644 index 298319306e0f..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/decimal.py +++ /dev/null @@ -1,131 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - -graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - - -def get_quantity(decimal: "pynini.FstLike", cardinal_up_to_hundred: "pynini.FstLike") -> "pynini.FstLike": - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. một triệu -> integer_part: "1" quantity: "triệu" - e.g. một tỷ rưỡi -> integer_part: "1" fractional_part: "5" quantity: "tỷ" - - Args: - decimal: decimal FST - cardinal_up_to_hundred: cardinal FST - """ - numbers = cardinal_up_to_hundred @ ( - pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT) - ) - suffix = pynini.union("triệu", "tỉ", "tỷ", "vạn") - graph_four = pynini.cross("tư", "4") - graph_one = pynini.cross("mốt", "1") - graph_half = pynini.cross("rưỡi", "5") - last_digit_exception = pynini.project(pynini.cross("năm", "5"), "input") - last_digit = pynini.union( - (pynini.project(graph_digit, "input") - last_digit_exception.arcsort()) @ graph_digit, - graph_one, - graph_four, - graph_half, - ) - optional_fraction_graph = pynini.closure( - delete_extra_space - + pynutil.insert('fractional_part: "') - + (last_digit | graph_half | graph_one | graph_four) - + pynutil.insert('"'), - 0, - 1, - ) - - res = ( - pynutil.insert('integer_part: "') - + numbers - + pynutil.insert('"') - + delete_extra_space - + pynutil.insert('quantity: "') - + suffix - + pynutil.insert('"') - + optional_fraction_graph - ) - res |= ( - decimal - + delete_extra_space - + pynutil.insert('quantity: "') - + (suffix | "ngàn" | "nghìn") - + pynutil.insert('"') - ) - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal - e.g. âm hai hai phẩy không năm tư năm tỉ -> decimal { negative: "true" integer_part: "22" fractional_part: "054" quantity: "tỉ" } - e.g. không chấm ba lăm -> decimal { integer_part: "0" fractional_part: "35" } - e.g. một triệu rưỡi -> decimal { integer_part: "1" quantity: "triệu" fractional_part: "5" } - Args: - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="decimal", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - - graph_decimal = graph_digit | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_one = pynini.cross("mốt", "1") - graph_four = pynini.cross("tư", "4") - graph_five = pynini.cross("lăm", "5") - - graph_decimal = pynini.union( - graph_decimal, - graph_four, - pynini.closure(graph_decimal + delete_space, 1) + (graph_decimal | graph_four | graph_five | graph_one), - ) - self.graph = graph_decimal - - point = pynutil.delete("chấm") | pynutil.delete("phẩy") - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"true"') + delete_extra_space, - 0, - 1, - ) - - graph_fractional = pynutil.insert('fractional_part: "') + graph_decimal + pynutil.insert('"') - graph_integer = pynutil.insert('integer_part: "') + cardinal_graph + pynutil.insert('"') - final_graph_wo_sign = ( - pynini.closure(graph_integer + delete_extra_space, 0, 1) + point + delete_extra_space + graph_fractional - ) - final_graph = optional_graph_negative + final_graph_wo_sign - - self.final_graph_wo_negative = final_graph_wo_sign | get_quantity( - final_graph_wo_sign, cardinal.graph_hundred_component_at_least_one_none_zero_digit, - ) - final_graph |= optional_graph_negative + get_quantity( - final_graph_wo_sign, cardinal.graph_hundred_component_at_least_one_none_zero_digit, - ) - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/electronic.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/electronic.py deleted file mode 100644 index 3eb0c8886678..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/electronic.py +++ /dev/null @@ -1,93 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_ALPHA, GraphFst, insert_space -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic: as URLs, email addresses, etc. - e.g. c d f một a còng a b c dot e d u -> tokens { electronic { username: "cdf1" domain: "abc.edu" } } - """ - - def __init__(self): - super().__init__(name="electronic", kind="classify") - - delete_extra_space = pynutil.delete(" ") - alpha_num = ( - NEMO_ALPHA - | pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - | pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - ) - - symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")).invert() - - accepted_username = alpha_num | symbols - process_dot = pynini.cross("chấm", ".") - username = ( - pynutil.insert('username: "') - + alpha_num - + pynini.closure(delete_extra_space + accepted_username) - + pynutil.insert('"') - ) - single_alphanum = pynini.closure(alpha_num + delete_extra_space) + alpha_num - server = single_alphanum | pynini.string_file(get_abs_path("data/electronic/server_name.tsv")) - domain = single_alphanum | pynini.string_file(get_abs_path("data/electronic/domain.tsv")) - multi_domain = ( - pynini.closure(process_dot + delete_extra_space + domain + delete_extra_space) - + process_dot - + delete_extra_space - + domain - ) - domain_graph = pynutil.insert('domain: "') + server + delete_extra_space + multi_domain + pynutil.insert('"') - graph = ( - username - + delete_extra_space - + pynutil.delete(pynini.union("a còng", "a móc", "a vòng")) - + insert_space - + delete_extra_space - + domain_graph - ) - - ############# url ### - protocol_end = pynini.cross(pynini.union("w w w", "www"), "www") - protocol_start = (pynini.cross("h t t p", "http") | pynini.cross("h t t p s", "https")) + pynini.cross( - " hai chấm sẹc sẹc ", "://" - ) - # .com, - ending = ( - delete_extra_space - + symbols - + delete_extra_space - + (domain | pynini.closure(accepted_username + delete_extra_space) + accepted_username) - ) - - protocol = ( - pynini.closure(protocol_start, 0, 1) - + protocol_end - + delete_extra_space - + process_dot - + pynini.closure(delete_extra_space + accepted_username, 1) - + pynini.closure(ending, 1, 2) - ) - protocol = pynutil.insert('protocol: "') + protocol + pynutil.insert('"') - graph |= protocol - ######## - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/fraction.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/fraction.py deleted file mode 100644 index 7798be65409a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/fraction.py +++ /dev/null @@ -1,57 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst, delete_extra_space, delete_space -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for classifying fraction - e.g. 2 phần 3 -> tokens { fraction { numerator: "2" denominator: "3" } } - e.g. 2 trên 3 -> tokens { fraction { numerator: "2" denominator: "3" } } - e.g. 2 chia 3 -> tokens { fraction { numerator: "2" denominator: "3" } } - - Args: - cardinal: OrdinalFst - """ - - def __init__(self, cardinal: GraphFst): - super().__init__(name="fraction", kind="classify") - # integer_part # numerator # denominator - - graph_cardinal = cardinal.graph_no_exception - graph_four = pynini.cross("tư", "4") - - numerator = pynutil.insert('numerator: "') + graph_cardinal + pynutil.insert('"') - fraction_component = pynutil.delete(pynini.union("phần", "trên", "chia")) - denominator = pynutil.insert('denominator: "') + (graph_cardinal | graph_four) + pynutil.insert('"') - - graph_fraction_component = numerator + delete_space + fraction_component + delete_extra_space + denominator - self.graph_fraction_component = graph_fraction_component - - graph = graph_fraction_component - graph = graph.optimize() - self.final_graph_wo_negative = graph - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"true"') + delete_extra_space, - 0, - 1, - ) - graph = optional_graph_negative + graph - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/measure.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/measure.py deleted file mode 100644 index 0b1f08b87ec7..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/measure.py +++ /dev/null @@ -1,103 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - GraphFst, - convert_space, - delete_extra_space, - delete_space, -) -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure - e.g. trừ mười hai ki lô gam -> measure { negative: "true" cardinal { integer: "12" } units: "kg" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="measure", kind="classify") - - cardinal_graph = cardinal.graph_no_exception - - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - graph_four = pynini.cross("tư", "4") - graph_one = pynini.cross("mốt", "1") - graph_half = pynini.cross("rưỡi", "5") - - graph_unit = pynini.string_file(get_abs_path("data/measurements.tsv")) - graph_unit_singular = pynini.invert(graph_unit) # singular -> abbr - - optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"true"') + delete_extra_space, - 0, - 1, - ) - - unit_singular = convert_space(graph_unit_singular) - unit_misc = pynutil.insert("/") + pynutil.delete("trên") + delete_space + convert_space(graph_unit_singular) - - unit_singular = ( - pynutil.insert('units: "') - + (unit_singular | unit_misc | pynutil.add_weight(unit_singular + delete_space + unit_misc, 0.01)) - + pynutil.insert('"') - ) - - subgraph_decimal = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + decimal.final_graph_wo_negative - + pynutil.insert(" }") - + delete_extra_space - + unit_singular - ) - - subgraph_cardinal = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert('integer: "') - + cardinal_graph - + pynutil.insert('"') - + pynutil.insert(" }") - + delete_extra_space - + unit_singular - ) - fraction_graph = ( - delete_extra_space - + pynutil.insert('fractional_part: "') - + (graph_digit | graph_half | graph_one | graph_four) - + pynutil.insert('"') - ) - - subgraph_cardinal |= ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert('integer: "') - + cardinal_graph - + pynutil.insert('" }') - + delete_extra_space - + unit_singular - + fraction_graph - ) - final_graph = subgraph_decimal | subgraph_cardinal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/money.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/money.py deleted file mode 100644 index b278773daf9e..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/money.py +++ /dev/null @@ -1,75 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - NEMO_DIGIT, - GraphFst, - convert_space, - delete_extra_space, -) -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money - e.g. mười hai đô la mỹ -> money { integer_part: "12" currency: "$" } - e.g. mười phẩy chín đồng -> money { integer_part: "10.9" currency: "đ" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst): - super().__init__(name="money", kind="classify") - # quantity, integer_part, fractional_part, currency - - cardinal_graph = cardinal.graph_no_exception - graph_decimal_final = decimal.final_graph_wo_negative - graph_half = pynini.cross("rưỡi", "5") - - unit = pynini.string_file(get_abs_path("data/currency.tsv")) - unit_singular = pynini.invert(unit) - - graph_unit_singular = pynutil.insert('currency: "') + convert_space(unit_singular) + pynutil.insert('"') - - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - - # twelve dollars fifty, only after integer - optional_cents_suffix = pynini.closure( - delete_extra_space - + pynutil.insert('fractional_part: "') - + (pynutil.add_weight(cardinal_graph @ add_leading_zero_to_double_digit, -0.7) | graph_half) - + pynutil.insert('"'), - 0, - 1, - ) - - graph_integer = ( - pynutil.insert('integer_part: "') - + cardinal_graph - + pynutil.insert('"') - + delete_extra_space - + graph_unit_singular - + optional_cents_suffix - ) - - graph_decimal = graph_decimal_final + delete_extra_space + graph_unit_singular + optional_cents_suffix - final_graph = graph_integer | graph_decimal - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/ordinal.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/ordinal.py deleted file mode 100644 index a7f79a1a8eee..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/ordinal.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst, delete_space -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal - e.g. thứ nhất -> ordinal { integer: "1" } - """ - - def __init__(self): - super().__init__(name="ordinal", kind="classify") - - graph_digit = pynini.string_file(get_abs_path("data/ordinals/digit.tsv")) - graph_ordinal = pynini.cross("thứ", "") - graph = graph_digit - - self.graph = graph - final_graph = pynutil.insert('integer: "') + graph_ordinal + delete_space + self.graph + pynutil.insert('"') - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/punctuation.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/punctuation.py deleted file mode 100644 index cbfe13063546..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/punctuation.py +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst -from pynini.lib import pynutil - - -class PunctuationFst(GraphFst): - """ - Finite state transducer for classifying punctuation - e.g. a, -> tokens { name: "a" } tokens { name: "," } - """ - - def __init__(self): - super().__init__(name="punctuation", kind="classify") - - s = "!#$%&'()*+,-./:;<=>?@^_`{|}~" - punct = pynini.union(*s) - - graph = pynutil.insert('name: "') + punct + pynutil.insert('"') - - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/telephone.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/telephone.py deleted file mode 100644 index 202547a403f9..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/telephone.py +++ /dev/null @@ -1,40 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst, delete_space -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone numbers, e.g. - một hai ba một hai ba năm sáu bảy tám -> { number_part: "1231235678" } - """ - - def __init__(self): - super().__init__(name="telephone", kind="classify") - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")) - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - digit = graph_digit | graph_zero - last_digit = digit | pynini.cross("mốt", "1") | pynini.cross("tư", "4") | pynini.cross("lăm", "5") - - graph_number_part = pynini.closure(digit + delete_space, 2) + last_digit - number_part = pynutil.insert('number_part: "') + graph_number_part + pynutil.insert('"') - - graph = number_part - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/time.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/time.py deleted file mode 100644 index c13d6467e451..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/time.py +++ /dev/null @@ -1,125 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - GraphFst, - convert_space, - delete_extra_space, - delete_space, - insert_space, -) -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time - e.g. hai rưỡi -> time { hours: "2" minutes: "30" } - e.g. chín giờ kém hai mươi -> time { hours: "8" minutes: "40" } - e.g. ba phút hai giây -> time { minutes: "3" seconds: "2" } - e.g. mười giờ chín phút bốn mươi lăm giây -> time { hours: "10" minutes: "9" seconds: "45" } - """ - - def __init__(self): - super().__init__(name="time", kind="classify") - # hours, minutes, seconds, suffix, zone, style, speak_period - - graph_hours_to = pynini.string_file(get_abs_path("data/time/hours_to.tsv")) - graph_minutes_to = pynini.string_file(get_abs_path("data/time/minutes_to.tsv")) - graph_hours = pynini.string_file(get_abs_path("data/time/hours.tsv")) - graph_minutes = pynini.string_file(get_abs_path("data/time/minutes.tsv")) - time_zone_graph = pynini.invert(pynini.string_file(get_abs_path("data/time/time_zone.tsv"))) - - graph_half = pynini.cross("rưỡi", "30") - oclock = pynini.cross("giờ", "") - minute = pynini.cross("phút", "") - optional_minute = pynini.closure(delete_space + minute, 0, 1) - second = pynini.cross("giây", "") - - final_graph_hour = pynutil.insert('hours: "') + graph_hours + pynutil.insert('"') + delete_space + oclock - graph_minute = graph_minutes + optional_minute - graph_second = graph_minutes + delete_space + second - final_time_zone_optional = pynini.closure( - delete_space - + insert_space - + pynutil.insert('zone: "') - + convert_space(time_zone_graph) - + pynutil.insert('"'), - 0, - 1, - ) - - graph_hm = ( - final_graph_hour - + delete_extra_space - + pynutil.insert('minutes: "') - + (graph_minute | graph_half) - + pynutil.insert('"') - ) - - graph_hms = ( - final_graph_hour - + delete_extra_space - + pynutil.insert('minutes: "') - + graph_minutes - + delete_space - + minute - + pynutil.insert('"') - + delete_extra_space - + pynutil.insert('seconds: "') - + graph_second - + pynutil.insert('"') - ) - - graph_ms = ( - pynutil.insert('minutes: "') - + graph_minutes - + delete_space - + minute - + pynutil.insert('"') - + delete_extra_space - + pynutil.insert('seconds: "') - + (graph_second | graph_half) - + pynutil.insert('"') - ) - - graph_hours_to_component = graph_hours @ graph_hours_to - graph_minutes_to_component = graph_minutes @ graph_minutes_to - - graph_time_to = ( - pynutil.insert('hours: "') - + graph_hours_to_component - + pynutil.insert('"') - + delete_space - + oclock - + delete_space - + pynutil.delete("kém") - + delete_extra_space - + pynutil.insert('minutes: "') - + graph_minutes_to_component - + pynutil.insert('"') - + optional_minute - ) - - final_graph = (final_graph_hour | graph_hm | graph_hms) + final_time_zone_optional - final_graph |= graph_ms - final_graph |= graph_time_to - - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/tokenize_and_classify.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/tokenize_and_classify.py deleted file mode 100644 index bd5ac1173dcb..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,116 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.inverse_text_normalization.vi.taggers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.date import DateFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.fraction import FractionFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.punctuation import PunctuationFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.whitelist import WhiteListFst -from nemo_text_processing.inverse_text_normalization.vi.taggers.word import WordFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="tokenize_and_classify", kind="classify") - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "_vi_itn.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars.") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - - fraction = FractionFst(cardinal) - fraction_graph = fraction.fst - - ordinal = OrdinalFst() - ordinal_graph = ordinal.fst - - decimal = DecimalFst(cardinal) - decimal_graph = decimal.fst - - measure_graph = MeasureFst(cardinal=cardinal, decimal=decimal).fst - date_graph = DateFst(cardinal=cardinal).fst - word_graph = WordFst().fst - time_graph = TimeFst().fst - money_graph = MoneyFst(cardinal=cardinal, decimal=decimal).fst - whitelist_graph = WhiteListFst().fst - punct_graph = PunctuationFst().fst - electronic_graph = ElectronicFst().fst - telephone_graph = TelephoneFst().fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.05) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.08) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(fraction_graph, 1.09) - | pynutil.add_weight(money_graph, 1.07) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/whitelist.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/whitelist.py deleted file mode 100644 index 199ce204e6ba..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/whitelist.py +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst, convert_space -from nemo_text_processing.inverse_text_normalization.vi.utils import get_abs_path -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelisted tokens - e.g. misses -> tokens { name: "mrs." } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - """ - - def __init__(self): - super().__init__(name="whitelist", kind="classify") - - whitelist = pynini.string_file(get_abs_path("data/whitelist.tsv")).invert() - graph = pynutil.insert('name: "') + convert_space(whitelist) + pynutil.insert('"') - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/taggers/word.py b/nemo_text_processing/inverse_text_normalization/vi/taggers/word.py deleted file mode 100644 index 3e1367d70818..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/taggers/word.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying plain tokens, that do not belong to any special class. This can be considered as the default class. - e.g. sleep -> tokens { name: "sleep" } - """ - - def __init__(self): - super().__init__(name="word", kind="classify") - word = pynutil.insert('name: "') + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert('"') - self.fst = word.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/utils.py b/nemo_text_processing/inverse_text_normalization/vi/utils.py deleted file mode 100644 index 436f27413508..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/utils.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + "/" + rel_path diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/__init__.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/cardinal.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/cardinal.py deleted file mode 100644 index 584758a3abfe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/cardinal.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinal - e.g. cardinal { integer: "23" negative: "-" } -> -23 - """ - - def __init__(self): - super().__init__(name="cardinal", kind="verbalize") - optional_sign = pynini.closure( - pynutil.delete("negative:") - + delete_space - + pynutil.delete('"') - + NEMO_NOT_QUOTE - + pynutil.delete('"') - + delete_space, - 0, - 1, - ) - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - self.numbers = graph - graph = optional_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/date.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/date.py deleted file mode 100644 index d746528db994..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/date.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { month: "1" year: "2012"} -> tháng 1 năm 2012 - date { day: "5" month: "10" year: "2021" preserve_order: true } -> 5 tháng 10 năm 2021 - """ - - def __init__(self): - super().__init__(name="date", kind="verbalize") - day = ( - pynutil.delete("day:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - month = ( - pynutil.delete("month:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - year = ( - pynutil.delete("year:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + delete_space - + pynutil.delete('"') - ) - - # (day) month year - # day month - graph_dm = day + delete_space + pynutil.insert(" tháng ") + month - graph_dmy = graph_dm + delete_space + pynutil.insert(" năm ") + year - graph_m = pynutil.insert("tháng ") + month - graph_my = pynutil.insert("tháng ") + month + delete_space + pynutil.insert(" năm ") + year - graph_y = pynutil.insert("năm ") + year - - optional_preserve_order = pynini.closure( - pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - | pynutil.delete("field_order:") - + delete_space - + pynutil.delete('"') - + NEMO_NOT_QUOTE - + pynutil.delete('"') - + delete_space - ) - - final_graph = (graph_y | graph_m | graph_dm | graph_dmy | graph_my) + delete_space + optional_preserve_order - - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/decimal.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/decimal.py deleted file mode 100644 index c016c20e0518..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/decimal.py +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, e.g. - decimal { negative: "true" integer_part: "12" fractional_part: "5006" quantity: "tỷ" } -> -12.5006 tỷ - """ - - def __init__(self): - super().__init__(name="decimal", kind="verbalize") - optionl_sign = pynini.closure(pynini.cross('negative: "true"', "-") + delete_space, 0, 1) - integer = ( - pynutil.delete("integer_part:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - optional_integer = pynini.closure(integer + delete_space, 0, 1) - fractional = ( - pynutil.insert(".") - + pynutil.delete("fractional_part:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - optional_fractional = pynini.closure(fractional + delete_space, 0, 1) - quantity = ( - pynutil.delete("quantity:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - optional_quantity = pynini.closure(pynutil.insert(" ") + quantity + delete_space, 0, 1) - graph = optional_integer + optional_fractional + optional_quantity - self.numbers = graph - graph = optionl_sign + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/electronic.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/electronic.py deleted file mode 100644 index 755172492f27..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/electronic.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. tokens { electronic { username: "cdf1" domain: "abc.edu" } } -> cdf1@abc.edu - """ - - def __init__(self): - super().__init__(name="electronic", kind="verbalize") - user_name = ( - pynutil.delete("username:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - domain = ( - pynutil.delete("domain:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - - protocol = ( - pynutil.delete("protocol:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - - graph = user_name + delete_space + pynutil.insert("@") + domain - graph |= protocol - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/fraction.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/fraction.py deleted file mode 100644 index e5e87767b0fe..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/fraction.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for verbalizing fraction, - e.g. fraction { numerator: "2" denominator: "3" } } -> 2/3 - e.g. fraction { numerator: "20" denominator: "3" negative: "true"} } -> 2/3 - """ - - def __init__(self): - super().__init__(name="fraction", kind="verbalize") - optional_sign = pynini.closure(pynini.cross('negative: "true"', "-") + delete_space, 0, 1) - numerator = pynutil.delete('numerator: "') + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete('"') - - denominator = ( - pynutil.insert("/") - + pynutil.delete('denominator: "') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - - graph = (numerator + delete_space + denominator).optimize() - self.numbers = graph - delete_tokens = self.delete_tokens(optional_sign + graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/measure.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/measure.py deleted file mode 100644 index abc06f724839..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/measure.py +++ /dev/null @@ -1,83 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - NEMO_CHAR, - NEMO_NOT_QUOTE, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { negative: "true" cardinal { integer: "12" } units: "kg" } -> -12 kg - - Args: - decimal: DecimalFst - cardinal: CardinalFst - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst): - super().__init__(name="measure", kind="verbalize") - optional_sign = pynini.closure(pynini.cross('negative: "true"', "-"), 0, 1) - unit = ( - pynutil.delete("units:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete('"') - + delete_space - ) - graph_decimal = ( - pynutil.delete("decimal {") - + delete_space - + optional_sign - + delete_space - + decimal.numbers - + delete_space - + pynutil.delete("}") - ) - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + delete_space - + cardinal.numbers - + delete_space - + pynutil.delete("}") - ) - fractional = ( - pynutil.insert(".") - + pynutil.delete("fractional_part:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - optional_fractional = pynini.closure(fractional + delete_space, 0, 1) - graph = ( - (graph_cardinal | graph_decimal) - + delete_space - + optional_fractional - + pynutil.insert(" ") - + unit - + delete_space - ) - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/money.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/money.py deleted file mode 100644 index dbea81ff44ed..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/money.py +++ /dev/null @@ -1,41 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_CHAR, GraphFst, delete_space -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { integer_part: "12" fractional_part: "05" currency: "$" } -> 12.05$ - - Args: - decimal: DecimalFst - """ - - def __init__(self, decimal: GraphFst): - super().__init__(name="money", kind="verbalize") - unit = ( - pynutil.delete("currency:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete('"') - ) - graph = decimal.numbers + delete_space + unit - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/ordinal.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/ordinal.py deleted file mode 100644 index c45e1ee7b68c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/ordinal.py +++ /dev/null @@ -1,39 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinal, e.g. - ordinal { integer: "2" } -> thứ 2 - """ - - def __init__(self): - super().__init__(name="ordinal", kind="verbalize") - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete('"') - ) - - graph = pynutil.insert("thứ ") + graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/telephone.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/telephone.py deleted file mode 100644 index d0e8de0b813a..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/telephone.py +++ /dev/null @@ -1,33 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { number_part: "1231235678" } - -> 1231235678 - """ - - def __init__(self): - super().__init__(name="telephone", kind="verbalize") - - number_part = pynutil.delete('number_part: "') + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete('"') - delete_tokens = self.delete_tokens(number_part) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/time.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/time.py deleted file mode 100644 index 446160611f3c..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/time.py +++ /dev/null @@ -1,89 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - GraphFst, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, e.g. - time { hours: "3" } -> 3h - time { hours: "12" minutes: "30" } -> 12:30 - time { hours: "1" minutes: "12" second: "22"} -> 1:12:22 - time { minutes: "36" second: "45"} -> 36p45s - time { hours: "2" zone: "gmt" } -> 2h gmt - """ - - def __init__(self): - super().__init__(name="time", kind="verbalize") - add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT) - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete('"') - ) - minute = ( - pynutil.delete("minutes:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete('"') - ) - second = ( - pynutil.delete("seconds:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_DIGIT, 1) - + pynutil.delete('"') - ) - zone = ( - delete_space - + insert_space - + pynutil.delete("zone:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete('"') - ) - optional_zone = pynini.closure(zone, 0, 1) - optional_second = pynini.closure( - delete_space + pynutil.insert(":") + (second @ add_leading_zero_to_double_digit), 0, 1, - ) - - graph_h = hour + pynutil.insert("h") - graph_hms = ( - hour + delete_space + pynutil.insert(":") + (minute @ add_leading_zero_to_double_digit) + optional_second - ) - graph_ms = ( - minute - + delete_space - + pynutil.insert("p") - + (second @ add_leading_zero_to_double_digit) - + pynutil.insert("s") - ) - - graph = (graph_h | graph_ms | graph_hms) + optional_zone - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/verbalize.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/verbalize.py deleted file mode 100644 index 28ea6883b0e3..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/verbalize.py +++ /dev/null @@ -1,66 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.cardinal import CardinalFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.date import DateFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.decimal import DecimalFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.electronic import ElectronicFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.fraction import FractionFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.measure import MeasureFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.money import MoneyFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.telephone import TelephoneFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.time import TimeFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.whitelist import WhiteListFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - """ - - def __init__(self): - super().__init__(name="verbalize", kind="verbalize") - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - ordinal_graph = OrdinalFst().fst - decimal = DecimalFst() - decimal_graph = decimal.fst - fraction = FractionFst() - fraction_graph = fraction.fst - measure_graph = MeasureFst(decimal=decimal, cardinal=cardinal).fst - money_graph = MoneyFst(decimal=decimal).fst - time_graph = TimeFst().fst - date_graph = DateFst().fst - whitelist_graph = WhiteListFst().fst - telephone_graph = TelephoneFst().fst - electronic_graph = ElectronicFst().fst - graph = ( - time_graph - | date_graph - | money_graph - | measure_graph - | ordinal_graph - | fraction_graph - | decimal_graph - | cardinal_graph - | whitelist_graph - | telephone_graph - | electronic_graph - ) - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/verbalize_final.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/verbalize_final.py deleted file mode 100644 index 40899e1919eb..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/verbalize_final.py +++ /dev/null @@ -1,44 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import GraphFst, delete_extra_space, delete_space -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.inverse_text_normalization.vi.verbalizers.word import WordFst -from pynini.lib import pynutil - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now - """ - - def __init__(self): - super().__init__(name="verbalize_final", kind="verbalize") - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/whitelist.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/whitelist.py deleted file mode 100644 index 558c75451667..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/whitelist.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - NEMO_CHAR, - NEMO_SIGMA, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for verbalizing whitelist - e.g. tokens { name: "mrs." } -> mrs. - """ - - def __init__(self): - super().__init__(name="whitelist", kind="verbalize") - graph = ( - pynutil.delete("name:") - + delete_space - + pynutil.delete('"') - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete('"') - ) - graph = graph @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - self.fst = graph.optimize() diff --git a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/word.py b/nemo_text_processing/inverse_text_normalization/vi/verbalizers/word.py deleted file mode 100644 index 3d7d6f8dbba8..000000000000 --- a/nemo_text_processing/inverse_text_normalization/vi/verbalizers/word.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.inverse_text_normalization.vi.graph_utils import ( - NEMO_CHAR, - NEMO_SIGMA, - GraphFst, - delete_space, -) -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for verbalizing plain tokens - e.g. tokens { name: "sleep" } -> sleep - """ - - def __init__(self): - super().__init__(name="word", kind="verbalize") - chars = pynini.closure(NEMO_CHAR - " ", 1) - char = pynutil.delete("name:") + delete_space + pynutil.delete('"') + chars + pynutil.delete('"') - graph = char @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/README.md b/nemo_text_processing/text_normalization/README.md deleted file mode 100644 index d14e4d1fa06e..000000000000 --- a/nemo_text_processing/text_normalization/README.md +++ /dev/null @@ -1,10 +0,0 @@ -# Text Normalization - -Text Normalization is part of NeMo's `nemo_text_processing` - a Python package that is installed with the `nemo_toolkit`. -It converts text from written form into its verbalized form, e.g. "123" -> "one hundred twenty three". - -See [NeMo documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/wfst_text_normalization.html) for details. - -Tutorial with overview of the package capabilities: [Text_(Inverse)_Normalization.ipynb](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/Text_(Inverse)_Normalization.ipynb) - -Tutorial on how to customize the underlying gramamrs: [WFST_Tutorial.ipynb](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/WFST_Tutorial.ipynb) diff --git a/nemo_text_processing/text_normalization/__init__.py b/nemo_text_processing/text_normalization/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/data_loader_utils.py b/nemo_text_processing/text_normalization/data_loader_utils.py deleted file mode 100644 index 4fde522f22d8..000000000000 --- a/nemo_text_processing/text_normalization/data_loader_utils.py +++ /dev/null @@ -1,351 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import json -import re -import string -import sys -from collections import defaultdict, namedtuple -from typing import Dict, List, Optional, Set, Tuple -from unicodedata import category - -from nemo.utils import logging - -EOS_TYPE = "EOS" -PUNCT_TYPE = "PUNCT" -PLAIN_TYPE = "PLAIN" -Instance = namedtuple('Instance', 'token_type un_normalized normalized') -known_types = [ - "PLAIN", - "DATE", - "CARDINAL", - "LETTERS", - "VERBATIM", - "MEASURE", - "DECIMAL", - "ORDINAL", - "DIGIT", - "MONEY", - "TELEPHONE", - "ELECTRONIC", - "FRACTION", - "TIME", - "ADDRESS", -] - - -def _load_kaggle_text_norm_file(file_path: str) -> List[Instance]: - """ - https://www.kaggle.com/richardwilliamsproat/text-normalization-for-english-russian-and-polish - Loads text file in the Kaggle Google text normalization file format: \t\t<`self` if trivial class or normalized text> - E.g. - PLAIN Brillantaisia - PLAIN is - PLAIN a - PLAIN genus - PLAIN of - PLAIN plant - PLAIN in - PLAIN family - PLAIN Acanthaceae - PUNCT . sil - - - Args: - file_path: file path to text file - - Returns: flat list of instances - """ - res = [] - with open(file_path, 'r') as fp: - for line in fp: - parts = line.strip().split("\t") - if parts[0] == "": - res.append(Instance(token_type=EOS_TYPE, un_normalized="", normalized="")) - else: - l_type, l_token, l_normalized = parts - l_token = l_token.lower() - l_normalized = l_normalized.lower() - - if l_type == PLAIN_TYPE: - res.append(Instance(token_type=l_type, un_normalized=l_token, normalized=l_token)) - elif l_type != PUNCT_TYPE: - res.append(Instance(token_type=l_type, un_normalized=l_token, normalized=l_normalized)) - return res - - -def load_files(file_paths: List[str], load_func=_load_kaggle_text_norm_file) -> List[Instance]: - """ - Load given list of text files using the `load_func` function. - - Args: - file_paths: list of file paths - load_func: loading function - - Returns: flat list of instances - """ - res = [] - for file_path in file_paths: - res.extend(load_func(file_path=file_path)) - return res - - -def clean_generic(text: str) -> str: - """ - Cleans text without affecting semiotic classes. - - Args: - text: string - - Returns: cleaned string - """ - text = text.strip() - text = text.lower() - return text - - -def evaluate(preds: List[str], labels: List[str], input: Optional[List[str]] = None, verbose: bool = True) -> float: - """ - Evaluates accuracy given predictions and labels. - - Args: - preds: predictions - labels: labels - input: optional, only needed for verbosity - verbose: if true prints [input], golden labels and predictions - - Returns accuracy - """ - acc = 0 - nums = len(preds) - for i in range(nums): - pred_norm = clean_generic(preds[i]) - label_norm = clean_generic(labels[i]) - if pred_norm == label_norm: - acc = acc + 1 - else: - if input: - print(f"inpu: {json.dumps(input[i])}") - print(f"gold: {json.dumps(label_norm)}") - print(f"pred: {json.dumps(pred_norm)}") - return acc / nums - - -def training_data_to_tokens( - data: List[Instance], category: Optional[str] = None -) -> Dict[str, Tuple[List[str], List[str]]]: - """ - Filters the instance list by category if provided and converts it into a map from token type to list of un_normalized and normalized strings - - Args: - data: list of instances - category: optional semiotic class category name - - Returns Dict: token type -> (list of un_normalized strings, list of normalized strings) - """ - result = defaultdict(lambda: ([], [])) - for instance in data: - if instance.token_type != EOS_TYPE: - if category is None or instance.token_type == category: - result[instance.token_type][0].append(instance.un_normalized) - result[instance.token_type][1].append(instance.normalized) - return result - - -def training_data_to_sentences(data: List[Instance]) -> Tuple[List[str], List[str], List[Set[str]]]: - """ - Takes instance list, creates list of sentences split by EOS_Token - Args: - data: list of instances - Returns (list of unnormalized sentences, list of normalized sentences, list of sets of categories in a sentence) - """ - # split data at EOS boundaries - sentences = [] - sentence = [] - categories = [] - sentence_categories = set() - - for instance in data: - if instance.token_type == EOS_TYPE: - sentences.append(sentence) - sentence = [] - categories.append(sentence_categories) - sentence_categories = set() - else: - sentence.append(instance) - sentence_categories.update([instance.token_type]) - un_normalized = [" ".join([instance.un_normalized for instance in sentence]) for sentence in sentences] - normalized = [" ".join([instance.normalized for instance in sentence]) for sentence in sentences] - return un_normalized, normalized, categories - - -def post_process_punctuation(text: str) -> str: - """ - Normalized quotes and spaces - - Args: - text: text - - Returns: text with normalized spaces and quotes - """ - text = ( - text.replace('( ', '(') - .replace(' )', ')') - .replace('{ ', '{') - .replace(' }', '}') - .replace('[ ', '[') - .replace(' ]', ']') - .replace(' ', ' ') - .replace('”', '"') - .replace("’", "'") - .replace("»", '"') - .replace("«", '"') - .replace("\\", "") - .replace("„", '"') - .replace("´", "'") - .replace("’", "'") - .replace('“', '"') - .replace("‘", "'") - .replace('`', "'") - .replace('- -', "--") - ) - - for punct in "!,.:;?": - text = text.replace(f' {punct}', punct) - return text.strip() - - -def pre_process(text: str) -> str: - """ - Optional text preprocessing before normalization (part of TTS TN pipeline) - - Args: - text: string that may include semiotic classes - - Returns: text with spaces around punctuation marks - """ - space_both = '[]' - for punct in space_both: - text = text.replace(punct, ' ' + punct + ' ') - - # remove extra space - text = re.sub(r' +', ' ', text) - return text - - -def load_file(file_path: str) -> List[str]: - """ - Loads given text file with separate lines into list of string. - - Args: - file_path: file path - - Returns: flat list of string - """ - res = [] - with open(file_path, 'r') as fp: - for line in fp: - res.append(line) - return res - - -def write_file(file_path: str, data: List[str]): - """ - Writes out list of string to file. - - Args: - file_path: file path - data: list of string - - """ - with open(file_path, 'w') as fp: - for line in data: - fp.write(line + '\n') - - -def post_process_punct(input: str, normalized_text: str, add_unicode_punct: bool = False): - """ - Post-processing of the normalized output to match input in terms of spaces around punctuation marks. - After NN normalization, Moses detokenization puts a space after - punctuation marks, and attaches an opening quote "'" to the word to the right. - E.g., input to the TN NN model is "12 test' example", - after normalization and detokenization -> "twelve test 'example" (the quote is considered to be an opening quote, - but it doesn't match the input and can cause issues during TTS voice generation.) - The current function will match the punctuation and spaces of the normalized text with the input sequence. - "12 test' example" -> "twelve test 'example" -> "twelve test' example" (the quote was shifted to match the input). - - Args: - input: input text (original input to the NN, before normalization or tokenization) - normalized_text: output text (output of the TN NN model) - add_unicode_punct: set to True to handle unicode punctuation marks as well as default string.punctuation (increases post processing time) - """ - # in the post-processing WFST graph "``" are repalced with '"" quotes (otherwise single quotes "`" won't be handled correctly) - # this function fixes spaces around them based on input sequence, so here we're making the same double quote replacement - # to make sure these new double quotes work with this function - if "``" in input and "``" not in normalized_text: - input = input.replace("``", '"') - input = [x for x in input] - normalized_text = [x for x in normalized_text] - punct_marks = [x for x in string.punctuation if x in input] - - if add_unicode_punct: - punct_unicode = [ - chr(i) - for i in range(sys.maxunicode) - if category(chr(i)).startswith("P") and chr(i) not in punct_default and chr(i) in input - ] - punct_marks = punct_marks.extend(punct_unicode) - - for punct in punct_marks: - try: - equal = True - if input.count(punct) != normalized_text.count(punct): - equal = False - idx_in, idx_out = 0, 0 - while punct in input[idx_in:]: - idx_out = normalized_text.index(punct, idx_out) - idx_in = input.index(punct, idx_in) - - def _is_valid(idx_out, idx_in, normalized_text, input): - """Check if previous or next word match (for cases when punctuation marks are part of - semiotic token, i.e. some punctuation can be missing in the normalized text)""" - return (idx_out > 0 and idx_in > 0 and normalized_text[idx_out - 1] == input[idx_in - 1]) or ( - idx_out < len(normalized_text) - 1 - and idx_in < len(input) - 1 - and normalized_text[idx_out + 1] == input[idx_in + 1] - ) - - if not equal and not _is_valid(idx_out, idx_in, normalized_text, input): - idx_in += 1 - continue - if idx_in > 0 and idx_out > 0: - if normalized_text[idx_out - 1] == " " and input[idx_in - 1] != " ": - normalized_text[idx_out - 1] = "" - - elif normalized_text[idx_out - 1] != " " and input[idx_in - 1] == " ": - normalized_text[idx_out - 1] += " " - - if idx_in < len(input) - 1 and idx_out < len(normalized_text) - 1: - if normalized_text[idx_out + 1] == " " and input[idx_in + 1] != " ": - normalized_text[idx_out + 1] = "" - elif normalized_text[idx_out + 1] != " " and input[idx_in + 1] == " ": - normalized_text[idx_out] = normalized_text[idx_out] + " " - idx_out += 1 - idx_in += 1 - except: - logging.debug(f"Skipping post-processing of {''.join(normalized_text)} for '{punct}'") - - normalized_text = "".join(normalized_text) - return re.sub(r' +', ' ', normalized_text) diff --git a/nemo_text_processing/text_normalization/de/__init__.py b/nemo_text_processing/text_normalization/de/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/__init__.py b/nemo_text_processing/text_normalization/de/data/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/electronic/__init__.py b/nemo_text_processing/text_normalization/de/data/electronic/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/electronic/domain.tsv b/nemo_text_processing/text_normalization/de/data/electronic/domain.tsv deleted file mode 100644 index 5738cd66ce8f..000000000000 --- a/nemo_text_processing/text_normalization/de/data/electronic/domain.tsv +++ /dev/null @@ -1,9 +0,0 @@ -.com punkt com -.uk punkt uk -.fr punkt fr -.net dot net -.br punkt br -.in punkt in -.ru punkt ru -.de punkt de -.it punkt it \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/electronic/server_name.tsv b/nemo_text_processing/text_normalization/de/data/electronic/server_name.tsv deleted file mode 100644 index c05c20585050..000000000000 --- a/nemo_text_processing/text_normalization/de/data/electronic/server_name.tsv +++ /dev/null @@ -1,12 +0,0 @@ -gmail g mail -nvidia -outlook -hotmail -yahoo -live -yandex -orange -wanadoo -web -comcast -aol \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/electronic/symbols.tsv b/nemo_text_processing/text_normalization/de/data/electronic/symbols.tsv deleted file mode 100644 index 57a0317f8682..000000000000 --- a/nemo_text_processing/text_normalization/de/data/electronic/symbols.tsv +++ /dev/null @@ -1,20 +0,0 @@ -. punkt -: doppelpunkt -- bindestrich -_ unterstrich -! ausrufezeichen -# raute -$ dollar zeichen -% prozent zeichen -& und -' apostroph -* asterisk -+ plus -/ slash -= gleichheitszeichen -? fragezeichen -^ zirkumflex -{ linke klammer auf -} rechte klammer zu -~ tilde -, komma \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/fractions.tsv b/nemo_text_processing/text_normalization/de/data/fractions.tsv deleted file mode 100644 index 50d8847a1fc3..000000000000 --- a/nemo_text_processing/text_normalization/de/data/fractions.tsv +++ /dev/null @@ -1,30 +0,0 @@ -halb zwei -drittel drei -viertel vier -fünftel fünf -sechstel sechs -siebtel sieben -achtel acht -neuntel neun -zehntel zehn -elftel elf -zwölftel zwölf -dreizehntel dreizehn -vierzehntel vierzehn -fünfzehntel fünfzehn -sechzehntel sechzehn -siebzehntel siebzehn -achtzehntel achtzehn -neunzehntel neunzehn -zwanzigstel zwanzig -dreißigstel dreißig -vierzigstel vierzig -fünfzigstel fünfzig -sechzigstel sechzig -siebzigstel siebzig -achtzigstel achtzig -neunzigstel neunzig -hundertstel hundert -tausendstel tausend -millionstel million -milliardstel milliarde \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/measure/__init__.py b/nemo_text_processing/text_normalization/de/data/measure/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/measure/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/measure/measurements.tsv b/nemo_text_processing/text_normalization/de/data/measure/measurements.tsv deleted file mode 100644 index 8292eca7fa2c..000000000000 --- a/nemo_text_processing/text_normalization/de/data/measure/measurements.tsv +++ /dev/null @@ -1,82 +0,0 @@ -% prozent -f fahrenheit -c celsius -°C grad celsius -°F grad fahrenheit -K kelvin -km kilometer -m meter -cm zentimeter -mm millimeter -μm mikrometer -nm nanometer -dm dezimeter -pm pikometer -hm hektometer -ha hektar -mi meile -m² quadrat meter -0.0001 -km² quadrat kilometer -0.0001 -mm² quadrat millimeter -0.0001 -cm² quadrat zentimeter -0.0001 -m³ kubik meter -0.0001 -km³ kubik kilometer -0.0001 -mm³ kubik millimeter -0.0001 -cm³ kubik zentimeter -0.0001 -m2 quadrat meter -km2 quadrat kilometer -mm2 quadrat millimeter -cm2 quadrat zentimeter -m3 kubik meter -km3 kubik kilometer -mm3 kubik millimeter -cm3 kubik zentimeter -ft fuß -g gramm -µg mikrogramm -mg milligramm -kg kilogramm -lb pfund -oz unze -cwt zentner -gr korn -dr drachne -μg mikrogramm -pg petagramm -h stunde -s sekunde -min minute -ds decisekunde -ms millisekunde -μs mikrosekunde -hz hertz -kw kilowatt -kwh kilowattstunde -ghz gigahertz -khz kilohertz -mhz megahertz -v volt -mc megacoulomb -mA milliampere -A ampere -tw terawatt -mv millivolt -mw megawatt -gw gigawatt -ω ohm -db dezibel -gb gigabyte -kb kilobit -pb petabit -mb megabyte -kb kilobyte -tb terabyte -kv kilovolt -mv megavolt -kn kilonewton -ml milliliter -l liter -ma megaampere -bar bar -kcal kilokalorie -cal kalorie \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/measure/suppletive.tsv b/nemo_text_processing/text_normalization/de/data/measure/suppletive.tsv deleted file mode 100644 index 449d545f67b5..000000000000 --- a/nemo_text_processing/text_normalization/de/data/measure/suppletive.tsv +++ /dev/null @@ -1,10 +0,0 @@ -meile meilen -unze unzen -drachne drachnen -stunde stunden -sekunde sekunden -minute minuten -minute minuten -bit bits -byte bytes -kalorie kalorien \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/money/__init__.py b/nemo_text_processing/text_normalization/de/data/money/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/money/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/money/currency.tsv b/nemo_text_processing/text_normalization/de/data/money/currency.tsv deleted file mode 100644 index fa6c618ce5a8..000000000000 --- a/nemo_text_processing/text_normalization/de/data/money/currency.tsv +++ /dev/null @@ -1,25 +0,0 @@ -€ euro -$ dollar -$ us dollar -£ pfund -₩ won -nzd neuseeland dollar -rs rupie -chf schweizer franken -dkk dänische krone -fim finnische mark -aed dirham -¥ yen -czk tschechische krone -mro ouguiya -pkr pakistanische rupie -crc colon -hkd hong kong dollar -npr nepalesische rupee -awg aruba florin -nok norwegische krone -tzs tansania schilling -sek schwedisch krone -cyp zypern pfund -dm d-mark -dm deutsche mark \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/money/currency_minor_plural.tsv b/nemo_text_processing/text_normalization/de/data/money/currency_minor_plural.tsv deleted file mode 100644 index 9818ee743793..000000000000 --- a/nemo_text_processing/text_normalization/de/data/money/currency_minor_plural.tsv +++ /dev/null @@ -1,3 +0,0 @@ -$ cent -€ cent -£ pence \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/money/currency_minor_singular.tsv b/nemo_text_processing/text_normalization/de/data/money/currency_minor_singular.tsv deleted file mode 100644 index fe629d87b693..000000000000 --- a/nemo_text_processing/text_normalization/de/data/money/currency_minor_singular.tsv +++ /dev/null @@ -1,3 +0,0 @@ -$ cent -€ cent -£ penny \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/months/__init__.py b/nemo_text_processing/text_normalization/de/data/months/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/months/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/months/abbr_to_name.tsv b/nemo_text_processing/text_normalization/de/data/months/abbr_to_name.tsv deleted file mode 100644 index 81a323845b14..000000000000 --- a/nemo_text_processing/text_normalization/de/data/months/abbr_to_name.tsv +++ /dev/null @@ -1,13 +0,0 @@ -jan januar -feb februar -mär märz -apr april -mai mai -jun juni -jul juli -aug august -sep september -sept september -okt oktober -nov november -dez dezember \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/months/numbers.tsv b/nemo_text_processing/text_normalization/de/data/months/numbers.tsv deleted file mode 100644 index 012afcc2a34d..000000000000 --- a/nemo_text_processing/text_normalization/de/data/months/numbers.tsv +++ /dev/null @@ -1,24 +0,0 @@ -1 januar -2 februar -3 märz -4 april -5 mai -6 juni -7 juli -8 august -9 september -10 oktober -11 november -12 dezember -01 januar -02 februar -03 märz -04 april -05 mai -06 juni -07 juli -08 august -09 september -10 oktober -11 november -12 dezember \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/numbers/__init__.py b/nemo_text_processing/text_normalization/de/data/numbers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/numbers/digit.tsv b/nemo_text_processing/text_normalization/de/data/numbers/digit.tsv deleted file mode 100644 index 7634e5ac545e..000000000000 --- a/nemo_text_processing/text_normalization/de/data/numbers/digit.tsv +++ /dev/null @@ -1,8 +0,0 @@ -zwei 2 -drei 3 -vier 4 -fünf 5 -sechs 6 -sieben 7 -acht 8 -neun 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/numbers/ones.tsv b/nemo_text_processing/text_normalization/de/data/numbers/ones.tsv deleted file mode 100644 index 7d12cd59b1d8..000000000000 --- a/nemo_text_processing/text_normalization/de/data/numbers/ones.tsv +++ /dev/null @@ -1,3 +0,0 @@ -eine 1 -ein 1 -eins 1 -0.0001 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/numbers/quantities.tsv b/nemo_text_processing/text_normalization/de/data/numbers/quantities.tsv deleted file mode 100644 index 712fe0f38514..000000000000 --- a/nemo_text_processing/text_normalization/de/data/numbers/quantities.tsv +++ /dev/null @@ -1,12 +0,0 @@ -million -millionen -milliarde -milliarden -billion -billionen -billiarde -billiarden -trillion -trillionen -trilliarde -trilliarde \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/numbers/teen.tsv b/nemo_text_processing/text_normalization/de/data/numbers/teen.tsv deleted file mode 100644 index 854712ea6156..000000000000 --- a/nemo_text_processing/text_normalization/de/data/numbers/teen.tsv +++ /dev/null @@ -1,10 +0,0 @@ -zehn 10 -elf 11 -zwölf 12 -dreizehn 13 -vierzehn 14 -fünfzehn 15 -sechzehn 16 -siebzehn 17 -achtzehn 18 -neunzehn 19 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/numbers/ties.tsv b/nemo_text_processing/text_normalization/de/data/numbers/ties.tsv deleted file mode 100644 index 28a3f8032455..000000000000 --- a/nemo_text_processing/text_normalization/de/data/numbers/ties.tsv +++ /dev/null @@ -1,8 +0,0 @@ -zwanzig 2 -dreißig 3 -vierzig 4 -fünfzig 5 -sechzig 6 -siebzig 7 -achtzig 8 -neunzig 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/numbers/zero.tsv b/nemo_text_processing/text_normalization/de/data/numbers/zero.tsv deleted file mode 100644 index e27b1c6405a4..000000000000 --- a/nemo_text_processing/text_normalization/de/data/numbers/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -null 0 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/ordinals/__init__.py b/nemo_text_processing/text_normalization/de/data/ordinals/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/ordinals/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/ordinals/digit.tsv b/nemo_text_processing/text_normalization/de/data/ordinals/digit.tsv deleted file mode 100644 index 31c91f635d80..000000000000 --- a/nemo_text_processing/text_normalization/de/data/ordinals/digit.tsv +++ /dev/null @@ -1,9 +0,0 @@ -ers eins -zwei zwei -drit drei -vier vier -fünf fünf -sechs sechs -sieb sieben -ach acht -neun neun \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/ordinals/thousands.tsv b/nemo_text_processing/text_normalization/de/data/ordinals/thousands.tsv deleted file mode 100644 index a97b94c744da..000000000000 --- a/nemo_text_processing/text_normalization/de/data/ordinals/thousands.tsv +++ /dev/null @@ -1,4 +0,0 @@ -hunderts hundert -tausends tausend -millions million -milliards milliarde \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/ordinals/ties.tsv b/nemo_text_processing/text_normalization/de/data/ordinals/ties.tsv deleted file mode 100644 index 4ab2bd508046..000000000000 --- a/nemo_text_processing/text_normalization/de/data/ordinals/ties.tsv +++ /dev/null @@ -1,8 +0,0 @@ -zwanzigs zwanzig -dreißigs dreißig -vierzigs vierzig -fünfzigs fünfzig -sechzigs sechzig -siebzigs siebzig -achtzigs achtzig -neunzigs neunzig \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/time/__init__.py b/nemo_text_processing/text_normalization/de/data/time/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/data/time/hour_to.tsv b/nemo_text_processing/text_normalization/de/data/time/hour_to.tsv deleted file mode 100644 index e681afc6c25c..000000000000 --- a/nemo_text_processing/text_normalization/de/data/time/hour_to.tsv +++ /dev/null @@ -1,12 +0,0 @@ -1 12 -2 1 -3 2 -4 3 -5 4 -6 5 -7 6 -8 7 -9 8 -10 9 -11 10 -12 11 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/time/hour_to_night.tsv b/nemo_text_processing/text_normalization/de/data/time/hour_to_night.tsv deleted file mode 100644 index b7765ac2a3c6..000000000000 --- a/nemo_text_processing/text_normalization/de/data/time/hour_to_night.tsv +++ /dev/null @@ -1,13 +0,0 @@ -12 0 -1 13 -2 14 -3 15 -4 16 -5 17 -6 18 -7 19 -8 20 -9 21 -10 22 -11 23 -12 24 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/de/data/time/minute_to.tsv b/nemo_text_processing/text_normalization/de/data/time/minute_to.tsv deleted file mode 100644 index edab4d5b03d6..000000000000 --- a/nemo_text_processing/text_normalization/de/data/time/minute_to.tsv +++ /dev/null @@ -1,59 +0,0 @@ -1 59 -2 58 -3 57 -4 56 -5 55 -6 54 -7 53 -8 52 -9 51 -10 50 -11 49 -12 48 -13 47 -14 46 -15 45 -16 44 -17 43 -18 42 -19 41 -20 40 -21 39 -22 38 -23 37 -24 36 -25 35 -26 34 -27 33 -28 32 -29 31 -30 30 -31 29 -32 28 -33 27 -34 26 -35 25 -36 24 -37 23 -38 22 -39 21 -40 20 -41 19 -42 18 -43 17 -44 16 -45 15 -46 14 -47 13 -48 12 -49 11 -50 10 -51 9 -52 8 -53 7 -54 6 -55 5 -56 4 -57 3 -58 2 -59 1 diff --git a/nemo_text_processing/text_normalization/de/data/time/time_zone.tsv b/nemo_text_processing/text_normalization/de/data/time/time_zone.tsv deleted file mode 100644 index 3e0ade467a84..000000000000 --- a/nemo_text_processing/text_normalization/de/data/time/time_zone.tsv +++ /dev/null @@ -1,7 +0,0 @@ -cst c s t -cet c e t -pst p s t -est e s t -pt p t -et e t -gmt g m t diff --git a/nemo_text_processing/text_normalization/de/data/whitelist.tsv b/nemo_text_processing/text_normalization/de/data/whitelist.tsv deleted file mode 100644 index b956ade12298..000000000000 --- a/nemo_text_processing/text_normalization/de/data/whitelist.tsv +++ /dev/null @@ -1,7 +0,0 @@ -z.B. zum beispiel -d.h. dass heißt -Dr. doktor -Mr. mister -Mrs. misses -Ms. miss -Nr. nummer diff --git a/nemo_text_processing/text_normalization/de/taggers/__init__.py b/nemo_text_processing/text_normalization/de/taggers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/taggers/cardinal.py b/nemo_text_processing/text_normalization/de/taggers/cardinal.py deleted file mode 100644 index 8f1a13b0c07c..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/cardinal.py +++ /dev/null @@ -1,199 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from collections import defaultdict - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - delete_space, - insert_space, -) -from pynini.lib import pynutil - -AND = "und" - - -def get_ties_digit(digit_path: str, tie_path: str) -> 'pynini.FstLike': - """ - getting all inverse normalizations for numbers between 21 - 100 - - Args: - digit_path: file to digit tsv - tie_path: file to tie tsv, e.g. 20, 30, etc. - Returns: - res: fst that converts numbers to their verbalization - """ - - digits = defaultdict(list) - ties = defaultdict(list) - for k, v in load_labels(digit_path): - digits[v].append(k) - digits["1"] = ["ein"] - - for k, v in load_labels(tie_path): - ties[v].append(k) - - d = [] - for i in range(21, 100): - s = str(i) - if s[1] == "0": - continue - - for di in digits[s[1]]: - for ti in ties[s[0]]: - word = di + f" {AND} " + ti - d.append((word, s)) - - res = pynini.string_map(d) - return res - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals, e.g. - "101" -> cardinal { integer: "ein hundert und zehn" } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = False): - super().__init__(name="cardinal", kind="classify", deterministic=deterministic) - - graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")).invert() - graph_digit_no_one = pynini.string_file(get_abs_path("data/numbers/digit.tsv")).invert() - graph_one = pynini.string_file(get_abs_path("data/numbers/ones.tsv")).invert() - graph_digit = graph_digit_no_one | graph_one - self.digit = (graph_digit | graph_zero).optimize() - graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")).invert() - - graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")).invert() - # separator = "." - - def tens_no_zero(): - return ( - pynutil.delete("0") + graph_digit - | get_ties_digit( - get_abs_path("data/numbers/digit.tsv"), get_abs_path("data/numbers/ties.tsv") - ).invert() - | graph_teen - | (graph_ties + pynutil.delete("0")) - ) - - def hundred_non_zero(): - return (graph_digit_no_one + insert_space | pynini.cross("1", "ein ")) + pynutil.insert("hundert") + ( - pynini.closure(insert_space + pynutil.insert(AND, weight=0.0001), 0, 1) + insert_space + tens_no_zero() - | pynutil.delete("00") - ) | pynutil.delete("0") + tens_no_zero() - - def thousand(): - return (hundred_non_zero() + insert_space + pynutil.insert("tausend") | pynutil.delete("000")) + ( - insert_space + hundred_non_zero() | pynutil.delete("000") - ) - - optional_plural_quantity_en = pynini.closure(pynutil.insert("en", weight=-0.0001), 0, 1) - optional_plural_quantity_n = pynini.closure(pynutil.insert("n", weight=-0.0001), 0, 1) - graph_million = pynini.union( - hundred_non_zero() + insert_space + pynutil.insert("million") + optional_plural_quantity_en, - pynutil.delete("000"), - ) - - graph_billion = pynini.union( - hundred_non_zero() + insert_space + pynutil.insert("milliarde") + optional_plural_quantity_n, - pynutil.delete("000"), - ) - - graph_trillion = pynini.union( - hundred_non_zero() + insert_space + pynutil.insert("billion") + optional_plural_quantity_en, - pynutil.delete("000"), - ) - - graph_quadrillion = pynini.union( - hundred_non_zero() + insert_space + pynutil.insert("billiarde") + optional_plural_quantity_n, - pynutil.delete("000"), - ) - - graph_quintillion = pynini.union( - hundred_non_zero() + insert_space + pynutil.insert("trillion") + optional_plural_quantity_en, - pynutil.delete("000"), - ) - - graph_sextillion = pynini.union( - hundred_non_zero() + insert_space + pynutil.insert("trilliarde") + optional_plural_quantity_n, - pynutil.delete("000"), - ) - graph = pynini.union( - graph_sextillion - + insert_space - + graph_quintillion - + insert_space - + graph_quadrillion - + insert_space - + graph_trillion - + insert_space - + graph_billion - + insert_space - + graph_million - + insert_space - + thousand() - ) - - fix_syntax = [ - ("eins tausend", "ein tausend"), - ("eins millionen", "eine million"), - ("eins milliarden", "eine milliarde"), - ("eins billionen", "eine billion"), - ("eins billiarden", "eine billiarde"), - ] - fix_syntax = pynini.union(*[pynini.cross(*x) for x in fix_syntax]) - self.graph = ( - ((NEMO_DIGIT - "0" + pynini.closure(NEMO_DIGIT, 0)) - "0" - "1") - @ pynini.cdrewrite(pynini.closure(pynutil.insert("0")), "[BOS]", "", NEMO_SIGMA) - @ NEMO_DIGIT ** 24 - @ graph - @ pynini.cdrewrite(delete_space, "[BOS]", "", NEMO_SIGMA) - @ pynini.cdrewrite(delete_space, "", "[EOS]", NEMO_SIGMA) - @ pynini.cdrewrite(pynini.cross(" ", " "), "", "", NEMO_SIGMA) - @ pynini.cdrewrite(fix_syntax, "[BOS]", "", NEMO_SIGMA) - ) - self.graph |= graph_zero | pynini.cross("1", "eins") - - # self.graph = pynini.cdrewrite(pynutil.delete(separator), "", "", NEMO_SIGMA) @ self.graph - self.graph = self.graph.optimize() - - self.graph_hundred_component_at_least_one_none_zero_digit = ( - ((NEMO_DIGIT - "0" + pynini.closure(NEMO_DIGIT, 0)) - "0" - "1") - @ pynini.cdrewrite(pynini.closure(pynutil.insert("0")), "[BOS]", "", NEMO_SIGMA) - @ NEMO_DIGIT ** 3 - @ hundred_non_zero() - ) | pynini.cross("1", "eins") - - self.graph_hundred_component_at_least_one_none_zero_digit = ( - self.graph_hundred_component_at_least_one_none_zero_digit.optimize() - ) - - self.two_digit_non_zero = ( - pynini.closure(NEMO_DIGIT, 1, 2) @ self.graph_hundred_component_at_least_one_none_zero_digit - ) - - optional_minus_graph = pynini.closure(pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1) - - final_graph = optional_minus_graph + pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/date.py b/nemo_text_processing/text_normalization/de/taggers/date.py deleted file mode 100644 index ab56ad5ce27f..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/date.py +++ /dev/null @@ -1,141 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - TO_LOWER, - GraphFst, - insert_space, -) -from pynini.lib import pynutil - -graph_teen = pynini.invert(pynini.string_file(get_abs_path("data/numbers/teen.tsv"))).optimize() -graph_digit = pynini.invert(pynini.string_file(get_abs_path("data/numbers/digit.tsv"))).optimize() -ties_graph = pynini.invert(pynini.string_file(get_abs_path("data/numbers/ties.tsv"))).optimize() -delete_leading_zero = (pynutil.delete("0") | (NEMO_DIGIT - "0")) + NEMO_DIGIT - - -def get_year_graph(cardinal: GraphFst) -> 'pynini.FstLike': - """ - Returns year verbalizations as fst - - < 2000 neunzehn (hundert) (vier und zwanzig), >= 2000 regular cardinal - **00 ** hundert - - Args: - delete_leading_zero: removed leading zero - cardinal: cardinal GraphFst - """ - - year_gt_2000 = (pynini.union("21", "20") + NEMO_DIGIT ** 2) @ cardinal.graph - - graph_two_digit = delete_leading_zero @ cardinal.two_digit_non_zero - hundred = pynutil.insert("hundert") - graph_double_double = ( - (pynini.accep("1") + NEMO_DIGIT) @ graph_two_digit - + insert_space - + pynini.closure(hundred + insert_space, 0, 1) - + graph_two_digit - ) - # for 20** - graph_double_double |= pynini.accep("20") @ graph_two_digit + insert_space + graph_two_digit - graph = ( - graph_double_double - | (pynini.accep("1") + NEMO_DIGIT) @ graph_two_digit + insert_space + pynutil.delete("00") + hundred - | year_gt_2000 - ) - return graph - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, e.g. - "01.04.2010" -> date { day: "erster" month: "april" year: "zwei tausend zehn" preserve_order: true } - "1994" -> date { year: "neunzehn vier und neuzig" } - "1900" -> date { year: "neunzehn hundert" } - - Args: - cardinal: cardinal GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool): - super().__init__(name="date", kind="classify", deterministic=deterministic) - - month_abbr_graph = load_labels(get_abs_path("data/months/abbr_to_name.tsv")) - number_to_month = pynini.string_file(get_abs_path("data/months/numbers.tsv")).optimize() - month_graph = pynini.union(*[x[1] for x in month_abbr_graph]).optimize() - month_abbr_graph = pynini.string_map(month_abbr_graph) - month_abbr_graph = ( - pynutil.add_weight(month_abbr_graph, weight=0.0001) - | ((TO_LOWER + pynini.closure(NEMO_CHAR)) @ month_abbr_graph) - ) + pynini.closure(pynutil.delete(".", weight=-0.0001), 0, 1) - - self.month_abbr = month_abbr_graph - month_graph |= (TO_LOWER + pynini.closure(NEMO_CHAR)) @ month_graph - # jan.-> januar, Jan-> januar, januar-> januar - month_graph |= month_abbr_graph - - numbers = cardinal.graph_hundred_component_at_least_one_none_zero_digit - optional_leading_zero = delete_leading_zero | NEMO_DIGIT - # 01, 31, 1 - digit_day = optional_leading_zero @ pynini.union(*[str(x) for x in range(1, 32)]) @ numbers - day = (pynutil.insert("day: \"") + digit_day + pynutil.insert("\"")).optimize() - - digit_month = optional_leading_zero @ pynini.union(*[str(x) for x in range(1, 13)]) - number_to_month = digit_month @ number_to_month - digit_month @= numbers - - month_name = (pynutil.insert("month: \"") + month_graph + pynutil.insert("\"")).optimize() - month_number = ( - pynutil.insert("month: \"") - + (pynutil.add_weight(digit_month, weight=0.0001) | number_to_month) - + pynutil.insert("\"") - ).optimize() - - # prefer cardinal over year - year = pynutil.add_weight(get_year_graph(cardinal=cardinal), weight=0.001) - self.year = year - - year_only = pynutil.insert("year: \"") + year + pynutil.insert("\"") - - graph_dmy = ( - day - + pynutil.delete(".") - + pynini.closure(pynutil.delete(" "), 0, 1) - + insert_space - + month_name - + pynini.closure(pynini.accep(" ") + year_only, 0, 1) - ) - - separators = ["."] - for sep in separators: - year_optional = pynini.closure(pynini.cross(sep, " ") + year_only, 0, 1) - new_graph = day + pynini.cross(sep, " ") + month_number + year_optional - graph_dmy |= new_graph - - dash = "-" - day_optional = pynini.closure(pynini.cross(dash, " ") + day, 0, 1) - graph_ymd = year_only + pynini.cross(dash, " ") + month_number + day_optional - - final_graph = graph_dmy + pynutil.insert(" preserve_order: true") - final_graph |= year_only - final_graph |= graph_ymd - - self.final_graph = final_graph.optimize() - self.fst = self.add_tokens(self.final_graph).optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/decimal.py b/nemo_text_processing/text_normalization/de/taggers/decimal.py deleted file mode 100644 index d5cd58ed0970..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/decimal.py +++ /dev/null @@ -1,82 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, insert_space -from pynini.lib import pynutil - -quantities = pynini.string_file(get_abs_path("data/numbers/quantities.tsv")) - - -def get_quantity(decimal: 'pynini.FstLike', cardinal_up_to_hundred: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. 1 million -> integer_part: "eine" quantity: "million" - e.g. 1.4 million -> integer_part: "eins" fractional_part: "vier" quantity: "million" - - Args: - decimal: decimal FST - cardinal_up_to_hundred: cardinal FST - """ - numbers = cardinal_up_to_hundred - - res = ( - pynutil.insert("integer_part: \"") - + numbers - + pynutil.insert("\"") - + pynini.accep(" ") - + pynutil.insert("quantity: \"") - + quantities - + pynutil.insert("\"") - ) - res |= decimal + pynini.accep(" ") + pynutil.insert("quantity: \"") + quantities + pynutil.insert("\"") - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal, e.g. - -11,4006 billion -> decimal { negative: "true" integer_part: "elf" fractional_part: "vier null null sechs" quantity: "billion" preserve_order: true } - 1 billion -> decimal { integer_part: "eins" quantity: "billion" preserve_order: true } - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - - graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")).invert() - graph_digit |= pynini.string_file(get_abs_path("data/numbers/zero.tsv")).invert() - graph_digit |= pynini.cross("1", "eins") - self.graph = graph_digit + pynini.closure(insert_space + graph_digit).optimize() - - point = pynutil.delete(",") - optional_graph_negative = pynini.closure(pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1) - - self.graph_fractional = pynutil.insert("fractional_part: \"") + self.graph + pynutil.insert("\"") - self.graph_integer = pynutil.insert("integer_part: \"") + cardinal.graph + pynutil.insert("\"") - final_graph_wo_sign = self.graph_integer + point + insert_space + self.graph_fractional - - self.final_graph_wo_negative = final_graph_wo_sign | get_quantity( - final_graph_wo_sign, cardinal.graph_hundred_component_at_least_one_none_zero_digit - ) - final_graph = optional_graph_negative + self.final_graph_wo_negative - final_graph += pynutil.insert(" preserve_order: true") - - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/electronic.py b/nemo_text_processing/text_normalization/de/taggers/electronic.py deleted file mode 100644 index 53a859700425..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/electronic.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_ALPHA, NEMO_DIGIT, GraphFst, insert_space -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic: email addresses - e.g. "abc@hotmail.com" -> electronic { username: "abc" domain: "hotmail.com" preserve_order: true } - e.g. "www.abc.com/123" -> electronic { protocol: "www." domain: "abc.com/123" preserve_order: true } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="classify", deterministic=deterministic) - - dot = pynini.accep(".") - accepted_common_domains = [x[0] for x in load_labels(get_abs_path("data/electronic/domain.tsv"))] - accepted_common_domains = pynini.union(*accepted_common_domains) - accepted_symbols = [x[0] for x in load_labels(get_abs_path("data/electronic/symbols.tsv"))] - accepted_symbols = pynini.union(*accepted_symbols) - dot - accepted_characters = pynini.closure(NEMO_ALPHA | NEMO_DIGIT | accepted_symbols) - - # email - username = pynutil.insert("username: \"") + accepted_characters + pynutil.insert("\"") + pynini.cross('@', ' ') - domain_graph = accepted_characters + dot + accepted_characters - domain_graph = pynutil.insert("domain: \"") + domain_graph + pynutil.insert("\"") - domain_common_graph = ( - pynutil.insert("domain: \"") - + accepted_characters - + accepted_common_domains - + pynini.closure((accepted_symbols | dot) + pynini.closure(accepted_characters, 1), 0, 1) - + pynutil.insert("\"") - ) - graph = (username + domain_graph) | domain_common_graph - - # url - protocol_start = pynini.accep("https://") | pynini.accep("http://") - protocol_end = pynini.accep("www.") - protocol = protocol_start | protocol_end | (protocol_start + protocol_end) - protocol = pynutil.insert("protocol: \"") + protocol + pynutil.insert("\"") - graph |= protocol + insert_space + (domain_graph | domain_common_graph) - self.graph = graph - - final_graph = self.add_tokens(self.graph + pynutil.insert(" preserve_order: true")) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/fraction.py b/nemo_text_processing/text_normalization/de/taggers/fraction.py deleted file mode 100644 index 71d51c600b2f..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/fraction.py +++ /dev/null @@ -1,54 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for classifying fraction - "23 4/6" -> - fraction { integer: "drei und zwanzig" numerator: "vier" denominator: "sechs" preserve_order: true } - - Args: - cardinal: cardinal GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal, deterministic: bool = True): - super().__init__(name="fraction", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph - - self.optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1 - ) - self.integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - self.numerator = ( - pynutil.insert("numerator: \"") + cardinal_graph + pynini.cross(pynini.union("/", " / "), "\" ") - ) - self.denominator = pynutil.insert("denominator: \"") + cardinal_graph + pynutil.insert("\"") - - self.graph = ( - self.optional_graph_negative - + pynini.closure(self.integer + pynini.accep(" "), 0, 1) - + self.numerator - + self.denominator - ) - - graph = self.graph + pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/measure.py b/nemo_text_processing/text_normalization/de/taggers/measure.py deleted file mode 100644 index c9dbe412056f..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/measure.py +++ /dev/null @@ -1,187 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_NON_BREAKING_SPACE, - NEMO_SIGMA, - GraphFst, - convert_space, - insert_space, -) -from pynini.examples import plurals -from pynini.lib import pynutil - -unit_singular = pynini.string_file(get_abs_path("data/measure/measurements.tsv")) -suppletive = pynini.string_file(get_abs_path("data/measure/suppletive.tsv")) - - -def singular_to_plural(): - # plural endung n/en maskuline Nomen mit den Endungen e, ent, and, ant, ist, or - _n = NEMO_SIGMA + pynini.union("e") + pynutil.insert("n") - _en = ( - NEMO_SIGMA - + pynini.union("ent", "and", "ant", "ist", "or", "ion", "ik", "heit", "keit", "schaft", "tät", "ung") - + pynutil.insert("en") - ) - _nen = NEMO_SIGMA + pynini.union("in") + (pynutil.insert("e") | pynutil.insert("nen")) - _fremd = NEMO_SIGMA + pynini.union("ma", "um", "us") + pynutil.insert("en") - # maskuline Nomen mit den Endungen eur, ich, ier, ig, ling, ör - _e = NEMO_SIGMA + pynini.union("eur", "ich", "ier", "ig", "ling", "ör") + pynutil.insert("e") - _s = NEMO_SIGMA + pynini.union("a", "i", "o", "u", "y") + pynutil.insert("s") - - graph_plural = plurals._priority_union( - suppletive, pynini.union(_n, _en, _nen, _fremd, _e, _s), NEMO_SIGMA - ).optimize() - - return graph_plural - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure, e.g. - "2,4 oz" -> measure { cardinal { integer_part: "zwei" fractional_part: "vier" units: "unzen" preserve_order: true } } - "1 oz" -> measure { cardinal { integer: "zwei" units: "unze" preserve_order: true } } - "1 million oz" -> measure { cardinal { integer: "eins" quantity: "million" units: "unze" preserve_order: true } } - This class also converts words containing numbers and letters - e.g. "a-8" —> "a acht" - e.g. "1,2-a" —> "ein komma zwei a" - - Args: - cardinal: CardinalFst - decimal: DecimalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, fraction: GraphFst, deterministic: bool = True): - super().__init__(name="measure", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph - - graph_unit_singular = convert_space(unit_singular) - graph_unit_plural = graph_unit_singular @ pynini.cdrewrite(convert_space(suppletive), "", "[EOS]", NEMO_SIGMA) - optional_graph_negative = pynini.closure("-", 0, 1) - - graph_unit_denominator = ( - pynini.cross("/", "pro") + pynutil.insert(NEMO_NON_BREAKING_SPACE) + graph_unit_singular - ) - - optional_unit_denominator = pynini.closure( - pynutil.insert(NEMO_NON_BREAKING_SPACE) + graph_unit_denominator, 0, 1, - ) - - unit_plural = ( - pynutil.insert("units: \"") - + (graph_unit_plural + (optional_unit_denominator) | graph_unit_denominator) - + pynutil.insert("\"") - ) - - unit_singular_graph = ( - pynutil.insert("units: \"") - + ((graph_unit_singular + optional_unit_denominator) | graph_unit_denominator) - + pynutil.insert("\"") - ) - - subgraph_decimal = decimal.fst + insert_space + pynini.closure(pynutil.delete(" "), 0, 1) + unit_plural - - subgraph_cardinal = ( - (optional_graph_negative + (pynini.closure(NEMO_DIGIT) - "1")) @ cardinal.fst - + insert_space - + pynini.closure(pynutil.delete(" "), 0, 1) - + unit_plural - ) - - subgraph_cardinal |= ( - (optional_graph_negative + pynini.accep("1")) - @ cardinal.fst - @ pynini.cdrewrite(pynini.cross("eins", "ein"), "", "", NEMO_SIGMA) - + insert_space - + pynini.closure(pynutil.delete(" "), 0, 1) - + unit_singular_graph - ) - - subgraph_fraction = fraction.fst + insert_space + pynini.closure(pynutil.delete(" "), 0, 1) + unit_plural - - cardinal_dash_alpha = ( - pynutil.insert("cardinal { integer: \"") - + cardinal_graph - + pynutil.delete('-') - + pynutil.insert("\" } units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.insert("\"") - ) - - alpha_dash_cardinal = ( - pynutil.insert("units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.delete('-') - + pynutil.insert("\"") - + pynutil.insert(" cardinal { integer: \"") - + cardinal_graph - + pynutil.insert("\" }") - ) - - decimal_dash_alpha = ( - pynutil.insert("decimal { ") - + decimal.final_graph_wo_negative - + pynutil.delete('-') - + pynutil.insert(" } units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.insert("\"") - ) - - decimal_times = ( - pynutil.insert("decimal { ") - + decimal.final_graph_wo_negative - + pynutil.insert(" } units: \"") - + pynini.union('x', 'X') - + pynutil.insert("\"") - ) - - cardinal_times = ( - pynutil.insert("cardinal { integer: \"") - + cardinal_graph - + pynutil.insert("\" } units: \"") - + pynini.union('x', 'X') - + pynutil.insert("\"") - ) - - alpha_dash_decimal = ( - pynutil.insert("units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.delete('-') - + pynutil.insert("\"") - + pynutil.insert(" decimal { ") - + decimal.final_graph_wo_negative - + pynutil.insert(" }") - ) - - final_graph = ( - subgraph_decimal - | subgraph_cardinal - | cardinal_dash_alpha - | alpha_dash_cardinal - | decimal_dash_alpha - | decimal_times - | alpha_dash_decimal - | subgraph_fraction - | cardinal_times - ) - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/money.py b/nemo_text_processing/text_normalization/de/taggers/money.py deleted file mode 100644 index bc27d41596a4..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/money.py +++ /dev/null @@ -1,148 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - convert_space, - insert_space, -) -from pynini.lib import pynutil - -min_singular = pynini.string_file(get_abs_path("data/money/currency_minor_singular.tsv")) -min_plural = pynini.string_file(get_abs_path("data/money/currency_minor_plural.tsv")) -maj_singular = pynini.string_file((get_abs_path("data/money/currency.tsv"))) - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money, e.g. - "€1" -> money { currency_maj: "euro" integer_part: "ein"} - "€1,000" -> money { currency_maj: "euro" integer_part: "ein" } - "€1,001" -> money { currency_maj: "euro" integer_part: "eins" fractional_part: "null null eins"} - "£1,4" -> money { integer_part: "ein" currency_maj: "pfund" fractional_part: "vierzig" preserve_order: true} - -> money { integer_part: "ein" currency_maj: "pfund" fractional_part: "vierzig" currency_min: "pence" preserve_order: true} - "£0,01" -> money { fractional_part: "ein" currency_min: "penny" preserve_order: true} - "£0,01 million" -> money { currency_maj: "pfund" integer_part: "null" fractional_part: "null eins" quantity: "million"} - - Args: - cardinal: CardinalFst - decimal: DecimalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph - graph_decimal_final = decimal.fst - - maj_singular_labels = load_labels(get_abs_path("data/money/currency.tsv")) - maj_singular_graph = convert_space(maj_singular) - maj_plural_graph = maj_singular_graph - - graph_maj_singular = pynutil.insert("currency_maj: \"") + maj_singular_graph + pynutil.insert("\"") - graph_maj_plural = pynutil.insert("currency_maj: \"") + maj_plural_graph + pynutil.insert("\"") - - optional_delete_fractional_zeros = pynini.closure( - pynutil.delete(",") + pynini.closure(pynutil.delete("0"), 1), 0, 1 - ) - graph_integer_one = pynutil.insert("integer_part: \"") + pynini.cross("1", "ein") + pynutil.insert("\"") - - # only for decimals where third decimal after comma is non-zero or with quantity - decimal_delete_last_zeros = ( - pynini.closure(NEMO_DIGIT, 1) - + pynini.accep(",") - + pynini.closure(NEMO_DIGIT, 2) - + (NEMO_DIGIT - "0") - + pynini.closure(pynutil.delete("0")) - ) - decimal_with_quantity = NEMO_SIGMA + NEMO_ALPHA - graph_decimal = ( - graph_maj_plural + insert_space + (decimal_delete_last_zeros | decimal_with_quantity) @ graph_decimal_final - ) - - graph_integer = ( - pynutil.insert("integer_part: \"") + ((NEMO_SIGMA - "1") @ cardinal_graph) + pynutil.insert("\"") - ) - - graph_integer_only = graph_maj_singular + insert_space + graph_integer_one - graph_integer_only |= graph_maj_plural + insert_space + graph_integer - - graph = (graph_integer_only + optional_delete_fractional_zeros) | graph_decimal - - # remove trailing zeros of non zero number in the first 2 digits and fill up to 2 digits - # e.g. 2000 -> 20, 0200->02, 01 -> 01, 10 -> 10 - # not accepted: 002, 00, 0, - two_digits_fractional_part = ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(pynutil.delete("0")) - ) @ ( - (pynutil.delete("0") + (NEMO_DIGIT - "0")) - | ((NEMO_DIGIT - "0") + pynutil.insert("0")) - | ((NEMO_DIGIT - "0") + NEMO_DIGIT) - ) - - graph_min_singular = pynutil.insert(" currency_min: \"") + min_singular + pynutil.insert("\"") - graph_min_plural = pynutil.insert(" currency_min: \"") + min_plural + pynutil.insert("\"") - - # format ** euro ** cent - decimal_graph_with_minor = None - for curr_symbol, _ in maj_singular_labels: - preserve_order = pynutil.insert(" preserve_order: true") - integer_plus_maj = graph_integer + insert_space + pynutil.insert(curr_symbol) @ graph_maj_plural - integer_plus_maj |= graph_integer_one + insert_space + pynutil.insert(curr_symbol) @ graph_maj_singular - # non zero integer part - integer_plus_maj = (pynini.closure(NEMO_DIGIT) - "0") @ integer_plus_maj - - graph_fractional_one = two_digits_fractional_part @ pynini.cross("1", "ein") - graph_fractional_one = pynutil.insert("fractional_part: \"") + graph_fractional_one + pynutil.insert("\"") - graph_fractional = ( - two_digits_fractional_part @ (pynini.closure(NEMO_DIGIT, 1, 2) - "1") @ cardinal.two_digit_non_zero - ) - graph_fractional = pynutil.insert("fractional_part: \"") + graph_fractional + pynutil.insert("\"") - - fractional_plus_min = graph_fractional + insert_space + pynutil.insert(curr_symbol) @ graph_min_plural - fractional_plus_min |= ( - graph_fractional_one + insert_space + pynutil.insert(curr_symbol) @ graph_min_singular - ) - - decimal_graph_with_minor_curr = integer_plus_maj + pynini.cross(",", " ") + fractional_plus_min - decimal_graph_with_minor_curr |= pynutil.add_weight( - integer_plus_maj - + pynini.cross(",", " ") - + pynutil.insert("fractional_part: \"") - + two_digits_fractional_part @ cardinal.two_digit_non_zero - + pynutil.insert("\""), - weight=0.0001, - ) - - decimal_graph_with_minor_curr |= pynutil.delete("0,") + fractional_plus_min - decimal_graph_with_minor_curr = ( - pynutil.delete(curr_symbol) + decimal_graph_with_minor_curr + preserve_order - ) - - decimal_graph_with_minor = ( - decimal_graph_with_minor_curr - if decimal_graph_with_minor is None - else pynini.union(decimal_graph_with_minor, decimal_graph_with_minor_curr) - ) - - final_graph = graph | decimal_graph_with_minor - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/ordinal.py b/nemo_text_processing/text_normalization/de/taggers/ordinal.py deleted file mode 100644 index 5644665518b0..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/ordinal.py +++ /dev/null @@ -1,49 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Adapted from https://github.com/google/TextNormalizationCoveringGrammars -# Russian minimally supervised number grammar. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals, e.g. - "2." -> ordinal { integer: "zwei" } } - "2tes" -> ordinal { integer: "zwei" } } - - Args: - cardinal: cardinal GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic=False): - super().__init__(name="ordinal", kind="classify", deterministic=deterministic) - - cardinal_graph = cardinal.graph - endings = ["ter", "tes", "tem", "te", "ten"] - self.graph = ( - ( - pynini.closure(NEMO_DIGIT | pynini.accep(".")) - + pynutil.delete(pynutil.add_weight(pynini.union(*endings), weight=0.0001) | pynini.accep(".")) - ) - @ cardinal_graph - ).optimize() - final_graph = pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/telephone.py b/nemo_text_processing/text_normalization/de/taggers/telephone.py deleted file mode 100644 index f4306b9be773..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/telephone.py +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst, insert_space -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone, which includes country code, number part and extension - - E.g - "+49 1234-1233" -> telephone { country_code: "plus neun und vierzig" number_part: "eins zwei drei vier eins zwei drei drei" preserve_order: true } - "(012) 1234-1233" -> telephone { country_code: "null eins zwei" number_part: "eins zwei drei vier eins zwei drei drei" preserve_order: true } - (0**) - - Args: - cardinal: cardinal GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="telephone", kind="classify", deterministic=deterministic) - - graph_zero = pynini.invert(pynini.string_file(get_abs_path("data/numbers/zero.tsv"))).optimize() - graph_digit_no_zero = pynini.invert( - pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - ).optimize() | pynini.cross("1", "eins") - graph_digit = graph_digit_no_zero | graph_zero - - numbers_with_single_digits = pynini.closure(graph_digit + insert_space) + graph_digit - - two_digit_and_zero = (NEMO_DIGIT ** 2 @ cardinal.two_digit_non_zero) | graph_zero - # def add_space_after_two_digit(): - # return pynini.closure(two_digit_and_zero + insert_space) + ( - # two_digit_and_zero - # ) - - country_code = pynini.closure(pynini.cross("+", "plus "), 0, 1) + two_digit_and_zero - country_code |= ( - pynutil.delete("(") + graph_zero + insert_space + numbers_with_single_digits + pynutil.delete(")") - ) - country_code |= graph_zero + insert_space + numbers_with_single_digits - - country_code = pynutil.insert("country_code: \"") + country_code + pynutil.insert("\"") - - del_separator = pynini.cross(pynini.union("-", " "), " ") - # numbers_with_two_digits = pynini.closure(graph_digit + insert_space) + add_space_after_two_digit() + pynini.closure(insert_space + graph_digit) - # numbers = numbers_with_two_digits + pynini.closure(del_separator + numbers_with_two_digits, 0, 1) - numbers = numbers_with_single_digits + pynini.closure(del_separator + numbers_with_single_digits, 0, 1) - number_length = pynini.closure((NEMO_DIGIT | pynini.union("-", " ", ")", "(")), 7) - number_part = pynini.compose(number_length, numbers) - number = pynutil.insert("number_part: \"") + number_part + pynutil.insert("\"") - - graph = country_code + pynini.accep(" ") + number - self.graph = graph - final_graph = self.add_tokens(self.graph + pynutil.insert(" preserve_order: true")) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/time.py b/nemo_text_processing/text_normalization/de/taggers/time.py deleted file mode 100644 index b9e244635eff..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/time.py +++ /dev/null @@ -1,97 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst, convert_space, insert_space -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time, e.g. - "02:15 Uhr est" -> time { hours: "2" minutes: "15" zone: "e s t"} - "2 Uhr" -> time { hours: "2" } - "09:00 Uhr" -> time { hours: "2" } - "02:15:10 Uhr" -> time { hours: "2" minutes: "15" seconds: "10"} - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="time", kind="classify", deterministic=deterministic) - - final_suffix = pynutil.delete(" ") + pynutil.delete("Uhr") | pynutil.delete("uhr") - time_zone_graph = pynini.string_file(get_abs_path("data/time/time_zone.tsv")) - - labels_hour = [str(x) for x in range(0, 25)] - labels_minute_single = [str(x) for x in range(1, 10)] - labels_minute_double = [str(x) for x in range(10, 60)] - - delete_leading_zero_to_double_digit = (pynutil.delete("0") | (NEMO_DIGIT - "0")) + NEMO_DIGIT - - graph_hour = pynini.union(*labels_hour) - - graph_minute_single = pynini.union(*labels_minute_single) - graph_minute_double = pynini.union(*labels_minute_double) - - final_graph_hour_only = pynutil.insert("hours: \"") + graph_hour + pynutil.insert("\"") - final_graph_hour = ( - pynutil.insert("hours: \"") + delete_leading_zero_to_double_digit @ graph_hour + pynutil.insert("\"") - ) - final_graph_minute = ( - pynutil.insert("minutes: \"") - + (pynutil.delete("0") + graph_minute_single | graph_minute_double) - + pynutil.insert("\"") - ) - final_graph_second = ( - pynutil.insert("seconds: \"") - + (pynutil.delete("0") + graph_minute_single | graph_minute_double) - + pynutil.insert("\"") - ) - final_time_zone_optional = pynini.closure( - pynini.accep(" ") + pynutil.insert("zone: \"") + convert_space(time_zone_graph) + pynutil.insert("\""), - 0, - 1, - ) - - # 02:30 Uhr - graph_hm = ( - final_graph_hour - + pynutil.delete(":") - + (pynutil.delete("00") | (insert_space + final_graph_minute)) - + final_suffix - + final_time_zone_optional - ) - - # 10:30:05 Uhr, - graph_hms = ( - final_graph_hour - + pynutil.delete(":") - + (pynini.cross("00", " minutes: \"0\"") | (insert_space + final_graph_minute)) - + pynutil.delete(":") - + (pynini.cross("00", " seconds: \"0\"") | (insert_space + final_graph_second)) - + final_suffix - + final_time_zone_optional - + pynutil.insert(" preserve_order: true") - ) - - # 2 Uhr est - graph_h = final_graph_hour_only + final_suffix + final_time_zone_optional - final_graph = (graph_hm | graph_h | graph_hms).optimize() - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/tokenize_and_classify.py b/nemo_text_processing/text_normalization/de/taggers/tokenize_and_classify.py deleted file mode 100644 index a446fcfdb714..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,144 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.de.taggers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.de.taggers.date import DateFst -from nemo_text_processing.text_normalization.de.taggers.decimal import DecimalFst -from nemo_text_processing.text_normalization.de.taggers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.de.taggers.fraction import FractionFst -from nemo_text_processing.text_normalization.de.taggers.measure import MeasureFst -from nemo_text_processing.text_normalization.de.taggers.money import MoneyFst -from nemo_text_processing.text_normalization.de.taggers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.de.taggers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.de.taggers.time import TimeFst -from nemo_text_processing.text_normalization.de.taggers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.de.taggers.word import WordFst -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is - lower cased. For deployment, this grammar will be compiled and exported to OpenFst Finite State Archive (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - """ - - def __init__( - self, - input_case: str, - deterministic: bool = False, - cache_dir: str = None, - overwrite_cache: bool = False, - whitelist: str = None, - ): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - whitelist_file = os.path.basename(whitelist) if whitelist else "" - far_file = os.path.join( - cache_dir, f"_{input_case}_de_tn_{deterministic}_deterministic{whitelist_file}.far" - ) - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - no_digits = pynini.closure(pynini.difference(NEMO_CHAR, NEMO_DIGIT)) - self.fst_no_digits = pynini.compose(self.fst, no_digits).optimize() - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars. This might take some time...") - - self.cardinal = CardinalFst(deterministic=deterministic) - cardinal_graph = self.cardinal.fst - - self.ordinal = OrdinalFst(cardinal=self.cardinal, deterministic=deterministic) - ordinal_graph = self.ordinal.fst - - self.decimal = DecimalFst(cardinal=self.cardinal, deterministic=deterministic) - decimal_graph = self.decimal.fst - - self.fraction = FractionFst(cardinal=self.cardinal, deterministic=deterministic) - fraction_graph = self.fraction.fst - self.measure = MeasureFst( - cardinal=self.cardinal, decimal=self.decimal, fraction=self.fraction, deterministic=deterministic - ) - measure_graph = self.measure.fst - self.date = DateFst(cardinal=self.cardinal, deterministic=deterministic) - date_graph = self.date.fst - word_graph = WordFst(deterministic=deterministic).fst - self.time = TimeFst(deterministic=deterministic) - time_graph = self.time.fst - self.telephone = TelephoneFst(cardinal=self.cardinal, deterministic=deterministic) - telephone_graph = self.telephone.fst - self.electronic = ElectronicFst(deterministic=deterministic) - electronic_graph = self.electronic.fst - self.money = MoneyFst(cardinal=self.cardinal, decimal=self.decimal, deterministic=deterministic) - money_graph = self.money.fst - self.whitelist = WhiteListFst(input_case=input_case, deterministic=deterministic, input_file=whitelist) - whitelist_graph = self.whitelist.fst - punct_graph = PunctuationFst(deterministic=deterministic).fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.1) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(fraction_graph, 1.1) - | pynutil.add_weight(date_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(decimal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - ) - - classify |= pynutil.add_weight(word_graph, 100) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(pynutil.add_weight(delete_extra_space, 1.1) + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - no_digits = pynini.closure(pynini.difference(NEMO_CHAR, NEMO_DIGIT)) - self.fst_no_digits = pynini.compose(self.fst, no_digits).optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/de/taggers/whitelist.py b/nemo_text_processing/text_normalization/de/taggers/whitelist.py deleted file mode 100644 index 4e8829bf17c9..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/whitelist.py +++ /dev/null @@ -1,63 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelist, e.g. - "Mr." -> tokens { name: "mister" } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - input_file: path to a file with whitelist replacements - """ - - def __init__(self, input_case: str, deterministic: bool = True, input_file: str = None): - super().__init__(name="whitelist", kind="classify", deterministic=deterministic) - - def _get_whitelist_graph(input_case, file): - whitelist = load_labels(file) - if input_case == "lower_cased": - whitelist = [[x[0].lower()] + x[1:] for x in whitelist] - graph = pynini.string_map(whitelist) - return graph - - graph = _get_whitelist_graph(input_case, get_abs_path("data/whitelist.tsv")) - if not deterministic and input_case != "lower_cased": - graph |= pynutil.add_weight( - _get_whitelist_graph("lower_cased", get_abs_path("data/whitelist.tsv")), weight=0.0001 - ) - - if input_file: - whitelist_provided = _get_whitelist_graph(input_case, input_file) - if not deterministic: - graph |= whitelist_provided - else: - graph = whitelist_provided - - if not deterministic: - units_graph = _get_whitelist_graph(input_case, file=get_abs_path("data/measure/measurements.tsv")) - graph |= units_graph - - self.graph = graph - self.final_graph = convert_space(self.graph).optimize() - self.fst = (pynutil.insert("name: \"") + self.final_graph + pynutil.insert("\"")).optimize() diff --git a/nemo_text_processing/text_normalization/de/taggers/word.py b/nemo_text_processing/text_normalization/de/taggers/word.py deleted file mode 100644 index 16743d28b574..000000000000 --- a/nemo_text_processing/text_normalization/de/taggers/word.py +++ /dev/null @@ -1,33 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying word. - e.g. sleep -> tokens { name: "sleep" } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="word", kind="classify") - word = pynutil.insert("name: \"") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert("\"") - self.fst = word.optimize() diff --git a/nemo_text_processing/text_normalization/de/utils.py b/nemo_text_processing/text_normalization/de/utils.py deleted file mode 100644 index 9186c73dbe6e..000000000000 --- a/nemo_text_processing/text_normalization/de/utils.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import csv -import os - -from nemo.utils import logging - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - abs_path = os.path.dirname(os.path.abspath(__file__)) + os.sep + rel_path - - if not os.path.exists(abs_path): - logging.warning(f'{abs_path} does not exist') - return abs_path - - -def load_labels(abs_path): - """ - loads relative path file as dictionary - - Args: - abs_path: absolute path - - Returns dictionary of mappings - """ - with open(abs_path, encoding="utf-8") as label_tsv: - labels = list(csv.reader(label_tsv, delimiter="\t")) - return labels diff --git a/nemo_text_processing/text_normalization/de/verbalizers/__init__.py b/nemo_text_processing/text_normalization/de/verbalizers/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/de/verbalizers/cardinal.py b/nemo_text_processing/text_normalization/de/verbalizers/cardinal.py deleted file mode 100644 index 6adf17dd78ea..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/cardinal.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinals - e.g. cardinal { integer: "zwei" } -> "zwei" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="cardinal", kind="verbalize", deterministic=deterministic) - optional_sign = pynini.closure(pynini.cross("negative: \"true\" ", "minus "), 0, 1) - self.optional_sign = optional_sign - integer = pynini.closure(NEMO_NOT_QUOTE, 1) - - self.integer = pynutil.delete(" \"") + integer + pynutil.delete("\"") - - integer = pynutil.delete("integer:") + self.integer - self.numbers = integer - graph = optional_sign + self.numbers - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/date.py b/nemo_text_processing/text_normalization/de/verbalizers/date.py deleted file mode 100644 index 2a1a8ed72546..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/date.py +++ /dev/null @@ -1,61 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_preserve_order, -) -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { day: "vier" month: "april" year: "zwei tausend zwei" } -> "vierter april zwei tausend zwei" - date { day: "vier" month: "mai" year: "zwei tausend zwei" } -> "vierter mai zwei tausend zwei" - - Args: - ordinal: ordinal verbalizer GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, ordinal: GraphFst, deterministic: bool = True): - super().__init__(name="date", kind="verbalize", deterministic=deterministic) - - day_cardinal = pynutil.delete("day: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - day = day_cardinal @ pynini.cdrewrite(ordinal.ordinal_stem, "", "[EOS]", NEMO_SIGMA) + pynutil.insert("ter") - - months_names = pynini.union(*[x[1] for x in load_labels(get_abs_path("data/months/abbr_to_name.tsv"))]) - month = pynutil.delete("month: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - final_month = month @ months_names - final_month |= month @ pynini.difference(NEMO_SIGMA, months_names) @ pynini.cdrewrite( - ordinal.ordinal_stem, "", "[EOS]", NEMO_SIGMA - ) + pynutil.insert("ter") - - year = pynutil.delete("year: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - # day month year - graph_dmy = day + pynini.accep(" ") + final_month + pynini.closure(pynini.accep(" ") + year, 0, 1) - graph_dmy |= final_month + pynini.accep(" ") + year - - self.graph = graph_dmy | year - final_graph = self.graph + delete_preserve_order - - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/decimal.py b/nemo_text_processing/text_normalization/de/verbalizers/decimal.py deleted file mode 100644 index 4e5ac7f9411e..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/decimal.py +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.taggers.decimal import quantities -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_preserve_order, - insert_space, -) -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal, e.g. - decimal { negative: "true" integer_part: "elf" fractional_part: "vier null sechs" quantity: "billionen" } -> minus elf komma vier null sechs billionen - decimal { integer_part: "eins" quantity: "billion" } -> eins billion - - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - - delete_space = pynutil.delete(" ") - self.optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "minus ") + delete_space, 0, 1) - self.integer = pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - self.fractional_default = ( - pynutil.delete("fractional_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) - - self.fractional = pynutil.insert(" komma ") + self.fractional_default - - self.quantity = ( - delete_space + insert_space + pynutil.delete("quantity: \"") + quantities + pynutil.delete("\"") - ) - self.optional_quantity = pynini.closure(self.quantity, 0, 1) - - graph = self.optional_sign + ( - self.integer + self.quantity | self.integer + delete_space + self.fractional + self.optional_quantity - ) - - self.numbers = graph - graph += delete_preserve_order - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/electronic.py b/nemo_text_processing/text_normalization/de/verbalizers/electronic.py deleted file mode 100644 index 184ce01b1c5f..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/electronic.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_preserve_order, - insert_space, -) -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. electronic { username: "abc" domain: "hotmail.com" } -> "a b c at hotmail punkt com" - -> "a b c at h o t m a i l punkt c o m" - -> "a b c at hotmail punkt c o m" - -> "a b c at h o t m a i l punkt com" - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="verbalize", deterministic=deterministic) - graph_digit_no_zero = pynini.invert( - pynini.string_file(get_abs_path("data/numbers/digit.tsv")) - ).optimize() | pynini.cross("1", "eins") - graph_zero = pynini.invert(pynini.string_file(get_abs_path("data/numbers/zero.tsv"))).optimize() - graph_digit = graph_digit_no_zero | graph_zero - graph_symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")).optimize() - server_common = pynini.string_file(get_abs_path("data/electronic/server_name.tsv")) - domain_common = pynini.string_file(get_abs_path("data/electronic/domain.tsv")) - - def add_space_after_char(): - return pynini.closure(NEMO_NOT_QUOTE - pynini.accep(" ") + insert_space) + ( - NEMO_NOT_QUOTE - pynini.accep(" ") - ) - - verbalize_characters = pynini.cdrewrite(graph_symbols | graph_digit, "", "", NEMO_SIGMA) - - user_name = pynutil.delete("username: \"") + add_space_after_char() + pynutil.delete("\"") - user_name @= verbalize_characters - - convert_defaults = pynutil.add_weight(NEMO_NOT_QUOTE, weight=0.0001) | domain_common | server_common - domain = convert_defaults + pynini.closure(insert_space + convert_defaults) - domain @= verbalize_characters - - domain = pynutil.delete("domain: \"") + domain + pynutil.delete("\"") - protocol = ( - pynutil.delete("protocol: \"") - + add_space_after_char() @ pynini.cdrewrite(graph_symbols, "", "", NEMO_SIGMA) - + pynutil.delete("\"") - ) - self.graph = (pynini.closure(protocol + pynini.accep(" "), 0, 1) + domain) | ( - user_name + pynini.accep(" ") + pynutil.insert("at ") + domain - ) - delete_tokens = self.delete_tokens(self.graph + delete_preserve_order) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/fraction.py b/nemo_text_processing/text_normalization/de/verbalizers/fraction.py deleted file mode 100644 index 2221a2912887..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/fraction.py +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_preserve_order, - insert_space, -) -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for verbalizing fraction - e.g. fraction { integer: "drei" numerator: "eins" denominator: "zwei" }-> drei ein halb - e.g. fraction { numerator: "vier" denominator: "zwei" } -> vier halbe - e.g. fraction { numerator: "drei" denominator: "vier" } -> drei viertel - - Args: - ordinal: ordinal GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, ordinal: GraphFst, deterministic: bool = True): - super().__init__(name="fraction", kind="verbalize", deterministic=deterministic) - - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "minus ") + pynutil.delete(" "), 0, 1) - change_one = pynini.cdrewrite( - pynutil.add_weight(pynini.cross("eins", "ein"), weight=-0.0001), "[BOS]", "[EOS]", NEMO_SIGMA - ) - change_numerator_two = pynini.cdrewrite(pynini.cross("zweitel", "halbe"), "[BOS]", "[EOS]", NEMO_SIGMA) - integer = pynutil.delete("integer_part: \"") + change_one + pynutil.delete("\" ") - numerator = pynutil.delete("numerator: \"") + change_one + pynutil.delete("\" ") - denominator = ( - pynutil.delete("denominator: \"") - + pynini.closure(NEMO_NOT_QUOTE) - @ ( - pynini.cdrewrite(pynini.closure(ordinal.ordinal_stem, 0, 1), "", "[EOS]", NEMO_SIGMA) - + pynutil.insert("tel") - ) - @ change_numerator_two - + pynutil.delete("\"") - ) - - integer += insert_space + pynini.closure(pynutil.insert("und ", weight=0.001), 0, 1) - - denominator_one_half = pynini.cdrewrite(pynini.cross("ein halbe", "ein halb"), "[BOS]", "[EOS]", NEMO_SIGMA) - - fraction_default = (numerator + insert_space + denominator) @ denominator_one_half - - self.graph = optional_sign + pynini.closure(integer, 0, 1) + fraction_default - - graph = self.graph + delete_preserve_order - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/measure.py b/nemo_text_processing/text_normalization/de/verbalizers/measure.py deleted file mode 100644 index b9bcd190e272..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/measure.py +++ /dev/null @@ -1,53 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_extra_space, - delete_preserve_order, -) -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { cardinal { integer: "zwei" units: "unzen" } } -> "zwei unzen" - measure { cardinal { integer_part: "zwei" quantity: "millionen" units: "unzen" } } -> "zwei millionen unzen" - - Args: - decimal: decimal GraphFst - cardinal: cardinal GraphFst - fraction: fraction GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst, fraction: GraphFst, deterministic: bool): - super().__init__(name="measure", kind="verbalize", deterministic=deterministic) - unit = pynutil.delete("units: \"") + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\"") - - graph_decimal = decimal.fst - graph_cardinal = cardinal.fst - graph_fraction = fraction.fst - - graph = (graph_cardinal | graph_decimal | graph_fraction) + pynini.accep(" ") + unit - - graph |= unit + delete_extra_space + (graph_cardinal | graph_decimal) - graph += delete_preserve_order - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/money.py b/nemo_text_processing/text_normalization/de/verbalizers/money.py deleted file mode 100644 index 94fde2482e14..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/money.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_preserve_order -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { currency_maj: "euro" integer_part: "ein"} -> "ein euro" - money { currency_maj: "euro" integer_part: "eins" fractional_part: "null null eins"} -> "eins komma null null eins euro" - money { integer_part: "ein" currency_maj: "pfund" fractional_part: "vierzig" preserve_order: true} -> "ein pfund vierzig" - money { integer_part: "ein" currency_maj: "pfund" fractional_part: "vierzig" currency_min: "pence" preserve_order: true} -> "ein pfund vierzig pence" - money { fractional_part: "ein" currency_min: "penny" preserve_order: true} -> "ein penny" - money { currency_maj: "pfund" integer_part: "null" fractional_part: "null eins" quantity: "million"} -> "null komma null eins million pfund" - - Args: - decimal: GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="verbalize", deterministic=deterministic) - - keep_space = pynini.accep(" ") - - maj = pynutil.delete("currency_maj: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - min = pynutil.delete("currency_min: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - fractional_part = ( - pynutil.delete("fractional_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) - - integer_part = pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - optional_add_and = pynini.closure(pynutil.insert("und "), 0, 1) - - # *** currency_maj - graph_integer = integer_part + keep_space + maj - - # *** currency_maj + (***) | ((und) *** current_min) - graph_integer_with_minor = ( - integer_part - + keep_space - + maj - + keep_space - + (fractional_part | (optional_add_and + fractional_part + keep_space + min)) - + delete_preserve_order - ) - - # *** komma *** currency_maj - graph_decimal = decimal.fst + keep_space + maj - - # *** current_min - graph_minor = fractional_part + keep_space + min + delete_preserve_order - - graph = graph_integer | graph_integer_with_minor | graph_decimal | graph_minor - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/ordinal.py b/nemo_text_processing/text_normalization/de/verbalizers/ordinal.py deleted file mode 100644 index 917337c7026d..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/ordinal.py +++ /dev/null @@ -1,50 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, NEMO_SIGMA, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing roman numerals - e.g. ordinal { integer: "vier" } } -> "vierter" - -> "viertes" ... - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="ordinal", kind="verbalize", deterministic=deterministic) - graph_digit = pynini.string_file(get_abs_path("data/ordinals/digit.tsv")).invert() - graph_ties = pynini.string_file(get_abs_path("data/ordinals/ties.tsv")).invert() - graph_thousands = pynini.string_file(get_abs_path("data/ordinals/thousands.tsv")).invert() - - graph = pynutil.delete("integer: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - suffixes = pynini.union("ten", "tem", "ter", "tes", "te") - convert_rest = pynutil.insert(suffixes, weight=0.01) - self.ordinal_stem = graph_digit | graph_ties | graph_thousands - - suffix = pynini.cdrewrite( - pynini.closure(self.ordinal_stem, 0, 1) + convert_rest, "", "[EOS]", NEMO_SIGMA, - ).optimize() - self.graph = pynini.compose(graph, suffix) - self.suffix = suffix - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/telephone.py b/nemo_text_processing/text_normalization/de/verbalizers/telephone.py deleted file mode 100644 index 25fbeae8c605..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/telephone.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_preserve_order -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { country_code: "plus neun und vierzig" number_part: "null eins eins eins null null null" } - -> "plus neun und vierzig null eins eins eins null null null" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="telephone", kind="verbalize", deterministic=deterministic) - - country_code = pynutil.delete("country_code: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - number_part = pynutil.delete("number_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - self.graph = country_code + pynini.accep(" ") + number_part - - graph = self.graph + delete_preserve_order - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/time.py b/nemo_text_processing/text_normalization/de/verbalizers/time.py deleted file mode 100644 index f6ba49332bfa..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/time.py +++ /dev/null @@ -1,120 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.de.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - convert_space, - delete_preserve_order, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing electronic, e.g. - time { hours: "2" minutes: "15"} -> "zwei uhr fünfzehn" - time { minutes: "15" hours: "2" } -> "viertel nach zwei" - time { minutes: "15" hours: "2" } -> "fünfzehn nach zwei" - time { hours: "14" minutes: "15"} -> "vierzehn uhr fünfzehn" - time { minutes: "15" hours: "14" } -> "viertel nach zwei" - time { minutes: "15" hours: "14" } -> "fünfzehn nach drei" - time { minutes: "45" hours: "14" } -> "viertel vor drei" - - Args: - cardinal_tagger: cardinal_tagger tagger GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal_tagger: GraphFst, deterministic: bool = True): - super().__init__(name="time", kind="verbalize", deterministic=deterministic) - - # add weight so when using inverse text normalization this conversion is depriotized - night_to_early = pynutil.add_weight( - pynini.invert(pynini.string_file(get_abs_path("data/time/hour_to_night.tsv"))).optimize(), weight=0.0001 - ) - hour_to = pynini.invert(pynini.string_file(get_abs_path("data/time/hour_to.tsv"))).optimize() - minute_to = pynini.invert(pynini.string_file(get_abs_path("data/time/minute_to.tsv"))).optimize() - time_zone_graph = pynini.invert( - convert_space(pynini.union(*[x[1] for x in load_labels(get_abs_path("data/time/time_zone.tsv"))])) - ) - - graph_zero = pynini.invert(pynini.string_file(get_abs_path("data/numbers/zero.tsv"))).optimize() - number_verbalization = graph_zero | cardinal_tagger.two_digit_non_zero - hour = pynutil.delete("hours: \"") + pynini.closure(NEMO_DIGIT, 1) + pynutil.delete("\"") - hour_verbalized = hour @ number_verbalization @ pynini.cdrewrite( - pynini.cross("eins", "ein"), "[BOS]", "[EOS]", NEMO_SIGMA - ) + pynutil.insert(" uhr") - minute = pynutil.delete("minutes: \"") + pynini.closure(NEMO_DIGIT, 1) + pynutil.delete("\"") - zone = pynutil.delete("zone: \"") + time_zone_graph + pynutil.delete("\"") - optional_zone = pynini.closure(pynini.accep(" ") + zone, 0, 1) - second = pynutil.delete("seconds: \"") + pynini.closure(NEMO_DIGIT, 1) + pynutil.delete("\"") - graph_hms = ( - hour_verbalized - + pynini.accep(" ") - + minute @ number_verbalization - + pynutil.insert(" minuten") - + pynini.accep(" ") - + second @ number_verbalization - + pynutil.insert(" sekunden") - + optional_zone - ) - graph_hms @= pynini.cdrewrite( - pynini.cross("eins minuten", "eine minute") | pynini.cross("eins sekunden", "eine sekunde"), - pynini.union(" ", "[BOS]"), - "", - NEMO_SIGMA, - ) - - min_30 = [str(x) for x in range(1, 31)] - min_30 = pynini.union(*min_30) - min_29 = [str(x) for x in range(1, 30)] - min_29 = pynini.union(*min_29) - - graph_h = hour_verbalized - graph_hm = hour_verbalized + pynini.accep(" ") + minute @ number_verbalization - - graph_m_past_h = ( - minute @ min_30 @ (number_verbalization | pynini.cross("15", "viertel")) - + pynini.accep(" ") - + pynutil.insert("nach ") - # + hour @ number_verbalization - + hour @ pynini.cdrewrite(night_to_early, "[BOS]", "[EOS]", NEMO_SIGMA) @ number_verbalization - ) - graph_m30_h = ( - minute @ pynini.cross("30", "halb") - + pynini.accep(" ") - + hour @ pynini.cdrewrite(night_to_early, "[BOS]", "[EOS]", NEMO_SIGMA) @ hour_to @ number_verbalization - ) - graph_m_to_h = ( - minute @ minute_to @ min_29 @ (number_verbalization | pynini.cross("15", "viertel")) - + pynini.accep(" ") - + pynutil.insert("vor ") - + hour @ pynini.cdrewrite(night_to_early, "[BOS]", "[EOS]", NEMO_SIGMA) @ hour_to @ number_verbalization - ) - - self.graph = ( - graph_hms - | graph_h - | graph_hm - | pynutil.add_weight(graph_m_past_h, weight=0.0001) - | pynutil.add_weight(graph_m30_h, weight=0.0001) - | pynutil.add_weight(graph_m_to_h, weight=0.0001) - ) + optional_zone - delete_tokens = self.delete_tokens(self.graph + delete_preserve_order) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/de/verbalizers/verbalize.py b/nemo_text_processing/text_normalization/de/verbalizers/verbalize.py deleted file mode 100644 index e0aaed12522e..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/verbalize.py +++ /dev/null @@ -1,76 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.text_normalization.de.taggers.cardinal import CardinalFst as CardinalTagger -from nemo_text_processing.text_normalization.de.verbalizers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.de.verbalizers.date import DateFst -from nemo_text_processing.text_normalization.de.verbalizers.decimal import DecimalFst -from nemo_text_processing.text_normalization.de.verbalizers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.de.verbalizers.fraction import FractionFst -from nemo_text_processing.text_normalization.de.verbalizers.measure import MeasureFst -from nemo_text_processing.text_normalization.de.verbalizers.money import MoneyFst -from nemo_text_processing.text_normalization.de.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.de.verbalizers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.de.verbalizers.time import TimeFst -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.en.verbalizers.whitelist import WhiteListFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="verbalize", kind="verbalize", deterministic=deterministic) - cardinal_tagger = CardinalTagger(deterministic=deterministic) - cardinal = CardinalFst(deterministic=deterministic) - cardinal_graph = cardinal.fst - ordinal = OrdinalFst(deterministic=deterministic) - ordinal_graph = ordinal.fst - decimal = DecimalFst(deterministic=deterministic) - decimal_graph = decimal.fst - fraction = FractionFst(ordinal=ordinal, deterministic=deterministic) - fraction_graph = fraction.fst - date = DateFst(ordinal=ordinal) - date_graph = date.fst - measure = MeasureFst(cardinal=cardinal, decimal=decimal, fraction=fraction, deterministic=deterministic) - measure_graph = measure.fst - electronic = ElectronicFst(deterministic=deterministic) - electronic_graph = electronic.fst - whitelist_graph = WhiteListFst(deterministic=deterministic).fst - money_graph = MoneyFst(decimal=decimal).fst - telephone_graph = TelephoneFst(deterministic=deterministic).fst - time_graph = TimeFst(cardinal_tagger=cardinal_tagger, deterministic=deterministic).fst - - graph = ( - cardinal_graph - | measure_graph - | decimal_graph - | ordinal_graph - | date_graph - | electronic_graph - | money_graph - | fraction_graph - | whitelist_graph - | telephone_graph - | time_graph - ) - self.fst = graph diff --git a/nemo_text_processing/text_normalization/de/verbalizers/verbalize_final.py b/nemo_text_processing/text_normalization/de/verbalizers/verbalize_final.py deleted file mode 100644 index fe1ceaad9089..000000000000 --- a/nemo_text_processing/text_normalization/de/verbalizers/verbalize_final.py +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.de.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.verbalizers.word import WordFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, deterministic: bool = True, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="verbalize_final", kind="verbalize", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, f"de_tn_{deterministic}_deterministic_verbalizer.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["verbalize"] - logging.info(f'VerbalizeFinalFst graph was restored from {far_file}.') - else: - verbalize = VerbalizeFst(deterministic=deterministic).fst - word = WordFst(deterministic=deterministic).fst - - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - - self.fst = graph.optimize() - if far_file: - generator_main(far_file, {"verbalize": self.fst}) - logging.info(f"VerbalizeFinalFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/en/__init__.py b/nemo_text_processing/text_normalization/en/__init__.py deleted file mode 100644 index a9d7d97c9257..000000000000 --- a/nemo_text_processing/text_normalization/en/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.text_normalization.en.taggers.tokenize_and_classify import ClassifyFst -from nemo_text_processing.text_normalization.en.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst diff --git a/nemo_text_processing/text_normalization/en/clean_eval_data.py b/nemo_text_processing/text_normalization/en/clean_eval_data.py deleted file mode 100644 index 8c33c4fa62ca..000000000000 --- a/nemo_text_processing/text_normalization/en/clean_eval_data.py +++ /dev/null @@ -1,342 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from argparse import ArgumentParser -from typing import List - -import regex as re -from nemo_text_processing.text_normalization.data_loader_utils import ( - EOS_TYPE, - Instance, - load_files, - training_data_to_sentences, -) - - -""" -This file is for evaluation purposes. -filter_loaded_data() cleans data (list of instances) for text normalization. Filters and cleaners can be specified for each semiotic class individually. -For example, normalized text should only include characters and whitespace characters but no punctuation. - Cardinal unnormalized instances should contain at least one integer and all other characters are removed. -""" - - -class Filter: - """ - Filter class - - Args: - class_type: semiotic class used in dataset - process_func: function to transform text - filter_func: function to filter text - - """ - - def __init__(self, class_type: str, process_func: object, filter_func: object): - self.class_type = class_type - self.process_func = process_func - self.filter_func = filter_func - - def filter(self, instance: Instance) -> bool: - """ - filter function - - Args: - filters given instance with filter function - - Returns: True if given instance fulfills criteria or does not belong to class type - """ - if instance.token_type != self.class_type: - return True - return self.filter_func(instance) - - def process(self, instance: Instance) -> Instance: - """ - process function - - Args: - processes given instance with process function - - Returns: processed instance if instance belongs to expected class type or original instance - """ - if instance.token_type != self.class_type: - return instance - return self.process_func(instance) - - -def filter_cardinal_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_cardinal_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r"[^0-9]", "", un_normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_ordinal_1(instance: Instance) -> bool: - ok = re.search(r"(st|nd|rd|th)\s*$", instance.un_normalized) - return ok - - -def process_ordinal_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r"[,\s]", "", un_normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_decimal_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_decimal_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - un_normalized = re.sub(r",", "", un_normalized) - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_measure_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_measure_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r",", "", un_normalized) - un_normalized = re.sub(r"m2", "m²", un_normalized) - un_normalized = re.sub(r"(\d)([^\d.\s])", r"\1 \2", un_normalized) - normalized = re.sub(r"[^a-z\s]", "", normalized) - normalized = re.sub(r"per ([a-z\s]*)s$", r"per \1", normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_money_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_money_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - un_normalized = re.sub(r",", "", un_normalized) - un_normalized = re.sub(r"a\$", r"$", un_normalized) - un_normalized = re.sub(r"us\$", r"$", un_normalized) - un_normalized = re.sub(r"(\d)m\s*$", r"\1 million", un_normalized) - un_normalized = re.sub(r"(\d)bn?\s*$", r"\1 billion", un_normalized) - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_time_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_time_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - un_normalized = re.sub(r": ", ":", un_normalized) - un_normalized = re.sub(r"(\d)\s?a\s?m\s?", r"\1 a.m.", un_normalized) - un_normalized = re.sub(r"(\d)\s?p\s?m\s?", r"\1 p.m.", un_normalized) - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_plain_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_plain_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_punct_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_punct_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_date_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_date_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - un_normalized = re.sub(r",", "", un_normalized) - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_letters_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_letters_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_verbatim_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_verbatim_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_digit_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_digit_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_telephone_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_telephone_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_electronic_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_electronic_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_fraction_1(instance: Instance) -> bool: - ok = re.search(r"[0-9]", instance.un_normalized) - return ok - - -def process_fraction_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -def filter_address_1(instance: Instance) -> bool: - ok = True - return ok - - -def process_address_1(instance: Instance) -> Instance: - un_normalized = instance.un_normalized - normalized = instance.normalized - normalized = re.sub(r"[^a-z ]", "", normalized) - return Instance(token_type=instance.token_type, un_normalized=un_normalized, normalized=normalized) - - -filters = [] -filters.append(Filter(class_type="CARDINAL", process_func=process_cardinal_1, filter_func=filter_cardinal_1)) -filters.append(Filter(class_type="ORDINAL", process_func=process_ordinal_1, filter_func=filter_ordinal_1)) -filters.append(Filter(class_type="DECIMAL", process_func=process_decimal_1, filter_func=filter_decimal_1)) -filters.append(Filter(class_type="MEASURE", process_func=process_measure_1, filter_func=filter_measure_1)) -filters.append(Filter(class_type="MONEY", process_func=process_money_1, filter_func=filter_money_1)) -filters.append(Filter(class_type="TIME", process_func=process_time_1, filter_func=filter_time_1)) - -filters.append(Filter(class_type="DATE", process_func=process_date_1, filter_func=filter_date_1)) -filters.append(Filter(class_type="PLAIN", process_func=process_plain_1, filter_func=filter_plain_1)) -filters.append(Filter(class_type="PUNCT", process_func=process_punct_1, filter_func=filter_punct_1)) -filters.append(Filter(class_type="LETTERS", process_func=process_letters_1, filter_func=filter_letters_1)) -filters.append(Filter(class_type="VERBATIM", process_func=process_verbatim_1, filter_func=filter_verbatim_1)) -filters.append(Filter(class_type="DIGIT", process_func=process_digit_1, filter_func=filter_digit_1)) -filters.append(Filter(class_type="TELEPHONE", process_func=process_telephone_1, filter_func=filter_telephone_1)) -filters.append(Filter(class_type="ELECTRONIC", process_func=process_electronic_1, filter_func=filter_electronic_1)) -filters.append(Filter(class_type="FRACTION", process_func=process_fraction_1, filter_func=filter_fraction_1)) -filters.append(Filter(class_type="ADDRESS", process_func=process_address_1, filter_func=filter_address_1)) -filters.append(Filter(class_type=EOS_TYPE, process_func=lambda x: x, filter_func=lambda x: True)) - - -def filter_loaded_data(data: List[Instance], verbose: bool = False) -> List[Instance]: - """ - Filters list of instances - - Args: - data: list of instances - - Returns: filtered and transformed list of instances - """ - updates_instances = [] - for instance in data: - updated_instance = False - for fil in filters: - if fil.class_type == instance.token_type and fil.filter(instance): - instance = fil.process(instance) - updated_instance = True - if updated_instance: - if verbose: - print(instance) - updates_instances.append(instance) - return updates_instances - - -def parse_args(): - parser = ArgumentParser() - parser.add_argument("--input", help="input file path", type=str, default='./en_with_types/output-00001-of-00100') - parser.add_argument("--verbose", help="print filtered instances", action='store_true') - return parser.parse_args() - - -if __name__ == "__main__": - args = parse_args() - file_path = args.input - - print("Loading training data: " + file_path) - instance_list = load_files([file_path]) # List of instances - filtered_instance_list = filter_loaded_data(instance_list, args.verbose) - training_data_to_sentences(filtered_instance_list) diff --git a/nemo_text_processing/text_normalization/en/data/__init__.py b/nemo_text_processing/text_normalization/en/data/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/address/__init__.py b/nemo_text_processing/text_normalization/en/data/address/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/nemo_text_processing/text_normalization/en/data/address/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/address/address_word.tsv b/nemo_text_processing/text_normalization/en/data/address/address_word.tsv deleted file mode 100644 index 2e9e71615acd..000000000000 --- a/nemo_text_processing/text_normalization/en/data/address/address_word.tsv +++ /dev/null @@ -1,14 +0,0 @@ -st Street -street Street -expy Expressway -fwy Freeway -hwy Highway -dr Drive -ct Court -ave Avenue -av Avenue -cir Circle -blvd Boulevard -alley Alley -way Way -jct Junction \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/address/state.tsv b/nemo_text_processing/text_normalization/en/data/address/state.tsv deleted file mode 100644 index 921704f76129..000000000000 --- a/nemo_text_processing/text_normalization/en/data/address/state.tsv +++ /dev/null @@ -1,52 +0,0 @@ -Alabama AL -Alaska AK -Arizona AZ -Arkansas AR -California CA -Colorado CO -Connecticut CT -Delaware DE -Florida FL -Georgia GA -Hawaii HI -Idaho ID -Illinois IL -Indiana IN -Indiana IND -Iowa IA -Kansas KS -Kentucky KY -Louisiana LA -Maine ME -Maryland MD -Massachusetts MA -Michigan MI -Minnesota MN -Mississippi MS -Missouri MO -Montana MT -Nebraska NE -Nevada NV -New Hampshire NH -New Jersey NJ -New Mexico NM -New York NY -North Carolina NC -North Dakota ND -Ohio OH -Oklahoma OK -Oregon OR -Pennsylvania PA -Rhode Island RI -South Carolina SC -South Dakota SD -Tennessee TN -Tennessee TENN -Texas TX -Utah UT -Vermont VT -Virginia VA -Washington WA -West Virginia WV -Wisconsin WI -Wyoming WY \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/date/__init__.py b/nemo_text_processing/text_normalization/en/data/date/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/date/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/date/day.tsv b/nemo_text_processing/text_normalization/en/data/date/day.tsv deleted file mode 100644 index ef8dd7af2852..000000000000 --- a/nemo_text_processing/text_normalization/en/data/date/day.tsv +++ /dev/null @@ -1,31 +0,0 @@ -one -two -three -four -five -six -seven -eight -nine -ten -eleven -twelve -thirteen -fourteen -fifteen -sixteen -seventeen -eighteen -nineteen -twenty -twenty one -twenty two -twenty three -twenty four -twenty five -twenty six -twenty seven -twenty eight -twenty nine -thirty -thirty one \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/date/month_abbr.tsv b/nemo_text_processing/text_normalization/en/data/date/month_abbr.tsv deleted file mode 100644 index e70e41045b3b..000000000000 --- a/nemo_text_processing/text_normalization/en/data/date/month_abbr.tsv +++ /dev/null @@ -1,12 +0,0 @@ -jan january -feb february -mar march -apr april -jun june -jul july -aug august -sep september -sept september -oct october -nov november -dec december diff --git a/nemo_text_processing/text_normalization/en/data/date/month_name.tsv b/nemo_text_processing/text_normalization/en/data/date/month_name.tsv deleted file mode 100644 index 1c05ac02a39e..000000000000 --- a/nemo_text_processing/text_normalization/en/data/date/month_name.tsv +++ /dev/null @@ -1,12 +0,0 @@ -january -february -march -april -may -june -july -august -september -october -november -december diff --git a/nemo_text_processing/text_normalization/en/data/date/month_number.tsv b/nemo_text_processing/text_normalization/en/data/date/month_number.tsv deleted file mode 100644 index f0cacd5d1ed3..000000000000 --- a/nemo_text_processing/text_normalization/en/data/date/month_number.tsv +++ /dev/null @@ -1,24 +0,0 @@ -1 january -2 february -3 march -4 april -5 may -6 june -7 july -8 august -9 september -10 october -11 november -12 december -01 january -02 february -03 march -04 april -05 may -06 june -07 july -08 august -09 september -10 october -11 november -12 december \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/date/year_suffix.tsv b/nemo_text_processing/text_normalization/en/data/date/year_suffix.tsv deleted file mode 100644 index 8c799ddbcfba..000000000000 --- a/nemo_text_processing/text_normalization/en/data/date/year_suffix.tsv +++ /dev/null @@ -1,16 +0,0 @@ -A. D AD -A.D AD -a. d AD -a.d AD -a. d. AD -a.d. AD -B. C BC -B.C BC -b. c BC -b.c BC -A. D. AD -A.D. AD -B. C. BC -B.C. BC -b. c. BC -b.c. BC diff --git a/nemo_text_processing/text_normalization/en/data/electronic/__init__.py b/nemo_text_processing/text_normalization/en/data/electronic/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/en/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/electronic/domain.tsv b/nemo_text_processing/text_normalization/en/data/electronic/domain.tsv deleted file mode 100644 index 0e7042c5f77f..000000000000 --- a/nemo_text_processing/text_normalization/en/data/electronic/domain.tsv +++ /dev/null @@ -1,12 +0,0 @@ -.com dot com -.org dot org -.gov dot gov -.uk dot UK -.fr dot FR -.net dot net -.br dot BR -.in dot IN -.ru dot RU -.de dot DE -.it dot IT -.jpg dot jpeg \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/electronic/symbol.tsv b/nemo_text_processing/text_normalization/en/data/electronic/symbol.tsv deleted file mode 100644 index f633c77cb793..000000000000 --- a/nemo_text_processing/text_normalization/en/data/electronic/symbol.tsv +++ /dev/null @@ -1,21 +0,0 @@ -. dot -- dash -_ underscore -! exclamation mark -# number sign -$ dollar sign -% percent sign -& ampersand -' quote -* asterisk -+ plus -/ slash -= equal sign -? question mark -^ circumflex -` right single quote -{ left brace -| vertical bar -} right brace -~ tilde -, comma \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/measure/__init__.py b/nemo_text_processing/text_normalization/en/data/measure/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/measure/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/measure/math_operation.tsv b/nemo_text_processing/text_normalization/en/data/measure/math_operation.tsv deleted file mode 100644 index 21e72fd0c405..000000000000 --- a/nemo_text_processing/text_normalization/en/data/measure/math_operation.tsv +++ /dev/null @@ -1,8 +0,0 @@ -+ plus -- minus -/ divided -÷ divided -: divided -× times -* times -· times \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/measure/unit.tsv b/nemo_text_processing/text_normalization/en/data/measure/unit.tsv deleted file mode 100644 index c033ab842385..000000000000 --- a/nemo_text_processing/text_normalization/en/data/measure/unit.tsv +++ /dev/null @@ -1,127 +0,0 @@ -amu atomic mass unit -bar bar -° degree -º degree -°c degree Celsius -°C degree Celsius -ºc degree Celsius -ºC degree Celsius -℃ degree Celsius -cm2 square centimeter -cm² square centimeter -cm3 cubic centimeter -cm³ cubic centimeter -cm centimeter -cwt hundredweight -db decibel -dm3 cubic decimeter -dm³ cubic decimeter -dm decimeter -ds decisecond -°f degree Fahrenheit -°F degree Fahrenheit -℉ degree Fahrenheit -ft foot -ghz gigahertz -gw gigawatt -gwh gigawatt hour -hz hertz -" inch -kbps kilobit per second -kcal kilo calory -kgf kilogram force -kg kilogram -khz kilohertz -km2 square kilometer -km² square kilometer -km3 cubic kilometer -km³ cubic kilometer -km kilometer -kpa kilopascal -kwh kilowatt hour -kw kilowatt -kW kilowatt -lb pound -lbs pound -m2 square meter -m² square meter -m3 cubic meter -m³ cubic meter -mbps megabit per second -mg milligram -mhz megahertz -mi2 square mile -mi² square mile -mi3 cubic mile -mi³ cubic mile -cu mi cubic mile -mi mile -min minute -ml milliliter -mm2 square millimeter -mm² square millimeter -mol mole -mpa megapascal -mph mile per hour -ng nanogram -nm nanometer -ns nanosecond -oz ounce -pa pascal -% percent -rad radian -rpm revolution per minute -sq ft square foot -sq mi square mile -sv sievert -tb terabyte -tj terajoule -tl teraliter -v volt -yd yard -μg microgram -μm micrometer -μs microsecond -ω ohm -atm ATM -au AU -bq BQ -cc CC -cd CD -da DA -eb EB -ev EV -f F -gb GB -g G -gl GL -gpa GPA -gy GY -ha HA -h H -hl HL -hp GP -hs HS -kb KB -kl KL -kn KN -kt KT -kv KV -lm LM -ma MA -mA MA -mb MB -mc MC -mf MF -m M -mm MM -ms MS -mv MV -mw MW -pb PB -pg PG -ps PS -s S -tb TB -tb YB -zb ZB \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/measure/unit_alternatives.tsv b/nemo_text_processing/text_normalization/en/data/measure/unit_alternatives.tsv deleted file mode 100644 index 77e4057ae70b..000000000000 --- a/nemo_text_processing/text_normalization/en/data/measure/unit_alternatives.tsv +++ /dev/null @@ -1,43 +0,0 @@ -atm atmosphere -bq becquerel -cd candela -da dalton -eb exabyte -f degree Fahrenheit -gb gigabyte -g gram -gl gigaliter -ha hectare -h hour -hl hectoliter -hp horsepower -hp horsepower -kb kilobit -kb kilobyte -ma megaampere -mA megaampere -ma milliampere -mA milliampere -mb megabyte -mc megacoulomb -mf megafarad -m meter -m minute -mm millimeter -mm millimeter -mm millimeter -ms megasecond -ms mega siemens -ms millisecond -mv millivolt -mV millivolt -mw megawatt -mW megawatt -pb petabyte -pg petagram -ps petasecond -s second -tb terabyte -tb terabyte -yb yottabyte -zb zettabyte diff --git a/nemo_text_processing/text_normalization/en/data/money/__init__.py b/nemo_text_processing/text_normalization/en/data/money/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/money/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/money/currency_major.tsv b/nemo_text_processing/text_normalization/en/data/money/currency_major.tsv deleted file mode 100644 index 5201efd8a3a2..000000000000 --- a/nemo_text_processing/text_normalization/en/data/money/currency_major.tsv +++ /dev/null @@ -1,39 +0,0 @@ -$ dollar -$ us dollar -US$ us dollar -฿ Thai Baht -£ pound -€ euro -₩ won -nzd new zealand dollar -rs rupee -chf swiss franc -dkk danish kroner -fim finnish markka -aed arab emirates dirham -¥ yen -czk czech koruna -mro mauritanian ouguiya -pkr pakistani rupee -crc costa rican colon -hk$ hong kong dollar -npr nepalese rupee -awg aruban florin -nok norwegian kroner -tzs tanzanian shilling -sek swedish kronor -cyp cypriot pound -r real -sar saudi riyal -cve cape verde escudo -rsd serbian dinar -dm german mark -shp saint helena pounds -php philippine peso -cad canadian dollar -ssp south sudanese pound -scr seychelles rupee -mvr maldivian rufiyaa -DH dirham -Dh dirham -Dhs. dirham diff --git a/nemo_text_processing/text_normalization/en/data/money/currency_minor_plural.tsv b/nemo_text_processing/text_normalization/en/data/money/currency_minor_plural.tsv deleted file mode 100644 index a2f67b3a3d00..000000000000 --- a/nemo_text_processing/text_normalization/en/data/money/currency_minor_plural.tsv +++ /dev/null @@ -1,4 +0,0 @@ -$ cents -US$ cents -€ cents -£ pence \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/money/currency_minor_singular.tsv b/nemo_text_processing/text_normalization/en/data/money/currency_minor_singular.tsv deleted file mode 100644 index fe629d87b693..000000000000 --- a/nemo_text_processing/text_normalization/en/data/money/currency_minor_singular.tsv +++ /dev/null @@ -1,3 +0,0 @@ -$ cent -€ cent -£ penny \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/money/per_unit.tsv b/nemo_text_processing/text_normalization/en/data/money/per_unit.tsv deleted file mode 100644 index 654806689127..000000000000 --- a/nemo_text_processing/text_normalization/en/data/money/per_unit.tsv +++ /dev/null @@ -1,2 +0,0 @@ -/ea each -/dozen \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/number/__init__.py b/nemo_text_processing/text_normalization/en/data/number/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/number/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/number/cardinal_number_name.far b/nemo_text_processing/text_normalization/en/data/number/cardinal_number_name.far deleted file mode 100755 index 2ec682541ca72e575663537b1555059536f6876f..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 325078 zcmbTf1-M+*756|bWh%Aftd@3)`l&di$s^0oFp`<#2uy-$37#okl3TCH71Zn^Wg9sAm+ 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3/4 -⅐ 1/7 -⅑ 1/9 -⅒ 1/10 -⅓ 1/3 -⅔ 2/3 -⅕ 1/5 -⅖ 2/5 -⅗ 3/5 -⅘ 4/5 -⅙ 1/6 -⅚ 5/6 -⅛ 1/8 -⅜ 3/8 -⅝ 5/8 -⅞ 7/8 diff --git a/nemo_text_processing/text_normalization/en/data/number/hundred.tsv b/nemo_text_processing/text_normalization/en/data/number/hundred.tsv deleted file mode 100644 index 10e2b9645a53..000000000000 --- a/nemo_text_processing/text_normalization/en/data/number/hundred.tsv +++ /dev/null @@ -1 +0,0 @@ -hundred \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/number/quantity_abbr.tsv b/nemo_text_processing/text_normalization/en/data/number/quantity_abbr.tsv deleted file mode 100644 index 7dba4f03713c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/number/quantity_abbr.tsv +++ /dev/null @@ -1,10 +0,0 @@ -M million -MLN million -m million -mln million -B billion -b billion -BN billion -bn billion -K thousand -k thousand \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/number/teen.tsv b/nemo_text_processing/text_normalization/en/data/number/teen.tsv deleted file mode 100644 index 8e60fa1d3cb3..000000000000 --- a/nemo_text_processing/text_normalization/en/data/number/teen.tsv +++ /dev/null @@ -1,10 +0,0 @@ -ten 10 -eleven 11 -twelve 12 -thirteen 13 -fourteen 14 -fifteen 15 -sixteen 16 -seventeen 17 -eighteen 18 -nineteen 19 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/number/thousand.tsv b/nemo_text_processing/text_normalization/en/data/number/thousand.tsv deleted file mode 100644 index bf30542bb6bc..000000000000 --- a/nemo_text_processing/text_normalization/en/data/number/thousand.tsv +++ /dev/null @@ -1,22 +0,0 @@ -thousand -million -billion -trillion -quadrillion -quintillion -sextillion -septillion -octillion -nonillion -decillion -undecillion -duodecillion -tredecillion -quattuordecillion -quindecillion -sexdecillion -septendecillion -octodecillion -novemdecillion -vigintillion -centillion \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/number/ty.tsv b/nemo_text_processing/text_normalization/en/data/number/ty.tsv deleted file mode 100644 index 65f9839fda6d..000000000000 --- a/nemo_text_processing/text_normalization/en/data/number/ty.tsv +++ /dev/null @@ -1,8 +0,0 @@ -twenty 2 -thirty 3 -forty 4 -fifty 5 -sixty 6 -seventy 7 -eighty 8 -ninety 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/number/zero.tsv b/nemo_text_processing/text_normalization/en/data/number/zero.tsv deleted file mode 100644 index a1b116c10f09..000000000000 --- a/nemo_text_processing/text_normalization/en/data/number/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -zero 0 diff --git a/nemo_text_processing/text_normalization/en/data/ordinal/__init__.py b/nemo_text_processing/text_normalization/en/data/ordinal/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/ordinal/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/ordinal/digit.tsv b/nemo_text_processing/text_normalization/en/data/ordinal/digit.tsv deleted file mode 100644 index 4b7fc24f1606..000000000000 --- a/nemo_text_processing/text_normalization/en/data/ordinal/digit.tsv +++ /dev/null @@ -1,9 +0,0 @@ -first one -second two -third three -fourth four -fifth five -sixth sixth -seventh seven -eighth eight -ninth nine \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/ordinal/teen.tsv b/nemo_text_processing/text_normalization/en/data/ordinal/teen.tsv deleted file mode 100644 index 496fefc086d1..000000000000 --- a/nemo_text_processing/text_normalization/en/data/ordinal/teen.tsv +++ /dev/null @@ -1 +0,0 @@ -twelfth twelve \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/roman/README.md b/nemo_text_processing/text_normalization/en/data/roman/README.md deleted file mode 100644 index 398e1974f823..000000000000 --- a/nemo_text_processing/text_normalization/en/data/roman/README.md +++ /dev/null @@ -1,20 +0,0 @@ -`female.tsv` - List of common female names. Copyright (c) January 1991 by Mark Kantrowitz, 4987 names, Version 1.3 (29-MAR-94) -Source: [https://www.cs.cmu.edu/Groups/AI/areas/nlp/corpora/names/female.txt](https://www.cs.cmu.edu/Groups/AI/areas/nlp/corpora/names/female.txt) - -`male.tsv` - List of common male names. Copyright (c) January 1991 by Mark Kantrowitz, 2940 names, Version 1.3 (29-MAR-94) -Source: [https://www.cs.cmu.edu/Groups/AI/areas/nlp/corpora/names/male.txt](https://www.cs.cmu.edu/Groups/AI/areas/nlp/corpora/names/male.txt) - -[Corpora Readme.txt](https://www.cs.cmu.edu/Groups/AI/areas/nlp/corpora/names/readme.txt): - -You may use the lists of names for any purpose, so long as credit is given -in any published work. You may also redistribute the list if you -provide the recipients with a copy of this README file. The lists are -not in the public domain (I retain the copyright on the lists) but are -freely redistributable. - -If you have any additions to the lists of names, I would appreciate -receiving them. - -My email address is mkant+@cs.cmu.edu. - -Mark Kantrowitz \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/roman/__init__.py b/nemo_text_processing/text_normalization/en/data/roman/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/roman/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/roman/female.tsv b/nemo_text_processing/text_normalization/en/data/roman/female.tsv deleted file mode 100644 index 4e248ce2ab7c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/roman/female.tsv +++ /dev/null @@ -1,4998 +0,0 @@ -Abagael -Abagail -Abbe -Abbey -Abbi -Abbie -Abby -Abigael -Abigail -Abigale -Abra -Acacia -Ada -Adah -Adaline -Adara -Addie -Addis -Adel -Adela -Adelaide -Adele -Adelice -Adelina -Adelind -Adeline -Adella -Adelle -Adena -Adey -Adi -Adiana -Adina -Adora -Adore -Adoree -Adorne -Adrea -Adria -Adriaens -Adrian -Adriana -Adriane -Adrianna -Adrianne -Adrien -Adriena -Adrienne -Aeriel -Aeriela -Aeriell -Ag -Agace -Agata -Agatha -Agathe -Aggi -Aggie -Aggy -Agna -Agnella -Agnes -Agnese -Agnesse -Agneta -Agnola -Agretha -Aida -Aidan -Aigneis -Aila -Aile -Ailee -Aileen -Ailene -Ailey -Aili -Ailina -Ailyn -Aime -Aimee -Aimil -Aina -Aindrea -Ainslee -Ainsley -Ainslie -Ajay -Alaine -Alameda -Alana -Alanah -Alane -Alanna -Alayne -Alberta -Albertina -Albertine -Albina -Alecia -Aleda -Aleece -Aleecia -Aleen -Alejandra -Alejandrina -Alena -Alene -Alessandra -Aleta -Alethea -Alex -Alexa -Alexandra -Alexandrina -Alexi -Alexia -Alexina -Alexine -Alexis -Alfie -Alfreda -Ali -Alia -Alica -Alice -Alicea -Alicia -Alida -Alidia -Alina -Aline -Alis -Alisa -Alisha -Alison -Alissa -Alisun -Alix -Aliza -Alla -Alleen -Allegra 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thousand, one hundred seventy one -MCLXXII one thousand, one hundred seventy two -MCLXXIII one thousand, one hundred seventy three -MCLXXIV one thousand, one hundred seventy four -MCLXXV one thousand, one hundred seventy five -MCLXXVI one thousand, one hundred seventy six -MCLXXVII one thousand, one hundred seventy seven -MCLXXVIII one thousand, one hundred seventy eight -MCLXXIX one thousand, one hundred seventy nine -MCLXXX one thousand, one hundred eighty -MCLXXXI one thousand, one hundred eighty one -MCLXXXII one thousand, one hundred eighty two -MCLXXXIII one thousand, one hundred eighty three -MCLXXXIV one thousand, one hundred eighty four -MCLXXXV one thousand, one hundred eighty five -MCLXXXVI one thousand, one hundred eighty six -MCLXXXVII one thousand, one hundred eighty seven -MCLXXXVIII one thousand, one hundred eighty eight -MCLXXXIX one thousand, one hundred eighty nine -MCXC one thousand, one hundred ninety -MCXCI one thousand, one hundred ninety one -MCXCII one thousand, one hundred ninety two -MCXCIII one thousand, one hundred ninety three -MCXCIV one thousand, one hundred ninety four -MCXCV one thousand, one hundred ninety five -MCXCVI one thousand, one hundred ninety six -MCXCVII one thousand, one hundred ninety seven -MCXCVIII one thousand, one hundred ninety eight -MCXCIX one thousand, one hundred ninety nine -MCC one thousand, two hundred -MCCI one thousand, two hundred one -MCCII one thousand, two hundred two -MCCIII one thousand, two hundred three -MCCIV one thousand, two hundred four -MCCV one thousand, two hundred five -MCCVI one thousand, two hundred six -MCCVII one thousand, two hundred seven -MCCVIII one thousand, two hundred eight -MCCIX one thousand, two hundred nine -MCCX one thousand, two hundred ten -MCCXI one thousand, two hundred eleven -MCCXII one thousand, two hundred twelve -MCCXIII one thousand, two hundred thirteen -MCCXIV one thousand, two hundred fourteen -MCCXV one thousand, two hundred fifteen -MCCXVI one thousand, two hundred sixteen -MCCXVII one thousand, two hundred seventeen -MCCXVIII one thousand, two hundred eighteen -MCCXIX one thousand, two hundred nineteen -MCCXX one thousand, two hundred twenty -MCCXXI one thousand, two hundred twenty one -MCCXXII one thousand, two hundred twenty two -MCCXXIII one thousand, two hundred twenty three -MCCXXIV one thousand, two hundred twenty four -MCCXXV one thousand, two hundred twenty five -MCCXXVI one thousand, two hundred twenty six -MCCXXVII one thousand, two hundred twenty seven -MCCXXVIII one thousand, two hundred twenty eight -MCCXXIX one thousand, two hundred twenty nine -MCCXXX one thousand, two hundred thirty -MCCXXXI one thousand, two hundred thirty one -MCCXXXII one thousand, two hundred thirty two -MCCXXXIII one thousand, two hundred thirty three -MCCXXXIV one thousand, two hundred thirty four -MCCXXXV one thousand, two hundred thirty five -MCCXXXVI one thousand, two hundred thirty six -MCCXXXVII one thousand, two hundred thirty seven -MCCXXXVIII one thousand, two hundred thirty eight -MCCXXXIX one thousand, two hundred thirty nine -MCCXL one thousand, two hundred forty -MCCXLI one thousand, two hundred forty one -MCCXLII one thousand, two hundred forty two -MCCXLIII one thousand, two hundred forty three -MCCXLIV one thousand, two hundred forty four -MCCXLV one thousand, two hundred forty five -MCCXLVI one thousand, two hundred forty six -MCCXLVII one thousand, two hundred forty seven -MCCXLVIII one thousand, two hundred forty eight -MCCXLIX one thousand, two hundred forty nine -MCCL one thousand, two hundred fifty -MCCLI one thousand, two hundred fifty one -MCCLII one thousand, two hundred fifty two -MCCLIII one thousand, two hundred fifty three -MCCLIV one thousand, two hundred fifty four -MCCLV one thousand, two hundred fifty five -MCCLVI one thousand, two hundred fifty six -MCCLVII one thousand, two hundred fifty seven -MCCLVIII one thousand, two hundred fifty eight -MCCLIX one thousand, two hundred fifty nine -MCCLX one thousand, two hundred sixty -MCCLXI one thousand, two hundred sixty one -MCCLXII one thousand, two hundred sixty two -MCCLXIII one thousand, two hundred sixty three -MCCLXIV one thousand, two hundred sixty four -MCCLXV one thousand, two hundred sixty five -MCCLXVI one thousand, two hundred sixty six -MCCLXVII one thousand, two hundred sixty seven -MCCLXVIII one thousand, two hundred sixty eight -MCCLXIX one thousand, two hundred sixty nine -MCCLXX one thousand, two hundred seventy -MCCLXXI one thousand, two hundred seventy one -MCCLXXII one thousand, two hundred seventy two -MCCLXXIII one thousand, two hundred seventy three -MCCLXXIV one thousand, two hundred seventy four -MCCLXXV one thousand, two hundred seventy five -MCCLXXVI one thousand, two hundred seventy six -MCCLXXVII one thousand, two hundred seventy seven -MCCLXXVIII one thousand, two hundred seventy eight -MCCLXXIX one thousand, two hundred seventy nine -MCCLXXX one thousand, two hundred eighty -MCCLXXXI one thousand, two hundred eighty one -MCCLXXXII one thousand, two hundred eighty two -MCCLXXXIII one thousand, two hundred eighty three -MCCLXXXIV one thousand, two hundred eighty four -MCCLXXXV one thousand, two hundred eighty five -MCCLXXXVI one thousand, two hundred eighty six -MCCLXXXVII one thousand, two hundred eighty seven -MCCLXXXVIII one thousand, two hundred eighty eight -MCCLXXXIX one thousand, two hundred eighty nine -MCCXC one thousand, two hundred ninety -MCCXCI one thousand, two hundred ninety one -MCCXCII one thousand, two hundred ninety two -MCCXCIII one thousand, two hundred ninety three -MCCXCIV one thousand, two hundred ninety four -MCCXCV one thousand, two hundred ninety five -MCCXCVI one thousand, two hundred ninety six -MCCXCVII one thousand, two hundred ninety seven -MCCXCVIII one thousand, two hundred ninety eight -MCCXCIX one thousand, two hundred ninety nine -MCCC one thousand, three hundred -MCCCI one thousand, three hundred one -MCCCII one thousand, three hundred two -MCCCIII one thousand, three hundred three -MCCCIV one thousand, three hundred four -MCCCV one thousand, three hundred five -MCCCVI one thousand, three hundred six -MCCCVII one thousand, three hundred seven -MCCCVIII one thousand, three hundred eight -MCCCIX one thousand, three hundred nine -MCCCX one thousand, three hundred ten -MCCCXI one thousand, three hundred eleven -MCCCXII one thousand, three hundred twelve -MCCCXIII one thousand, three hundred thirteen -MCCCXIV one thousand, three hundred fourteen -MCCCXV one thousand, three hundred fifteen -MCCCXVI one thousand, three hundred sixteen -MCCCXVII one thousand, three hundred seventeen -MCCCXVIII one thousand, three hundred eighteen -MCCCXIX one thousand, three hundred nineteen -MCCCXX one thousand, three hundred twenty -MCCCXXI one thousand, three hundred twenty one -MCCCXXII one thousand, three hundred twenty two -MCCCXXIII one thousand, three hundred twenty three -MCCCXXIV one thousand, three hundred twenty four -MCCCXXV one thousand, three hundred twenty five -MCCCXXVI one thousand, three hundred twenty six -MCCCXXVII one thousand, three hundred twenty seven -MCCCXXVIII one thousand, three hundred twenty eight -MCCCXXIX one thousand, three hundred twenty nine -MCCCXXX one thousand, three hundred thirty -MCCCXXXI one thousand, three hundred thirty one -MCCCXXXII one thousand, three hundred thirty two -MCCCXXXIII one thousand, three hundred thirty three -MCCCXXXIV one thousand, three hundred thirty four -MCCCXXXV one thousand, three hundred thirty five -MCCCXXXVI one thousand, three hundred thirty six -MCCCXXXVII one thousand, three hundred thirty seven -MCCCXXXVIII one thousand, three hundred thirty eight -MCCCXXXIX one thousand, three hundred thirty nine -MCCCXL one thousand, three hundred forty -MCCCXLI one thousand, three hundred forty one -MCCCXLII one thousand, three hundred forty two -MCCCXLIII one thousand, three hundred forty three -MCCCXLIV one thousand, three hundred forty four -MCCCXLV one thousand, three hundred forty five -MCCCXLVI one thousand, three hundred forty six -MCCCXLVII one thousand, three hundred forty seven -MCCCXLVIII one thousand, three hundred forty eight -MCCCXLIX one thousand, three hundred forty nine -MCCCL one thousand, three hundred fifty -MCCCLI one thousand, three hundred fifty one -MCCCLII one thousand, three hundred fifty two -MCCCLIII one thousand, three hundred fifty three -MCCCLIV one thousand, three hundred fifty four -MCCCLV one thousand, three hundred fifty five -MCCCLVI one thousand, three hundred fifty six -MCCCLVII one thousand, three hundred fifty seven -MCCCLVIII one thousand, three hundred fifty eight -MCCCLIX one thousand, three hundred fifty nine -MCCCLX one thousand, three hundred sixty -MCCCLXI one thousand, three hundred sixty one -MCCCLXII one thousand, three hundred sixty two -MCCCLXIII one thousand, three hundred sixty three -MCCCLXIV one thousand, three hundred sixty four -MCCCLXV one thousand, three hundred sixty five -MCCCLXVI one thousand, three hundred sixty six -MCCCLXVII one thousand, three hundred sixty seven -MCCCLXVIII one thousand, three hundred sixty eight -MCCCLXIX one thousand, three hundred sixty nine -MCCCLXX one thousand, three hundred seventy -MCCCLXXI one thousand, three hundred seventy one -MCCCLXXII one thousand, three hundred seventy two -MCCCLXXIII one thousand, three hundred seventy three -MCCCLXXIV one thousand, three hundred seventy four -MCCCLXXV one thousand, three hundred seventy five -MCCCLXXVI one thousand, three hundred seventy six -MCCCLXXVII one thousand, three hundred seventy seven -MCCCLXXVIII one thousand, three hundred seventy eight -MCCCLXXIX one thousand, three hundred seventy nine -MCCCLXXX one thousand, three hundred eighty -MCCCLXXXI one thousand, three hundred eighty one -MCCCLXXXII one thousand, three hundred eighty two -MCCCLXXXIII one thousand, three hundred eighty three -MCCCLXXXIV one thousand, three hundred eighty four -MCCCLXXXV one thousand, three hundred eighty five -MCCCLXXXVI one thousand, three hundred eighty six -MCCCLXXXVII one thousand, three hundred eighty seven -MCCCLXXXVIII one thousand, three hundred eighty eight -MCCCLXXXIX one thousand, three hundred eighty nine -MCCCXC one thousand, three hundred ninety -MCCCXCI one thousand, three hundred ninety one -MCCCXCII one thousand, three hundred ninety two -MCCCXCIII one thousand, three hundred ninety three -MCCCXCIV one thousand, three hundred ninety four -MCCCXCV one thousand, three hundred ninety five -MCCCXCVI one thousand, three hundred ninety six -MCCCXCVII one thousand, three hundred ninety seven -MCCCXCVIII one thousand, three hundred ninety eight -MCCCXCIX one thousand, three hundred ninety nine -MCD one thousand, four hundred -MCDI one thousand, four hundred one -MCDII one thousand, four hundred two -MCDIII one thousand, four hundred three -MCDIV one thousand, four hundred four -MCDV one thousand, four hundred five -MCDVI one thousand, four hundred six -MCDVII one thousand, four hundred seven -MCDVIII one thousand, four hundred eight -MCDIX one thousand, four hundred nine -MCDX one thousand, four hundred ten -MCDXI one thousand, four hundred eleven -MCDXII one thousand, four hundred twelve -MCDXIII one thousand, four hundred thirteen -MCDXIV one thousand, four hundred fourteen -MCDXV one thousand, four hundred fifteen -MCDXVI one thousand, four hundred sixteen -MCDXVII one thousand, four hundred seventeen -MCDXVIII one thousand, four hundred eighteen -MCDXIX one thousand, four hundred nineteen -MCDXX one thousand, four hundred twenty -MCDXXI one thousand, four hundred twenty one -MCDXXII one thousand, four hundred twenty two -MCDXXIII one thousand, four hundred twenty three -MCDXXIV one thousand, four hundred twenty four -MCDXXV one thousand, four hundred twenty five -MCDXXVI one thousand, four hundred twenty six -MCDXXVII one thousand, four hundred twenty seven -MCDXXVIII one thousand, four hundred twenty eight -MCDXXIX one thousand, four hundred twenty nine -MCDXXX one thousand, four hundred thirty -MCDXXXI one thousand, four hundred thirty one -MCDXXXII one thousand, four hundred thirty two -MCDXXXIII one thousand, four hundred thirty three -MCDXXXIV one thousand, four hundred thirty four -MCDXXXV one thousand, four hundred thirty five -MCDXXXVI one thousand, four hundred thirty six -MCDXXXVII one thousand, four hundred thirty seven -MCDXXXVIII one thousand, four hundred thirty eight -MCDXXXIX one thousand, four hundred thirty nine -MCDXL one thousand, four hundred forty -MCDXLI one thousand, four hundred forty one -MCDXLII one thousand, four hundred forty two -MCDXLIII one thousand, four hundred forty three -MCDXLIV one thousand, four hundred forty four -MCDXLV one thousand, four hundred forty five -MCDXLVI one thousand, four hundred forty six -MCDXLVII one thousand, four hundred forty seven -MCDXLVIII one thousand, four hundred forty eight -MCDXLIX one thousand, four hundred forty nine -MCDL one 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-MCDLXXII one thousand, four hundred seventy two -MCDLXXIII one thousand, four hundred seventy three -MCDLXXIV one thousand, four hundred seventy four -MCDLXXV one thousand, four hundred seventy five -MCDLXXVI one thousand, four hundred seventy six -MCDLXXVII one thousand, four hundred seventy seven -MCDLXXVIII one thousand, four hundred seventy eight -MCDLXXIX one thousand, four hundred seventy nine -MCDLXXX one thousand, four hundred eighty -MCDLXXXI one thousand, four hundred eighty one -MCDLXXXII one thousand, four hundred eighty two -MCDLXXXIII one thousand, four hundred eighty three -MCDLXXXIV one thousand, four hundred eighty four -MCDLXXXV one thousand, four hundred eighty five -MCDLXXXVI one thousand, four hundred eighty six -MCDLXXXVII one thousand, four hundred eighty seven -MCDLXXXVIII one thousand, four hundred eighty eight -MCDLXXXIX one thousand, four hundred eighty nine -MCDXC one thousand, four hundred ninety -MCDXCI one thousand, four hundred ninety one -MCDXCII one thousand, four hundred ninety two -MCDXCIII one thousand, four hundred ninety three -MCDXCIV one thousand, four hundred ninety four -MCDXCV one thousand, four hundred ninety five -MCDXCVI one thousand, four hundred ninety six -MCDXCVII one thousand, four hundred ninety seven -MCDXCVIII one thousand, four hundred ninety eight -MCDXCIX one thousand, four hundred ninety nine -MD one thousand, five hundred -MDI one thousand, five hundred one -MDII one thousand, five hundred two -MDIII one thousand, five hundred three -MDIV one thousand, five hundred four -MDV one thousand, five hundred five -MDVI one thousand, five hundred six -MDVII one thousand, five hundred seven -MDVIII one thousand, five hundred eight -MDIX one thousand, five hundred nine -MDX one thousand, five hundred ten -MDXI one thousand, five hundred eleven -MDXII one thousand, five hundred twelve -MDXIII one thousand, five hundred thirteen -MDXIV one thousand, five hundred fourteen -MDXV one thousand, five hundred fifteen -MDXVI one thousand, five hundred sixteen -MDXVII one thousand, five hundred seventeen -MDXVIII one thousand, five hundred eighteen -MDXIX one thousand, five hundred nineteen -MDXX one thousand, five hundred twenty -MDXXI one thousand, five hundred twenty one -MDXXII one thousand, five hundred twenty two -MDXXIII one thousand, five hundred twenty three -MDXXIV one thousand, five hundred twenty four -MDXXV one thousand, five hundred twenty five -MDXXVI one thousand, five hundred twenty six -MDXXVII one thousand, five hundred twenty seven -MDXXVIII one thousand, five hundred twenty eight -MDXXIX one thousand, five hundred twenty nine -MDXXX one thousand, five hundred thirty -MDXXXI one thousand, five hundred thirty one -MDXXXII one thousand, five hundred thirty two -MDXXXIII one thousand, five hundred thirty three -MDXXXIV one thousand, five hundred thirty four -MDXXXV one thousand, five hundred thirty five -MDXXXVI one thousand, five hundred thirty six -MDXXXVII one thousand, five 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hundred fifty nine -MDLX one thousand, five hundred sixty -MDLXI one thousand, five hundred sixty one -MDLXII one thousand, five hundred sixty two -MDLXIII one thousand, five hundred sixty three -MDLXIV one thousand, five hundred sixty four -MDLXV one thousand, five hundred sixty five -MDLXVI one thousand, five hundred sixty six -MDLXVII one thousand, five hundred sixty seven -MDLXVIII one thousand, five hundred sixty eight -MDLXIX one thousand, five hundred sixty nine -MDLXX one thousand, five hundred seventy -MDLXXI one thousand, five hundred seventy one -MDLXXII one thousand, five hundred seventy two -MDLXXIII one thousand, five hundred seventy three -MDLXXIV one thousand, five hundred seventy four -MDLXXV one thousand, five hundred seventy five -MDLXXVI one thousand, five hundred seventy six -MDLXXVII one thousand, five hundred seventy seven -MDLXXVIII one thousand, five hundred seventy eight -MDLXXIX one thousand, five hundred seventy nine -MDLXXX one thousand, five hundred eighty -MDLXXXI one thousand, five hundred eighty one -MDLXXXII one thousand, five hundred eighty two -MDLXXXIII one thousand, five hundred eighty three -MDLXXXIV one thousand, five hundred eighty four -MDLXXXV one thousand, five hundred eighty five -MDLXXXVI one thousand, five hundred eighty six -MDLXXXVII one thousand, five hundred eighty seven -MDLXXXVIII one thousand, five hundred eighty eight -MDLXXXIX one thousand, five hundred eighty nine -MDXC one thousand, five hundred ninety -MDXCI one thousand, five hundred ninety one -MDXCII one thousand, five hundred ninety two -MDXCIII one thousand, five hundred ninety three -MDXCIV one thousand, five hundred ninety four -MDXCV one thousand, five hundred ninety five -MDXCVI one thousand, five hundred ninety six -MDXCVII one thousand, five hundred ninety seven -MDXCVIII one thousand, five hundred ninety eight -MDXCIX one thousand, five hundred ninety nine -MDC one thousand, six hundred -MDCI one thousand, six hundred one -MDCII one thousand, six hundred two -MDCIII one thousand, six hundred three -MDCIV one thousand, six hundred four -MDCV one thousand, six hundred five -MDCVI one thousand, six hundred six -MDCVII one thousand, six hundred seven -MDCVIII one thousand, six hundred eight -MDCIX one thousand, six hundred nine -MDCX one thousand, six hundred ten -MDCXI one thousand, six hundred eleven -MDCXII one thousand, six hundred twelve -MDCXIII one thousand, six hundred thirteen -MDCXIV one thousand, six hundred fourteen -MDCXV one thousand, six hundred fifteen -MDCXVI one thousand, six hundred sixteen -MDCXVII one thousand, six hundred seventeen -MDCXVIII one thousand, six hundred eighteen -MDCXIX one thousand, six hundred nineteen -MDCXX one thousand, six hundred twenty -MDCXXI one thousand, six hundred twenty one -MDCXXII one thousand, six hundred twenty two -MDCXXIII one thousand, six hundred twenty three -MDCXXIV one thousand, six hundred twenty four -MDCXXV one thousand, six hundred twenty five -MDCXXVI one thousand, six hundred twenty six -MDCXXVII one thousand, six hundred twenty seven -MDCXXVIII one thousand, six hundred twenty eight -MDCXXIX one thousand, six hundred twenty nine -MDCXXX one thousand, six hundred thirty -MDCXXXI one thousand, six hundred thirty one -MDCXXXII one thousand, six hundred thirty two -MDCXXXIII one thousand, six hundred thirty three -MDCXXXIV one thousand, six hundred thirty four -MDCXXXV one thousand, six hundred thirty five -MDCXXXVI one thousand, six hundred thirty six -MDCXXXVII one thousand, six hundred thirty seven -MDCXXXVIII one thousand, six hundred thirty eight -MDCXXXIX one thousand, six hundred thirty nine -MDCXL one thousand, six hundred forty -MDCXLI one thousand, six hundred forty one -MDCXLII one thousand, six hundred forty two -MDCXLIII one thousand, six hundred forty three -MDCXLIV one thousand, six hundred forty four -MDCXLV one thousand, six hundred forty five -MDCXLVI one thousand, six hundred forty six -MDCXLVII one thousand, six hundred forty seven -MDCXLVIII one thousand, six hundred forty eight -MDCXLIX one thousand, six hundred forty nine -MDCL one thousand, six hundred fifty -MDCLI one thousand, six hundred fifty one -MDCLII one thousand, six hundred fifty two -MDCLIII one thousand, six hundred fifty three -MDCLIV one thousand, six hundred fifty four -MDCLV one thousand, six hundred fifty five -MDCLVI one thousand, six hundred fifty six -MDCLVII one thousand, six hundred fifty seven -MDCLVIII one thousand, six hundred fifty eight -MDCLIX one thousand, six hundred fifty nine -MDCLX one thousand, six hundred sixty -MDCLXI one thousand, six hundred sixty one -MDCLXII one thousand, six hundred sixty two -MDCLXIII one thousand, six hundred sixty three -MDCLXIV one thousand, six hundred sixty four -MDCLXV one thousand, six hundred sixty five -MDCLXVI one thousand, six hundred sixty six -MDCLXVII one thousand, six hundred sixty seven -MDCLXVIII one thousand, six hundred sixty eight -MDCLXIX one thousand, six hundred sixty nine -MDCLXX one thousand, six hundred seventy -MDCLXXI one thousand, six hundred seventy one -MDCLXXII one thousand, six hundred seventy two -MDCLXXIII one thousand, six hundred seventy three -MDCLXXIV one thousand, six hundred seventy four -MDCLXXV one thousand, six hundred seventy five -MDCLXXVI one thousand, six hundred seventy six -MDCLXXVII one thousand, six hundred seventy seven -MDCLXXVIII one thousand, six hundred seventy eight -MDCLXXIX one thousand, six hundred seventy nine -MDCLXXX one thousand, six hundred eighty -MDCLXXXI one thousand, six hundred eighty one -MDCLXXXII one thousand, six hundred eighty two -MDCLXXXIII one thousand, six hundred eighty three -MDCLXXXIV one thousand, six hundred eighty four -MDCLXXXV one thousand, six hundred eighty five -MDCLXXXVI one thousand, six hundred eighty six -MDCLXXXVII one thousand, six hundred eighty seven -MDCLXXXVIII one thousand, six hundred eighty eight -MDCLXXXIX one thousand, six hundred eighty nine -MDCXC one thousand, six hundred ninety -MDCXCI one thousand, six hundred ninety one -MDCXCII one thousand, six hundred ninety two -MDCXCIII one thousand, six hundred ninety three -MDCXCIV one thousand, six hundred ninety four -MDCXCV one thousand, six hundred ninety five -MDCXCVI one thousand, six hundred ninety six -MDCXCVII one thousand, six hundred ninety seven -MDCXCVIII one thousand, six hundred ninety eight -MDCXCIX one thousand, six hundred ninety nine -MDCC one thousand, seven hundred -MDCCI one thousand, seven hundred one -MDCCII one thousand, seven hundred two -MDCCIII one thousand, seven hundred three -MDCCIV one thousand, seven hundred four -MDCCV one thousand, seven hundred five -MDCCVI one thousand, seven hundred six -MDCCVII one thousand, seven hundred seven -MDCCVIII one thousand, seven hundred eight -MDCCIX one thousand, seven hundred nine -MDCCX one thousand, seven hundred ten -MDCCXI one thousand, seven hundred eleven -MDCCXII one thousand, seven hundred twelve -MDCCXIII one thousand, seven hundred thirteen -MDCCXIV one thousand, seven hundred fourteen -MDCCXV one thousand, seven hundred fifteen -MDCCXVI one thousand, seven hundred sixteen -MDCCXVII one thousand, seven hundred seventeen -MDCCXVIII one thousand, seven hundred eighteen -MDCCXIX one thousand, seven hundred nineteen -MDCCXX one thousand, seven hundred twenty -MDCCXXI one thousand, seven hundred twenty one -MDCCXXII one thousand, seven hundred twenty two -MDCCXXIII one thousand, seven hundred twenty three -MDCCXXIV one thousand, seven hundred twenty four -MDCCXXV one thousand, seven hundred twenty five -MDCCXXVI one thousand, seven hundred twenty six -MDCCXXVII one thousand, seven hundred twenty seven -MDCCXXVIII one thousand, seven hundred twenty eight -MDCCXXIX one thousand, seven hundred twenty nine -MDCCXXX one thousand, seven hundred thirty -MDCCXXXI one thousand, seven hundred thirty one -MDCCXXXII one thousand, seven hundred thirty two -MDCCXXXIII one thousand, seven hundred thirty three -MDCCXXXIV one thousand, seven hundred thirty four -MDCCXXXV one thousand, seven hundred thirty five -MDCCXXXVI one thousand, seven hundred thirty six -MDCCXXXVII one thousand, seven hundred thirty seven -MDCCXXXVIII one thousand, seven hundred thirty eight -MDCCXXXIX one thousand, seven hundred thirty nine -MDCCXL one thousand, seven hundred forty -MDCCXLI one thousand, seven hundred forty one -MDCCXLII one thousand, seven hundred forty two -MDCCXLIII one thousand, seven hundred forty three -MDCCXLIV one thousand, seven hundred forty four -MDCCXLV one thousand, seven hundred forty five -MDCCXLVI one thousand, seven hundred forty six -MDCCXLVII one thousand, seven hundred forty seven -MDCCXLVIII one thousand, seven hundred forty eight -MDCCXLIX one thousand, seven hundred forty nine -MDCCL one thousand, seven hundred fifty -MDCCLI one thousand, seven hundred fifty one -MDCCLII one thousand, seven hundred fifty two -MDCCLIII one thousand, seven hundred fifty three -MDCCLIV one thousand, seven hundred fifty four -MDCCLV one thousand, seven hundred fifty five -MDCCLVI one thousand, seven hundred fifty six -MDCCLVII one thousand, seven hundred fifty seven -MDCCLVIII one thousand, seven hundred fifty eight -MDCCLIX one thousand, seven hundred fifty nine -MDCCLX one thousand, seven hundred sixty -MDCCLXI one thousand, seven hundred sixty one -MDCCLXII one thousand, seven hundred sixty two -MDCCLXIII one thousand, seven hundred sixty three -MDCCLXIV one thousand, seven hundred sixty four -MDCCLXV one thousand, seven hundred sixty five -MDCCLXVI one thousand, seven hundred sixty six -MDCCLXVII one thousand, seven hundred sixty seven -MDCCLXVIII one thousand, seven hundred sixty eight -MDCCLXIX one thousand, seven hundred sixty nine -MDCCLXX one thousand, seven hundred seventy -MDCCLXXI one thousand, seven hundred seventy one -MDCCLXXII one thousand, seven hundred seventy two -MDCCLXXIII one thousand, seven hundred seventy three -MDCCLXXIV one thousand, seven hundred seventy four -MDCCLXXV one thousand, seven hundred seventy five -MDCCLXXVI one thousand, seven hundred seventy six -MDCCLXXVII one thousand, seven hundred seventy seven -MDCCLXXVIII one thousand, seven hundred seventy eight -MDCCLXXIX one thousand, seven hundred seventy nine -MDCCLXXX one thousand, seven hundred eighty -MDCCLXXXI one thousand, seven hundred eighty one -MDCCLXXXII one thousand, seven hundred eighty two -MDCCLXXXIII one thousand, seven hundred eighty three -MDCCLXXXIV one thousand, seven hundred eighty four -MDCCLXXXV one thousand, seven hundred eighty five -MDCCLXXXVI one thousand, seven hundred eighty six -MDCCLXXXVII one thousand, seven hundred eighty seven -MDCCLXXXVIII one thousand, seven hundred eighty eight -MDCCLXXXIX one thousand, seven hundred eighty nine -MDCCXC one thousand, seven hundred ninety -MDCCXCI one thousand, seven hundred ninety one -MDCCXCII one thousand, seven hundred ninety two -MDCCXCIII one thousand, seven hundred ninety three -MDCCXCIV one thousand, seven hundred 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thousand, nine hundred forty -MCMXLI one thousand, nine hundred forty one -MCMXLII one thousand, nine hundred forty two -MCMXLIII one thousand, nine hundred forty three -MCMXLIV one thousand, nine hundred forty four -MCMXLV one thousand, nine hundred forty five -MCMXLVI one thousand, nine hundred forty six -MCMXLVII one thousand, nine hundred forty seven -MCMXLVIII one thousand, nine hundred forty eight -MCMXLIX one thousand, nine hundred forty nine -MCML one thousand, nine hundred fifty -MCMLI one thousand, nine hundred fifty one -MCMLII one thousand, nine hundred fifty two -MCMLIII one thousand, nine hundred fifty three -MCMLIV one thousand, nine hundred fifty four -MCMLV one thousand, nine hundred fifty five -MCMLVI one thousand, nine hundred fifty six -MCMLVII one thousand, nine hundred fifty seven -MCMLVIII one thousand, nine hundred fifty eight -MCMLIX one thousand, nine hundred fifty nine -MCMLX one thousand, nine hundred sixty -MCMLXI one thousand, nine hundred sixty one 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hundred eighty two -MCMLXXXIII one thousand, nine hundred eighty three -MCMLXXXIV one thousand, nine hundred eighty four -MCMLXXXV one thousand, nine hundred eighty five -MCMLXXXVI one thousand, nine hundred eighty six -MCMLXXXVII one thousand, nine hundred eighty seven -MCMLXXXVIII one thousand, nine hundred eighty eight -MCMLXXXIX one thousand, nine hundred eighty nine -MCMXC one thousand, nine hundred ninety -MCMXCI one thousand, nine hundred ninety one -MCMXCII one thousand, nine hundred ninety two -MCMXCIII one thousand, nine hundred ninety three -MCMXCIV one thousand, nine hundred ninety four -MCMXCV one thousand, nine hundred ninety five -MCMXCVI one thousand, nine hundred ninety six -MCMXCVII one thousand, nine hundred ninety seven -MCMXCVIII one thousand, nine hundred ninety eight -MCMXCIX one thousand, nine hundred ninety nine -MM two thousand diff --git a/nemo_text_processing/text_normalization/en/data/suppletive.tsv b/nemo_text_processing/text_normalization/en/data/suppletive.tsv deleted file mode 100644 index 115460aa2fae..000000000000 --- a/nemo_text_processing/text_normalization/en/data/suppletive.tsv +++ /dev/null @@ -1,83 +0,0 @@ -deer -fish -sheep -foot feet -goose geese -man men -mouse mice -tooth teeth -woman women -won -child children -ox oxen -wife wives -wolf wolves -analysis analyses -criterion criteria -lbs -focus foci -percent -hertz -kroner krone -inch inches -calory calories -yen -megahertz -gigahertz -kilohertz -hertz -CC -c c -horsepower -hundredweight -kilogram force kilograms force -mega siemens -revolution per minute revolutions per minute -mile per hour miles per hour -megabit per second megabits per second -square foot square feet -kilobit per second kilobits per second -degree Celsius degrees Celsius -degree Fahrenheit degrees Fahrenheit -ATM -AU -BQ -CC -CD -DA -EB -EV -F -GB -G -GL -GPA -GY -HA -H -HL -GP -HS -KB -KL -KN -KT -KV -LM -MA -MA -MB -MC -MF -M -MM -MS -MV -MW -PB -PG -PS -S -TB -YB -ZB \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/telephone/__init__.py b/nemo_text_processing/text_normalization/en/data/telephone/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/en/data/telephone/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/telephone/ip_prompt.tsv b/nemo_text_processing/text_normalization/en/data/telephone/ip_prompt.tsv deleted file mode 100644 index 03e2529895d9..000000000000 --- a/nemo_text_processing/text_normalization/en/data/telephone/ip_prompt.tsv +++ /dev/null @@ -1,2 +0,0 @@ -IP address is -IP is \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/telephone/ssn_prompt.tsv b/nemo_text_processing/text_normalization/en/data/telephone/ssn_prompt.tsv deleted file mode 100644 index 8bbdb9f752f7..000000000000 --- a/nemo_text_processing/text_normalization/en/data/telephone/ssn_prompt.tsv +++ /dev/null @@ -1,4 +0,0 @@ -ssn is SSN is -ssn is SSN is -SSN is -SSN \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/telephone/telephone_prompt.tsv b/nemo_text_processing/text_normalization/en/data/telephone/telephone_prompt.tsv deleted file mode 100644 index 6dcfb6cad223..000000000000 --- a/nemo_text_processing/text_normalization/en/data/telephone/telephone_prompt.tsv +++ /dev/null @@ -1,5 +0,0 @@ -call me at -reach at -reached at -my number is -hit me up at \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/time/__init__.py b/nemo_text_processing/text_normalization/en/data/time/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/time/suffix.tsv b/nemo_text_processing/text_normalization/en/data/time/suffix.tsv deleted file mode 100644 index 026a6a90ccce..000000000000 --- a/nemo_text_processing/text_normalization/en/data/time/suffix.tsv +++ /dev/null @@ -1,12 +0,0 @@ -p.m. PM -p.m PM -pm PM -P.M. PM -P.M PM -PM PM -a.m. AM -a.m AM -am AM -A.M. AM -A.M AM -AM AM diff --git a/nemo_text_processing/text_normalization/en/data/time/zone.tsv b/nemo_text_processing/text_normalization/en/data/time/zone.tsv deleted file mode 100644 index 0fda04208c87..000000000000 --- a/nemo_text_processing/text_normalization/en/data/time/zone.tsv +++ /dev/null @@ -1,14 +0,0 @@ -cst CST -c.s.t CST -cet CET -c.e.t CET -pst PST -p.s.t PST -est EST -e.s.t EST -pt PT -p.t PT -et ET -e.t ET -gmt GMT -g.m.t GMT diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/__init__.py b/nemo_text_processing/text_normalization/en/data/whitelist/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/alternatives.tsv b/nemo_text_processing/text_normalization/en/data/whitelist/alternatives.tsv deleted file mode 100644 index 0ee8e2c1d79b..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/alternatives.tsv +++ /dev/null @@ -1,45 +0,0 @@ -Hon. Honorable -Mr. Mister -Mrs. Misses -Ms. Miss -Mr Mister -Mrs Misses -Ms Miss -AC air conditioning -AC air conditioner -AC air conditioners -AC alternating current -&Co. and Co. -&Co. and Company -Mon Monday -Tu Tuesday -Wed Wednesday -Th Thursday -Thur Thursday -Thurs Thursday -Fri Friday -Sat Saturday -Sun Sunday -Mon Mon -Tu Tu -Wed Wed -Th Th -Thur Thur -Thurs Thurs -Fri Fri -Sat Sat -Sun Sun -= equals -# number -No. number -No number -NO number -NO. number -NO nitrogen monoxide -NO NO -NO. NO. -No. No. -No No -VOL Volume -VOL. Volume -TV Television diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/alternatives_all_format.tsv b/nemo_text_processing/text_normalization/en/data/whitelist/alternatives_all_format.tsv deleted file mode 100644 index 449195c4f41f..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/alternatives_all_format.tsv +++ /dev/null @@ -1,14 +0,0 @@ -st street -st saint -dr doctor -dr drive -mt mount -sr senior -prof professor -mt mountain -sr senior -jr junior -vol volume -rd road -ave avenue -approx approximately diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/asr.tsv b/nemo_text_processing/text_normalization/en/data/whitelist/asr.tsv deleted file mode 100644 index c067e1796422..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/asr.tsv +++ /dev/null @@ -1,14713 +0,0 @@ -Ph.D. p h d -Hon. honorable -& and -Mt. Mount -Maj. Major -Rev. 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G. a b g -ABG a b g -ABH a b h -ABHD a b h d -Abhi a b h i -ABK a b k -abl a b l -Abl a b l -ABL a b l -ABLV a b l v -ABM a b m -ABMC a b m c -ABN a b n -ABN's a b n's -Abp a b p -ABP a b p -ABPD a b p d -ABPI a b p i -ABPN a b p n -ABPP a b p p -ABPRS a b p r s -ABPW a b p w -Abr a b r -ABR a b r -abv a b v -ABV a b v -ABW a b w -ABX a b x -Abz a b z -A.C.A. a c a -ACA a c a -A&C a and c -A. C. a c -A.C. a c -acac a c a c -Acad a c a d -ACAD a c a d -A.C.A.P. a c a p -ACAP a c a p -ACAS a c a s -ACAZ a c a z -ACBA a c b a -ACB a c b -ACBL a c b l -ACBS a c b s -ACBSP a c b s p -ACCA a c c a -ACC a c c -ACCC a c c c -ACCJ a c c j -ACC&S a c c and s -ACC's a c c's -ACCS a c c s -ACD a c d -ACDC a c d c -A.C. D.F.C. A.F.C. a c d f c a f c -A.C.E. a c e -ACF a c f -ACFE a c f e -A.C.G. a c g -ACG a c g -ACGIH's a c g i h's -A.C.H. a c h -ACH a c h -ACHP a c h p -ACHR a c h r -ACHRE a c h r e -Achs a c h's -ACHS a c h s -ACIA a c i a -ACI a c i -ACICS a c i c s -ACIGA a c i g a -ACIP a c i p -Acis a c i's -ACIS a c i s -ACLA a c l a -A.C.L. a c l -ACL a c l -A.C.L.N. a c l n -acls a c l s -ACL's a c l's -ACLS a c l s -ACLU a c l u -ACM a c m -ACMI a c m i -ACMs a c m's -ACN a c n -ACO's a c o's -AcpA a c p a -ACP a c p -AcpB a c p b -ACPI a c p i -ACPO a c p o -ACPP a c p p -ACPSEM a c p s e m -acq a c q -A&CR a and c r -ACR a c r -ACRPS a c r p s -ACSA a c s a -ACSAC a c s a c -ACSBR a c s b r -ACSCN a c s c n -ACSEL a c s e l -ACSIA a c s i a -ACSI a c s i -AcSOC a c s o c -ACSR a c s r -ACSS a c s s -ACSS's a c s s's -A.C.T. a c t -A.C.T.A.F.L. a c t a f l -acu a c u -ACU a c u -ACU's a c u's -ACUS a c u s -ACUV a c u v -ACV a c v -ACWA a c w a -AC&W a c and w -ACW a c w -ACWM a c w m -ACWS a c w s -Acy a c y -ADAA a d a a -A&D a and d -Adab a d a b -ADAC a d a c -A. D. a d -A.D. a d -A.D.A.M. adam -AdaSL a d a s l -ADATA a d a t a -ADBAC a d b a c -ADB a d b -ADBGR a d b g r -ADBICA a d b i c a -ADCA a d c a -AdC a d c -A.D.C. a d c -ADC a d c -ADCAF a d c a f -ADCC a d c c -ADC's a d c's -ADCs a d c's -ADCY a d c y -ADDA a d d a -AD&D a d and d -ADF a d f -ADF's a d f's -ADFS a d f s -ADG a d g -ADGB a d g b -ADH a d h -ADHD a d h d -ADHM a d h m -ADHS a d h s -ADIAC a d i a c -AdK a d k -ADK a d k -Adl a d l -ADL a d l -ADLL a d l l -ADLs a d l's -A.D.M.A.C. a d m a c -adm a d m -Adm a d m -ADM a d m -ADMK a d m k -admn a d m n -ADMN a d m n -ADNAC a d n a c -ADNEC a d n e c -ADNs a d n's -AdP a d p -A.D.P. a d p -ADP a d p -ADPCM a d p c m -ADPF a d p f -ADQ a d q -ADQ's a d q's -ADR a d r -ADRC a d r c -ADRP a d r p -ADRs a d r's -ADSB a d s b -ADSL a d s l -ADSR a d s r -ADSRs a d s r's -ADSs a d s's -ADT a d t -ADTG a d t g -Adwa a d w a -ADWC a d w c -ADX a d x -AEA a e a -A&E a and e -A. E. a e -A.E. a e -AEBN a e b n -A.E.C. a e c -AEC a e c -AECL a e c l -AECR a e c r -AEC's a e c's -Aed a e d -AED a e d -AEE a e e -AEF a e f -AEG a e g -A.E.G.I.S. a e g i s -aegte a e g t e -AEHL a e h l -AEIA a e i a -AEI a e i -AEIOU a e i o u -Aeka a e k a -AEK a e k -ael a e l -AEL a e l -Aema a e m a -AEM a e m -aen a e n -AEO a e o -AEPA a e p a -AEP a e p -aere a e r e -AEre a e r e -AErn a e r n -AERN a e r n -Aert a e r t -AESA a e s a -Aes a e's -AES a e s -aet a e t -AET a e t -AETC a e t c -AEU a e u -AEV a e v -AEW a e w -AEX a e x -Afa a f a -AFA a f a -af a f -Af a f -A. F. a f -A.F. a f -AF a f -Afaf a f a f -AFAP a f a p -AFB a f b -AFCA a f c a -afc a f c -A.F.C. a f c -AFC a f c -AFCEC a f c e c -AFCO a f c o -AFC's a f c's -AFCS a f c s -AFCSThe a f c s t h e -Afd a f d -AfD a f d -AfDB a f d b -AFDD a f d d -Afe a f e -AFE a f e -Aff a f f -AFF a f f -AFG a f g -AFGM a f g m -AFH a f h -AFIA a f i a -Afi a f i -AFI a f i -AFIP a f i p -Afiq a f i q -AFI's a f i's -AFJ a f j -A.F.L. a f l -AFL a f l -AFLEG a f l e g -AFLPA a f l p a -AFLP a f l p -AFL's a f l's -AFLUA a f l u a -A. F.M.A. a f m a -AFM a f m -AFMC a f m c -AFMs a f m's -AFN a f n -AFNET a f n e t -AFNOR a f n o r -AfNS a f n s -Afo a f o -AFO a f o -AFOP a f o p -AFP a f p -AFRA a f r a -Afr a f r -AFR a f r -AFRC a f r c -AFRL a f r l -AFROTC a f r o t c -AFRTS a f r t s -AFS a f s -AFSC a f s c -AFSPC a f s p c -A. F. T. a f t -AFTRA a f t r a -AFTRA's a f t r a's -AFTRS a f t r s -AFV a f v -AFW a f w -AFWS a f w s -AFX a f x -A. G. a g -A.G. a g -AGB a g b -AGC a g c -Agco a g c o -AGCO a g c o -Agda a g d a -AGD a g d -A.G.E. a g e -AGF a g f -AG&G a g and g -agg a g g -Agi a g i -AGI a g i -AGID a g i d -AGIR a g i r -Agis a g i's -A.G.J. a g j -A. G. K. a g k -AGL a g l -agli a g l i -AGM a g m -Agn a g n -AgN a g n -AGN a g n -AGNs a g n's -A.G.P. a g p -AGP a g p -AGPL a g p l -AGPS a g p s -AGPW a g p w -AGRs a g r's -AGS a g s -AGSM a g s m -Agsu a g s u -agt a g t -AGT a g t -Agte a g t e -Agu a g u -AGU a g u -AGV a g v -A.H.A. a h a -A. H. a h -A.H. a h -A. H. C. a h c -AHC a h c -AHD a h d -Ahdhra a h d h r a -AHDR a h d r -ahe a h e -Ahe a h e -AHEC a h e c -AHF a h f -Ahirs a h i r's -Ahk a h k -AHL's a h l's -AHP a h p -AHRC a h r c -AHRS a h r s -AHSAA a h s a a -Ahsa'i a h s a i -Ahta a h t a -aht a h t -AHT a h t -AHTD a h t d -Ahu a h u -Ahva a h v a -AHV a h v -AIAA a i a a -A.I.A. a i a -A&I a and i -A. I. a i -A.I. a i -AI a i -AIAP a i a p -Aias a i a's -AIAS a i a s -AIATSIS a i a t s i s -AIAW a i a w -AIAWU a i a w u -A.I.B.A. a i b a -AIB a i b -AIBO's a i b o's -AIBS a i b s -AIC a i c -AICAR a i c a r -AICC a i c c -AICCCR a i c c c r -aici a i c i -Aicme a i c m e -AICN a i c n -AICPA a i c p a -AICP a i c p -AICPS a i c p s -AICs a i c's -AICTE a i c t e -AICUF a i c u f -AIDA a i d a -AIDN a i d n -AIEC a i e c -AIEE a i e e -Aiel a i e l -AIEP a i e p -AIFA a i f a -AIF a i f -AIFB a i f b -Aife a i f e -AIFF a i f f -AIFM a i f m -AIFMD a i f m d -AiG a i g -AIG a i g -Aigis a i g i's -AIHA a i h a -AIH a i h -AIHL a i h l -AIIMS a i i m s -Aija a i j a -Aik a i k -AIK a i k -AIKR a i k r -A.I.M. a i m -AIP a i p -A.I.R. a i r -AIs a i's -AISC a i s c -AISD a i s d -AISRI a i s r i -Aist a i s t -AIST a i s t -AIT's a i t's -Aitu a i t u -Aiud a i u d -aius a i u s -AIVC a i v c -AIW a i w -AIX a i x -A. J. a j -A.J. a j -Ajba a j b a -A.J.B. a j b -AJC a j c -A.J.E. a j e -A.J.G.C. a j g c -A. J. J. a j j -A.J.K. a j k -AJK a j k -AJKF a j k f -AJL a j l -A. J. M. a j m -Ajmi a j m i -AJN a j n -AJO a j o -Ajok a j o k -A. J. P. a j p -A.J.P. a j p -AJPW a j p w -A.J.R. a j r -AJR a j r -Ajsa a j s a -A.J.S. a j s -AJS a j s -A. J. T. a j t -A.J.T. a j t -AJT a j t -Aju a j u -AJUFE a j u f e -AJUSCO a j u s c o -AJV a j v -AJW a j w -AJWRC a j w r c -Akaa a k a a -a.k.a. a k a -aka. a k a -aka a k a -Aka. a k a -Aka a k a -AKA a k a -A&K a and k -A. K. a k -A.K. a k -AK a k -AKAP a k a p -AKAPs a k a p's -akas a k a's -AKAs a k a's -AKB a k b -AKC a k c -AKCR a k c r -AKD a k d -AKG a k g -AKG's a k g's -akh a k h -AKH a k h -AKHS a k h s -AKM a k m -AKN a k n -Akpa a k p a -AKP a k p -AKPD a k p d -AKQA a k q a -AKR a k r -A.K.S. a k s -AKS a k s -Aku a k u -AKU a k u -AKW a k w -A&L a and l -A. L. a l -A.L. a l -ALDF a l d f -ALDH a l d h -ALDS a l d s -ALDT a l d t -ALFASID a l f a s i d -ALFIDI a l f i d i -ALFTP a l f t p -Alh a l h -ALH a l h -A. L. M. a l m -A.L.P. a l p -ALPG a l p g -ALR a l r -ALSC a l s c -ALSF a l s f -ALSP a l s p -ALUs a l u's -A.L.V. a l v -ALVF a l v f -ALW a l w -ALWS a l w s -AMAA a m a a -A'ma a m a -A&M a and m -a.m. a m -a.m a m -A. M. a m -A.M. a m -AMAP a m a p -AMARC a m a r c -AMAs a m a's -amb a m b -Amb a m b -AMB a m b -AmBX a m b x -A.M.C. a m c -AMC a m c -AMC's a m c's -AMCs a m c's -Amda a m d a -Amd a m d -AMD a m d -AMDH a m d h -AMDISA a m d i s a -AMD's a m d's -A.M.E. a m e -AMF a m f -AM&FM a m and f m -A. M. G. a m g -AMG a m g -AMGTV a m g t v -Amha a m h a -AMH a m h -A.M.H.S. a m h s -A. M. J. a m j -AMJ a m j -A. M. K. a m k -A.M.K. a m k -AMK a m k -aml a m l -AML a m l -Amli a m l i -AMLS a m l s -Amlwch a m l w c h -Amm a m m -A. M. M. a m m -AMM a m m -AMMAYI a m m a y i -AMMB a m m b -AMMK a m m k -AMN a m n -AMNH a m n h -AMNRL a m n r l -AM&O a m and o -AMPK a m p k -AMPL a m p l -AMP's a m p's -Ampt a m p t -AMPTP a m p t p -amr a m r -A. M. R. a m r -AMREF a m r e f -AMSA a m s a -A&M's a and m's -Ams' a m's -amsl a m s l -AMSO's a m s o's -AMSRS a m s r s -AMS's a m s's -AMSS a m s s -AMSU a m s u -Amta a m t a -amt a m t -Amt a m t -A.M.T. a m t -AMT a m t -AMTB a m t b -AMTPAT a m t p a t -Amts a m t's -AMTV a m t v -Amu a m u -AMU a m u -AMU's a m u's -A.M.V.M. a m v m -AMW a m w -AMX a m x -AMYF a m y f -A. N. a n -A.N. a n -ANB a n b -ANBO a n b o -ANC a n c -ANCC a n c c -ANC's a n c's -andFHL a n d f h l -ANDOC a n d o c -ANDP a n d p -ANDPOP a n d p o p -andPPP a n d p p p -Anej a n e j -ANELFA a n e l f a -ANF a n f -ANFIS a n f i s -ANFP's a n f p's -ANGB a n g b -ANGPTL a n g p t l -ANGRAU a n g r a u -Angti a n g t i -Angu a n g u -Anhe a n h e -ANI a n i -ANL a n l -ANM a n m -ANP a n p -ANPP a n p p -ANPR a n p r -Anr a n r -ANR a n r -ANRC a n r c -ANREF's a n r e f's -Anrep a n r e p -ANRS a n r s -ANRW a n r w -A.N.S. a n s -ANS a n s -ANSF a n s f -ANTB a n t b -ANTM a n t m -ANTV a n t v -ANUGA a n u g a -ANWB a n w b -ANX a n x -ANZ a n z -A&O a and o -AOA a o a -AOAC a o a c -A. O. a o -A.O. a o -AOB a o b -AOC a o c -AOCB a o c b -AOCCs a o c c's -AOCE a o c e -AOD a o d -Aodh a o d h -Aodla a o d l a -AODV a o d v -AOE a o e -AOGCC a o g c c -Aogo a o g o -AOH a o h -Aoke a o k e -Aoko a o k o -AOKP a o k p -Aola a o l a -Aol a o l -AOL a o l -AOL's a o l's -AOLTV a o l t v -AOM a o m -AOMC a o m c -AONB a o n b -Aone a o n e -Aoni a o n i -Aoos a o o's -AOPA a o p a -AOP a o p -aor a o r -AOR a o r -AORs a o r's -AORS a o r s -aos a o s -AoS a o s -AOS a o s -Aotus a o t u's -AOTW a o t w -aov a o v -aovf a o v f -AOWC a o w c -A&P a and p -A. P. a p -A.P. a p -APBA a p b a -APB a p b -APBL a p b l -APCA a p c a -Apc a p c -APC a p c -APCCR a p c c r -APCh a p c h -APCR a p c r -APCRDA a p c r d a -APC's a p c's -APCs a p c's -APDA a p d a -APD a p d -APDM a p d m -APEGBC a p e g b c -APFA a p f a -APF a p f -APFCT a p f c t -APFOL a p f o l -APFSDS a p f s d s -APFUTU a p f u t u -apg a p g -APG a p g -APGAW a p g a w -Aph a p h -A.P.H. a p h -APH a p h -APHEDA a p h e d a -APHL a p h l -Apiao a p i a o -Api a p i -APi a p i -API a p i -Apic a p i c -APICv a p i c v -API's a p i's -A.P.J. a p j -APJ a p j -Apl a p l -APL a p l -APLP a p l p -APLS a p l s -Aplu a p l u -APM a p m -APML a p m l -APMR a p m r -APMSO a p m s o -APN a p n -A.P.N.C. a p n c -Apphttp a p p h t t p -Appl a p p l -APPO's a p p o's -appr a p p r -Appts a p p t's -appu a p p u -Appu a p p u -APRA's a p r a's -APRC a p r c -APR's a p r's -APRS a p r s -APRST a p r s t -A&P's a and p's -Aps a p's -APs a p's -APS a p s -APSF a p s f -APSL a p s l -APTA a p t a -AP&T a p and t -APW a p w -APX a p x -APXS a p x s -Aqa a q a -AQA a q a -AQC a q c -AQI a q i -Aql a q l -AQP a q p -Aqr a q r -A&R a and r -ARA a r a -A. R. a r -A.R. a r -A.R.B. a r b -ARD a r d -ARDF a r d f -A.R.E. a r e -A.R.F. a r f -ARF a r f -A.R.G. a r g -ArgR a r g r -ARGs a r g's -ARGT a r g t -ArH a r h -ARJ a r j -ARL a r l -ARLFC a r l f c -A. R. M. a r m -ARMv a r m v -Arnd a r n d -ARNG a r n g -ARNT a r n t -A.R.P. a r p -ARQ a r q -ARTL a r t l -A.R.U. a r u -arv a r v -Arv a r v -ARV a r v -ARVD a r v d -ARVN a r v n -ARW a r w -Arwi a r w i -ARWU a r w u -A.S.A. a s a -ASA a s a -As'ad a s a d -Asai a s a i -Asao a s a o -A.s a's -A. S. a s -A.S. a s -ASAS a s a s -Asasp a s a s p -ASAU a s a u -A.S.B. a s b -ASB a s b -ASBDA a s b d a -asbl a s b l -ASBM a s b m -ASBMH a s b m h -ASBO a s b o -A.S.C. a s c -ASC a s c -ASCB a s c b -ASCE a s c e -asci a s c i -Asci a s c i -ASCP a s c p -ASCW a s c w -A.S.D. a s d -ASD a s d -ASDIC a s d i c -Asdis a s d i's -ASE a s e -ASEC a s e c -ASEE a s e e -ASEF a s e f -ASFA a s f a -ASF a s f -Asfi a s f i -ASGA a s g a -ASG a s g -ASGC a s g c -ASGE a s g e -ASGS a s g s -A. S. H. a s h -A.S.I. a s i -ASL a s l -A.S.M. a s m -ASM a s m -ASMD a s m d -ASME a s m e -ASMIK a s m i k -ASML a s m l -ASMPH a s m p h -ASMSU a s m s u -Asn a s n -ASN a s n -Aso a s o -ASO a s o -ASP a s p -ASPCA a s p c a -Aspe a s p e -ASPTS a s p t s -Asr a s r -ASR a s r -Assn a s s n -assoc a s s o c -Assoc a s s o c -ASSPs a s s p's -ASSR a s s r -Asst a s s t -ASSU a s s u -A. S. T. a s t -ASTAT a s t a t -ASTCL a s t c l -Aste a s t e -ASTE a s t e -ASTM a s t m -ASTR a s t r -Astt a s t t -A.S.U. a s u -ASU a s u -A.S.V. a s v -ASV a s v -Aswa a s w a -ASW a s w -ASX a s x -A&T a and t -atac a t a c -Atac a t a c -Atad a t a d -Ata's a t a's -Atas a t a's -ATA's a t a's -A. T. a t -A.T. a t -ATBF a t b f -ATBs a t b's -atc a t c -A.T.C. a t c -ATC a t c -atcc a t c c -ATCC a t c c -ATCDE a t c d e -ATCL a t c l -ATDC a t d c -ATF a t f -Atg a t g -ATG a t g -ATGM a t g m -ath a t h -Ath a t h -ATH a t h -ATHN a t h n -ATIA a t i a -Atia's a t i a's -Ati a t i -ATi a t i -ATI a t i -Atid a t i d -Atiiq a t i i q -Atil a t i l -ATINC a t i n c -ATIP a t i p -Atiq a t i q -Ativ a t i v -ATJ a t j -Atka a t k a -ATK a t k -ATKN a t k n -ATK's a t k's -Atl a t l -ATL a t l -Atli a t l i -ATLY a t l y -A.T.M.A. a t m a -atm a t m -Atm a t m -ATM a t m -ATMs a t m's -ATN a t n -ATO a t o -Atos a t o's -ATO's a t o's -ATOs a t o's -ATOS a t o s -ATP a t p -atpB a t p b -A.T.Q. a t q -ATR a t r -atri a t r i -Atri a t r i -ATRP a t r p -A&T's a and t's -A.T.s a t's -A.T.S. a t s -ATS a t s -ATSC a t s c -ATSDR a t s d r -AT&SF a t and s f -ATSF a t s f -ATSIC a t s i c -AT&T a t and t -attd a t t d -ATTESA a t t e s a -ATTF a t t f -AT&T's a t and t's -ATTS a t t s -ATTWI a t t w i -ATTWX's a t t w x's -ATU's a t u's -atv a t v -ATV a t v -ATV's a t v's -ATVs a t v's -ATW a t w -AtxA a t x a -ATX a t x -ATXN a t x n -A. U. a u -A.U. a u -Aub a u b -Aubl a u b l -AUC a u c -AUVs a u v's -Auw a u w -avab a v a b -AVAC a v a c -A. V. a v -A.V. a v -AVCA a v c a -AVC a v c -AVCHD a v c h d -AVCs a v c's -AVCS a v c s -AVD a v d -avg a v g -AVG a v g -AVK a v k -AVL a v l -A. V. M. a v m -AVM a v m -Avn a v n -AVN a v n -Avo a v o -AvP a v p -AVP a v p -AVR a v r -AVRs a v r's -AVSA a v s a -Avs' a v's -Avs a v's -AVS a v s -AVSM a v s m -AVU a v u -avvo a v v o -AVX a v x -Awa a w a -A. W. A. a w a -AWA a w a -A. W. A. M. a w a m -AWAs a w a's -A. W. a w -A.W. a w -A. W. B. a w b -A.W.B. a w b -AWB a w b -AWB's a w b's -A.W.C. a w c -AWC a w c -AWD a w d -A. W. F. a w f -AWG a w g -AWGIE a w g i e -AWGN a w g n -A. W. H. a w h -AWHL a w h l -AWI a w i -AWM a w m -Awo a w o -AWP a w p -AWP's a w p's -AWR a w r -AWSA a w s a -AWU a w u -Awwa a w w a -AXAF a x a f -A. X. a x -AXS a x s -AXV a x v -A. Y. a y -A.Y. a y -AYF a y f -AYK a y k -AYP a y p -A. Z. a z -A.Z. a z -AZE a z e -Azg a z g -Azi a z i -AZI a z i -AZL a z l -azm a z m -AZN a z n -AZS a z s -AZSTA's a z s t a's -AZT a z t -AzTV a z t v -Baad b a a d -BAAG b a a g -Ba'al b a a l -Baal b a a l -BAAL b a a l -Baam b a a m -Baap b a a p -ba'as b a a's -Baat b a a t -Ba'ath b a a t h -B. A. b a -B.A. b a -B&A b and a -Bac b a c -B.A.C. b a c -BAC b a c -bae b a e -Bae b a e -BAe b a e -BAE b a e -BAFA b a f a -BAF b a f -B.A.R. b a r -BARV b a r v -BASCA b a s c a -BASEC b a s e c -BASF b a s f -B.A.S.P. b a s p -BATVG b a t v g -Bauw b a u w -B'Av b a v -BAV b a v -BBA b b a -BBAG b b a g -B&B b and b -bb b b -B. B. b b -B.B. b b -BB b b -BBB b b b -bbc b b c -B.B.C. b b c -BBC b b c -BBCBBC b b c b b c -BB&CI b b and c i -BBC&PJR b b c and p j r -BBC's b b c's -B.B.D. b b d -BBDO b b d o -BBE b b e -BBF b b f -BBFC b b f c -BBFF b b f f -BBG b b g -BBH b b h -BBI b b i -BBK b b k -BBKL b b k l -BBLB b b l b -BBL b b l -BBM b b m -BBMP b b m p -BBNG b b n g -BBN's b b n's -BBO b b o -BBP b b p -BBQ'er b b q e r -B&Bs b and b's -BB&S b b and s -BBS b b s -BBSes b b s e's -BBS's b b s's -BB&T b b and t -BBT b b t -BBTV b b t v -BBU b b u -BBVA b b v a -BbvCI b b v c i -BBV's b b v's -BBWAA b b w a a -BBWA b b w a -BBWR's b b w r's -BBYA b b y a -BBYO b b y o -BCA b c a -BCAD b c a d -BCAM b c a m -BCATP b c a t p -BCBA b c b a -BCB b c b -bc b c -B. C. b c -B.C. b c -BC b c -BCCA b c c a -BCC b c c -BCCCA b c c c a -Bcci b c c i -BCCI b c c i -BCCP b c c p -BCC's b c c's -BCDA b c d a -BCD b c d -BCEA b c e a -BCE b c e -BCE's b c e's -BCF b c f -BCG b c g -BCG's b c g's -BCHL b c h l -BCHR's b c h r's -BCHS b c h s -BCI b c i -B. C. J. b c j -BCL b c l -BCLR b c l r -BCMA b c m a -BCM b c m -BCMG b c m g -BCMHS b c m h s -BCMS b c m s -BCN b c n -BCN's b c n's -BCP b c p -BCPM b c p m -BCR b c r -BCRF's b c r f's -B.C.'s b c's -BC's b c's -BCs b c's -BCS b c s -BCSC b c s c -BCSic b c s i c -BCSN b c s n -BCT b c t -BCTC b c t c -BCU b c u -BCYP b c y p -BdA b d a -BDA b d a -bd b d -B. D. b d -B.D. b d -BD b d -BDBL b d b l -BDC b d c -BDC's b d c's -BDD b d d -Bde b d e -B. D. E. b d e -BDE b d e -BDF b d f -BDI b d i -BDJ b d j -BDK b d k -BDK's b d k's -BDMI b d m i -BDN b d n -BDNF b d n f -BDO b d o -BDO's b d o's -BDOS b d o s -BDP b d p -BDR b d r -bds b d s -BDS b d s -BDSM b d s m -BdU b d u -BDU b d u -BDV b d v -B. D. W. b d w -B.E.A. b e a -B. E. b e -B.E. b e -Bedw b e d w -B.E.E. b e e -bef b e f -B.E.F. b e f -BEF b e f -BEF's b e f's -bei b e i -Bei b e i -Beih b e i h -BEIR b e i r -Beis b e i's -bej b e j -B.E.M. b e m -BEMs b e m's -BEP b e p -Ber b e r -BER b e r -Bes b e's -B.E.S. b e s -BES b e s -B.F.A. b f a -BFA b f a -bf b f -B. F. b f -B.F. b f -BF b f -BFCA b f c a -BFC b f c -BFC's b f c's -BFDG b f d g -BFES b f e s -BFF b f f -BFFs b f f's -B. F. G. b f g -BFG b f g -BFG's b f g's -BFI b f i -BFI's b f i's -BFJA b f j a -BFKL b f k l -BFL b f l -BFM b f m -BFO b f o -BFRA b f r a -BFR b f r -BFSA b f s a -BFS b f s -BFT b f t -BFU b f u -bfy b f y -BGAB b g a b -BGA b g a -BGB b g b -B. G. b g -B.G. b g -BGC b g c -BGCI b g c i -BGD b g d -BGEA b g e a -B. G. E. b g e -BGH b g h -B. G. J. S. b g j s -BGL b g l -BglII b g l i i -BGM b g m -BGP b g p -BGRA b g r a -BGR b g r -BGRC b g r c -BGRSO b g r s o -bgs b g s -B.G.S. b g s -BGS b g s -BGSU b g s u -BGT b g t -Bgy b g y -Bha b h a -B&H b and h -B. H. b h -B.H. b h -BHCC b h c c -BHDP b h d p -BH&E b h and e -Bhe b h e -BHL b h l -BHMA b h m a -BHMO b h m o -BHMs b h m's -BHMT b h m t -BHO b h o -B. H. P. b h p -BHP b h p -BHRT b h r t -BHS b h s -BHSN b h s n -BHSU b h s u -bhttp b h t t p -BHU b h u -BHUSD b h u s d -BHVS b h v s -B. I. b i -B.I. b i -Bie b i e -BIE b i e -biedt b i e d t -Biem b i e m -B.I.G. b i g -B.I.G.'s b i g's -BiH b i h -BIH b i h -B.I.O.L.A. b i o l a -B. J. b j -B.J. b j -BJCC b j c c -BJCP b j c p -BJD b j d -B.J.F. b j f -B. J. I. b j i -BJJ b j j -BJP b j p -BJP's b j p's -BJPs b j p's -BJPS b j p s -B.J.'s b j's -B.J.T. b j t -BJT b j t -BJU b j u -BJY b j y -B.K.A. b k a -B&K b and k -B. K. b k -B.K. b k -BKCa b k c a -BKC b k c -BKF b k f -BKI b k i -BKN's b k n's -BKO b k o -B.K.R. b k r -BKR b k r -BK's b k's -BKS b k s -BKT b k t -BKTV b k t v -BKV b k v -B. L. b l -B.L. b l -BL b l -BLC b l c -BLCC b l c c -BLCN b l c n -ble b l e -bleg b l e g -blev b l e v -BLG b l g -bli b l i -BLI b l i -Blla b l l a -BLL b l l -BLM b l m -BLMC b l m c -BLOU's b l o u's -BLPP b l p p -BLR b l r -BLRC b l r c -BLR&D b l r and d -B.L.S. b l s -BLS b l s -BLT b l t -BLTF b l t f -BLTs b l t's -BLV b l v -BMAA b m a a -B.M.A. b m a -BMA b m a -BMAL b m a l -BMARC b m a r c -BMA's b m a's -B&M b and m -BMB b m b -B. M. b m -B.M. b m -BMCA b m c a -B.M.C. b m c -BMC b m c -bmd b m d -BMD b m d -BME b m e -BMF b m f -BMG b m g -BMHS b m h s -bmi b m i -BMI b m i -BMIC b m i c -BMIR b m i r -BMI's b m i's -BMIT b m i t -BMJ b m j -BMK b m k -BMKG b m k g -BMMO b m m o -BMNA b m n a -BMNH b m n h -BMNP b m n p -BMO b m o -BMP b m p -BMPs b m p's -BMR b m r -BMRs b m r's -BMSA b m s a -B.M.S. b m s -BMS b m s -bmt b m t -B. M. T. b m t -B.M.T. b m t -BMT b m t -BMT's b m t's -BMU b m u -B.M.V. b m v -BMV b m v -B. M. W. b m w -BMW b m w -BMW M b m w -BMW's b m w's -BMX b m x -BNA b n a -B&N b and n -bnb b n b -BNB b n b -B. N. b n -B.N. b n -BNC b n c -BNCI b n c i -BNCM b n c m -BNCT b n c t -BND b n d -BNDY b n d y -BNET b n e t -BNF b n f -BNFL b n f l -BNI b n i -BNIC b n i c -BNL b n l -BNO b n o -BNP b n p -BNR b n r -BNRC b n r c -BNS b n s -BNSF b n s f -BNST b n s t -BNT b n t -BNU b n u -BNY b n y -BNZ b n z -Boac b o a c -BOAC b o a c -B&O b and o -B. O. b o -B.O. b o -Boc b o c -BoC b o c -BOC b o c -BOCs b o c's -BOCS b o c s -boj b o j -Boj b o j -BOJ b o j -B.O.M.B. b o m b -B&O's b and o's -B.O.S. b o s -BOYZZ b o y z z -BPA b p a -BPB b p b -bp b p -B. P. b p -B.P. b p -BP b p -BPC b p c -BPD b p d -BPER b p e r -B.P.H. b p h -BPI b p i -BPJ b p j -BPK b p k -bpl b p l -BPL b p l -B. P. M. b p m -BPM b p m -BPMN b p m n -B.P.N. b p n -BPN b p n -B.P.O. b p o -BPO b p o -BPPA b p p a -BPP b p p -BPR b p r -B.P.R.D. b p r d -BPRD b p r d -BPSA b p s a -BP's b p's -BPS b p s -BPSK b p s k -BPUP b p u p -BPV b p v -BPY b p y -B&Q b and q -BQB b q b -B. Q. b q -BRAC's b r a c's -BRAM b r a m -BRBDP b r b d p -Brbic b r b i c -B. R. b r -B.R. b r -BRBR b r b r -BRBs b r b's -BRCA b r c a -BRC b r c -BRCC b r c c -BRD b r d -BRF b r f -BRGF b r g f -BRGM b r g m -BRHS b r h s -B.R.I.C.K. b r i c k -BRK b r k -BRL b r l -BRM b r m -BRMS b r m s -BRN b r n -BRNC b r n c -Brne b r n e -Brno b r n o -BRNV b r n v -BRP b r p -BRPS b r p s -BRRA b r r a -BRS b r s -BRSCC's b r s c c's -BRT b r t -BRTs b r t's -BRTS b r t s -BRVM b r v m -BRW b r w -BRWK b r w k -Brza b r z a -BRZ b r z -brzu b r z u -brzy b r z y -Brzyk b r z y k -BSAA b s a a -B.S.A. b s a -BSA b s a -BSAC b s a c -BsaL b s a l -BSBA b s b a -BSB b s b -BSBI b s b i -B. s b's -B.'s b's -Bs b's -B. S. b s -B.S. b s -BS b s -B.S.C. b s c -BSC b s c -BSCL b s c l -bsd b s d -BSD b s d -BSDE b s d e -BSE b s e -BSET b s e t -BSFA b s f a -BSF b s f -BSG b s g -BSH b s h -BSIB b s i b -BSI b s i -BSK b s k -BSL b s l -BSM b s m -BSME b s m e -BSN b s n -BSNL b s n l -BSOG b s o g -BSPA b s p a -BSP b s p -BSPP b s p p -BSR b s r -BSRN b s r n -BSS b s s -BSU b s u -BSV b s v -BSX b s x -BTA b t a -BTAF b t a f -BTB b t b -BTBD b t b d -bt b t -B. T. b t -B.T. b t -BT b t -BTCA b t c a -BTC b t c -BTCC b t c c -BTD b t d -BTF b t f -BTG b t g -BTH b t h -BTK b t k -BTL b t l -BTM b t m -BTN b t n -BTNK b t n k -BTOB b t o b -BTO b t o -BTP b t p -BTRC b t r c -BTRDA b t r d a -Btry b t r y -btsan b t s a n -BT's b t's -BTS b t s -BTT b t t -BTU b t u -btus b t u s -BTUs b t u's -BTV b t v -B.U. b u -B.U.M. b u m -BUV b u v -BVA b v a -BVB b v b -BVB's b v b's -B. V. b v -B.V. b v -BVC b v c -BVFB b v f b -BVI b v i -BVM b v m -BVO b v o -BVR b v r -BVRC b v r c -BVT b v t -BVVL b v v l -Bwa b w a -BWAF b w a f -B&W b and w -BWB b w b -BWBR b w b r -B. W. b w -B.W. b w -B.W.C. b w c -BWC b w c -BWF b w f -BWFC b w f c -BWHBC b w h b c -B. W. I. b w i -BWI b w i -BWIR b w i r -BWO b w o -BWR b w r -BWS b w s -BWT b w t -BWTs b w t's -BWV b w v -BWW b w w -bwwtv b w w t v -Bxa b x a -BX b x -Bxe b x e -BXML b x m l -BYA's b y a's -BYB b y b -B. Y. b y -byc b y c -BYC b y c -BYD b y d -BYFC b y f c -BYG b y g -bygd b y g d -Byk b y k -byn b y n -BYOB b y o b -Byo b y o -BYO b y o -Byou b y o u -BYR b y r -Byrl b y r l -bySLC b y s l c -BYST b y s t -byt b y t -B.Y.U. b y u -BYU b y u -BYU's b y u's -BYX b y x -BYZ b y z -B.Z. b z -BZ b z -BZD b z d -bzhed b z h e d -Bzik b z i k -BZK b z k -BZP b z p -Bzyb b z y b -CAA c a a -CAAC c a a c -CAAC's c a a c's -CAAHEP c a a h e p -CAAM c a a m -CAAS c a a s -CAASE c a a s e -Caat c a a t -CAAT c a a t -C. A. c a -C.A. c a -CA c a -C&A c and a -CAC c a c -CA&CC c a and c c -CACC c a c c -CACM c a c m -Cadw c a d w -CADW c a d w -caeca c a e c a -Cae c a e -CAE c a e -C.A.F.B. c a f b -CAFTT c a f t t -C. A. G. c a g -CAG c a g -CAGM c a g m -C. A. I. c a i -C. A. J. c a j -CALUX c a l u x -CAMC c a m c -CAMLG c a m l g -C.A.M.'s c a m's -C. A. N. c a n -Capt. captain -C. A. R. c a r -cas c a s -Cas c a's -C.A.S. c a s -CAS c a s -Casc c a s c -CASC c a s c -CASD c a s d -CASF c a s f -CASG c a s g -CASQ c a s q -C. A. T. c a t -C.A.T. c a t -CATV c a t v -C.A.W. c a w -CBA c b a -CBBB c b b b -CBB c b b -CBBC c b b c -CBBS c b b s -CBCA c b c a -cb c b -C. B. c b -C.B. c b -CB c b -cbc c b c -CBC c b c -CB&CNS c b and c n s -CBC's c b c's -CBCS c b c s -CBDA c b d a -CBD c b d -CBDs c b d's -C.B.E. c b e -CBE c b e -CBEF c b e f -CBE's c b e's -CBF c b f -CBGB c b g b -CBGB's c b g b's -CBGBs c b g b's -CBG c b g -CBH c b h -CBHG c b h g -CBI c b i -CBI's c b i's -CbiXS c b i x s -CBKB c b k b -CBK c b k -CBKMT c b k m t -CBKRT c b k r t -CBL c b l -CBL's c b l's -CBM c b m -CBMS c b m s -CBN c b n -CBN's c b n's -CBNT c b n t -CBO c b o -CBOT c b o t -CBP c b p -CBPE c b p e -CB&Q c b and q -CBR c b r -CBRE c b r e -CBRN c b r n -CBRNE c b r n e -CBSA c b s a -CBs c b's -CBS c b s -C.B.S.E. c b s e -CBSE c b s e -CBS's c b s's -CBT c b t -CBTC c b t c -CBTU c b t u -CBU c b u -CBUT c b u t -CBV c b v -CBWT c b w t -CBX c b x -CBYT c b y t -CBZH c b z h -'c c -CcaA c c a a -CCAA c c a a -CCAAT c c a a t -cca c c a -Cca c c a -CCA c c a -CCAF c c a f -CCAP c c a p -CCAR c c a r -CCAS c c a s -CCB c c b -CCBCC c c b c c -CCBE c c b e -CCCA c c c a -C&C c and c -C. C. c c -C.C. c c -CCCE c c c e -CCCF c c c f -CCCP c c c p -CCC's c c c's -CCDB c c d b -CCDC c c d c -ccd c c d -CCD c c d -CCDev c c d e v -CCDI c c d i -CCDI's c c d i's -CCDM c c d m -CCDR c c d r -CCD's c c d's -CCDs c c d's -CCEd c c e d -C.C.E.D. c c e d -CCF c c f -CCFO c c f o -CCG c c g -C.C.G.S. c c g s -CCGS c c g s -CCHA c c h a -CCHC c c h c -C.C.H. c c h -CCH c c h -CCHD c c h d -CCHS c c h s -C.C.I.A.A. c c i a a -CCIAA c c i a a -CCi c c i -CCI c c i -CCID c c i d -CCIE c c i e -CCIH c c i h -CCITT c c i t t -CCJ c c j -CCK c c k -CCLC c c l c -CCL c c l -CCMA c c m a -ccm c c m -CCM c c m -CCMM c c m m -CCMP c c m p -CCMS c c m s -CCN c c n -CCNY c c n y -CCO c c o -CCOKC c c o k c -CCOO c c o o -CCOP c c o p -C.C.O.W.E. E.T.F. c c o w e e t f -CCP c c p -CCPD c c p d -CCPL c c p l -CCPN c c p n -CCP's c c p's -CCQ c c q -CCRC c c r c -CCR c c r -CCRCs c c r c's -CCRH c c r h -CCRS c c r s -CCSA c c s a -CCSC c c s c -CC's c c's -CCS c c s -CCSD c c s d -C.C.S.D.N.Y. c c s d n y -C.C.S.M. c c s m -CCSN c c s n -CCSR c c s r -CCS's c c s's -cct c c t -CCT c c t -CCTF c c t f -CCTRN c c t r n -CCTT c c t t -CCTV c c t v -CCUA c c u a -CCU c c u -ccus c c u s -CCV c c v -CCVG c c v g -C. C. W. c c w -CCWD c c w d -CDA c d a -CDAT c d a t -CDB c d b -CDBS c d b s -CDCA c d c a -C&D c and d -cdc c d c -CDC c d c -cd c d -C. D. c d -C.D. c d -CD c d -CDC's c d c's -CDDB c d d b -CD&DR c d and d r -CDE c d e -CDF c d f -CDFI c d f i -CDFW c d f w -CDH c d h -CDi c d i -CDI c d i -CDISC c d i s c -CDI's c d i's -CDK c d k -CDKN c d k n -CDL c d l -CDLI c d l i -CDLS c d l s -CDMA c d m a -CDM c d m -cDNA c d n a -cdnas c d n a s -cDNAs c d n a's -CDN c d n -CDN's c d n's -CDO c d o -CDOs c d o's -CDPC c d p c -CDP c d p -CDP's c d p's -CDPs c d p's -CD&R c d and r -CDR c d r -cds c d s -CD's c d's -CDs c d's -CDS c d s -CDSG c d s g -CDSP c d s p -CDSPCo c d s p c o -CdtA c d t a -CDT c d t -CdTe c d t e -CDTi c d t i -CDTI c d t i -CDT's c d t's -CDTV c d t v -CDTV's c d t v's -CDU c d u -CDU's c d u's -CD&V c d and v -CDV c d v -CDW c d w -CDWP c d w p -Cec c e c -CEC c e c -c'e c e -ce c e -C'e c e -Ce c e -C. E. c e -C.E. c e -CE c e -CECP c e c p -CEDA c e d a -CEDO c e d o -CEDR c e d r -CEDS c e d s -CEEBA c e e b a -CEEB c e e b -CEEH c e e h -Ceel c e e l -CEEOL c e e o l -CEESA c e e s a -CEFC c e f c -CEF c e f -Cefn c e f n -CEFP c e f p -CEFR c e f r -CEGB c e g b -C.E.G. c e g -C. E. H. c e h -CEI c e i -C&EI's c and e i's -C. E. M. c e m -C&EN c and e n -cen c e n -Cen c e n -CEN c e n -ceo c e o -C.E.O. c e o -CEO c e o -Ceol c e o l -CEOP c e o p -Ceorl c e o r l -Ceos c e o's -CEO's c e o's -CEOs' c e o's -CEOs c e o's -C.E.P. c e p -cer c e r -Cer c e r -CER c e r -CERP c e r p -CERPER c e r p e r -CERS c e r s -ces c e s -Ces c e's -C.E.S. c e s -CES c e s -CESL c e s l -CESO c e s o -CETB c e t b -C. E. T. c e t -CEV c e v -CEVCP c e v c p -CEVG c e v g -CEW c e w -Cex c e x -CeX c e x -CEX c e x -CEZ c e z -CEZMS c e z m s -CFAB c f a b -Cfa c f a -CFA c f a -CFAS c f a s -C. F. B. c f b -CFB c f b -CFBG c f b g -CFBISD c f b i s d -CFB's c f b's -C&F c and f -CFC c f c -cf c f -C. F. c f -C.F. c f -CF c f -CFC's c f c's -CFDA c f d a -CFD c f d -C.F.E. c f e -CFE c f e -CFFC c f f c -C. F. F. c f f -CFF c f f -C. F. H. c f h -CFH c f h -CFHS c f h s -CFI c f i -CFIT c f i t -CFJL c f j l -CFJR c f j r -CFL c f l -CFL's c f l's -CFM c f m -CFMEU c f m e u -CFMI c f m i -CFND c f n d -CFNY c f n y -C.F.O.A. c f o a -CFO c f o -CFOP c f o p -CFOs c f o's -CFPI c f p i -CFPL c f p l -CFQ c f q -CFRB c f r b -C.F.R. c f r -CFR c f r -CFRP c f r p -CFS c f s -CFSCI c f s c i -CFSP c f s p -CFTA c f t a -CFT c f t -CFTO c f t o -CFTR c f t r -CFTs c f t's -CFTXOP c f t x o p -CFU c f u -CFYN c f y n -CFZ c f z -CGA c g a -CGAP c g a p -CGB c g b -C&G c and g -CGCFAD c g c f a d -C. G. c g -C.G. c g -CGCRI c g c r i -CGCS c g c s -CGD c g d -CGDK c g d k -CGE c g e -CGF c g f -CGFP c g f p -CGG c g g -CGI c g i -CGIL c g i l -CGKD c g k d -cgl c g l -CGL c g l -CGP c g p -CGPM c g p m -CGPME c g p m e -CGPW c g p w -CGR c g r -CGRP c g r p -CGS c g s -CGSS c g s s -CGT c g t -CGTG c g t g -CGTIC c g t i c -CGU c g u -CGW c g w -CGW's c g w's -C.H.B. c h b -CHBM c h b m -CHBX c h b x -C&H c and h -C.H.C. c h c -C. H. c h -C.H. c h -CHCO c h c o -CHD c h d -CHDK c h d k -CHDS c h d s -CHF c h f -CHFI c h f i -C.H.G. c h g -CHGO c h g o -CHH c h h -CHHOTO c h h o t o -CHHS c h h s -Chhu c h h u -Chirs c h i r's -CHISMS c h i s m s -CHISZ c h i s z -CHK c h k -CHL c h l -CHLR c h l r -CHL's c h l's -C. H. M. c h m -CHM c h m -CHN c h n -CHP c h p -CHP'den c h p d e n -CHPs c h p's -CHPS c h p s -CHR c h r -CHRDI c h r d i -CHRGD c h r g d -C.H.S. c h s -CHS c h s -CHSE c h s e -CHT c h t -CHV c h v -CHX c h x -Chy c h y -CHYR c h y r -CIAC c i a c -Cia c i a -C.I.A. c i a -CIA c i a -CIC c i c -ci c i -Ci c i -C. I. c i -C.I. c i -CI c i -Cicic c i c i c -CICL c i c l -C.I.C.M. c i c m -CICO c i c o -CIC's c i c's -C.I.D. c i d -CIFF c i f f -CIFL c i f l -CIHE c i h e -CIHR c i h r -cii c i i -CII c i i -CIID c i i d -CIJ c i j -CIKM c i k m -C.I.L. c i l -CIL c i l -cim c i m -Cim c i m -CIM c i m -Cio c i o -C.I.O. c i o -CIO c i o -CIOs c i o's -CIOT c i o t -CIPCA c i p c a -Cip c i p -C.I.P. c i p -CIP c i p -CIPD c i p d -CIPFA c i p f a -CIPM c i p m -CISA c i s a -CISC c i s c -cis c i s -CIs c i's -CIS c i s -CITB c i t b -cit c i t -CIT c i t -CiTD c i t d -CITM c i t m -CITN c i t n -CITP c i t p -citS c i t s -CITV c i t v -CITWF c i t w f -CitX c i t x -Ciuc c i u c -Ciu c i u -CiU c i u -CIU c i u -CIUT c i u t -CIVD c i v d -CIW c i w -CIWS c i w s -CIX c i x -Cixi c i x i -CIY c i y -CIZN c i z n -CJA c j a -CJBHL c j b h l -CJCA c j c a -CJCB c j c b -CJC c j c -C. J. c j -C.J. c j -CJD c j d -C. J. E. c j e -CJFL c j f l -CJFT c j f t -CJFX c j f x -CJGC c j g c -CJGO c j g o -CJHL c j h l -CJK c j k -CJL c j l -CJLS c j l s -CJM c j m -CJNT c j n t -CJOC c j o c -CJP c j p -C. J. R. c j r -C.J.R. c j r -CJR c j r -CJSC c j s c -C. J. S. c j s -CJS c j s -CJT c j t -CJUF c j u f -CJWC c j w c -CKAC c k a c -CKC c k c -C. K. c k -C.K. c k -CK c k -CKD c k d -CKE c k e -CKLM c k l m -CKLQ c k l q -CKLW c k l w -CKS c k s -CKSO c k s o -CKVL c k v l -C. K. W. c k w -CKWK c k w k -ckx c k x -CKXX c k x x -CKY c k y -CLAC c l a c -CLA c l a -CLAS c l a s -CLBs c l b's -clc c l c -CLC c l c -cl c l -C. L. c l -C.L. c l -CL c l -CLCN c l c n -CLD c l d -Cle c l e -CLE c l e -CLF c l f -C.L.G. c l g -CLG c l g -CLHIA c l h i a -CLHS c l h s -CLI c l i -CLK c l k -cllr c l l r -CLM c l m -CLMD c l m d -CLMP c l m p -CL&N c l and n -Clo c l o -CL&P c l and p -CLP c l p -CLRC c l r c -C. L. R. c l r -C.L.R. c l r -CLR c l r -CLRK c l r k -CLSA c l s a -CLSC c l s c -CLs c l's -CLS c l s -CLT c l t -CLTD c l t d -CLTPA c l t p a -CLTs c l t's -Clu c l u -CLU c l u -CLUK c l u k -CLV c l v -Clwyd c l w y d -CLX c l x -C&MA c and m a -CMAC c m a c -C.M.A. c m a -CMA c m a -CMAL c m a l -CMAP's c m a p's -CMAS c m a s -CMAT c m a t -C.M.B. c m b -CMB c m b -CMCC c m c c -CMCCDI c m c c d i -C.M.C. c m c -CMC c m c -cm c m -C. M. c m -C.M. c m -CM c m -CMCs c m c's -CMCS c m c s -CMD c m d -Cmde c m d e -CMDISE c m d i s e -cmdr c m d r -CMEC c m e c -CME c m e -CMF c m f -CMFS c m f s -C. M. G. c m g -C.M.G. c m g -CMG c m g -CMHC c m h c -CMH c m h -CMHR c m h r -CMI c m i -CMJ c m j -CMLA c m l a -cml c m l -C.M.L. c m l -CML c m l -CMLDP c m l d p -CMLL c m l l -CMLL's c m l l's -CMM c m m -CMMI c m m i -CMMs c m m's -cmn c m n -CMO c m o -CMO's c m o's -CMPC c m p c -CMP c m p -CMPS c m p s -CMPSO c m p s o -CMPV c m p v -CMQ c m q -CMQT c m q t -C. M. R. c m r -CMR c m r -CMSAF c m s a f -C.M.S. c m s -CMS c m s -C.M.S.L. c m s l -CMT c m t -Cmte c m t e -CMT's c m t's -CMTU c m t u -CMUCL c m u c l -CMU c m u -CMU's c m u's -CMV c m v -CMVM c m v m -CMVSS c m v s s -CMWF c m w f -CMXXII c m x x i i -CMYK c m y k -CNA c n a -CNBC c n b c -CNB c n b -CNC c n c -cn c n -C. N. c n -C.N. c n -CN c n -CNC's c n c's -CND c n d -CNDL c n d l -CNEB c n e b -CNE c n e -CNF c n f -CNFE c n f e -CNFK c n f k -CNG c n g -CNI c n i -CNJ c n j -CNJF c n j f -CNK c n k -C. N. L. c n l -C.N.L. c n l -CNL c n l -CNMs c n m's -CNN c n n -CNO c n o -CNPC c n p c -CNP c n p -cnr c n r -CNR c n r -CNRMA c n r m a -CNRS c n r s -CNSA c n s a -CNs c n's -CNS c n s -CNSS c n s s -CNSW c n s w -CNTA c n t a -CNT c n t -CNTE c n t e -CNTI c n t i -CNTK c n t k -CNTN c n t n -CNTs c n t's -CNTS c n t s -CNTV c n t v -CNU c n u -Cnut's c n u t's -CNV c n v -CNVs c n v's -CNW c n w -CNWS c n w s -CNZ c n z -COA c o a -C&O c and o -C. O. c o -C.O. c o -Co. company -C.O.D. c o d -Col. colonel -C.O.M.L. c o m l -CPAC c p a c -CPA c p a -CPA's c p a's -CPB c p b -CPBL c p b l -C&P c and p -CPC c p c -cp c p -C. P. c p -C.P. c p -CP c p -CPC's c p c's -CPCs c p c's -CPCS c p c s -CPD c p d -CPDM c p d m -CPD's c p d's -CPEB c p e b -CPEC c p e c -C.P.E. c p e -CPE c p e -CPEO c p e o -CPF c p f -CPFO c p f o -CPG c p g -CPHC c p h c -CPH c p h -CPI c p i -CPIFL c p i f l -CPIM c p i m -CPI's c p i's -CPJ c p j -CPL c p l -CPLP c p l p -CPM c p m -CPN c p n -CPNI c p n i -cpo c p o -C.P.O. c p o -CPO c p o -CPOE c p o e -CPPA c p p a -CPPCC c p p c c -CPP c p p -CPPE c p p e -CPPIB c p p i b -CPPM c p p m -CPQ c p q -CPR c p r -CPRS c p r s -CPSA c p s a -CPSC c p s c -CPS c p s -CPSF c p s f -CPSK c p s k -CPSL c p s l -CPSU c p s u -CPTA c p t a -CPT c p t -CPTM c p t m -CPUC c p u c -CPU c p u -CPUID c p u i d -CPUSA c p u s a -CPUs c p u's -CPUT c p u t -CPVA c p v a -CPV c p v -CPW c p w -CQAC c q a c -CQBR c q b r -CQC c q c -cq c q -CQ c q -CQD c q d -CQDs c q d's -CQM c q m -CQO c q o -CQU c q u -C. R. A. c r a -CRA c r a -C.R.A.Z.Y. c r a z y -CRBC c r b c -CRC c r c -cr c r -C. R. c r -C.R. c r -CR c r -Cre c r e -CRE c r e -CRF c r f -CRG c r g -CRHK c r h k -CRH's c r h's -CRHS c r h s -CRJ c r j -crk c r k -Crkva c r k v a -crkve c r k v e -CRL c r l -CRLs c r l's -crm c r m -CRM c r m -CRNA c r n a -CRN c r n -Crne c r n e -Crni c r n i -Crno c r n o -CRP c r p -CRPF c r p f -CRRF c r r f -CRs c r's -CRS c r s -CRSP c r s p -CRST c r s t -CRTC c r t c -CRT c r t -CRTC's c r t c's -CRUA c r u a -CRWRC c r w r c -CRW's c r w's -CRX c r x -CSAC c s a c -csa c s a -Csa c s a -C.S.A. c s a -CSA c s a -CSAH c s a h -Csak c s a k -Csaky c s a k y -CSAR c s a r -CSAT c s a t -CSAV c s a v -CSB c s b -C&S c and s -C.S.C. c s c -CSC c s c -CSCD c s c d -CSCE c s c e -CSCR c s c r -cs c s -C.s c's -Cs c's -C. S. c s -C.S. c s -CS c s -CSC's c s c's -CSDA c s d a -CSDB c s d b -CSD c s d -CSDL c s d l -CSDN c s d n -CSDP c s d p -CSD's c s d's -CSDS c s d s -CSE c s e -C&SF c and s f -CSF c s f -CSFL c s f l -CSFSO c s f s o -CSGA c s g a -csg c s g -CSG c s g -CSG's c s g's -CSH c s h -CSHL c s h l -CSIC c s i c -CsI c s i -CSI c s i -CSIDC c s i d c -CSILUS c s i l u s -CSIO c s i o -CSIR c s i r -CSIRO c s i r o -CSis c s i's -CSIs c s i's -CSIS c s i s -CSIU c s i u -CSKA c s k a -CSKA's c s k a's -CSK c s k -CSK's c s k's -CSL c s l -CSLI c s l i -CSM c s m -CSNB c s n b -CSNBX c s n b x -CSN c s n -CSN's c s n's -CSOB c s o b -CSO c s o -CSO's c s o's -CSOs c s o's -cspA c s p a -csp c s p -CSP c s p -CSPH c s p h -CSPI c s p i -CSPRA c s p r a -CSPs c s p's -CSRA c s r a -CSR c s r -CSRS c s r s -CSRT c s r t -CSRTT c s r t t -CSSA c s s a -CSS c s s -CSSD c s s d -CSSE c s s e -CSSL c s s l -CSSNCs c s s n c's -CSSR c s s r -CSSS c s s s -CSST c s s t -CSTB c s t b -CST c s t -CSTF c s t f -CSTI c s t i -CSTS c s t s -CSUB c s u b -CSU c s u -CSU's c s u's -Csuz c s u z -CSV c s v -CSW c s w -CSWF c s w f -CSWIP c s w i p -CSWS c s w s -CSX c s x -CSX's c s x's -CSXT c s x t -C.T.A. c t a -CTA c t a -CTAF c t a f -CTARL c t a r l -CTA's c t a's -CTAs c t a's -CTBT c t b t -CTBTO c t b t o -C&T c and t -CTC c t c -ct c t -C. T. c t -C.T. c t -CT c t -CTD c t d -cte c t e -CTE c t e -CTEQ c t e q -CTF c t f -CTGF c t g f -CTI c t i -CTLA c t l a -CTL c t l -CTLLS c t l l s -CTLs c t l's -CTM c t m -CTN c t n -CTO c t o -CTP c t p -ctr c t r -CTRG c t r g -Ctrip c t r i p -CTRL c t r l -CTRP c t r p -CTR's c t r's -CTS c t s -CTSD c t s d -CTSF c t s f -CTSG c t s g -CTUC c t u c -CTU c t u -CTUG c t u g -CTU's c t u's -CTVA c t v a -ctv c t v -CTV c t v -CTV's c t v's -CTX c t x -CTZ c t z -cu c u -C. U. c u -CU c u -C.U.L. c u l -C. U. S. c u s -C. U. T. c u t -CUW c u w -Cuyp c u y p -CVA c v a -CVAK c v a k -CVARG c v a r g -CVB c v b -C&V c and v -CVC c v c -cvcp c v c p -'cv c v -cv c v -C. V. c v -C.V. c v -CV c v -CVD c v d -CVEs c v e's -CVG c v g -CVI c v i -CVJM c v j m -CVM c v m -C.V.N. c v n -CVN c v n -C.V.O. c v o -CVO c v o -CVODE c v o d e -CVOs c v o's -CVP c v p -CVR c v r -CVs c v's -CVS c v s -CVSNT c v s n t -CVT c v t -CVTs c v t's -CVV c v v -CVVHDF c v v h d f -CVW c v w -CVZ c v z -CWA c w a -CWBI c w b i -CWBL c w b l -CWC c w c -C. W. c w -C.W. c w -CWD c w d -CWDS c w d s -C. W. E. c w e -CWE c w e -Cwej c w e j -Cwele c w e l e -CWF c w f -CWGC c w g c -CWG c w g -CWI c w i -C. W. K. c w k -cwm c w m -CWM c w m -CWO c w o -CWPA c w p a -CWR c w r -cwrt c w r t -CWRU c w r u -CWSAC c w s a c -CW's c w's -CWS c w s -CWTS c w t s -CWUR c w u r -C. W. Y. c w y -CWYFL c w y f l -CXC c x c -CXCL c x c l -CXCR c x c r -C.X. c x -C. Y. c y -C.Y. c y -cyl c y l -Cyn c y n -CYOG c y o g -CyP c y p -CYP c y p -Cyrl c y r l -Cys c y's -CYS c y s -CYSK c y s k -CYSY c y s y -czci c z c i -cz c z -C.Z. c z -CZ c z -CZE c z e -CZM c z m -CZW c z w -czy c z y -DAAD d a a d -Daai d a a i -D. A. d a -D.A. d a -D&AD d and a d -D. A. H. d a h -D.A.M. d a m -D.A.N.C.E. dance -D. A. T. d a t -Dav d a v -D.A.V. d a v -DAV d a v -DAV's d a v's -dBa d b a -DBA d b a -DBC d b c -DBCS d b c s -db d b -D. B. d b -D.B. d b -DB d b -DBE d b e -DBI d b i -DBL d b l -DBLE d b l e -DBLP d b l p -DBM d b m -DBMS d b m s -DBR d b r -DB's d b's -D. B. S. d b s -DBS d b s -DBU d b u -DBYC d b y c -DBZ d b z -DCA d c a -DCAF d c a f -DCAM d c a m -DCB d c b -DCCC d c c c -DCCCD d c c c d -DCC d c c -DCCG d c c g -DCCs d c c's -D&C d and c -dc d c -D. C. d c -D.C. d c -DC d c -DCE d c e -DCFC d c f c -DCF d c f -DCG d c g -DCH d c h -DCI d c i -DCK d c k -D.C.L. d c l -DCL d c l -DCMA d c m a -DCM d c m -DCMF d c m f -DCMI d c m i -DCMS d c m s -DCO d c o -DCom d c o m -DCOM d c o m -DCP d c p -DCR d c r -D.C.'s d c's -DC's d c's -DCs d c's -DCS d c s -DCSD d c s d -DCSO d c s o -DCSPER d c s p e r -DCSS d c s s -DCTA d c t a -DCT d c t -DCU d c u -DCUO d c u o -DCUs d c u's -DDA d d a -DDB d d b -D.D.C. d d c -DDC d d c -D&D d and d -D. D. d d -D.D. d d -DDF d d f -DDG d d g -DDHH d d h h -DDi d d i -DDI d d i -DDK d d k -DDLJ d d l j -DDM d d m -DDMS d d m s -DDN d d n -DDNOS d d n o s -Ddoc d d o c -DDO d d o -DDP d d p -DDR d d r -DDRMAX d d r m a x -DDSB d d s b -D.D.S. d d s -DDS d d s -DDT d d t -DDTV d d t v -Ddu d d u -DDWFTTW d d w f t t w -DDX d d x -D.E.A.F. d e a f -Deah d e a h -DEA's d e a's -DECC d e c c -DEC d e c -DECS d e c s -DEDD d e d d -D. E. d e -D.E. d e -deg d e g -D. E. G. d e g -DEG d e g -DEH d e h -DEHP d e h p -dei d e i -Dei d e i -DeI d e i -DEI d e i -Deijm d e i j m -Deip d e i p -D. E. J. d e j -D.E.R. d e r -dez d e z -Dez d e z -Dfa d f a -DFA d f a -DFB d f b -D.F.C. d f c -DFC d f c -DFCs d f c's -D. F. d f -D.F. d f -DFD's d f d's -DfE d f e -D.F.E. d f e -DFE d f e -DfES d f e s -DFF d f f -DFG d f g -DFJ d f j -DFL d f l -DFM d f m -DFOA d f o a -DFO d f o -DFP d f p -DFPs d f p's -DFRC d f r c -DFR d f r -DFs d f's -DFS d f s -DFT d f t -DFW d f w -dfx d f x -DFX d f x -DGAC d g a c -DGA d g a -DGALS d g a l s -DGAP d g a p -DGB d g b -DGCA d g c a -DGC d g c -DGCR d g c r -D&G d and g -D. G. d g -D.G. d g -D. G. E. d g e -DGE d g e -DGERT d g e r t -DGF d g f -DGFI d g f i -DGH d g h -DGK d g k -D. G. L. R. d g l r -DGM d g m -DGMO d g m o -DGP d g p -DGPS d g p s -DGR d g r -Dha d h a -DHA d h a -DHB d h b -DHBs d h b's -DHCP d h c p -D&H d and h -dh d h -D. H. d h -D.H. d h -DH d h -DHEA d h e a -d'HEC d h e c -dhe d h e -DHE d h e -Dheku d h e k u -DHFS d h f s -DHHC d h h c -DHH d h h -DHL d h l -DHMO d h m o -DHNC d h n c -D.H.N. d h n -DHNS d h n s -Dhod d h o d -dhol d h o l -Dhol d h o l -Dhoo d h o o -Dhor d h o r -Dhou d h o u -DHP d h p -DHPH d h p h -DHQ d h q -dhr d h r -D.H.R. d h r -DHRS d h r s -DHS d h s -DHSs d h s's -DHSS d h s s -DHT d h t -DHV d h v -DHW d h w -DHX d h x -D.I. d i -DIFC d i f c -DISD d i s d -DIW d i w -DIX d i x -diy d i y -DiY d i y -D.I.Y. d i y -DIY d i y -Diyn d i y n -DIYs d i y's -D. J. A. d j a -Djam d j a m -dj d j -D. J. d j -D.J. d j -DJ d j -DJ'ed d j e d -Djem d j e m -D.J.H. d j h -Dji d j i -DJI d j i -D.J.N. d j n -Djo d j o -D'Jok d j o k -djr d j r -DJR d j r -D.J.s d j's -DJ's d j's -DJs d j's -D. J. S. d j s -D.J.T. d j t -DjVu d j v u -DJVU d j v u -DjVus d j v u's -D. J. Y. d j y -DKC d k c -D. K. d k -D.K. d k -DKI d k i -DKIM d k i m -DKK d k k -DKNY d k n y -DKPP d k p p -D. K. R. d k r -DKW d k w -dla d l a -DLA d l a -DLC d l c -DLD d l d -dl d l -D. L. d l -D.L. d l -DL d l -DLE d l e -D.L.F. d l f -DLF d l f -DLFN d l f n -DLG d l g -D. L. H. d l h -dlia d l i a -DLI d l i -DLJ d l j -DLJ's d l j's -DLK d l k -DLL d l l -DL&LR d l and l r -DLL's d l l's -DLLs d l l's -DLM d l m -DLMPST d l m p s t -dlo d l o -DLP d l p -DLPFC d l p f c -DLP's d l p's -DLR d l r -DLS d l s -DLSS d l s s -DLSU d l s u -DLSU's d l s u's -DLT d l t -DL&W d l and w -DLZ d l z -DMAA d m a a -DMA d m a -DMB d m b -DMBT d m b t -DMCA d m c a -DMCC d m c c -DMC d m c -DMCM d m c m -D.M.C.'s d m c's -D&M d and m -DMD d m d -DMDK d m d k -D. M. d m -D.M. d m -DM d m -DMDS d m d s -DMed d m e d -DM&E d m and e -DME d m e -DMF d m f -DMG d m g -DMGT d m g t -DMHS d m h s -DMI d m i -DMK d m k -DML d m l -DMN d m n -DMO d m o -DMOFD d m o f d -DMOZ d m o z -DMP d m p -DMRC d m r c -DMR d m r -DMRG d m r g -DMs d m's -DMS d m s -DMSII d m s i i -DMT d m t -DMTF d m t f -DMU d m u -DMUs d m u's -DMV d m v -DMX d m x -DMZ d m z -Dna d n a -DnA d n a -DNA d n a -DNADTC d n a d t c -DNAITV d n a i t v -DNAJA d n a j a -DNAJC d n a j c -DnaJ d n a j -DNAN d n a n -DNB d n b -DNBY d n b y -DNC d n c -DNCG d n c g -DND d n d -D. N. d n -D.N. d n -Dnepr d n e p r -dnes d n e s -Dnes d n e's -DNES d n e s -DNF d n f -DNF's d n f's -DNFs d n f's -DNG d n g -DNJO d n j o -DNKA d n k a -DNK d n k -DNM d n m -DNMT d n m t -DNP d n p -DNQ d n q -DNR d n r -DNSBLs d n s b l's -dns d n s -D.N.S. d n s -DNS d n s -DNSS d n s s -DNT d n t -DNU d n u -DNVP d n v p -D.O.A. d o a -D.O.A.'s d o a's -DOAS d o a s -D.O.B. d o b -D.O.C. d o c -DOCG d o c g -dod d o d -Dod d o d -DoD d o d -DOD d o d -D. O. d o -D.O. d o -DOD's d o d's -D.O.E. d o e -DOGNY d o g n y -DOHC d o h c -D'oh d o h -DOJ d o j -DOJ's d o j's -dok d o k -Dok d o k -domt d o m t -Domt d o m t -Dop d o p -DOP d o p -DOPR d o p r -DOSAAF d o s a a f -DOTC d o t c -dotCMS d o t c m s -DOTD d o t d -DOTP d o t p -DotSVN d o t s v n -Douw d o u w -DOW d o w -DOXO d o x o -dozd d o z d -d'OZ d o z -Dozhd d o z h d -DPAA's d p a a's -DPA d p a -DPB d p b -DPD d p d -dp d p -D. P. d p -D.P. d p -DP d p -DPG d p g -DPJ d p j -DPMA d p m a -DPM d p m -DPN d p n -DPNM d p n m -DPO d p o -dpon d p o n -DPP d p p -DPP's d p p's -DPPX d p p x -DPR d p r -DPRK d p r k -DPRK's d p r k's -DProf d p r o f -DPRP d p r p -DPRT d p r t -DPs d p's -DPS d p s -DPSS d p s s -DPSSL d p s s l -DPT d p t -DPW d p w -DPW's d p w's -DPX d p x -DPYS d p y s -D.Q. d q -DQOY d q o y -DQV d q v -DRB d r b -DRBG d r b g -DRB's d r b's -DRCA d r c a -drc d r c -DRC d r c -DRDA d r d a -DRDC d r d c -DRD d r d -Dr. doctor -D. R. d r -D.R. d r -DRG d r g -dri d r i -Dri d r i -DRI d r i -DRIs d r i's -DRITTES d r i t t e s -Driu d r i u -Driv d r i v -DRJTBC d r j t b c -DRK d r k -DRL d r l -DRLR d r l r -DRMC d r m c -D.R.M. d r m -DRM d r m -Drnis d r n i's -Dro d r o -DRO d r o -DRP d r p -Drs. doctors -DR's d r's -DRS d r s -Drska d r s k a -DRT d r t -druj d r u j -DSA d s a -DsbA d s b a -DS&BB d s and b b -DSB d s b -DSBL d s b l -D.S.C. d s c -DSC d s c -D.S.C.H. d s c h -DSCM d s c m -DSCR d s c r -DSCS d s c s -DSDB d s d b -DSD d s d -DSDM d s d m -dsDNA d s d n a -DSDP d s d p -ds d s -Ds d's -D. S. d s -D.S. d s -DS d s -DSDS d s d s -DSG d s g -DSGi d s g i -DSIC d s i c -dsi d s i -DSi d s i -DSI d s i -DSIF d s i f -DSIR d s i r -DSJ d s j -dsl d s l -D. S. L. d s l -DSL d s l -DSLR d s l r -DSMB d s m b -D.S.M. d s m -DSM d s m -DSMs d s m's -dsn d s n -D&SNGRR d and s n g r r -DSNP d s n p -D.S.O. d s o -DSO d s o -DSPA d s p a -DSP d s p -DSR d s r -DS's d s's -DSS d s s -DST d s t -dsu' d s u -DSU d s u -DSV d s v -DSW d s w -DSX d s x -DSZG d s z g -D.T.A. d t a -DTA d t a -DTC d t c -DTC's d t c's -DTCs d t c's -DTDC d t d c -DTD d t d -DTDs d t d's -D. T. d t -D.T. d t -DT&E d t and e -DTE d t e -DTEK d t e k -DTES d t e s -DTG d t g -DTH d t h -DTIC d t i c -DT&I d t and i -DTI d t i -DTLA d t l a -dtl d t l -DTL d t l -DTLLS d t l l s -DTLS d t l s -DTM d t m -DTO d t o -DTPA d t p a -DTPC d t p c -DTRA d t r a -DTR d t r -DTRS d t r s -DTs d t's -DTS d t s -DTT d t t -D.T.U. d t u -DTU d t u -DTV d t v -dty d t y -D.U. d u -dva d v a -Dva d v a -DVA d v a -DVB d v b -DVBE d v b e -DVBIC d v b i c -DVC d v c -DVCs d v c's -DVCS d v c s -dvd d v d -DVD d v d -DVD's d v d's -DVDs d v d's -dv d v -D. V. d v -D.V. d v -DV d v -dve d v e -dvfb d v f b -DVFS d v f s -DVGS d v g s -DVHS d v h s -dvi d v i -DVI d v i -dvije d v i j e -Dvin d v i n -Dvir d v i r -DVLA d v l a -DVLA's d v l a's -DVL d v l -DVM d v m -DVP d v p -DVR d v r -DVRJRBC d v r j r b c -DVR's d v r's -DVSC d v s c -DVS d v s -DVT d v t -DVV d v v -DVVT d v v t -DVWK d v w k -Dwa d w a -DWA d w a -D&W d and w -D. W. d w -D.W. d w -Dwedw d w e d w -DWET d w e t -DWF d w f -DWG d w g -D.W.H. d w h -Dwi d w i -DWI d w i -DWM d w m -DWN d w n -DWNU d w n u -DWP d w p -dwr d w r -DWR d w r -DWRFC d w r f c -DWS d w s -DWT d w t -DWTS d w t s -dwur d w u r -dxa d x a -DXA d x a -dx d x -D.X. d x -DX d x -DXED d x e d -DXers d x e r's -DXII d x i i -DXK d x k -DXR d x r -DXZ d x z -Dydd d y d d -dy d y -Dy d y -D. Y. d y -DY d y -DYFI d y f i -DYIS d y i s -DYNC d y n c -dypl d y p l -dyr d y r -DYSP d y s p -DZBB d z b b -DZB d z b -dz d z -DZEC d z e c -DZEM d z e m -dzis d z i s -DZNE d z n e -Dzog d z o g -Dzor d z o r -DZRH d z r h -DZRH's d z r h's -DZS d z s -Dzus d z u's -DZXL d z x l -DZZ d z z -EAAB e a a b -EAA e a a -EAAP e a a p -E. A. C. e a c -EAC e a c -EACEF e a c e f -EACS e a c s -EAD e a d -E. A. e a -E.A. e a -EAF e a f -EAGE e a g e -E.A.H. e a h -EAH e a h -EAI e a i -EAIE e a i e -E. A. J. e a j -EAMs e a m's -EAP e a p -E.A.R.L. e a r l -E.A.R.T.H. e a r t h -EASA e a s a -EASB e a s b -eas e a s -Eas e a's -EA's e a's -EAS e a s -Eav e a v -EAX e a x -E. B. e b -E.B. e b -EBL e b l -Ebn e b n -EBNF e b n f -EBOV e b o v -E&BR e and b r -EBR e b r -Ebru e b r u -EBS e b s -EBSL e b s l -EBT e b t -EBU e b u -EBV e b v -E.B.W. e b w -EBWs e b w's -EBZR e b z r -ECAC e c a c -ECA e c a -ECAR e c a r -ECB e c b -ECBJ e c b j -ECBL e c b l -ECCA e c c a -ECCC e c c c -ecc e c c -ECC e c c -ECCI e c c i -Eccl e c c l -ECCRFA e c c r f a -ECCW e c c w -ECD e c d -ec e c -Ec e c -E. C. e c -E.C. e c -EC e c -ece e c e -Ece e c e -ECE e c e -Ecem e c e m -ECFA e c f a -ECF e c f -ECFR e c f r -ECFU e c f u -ecg e c g -ECG e c g -ECH e c h -ECHL e c h l -ECHR e c h r -ECI e c i -ECJ e c j -ECLAC e c l a c -ECLA e c l a -ECLC e c l c -ECL e c l -ECLI e c l i -ECLSS e c l s s -ecma e c m a -ECMA e c m a -ECMC e c m c -ECMDB e c m d b -E.C.M. e c m -ECM e c m -ECMI e c m i -ECML e c m l -ECMLRUS e c m l r u s -ECMWF e c m w f -ECN e c n -ECNP e c n p -ECNs e c n's -ECNS e c n s -ECNZ e c n z -ECP&DA's e c p and d a's -ECP e c p -ECPR e c p r -ECQ e c q -ECR e c r -eCRM e c r m -ECRR e c r r -ECR's e c r's -ECSA e c s a -EC's e c's -E. C. S. e c s -E.C.S. e c s -ECS e c s -ect e c t -E. C. T. e c t -ECT e c t -ECTLO e c t l o -ECTN e c t n -ECTS e c t s -ECV e c v -ECVs e c v's -ECWA e c w a -ECW e c w -edb e d b -EDB e d b -EDC e d c -E. D. e d -E.D. e d -EDF e d f -Edh e d h -EDH e d h -edhe e d h e -EDHF e d h f -EDIB e d i b -EDI e d i -EDK e d k -EDL e d l -EDMA e d m a -EDM e d m -EDMs e d m's -EDMW e d m w -Edmx e d m x -edn e d n -Edn e d n -EDN e d n -EDP e d p -EDQH e d q h -E.D.R. e d r -EDRP e d r p -EDSA e d s a -EDSC e d s c -eds e d s -Eds e d's -E. D. S. e d s -EDS e d s -EDSP e d s p -EDTA e d t a -EDT e d t -EDVAC e d v a c -EDWDO e d w d o -Edw e d w -EDXRD e d x r d -EEA e e a -EEAF e e a f -EEAS e e a s -EEBC e e b c -Eeb e e b -EEC e e c -EECS e e c s -E. E. e e -E.E. e e -Eef e e f -EEF e e f -Eega e e g a -EEI e e i -EEI's e e i's -EEJF e e j f -EELC e e l c -eene e e n e -EEOC e e o c -EEPCO e e p c o -eep e e p -EEP e e p -EERC e e r c -EERI e e r i -Ees e e's -EES e e s -EEST e e s t -EEUU e e u u -eeuw e e u w -Eeuw e e u w -EEZs e e z's -EFA e f a -EFAS e f a s -EFCC e f c c -efc e f c -EFC e f c -EFCJ e f c j -EFD e f d -ef e f -Ef e f -E. F. e f -E.F. e f -EF e f -E. F. J. e f j -E. F. K. e f k -EFL e f l -EFM e f m -EFNB e f n b -EFPA e f p a -EFP e f p -EFQUEL e f q u e l -EFR e f r -EFRU e f r u -EFSA e f s a -eFS e f s -Efs e f's -EFSET e f s e t -EFTPOS e f t p o s -EFUA e f u a -Efu e f u -EFV e f v -EFVR e f v r -EFVS e f v s -E. F. W. e f w -EFX e f x -EFY e f y -E. G. A. e g a -EGA e g a -Egba e g b a -EGBA e g b a -EGBT e g b t -EGC e g c -EGD e g d -EGF e g f -egfl e g f l -EGFL e g f l -e.g. for example -e. g. for example -EGFR e g f r -EG&G e g and g -E. G. H. e g h -Egi e g i -EGL e g l -EGM e g m -E&GR e and g r -EGR e g r -EGREM e g r e m -EGSC e g s c -EGX e g x -egy e g y -EGY e g y -Egyl e g y l -EHAAT e h a a t -EHAs e h a's -EHC e h c -EHCI e h c i -EHD e h d -E. H. e h -E.H. e h -ehf e h f -EHF e h f -E. H. M. e h m -EHP e h p -EHRC e h r c -EHR e h r -EHS e h s -EHSH e h s h -Ehttp e h t t p -EIA e i a -EIC e i c -EiCs e i c's -EIC's e i c's -E. I. e i -E.I. e i -EIES e i e s -eIF e i f -EIF e i f -EIFF e i f f -EIF's e i f's -EIT e i t -EITI e i t i -Eitr e i t r -EITs e i t's -EIU e i u -E. J. A. e j a -EJB e j b -EJBs e j b's -EJC e j c -ej e j -E. J. e j -E.J. e j -EJ e j -E. J. H. e j h -E.J.H. e j h -EJH e j h -EJHL e j h l -EJMA e j m a -E. J. M. e j m -EJML e j m l -E. J. R. e j r -E.J.S. e j s -EJSM e j s m -EJV e j v -EKB e k b -EKBO e k b o -EKCO's e k c o's -EKD e k d -E. K. e k -E.K. e k -EKF e k f -EKG e k g -eki e k i -EKIZ e k i z -EKL e k l -EKLR e k l r -Ekma e k m a -EKNU e k n u -Ekow e k o w -eks e k s -Eks e k's -EKS e k s -E. K. U. e k u -EKU e k u -E. L. C. e l c -E. L. e l -E.L. e l -ELH e l h -ELTs e l t's -ELUs e l u's -ELV e l v -EMA e m a -EMAS e m a s -Embd e m b d -EMB e m b -eMC e m c -EMC e m c -EMD e m d -EMD's e m d's -EMDs e m d's -EMDS e m d s -Emea e m e a -EMEA e m e a -E&M e and m -E. M. e m -E.M. e m -EMF e m f -Emge e m g e -EMG e m g -EMLL e m l l -E.M.M. e m m -EMNLP e m n l p -EMP e m p -emra e m r a -EMR e m r -EMSC e m s c -E.M.S. e m s -EMTE e m t e -EMT e m t -EMV e m v -E&NA e and n a -Enas e n a's -ENAS e n a s -EnBW e n b w -ENC e n c -EncFS e n c f s -Encyc e n c y c -E.N.D. e n d -ENEC e n e c -E. N. e n -E.N. e n -Enes e n e's -engl e n g l -Engl e n g l -ENGM e n g m -Engr e n g r -Eni e n i -ENI e n i -enn e n n -Enn e n n -ENP e n p -ENR e n r -ens e n s -Ens e n's -ENS e n s -Enso e n s o -ENSO e n s o -ENTJs e n t j's -ENTP e n t p -ENTV e n t v -EOC e o c -EOC's e o c's -EoD e o d -EOD e o d -E. O. e o -E.O. e o -EOFFTV e o f f t v -EOG e o g -Eois e o i's -EOKA e o k a -eok e o k -Eole e o l e -Eol e o l -EOL e o l -Eolss e o l s's -Eom e o m -EOOW e o o w -eop e o p -eoptta e o p t t a -Eora e o r a -EOR e o r -Eorl e o r l -Eors e o r's -EOSHD e o s h d -EOTC e o t c -EOTDC e o t d c -EOU e o u -E.O.W. e o w -E&P e and p -Epe e p e -E. P. E. e p e -EPEG e p e g -ep e p -Ep e p -E. P. e p -E.P. e p -EP e p -EPF e p f -EPFL e p f l -EPG e p g -EPHAR e p h a r -EPHB e p h b -Eph e p h -EPH e p h -Ephs e p h's -EPIA e p i a -epi e p i -Epi e p i -EPI e p i -E.P.J. e p j -EPL e p l -EPLF e p l f -EPM e p m -EPOC e p o c -ePO e p o -EPO e p o -epos' e p o's -epos e p o s -Epos e p o's -EPRDF e p r d f -EPR e p r -EPRI e p r i -EPRO e p r o -EPSC e p s c -E.P.s e p's -EPT e p t -EPV e p v -EPZA e p z a -EPZ e p z -EQAO e q a o -eq e q -Eq e q -EQ e q -EQG e q g -EQN e q n -EQP e q p -EQS e q s -EQT e q t -E.R.A. e r a -ERAF e r a f -ERAU e r a u -ERCB e r c b -ERC e r c -ERCES e r c e s -ERCIM e r c i m -ERCS e r c s -E. R. D. e r d -E. R. e r -E.R. e r -ERF e r f -ERH e r h -ERJs e r j's -ERK e r k -ERP e r p -ERPM e r p m -ERPMRP e r p m r p -ERRC e r r c -E. R. R. e r r -E.R.R. e r r -ERSAR e r s a r -ERT e r t -Eru e r u -ERU e r u -ERUUF e r u u f -Eruv e r u v -Erv e r v -ERW e r w -ES3 e s three -Esa e s a -E.S.A. e s a -ESA e s a -Esam e s a m -Esa's e s a's -ESA's e s a's -Esat e s a t -ESB e s b -ESC e s c -ESCHL e s c h l -ESCs e s c's -Esd e s d -ESD e s d -ESDI e s d i -E.S.E. e s e -E. S. e s -E.S. e s -ESF e s f -ESFG e s f g -E.S.G. e s g -ESG e s g -ESGR e s g r -esi e s i -ESI e s i -ESL e s l -ESM e s m -ESMLC e s m l c -ESMT e s m t -ESNAGI e s n a g i -ESN e s n -ESPA e s p a -ESPC e s p c -ESPD e s p d -ESP e s p -espn e s p n -ESPN e s p n -ESPNhttp e s p n h t t p -ESPN's e s p n's -ESPNU e s p n u -ESPNW's e s p n w's -esq e s q -Esq e s q -Esq. esquire -Esraa e s r a a -Esra e s r a -ESRB e s r b -ESRC e s r c -Esref e s r e f -ESR e s r -ESRF e s r f -Esri e s r i -ESRI e s r i -ESSR e s s r -estd e s t d -Estd e s t d -EST e s t -ESTP e s t p -esu e s u -ESU e s u -ESU's e s u's -Esva e s v a -ESV e s v -ESWAT e s w a t -ESW e s w -Etad e t a d -ETA e t a -ETAF e t a f -ETA's e t a's -ETASU e t a s u -ETB e t b -ETBs e t b's -E.T.C. e t c -ETCO's e t c o's -ETCS e t c s -ETCSL e t c s l -ETD e t d -E. T. e t -E.T. e t -ETF e t f -ETFs e t f's -ETFS e t f s -Et'hem e t h e m -ETH e t h -Eti e t i -ETI e t i -ETIM e t i m -ETIM's e t i m's -etj e t j -ETJ e t j -ETL e t l -ETNZ e t n z -Eto e t o -ETO e t o -ETRM e t r m -ETRS e t r s -ETSEIB e t s e i b -ets e t s -Ets e t's -ET's e t's -ETs e t's -ETS e t s -ett e t t -Ett e t t -ETT e t t -Ettre e t t r e -Etts e t t's -ETU e t u -ETV e t v -Etz e t z -EUA e u a -EUB e u b -EUBs e u b's -EUBS e u b s -EUCAP e u c a p -EUCE e u c e -EUC e u c -EUCOM's e u c o m's -EUDEC e u d e c -EUD e u d -E. U. e u -E.U. e u -EU e u -eup e u p -EUP e u p -Eurwg e u r w g -EUSA e u s a -Euse e u s e -EU's e u's -EUS e u s -EUSEW e u s e w -Eusi e u s i -EUV e u v -EUX e u x -EVAAP e v a a p -EvaGT e v a g t -EVDC e v d c -EVD e v d -EVDO e v d o -E. V. e v -E.V. e v -EVEX e v e x -EVIT e v i t -evl e v l -EVL e v l -EVM e v m -Evna e v n a -EVN e v n -EVNS e v n s -evnt e v n t -E.V.O. e v o -E.V.O.L. e v o l -EVP e v p -EVR e v r -EVs e v's -EVS e v s -evv e v v -EVV e v v -Ewa's e w a's -EWD e w d -EWEB e w e b -E. W. e w -E.W. e w -EWF e w f -EWF's e w f's -Ewha e w h a -EWH e w h -E.W.K. e w k -EWLA e w l a -EWL e w l -EWO e w o -EWOs e w o's -EWP e w p -EW's e w's -EWS e w s -EWTN e w t n -Ewu e w u -EWU e w u -excl e x c l -exd e x d -E.X. e x -exhb e x h b -exh e x h -EXI e x i -EXIF e x i f -EXIN e x i n -EXL e x l -EXLM e x l m -E. X. M. e x m -Exptl e x p t l -EXR e x r -exsul e x s u l -EXT e x t -EYA e y a -EYCN e y c n -EYD e y d -E&Y e and y -E. Y. e y -EY e y -Eyk e y k -eyu e y u -Ezaa e z a a -ez e z -Ez e z -EZ e z -Ezh e z h -EZH e z h -EZO e z o -EZR e z r -EZTV e z t v -Ezu e z u -EZW e z w -Ezy e z y -Faaa f a a a -faa f a a -Faa f a a -FAA f a a -faama f a a m a -FAANP f a a n p -FabH f a b h -FABM f a b m -FabR f a b r -F.A.B.'s f a b's -F.A.C.E. f a c e -FACR f a c r -F.A.C.S. f a c s -FADD f a d d -Fadl f a d l -FADS f a d s -FAEM f a e m -fa f a -Fa f a -F. A. f a -F.A. f a -FA f a -Faf f a f -FAFG f a f g -Fafhrd f a f h r d -FAFL f a f l -F. A. G. f a g -F.A.H. f a h -fai f a i -Fai f a i -FAI f a i -FAIM f a i m -FAIP f a i p -FAIPs f a i p's -Faiq f a i q -fajn f a j n -FAK f a k -Fal f a l -FAL f a l -F.A.M.E. f a m e -F.A.M. f a m -FAQ f a q -FARC's f a r c's -FARDC f a r d c -F.A.R. f a r -farw f a r w -FASA f a s a -FASB f a s b -fasc f a s c -Fasc f a s c -fas f a s -Fas f a's -FAs f a's -F.A.S. f a s -FAS f a s -FASG f a s g -FasL f a s l -FASRE f a s r e -FATF f a t f -FAUP f a u p -FAVC f a v c -FBA f b a -FBD f b d -FBFA f b f a -F. B. f b -F.B. f b -FB f b -F.B.G.s f b g's -F.B.I. f b i -FBI f b i -FBI's f b i's -FBK f b k -FBL f b l -FBMW f b m w -FBN f b n -FBO f b o -FBOs f b o's -FBPA f b p a -FBR f b r -FBS f b s -FBSN f b s n -FBSU f b s u -FBT f b t -FCA f c a -fcb f c b -FCB f c b -FCBF f c b f -F.C.B.I. f c b i -FCBL f c b l -FCBs f c b's -F.C.C. f c c -FCC f c c -FCD f c d -F&C f and c -fc f c -F. C. f c -F.C. f c -FCF f c f -FCGR f c g r -F. C. H. f c h -F.C.H.L. f c h l -FCIAC f c i a c -FCIC f c i c -FCI f c i -FCIP f c i p -FCK f c k -FCL f c l -FCNM f c n m -FCNZ f c n z -FCO f c o -FCP f c p -F.C.P.R.E.M.I.X. f c p r e m i x -FCPS f c p s -FCRLA f c r l a -F.C.'s f c's -FC's f c's -FCS f c s -FCT f c t -FCU f c u -FCUL f c u l -FCV f c v -F. C. W. f c w -FCW f c w -FCW's f c w's -FDA f d a -FDCC f d c c -FD&C f d and c -FDCPA f d c p a -FDCPAs f d c p a's -FDD f d d -FDDI f d d i -FDE f d e -F. D. f d -F.D. f d -FDFL f d f l -FDGB f d g b -FDG f d g -FDICs f d i c's -FdI f d i -FDI f d i -FDIO f d i o -FDJ f d j -FDL f d l -FDLT f d l t -FDM f d m -FDMNES f d m n e s -FDNY f d n y -FDP f d p -FDP's f d p's -FDR f d r -FDU f d u -F. E. f e -F.E. f e -FEFK f e f k -FEFSI f e f s i -FEFY f e f y -FEG f e g -FEGs f e g's -FEP f e p -F.E.R.S. f e r s -Fes f e's -FES f e s -FFA f f a -FFAK f f a k -ffc f f c -FFC f f c -FFC's f f c's -FFDO f f d o -ff f f -F. F. f f -F.F. f f -FF f f -FFF f f f -FFG f f g -FFH f f h -FFI f f i -FFK f f k -FFL f f l -FFL's f f l's -FFME f f m e -ffm f f m -FFOM f f o m -FFP f f p -FFPIR f f p i r -FFR f f r -FFSA f f s a -FF's f f's -FFs f f's -FFS f f s -FFU f f u -FFV f f v -FFWD f f w d -FGCU f g c u -FGFA f g f a -FGF f g f -F. G. f g -F.G. f g -FGFR f g f r -FGID f g i d -fgk f g k -FGL f g l -FGM f g m -FGR f g r -FGs f g's -FGS f g s -FGU f g u -FGV f g v -F. H. A. f h a -FHA f h a -FHAR f h a r -F. H. C. f h c -FHFA f h f a -F. H. f h -F.H. f h -FHI's f h i's -FHL f h l -fhm f h m -FHM f h m -FHM's f h m's -FHQ f h q -FHSAA f h s a a -FHS f h s -FHWA f h w a -F. H. W. f h w -FIAC f i a c -fiadh f i a d h -fia f i a -FIA f i a -FIAPO f i a p o -FIA's f i a's -FIAS f i a s -FIBCO f i b c o -F. I. B. f i b -FiBL f i b l -FIBT f i b t -FIC f i c -Fi'd f i d -FIDH f i d h -F.I f -F&I f and i -F. I. f i -F.I. f i -FIFTA f i f t a -FIGC f i g c -Figl f i g l -FIH f i h -FIH's f i h's -fija f i j a -FIJL f i j l -FIK f i k -F.I.M. f i m -FIM f i m -FIMI f i m i -Fio f i o -FiO f i o -FIO f i o -F.I.R. f i r -F.I.T.T. f i t t -FIU f i u -FIVB f i v b -F. J. A. f j a -FJE f j e -F. J. f j -F.J. f j -F.J.G. f j g -FJK f j k -F. J. M. f j m -FKA f k a -FKBP f k b p -F. K. f k -F.K. f k -FKK f k k -FKL's f k l's -FKS f k s -FKY f k y -Fla f l a -FLB f l b -FLCL f l c l -FLCS f l c s -FLD f l d -FLDS f l d s -FLEC f l e c -FLE f l e -Fles f l e's -FLEST f l e s t -FLETC f l e t c -fl f l -F. L. f l -F.L. f l -FL f l -FLH f l h -fli f l i -FLI f l i -FLI's f l i's -FLL f l l -F.L.M. f l m -FLM f l m -FLNB f l n b -FLN f l n -FLP f l p -FLPP f l p p -FLQ f l q -FLRA f l r a -FLR f l r -FLRL f l r l -FLS f l s -FLSW f l s w -FLT f l t -FLTK f l t k -FLTR f l t r -FLTS f l t s -FLV f l v -FLW f l w -flyr f l y r -FMA f m a -FMARS f m a r s -FMC f m c -FMCG f m c g -FMCSA f m c s a -FMCS f m c s -FMF f m f -fm f m -F. M. f m -F.M. f m -FM f m -FMH f m h -FMHS f m h s -FMI f m i -FMJD f m j d -FMLN f m l n -FMM f m m -FMN f m n -FMNJ f m n j -FMNP f m n p -FMPA's f m p a's -FMP f m p -FMQB f m q b -FMR f m r -fMRI f m r i -FMRP f m r p -FMRU f m r u -FM's f m's -FMs f m's -FMS f m s -FMSF's f m s f's -FMSO f m s o -FMV f m v -FMW f m w -FMX f m x -FMY f m y -FNAC f n a c -F. N. A. f n a -FNA f n a -FNB f n b -FNC f n c -F. N. D. f n d -FNE f n e -F. N. f n -F.N. f n -FNIC f n i c -FNI f n i -FNLA f n l a -FNLC f n l c -FNLC's f n l c's -FNL f n l -FNO f n o -FNP f n p -FNPI f n p i -FNSEA f n s e a -FNU f n u d s a -FOF f o f -F. O. f o -FPA f p a -FPB f p b -FPC f p c -FPCP f p c p -F.P.D. f p d -FPDs f p d's -fp f p -F. P. f p -F.P. f p -FP f p -FPGA f p g a -FPGAs f p g a's -FPI f p i -FPJ f p j -FPK f p k -F. P. L. f p l -FPL f p l -FPMR f p m r -FPM&SA f p m and s a -FPO f p o -FPP f p p -FPPS f p p s -F.P.R. f p r -FPR f p r -FPSC f p s c -fps f p s -FPS f p s -FPSO f p s o -FPSs f p s's -FPTP f p t p -FPU f p u -FQAD f q a d -F.Q. f q -FRA f r a -FRA's f r a's -FRAXA f r a x a -FRB f r b -FRBNF f r b n f -FRCC f r c c -F. R. C. f r c -FRC f r c -FRCNA f r c n a -FRCP f r c p -FRCS f r c s -FRDF f r d f -F.R.D. f r d -fr f r -F. R. f r -F.R. f r -FR f r -FRFS f r f s -FRFT f r f t -FRG f r g -F.R.G.S. f r g s -F.R.H.S. f r h s -F.R.I.B.A. f r i b a -FRMN f r m n -FRMR f r m r -FRMS f r m s -F. R. P. f r p -FRP f r p -FRR f r r -F.R.S.A. f r s a -FRSA f r s a -FRSC f r s c -FRSE f r s e -frs f r s -F. R. S. f r s -F.R.S. f r s -FRS f r s -FRSL f r s l -Fru f r u -FRU f r u -FRV f r v -FRWT f r w t -Frwydr f r w y d r -FSA f s a -FSB f s b -FSC f s c -FSCS f s c s -FSE f s e -fsf f s f -FSF f s f -FSFH f s f h -FSFLA f s f l a -fs f s -F. s f's -Fs f's -F. S. f s -F.S. f s -FS f s -FSFS f s f s -FSG f s g -FSGS f s g s -FSH f s h -FSIC f s i c -FSI f s i -FSIL f s i l -FSK f s k -FSKN f s k n -FSLF f s l f -FSL f s l -FSLN f s l n -FSM f s m -FSM's f s m's -fsn f s n -FSN f s n -FSO f s o -FSP f s p -FSPS f s p s -FSR f s r -FSRU f s r u -FSSB f s s b -FSS f s s -FSSM f s s m -FSSRU f s s r u -FSSs f s s's -FST f s t -FSU f s u -FSU's f s u's -FSV f s v -FTA f t a -FTAs f t a's -F.T.B. f t b -FTC f t c -FTD f t d -FTDI f t d i -FTE f t e -FTF f t f -Ft. Fort -F. T. f t -F.T. f t -FTI f t i -FTII f t i i -FTJ f t j -FTK f t k -FTL f t l -FTM f t m -FTN f t n -FTO f t o -ftp f t p -FTP f t p -FTPI f t p i -FTPL f t p l -FTRA f t r a -FTR f t r -FtsA f t s a -FT's f t's -FTS f t s -FTT f t t -FTTH f t t h -FTUC f t u c -Ftuh f t u h -FTU's f t u's -FTV f t v -F. V. B. f v b -F. V. f v -F.V. f v -FVGM f v g m -FVHS f v h s -FVJC f v j c -FVL f v l -FVP f v p -FVW f v w -FVWM f v w m -FWAA f w a a -FWA f w a -FWCD f w c d -FWD f w d -FWE f w e -F&W f and w -F. W. f w -F.W. f w -FWH f w h -FWI f w i -FWMW f w m w -FWO f w o -fwr f w r -F.W.R. f w r -F. W. S. f w s -F.W.S. f w s -FWS f w s -FWX f w x -FXCM's f x c m's -FXE f x e -FXFL f x f l -fx f x -FX f x -FXI f x i -F.X.R. f x r -FX's f x's -FXS f x s -FXX f x x -FXX's f x x's -FXXT f x x t -Fyb f y b -FYCO f y c o -F.Y. f y -F.Y.I. f y i -FYI f y i -Fyn f y n -FYN f y n -FYP f y p -fyr f y r -F.Y.R. f y r -FYR f y r -FYT f y t -FYU f y u -Fyw f y w -FZCI f z c i -FZD f z d -F.Z. f z -FZG f z g -FZJD f z j d -FZKA f z k a -Gaac g a a c -GAAF g a a f -G.A.A. g a a -G. A. g a -G.A. g a -G.A.R. g a r -GASL g a s l -GATA g a t a -GATV g a t v -GATX g a t x -G. A. W. g a w -GBA g b a -GBAG g b a g -GBASE g b a s e -GBA's g b a's -GBB g b b -GBBI g b b i -GBCA g b c a -GBC g b c -GBCM g b c m -GBD g b d -Gbe g b e -GbE g b e -GBE g b e -G. B. g b -G.B. g b -GBGC g b g c -GBGM g b g m -GBH g b h -GBIB g b i b -GBIF g b i f -GBI g b i -GBK g b k -GBL g b l -GBMA g b m a -G. B. M. g b m -GB&NDR g b and n d r -GBP g b p -GBR g b r -GB's g b's -GBS g b s -GBV g b v -GBX g b x -GBYLA g b y l a -GCAC g c a c -GCAF g c a f -GCA g c a -G. C. B. g c b -GCB g c b -GCC g c c -GCCN g c c n -GCC's g c c's -GCCS g c c s -GCD g c d -G.C.E. g c e -GCEP g c e p -GCF g c f -G&C g and c -G. C. g c -G.C. g c -GCHQ g c h q -GCI g c i -GCIP g c i p -GCIT's g c i t's -GCIV g c i v -GCJ g c j -GCL g c l -GCMC g c m c -G.C.M. g c m -GCM g c m -GCMG g c m g -GCN g c n -GCNT g c n t -GCOEC g c o e c -GCOS g c o s -GCPD g c p d -GCPH g c p h -GCR g c r -GCRIO g c r i o -GCSE g c s e -GCSEs g c s e's -GC&SF g c and s f -GCS g c s -GCSI g c s i -GCU g c u -GCV g c v -GCVO g c v o -GCVS g c v s -GDA g d a -Gdal g d a l -GDAL g d a l -GDAP g d a p -GDB g d b -GDC g d c -GDD g d d -GDDM g d d m -GDDR g d d r -Gde g d e -G. D. F. g d f -GDF g d f -gd g d -G. D. g d -G.D. g d -GD g d -GDI g d i -G.D.L. g d l -GDN g d n -G.D.O.D. g d o d -Gdow g d o w -G.D.P. g d p -GDP g d p -GDPs g d p's -gdr g d r -GDR g d r -GDR's g d r's -GDS g d s -GDST g d s t -GDT g d t -GDV g d v -Gebr g e b r -Gebt g e b t -GEC g e c -Ged g e d -GED g e d -GEF g e f -GEGB g e g b -ge g e -G. E. g e -G.E. g e -GE g e -GEHA g e h a -GEHX g e h x -Gek g e k -G.E.M. g e m -Gen. general -G.E.O. g e o -G. E. P. g e p -geq g e q -Geu g e u -GEU g e u -Gev g e v -GeV g e v -GEV g e v -Gfa g f a -GFA g f a -GF&A g f and a -GFC g f c -GFD g f d -GFDL g f d l -GFE g f e -GFF g f f -G. F. g f -G.F. g f -GFM g f m -GFP g f p -G. F. R. g f r -GFR g f r -GFS g f s -GFSN g f s n -GFSR g f s r -GFT g f t -GFWC g f w c -GFW g f w -GFY g f y -G. G. g g -G.G. g g -G. G. J. g g j -GGL g g l -GGM g g m -GGMRC g g m r c -GGS g g s -G.H.A. g h a -GHB g h b -GHC g h c -GHD g h d -Ghe g h e -G. H. g h -G.H. g h -GHGs g h g's -Ghir g h i r -GHK g h k -GHMC g h m c -G.H.N. g h n -G.H.Q. g h q -GHQ g h q -ghra g h r a -GHR g h r -GH&SA g h and s a -GHSA g h s a -GHSFHA g h s f h a -GHS g h s -GHSR g h s r -GHSU g h s u -GHU g h u -G.H.W. g h w -GICL g i c l -Giei g i e i -GIFV g i f v -G. I. g i -G.I. g i -G.J.B. g j b -G. J. g j -G.J. g j -G. K. g k -G.K. g k -Gla g l a -GLA g l a -GLB g l b -GLBT g l b t -GLBTQ g l b t q -GLC g l c -G&L g and l -G. L. g l -G.L. g l -gli g l i -Gli g l i -GLI g l i -Glis g l i's -GLK g l k -GLL g l l -GLLI g l l i -GLM g l m -glnA g l n a -G.L.O.R.Y. g l o r y -Glos g l o's -GLRS g l r s -GLS g l s -GLT g l t -GLVC g l v c -GLX g l x -GMAC g m a c -gma g m a -GMA g m a -GMAM g m a m -GMA's g m a's -GMAT g m a t -GMB g m b -GmbH g m b h -GMBH g m b h -GMB's g m b's -GMCC g m c c -GMC g m c -GMCL g m c l -GMC's g m c's -GMDSS g m d s s -GME g m e -Gmel g m e l -GMES g m e s -GMFF g m f f -GMF g m f -GMG g m g -gm g m -G. M. g m -G.M. g m -GM g m -GMG's g m g's -gmin g m i n -GMM g m m -GMO g m o -GMOs g m o's -GMPC g m p c -GMPE g m p e -GMP g m p -GMPTE g m p t e -GMR g m r -GMRL g m r l -GM's g m's -GMs g m's -GMS g m s -gmt g m t -GMT g m t -GMTV g m t v -Gmul g m u l -GNAA g n a a -GNA g n a -gnb g n b -GNB g n b -GNCC g n c c -G. N. C. g n c -GNC g n c -G. N. g n -G.N. g n -GNL g n l -GNP&BR g n p and b r -GNPDA g n p d a -gnp g n p -GNP g n p -GNPs g n p's -GNRD g n r d -GNR g n r -GNR's g n r's -GNS g n s -GNSS g n s s -GNT g n t -G.O. g o -G.O.O.D. g o o d -GOPB g o p b -G.O.P. g o p -GOP g o p -GOPIO g o p i o -GOP's g o p's -GOQ g o q -GPA g p a -GPB g p b -G.P.C. g p c -GPC g p c -GPCR g p c r -GPCRs g p c r's -GPD g p d -GPdI g p d i -GPDSC g p d s c -GPF g p f -GPFS g p f s -G&P g and p -GPG g p g -gp g p -G. P. g p -G.P. g p -GP g p -GPGPU g p g p u -GPI g p i -GpIIb g p i i b -GPIO g p i o -GPL g p l -GPMGs g p m g's -G.P.O. g p o -GPO g p o -GPP g p p -GPRA g p r a -GPRF g p r f -GPR g p r -GPRs g p r's -GPRS g p r s -GPSC g p s c -GPS g p s -GPT g p t -GPU g p u -GPUs g p u's -GPX g p x -G. Q. g q -GQ g q -GQNYGK g q n y g k -GQ's g q's -GQT's g q t's -G.R.A.B. g r a b -grac g r a c -gra g r a -Gra g r a -GRA g r a -Grbac g r b a c -GRB g r b -GRBs g r b's -grc g r c -GRC g r c -GRCs g r c's -GRDA g r d a -GRDC g r d c -G.R.D. g r d -GRD g r d -gre g r e -Gre g r e -GRE g r e -GRF g r f -GRG g r g -gr g r -G. R. g r -G.R. g r -GR g r -GRK g r k -G.R.L. g r l -GRL g r l -GRMG g r m g -GRM g r m -GRO g r o -GRP g r p -grrl g r r l -G. R. S. g r s -GRS g r s -GRT g r t -GRU g r u -GRX g r x -Gryf g r y f -gry g r y -Gry g r y -GRY g r y -grz g r z -GSA g s a -GSAPP g s a p p -GSAS g s a s -GSB g s b -GSC g s c -GSDF g s d f -GSD g s d -G.S.E. g s e -GSE g s e -GSFC g s f c -GSF g s f -G&S g and s -GSG g s g -Gs g's -G. S. g s -G.S. g s -GS g s -GSHD g s h d -GSH g s h -GSI g s i -GSIs g s i's -GSIS g s i s -GSK g s k -GSL g s l -GSLV g s l v -GSMA g s m a -GSM g s m -GSNAS g s n a s -G. S. N. g s n -GSN g s n -GSNM g s n m -GSN's g s n's -GSO g s o -GSOM's g s o m's -GSOp g s o p -GSPC g s p c -G. S. P. g s p -GSP g s p -GSR g s r -GSSE g s s e -GSS g s s -GSSP g s s p -GSTA g s t a -G.S.T. g s t -GST g s t -GSU g s u -GSUSA g s u s a -GSVD g s v d -GSVS g s v s -GSX g s x -GTAA g t a a -GTA g t a -GTAs g t a's -GTB g t b -GTBK g t b k -GTBP g t b p -GTC g t c -GTCR g t c r -GTD g t d -GTEC g t e c -GTE g t e -GTF g t f -GTFT g t f t -GTFU g t f u -gt g t -G. T. g t -G.T. g t -GT g t -G. T. H. g t h -GTi g t i -GTI g t i -GTK g t k -GTL g t l -GTMO g t m o -G. T. O. g t o -GTO g t o -GTPBP g t p b p -GTP g t p -GTPR g t p r -GTRA g t r a -GTR g t r -GTRI g t r i -GTs g t's -GTS g t s -GTSV g t s v -GTT g t t -GTTP g t t p -GTU g t u -GTV g t v -GTW g t w -GTW's g t w's -GTX g t x -G. U. g u -G.U. g u -GUI's g u i's -GUIs g u i's -G.U.Y. g u y -GVA g v a -GVAV g v a v -GVBA g v b a -GVC g v c -G. V. g v -G.V. g v -GVHSS g v h s s -GVJZ g v j z -GVK g v k -GvpA g v p a -GVP g v p -GVRD g v r d -GVSU g v s u -GVT g v t -GVU g v u -GVVV g v v v -GVW g v w -GVWR g v w r -GWA g w a -GWB g w b -G. W. C. g w c -GWe g w e -Gwet g w e t -G.W.F. g w f -GWF g w f -gw g w -G. W. g w -G.W. g w -GW g w -G. W. H. g w h -GWHS g w h s -Gwi g w i -GWK g w k -G.W.L. g w l -GWO g w o -GWOT g w o t -gwr g w r -GWR g w r -GWR's g w r's -GW's g w's -G. W. S. g w s -GWS g w s -GWU g w u -GXG g x g -GX g x -GXP g x p -GYAN's g y a n's -GYC g y c -GYF g y f -Gy g y -G. Y. g y -GY g y -Gyn g y n -GYN g y n -Gyps g y p's -gyu g y u -Gyu g y u -GZA g z a -GZ g z -GZR g z r -HAFV h a f v -H. A. h a -H.A. h a -H&A h and a -HBA h b a -HBA's h b a's -HBBO h b b o -HBC h b c -HBCo h b c o -HBC's h b c's -HBCU h b c u -HBES h b e s -HBF h b f -HBGAs h b g a's -H. B. h b -H.B. h b -HB h b -HBI h b i -HBK h b k -HBLX h b l x -HBMP h b m p -HBO h b o -HBO's h b o's -HBPU h b p u -H&BR h and b r -HBR h b r -HBRN h b r n -HBRY h b r y -HB's h b's -HBS h b s -HBSS h b s s -HBU's h b u's -HBV h b v -HBW h b w -HCA h c a -HCAW h c a w -HCBE h c b e -HCB h c b -HCBS h c b s -HCCA h c c a -HCCB h c c b -HCCC h c c c -HCC h c c -HCDCH h c d c h -HCE h c e -HCEs h c e's -HCF h c f -H. C. G. h c g -HCGVN h c g v n -H. C. h c -H.C. h c -HC h c -HCH h c h -HCHS h c h s -HCI h c i -HCJB h c j b -hcl h c l -HCL h c l -HClO h c l o -HCMC's h c m c's -HCME h c m e -HCM h c m -HCN h c n -HCO h c o -HCoV h c o v -HCPA h c p a -H. C. P. h c p -HCP h c p -HCPs h c p's -HCR h c r -HCS h c s -HCT h c t -HCTV's h c t v's -HCUP h c u p -HCV h c v -Hcy h c y -HDAC h d a c -Hdad h d a d -hDAF h d a f -HDA h d a -HDB h d b -HDCAM h d c a m -HDC h d c -HDCP h d c p -HDD h d d -HDDs h d d's -HDFC h d f c -H.D.F. h d f -HDFM h d f m -H.D.G. h d g -HDG h d g -hd h d -H. D. h d -H.D. h d -HD h d -hdh h d h -HDi h d i -HDI h d i -HDLC h d l c -HDL h d l -HDLS h d l s -HDM h d m -HDMI h d m i -HDPE h d p e -HDP h d p -HDR h d r -HDRO h d r o -HDRR h d r r -H. E. h e -H.E. h e -hezb h e z b -Hezb h e z b -HFA h f a -HFB h f b -HFC h f c -HFCS h f c s -HFDF h f d f -HFF h f f -HFF's h f f's -H&F h and f -H. F. h f -H.F. h f -HFI h f i -H. F. J. h f j -HFNB h f n b -HFPA h f p a -HFP h f p -HFPPV h f p p v -HFRS h f r s -HFS h f s -HFTP h f t p -H.G.B. h g b -hgcA h g c a -HGC h g c -HGF h g f -hg h g -H. G. h g -H.G. h g -HG h g -HGH h g h -HGNC h g n c -HgO h g o -H. G. O. h g o -HGPIN h g p i n -HGPs h g p's -HGTV h g t v -HGTV's h g t v's -HgU h g u -HGVs h g v's -HGY h g y -HHA h h a -H. H. B. h h b -HHC h h c -HHD h h d -HHDP h h d p -HHG h h g -H&H h and h -HHHDB h h h d b -H. H. h h -H.H. h h -HHPC h h p c -HHSAA h h s a a -HHS h h s -H.H.T. h h t -H. I. h i -H.I. h i -H.I.V.E. h i v e -HIV h i v -HIY h i y -Hizb h i z b -hja h j a -HJC h j c -H. J. h j -H.J. h j -HJ h j -HJK h j k -H.J.M. h j m -HJN h j n -H. J. R. h j r -H.J.R. h j r -H. J. W. h j w -HJW h j w -HKAA h k a a -Hkam h k a m -HKB h k b -HKCEC h k c e c -HKCEE h k c e e -HKDF h k d f -HKD h k d -HKDSE h k d s e -HKFC h k f c -H&K h and k -H. K. h k -H.K. h k -HK h k -H. K. J. h k j -HKK h k k -HKMA h k m a -HKN h k n -H.K.P. h k p -HKP h k p -HKSAR h k s a r -HK's h k's -HKT h k t -HKTWU h k t w u -HKU h k u -Hla h l a -HLA h l a -HLBN h l b n -HLE h l e -HLH h l h -H. L. h l -H.L. h l -HLL h l l -HLLS h l l s -HLN h l n -HLN's h l n's -HLS h l s -HLT h l t -HLTV h l t v -Hluk h l u k -hlutr h l u t r -HLV h l v -Hly h l y -HMAC h m a c -HMA h m a -Hman h m a n -H.M.A.S. h m a s -HMAS h m a s -HMB h m b -HMC h m c -HMCS h m c s -HMDA h m d a -HMD h m d -HMDI h m d i -HMDP h m d p -HME h m e -HMEL h m e l -HMF h m f -HMGA h m g a -HMG h m g -HMGIC h m g i c -HMGN h m g n -H&M h and m -HMH h m h -hm h m -H. M. h m -H.M. h m -HM h m -HMI h m i -HMIS h m i s -HMMC h m m c -HMM h m m -HMMWV h m m w v -HMN h m n -HMNZS h m n z s -HMNZT h m n z t -HMO h m o -HMOs h m o's -HMPC h m p c -HMP h m p -HMRC h m r c -hMRE h m r e -H&M's h and m's -H. M. S. h m s -H.M.S. h m s -HMS h m s -HMSN h m s n -H.M.S.O. h m s o -HMSO h m s o -H. N. h n -H.N. h n -HNI h n i -HNK h n k -HNL h n l -HNLMS h n l m s -HNMT h n m t -HNN h n n -HNO h n o -HNS h n s -H. O. h o -H.O. h o -HPA h p a -H.P.B. h p b -hpc h p c -HPC h p c -HPCT h p c t -H. P. D. h p d -HPD h p d -HPE h p e -HPH h p h -hp h p -H. P. h p -H.P. h p -HP h p -HPI h p i -HPLC h p l c -HPL h p l -HPP h p p -HPRA h p r a -HPR h p r -HPRT h p r t -HP's h p's -HPS h p s -H. P. T. h p t -HPV h p v -HQAA h q a a -HQDA h q d a -H.Q. h q -HQ h q -HRG h r g -H&R h and r -H.R.H. h r h -HRH h r h -H. R. h r -H.R. h r -HR h r -HRK h r k -HRL h r l -HRM h r m -hroa h r o a -HRo h r o -HRO h r o -HRP h r p -HRSA h r s a -HRSA's h r s a's -HRSG h r s g -hrs h r s -HRs h r's -HRST h r s t -HRT h r t -HRV h r v -HRW h r w -HRX h r x -HSA h s a -HSAN h s a n -HSBC h s b c -HSB h s b -HSCA h s c a -HSC h s c -hscy h s c y -HSD h s d -HSDPA h s d p a -Hsee h s e e -HSE h s e -HSE's h s e's -HSF h s f -HSG h s g -HSHB h s h b -H.S.H. h s h -hs h s -Hs h's -H. S. h s -H.S. h s -HS h s -HSHS h s h s -hsi h s i -HSJ h s j -HSK h s k -HSL h s l -hSlo h s l o -H.S.M. h s m -HSM h s m -HSMR h s m r -HSN h s n -HSNY's h s n y's -HSPA h s p a -HSPA's h s p a's -HSPG h s p g -HSPH h s p h -HSP h s p -HSP's h s p's -HSPs h s p's -HSRC h s r c -HSR h s r -HSSCCT h s s c c t -HSSF h s s f -HSS h s s -HST h s t -HST's h s t's -HSTs h s t's -HSTS h s t s -hsv h s v -HSV h s v -HSX h s x -HSY h s y -HSYK's h s y k's -HSZ h s z -HTA h t a -hTAS h t a s -HTAs h t a's -htc h t c -HTC h t c -HTC's h t c's -HTGL h t g l -HTHC h t h c -ht h t -H. T. h t -H.T. h t -HT h t -HTIB h t i b -hti h t i -Htin h t i n -HTK h t k -HTLA h t l a -HTLV h t l v -HTML h t m l -HTM's h t m's -Htoo h t o o -HTPB h t p b -HTPC h t p c -HTP h t p -HtrA h t r a -HTR h t r -HTRs h t r's -HTS h t s -http h t t p -HTTP h t t p -https h t t p s -HTTPS h t t p s -HTV h t v -HTV's h t v's -Htwa h t w a -HTW h t w -HTX h t x -H. U. h u -HVC h v c -HVCs h v c's -hvcv h v c v -HVDC h v d c -hvem h v e m -Hvem h v e m -HVF h v f -HVHS h v h s -H. V. h v -H.V. h v -H.W.A. h w a -H. W. F. h w f -H. W. h w -H.W. h w -H.W.L. h w l -HWL h w l -HWM h w m -HWRT h w r t -HWT h w t -HWV h w v -hwy h w y -Hwy h w y -hxt h x t -H. Y. h y -H.Y. h y -H. Z. h z -HZ&PC h z and p c -iaaf i a a f -IAAF i a a f -IAAF's i a a f's -IAA i a a -IAAPA i a a p a -IAAP i a a p -IaaS i a a s -IAAS i a a s -IABSE i a b s e -Iaca i a c a -IACC i a c c -IACD i a c d -IAC i a c -Iacob i a c o b -IACR i a c r -IAC's i a c's -IACTs i a c t's -Iacub i a c u b -IACUC i a c u c -IACW i a c w -IAD i a d -IAD's i a d's -IAEA i a e a -IAEG i a e g -I.A.E. i a e -IAE i a e -IAF i a f -IAF's i a f's -IAG i a g -IAG's i a g's -iagt i a g t -IAHP i a h p -IAHRC i a h r c -I. A. i a -I.A. i a -I.A.M. i a m -IAO i a o -Iapa i a p a -IAPHC i a p h c -IAP i a p -iar i a r -Iar i a r -IAR i a r -IAST i a s t -IATA i a t a -I.A.T. i a t -IAT i a t -IATR i a t r -IAUC i a u c -IAUCs i a u c's -IAU i a u -IAV i a v -IAWTV i a w t v -Iax i a x -IAX i a x -Ibac i b a c -Ibaes i b a e's -IBA's i b a's -IBB i b b -IBC i b c -IBCs i b c's -IBCT i b c t -IBDA'A i b d a a -Ibda i b d a -ibdal i b d a l -IBDB i b d b -IBDE i b d e -IBD i b d -IBE i b e -IBF i b f -IBGE i b g e -IBH i b h -I. B. i b -I.B. i b -IBJJF i b j j f -IBL i b l -IBLT i b l t -IBMA's i b m a's -IBMC i b m c -Ibm i b m -I.B.M. i b m -IBM i b m -IBM's i b m's -IBMXF i b m x f -Ibne i b n e -ibn i b n -IBO i b o -IBPA i b p a -IBP i b p -Ibra i b r a -IBRA i b r a -IBRC i b r c -IBR i b r -IBRO i b r o -Ibsa i b s a -IBSA i b s a -IBSF i b s f -Ibs i b's -IBS i b s -IBSL i b s l -IBTC i b t c -iBT i b t -IBTS i b t s -Ibu i b u -IBU i b u -IBV i b v -IBWFF i b w f f -iby i b y -ICBA i c b a -ICBC i c b c -ICB i c b -ICBL i c b l -ICBM i c b m -ICBMs i c b m's -ICBP i c b p -ICBS i c b s -ICBTT i c b t t -ICCC i c c c -ICCC's i c c c's -ICCEC i c c e c -ICCF i c c f -Icche i c c h e -I.C.C. i c c -ICC i c c -ICCID i c c i d -ICCI i c c i -ICCR i c c r -ICC's i c c's -ICCS i c c s -ICCW i c c w -ICDC i c d c -ICD i c d -ICDS i c d s -I.C.E. i c e -ICFF i c f f -icf i c f -ICF i c f -ICFR i c f r -ICG i c g -ICHC i c h c -I&C i and c -ic i c -Ic i c -I. C. i c -I.C. i c -IC i c -Ici i c i -ICI i c i -ICJ i c j -ICL i c l -ICL's i c l's -ICMA i c m a -ICME i c m e -I.C.M. i c m -ICM i c m -iCN i c n -ICN i c n -Ico i c o -ICO i c o -ICOP i c o p -ICPC i c p c -ICPD i c p d -ICP i c p -ICP's i c p's -ICQ i c q -ICRC i c r c -ICRF i c r f -ICR i c r -IcRn i c r n -ICRP i c r p -ICRS i c r s -ICRW i c r w -ICSA i c s a -ICSB i c s b -ICSC i c s c -ICSE i c s e -ICSG i c s g -ics i c s -ICs i c's -ICS i c s -ICSS i c s s -ICSSR i c s s r -ICTA i c t a -ICT i c t -ICTM i c t m -ICTP i c t p -ICTSF i c t s f -ICTs i c t's -ICTS i c t s -ICTU i c t u -ICTUR i c t u r -ICTVdB i c t v d b -ICTV's i c t v's -ICTY i c t y -ICU i c u -ICUN i c u n -ICU's i c u's -ICv i c v -ICV i c v -ICVS i c v s -ICWA i c w a -ICWC i c w c -ICW i c w -ICW's i c w's -iCyt i c y t -ICZ i c z -ICZN i c z n -IDAF i d a f -IDBF i d b f -IDB i d b -IDBI i d b i -IDC i d c -Iddaa i d d a a -Idd i d d -ID'd i d d -IDEF i d e f -IDE i d e -IDFA i d f a -IDFG i d f g -IDF i d f -IDFL i d f l -IDF's i d f's -IDG i d g -I. D. H. i d h -IDH i d h -id i d -I. D. i d -I.D. i d -ID i d -Idi i d i -Idir i d i r -IDIS i d i s -IDLHs i d l h's -IDL i d l -Idm i d m -IDM i d m -IDMR i d m r -IDMS i d m s -IDNA i d n a -IDN i d n -IDNR i d n r -IDNR's i d n r's -IDPs i d p's -IDRC i d r c -IDRO i d r o -IDSA i d s a -IDSA's i d s a's -IDSF i d s f -ids i d s -ID's i d's -IDs i d's -IDV i d v -IDW i d w -IDWO i d w o -IDW's i d w's -IDx i d x -IDX i d x -IEA i e a -I.E.M. i e m -IEM i e m -I.E.S. i e s -IES i e s -i.e. that is -Ifa i f a -IFA i f a -IFBB i f b b -IFBC i f b c -I.F.B. i f b -IFCC i f c c -ifc i f c -IFC i f c -IFC's i f c's -IfF i f f -I. F. F. i f f -IFF i f f -IFFI i f f i -IFFK i f f k -Ifft i f f t -IFHA i f h a -IFHP i f h p -ifi i f i -Ifi i f i -IFI i f i -IFIP i f i p -IFIs i f i's -IFK i f k -IFLA i f l a -IFL i f l -IfM i f m -IFM i f m -IFN i f n -Ifni i f n i -IFNs i f n's -IFO i f o -Ifop i f o p -IFP i f p -IFPI i f p i -IFPRI i f p r i -IFRC i f r c -IFR i f r -IFRS i f r s -IFRSs i f r s's -IFSB i f s b -IFSC i f s c -IFSTA i f s t a -IFTA i f t a -IFTF i f t f -IFT i f t -Iga i g a -IgA i g a -IGA i g a -IGA's i g a's -IGBT i g b t -IGC i g c -IGCP i g c p -IGCSE i g c s e -IGD i g d -IGF i g f -IGFI i g f i -IGFs i g f's -IGIB i g i b -'ig i g -Ig i g -I.G. i g -IG i g -igi i g i -IGI i g i -IgM i g m -IGM i g m -IGMP i g m p -ign i g n -Ign i g n -IGN i g n -IHF i h f -IHGS i h g s -IHH i h h -Ih i h -I. H. i h -IH i h -ihi i h i -IHI i h i -IHL i h l -IHL's i h l's -IHMC i h m c -IHME i h m e -ihm i h m -ihn i h n -Ihn i h n -IHOM i h o m -Ihor i h o r -IHPK i h p k -IHRC i h r c -IHSAA i h s a a -IHSA i h s a -IHS i h s -Iht i h t -IIA i i a -IIb i i b -IIB i i b -IIc i i c -IIDC i i d c -IID i i d -IIDI i i d i -IIDS i i d s -IIDX i i d x -IIED i i e d -IIFA i i f a -IIF i i f -IIfx i i f x -Iiga i i g a -IIga i i g a -IIG i i g -IIgs i i g's -IIGs i i g's -IIGS i i g s -IIGS's i i g s's -IIHF i i h f -IIHR i i h r -IIHS i i h s -IIIA i i i a -IIIb i i i b -IIIB i i i b -IIIBy i i i b y -IIIc i i i c -IIId i i i d -IIIF i i i f -I. I. i i -I.I. i i -ija i j a -Ija i j a -IJA i j a -IJF i j f -IJGL i j g l -IJHCD i j h c d -IJHL i j h l -ij i j -I. J. i j -IJ i j -IJN i j n -Ijok i j o k -IJSB i j s b -IJSE i j s e -IJSEM i j s e m -IJS i j s -Ijui i j u i -IJVM i j v m -IKBN i k b n -IKCO i k c o -IKF i k f -Ikh i k h -I.K. i k -IKK i k k -IKL i k l -IKr i k r -Iksa i k s a -IKTA i k t a -Iku i k u -Ilbe i l b e -ILB i l b -ILC i l c -ILCS i l c s -ILD i l d -ILDIS i l d i s -ILFC i l f c -ILF i l f -IL&FS i l and f s -ili i l i -Ili i l i -ILI i l i -I. L. i l -I.L. i l -Ilm i l m -ILM i l m -ILM's i l m's -ILN i l n -ILP i l p -ILR i l r -ILRS i l r s -ilu i l u -Ilu i l u -ILU i l u -IMbd i m b d -IMBD i m b d -IMB i m b -IMCB i m c b -IMCI i m c i -imc i m c -IMC i m c -imdb i m d b -IMDb. i m d b -IMDb i m d b -IMDB i m d b -IMD i m d -IMD's i m d's -ime i m e -IME i m e -IMF i m f -IMG i m g -I&M i and m -IMI i m i -I. M. i m -I.M. i m -IMIS i m i s -IMK i m k -Iml i m l -IMMEX i m m e x -Imm i m m -Imms' i m m's -imoa i m o a -IMO's i m o's -IMPA i m p a -IMPDH i m p d h -impr i m p r -Impr i m p r -IMPSA i m p s a -IMR i m r -IMSLP i m s l p -iMSNs i m s n's -Imst i m s t -IMTA i m t a -IMT i m t -IMTV i m t v -IMUK i m u k -IMU's i m u's -IMWF i m w f -INAC i n a c -Inba i n b a -INBA i n b a -INBF i n b f -inb i n b -incl i n c l -INDC i n d c -ind i n d -Ind i n d -IND i n d -INFJ i n f j -I.N.F.O. i n f o -Infs i n f's -ING i n g -INGR i n g r -inHg i n h g -INH i n h -INI i n i -I. N. i n -I.N. i n -InlB i n l b -INL i n l -INM i n m -INPD i n p d -INPE i n p e -InP i n p -INP i n p -INPP i n p p -Inre i n r e -I.N.R.I. i n r i -INR i n r -INSB i n s b -INSDC i n s d c -INSD i n s d -Inspx i n s p x -INSS i n s s -INTF i n t f -Ints i n t's -INTs i n t's -Intu i n t u -INVA i n v a -inv i n v -INXS i n x s -INXS's i n x s's -Ioba i o b a -IOCG i o c g -IOC i o c -IOCP i o c p -IODP i o d p -IODs i o d's -IOE i o e -IOFB i o f b -IOF i o f -io. i o -io i o -.I.o. i o -Io. i o -Io i o -.IO i o -I/O i o -IO i o -Ioka i o k a -Iok i o k -IOL i o l -IoM i o m -IOM i o m -IOPI i o p i -IOP i o p -IOPs i o p's -IORG i o r g -IOR i o r -IORM i o r m -IOSA i o s a -IOSB i o s b -iOS i o s -Io's i o's -I/Os i o's -I.O.'s i o's -IOS i o s -IOSR i o s r -Iosu i o s u -IoT i o t -IOT i o t -I.O.U. i o u -IOU i o u -IoW i o w -IOW i o w -IPA i p a -IPA's i p a's -IPB i p b -IPCC i p c c -IPCC's i p c c's -IPC i p c -IPCRI i p c r i -IPCs i p c's -IPDA i p d a -IPDI i p d i -IPD i p d -IPE i p e -IPFA i p f a -IPFI i p f i -IPF i p f -IPFP i p f p -IPFW i p f w -IPG i p g -IPH i p h -ip i p -Ip i p -I.P. i p -IP i p -IPL i p l -IPMG i p m g -IPM i p m -IPNI i p n i -IPN i p n -Ipo i p o -I.P.O. i p o -IPO i p o -IPP i p p -IPPL i p p l -IPPs i p p's -IPPT i p p t -Ippu i p p u -iPPV i p p v -IPR i p r -iPSC i p s c -IPSC i p s c -iPSCs i p s c's -ipse i p s e -IPSF i p s f -iPS i p s -IPs i p's -I.P.S. i p s -IPS i p s -IPTA i p t a -IPTC i p t c -IPTG i p t g -IPT i p t -IPTL i p t l -IPTV i p t v -IPU i p u -IPUM i p u m -IPv i p v -IPWA i p w a -IPW i p w -IPX i p x -iQ i q -I.Q. i q -IQ i q -IRAC i r a c -I.R.A. i r a -IRB i r b -IRBM i r b m -IRCA i r c a -IRC i r c -IRCM i r c m -IRCTC i r c t c -IRCT i r c t -IRD i r d -IRDS i r d s -IREC i r e c -I.R.E. i r e -IRE i r e -IRFCA i r f c a -IRFC i r f c -IRF i r f -IRFU i r f u -IRGC i r g c -Irgm i r g m -IRHG i r h g -IRHT i r h t -IRIB i r i b -Irig i r i g -IRI i r i -Iril i r i l -IRIN i r i n -i'r i r -ir i r -Ir i r -I. R. i r -I.R. i r -IR i r -IRIX i r i x -Irla i r l a -IRL i r l -IRM i r m -Irmis i r m i's -IRM's i r m's -IRNE i r n e -IRN i r n -iro i r o -Iro i r o -IRO i r o -IRP i r p -IRP's i r p's -IRPS i r p s -IRQ i r q -Irra i r r a -IRRI i r r i -IRR i r r -IRs i r's -I.R.S. i r s -IRS i r s -IRSN i r s n -I.R.T. i r t -IRT i r t -iru i r u -Iru i r u -ISA i s a -ISAv i s a v -Isba i s b a -ISBA i s b a -ISBER i s b e r -ISBHF i s b h f -ISB i s b -isbn i s b n -ISBN i s b n -ISBNs i s b n's -ISBO i s b o -ISCB i s c b -ISCE i s c e -isCf i s c f -ISCI i s c i -iSC i s c -Isc i s c -ISC i s c -ISCM i s c m -ISCM's i s c m's -ISCP i s c p -ISDA i s d a -Isd i s d -ISD i s d -isdn i s d n -ISDN i s d n -ISDS i s d s -ISDT i s d t -ISFI i s f i -ISF i s f -Isgec i s g e c -ISG i s g -ISHC i s h c -ishq i s h q -Ishq i s h q -ISHS i s h s -I. S. i s -I.S. i s -ISKB i s k b -ISK i s k -Isl i s l -ISL i s l -ISMF i s m f -ISMIR i s m i r -ISMNs i s m n's -ISN i s n -ISNTUC i s n t u c -ISOGG i s o g g -ISO i s o -ISO's i s o's -I.S.P.C.K. i s p c k -ISPF i s p f -ISPI i s p i -ISP i s p -ISPL i s p l -ISPR i s p r -ISPs i s p's -Isra'il i s r a i l -Isra i s r a -ISRA i s r a -ISR i s r -ISRN i s r n -ISRO i s r o -ISRP i s r p -ISSCC i s s c c -ISSF i s s f -iss i s s -Iss i s's -ISS i s s -ISSN i s s n -ISSNs i s s n's -ISSSSP i s s s s p -ISSUU i s s u u -ISTAF i s t a f -ISTD i s t d -Isu i s u -ISU i s u -ISU's i s u's -ISWC i s w c -ISWI i s w i -ISW i s w -I.T.A. i t a -ITA i t a -ITB i t b -ITC i t c -Ite i t e -ITE i t e -ITF i t f -ITG i t g -ITHF i t h f -I.T.H.M. i t h m -ITHs i t h's -iti i t i -Iti i t i -ITI i t i -I.T. i t -itk i t k -Itk i t k -ITK i t k -ITM i t m -ITMO i t m o -ITN i t n -ITNNs i t n n's -ITN's i t n's -Itoi i t o i -ITPF i t p f -iTP i t p -ITP i t p -ITRD i t r d -Itse i t s e -ITSF i t s f -ITTF i t t f -itt i t t -ITT i t t -ITUC i t u c -Itu i t u -ITU i t u -ITV i t v -ITV's i t v's -ITWF i t w f -ITW i t w -Itz i t z -IUB i u b -I.U.C.N.B. i u c n b -Iucn i u c n -IUCN i u c n -IUCN's i u c n's -IUD i u d -IUDs i u d's -IU i u -IUT i u t -IUU i u u -Iuz i u z -IVAA i v a a -IVAW i v a w -IVB i v b -I. V. i v -I.V. i v -IVL i v l -IVLP i v l p -IVM's i v m's -IVP i v p -IVPP i v p p -IVPTC i v p t c -IVRCL i v r c l -IVs i v's -Ivu i v u -IVWA i v w a -IWA i w a -Iwas i w a's -Iwaz i w a z -IWBs i w b's -IWC i w c -IWD i w d -IWF i w f -IWFL i w f l -IWF's i w f's -IWFS i w f s -IWG i w g -IWGP i w g p -iwi i w i -iw i w -I. W. i w -IW i w -IWL i w l -IWMF i w m f -IWM i w m -IWPR i w p r -iwrg i w r g -IWRG i w r g -IWR i w r -IWRS i w r s -IWSA i w s a -iwspy i w s p y -Iwuh i w u h -IWU's i w u's -I.W.W. i w w -IWW i w w -IXA i x a -IXb i x b -IXBs i x b's -IXC i x c -IXCs i x c's -IXe i x e -IX i x -iXL i x l -IXO i x o -ixtle i x t l e -IXV i x v -Iya i y a -IYA i y a -Iyar i y a r -IYC i y c -iyem i y e m -IYHF i y h f -Iyi i y i -iy i y -I. Y. i y -I.Y. i y -IY i y -J.A.A. j a a -J. A. B. j a b -Jaf j a f -J.A.G. j a g -JAG j a g -JAIR j a i r -J. A. j a -J.A.K.E. j a k e -J. A. N. j a n -J.A.P. j a p -J.A.S. j a s -JBA j b a -JBBA j b b a -JBB j b b -JBC j b c -JBG j b g -J&B j and b -jb j b -J. B. j b -J.B. j b -JB j b -J.B.L.D. j b l d -JBL j b l -J.B.M. j b m -JBM j b m -JB's j b's -J. B. S. j b s -J.B.S. j b s -JBT j b t -JBZ j b z -JCA j c a -JCB j c b -JCC j c c -JCF j c f -JCFS j c f s -J.C.G. j c g -JCG j c g -JCGM j c g m -JCIB j c i b -JCI j c i -jcis j c i s -jc j c -J. C. j c -J.C. j c -JC j c -JCJC j c j c -J. C. L. j c l -JCPA j c p a -J. C. P. j c p -JCP j c p -JCPV j c p v -JCRB j c r b -JCR j c r -JCRs j c r's -J.C.S. j c s -JCS j c s -JCSR j c s r -JCVI j c v i -J. C. W. j c w -JCW j c w -J. D. A. j d a -JDA j d a -JDBC j d b c -JDC j d c -JdeBP j d e b p -J.D.E. j d e -JDE j d e -JDENET j d e n e t -J.D.F. j d f -JDF j d f -jdi j d i -JDI j d i -jd j d -J. D. j d -J.D. j d -JD j d -jdk j d k -JDK j d k -J.D.M. j d m -JDM j d m -JDO j d o -JDRF j d r f -J&D's j and d's -J.D.s j d's -JDT j d t -JDU j d u -JDV j d v -J. E. A. j e a -J.E.A.L. j e a l -J.E.B. j e b -J. E. C. j e c -J. E. E. j e e -J. E. j e -J.E. j e -J.F.G. j f g -JFH j f h -jf j f -J. F. j f -J.F. j f -JF j f -JFK j f k -JFN j f n -JFQA j f q a -JFS j f s -J. G. A. j g a -J.G.B. j g b -JGI j g i -J. G. j g -J.G. j g -J. G. L. j g l -JGLS j g l s -J. G. M. j g m -J.G.M. j g m -JGO j g o -JGP j g p -JGR j g r -JGR's j g r's -JGSDF j g s d f -JGTC j g t c -JGU j g u -J.H.B. j h b -JHB j h b -J. H. C. j h c -JHC j h c -JHED j h e d -J.H.F. j h f -J.H.H. j h h -jh j h -J. H. j h -J.H. j h -JH j h -JHL j h l -J. H. M. j h m -J.H.R. j h r -JHs j h's -JHS j h s -JHSVs j h s v's -JHud j h u d -JHU j h u -J. I. j i -J.I. j i -J.J.A. j j a -JJB j j b -J. J. C. j j c -J.J.G. j j g -J&J j and j -J. J. j j -J.J. j j -JJ j j -JJK j j k -J. J. L. j j l -J.J.M. j j m -J.J.N. j j n -JJN j j n -Jka j k a -JKA j k a -JKC j k c -jkd j k d -JKH j k h -J&K j and k -J.K. J. j k j -J. K. j k -J.K. j k -JK j k -JKNPP j k n p p -J. K. S. j k s -JKT j k t -jkx j k x -JKX j k x -JLA j l a -J.L.B. j l b -JLB j l b -JLC j l c -J. L. E. j l e -J.L.E. j l e -JLG j l g -JLI j l i -J. L. j l -J.L. j l -J.L.L. j l l -JLM j l m -JLO's j l o's -JLPGA j l p g a -JLP j l p -JLS j l s -JLT j l t -JMA j m a -JMBG j m b g -J.M.C. j m c -JMC j m c -J. M. D. j m d -JMD j m d -J. M. E. j m e -JMI j m i -J. M. J. j m j -J.M.J. j m j -J. M. j m -J.M. j m -JMKR j m k r -J. M. L. j m l -JML j m l -JMM j m m -JMP j m p -JMS j m s -JMU j m u -JMV j m v -J. M. W. j m w -J.M.W. j m w -JMX j m x -JNA j n a -jnb j n b -JNF j n f -JNG j n g -JNI j n i -J. N. j n -J.N. j n -JN j n -JNK j n k -J. N. L. j n l -Jno j n o -JNPT j n p t -jnr j n r -JNR j n r -JNS's j n s's -JOJ j o j -J. O. j o -J.O. j o -J.P.D.B. j p d b -J. P. F. j p f -JPF j p f -jpg j p g -JPG j p g -JPH j p h -J&P j and p -jp j p -J.P. j p -JP j p -J.P.R. j p r -J.Q. j q -JQ j q -J.R.A. j r a -JRA j r a -J.R.C. j r c -JRC j r c -J.R.E. j r e -JRG j r g -JRHU j r h u -J. R. I. j r i -J&R j and r -J. R. j r -J.R. j r -JR j r -JRJ's j r j's -Jr. junior -jr. junior -Jr junior -jr junior -JRPG j r p g -J. R. P. j r p -J. R. R. j r r -J.R.R. j r r -J.R.'s j r's -JRSP j r s p -J. R. T. j r t -JRU j r u -JRX j r x -JSA j s a -JSAP j s a p -JSA's j s a's -jsb j s b -JSCA j s c a -JSC j s c -J.S.D. j s d -JSD j s d -JSE j s e -JSF j s f -JSH j s h -Js j's -J. S. j s -J.S. j s -JS j s -J.S.K. j s k -J.S.L. j s l -JSL j s l -J. S. M. j s m -JSM j s m -JSNN j s n n -JSOC j s o c -JSO j s o -JSP j s p -JSPS j s p s -JSR j s r -JSS j s s -JSW j s w -JSW's j s w's -JSX j s x -JTA j t a -J.T.B. j t b -JTB j t b -JTC j t c -JTF j t f -JTG j t g -JTI j t i -J&T j and t -J. T. j t -J.T. j t -JT j t -JT&KW j t and k w -JTL j t l -JTO j t o -JTR j t r -JTRO j t r o -JTS j t s -JTTF j t t f -JTT j t t -JTV j t v -J. U. j u -J.U.L.I.A. j u l i a -J.V.B. j v b -JVB j v b -JVC j v c -J.V.E. j v e -JVG j v g -JVH j v h -J&V j and v -J. V. j v -J.V. j v -JV j v -JVM j v m -JVNW j v n w -JVP j v p -JVRA j v r a -JVS j v s -Jwa j w a -J. W. A. j w a -J. W. B. j w b -JWB j w b -J.W.C. U.S. j w c u s -JWHA j w h a -J.W.J. j w j -J. W. j w -J.W. j w -JWM j w m -J. W. P. j w p -JWP j w p -JWRC j w r c -J. W. S. j w s -J.W.S. j w s -JWS j w s -JWST j w s t -JWT j w t -jx j x -JX j x -J.X.W.P. j x w p -JYJ j y j -JYJ's j y j's -J. Y. j y -J.Y. j y -JY j y -Jym j y m -Jymn j y m n -JYP j y p -J. Y. S. j y s -J. Z. j z -J.Z. j z -JZ j z -K.A.A. k a a -K. A. k a -K.A. k a -K.A.N. k a n -K. A. R. k a r -K.A.S. k a s -KBBI k b b i -KBB k b b -KBCI k b c i -KBC k b c -KBCO k b c o -KBD k b d -KBE k b e -KBFC k b f c -KBFL k b f l -KBFR k b f r -KBGD k b g d -KBG k b g -KBIG k b i g -kbi k b i -K&B k and b -K. B. k b -K.B. k b -KBKR k b k r -KBKS k b k s -KBKW k b k w -KBL k b l -KBMT k b m t -KBND k b n d -KBNZ k b n z -KBO k b o -KBRC k b r c -KBR k b r -KBS k b s -KBSN k b s n -KCB k c b -KCBS k c b s -KCCC k c c c -KCCI k c c i -KCC k c c -KCCO k c c o -KCDC k c d c -K. C. D. k c d -KCD k c d -KCED k c e d -KCET k c e t -KCG k c g -KCHS k c h s -K.C.I.E. k c i e -K. C. k c -K.C. k c -KCK k c k -KCKM k c k m -KCLU k c l u -K.C.M.G. k c m g -KCMG k c m g -KCNA k c n a -KCNH k c n h -KCNJ k c n j -KCN k c n -KCNN k c n n -KCNQ k c n q -KCNV k c n v -KCPD k c p d -KCPI k c p i -KCPM k c p m -KCPQ k c p q -KCPQ's k c p q's -KCQL k c q l -KCRA k c r a -KCRC k c r c -KCRH k c r h -KCR k c r -KCRW k c r w -KCSD k c s d -KCSG k c s g -K.C.S.I. k c s i -KCSI k c s i -K.C.'s k c's -KCS k c s -KCSP k c s p -KCTD k c t d -KCT k c t -KCTL k c t l -KCTV k c t v -KCUB k c u b -KCU k c u -KCVO k c v o -KCYX k c y x -kDa k d a -KDA k d a -kdal k d a l -KDAL k d a l -KDB k d b -KDCE k d c e -KDCO k d c o -KDDG k d d g -KDDI k d d i -KDD k d d -KDE k d e -KDFW k d f w -KDFX k d f x -K. D. G. k d g -KDGS k d g s -KDHS k d h s -KDKA k d k a -K&D k and d -kd k d -K. D. k d -K.D. k d -KD k d -KDP k d p -KDPM k d p m -KDR k d r -K. D.'s k d's -K.D.'s k d's -KDS k d s -ke k e -Ke k e -K. E. k e -K.E. k e -KE k e -KFAC k f a c -KFAED k f a e d -KFAI k f a i -KFA k f a -KFBK k f b k -KFBT k f b t -KFCC k f c c -KFCD k f c d -kfc k f c -K.F.C. k f c -KFC k f c -KFC's k f c's -KFD k f d -KFDM k f d m -KFEM k f e m -KFFL k f f l -KFH k f h -KFI k f i -KFJB k f j b -K.F. k f -KFLX k f l x -KFMB's k f m b's -KFMJ k f m j -K. F. M. k f m -K.F.M. k f m -KFOR k f o r -KFQC k f q c -KFQ k f q -KFRC k f r c -KFRC's k f r c's -KFRD k f r d -KFRG k f r g -KFRH k f r h -KFRO k f r o -KFSD k f s d -KFSN k f s n -KFST k f s t -KFT k f t -KFTL k f t l -KFUM's k f u m's -KFVD k f v d -KFV k f v -KFWB k f w b -KFXO k f x o -KFYO's k f y o's -KGA k g a -K.G.B. k g b -KGB k g b -KGC k g c -KGPH k g p h -KGP k g p -KGRI k g r i -kgr k g r -KGRK k g r k -KGS k g s -kgt k g t -KGT k g t -KGTV k g t v -KgU k g u -KGU k g u -KGUN k g u n -kgv k g v -K.G.V. k g v -KGWB k g w b -KGW k g w -KHHZ k h h z -KHI k h i -Khizr k h i z r -KHJ k h j -K. H. k h -K.H. k h -KH k h -KHK k h k -KHKV k h k v -Khlav k h l a v -KHL k h l -KHL's k h l's -Khmu k h m u -KHMY k h m y -KHOJ k h o j -KHOW k h o w -KHQA k h q a -KHQ k h q -Khri k h r i -Khru k h r u -KHRW k h r w -KHSAA k h s a a -KHS k h s -KHTL k h t l -KHTZ k h t z -KHUI k h u i -KHUT k h u t -KHWI k h w i -K.I.D. k i d -K. I. k i -K.I. k i -K.I.M. k i m -KIP k i p -K.I.S.S. k i s s -KJCE k j c e -KJCT k j c t -KJEF k j e f -Kjer k j e r -KJHK k j h k -KJI k j i -KJIN k j i n -kj k j -K. J. k j -K.J. k j -KJ k j -KJKP k j k p -KJMM k j m m -KJNE k j n e -KJNW k j n w -Kjop k j o p -KJo's k j o's -KJQY k j q y -KJV k j v -KJZI k j z i -KKBL k k b l -KKBQ k k b q -KKCR k k c r -KKDA k k d a -K.K.E. k k e -KKE k k e -K. K. k k -K.K. k k -KKMC k k m c -KKMI k k m i -KKM k k m -KKMX k k m x -KKRG k k r g -KKR k k r -KKSF k k s f -KK's k k's -KKSY k k s y -KKT k k t -KLA k l a -KLBK k l b k -KLBM k l b m -KLCI k l c i -KLC k l c -KLDS k l d s -Kle k l e -KLE k l e -KLF k l f -KLGH k l g h -KLH k l h -KLK k l k -kl k l -K. L. k l -K.L. k l -KL k l -KLKS k l k s -KLLP k l l p -KLLV k l l v -KLM k l m -KLN's k l n's -KLQQ k l q q -KLQT k l q t -KLRY k l r y -KLSC k l s c -KLSD k l s d -KLS k l s -KLSX k l s x -KLT k l t -KLX k l x -KMB k m b -KMC k m c -KMD k m d -KMGO k m g o -KMGT k m g t -KMIH k m i h -KMIR k m i r -KMITL k m i t l -KMJ k m j -K&M k and m -KMK k m k -km k m -K. M. k m -K.M. k m -KM k m -KMLA k m l a -KML k m l -KMME k m m e -KMML k m m l -KMRL k m r l -KMS k m s -KMSP k m s p -KMT k m t -KMTP k m t p -KMTV k m t v -KMVA k m v a -KMXW k m x w -KMZ k m z -KNFM k n f m -KNHP k n h p -K&N k and n -kn k n -K. N. k n -K.N. k n -KN k n -KNKT k n k t -KNLA k n l a -KNMI k n m i -KNNV k n n v -KNPN k n p n -KNPR k n p r -KNPU k n p u -KNRE k n r e -KNRS k n r s -KNS k n s -KNSM k n s m -KNST k n s t -KNTH k n t h -K.N.T. k n t -KNTN k n t n -KNTU k n t u -KNVA's k n v a's -KNVB k n v b -KNVN k n v n -KNX k n x -KNXT k n x t -K.O.D. k o d -k'o k o -K. O. k o -K.O. k o -KOTC k o t c -KOTD k o t d -K.O.T. k o t -KOWL k o w l -K. P. A. C. k p a c -KPAC k p a c -KPA k p a -KPAN k p a n -KPCC k p c c -KPC k p c -KPD k p d -KPE k p e -KPIF k p i f -KPI k p i -KPIs k p i's -K&P k and p -K. P. k p -K.P. k p -KP k p -KPLC k p l c -KPL k p l -KPLZ k p l z -KPMG k p m g -KPM k p m -KPNA k p n a -KPNB k p n b -KPO k p o -Kppen k p p e n -KPPV k p p v -KPS k p s -kptm k p t m -KPTV k p t v -KPU k p u -KPVD k p v d -KPVX k p v x -KPWR k p w r -KPXE k p x e -KQA k q a -KQED k q e d -KQHN k q h n -KQKK k q k k -KQKS k q k s -KQLT k q l t -KQLZ k q l z -KQMO k q m o -KQV k q v -KQXR k q x r -KRBM k r b m -krc k r c -KRCR k r c r -KRCs k r c's -KRF k r f -KRH k r h -K.R.I.T. k r i t -K.R.I.T.'s k r i t's -Krka k r k a -KRKC k r k c -KRK k r k -kr k r -K. R. k r -K.R. k r -KR k r -KRMT k r m t -Krne k r n e -KRNS k r n s -KRNV k r n v -KROQ k r o q -kroz k r o z -Kroz k r o z -KRPS k r p s -KRRT k r r t -K. R. S. k r s -KRS k r s -KRT k r t -Kru k r u -KRU k r u -KRWC k r w c -KRX k r x -K.R.Y. k r y -KRZA k r z a -ksa k s a -KSA k s a -K. S. B. k s b -KSBW k s b w -KSBY k s b y -KSCB k s c b -KSC k s c -KSCO k s c o -KSC's k s c's -KSCS k s c s -KSDB k s d b -KSDO k s d o -KSEB k s e b -KSEG k s e g -KSE k s e -KSEQ k s e q -kset k s e t -KSET k s e t -Kseur k s e u r -Ksevt k s e v t -KSFO k s f o -KSG k s g -KSHB k s h b -KSI's k s i's -KSJR k s j r -KSKJ k s k j -KSKK k s k k -K.S.K. k s k -KSK k s k -ks k s -K. S. k s -K.S. k s -KS k s -KSLC k s l c -KSL k s l -KSLM k s l m -KSLU k s l u -KSMB k s m b -KSNR k s n r -KSNV k s n v -KSP k s p -KSPS k s p s -KSTE k s t e -KSTH k s t h -KST k s t -KSTP k s t p -KSU k s u -K.S.V. k s v -KSWD k s w d -KSWT k s w t -KSWW k s w w -KSYL k s y l -KSZR k s z r -Ktav k t a v -KTAV k t a v -KTBS k t b s -KTCC k t c c -KTC k t c -KTCZ k t c z -KTDA k t d a -KTDD k t d d -KTE k t e -KTH k t h -KT&K k t and k -kt k t -K. T. k t -K.T. k t -KT k t -KTKZ k t k z -KTLA k t l a -K. T. M. k t m -KTM k t m -KTN k t n -KTOK k t o k -KTO k t o -KTRE k t r e -KTRH k t r h -KTRK k t r k -KTR k t r -KT's k t's -KTSM k t s m -KTT k t t -KTTN k t t n -KTTV k t t v -KTU k t u -KTUM k t u m -KTVA k t v a -KTVK k t v k -KTVS k t v s -KTVT k t v t -KTVU k t v u -KTVZ k t v z -KTWD's k t w d's -KTWO k t w o -KTX k t x -KTXL k t x l -Kuaa k u a a -Kud k u d -KUFM k u f m -KUGB k u g b -kuih k u i h -K. U. k u -K.U. k u -Kutb k u t b -KUTV k u t v -KUUU k u u u -KUWL k u w l -KUYI k u y i -KVAB k v a b -KVBC k v b c -KVB k v b -K.V.G.K. k v g k -KVHV k v h v -Kvik k v i k -KVI k v i -Kvit k v i t -KVIT k v i t -KVK k v k -K. V. k v -K.V. k v -KVLO k v l o -KVLY k v l y -KVM k v m -KVMRT k v m r t -KVMX k v m x -KVNG k v n g -KVN k v n -KVP k v p -KVTV k v t v -KVVS's k v v s's -KVVV k v v v -Kvyat k v y a t -KVZ k v z -kwa k w a -KWBM k w b m -KWC k w c -KWD k w d -KWEI k w e i -kwe k w e -KWG k w g -KWJJ k w j j -KWKH k w k h -KWKW k w k w -KWMR k w m r -KWMT k w m t -KWNA k w n a -KWNK k w n k -KWOA k w o a -KWP k w p -KWPT k w p t -KWQC k w q c -KWRE k w r e -KWRU k w r u -KWSB k w s b -KWSX k w s x -KWU k w u -KWWL's k w w l's -KXAN k x a n -KXAS k x a s -KXI k x i -KXJB k x j b -KXKS k x k s -KX k x -KXLX k x l x -KXLY k x l y -KXMC k x m c -KXNA k x n a -KXOL's k x o l's -KXTA k x t a -KXTN k x t n -KXTX k x t x -KYAY k y a y -KYBE k y b e -KYEZ k y e z -KYNM k y n m -Kyse k y s e -KYSL k y s l -KYTC k y t c -kyt k y t -Kyt k y t -KYW k y w -kz k z -K. Z. k z -KZ k z -KZLZ k z l z -KZMP k z m p -KZMU k z m u -KZQX k z q x -KZZQ k z z q -L. A. G. l a g -L. A. l a -L.A.'s l a's -Lay's l a y's -L.B.A. l b a -LBA l b a -LBCC l b c c -LBC l b c -LBC's l b c's -LBE l b e -LBF l b f -LBi l b i -LBJ l b j -LBJ's l b j's -L. B. l b -L.B. l b -LB l b -LBL l b l -LBM l b m -LBN l b n -LBNL l b n l -LBP l b p -LBPs l b p's -LBR l b r -LBS l b s -LBV l b v -LBW l b w -LCAC l c a c -LCA l c a -LCAs l c a's -LCAS l c a s -L.C.B. l c b -LCBL l c b l -LCBM l c b m -lcc l c c -LCC l c c -LCCN l c c n -LCCs l c c's -LCCS l c c s -LCDB l c d b -LCD l c d -LCDP l c d p -LC&DR l c and d r -LCDR l c d r -LCDs l c d's -L.C.E. l c e -LCFC l c f c -LCF l c f -LCH l c h -LCI l c i -LCIs l c i's -L. C. l c -L.C. l c -LC l c -LCL l c l -LCMC l c m c -LCM l c m -LCMR l c m r -LCMV l c m v -lcn l c n -LCO l c o -LCP l c p -LCQ l c q -LCR l c r -LCSB l c s b -LCSC l c s c -LC's l c's -LCS l c s -LCSs l c s's -LCST l c s t -LCT l c t -LCTs l c t's -LCU l c u -LCV l c v -LCVP l c v p -LCVPs l c v p's -LCZ l c z -Lda l d a -LDA l d a -LDAP l d a p -LDB l d b -LDBV l d b v -L.D.C. l d c -LDC l d c -LDCM l d c m -LDCs l d c's -LDD l d d -LDDP l d d p -LDF l d f -LDH l d h -L.D.I. l d i -LDK l d k -L. D. l d -L.D. l d -LDL l d l -LDLR l d l r -LDM l d m -LDMR l d m r -LDN l d n -LDP l d p -LDS l d s -LDU l d u -LDV l d v -LEB l e b -L. E. l e -L.E. l e -LFA l f a -L.F.C. l f c -LFC l f c -L.F.D. l f d -LFE l f e -LFFCs l f f c's -LFF l f f -LFG l f g -LFHC l f h c -LFH l f h -L. F. l f -L.F. l f -LFL l f l -LFM l f m -LFOC l f o c -LFO l f o -LFOM l f o m -LFPB l f p b -LFP l f p -LFQD l f q d -LFRJ l f r j -LFR l f r -LFs l f's -LFS l f s -LFSRs l f s r's -LFTR l f t r -LFXA l f x a -LGA l g a -LGB l g b -LGBTI l g b t i -LGBT l g b t -LGBTQ l g b t q -LGC l g c -LGD l g d -LGI l g i -L. G. l g -L.G. l g -LG l g -LGMB l g m b -LGMs l g m's -LGN l g n -LGPL l g p l -LGPZ l g p z -LG&RDD l g and r d d -LGR l g r -LGs l g's -LGS l g s -LGTB l g t b -LGT's l g t's -LGU l g u -LGUs l g u's -LGV l g v -LGVs l g v's -Lha l h a -LHB l h b -L. H. C. l h c -LHC l h c -LHD l h d -LHFP l h f p -LHICE l h i c e -LHI l h i -L. H. l h -L.H. l h -LHMC l h m c -L.H.M. l h m -LHO l h o -L. H. P. l h p -LHP l h p -LHS l h s -LHW l h w -LHX l h x -LHY l h y -L. I. l i -L.I. l i -LJBL l j b l -Lje l j e -LJJ l j j -L. J. K. l j k -L. J. l j -L.J. l j -L.J.V. l j v -LKB l k b -LKG l k g -LKK l k k -L. K. l k -LK l k -LKL l k l -LKML l k m l -LKPR l k p r -LKRN l k r n -lks l k s -LKS l k s -LKTI l k t i -Llapi l l a p i -LLAW l l a w -L.L.B. l l b -LLB l l b -LLCC l l c c -L.L.C. l l c -LLC l l c -LLD l l d -LL.D l l d -lle l l e -LLE l l e -LLHS l l h s -lli l l i -LLI l l i -L&L l and l -LLLE l l l e -L. L. l l -L.L. l l -LL l l -LLL l l l -LLLP l l l p -LLM l l m -LLMNR l l m n r -LLPFX l l p f x -llp l l p -LLP l l p -LLPX l l p x -LLRW l l r w -LLT l l t -LLTV l l t v -llu l l u -LLVM l l v m -LLWS l l w s -LMA l m a -LMC l m c -LMCT l m c t -LMDB l m d b -LMDC l m d c -LMD l m d -LME l m e -LMFAO's l m f a o's -LMFF l m f f -LMG l m g -LMGs l m g's -LMGTE l m g t e -LMH l m h -LMHS l m h s -lm l m -L. M. l m -L.M. l m -LM l m -LMM l m m -LMP l m p -LMPs l m p's -LMQ l m q -LMQs l m q's -L.M.S. l m s -LMS l m s -LMT l m t -LMTP l m t p -LMU l m u -LMWH l m w h -LMX l m x -LnAIB l n a i b -LNA l n a -LNAV l n a v -LNBF l n b f -LNB l n b -L.N.C. l n c -LNCS l n c s -L.N.E.R. l n e r -LNER l n e r -LNFS l n f s -LNG l n g -LNH l n h -L&N l and n -L. N. l n -L.N. l n -L.O.C.'s l o c's -Lokk l o k k -l'OL l o l -L.O.L. l o l -L. O. l o -L.O. l o -L.O.V.E. l o v e -L.O.V. l o v -LOXL l o x l -LPA l p a -L.P.A.M. l p a m -LPAM l p a m -LPARs l p a r's -LPAVS l p a v s -LPBG l p b g -L.P.B. l p b -LPB l p b -LPC l p c -LPCM l p c m -LPDA l p d a -LPDR l p d r -LPE l p e -LPF l p f -LPFM l p f m -LPGA l p g a -LPG l p g -L.P.H. l p h -LPH l p h -LPI l p i -LPLA l p l a -L&P l and p -LPL l p l -lp l p -L. P. l p -L.P. l p -LP l p -L&PM l and p m -LPMN l p m n -LPMud l p m u d -LPMUD l p m u d -LPN l p n -LPO l p o -LPRP l p r p -LPSC l p s c -LP's l p's -LPs l p's -LPS l p s -LPSN l p s n -LPTB l p t b -LPThe l p t h e -LPTV l p t v -LQ l q -LRAD l r a d -LRA l r a -LRCD l r c d -LRC l r c -L.R.C.P. l r c p -LRCP l r c p -LRDG l r d g -LRG l r g -lr l r -L. R. l r -L.R. l r -LR l r -LRO l r o -L.R.P.C. l r p c -LRP l r p -LRPPRC l r p p r c -LRRI l r r i -LRRP l r r p -LRS l r s -LRTA l r t a -LRT l r t -LRTR l r t r -LRTs l r t's -LRVs l r v's -LRY l r y -LSAC l s a c -LSA l s a -LSBC l s b c -LSB l s b -LSC l s c -LSCS l s c s -LSDHH l s d h h -L.S.D. l s d -LSD l s d -LSDP l s d p -LSDs l s d's -LSE l s e -LSF l s f -LSG l s g -LSH l s h -LSi l s i -LSI l s i -LSJ l s j -LSK l s k -L.S.L. l s l -ls l s -Ls l's -L. S. l s -L.S. l s -LSM l s m -LSO l s o -LSP l s p -LSPN l s p n -LSQC l s q c -LSRI l s r i -L. S. R. l s r -LSS l s s -LSSP l s s p -LSSR l s s r -LST l s t -LSTM l s t m -LSTs l s t's -LSUA l s u a -LSU l s u -LSU's l s u's -LSVCCs l s v c c's -LSV l s v -LSWR l s w r -LTAF l t a f -L. T. B. l t b -LTB l t b -LTCF l t c f -LTCI l t c i -L. T. C. l t c -L.T.C. l t c -LTC l t c -Ltda l t d a -LTDA l t d a -Ltd. limited -LTE l t e -LTFA l t f a -LTHS l t h s -LTI l t i -LTK l t k -L&T l and t -Lt. lieutenant -LTL l t l -lt l t -L. T. l t -L.T. l t -L.T.M. l t m -LTM l t m -LTMPS l t m p s -LTN l t n -ltoh l t o h -LTP l t p -LTRPC l t r p c -LTTE l t t e -LTTR l t t r -LTU l t u -LTV l t v -L. U. l u -lv l v -L. V. l v -L.V. l v -LV l v -LVMH l v m h -LWDB l w d b -LWD l w d -LWDS l w d s -LWE l w e -LWF l w f -LWH l w h -L. W. l w -L.W. l w -L.Y. l y -L&YR l and y r -M.A.D.E. m a d e -M.A.D. m a d -M.A.J. m a j -M.A.K. m a k -M. A. m a -M.A. m a -M&A m and a -M. A. O. m a o -M.A.O. m a o -M.A.R. m a r -M.A.S.K. m a s k -M.A.S. m a s -M.A.S.S. m a s s -M.B.A. m b a -M.B.B.S. m b b s -MBBS m b b s -MBC m b c -MBC's m b c's -MBDA m b d a -MBD m b d -M.B. D.P.M. m b d p m -M.B.E. m b e -MBE m b e -Mbewu m b e w u -MBF m b f -MBFW m b f w -MBGN m b g n -MBH m b h -mbi m b i -MBI m b i -M. B. J. m b j -MBJ m b j -MBK m b k -MBL m b l -M. B. m b -M.B. m b -MBM m b m -MBNA m b n a -mBo m b o -MBO m b o -MBPJ m b p j -MBP m b p -Mbre m b r e -mbr m b r -MBR m b r -MBSE m b s e -MBSI m b s i -MBS m b s -MBTI m b t i -MBT m b t -MBU's m b u's -MBX m b x -MCAF m c a f -MCAL m c a l -M.C.A. m c a -MCA m c a -MCA's m c a's -MCAS m c a s -MCB m c b -M. C. C. m c c -M.C.C. m c c -MCC m c c -MCC's m c c's -MCCs m c c's -MCCU m c c u -MCDA m c d a -MCDC m c d c -MCD m c d -MCDM m c d m -MCE m c e -MCFA m c f a -M. C. F. m c f -MCF m c f -MCFM m c f m -MCGJCW m c g j c w -MCG m c g -MCI m c i -MCJ m c j -MCLA m c l a -MCL m c l -M. C. m c -M.C. m c -MCMC m c m c -M. C. M. m c m -MCM m c m -MCN m c n -MCO m c o -MCOT's m c o t's -MCPC m c p c -MCPI m c p i -MCP m c p -MCPON m c p o n -MCPP m c p p -MCQ m c q -MCRD m c r d -MCR m c r -MCRP m c r p -MCSBA m c s b a -MCs m c's -M.C. S. m c s -MCS m c s -MCST m c s t -MCTFS m c t f s -MCT m c t -MCTU m c t u -MCTV m c t v -MCU m c u -MCV m c v -MCVTS m c v t s -MCW m c w -mcyG m c y g -MCYO m c y o -MCZ m c z -MDAA m d a a -MDAH m d a h -MDA m d a -mdb m d b -MDB m d b -MDC m d c -MDC's m d c's -MDCs m d c's -MDCT m d c t -mdDA m d d a -MD&DI m d and d i -Mde m d e -MDE m d e -MDF m d f -MDG m d g -MDGs m d g's -MDH m d h -MDHUs m d h u's -mDia m d i a -MDIB m d i b -MDic m d i c -MDI m d i -MDJT's m d j t's -MDK m d k -mdla m d l a -MDL m d l -MDMA m d m a -md m d -M. D. m d -M.D. m d -MD m d -MDM m d m -MDNA m d n a -M.D.N. m d n -MDPD's m d p d's -MDP m d p -MDPPP m d p p p -MDPS m d p s -MDPV m d p v -MDQ m d q -MDRC m d r c -mdr m d r -MDR m d r -MDT m d t -MDV m d v -MDX m d x -M. E. m e -M.E. m e -M.E.N. m e n -M. E. P. m e p -M.F.A. m f a -MFA m f a -MFB m f b -MFCC m f c c -MFC m f c -MFCS m f c s -MFD m f d -MFDs m f d's -MFe m f e -MFF m f f -MFG m f g -MFI m f i -MFJ m f j -MFK m f k -M. F. m f -M.F. m f -MFMF m f m f -MFM m f m -MFN m f n -MFNW m f n w -MFP m f p -MFR m f r -MFS m f s -MFS's m f s's -MFTBC m f t b c -MFT m f t -MFTs m f t's -Mgadla m g a d l a -Mgal m g a l -mga m g a -Mga m g a -MGA m g a -MGB m g b -Mgbo m g b o -MGCCC m g c c c -MGC m g c -MGE m g e -MGen m g e n -MGG m g g -MGH m g h -MGIMO m g i m o -MGIT m g i t -MGJH m g j h -MGK m g k -M.G.L. m g l -M&G m and g -M. G. m g -M.G. m g -M. G. M. m g m -MGM m g m -MGM's m g m's -MGMT m g m t -M&GN m and g n -MGN m g n -MGO m g o -MGP m g p -M&GR's m and g r's -Mha m h a -M.H.A. m h a -MHA m h a -MHB's m h b's -MHC m h c -MHCs m h c's -MHD m h d -MHI m h i -MHK m h k -MH&L m h and l -MHL m h l -M&H m and h -M. H. m h -M.H. m h -Mhor m h o r -Mhow m h o w -MHPL m h p l -M.H.P. m h p -MHP m h p -MHP's m h p's -MHRA m h r a -M. H. R. m h r -MHSA m h s a -MHSC m h s c -MHS m h s -MHT m h t -M.I.A. m i a -M.I.A.'s m i a's -M.I.C.M. m i c m -M.I.H. m i h -M&I m and i -M. I. m i -M.I. m i -M.I.N. m i n -M.I.R.V. m i r v -M.I.S. m i s -M.I.T. m i t -MJAHL's m j a h l's -M.J.A. m j a -MJA m j a -MJBHA m j b h a -MJB m j b -MJC m j c -M.J.F. m j f -MJF m j f -MJG m j g -MJHL m j h l -MJHL's m j h l's -M&J m and j -M. J. m j -M.J. m j -M. J. Y. m j y -MKBHD m k b h d -MKB m k b -MKDE m k d e -MKE m k e -MKFM m k f m -MKG m k g -MKK m k k -MKMF m k m f -M. K. m k -M.K. m k -MKNG m k n g -MKP m k p -MKRN m k r n -MKs m k's -MKS m k s -MKT m k t -MKTO m k t o -MKTV m k t v -MKZ's m k z's -M.L.A. m l a -MLA m l a -MLANA m l a n a -MLAs m l a's -MLB m l b -MLBPA m l b p a -MLCA m l c a -mlc m l c -M.L.C. m l c -MLC m l c -MLCs m l c's -MLD m l d -MLE m l e -MLF m l f -mlg m l g -MLG m l g -MLH m l h -MLIA m l i a -mli m l i -MLI m l i -MLIM m l i m -MLK m l k -MLK's m l k's -Mlle m l l e -MLL m l l -MLLT m l l t -M&L m and l -M. L. m l -M.L. m l -MLM m l m -MLND m l n d -M.L.N. m l n -MLN m l n -MLPH m l p h -MLP m l p -MLPs m l p's -M. L. R. m l r -MLR m l r -MLSE m l s e -M. L. S. m l s -M.L.S. m l s -MLS m l s -MLT m l t -MLW m l w -MLWS m l w s -MM&A m m and a -M. M. J. m m j -MMK m m k -MML m m l -M&M m and m -M. M. m m -M.M. m m -MMSA m m s a -M&M's m and m's -M. M. S. m m s -MMS m m s -MMST m m s t -MMTB's m m t b's -MMTS m m t s -MMTV m m t v -MMWR m m w r -MMX m m x -MNA m n a -MNBA m n b a -MNC m n c -MNCPPC m n c p p c -MNCs m n c's -MNDM m n d m -MNDNR m n d n r -MNDO m n d o -MNDR m n d r -M&NF m and n f -MNF m n f -MNG m n g -MNI m n i -MNLA m n l a -MNLA's m n l a's -MNLF m n l f -MNM m n m -M. N. m n -M.N. m n -MNNA m n n a -MNN m n n -MNP m n p -MNPP m n p p -MNRG m n r g -MNSD m n s d -MNS m n s -MNTC m n t c -MNT m n t -MNZM m n z m -MNZ m n z -MOBKL m o b k l -MOBK m o b k -M.O.B. m o b -M.O.D. m o d -M.O.D.O.K. m o d o k -M.O.G.U.E.R.A.'s m o g u e r a's -M. O. H. m o h -M. O. m o -M.O. m o -M.O.P. m o p -M.O.R. m o r -M.O.T. m o t -MPAA m p a a -MpA m p a -MPA m p a -MPAs m p a's -MPB m p b -MPBN m p b n -MPBu m p b u -MPCA m p c a -MPCI m p c i -MPC m p c -MPD m p d -MPE m p e -MPF m p f -MPG m p g -M.P.H. m p h -MPH m p h -MP&I m p and i -MPi m p i -MPI m p i -MPIO m p i o -MPKAB m p k a b -MPLAD m p l a d -MPLA m p l a -MPL m p l -MPLMs m p l m's -MPLR m p l r -MPLS m p l s -M&P m and p -MPM m p m -M. P. m p -M.P. m p -MPO m p o -MPPJ m p p j -M.P.P. m p p -MPP m p p -MPPSC m p p s c -MPPs m p p's -MPQC m p q c -MPR m p r -MPRO m p r o -MPRP m p r p -MPRS m p r s -MPSE m p s e -MPSF m p s f -M.P.'s m p's -MP's m p's -MPs m p's -MPS m p s -MPThe m p t h e -MPT m p t -Mpu m p u -MPU m p u -MPV m p v -MPW m p w -MPZ m p z -MQM m q m -M. Q. m q -Mra m r a -MRA m r a -M. R. B. m r b -MRB m r b -MRBs m r b's -MRCB m r c b -MRCK m r c k -MRCM m r c m -MRC m r c -M.R.C.S. m r c s -MRCS m r c s -MRDC m r d c -MRD m r d -mre m r e -MRF m r f -MR&LE m r and l e -MRL m r l -Mr. mister -MRM m r m -M. R. m r -M.R. m r -mRNA m r n a -mRNAs m r n a's -MRPGM m r p g m -MRP m r p -MRPS m r p s -MRR m r r -MRSA m r s a -M.R.S.C. m r s c -Mrs. misses -MRSM m r s m -MRT m r t -MRTs m r t's -MRTS m r t s -MRTT m r t t -MRU m r u -MSAA m s a a -MSAC m s a c -MSAD m s a d -MSA m s a -M.S.A.S. m s a s -MSAW m s a w -MSB m s b -MSBO m s b o -MSBSD m s b s d -MSCC m s c c -M.S.C. m s c -MSC m s c -msd m s d -MSD m s d -MSDN m s d n -MSDS m s d s -Mse m s e -MSFC m s f c -M.S.F. m s f -MSF m s f -MSFT m s f t -MSG m s g -MSI m s i -MSJ m s j -MSK m s k -MSL m s l -M&S m and s -Ms. miss -MSML m s m l -M.S.M. m s m -MSM m s m -M. S. m s -M.S. m s -MSNBC m s n b c -MSNBC's m s n b c's -MSN m s n -MSOB m s o b -MSOM m s o m -M.S.P. m s p -MSP m s p -MSPs m s p's -MSR m s r -MSRP m s r p -MSRTC m s r t c -MSSH m s s h -MSSK m s s k -MSSMLP m s s m l p -MSSM m s s m -MSS m s s -MSTA m s t a -mst m s t -MST m s t -MSTS m s t s -MSU's m s u's -MSVCC m s v c c -MSV m s v -MSVU m s v u -MSX m s x -MSY m s y -MSZP m s z p -MTAC m t a c -Mta m t a -M.T.A. m t a -MTA m t a -MTA's m t a's -MTAs m t a's -MTBE m t b e -MTBI m t b i -MTB m t b -MTC m t c -MTDB m t d b -M.T.D. m t d -MTD m t d -MTD's m t d's -MTG m t g -MTHFR m t h f r -MTHL m t h l -MTIC m t i c -MTI m t i -MTJ m t j -MTK m t k -MTKO m t k o -M&T m and t -MTM m t m -MTMR m t m r -M. T. m t -M.T. m t -Mtor m t o r -MTOSI m t o s i -M.T.O.W. m t o w -MTPA m t p a -MTPC m t p c -MTP m t p -MTQ m t q -MTRCB m t r c b -MTRC m t r c -MTRJ m t r j -MTR m t r -M. T. S. m t s -MTS m t s -MTSU m t s u -MTTM m t t m -MTT m t t -MTU m t u -MTV m t v -MTVR m t v r -MTV's m t v's -mtvU m t v u -MTVu m t v u -MTVU m t v u -MTY m t y -MTZ m t z -MUKW m u k w -M. U. m u -MUSL m u s l -M.U.s m u's -M. U.S. m u s -MVA m v a -M. V. C. m v c -M.V.C. m v c -MVC m v c -M. V. D. m v d -MVD m v d -MVH m v h -MVK m v k -M.V.M. m v m -MVM m v m -MVMs m v m's -M. V. m v -M.V. m v -M.V.O. m v o -MVO m v o -MVP m v p -MVPs m v p's -MVPS m v p s -M.V. P.T. m v p t -MVs m v's -MVS m v s -MVSN m v s n -MVSR m v s r -MVT m v t -MVV m v v -M.W.A.M. m w a m -MWA m w a -MWC m w c -MWe m w e -M. W. E. m w e -MWF m w f -MWHL m w h l -MWIFF m w i f f -MWI m w i -MWJCHL m w j c h l -MWJHL m w j h l -M. W. J. m w j -M. W. m w -M.W. m w -M. X. m x -myb m y b -myc m y c -Myc m y c -MYC m y c -MYCN m y c n -MyDD m y d d -M. Y. m y -M.Y. m y -MySQL m y s q l -MYSQL m y s q l -MZC m z c -MZH m z h -MZM m z m -M. Z. m z -MZP m z p -MZT m z t -NAACCR n a a c c r -NAACL n a a c l -NAAC n a a c -N.A.A.C.P. n a a c p -NAACP n a a c p -NAACP's n a a c p's -N.A.C.L. n a c l -NAFBL n a f b l -NAFC n a f c -NAFC's n a f c's -NAFH n a f h -NAFI n a f i -N. A. n a -N.A. n a -NBADL n b a d l -N.B.A. n b a -NBA n b a -N.B.A.'s n b a's -NBA's n b a's -NBAs n b a's -NBCC n b c c -NBC n b c -NBC's n b c's -NBCSN n b c s n -NBDL n b d l -NBD n b d -NBFA's n b f a's -NBF n b f -NBG n b g -NBI n b i -NBK n b k -NBL n b l -N. B. n b -N.B. n b -N.B.N. n b n -NBN n b n -NBP n b p -NBQ n b q -NBR n b r -NBR's n b r's -NBSK n b s k -nbs n b s -NBS n b s -NBSP n b s p -NBTE n b t e -NBT n b t -NBTwo n b t w o -NBTY n b t y -NBW n b w -NCAAs n c a a's -NCAM n c a m -NCA n c a -NCAP n c a p -NCBC n c b c -NCBI n c b i -NCCC n c c c -NCCF n c c f -NCCMH n c c m h -NCC n c c -NCCP n c c p -NCCs n c c's -NCCS n c c s -NCCU n c c u -NCDC n c d c -NCDD's n c d d's -NCD n c d -NCES n c e s -NCFA n c f a -N.C.F. n c f -NCF n c f -NCG n c g -NCGS n c g s -NCHC n c h c -NCH n c h -NCHU n c h u -NCID n c i d -NCI n c i -NCIS n c i s -NCIS's n c i s's -NCKU n c k u -NCLB n c l b -NCLC n c l c -NCL n c l -NCLR n c l r -NCLT n c l t -NCMA n c m a -NCMC n c m c -NCMM n c m m -NCM n c m -NCMP n c m p -NCNB n c n b -N. C. n c -N.C. n c -N.C.O. n c o -NCO n c o -NCO's n c o's -NCOs n c o's -NCPA n c p a -NCPC n c p c -NCP n c p -NCPO n c p o -NCRC n c r c -NCR n c r -NCSU n c s u -NCSY n c s y -NCTA n c t a -NCTC n c t c -NCTE n c t e -NCT n c t -NCUA n c u a -NCVO n c v o -NCVS n c v s -NCVT n c v t -NCWM n c w m -NCW n c w -NDA n d a -NDE n d e -NDEP n d e p -NDFB n d f b -NDFT n d f t -N.D.G. n d g -N. D. n d -N.D. n d -N.D.N.Y. n d n y -NDPH n d p h -NDPK n d p k -N.D.P. n d p -NDP n d p -NDP's n d p's -NDRC n d r c -NDRE n d r e -NDRF n d r f -N.E.A.R. n e a r -NECW n e c w -N. E. n e -N.E. n e -N.E.R.D. n e r d -NERFU n e r f u -ner n e r -N.E.R. n e r -NER n e r -N.E.W.S.T. n e w s t -NFA n f a -NFATc n f a t c -NFAT n f a t -NFB n f b -NFB's n f b's -NFC n f c -NFC's n f c's -NFD n f d -NFEA n f e a -nfed n f e d -NFFC n f f c -NFF n f f -NFH n f h -NFHS n f h s -NFIB n f i b -NFI n f i -NFISD n f i s d -N.F.L. n f l -NFL n f l -NFLPA n f l p a -NFL's n f l's -N. F. n f -N.F. n f -NFO n f o -NFPA n f p a -NFPF n f p f -NFP n f p -NFPW n f p w -NFRS n f r s -NFS n f s -NGC n g c -Nge n g e -NGF n g f -N.G.L. n g l -N. G. n g -N.G. n g -NGO n g o -NGO's n g o's -NGOs n g o's -NGRC n g r c -N.G.R. n g r -NGR n g r -NGRR n g r r -NGS n g s -NGSS n g s s -NGST n g s t -NGTC n g t c -Nha n h a -NHA n h a -NHCEs n h c e's -NHC n h c -NHCP n h c p -NHCs n h c's -NHD n h d -NHHD n h h d -NHHI n h h i -nhi n h i -NHI n h i -NHK n h k -NHK's n h k's -N.H.L. n h l -NHM&W n h m and w -N. H. n h -N.H. n h -NHP n h p -NHPs n h p's -NHPS n h p s -NHRA n h r a -NHRC n h r c -NHSCT n h s c t -NHS n h s -NHST n h s t -NHW n h w -N.I.B.B.L.E. n i b b l e -NIBC n i b c -NIBR n i b r -N. I. n i -N.I. n i -N'I n i -N.J.A.C. n j a c -N. J. A. n j a -NJA n j a -N. J. C. n j c -NJC n j c -NJIT n j i t -N. J. M. n j m -NJM n j m -N. J. n j -N.J. n j -NJN n j n -Njoo n j o o -NJPS n j p s -NJPW n j p w -N.J.S.A. n j s a -N.J.'s n j's -NKL n k l -N. K. n k -N.K. n k -N. K. N. n k n -NKP n k p -NKP's n k p's -NKR n k r -NKT n k t -NKU n k u -nkvd n k v d -NKVD n k v d -NKVM n k v m -nkv n k v -NKX n k x -NLAES n l a e s -NLAI n l a i -NLA n l a -NLB n l b -NLCF n l c f -NLC n l c -NLCS n l c s -NLDC n l d c -NLD n l d -NLD's n l d's -NLDS n l d s -N. L. n l -N.L. n l -NLP n l p -NLRB n l r b -NLRP n l r p -NLRs n l r's -NLW n l w -NLX n l x -NMAA n m a a -NMA n m a -NMBS n m b s -NMBU n m b u -NMCA n m c a -NMCB n m c b -NMC n m c -N. M. n m -N.M. n m -NMP n m p -NMR n m r -NMRW n m r w -NMT n m t -NMU n m u -NMV n m v -NMW n m w -NNCL n n c l -NNFL n n f l -NNF n n f -N. N. n n -N.N. n n -NNSA n n s a -NNSS n n s s -NNSU n n s u -NNSW n n s w -N.O.R. n o r -NPA n p a -NPBD n p b d -NPBL n p b l -NPB n p b -NPC n p c -NPCs n p c's -NPDC n p d c -NPD n p d -NPF n p f -NPF's n p f's -NPGL n p g l -NPG n p g -NPGS n p g s -NPH n p h -NPHS n p h s -NPIM n p i m -NPI n p i -NPJ n p j -NPK n p k -NPL n p l -NPMA n p m a -NPM n p m -NPMs n p m's -N. P. n p -N.P. n p -NP n p -NPO n p o -NPP n p p -NPP's n p p's -NPRL n p r l -NPRN n p r n -NPR n p r -NPRR n p r r -NPR's n p r's -NPRSO n p r s o -NPSC n p s c -NPSG n p s g -NPSL n p s l -NP's n p's -NPs n p's -NPS n p s -NPTI n p t i -NPT n p t -NPV n p v -NPWE n p w e -NPWS n p w s -NPY n p y -NQAI n q a i -NQEA n q e a -NQHS n q h s -N. Q. n q -nri n r i -Nri n r i -NRI n r i -NRIs n r i's -NRJ n r j -NRJs n r j's -NRK n r k -NRLA n r l a -NRL n r l -NRL's n r l's -NRMA n r m a -NRM n r m -NRN n r n -nr n r -N. R. n r -N.R. n r -N.R.A. n r a -NSA n s a -NSAP n s a p -NSA's n s a's -NSB n s b -NSC n s c -NSD n s d -NSE n s e -NSFE n s f e -NSF n s f -NSFW n s f w -NSG n s g -NSI n s i -NSL n s l -NSM n s m -NSN n s n -N. S. n s -N.S. n s -NSO n s o -NSOs n s o's -NSPCC n s p c c -NSPC n s p c -NSP n s p -NSRI n s r i -NSRL n s r l -NSR n s r -NSSCD n s s c d -NSSDC n s s d c -NSS n s s -NSTA n s t a -NST n s t -NSU n s u -NSV n s v -NSVT n s v t -NSWBLF n s w b l f -NSWC n s w c -NSWCV n s w c v -NSWEC n s w e c -NSWGR n s w g r -N.S.W. n s w -NSW n s w -Nta n t a -NTA n t a -NTA's n t a's -ntb n t b -NTB n t b -NTC n t c -NTD n t d -NTFL n t f l -NTF n t f -NTI n t i -NTKF n t k f -NTL n t l -N. T. n t -N.T. n t -NTR n t r -NTR's n t r's -NTSB n t s b -NTSB's n t s b's -NTSC n t s c -NTS n t s -NTTF n t t f -NTT n t t -NTTR n t t r -NTUC n t u c -NTU n t u -NTVB n t v b -NTV n t v -ntw n t w -N.U. n u -NVA n v a -NVAO n v a o -NVC n v c -NVDA n v d a -NvDA's n v d a's -NVFC n v f c -NVGOP n v g o p -NVHJ's n v h j's -NVH n v h -NVI n v i -NVL n v l -N. V. n v -N.V. n v -NWAFU n w a f u -nwa n w a -N.W.A. n w a -NWA n w a -NWA's n w a's -N.W.F.P. n w f p -NWFP n w f p -NWMP n w m p -N&W n and w -NWN n w n -N. W. n w -N.W. n w -NWPD n w p d -N.W.P. n w p -NWP n w p -NWS n w s -N.W.T. n w t -NWT n w t -nyc n y c -N.Y.C. n y c -NYC n y c -NYC's n y c's -N.Y. G.O.P. n y g o p -N.Y.L. n y l -N. Y. n y -N.Y. n y -N.Y.P.D. n y p d -NYPD n y p d -NYPD's n y p d's -NYPL n y p l -N.Y.P. n y p -NY's n y's -N.Y.S. n y s -N.Y.S.V. n y s v -N.Y.U. n y u -NYU n y u -NYU's n y u's -NYYC n y y c -NZAID n z a i d -NZAOD n z a o d -NZCA n z c a -NZDT n z d t -NZEF n z e f -NZETC n z e t c -NZFC n z f c -NZF n z f -N'Zif n z i f -NZiK n z i k -N'Zi n z i -NZIV n z i v -NZL n z l -NZLP n z l p -N.Z. n z -NZPA n z p a -NZSAS n z s a s -NZ's n z's -NZS n z s -NZTA n z t a -N.Z.W.P.W. n z w p w -O.A.C. o a c -O. A. o a -O.A. o a -O.A.R. o a r -O.A.S. o a s -O.B.E. o b e -obl o b l -Oblt o b l t -O.B. o b -O. C. o c -O.C. o c -Octl o c t l -O.C.T. o c t -O. D. o d -O.E. o e -O.F.M. o f m -O.F. o f -ofr o f r -O.F.R. o f r -OFR o f r -O.F.T.B. o f t b -OGL o g l -O&G o and g -O. G. o g -O.G. o g -O.G.S. o g s -OGS o g s -O.H.A. o h a -O. H. o h -O.H. o h -OHV o h v -O. I. o i -O.I. o i -O. J. o j -O.J. o j -OJ o j -OJSC o j s c -OKBM o k b m -OKB o k b -OKC o k c -OK'd o k d -OKd o k d -OKD o k d -oke o k e -Oke o k e -OKH o k h -O.K.I. o k i -OKK o k k -OKM o k m -O&K o and k -O. K. o k -O.K. o k -O.L.F.A.L. o l f a l -O. L. K. o l k -O. L. o l -O.L. o l -Olo o l o -Olov o l o v -OLPC o l p c -OLPH o l p h -ols o l s -OLs o l's -OLS o l s -OLSR o l s r -OLTL o l t l -OLVT o l v t -olvwm o l v w m -olwm o l w m -OMB o m b -OMC o m c -OMCS o m c s -OMD o m d -O&MFL o and m f l -OMF o m f -omg o m g -OMG o m g -OMGs o m g's -O. M. o m -O.M. o m -OmOm o m o m -Om's o m's -OMTP o m t p -OMVG o m v g -OMW o m w -OMX o m x -ONCHR o n c h r -ONC o n c -oncu o n c u -ONDH o n d h -ond o n d -onf o n f -ONF o n f -ONGC o n g c -ONIR o n i r -ONJSC o n j s c -ONM o n m -ONMR o n m r -O. N. o n -O.N. o n -O&O o and o -OOOA o o o a -O. O. o o -O.O. o o -OO o o -OOO's o o o's -Oop o o p -OOP o o p -OOPSLA o o p s l a -oor o o r -oose o o s e -Oo's o o's -OOTP o o t p -Ootw o o t w -OOUR o o u r -OPAC o p a c -OPAG o p a g -O.P.A. o p a -OPBF o p b f -OPB o p b -OPC o p c -OPCS o p c s -OPCW o p c w -OPD o p d -O.P.I. o p i -OPIRG o p i r g -OPJHL o p j h l -OPLC o p l c -OPL o p l -OPMB o p m b -OPM o p m -OPMs o p m's -OPN o p n -O. P. o p -O.P. o p -opr o p r -Opr o p r -OPR o p r -O.R.C. o r c -ORECA o r e c a -ORFs o r f's -ORMO o r m o -ORNL o r n l -OR&N o r and n -O. R. o r -osaa o s a a -OSAA o s a a -osa o s a -Osa o s a -O.S.A. o s a -OSA o s a -O.S.B. o s b -OSB o s b -OSBs o s b's -O.S.N. o s n -OSN o s n -O. S. o s -O.S. o s -OSP o s p -OSR o s r -OSTM o s t m -O.S.T. o s t -OSTP o s t p -OSTs o s t's -osv o s v -OSV o s v -OTB o t b -OTC o t c -OTJ o t j -OTL o t l -OTMH o t m h -OTO o t o -O.T. o t -OTP o t p -OTR o t r -OTs o t's -OTS o t s -Otu o t u -OTU o t u -otv o t v -O.U. o u -OU o u -OUP o u p -OUSA o u s a -OVA's o v a's -ovca o v c a -Ovca o v c a -OVC o v c -OVC's o v c's -Ovda o v d a -OVF o v f -OVM o v m -Ovo o v o -OVO o v o -ov o v -Ov o v -O. V. o v -O.V. o v -OV o v -OVP o v p -OVS o v s -OVT o v t -OVW o v w -O.W.A. o w a -OWBT o w b t -OWCs o w c's -OWGR o w g r -OWHA's o w h a's -OWIU o w i u -OWM o w m -O. W. o w -O.W. o w -P. A. C. p a c -P. A. J. p a j -P.A.J. p a j -P. A. M. p a m -P.A.M. p a m -pa p a -P. A. p a -P.A. p a -PA p a -PAQ p a q -P.A.R. p a r -P. A. S. p a s -PBAA p b a a -PBA p b a -PBA's p b a's -PBB p b b -PBCC p b c c -pBCE p b c e -pbc p b c -P.B.C. p b c -PBF p b f -PBG p b g -PBIL p b i l -PBI p b i -PBK p b k -PBL p b l -PBM p b m -PBMR p b m r -PBO p b o -pb p b -P. B. p b -P.B. p b -PB p b -PBP p b p -PBR p b r -PBS p b s -PBT p b t -PBX p b x -PBY p b y -P. C. A. p c a -PCA p c a -PCB p c b -PCB's p c b's -PCBs p c b's -PCBS p c b s -PCC p c c -PCCS p c c s -PCCW p c c w -PCCW's p c c w's -PCDDs p c d d's -PCDHB p c d h b -PCDH p c d h -PCD p c d -PCE p c e -PCeU p c e u -PCFCL p c f c l -PCFL p c f l -PCF p c f -PCFS p c f s -PCG p c g -PCGS p c g s -PCHA p c h a -PCHA's p c h a's -P.C.H. p c h -PCH p c h -PCHR p c h r -PCIe p c i e -pci p c i -PCI p c i -PCJHL p c j h l -P. C. J. p c j -PCJ p c j -PCK p c k -PCLM p c l m -pcl p c l -PCL p c l -PCMCIA p c m c i a -PCMNO p c m n o -PCM p c m -PCMS p c m s -PCNA p c n a -PCN p c n -PcoA p c o a -PCOE p c o e -PCO p c o -pc p c -P. C. p c -P.C. p c -PC p c -PCPFL p c p f l -PCP p c p -PCPV p c p v -PCRC p c r c -PCRE p c r e -PCRev p c r e v -PCRM p c r m -PCR p c r -PCSK p c s k -PCSOM p c s o m -pcs p c s -P.C.s p c's -PC's p c's -PCTL p c t l -PCT p c t -PCTV p c t v -PCU p c u -PCU's p c u's -PCW p c w -PCX p c x -pDAB p d a b -PDAB p d a b -PDA p d a -PDAs p d a's -PDBML p d b m l -PDB p d b -pdbp p d b p -PDBsum p d b s u m -PDCI p d c i -PDC p d c -PDCPD p d c p d -PDC's p d c's -PDCs p d c's -PD&D p d and d -PDD p d d -PDE p d e -PDEs p d e's -PDES p d e s -pdf p d f -PDF p d f -PDFs p d f's -PDFT p d f t -PDGF p d g f -PDG p d g -PDHJ p d h j -PDH p d h -PDI p d i -PDJ p d j -PDK p d k -PDL p d l -PDN p d n -PDO p d o -P&D p and d -P. D. p d -P.D. p d -PD p d -PDP p d p -PDP's p d p's -PDPs p d p's -P. D. Q. p d q -PDR p d r -PDSA p d s a -PDSI p d s i -PD's p d's -PDs p d's -P.D.S. p d s -PDS p d s -PDSP p d s p -PDT p d t -P.E.I. p e i -P.E.I.'s p e i's -P.E.N. p e n -P. E. p e -P.E. p e -P.F.L. p f l -PF's p f's -PFs p f's -PFS p f s -PFU p f u -PFV p f v -PFW&C p f w and c -P.G.A. p g a -PGA p g a -PGM p g m -PGMs p g m's -PG&N p g and n -P&G p and g -P. G. p g -P.G. p g -P.G.T. p g t -PHD p h d -P. H. G. p h g -PHH p h h -PHHS p h h s -PHLF p h l f -Phlo p h l o -PHL p h l -PHN p h n -P&H p and h -P. H. p h -P.H. p h -php p h p -PHP p h p -PHPs p h p's -P.I.D.E. p i d e -P&I p and i -P. I. p i -P.I. p i -P. I. W. p i w -Piz p i z -PJB p j b -PJC p j c -PJD p j d -P. J. F. p j f -P.J.K. p j k -pj p j -P. J. p j -P.J. p j -PJ p j -PJ's p j's -PJs p j's -P.J.T. p j t -P. K. p k -P.K. p k -PK p k -PLCC p l c c -plc p l c -PLC p l c -PLC's p l c's -PLCs p l c's -P.L.O. p l o -P. L. p l -P.L. p l -PLP p l p -PLX p l x -P. M. A. p m a -PMC p m c -PMG p m g -PML p m l -PMLP p m l p -PMMA p m m a -PMMoV p m m o v -PMM p m m -PMMS p m m s -PMMT p m m t -PMOI p m o i -PMO p m o -PMPC p m p c -PMPF p m p f -p.m. p m -p.m p m -P. M. p m -P.M. p m -PM p m -PMP p m p -PMP's p m p's -PMRN p m r n -PMRO p m r o -PMR p m r -PMRR p m r r -PMSE p m s e -PMSL p m s l -PMSM p m s m -PM's p m's -PMs p m's -P. M. S. p m s -PMS p m s -PMSSY p m s s y -PMT p m t -PMVY p m v y -PMWA p m w a -PNaCl p n a c l -pna p n a -PNA p n a -Pnau p n a u -pnb p n b -PNB p n b -PNC p n c -PNE p n e -PNE's p n e's -PNEs p n e's -PNETs p n e t's -pneus p n e u s -PNFA p n f a -PNF p n f -PNGIA p n g i a -png p n g -PNG p n g -PNH p n h -PNI p n i -PNL p n l -PNL's p n l's -PNMT p n m t -PNNL p n n l -PNNs p n n's -PNoy p n o y -pn p n -P. N. p n -P.N. p n -PN p n -PNP p n p -P.N.R.A. p n r a -P.O.D. p o d -P.O.D.'s p o d's -P&O p and o -P. O. p o -P.O. p o -P.O.S. p o s -P.O.V. p o v -P.O.W. p o w -P.O.W.'s p o w's -PPACA p p a c a -PPA p p a -PPBS p p b s -PPC p p c -PPD p p d -PPE p p e -PPF p p f -PPG p p g -P&PH p and p h -PPH p p h -PPi p p i -P.P.I. p p i -PPI p p i -PPJ p p j -PPKM p p k m -PPK p p k -PPL p p l -PPM p p m -PPNB p p n b -PPN p p n -PPO p p o -P. P. p p -P.P. p p -PPRP p p r p -PPR p p r -PP's p p's -PPS p p s -PPT p p t -PPTV p p t v -PPV p p v -PPVs p p v's -PPy p p y -PQDT p q d t -PQ p q -PQQ p q q -PQ's p q's -PQS p q s -PRB p r b -PRCA p r c a -PRC p r c -PRCS p r c s -PRDM p r d m -PRD p r d -PRD's p r d's -P.R.I.M.E. p r i m e -pr p r -P. R. p r -P.R. p r -PR p r -P.S.A. p s a -P.S.C. p s c -P.S.K. p s k -PSP p s p -P. s p's -P.'s p's -Ps p's -P. S. p s -P.S. p s -PSQL p s q l -PSR p s r -PSRU p s r u -PSSA p s s a -PSSA's p s s a's -PSSAs p s s a's -PSSI p s s i -PSS p s s -PSS's p s s's -PST p s t -PSU p s u -PSV p s v -PSW p s w -pTA p t a -PTA p t a -PTA's p t a's -PTAs p t a's -PTB p t b -PTBT p t b t -PTCH p t c h -PTC p t c -Pte p t e -PTEs p t e's -PTFE p t f e -ptf p t f -PTF p t f -PTH p t h -Ptie p t i e -PTI p t i -PTI's p t i's -PTK p t k -PTLLS p t l l s -PTL p t l -PTLs p t l's -PTNNT p t n n t -Ptol p t o l -PTO p t o -PTPN p t p n -PTP p t p -pt p t -P. T. p t -P.T. p t -PT p t -PTSD p t s d -PTSE p t s e -PTS p t s -PTTGC p t t g c -PTTG p t t g -PTTOW p t t o w -PTT p t t -PTTs p t t's -PTUN p t u n -PTV p t v -PTV's p t v's -P'Twa p t w a -PTY p t y -P.U.F. p u f -Puiu p u i u -PUKKE p u k k e -PUK p u k -Pul p u l -P. U. M. p u m -PVA p v a -PVAs p v a's -PVB p v b -P.V.C. p v c -PVC p v c -PvdA p v d a -PVEM p v e m -pve p v e -PVH p v h -P.V.L. p v l -PVL p v l -PVN p v n -PVO p v o -PVP p v p -P. V. p v -P.V. p v -PV p v -pvr p v r -PVR p v r -PVRS p v r s -PVs p v's -PVS p v s -PVU p v u -PWA p w a -PWB p w b -PWC p w c -PWD p w d -PWF p w f -P. W. G. p w g -P.W.G. p w g -PWG p w g -PWI p w i -pwll p w l l -PWM p w m -P.W.O. p w o -P&W p and w -P. W. p w -P.W. p w -PW p w -Pyi p y i -PYI p y i -Pyk p y k -PYK p y k -Pyl p y l -PyL p y l -PYP p y p -P. Y. p y -Pyu p y u -Pyw p y w -Pyx p y x -PZB p z b -PZL p z l -PZP p z p -P. Z. p z -Q. A. P. q a p -QAP q a p -Q. A. q a -QA q a -Q&A q and a -Q&A's q and a's -Q&As q and a's -QbA q b a -QBE q b e -QBH q b h -QBL q b l -Q.B. q b -QB q b -Q.C.B. q c b -QCD q c d -Q.C. q c -QD q d -QDS q d s -QEA q e a -QEC q e c -Q.E.D. q e d -QED q e d -Q.E.H. q e h -Q. E. q e -Q.H.C. q h c -QHP q h p -Q.H. q h -Q.I. q i -Q. J. q j -QJ q j -Q. J. R. q j r -Q. N. q n -QPF q p f -QPFS q p f s -QPM q p m -QPO q p o -QPOs q p o's -QPP q p p -QP q p -Q.P.R. q p r -QPR q p r -QQ q q -QRL q r l -QRL's q r l's -QRNA q r n a -QROPS q r o p s -QRP q r p -QR q r -QRS q r s -QRT q r t -QRV q r v -QSAR q s a r -QSES q s e s -QSI q s i -QSL q s l -QSM q s m -QSO q s o -QST q s t -QSY q s y -QVC q v c -QVD q v d -QVM q v m -Q.V. q v -R.A.B. r a b -R. A. E. r a e -R.A.F. r a f -R.A.J. r a j -R. A. r a -R.A. r a -R&A r and a -RAV r a v -R&AW r and a w -RAZR r a z r -RBAC r b a c -RbAg r b a g -RBA r b a -RBBP r b b p -RBC r b c -RBCs r b c's -RBD r b d -RBE r b e -RBGE r b g e -RBG r b g -RBI r b i -RBIs r b i's -R. B. J. r b j -R.B.J. r b j -RBK r b k -R.B.L. r b l -RBL r b l -RBMG r b m g -RBMG's r b m g's -RBM r b m -RBMY r b m y -RBO r b o -RBP r b p -R&B r and b -R. B. r b -R.B. r b -RBR r b r -RBS r b s -RBTCO's r b t c o's -RBTH r b t h -RBWH r b w h -RBW r b w -RBX r b x -RBZ r b z -RCAC r c a c -RCAF r c a f -rca r c a -R.C.A. r c a -RCA r c a -RCA's r c a's -RCBC r c b c -RCB r c b -RCCA r c c a -RCCD r c c d -RCCL r c c l -RCCM r c c m -RCC r c c -RCI r c i -R. C. K. r c k -RCL r c l -R.C.M. r c m -RCM r c m -RCN r c n -RCPO r c p o -RCP r c p -RCPT r c p t -R&C r and c -rc r c -R. C. r c -R.C. r c -RCRD r c r d -RCR r c r -RCSB r c s b -RCS r c s -RCT r c t -RCTs r c t's -RCTS r c t s -RCTV r c t v -RCV r c v -RCW r c w -RDB r d b -RDC r d c -RDD r d d -RdE r d e -RDFC r d f c -RDF r d f -R.D.G. r d g -R&D r and d -R. D. r d -R.D. r d -R.E.A. r e a -R. E. B. r e b -R.E.D. r e d -R.E.L. r e l -R.E.M. r e m -R.E.M.'s r e m's -R.E.O. r e o -REPL r e p l -REPLs r e p l's -R.E.P. r e p -R. E. r e -R.E. r e -R.E.R. r e r -R.F.A. r f a -R.F.C. r f c -R. F. r f -R.F. r f -R. F.S. r f s -R.F.W. r f w -RFW r f w -RFX r f x -RGB r g b -RGD r g d -RGF r g f -RGG r g g -RGI r g i -RGK r g k -RGMA r g m a -RGNL r g n l -RGPH r g p h -R&G r and g -R. G. r g -R.G. r g -RGR r g r -RGS r g s -RGS's r g s's -RGTP r g t p -RGU r g u -RGV r g v -RGX r g x -R. H. C. r h c -RHC r h c -RHD r h d -RHHF r h h f -RHH r h h -RHHS r h h s -RHIBs r h i b's -RHIC r h i c -RHI r h i -Rhiw r h i w -RHK r h k -rhl r h l -RHM r h m -RhoG r h o g -Rho's r h o's -RHP r h p -R. H. r h -R.H. r h -R.H.S.J. r h s j -R. I. C. r i c -R.I.C. r i c -R. I. P. r i p -R.I.P. r i p -R&I r and i -R. I. r i -R.I. r i -riu r i u -Riu r i u -rivs r i v s -Rivu r i v u -RIXS r i x s -Rixt r i x t -RJB r j b -RJD r j d -RJE r j e -rjf r j f -RJHS r j h s -R. J. J. r j j -RJJ r j j -RJL r j l -RJN r j n -R. J. r j -R.J. r j -RJ r j -RJR r j r -RJ's r j's -RJTD r j t d -R. K. B. r k b -RKD r k d -RKI r k i -RKKA r k k a -RKL r k l -R.K.O. r k o -RKO r k o -RKO's r k o's -R. K. r k -R.K. r k -RLM r l m -RLM's r l m's -R. L. r l -R.L. r l -RL r l -RLV r l v -rly r l y -RMAF r m a f -RMAG r m a g -RMA r m a -RMB r m b -RMCH r m c h -RMCL r m c l -R.M.C. r m c -RMC r m c -RMDs r m d's -R.M.E.S. r m e s -RMFL r m f l -R.M.F. r m f -RMF r m f -RMG r m g -R. M. H. r m h -RMI r m i -RMIT r m i t -RMIT's r m i t's -RMJM r m j m -R.M.K. r m k -RMK r m k -R. M. L. r m l -RML r m l -RMLs r m l's -RMM r m m -RMP r m p -rm r m -R. M. r m -R.M. r m -RM r m -RMR r m r -RMRS r m r s -RMSD r m s d -RMSDs r m s d's -RMSE r m s e -RMs r m's -RMS r m s -R. M. W. r m w -R.M.W. r m w -RMW r m w -RMX r m x -RNAO r n a o -rna r n a -RNA r n a -RNA's r n a's -RNAs r n a's -RNAS r n a s -RNC r n c -RND r n d -RNE r n e -Rnet r n e t -RNF r n f -RNG r n g -Rnic r n i c -RNJD r n j d -RNK r n k -RNLAF r n l a f -RNLI r n l i -RNLI's r n l i's -RNNs r n n's -RNOH r n o h -RNP r n p -RNPs r n p's -RNPS r n p s -R. N. r n -R.N. r n -RN r n -R.N.R. r n r -RNZ r n z -R.O.C.K. r o c k -R.O.C. r o c -ROKMC r o k m c -ROKN r o k n -rOmpB r o m p b -Rooi r o o i -ROP r o p -R. O. r o -R.O. r o -ROVs r o v's -Roxb r o x b -Roxx r o x x -RPA r p a -RPAYC r p a y c -RPB r p b -RP&C r p and c -rpc r p c -RPC r p c -Rpe r p e -RPE r p e -RPF r p f -RPGA r p g a -rpg r p g -RPG r p g -RPG's r p g's -RPGs r p g's -RPI r p i -RPI's r p i's -RPK r p k -RPL r p l -rpm r p m -RPM r p m -RPMS r p m s -RPO r p o -RPP r p p -R. P. r p -R.P. r p -RP r p -RPs r p's -R.P.S. r p s -RPS r p s -RPT r p t -RPVE r p v e -RPV r p v -R. Q. r q -R.Q. r q -RQW r q w -rra r r a -RRA r r a -RRC r r c -RRDE r r d e -rrd r r d -Rreli r r e l i -rre r r e -RRE r r e -RRG r r g -R. R. H. r r h -RRH r r h -RRKM r r k m -R.R.K. r r k -rRNA r r n a -rRNAs r r n a's -RRN r r n -RRP r r p -R&R r and r -rr r r -R. R. r r -R.R. r r -RR r r -RRR r r r -RRSR r r s r -RRS r r s -RSAF r s a f -R. S. A. r s a -RSA r s a -RSCG r s c g -RSCJ r s c j -R.S.C. r s c -RSC r s c -RSCS r s c s -RSD r s d -RSE r s e -RSF r s f -RSFSR r s f s r -RSG r s g -RSHA r s h a -rsh r s h -RSHS r s h s -RSICC r s i c c -RSID r s i d -RSI r s i -Rsis r s i's -RSI's r s i's -RSIS r s i s -RSK r s k -RSL r s l -rsly r s l y -RsmA r s m a -RSMC r s m c -RSMI r s m i -RSML r s m l -RSM r s m -RSM's r s m's -RSNO r s n o -RSN r s n -RSNZ r s n z -R. S. O. r s o -RSO r s o -RSPB r s p b -RSPCA r s p c a -RSpec r s p e c -RSPK r s p k -RSPO r s p o -R. S. P. r s p -RSP r s p -RSR r s r -rs r s -Rs r's -R. S. r s -R.S. r s -RS r s -RSSI r s s i -R. S. S. r s s -RSS r s s -RSSSF r s s s f -RSTC r s t c -RST r s t -RSu r s u -R.S.U. r s u -RSU r s u -RSU's r s u's -RSVP r s v p -RSV r s v -RSX r s x -RTAFB r t a f b -RTA r t a -RTBF r t b f -rtb r t b -RTB r t b -RTCG's r t c g's -RTC r t c -RTCs r t c's -RTD r t d -RTEC r t e c -RTEjr r t e j r -RTeOR r t e o r -RTE r t e -RTE's r t e's -RTFB r t f b -RTFM r t f m -RTF r t f -RTF's r t f's -RTFS r t f s -RTHK r t h k -RTHK's r t h k's -RTHL r t h l -RTIP r t i p -RTI r t i -RTKL r t k l -RTK r t k -RTLM r t l m -RTL r t l -RTL's r t l's -RTML r t m l -RTMP r t m p -RTM r t m -RTN r t n -RTO r t o -RTOs r t o's -RTOS r t o s -rtPA r t p a -RTP r t p -RTR r t r -rt r t -R. T. r t -R.T. r t -RT r t -rts r t s -RTS r t s -RTS's r t s's -RTTOV r t t o v -RTT r t t -RTTY r t t y -RTUK r t u k -RTU r t u -RTVC r t v c -RTVE r t v e -RTVFBiH r t v f b i h -RTV r t v -RTVV r t v v -RTW r t w -RTXC r t x c -RTX r t x -RTZ r t z -Ruao r u a o -RUC r u c -RUC's r u c's -RUFC r u f c -Rukn r u k n -Ruk r u k -RUMC r u m c -RUNX r u n x -Rupf r u p f -Rupr r u p r -rup r u p -Rup r u p -RUP r u p -R.U.R. r u r -RUR r u r -R. U. r u -R.U. r u -RU r u -RUSD r u s d -RutB r u t b -Ruu r u u -RUV r u v -Ruwa r u w a -Ruy r u y -Ruyt r u y t -RVAR r v a r -Rvat r v a t -RVC r v c -RVCT r v c t -RVD r v d -R. V. E. r v e -RVE r v e -RVGK r v g k -R.V.G. r v g -R. V. J. r v j -R.V.J. r v j -RVM r v m -RVNG r v n g -Rvo r v o -RVO r v o -RVR r v r -R. V. r v -R.V. r v -RV r v -rvs r v s -RVTD's r v t d's -RVU r v u -rwa r w a -Rwa r w a -RWA r w a -rwb r w b -RWB r w b -RWC r w c -RWD r w d -RWDSU r w d s u -RWE r w e -RWEs r w e's -RWFC r w f c -RWIS r w i s -rwjf r w j f -R.W.R.J. r w r j -R. W. r w -R.W. r w -RW r w -RWSL r w s l -R. W. S. r w s -RWS r w s -Rxa r x a -RXL r x l -RX r x -RZR r z r -rz r z -R. Z. r z -RZ r z -RZS r z s -S.A.B. s a b -S.A.D. s a d -SAIC s a i c -Sa'id s a i d -S.A.I. s a i -SAIT's s a i t's -SAKEC s a k e c -S. A. L. s a l -S.A.P.A. s a p a -S.A.P.I. s a p i -S. A. R. s a r -S.A.R. s a r -S. A. s a -S.A. s a -SA s a -S.A.S. s a s -SAS s a s -S.A.V.A. s a v a -Saxl s a x l -Sa'yo s a y o -SAZU s a z u -SBAC's s b a c's -Sbai s b a i -S.B.A. s b a -SBA s b a -SBBK s b b k -SBB s b b -SBCM s b c m -SBCMT s b c m t -sbc s b c -SBC s b c -SBCs s b c's -SBDE s b d e -SBD s b d -SBE s b e -SBF s b f -SBI s b i -SBKP s b k p -sbk s b k -SBK s b k -SBL s b l -SBML s b m l -SBMNH s b m n h -SBM s b m -SBN s b n -SBOE s b o e -SBOL s b o l -SBOP s b o p -Sborz s b o r z -SBP s b p -SBRJ s b r j -sb s b -S. B. s b -S.B. s b -SB s b -SBSE s b s e -SBS s b s -SBS's s b s's -SBTDC s b t d c -SBT s b t -SBTU s b t u -Sbu s b u -SBU s b u -SBY s b y -SBZ s b z -S.C.A. s c a -SCA s c a -SCBA s c b a -SCB s c b -SCBWI s c b w i -SCCA s c c a -SCCA's s c c a's -SCCC s c c c -SCCI s c c i -SCCP s c c p -S.C.C. s c c -SCC s c c -scr s c r -SCR s c r -SCRs s c r's -SCRS s c r s -SCRTC s c r t c -scry s c r y -sc s c -S. C. s c -S.C. s c -SC s c -S.C.S.C. s c s c -SC's s c's -SCS s c s -SCTC s c t c -SCTE s c t e -SCTO s c t o -SCTP s c t p -SCT s c t -SCTS s c t s -SCTV s c t v -SCUAA s c u a a -Scuf s c u f -SCU's s c u's -SCW s c w -Scymn s c y m n -SD&AE s d and a e -SDAP s d a p -SDAPS s d a p s -SDA s d a -SDAS s d a s -SDASS s d a s s -SDAT s d a t -SDAX s d a x -SDB s d b -SDCC s d c c -SDCG s d c g -SDC s d c -SDDI s d d i -SDDOT s d d o t -SDD s d d -SDDS s d d s -Sdei s d e i -sde s d e -Sde s d e -SDF s d f -SDG&E s d g and e -SDHA s d h a -SDHC s d h c -SDHD s d h d -SDHHD s d h h d -SDH s d h -SDI s d i -SDJ s d j -sdk s d k -SDK s d k -SDK's s d k's -SDLC s d l c -SDLP s d l p -SDLP's s d l p's -S. D. L. s d l -S.D.N.Y. s d n y -S. D. s d -S.D. s d -SDSM&T's s d s m and t's -S. D. S. s d s -S.E.C. s e c -Sejms s e j m's -sejr s e j r -Sekl s e k l -Sek s e k -SEK s e k -S. E. s e -S.E. s e -SESL s e s l -ses s e s -Ses s e's -SEs s e's -S.E.S. s e s -SES s e s -S.E.S.'s s e s's -S.E.X. s e x -Seyh s e y h -sfadb s f a d b -SFA s f a -SFA's s f a's -Sfax s f a x -S.F.B.J. s f b j -SFB s f b -SFCC s f c c -SFCH s f c h -SFC s f c -SFDR s f d r -SFD s f d -SFE s f e -SFES s f e s -SFFAS s f f a s -SFFCo s f f c o -SFFH s f f h -SFF s f f -SFG s f g -SFI s f i -S. F. L. s f l -SFL s f l -sfn s f n -SFN s f n -SFOR s f o r -SFO s f o -SFPA s f p a -SFPD s f p d -SFP s f p -SFRA s f r a -SFRJ s f r j -SFR s f r -'sf s f -sf s f -S. F. s f -S.F. s f -SF s f -SFSG s f s g -SFSR s f s r -sfs s f s -S.F.'s s f's -SFS s f s -SFSS s f s s -SFSU s f s u -SFU s f u -SFWA s f w a -SFX s f x -SFX's s f x's -SGAE s g a e -SGAP s g a p -SGA s g a -SG&A s g and a -SGA's s g a's -sgb s g b -SGB s g b -S.G.C. s g c -SGC s g c -SGD s g d -SGE s g e -S. G. F. s g f -SGF s g f -SGH s g h -Sgip s g i p -SGI s g i -SGL s g l -sgml s g m l -SGML s g m l -SGP s g p -SGRAM s g r a m -sgra s g r a -SGR s g r -S. G. s g -S.G. s g -SGSN s g s n -SGSNs s g s n's -SGS s g s -SGSY s g s y -Sgt. sergeant -sgt s g t -SGT s g t -SGU s g u -SGV s g v -SGX s g x -SHBG s h b g -SHB s h b -SHBT s h b t -SHCA s h c a -SHC s h c -SHG s h g -SHH s h h -S.H.I.E.L.D.'s s h i e l d's -S.H.I.E.L. s h i e l -SHL s h l -Shma s h m a -SHMD s h m d -SHM s h m -SHN s h n -S. H. s h -S.H. s h -S.I.D. s i d -SIF s i f -S.I.R. s i r -S. I. s i -S.I. s i -S.I.T. s i t -SJAM s j a m -SJCH s j c h -SJC s j c -SJDA s j d a -S.J.D. s j d -sjef s j e f -SJEM s j e m -S. J. J. F. s j j f -SJK s j k -S.J.L. s j l -SJL s j l -SJM s j m -Sjon s j o n -SJPCD s j p c d -SJP s j p -SJPT s j p t -SJR s j r -SJR's s j r's -S. J. s j -S.J. s j -SJ s j -SKB s k b -SKC s k c -SKD s k d -S. K. F. s k f -SKF s k f -SKG s k g -SKH s k h -SKJ s k j -SKPC s k p c -SKP s k p -SKR s k r -SKSD s k s d -S. K. s k -S.K. s k -SK s k -S. K. S. s k s -S.L.A.A.'s s l a a's -SLAF s l a f -sla s l a -SLA s l a -SLAs s l a's -SLCO s l c o -SLC s l c -SLDL s l d l -SLD s l d -S.L.E. s l e -SLF s l f -SLG s l g -SLHS s l h s -S.L.I.F.E.R. s l i f e r -SLL s l l -SLMC s l m c -S. L. M. s l m -SLM s l m -SLN s l n -SLPIM s l p i m -SLP s l p -SLRC s l r c -SLR s l r -S&L s and l -SLS&E s l s and e -SLSF s l s f -SLSK s l s k -S. L. s l -S.L. s l -SL s l -SLS s l s -SLVR s l v r -SLV s l v -S.M.A.R.T. s m a r t -S.M.A.S.H. s m a s h -SMA s m a -SMB s m b -SMe s m e -SME s m e -SME's s m e's -SMEs s m e's -SMF s m f -SMG s m g -SMHI s m h i -SMH s m h -SmI s m i -SMI s m i -SMJR s m j r -SMK s m k -SMLS s m l s -SMMT s m m t -SMN s m n -SMNS s m n s -SMP s m p -SMP's s m p's -SMPSs s m p s's -SMPTE s m p t e -SMRJ s m r j -smr s m r -SMR s m r -S&M s and m -sm s m -S. M. s m -S.M. s m -SM s m -S.M.'s s m's -SMs s m s -S.M.S. s m s -SMS s m s -SMS's s m s's -SMSU s m s u -SMTP s m t p -S.M.T. s m t -SMT s m t -SMTV s m t v -SMU s m u -SMW s m w -SMX s m x -Smyl s m y l -SMYS s m y s -SNA s n a -SNBA s n b a -SNB s n b -SNCB s n c b -SNCC s n c c -SNCF s n c f -SNC s n c -SNDC s n d c -SND s n d -SNEP s n e p -SNESjr s n e s j r -SNES s n e s -SNET s n e t -SNF s n f -SNFU s n f u -sngle s n g l e -SNG s n g -SNK s n k -SNLA s n l a -SNL s n l -SNLS s n l s -SNMCMG s n m c m g -SNMC s n m c -SNMMA s n m m a -SNMP s n m p -SNNPR s n n p r -SNNR s n n r -SNPJ s n p j -SNP s n p -SNPs s n p's -SNRI s n r i -SNR s n r -SNSD's s n s d's -SnSe s n s e -S. N. s n -S.N. s n -SN s n -SNS s n s -S.O.E. s o e -S. O. s o -S.O. s o -Sos s o's -S.O.S. s o s -SOS s o s -Sovn s o v n -Sov s o v -SOX s o x -S. O. Y. s o y -S&P 500 s and p five hundred -S.P.A.L. s p a l -SPB s p b -SPCAs s p c a's -SPCG s p c g -SPCK s p c k -S.P.C. s p c -SPC s p c -SPDI s p d i -SPD s p d -Spe s p e -SPE s p e -SPES s p e s -SPFH s p f h -SPFL s p f l -SPF s p f -SPG s p g -SPHL s p h l -SPH s p h -SPINE's s p i n e's -SPIN's s p i n's -SPIR s p i r -SPI s p i -S.P.I.T. s p i t -SPJA s p j a -SPK s p k -SPLA s p l a -SPLC s p l c -SPL s p l -SPME s p m e -SPML s p m l -SPMRL s p m r l -SPM s p m -SPNJ s p n j -SPNM s p n m -SPNN s p n n -SPN s p n -Spoa s p o a -SPOC s p o c -SPOF s p o f -SPO s p o -SPOU s p o u -SpPIn s p p i n -SPP s p p -SPP's s p p's -SPQA s p q a -SPRL s p r l -SPRM s p r m -SPR s p r -SPRU s p r u -S&P s and p -SPSA s p s a -SPSL s p s l -S. P. s p -S.P. s p -SP s p -SP's s p's -SPs s p's -SPS s p s -SPSS s p s s -SPTA s p t a -SPT s p t -SPUC s p u c -SPUP s p u p -SPU s p u -SPUs s p u's -SPV s p v -SQA s q a -SQBB s q b b -SQI s q i -sql s q l -SQL s q l -SQM s q m -sq s q -S. Q. s q -SQ s q -Sra s r a -SRA s r a -SRAs s r a's -Srba s r b a -SRBIJA s r b i j a -Srbi s r b i -SRBOC s r b o c -SRBP s r b p -SRB s r b -SRBs s r b's -SRBY s r b y -SRCC s r c c -SRCL s r c l -SRC s r c -SRC's s r c's -SRCS s r c s -S.R.E. s r e -SRE s r e -SRFC s r f c -S.R.F. s r f -SRF s r f -S.R.G. s r g -SRG s r g -SRGs s r g's -Srhir s r h i r -SRH s r h -S. R. J. s r j -SRK s r k -SRK's s r k's -SRLGs s r l g's -S.R.L. s r l -SRL s r l -SRMC s r m c -S.R.M. s r m -SRM s r m -SRMs s r m's -Srni s r n i -SRN s r n -srp s r p -SRPT s r p t -S. R. R. s r r -SRR s r r -sr s r -S. R. s r -S.R. s r -SR s r -SRS s r s -SRT s r t -SRT's s r t's -Srul s r u l -SRU s r u -SRU's s r u's -SRV s r v -srx s r x -SRY s r y -SSAA s s a a -SSAB s s a b -SSAC s s a c -SSAR s s a r -SSA s s a -SSAs s s a's -SSBSE s s b s e -S.S.B. s s b -SSB s s b -SSCCC s s c c c -S.S.C. s s c -SSC s s c -SSCV s s c v -SSDB s s d b -SSDL s s d l -SSDP s s d p -S.S.D. s s d -SSD s s d -SSDs s s d's -SSE s s e -SSFL s s f l -SSF s s f -SSGRC s s g r c -SSG s s g -SSHSA's s s h s a's -SSH s s h -SSI s s i -SSIS s s i s -SSJA s s j a -SSKI's s s k i's -SSK s s k -SSLAM s s l a m -ssl s s l -SSL s s l -SSLT s s l t -SSME s s m e -SSM s s m -SSN s s n -SSOD s s o d -SSOF s s o f -SSO s s o -SSoSV s s o s v -SSPA s s p a -SSPH s s p h -SSPR s s p r -SSP s s p -SSPX s s p x -SSQ s s q -SSRAA s s r a a -SSRF s s r f -SSRI s s r i -SSRIs s s r i's -SSRN s s r n -SSRP s s r p -SSR s s r -S&S s and s -SSSC s s s c -SSSI s s s i -SSSR s s s r -ss s s -S. s s's -Ss s's -S. S. s s -S.S. s s -SSS s s s -SSTH s s t h -SSTL s s t l -SSTR s s t r -SST s s t -Ssu s s u -SSU s s u -SSVC s s v c -SSV s s v -SSWAHS s s w a h s -SSWC s s w c -ssw s s w -SSW s s w -SSX s s x -Ssy s s y -ST&AJ s t and a j -S.T.A.L.K.E.R. s t a l k e r -S.T.A.T.U.S. s t a t u s -STB s t b -STCC s t c c -S.T.C. s t c -STC s t c -STCW s t c w -STDP s t d p -STDs s t d's -STD s t d -STF s t f -stfv s t f v -STGs s t g's -STG s t g -STIs s t i's -STIS s t i s -STi s t i -STI s t i -STK s t k -stl s t l -S.T.L. s t l -STL s t l -STMB s t m b -STMIK s t m i k -STM's s t m's -STM s t m -STNS s t n s -STN s t n -STPI s t p i -STPNS s t p n s -STPRI s t p r i -STP s t p -S.T.R.I.D.E. s t r i d e -STRV s t r v -Stryj s t r y j -STRZ s t r z -S&T s and t -STScI s t s c i -ST's s t's -STS s t s -S. T. s t -S.T. s t -STT s t t -STVL s t v l -STVS s t v s -STV s t v -STXBP s t x b p -STX s t x -S.U.C. s u c -SUDV s u d v -suo s u o -Suo s u o -S. U. s u -SUSV s u s v -Susz s u s z -SUTs s u t's -SUT s u t -Suu s u u -SUVF s u v f -SUVs s u v's -SUV s u v -SUWN s u w n -SUW s u w -Suy s u y -Svac s v a c -svar s v a r -SVA s v a -SVB s v b -SVC s v c -SVD s v d -sve s v e -Sve s v e -SVGA s v g a -SVG s v g -SVGT s v g t -SVIA s v i a -SVM's s v m's -SVMs s v m's -SVM s v m -svn s v n -svom s v o m -SVOPC s v o p c -SVO s v o -SVP s v p -SVPW s v p w -SVSCEP s v s c e p -SVSC s v s c -SVS s v s -sv s v -S. V. s v -S.V. s v -SV s v -SVTs s v t's -SVT s v t -S.V.U. s v u -SVU s v u -SVV s v v -SVW s v w -SVYASA s v y a s a -SVZ s v z -SWABC s w a b c -SWAC s w a c -S.W.A. s w a -SWC s w c -SWD s w d -S.W.E.A.T. s w e a t -Swe s w e -SWE s w e -SWF s w f -SWG s w g -SWHL s w h l -SWHS s w h s -SWH s w h -SWJN s w j n -S. W. K. s w k -SWMRS s w m r s -SWM s w m -SWNH s w n h -SWOC s w o c -S.W.O.R.D. s w o r d -SWPA s w p a -SWPL s w p l -SWP s w p -SwRI s w r i -SWR s w r -S&W s and w -SWS s w s -sw s w -S. W. s w -S.W. s w -SW s w -SWTPC s w t p c -SWT s w t -SWWTP s w w t p -SXCT s x c t -SXN s x n -SXSW s x s w -sx s x -S.X. s x -SX s x -SXY s x y -SXZ s x z -SysML s y s m l -SysRq s y s r q -Sys s y's -SYS s y s -SysV s y s v -S. Y. s y -S.Y. s y -SyT s y t -syv s y v -Syxx s y x x -SZA s z a -Szasz s z a s z -SZDSZ s z d s z -Szer s z e r -szkic s z k i c -Szklo s z k l o -Szlak s z l a k -SzMME s z m m e -Szpir s z p i r -SZSE s z s e -sz s z -S. Z. s z -SZ s z -Szu s z u -Szyk s z y k -SZZ s z z -taf t a f -Taf t a f -TAF t a f -T.A.P. t a p -T.A.S. t a s -T. A. t a -T.A. t a -T&A t and a -TAZ t a z -TBA t b a -TBCA t b c a -TBCs t b c's -TBCS t b c s -TBD t b d -TBE t b e -TBF t b f -TBHS t b h s -TBI t b i -TBK t b k -TBL t b l -TBMA t b m a -TBMM t b m m -TBMs t b m's -T.B.M. t b m -TBM t b m -TBNJ t b n j -TBN t b n -TBP t b p -TBSC t b s c -TBS t b s -T. B. t b -T.B. t b -TB t b -TBTG t b t g -TBT t b t -TBV t b v -TBWA t b w a -TBX t b x -TCAR t c a r -TCA t c a -TCC t c c -TCDB t c d b -TCDC t c d c -TCDD t c d d -TCDOG t c d o g -TCDSB t c d s b -TCEB t c e b -T.C.E. t c e -TCE t c e -TCFAQ t c f a q -TCF t c f -TCGA t c g a -TCG t c g -TCHC t c h c -TCHRD t c h r d -TCH t c h -TCiAP t c i a p -TCI t c i -TCKs t c k's -TCLP t c l p -TCL t c l -TCM t c m -TCO t c o -TCPL t c p l -TCPMP t c p m p -TCP's t c p's -TCP t c p -TCR t c r -T. C. S. t c s -TCS t c s -tc t c -T. C. t c -T.C. t c -TC t c -TCT t c t -TCU's t c u's -TCUs t c u's -tcu t c u -TCU t c u -TCV t c v -TCWC t c w c -TCWP t c w p -TCW t c w -TDA t d a -tdb t d b -TDCC t d c c -TDCi t d c i -TDCJ t d c j -TDC's t d c's -TDC t d c -TDD t d d -TDE t d e -TDF t d f -TDH t d h -TdIF t d i f -TDI t d i -TDK t d k -TDLAS t d l a s -TDMA t d m a -TDME t d m e -TDM t d m -TDO t d o -TDP t d p -TDRS t d r s -TDR t d r -TDSB's t d s b's -TD's t d's -TDs t d's -T. D. t d -T.D. t d -TDT t d t -Teatr t e a t r -TEBD t e b d -T. E. t e -T.E. t e -TEVT t e v t -TFAP t f a p -TFAS t f a s -TFA t f a -TFC t f c -TFCU t f c u -TFF t f f -TFG t f g -T.F.H. t f h -TFH t f h -TFIH t f i h -TFIID t f i i d -TFK t f k -TFL t f l -TFM t f m -TFN t f n -TFO t f o -TFP t f p -TFR t f r -TFSA t f s a -TFSI t f s i -TFSP t f s p -TFS t f s -T&F t and f -TFTC t f t c -tf t f -T. F. t f -T.F. t f -TF t f -TFTR t f t r -TFT t f t -TFVC t f v c -TFWA t f w a -TFW t f w -TGA t g a -T. G. C. t g c -TGC t g c -tge t g e -T.G.E. t g e -TGE t g e -tgf t g f -TGF t g f -TGG t g g -TGIF t g i f -TGL t g l -TGM's t g m's -TGM t g m -TGP t g p -TGS t g s -tg t g -T. G. t g -T.G. t g -TG t g -TGVs t g v's -tgv t g v -TGV t g v -THB t h b -THCF t h c f -THC t h c -T.H.E.M. t h e m -T.H.F. t h f -THF t h f -THG t h g -THHK t h h k -T.H.I.N.K. B.I.G. t h i n k b i g -THLL t h l l -THL t h l -THMP t h m p -THM t h m -THNN t h n n -Thok t h o k -T.H.P. t h p -THQ's t h q's -THQ t h q -THR's t h r's -THR t h r -ThSe t h s e -THSR t h s r -T. H. S. t h s -T. H. t h -T.H. t h -T.H.U.N.D.E.R. t h u n d e r -THW t h w -THX t h x -TIAA t i a a -T. I. A. t i a -TIFR t i f r -TIF t i f -T.I.'s t i's -T.I. t i -Tiu t i u -tiv t i v -Tiv t i v -TIYM t i y m -Tiy's t i y's -TJFR t j f r -T.J.F. t j f -T. J. J. t j j -TJJ t j j -TJP t j p -TJRC t j r c -T. J. S. t j s -T. J. t j -T.J. t j -TJ t j -t'ju t j u -TJX t j x -tjz t j z -TKAG t k a g -TKA's t k a's -TKA t k a -T. K. B. t k b -TKD t k d -TKE t k e -TKI t k i -tko t k o -Tko t k o -TKO t k o -TKP t k p -TK's t k's -TKS t k s -tk t k -T. K. t k -T.K. t k -TK t k -TKT t k t -Tlas t l a's -TLA t l a -TLC's t l c's -TLC t l c -TlCu t l c u -TLDs t l d's -TLDS t l d s -TLD t l d -TLE t l e -TLF t l f -TLG t l g -TLH t l h -tli t l i -TLI t l i -TLM t l m -TLN t l n -tlp t l p -TLP t l p -TLRs t l r's -TLR t l r -TLs t l's -TLS t l s -TLTB t l t b -tl t l -T. L. t l -T.L. t l -TL t l -Tluk t l u k -TLU's t l u's -Tluszcz t l u s z c z -TLV t l v -TMA t m a -TMBG t m b g -TMB t m b -tmc t m c -TMC t m c -TMDL t m d l -TMD t m d -TMEM t m e m -TMF t m f -TMGs t m g's -TMG t m g -TMI t m i -TMJ t m j -T. M. M. t m m -TMMTX t m m t x -TMNT t m n t -TMOK t m o k -tmos t m o s -TMO's t m o's -TMOS t m o s -TMO t m o -TMPRSS t m p r s s -TMP t m p -tmRNA t m r n a -TMRS t m r s -TMR t m r -TMSI t m s i -TMSs t m s's -T.M.s t m's -TM's t m's -TMS t m s -tm t m -T. M. t m -T.M. t m -TM t m -T.M.T. t m t -TMT t m t -TMU t m u -TMX t m x -TMZ t m z -TNA's t n a's -TNAS t n a s -tna t n a -TNA t n a -tnbc t n b c -TNCA t n c a -TNCC t n c c -TNCDSB t n c d s b -TNC t n c -TNFA t n f a -TNFRSF t n f r s f -TNFSF t n f s f -TNF t n f -TNGHT t n g h t -TNG t n g -TNIP t n i p -TNI t n i -TNL t n l -TNMM t n m m -TNMS t n m s -TNM t n m -TNNC t n n c -TNN t n n -TNO t n o -TNPL t n p l -TNP t n p -TNQ t n q -TNRIS t n r i s -TNRP t n r p -TNR t n r -TNSDL t n s d l -TNSTC t n s t c -TNS t n s -TNTAs t n t a's -tn t n -T. N. t n -T.N. t n -TN t n -TNT's t n t's -TNT t n t -T.O.'s t o's -T. O. t o -T.O. t o -TOTP t o t p -tou t o u -Tou t o u -ToU t o u -TOU t o u -TPAC t p a c -TPAO t p a o -tPA t p a -TPA t p a -TPB t p b -TPC t p c -TPEC t p e c -TPF t p f -TPG t p g -TPH t p h -TPI t p i -TPLF t p l f -TPMS t p m s -TPM t p m -TPO t p o -TPP t p p -tpr t p r -TPR t p r -TPS t p s -tp t p -T. P. t p -T.P. t p -TP t p -TPU t p u -TPVs t p v's -TPWS t p w s -TPW t p w -TQR t q r -TQS t q s -T.Q. t q -TQ t q -tra t r a -Tra t r a -TRA t r a -TRAXX t r a x x -Trbic t r b i c -T. R. B. t r b -TRB t r b -Trcek t r c e k -TRC t r c -TRD t r d -TRFA t r f a -TRF t r f -TRG t r g -TRHS t r h s -TRH t r h -T.R.I.B.E. t r i b e -TRIZ t r i z -TrkA t r k a -TRL t r l -Trmcic t r m c i c -TRMM t r m m -T.R.M.P.A. t r m p a -T. R. M. t r m -tRNA t r n a -TRNC t r n c -TRPC t r p c -TRPM t r p m -TRPP t r p p -TRP's t r p's -TRPs t r p's -TRP t r p -TRPV t r p v -TRPY t r p y -TRSC t r s c -TRSI t r s i -trs t r s -T.R.S. t r s -TRS t r s -TRSV t r s v -tr t r -T. R. t r -T.R. t r -TR t r -TRT t r t -T.R.U. t r u -truTV t r u t v -TruTV t r u t v -Trve t r v e -TRVL t r v l -TRV t r v -TRW t r w -TRX t r x -TRZ t r z -Tsa t s a -TSA t s a -TSB t s b -TSCC t s c c -TSC t s c -TSF t s f -TSG t s g -TSH t s h -TSI t s i -tsit t s i t -Tsiv t s i v -TSJDF t s j d f -TSLA t s l a -TSLC t s l c -TSL t s l -TSN t s n -T.S.O.L. t s o l -tso t s o -Tso t s o -T.S.O. t s o -TSO t s o -TSP t s p -TSRA t s r a -TSRTC t s r t c -tsr t s r -TSR t s r -TSSA t s s a -TSS t s s -TSTA t s t a -TSTC t s t c -Ts t's -T. S. t s -T.S. t s -TS t s -TST t s t -tsus t s u s -Tsvi t s v i -TSV t s v -TSW t s w -TSX t s x -TTAB t t a b -Tta t t a -TTA t t a -TTBB t t b b -TTCP t t c p -TTC's t t c's -TTC t t c -TTDC t t d c -TTD t t d -tteok t t e o k -tte t t e -TTFF t t f f -TTHS t t h s -TTH t t h -TTI t t i -TTKG t t k g -TTKST t t k s t -TTL t t l -T.T.N. t t n -ttp t t p -TTP t t p -TTR t t r -TTS t t s -T&T t and t -T. T. t t -T.T. t t -TT t t -TTU t t u -TTV t t v -TTW t t w -TUAW t u a w -TUBB t u b b -TUDCA t u d c a -TUHUS t u h u s -TUKP's t u k p's -T'uqu t u q u -TUSCC t u s c c -TUSC t u s c -T.U. t u -TU t u -Tuzk t u z k -tvaan t v a a n -Tvam t v a m -TVARK t v a r k -tva t v a -TVA t v a -TVB's t v b's -TVB t v b -TVCM t v c m -TVC t v c -TVD t v d -TVETs t v e t's -TVE t v e -TVF t v f -TVGN t v g n -TVGOS t v g o s -TVii t v i i -TVIn t v i n -TVi t v i -TVI t v i -TVL t v l -TVMK t v m k -TVM t v m -TVN t v n -TVNZ's t v n z's -TVNZ t v n z -tvo t v o -Tvo t v o -TVO t v o -TVP t v p -TVRi t v r i -tvr t v r -TVR t v r -TVSpy t v s p y -tvs t v s -TV's t v's -TVs t v's -TVS t v s -tVTA t v t a -TVT t v t -tv t v -T. V. t v -T.V. t v -TV t v -TVXQ's t v x q's -TVXQ t v x q -TVX t v x -TWAP t w a p -TWA's t w a's -Twa t w a -TWA t w a -T. W. B. t w b -TWCS t w c s -TWC t w c -TWF t w f -Twi t w i -TWI t w i -TWK t w k -T.W.P. t w p -TWP t w p -TWR t w r -TWTs t w t's -TWT t w t -T. W. t w -T.W. t w -TW t w -T.W.U. t w u -TWU t w u -TXC t x c -TxDOT t x d o t -TXII t x i i -TXJS t x j s -TXK t x k -TXMM t x m m -TXNDC t x n d c -TXP t x p -TXTC t x t c -TXT t x t -T.X. t x -TX t x -TXU t x u -tya t y a -TYC t y c -TYIB t y i b -TYIN t y i n -Tyk t y k -Tza'ar t z a a r -Tze t z e -TZL t z l -Tzrif t z r i f -Tzuh t z u h -TZUM t z u m -Tzvi t z v i -UAAP's u a a p's -UAAP u a a p -UAB's u a b's -UAB u a b -UAC u a c -UADY u a d y -UAE's u a e's -U.A.E. u a e -UAE u a e -UAF u a f -UAHC u a h c -UAIC u a i c -UAI u a i -UALR u a l r -UAL u a l -UALVP u a l v p -UAM u a m -UANL u a n l -UAN u a n -UAOC u a o c -UAP u a p -UAR's u a r's -UARS u a r s -UAR u a r -UASLP u a s l p -UASL u a s l -Ua's u a's -UAs u a's -UAS u a s -uat u a t -U.A. u a -UA u a -UAVs u a v's -UAV u a v -U.A.W. u a w -UAW u a w -Uba u b a -UBA u b a -UBBC u b b c -UBB u b b -UbcM u b c m -UBC's u b c's -UBC u b c -UBD u b d -Ube u b e -UBE u b e -ubi u b i -Ubi u b i -U.B.I. u b i -UBI u b i -UBM's u b m's -UBM u b m -UBOS u b o s -UBO u b o -UBPR u b p r -UBP u b p -UBRE u b r e -UBRS u b r s -UB's u b's -UBS u b s -UB u b -UBU u b u -UBV u b v -UBX u b x -UCAC u c a c -Ucar u c a r -UCAR u c a r -Uca u c a -UCA u c a -UCAV u c a v -UCBH u c b h -UCBTLA u c b t l a -UCB u c b -UCCE u c c e -UCCJ u c c j -UCCS u c c s -UCC u c c -UCDA u c d a -UCDP u c d p -UCD u c d -UCF's u c f's -UCF u c f -UCG u c g -UCIEP u c i e p -UCI's u c i's -UCI u c i -UCLA's u c l a's -UCLA u c l a -UCLH u c l h -UCL u c l -Ucmak u c m a k -UCMJ u c m j -UCMMA u c m m a -UCMP u c m p -UCM u c m -Ucn u c n -UCOS u c o s -UCO u c o -UCP u c p -UCREF u c r e f -UCR u c r -UCSB u c s b -UCSC u c s c -UCSD's u c s d's -UCSD u c s d -UCSF u c s f -UCSN u c s n -uCs u c's -UCS u c s -UCTI u c t i -UCT u c t -Uc u c -U.C. u c -UC u c -Ucuncu u c u n c u -UCU u c u -UCVTS u c v t s -UCW u c w -Uczta u c z t a -UDAR u d a r -UDA's u d a's -Uda u d a -UDA u d a -UDC u d c -UDF u d f -UDG u d g -UDHR u d h r -UDICHI u d i c h i -Udit u d i t -UDK u d k -UDN u d n -Udny u d n y -UDP u d p -UDRP u d r p -UDR u d r -UDS u d s -UDTs u d t's -UDT u d t -ud u d -Ud u d -U. D. u d -UD u d -udu u d u -Udu u d u -UDYCO u d y c o -UEA u e a -UEBT u e b t -UEC u e c -Ueda's u e d a's -Uéda u e acute d a -UEFA's u e f a's -UEFA u e f a -UEFI u e f i -UEFS u e f s -UEF u e f -UEGCL u e g c l -UEI u e i -UET u e t -U. E. u e -UE u e -UFABC u f a b c -UFA's u f a's -UFCO u f c o -UFC's u f c's -UFC u f c -UFCW u f c w -UFD u f d -UFE u f e -UFF u f f -UFIA u f i a -UFIP u f i p -UFI u f i -UFJ u f j -UFL's u f l's -UFL u f l -UFM u f m -UFOFU u f o f u -UFORE u f o r e -UFO's u f o's -UFOs u f o's -Ufot u f o t -ufo u f o -Ufo u f o -UFO u f o -UFPE u f p e -UFPLS u f p l s -UFPR u f p r -UFRGS u f r g s -UFRJ u f r j -UFSB u f s b -UFSM u f s m -UF's u f's -UFS u f s -UFTP u f t p -UFT u f t -U. F. u f -UF u f -UFU u f u -UFW u f w -Uga u g a -UGA u g a -UGCCWA u g c c w a -UGC u g c -Uge u g e -UGK u g k -UGME u g m e -Ugni u g n i -UGP u g p -Ugra u g r a -Ugrszke u g r s z k e -UGS u g s -UGT u g t -Ug u g -UG u g -UHD u h d -UHF u h f -Uhha u h h a -UHMW u h m w -uhn u h n -UHOA u h o a -UHPT u h p t -UHP u h p -UHRA u h r a -UHRF u h r f -UHSAA u h s a a -UHTCs u h t c's -UHTI u h t i -Uhud u h u d -U.H. u h -uhur u h u r -UIAA u i a a -Uiam u i a m -UIA u i a -UIAW u i a w -Uibh u i b h -Uible u i b l e -UIC u i c -UID u i d -UIFL u i f l -Uig u i g -UIL u i l -UIMC u i m c -UIM u i m -UIN u i n -UIP u i p -uisae u i s a e -UISD u i s d -UiS u i s -UI's u i's -UIS u i s -UiTM u i t m -uit u i t -Uit u i t -UIT u i t -UI u i -UIV u i v -Uiy u i y -UJA u j a -UJC u j c -Ujed u j e d -UJEP u j e p -Ujsag u j s a g -UJS u j s -uj u j -U.J. u j -UJ u j -Uka u k a -UKA u k a -UKCC u k c c -UKC u k c -Ukhra u k h r a -Ukic u k i c -UKIP's u k i p's -Uki u k i -UKM u k m -UKNC u k n c -Ukoh u k o h -Uko u k o -UKPC u k p c -UKRDA's u k r d a's -UKRDA u k r d a -ukr u k r -Ukr u k r -UKR u k r -UK's u k's -UKTV's u k t v's -UKTV u k t v -Ukui u k u i -u'k u k -uk u k -Uk u k -U.K. u k -UK u k -UKUP u k u p -UKVRN u k v r n -UKW u k w -Ukwu u k w u -ULC u l c -ULDB u l d b -ULEB u l e b -ULEV u l e v -ULFA u l f a -Ulic u l i c -Ull u l l -Ulms u l m's -UL's u l's -ULS u l s -UlSU u l s u -Uluj u l u j -U.L. u l -UL u l -ulus u l u s -Ulus u l u's -ULV u l v -Ulwa u l w a -Ulwe u l w e -UMBC u m b c -Umbr u m b r -UMCC u m c c -UMC u m c -UMD u m d -umelcu u m e l c u -UMe u m e -UMF u m f -UMG u m g -UMHB u m h b -UMH u m h -UMKC's u m k c's -UMKC u m k c -UMK u m k -Umla u m l a -UML u m l -Umme u m m e -UMMSM u m m s m -UMNO's u m n o's -Umno u m n o -UMNO u m n o -UMN u m n -UMO u m o -UMPP u m p p -UMP's u m p's -Umri u m r i -UM's u m's -UMTS u m t s -UMTV u m t v -UMUC u m u c -U. M. u m -U.M. u m -UMWA's u m w a's -UMWA u m w a -UMW's u m w's -UNAB u n a b -UNAFF u n a f f -UNAH u n a h -UNAMIR u n a m i r -UNAPACK's u n a p a c k's -UNB u n b -UNCAC u n c a c -UNCAF u n c a f -UNCG's u n c g's -UNCG u n c g -UNCHE u n c h e -UNCHS u n c h s -UNCMAC u n c m a c -UNCRO u n c r o -UNC's u n c's -UNCTAD u n c t a d -UNC u n c -UNCW u n c w -UNFCCC u n f c c c -UNFICYP u n f i c y p -UNFPA u n f p a -UNFP u n f p -UNF u n f -UNFWP u n f w p -UNGC u n g c -UNHCR u n h c r -UNHRC's u n h r c's -UNH u n h -UNJLC u n j l c -Unli u n l i -UNL u n l -Unlu u n l u -UNLV u n l v -UNMCK u n m c k -UNMC u n m c -UNMEE's u n m e e's -UNMEE u n m e e -UNMIH u n m i h -UNMIK u n m i k -UNMIL u n m i l -UNMOVIC u n m o v i c -unm u n m -UNM u n m -UNNC u n n c -unnd u n n d -UNODC u n o d c -UNOMIG u n o m i g -UNPA u n p a -UNPD u n p d -UNPO u n p o -UNP u n p -UNRA u n r a -UNRSGN u n r s g n -UNRWA u n r w a -UNSCOM u n s c o m -UNSCR u n s c r -UNSC's u n s c's -UNSC u n s c -UNSh u n s h -Unst u n s t -Uns u n's -U.N.'s u n's -UNSW u n s w -UNTSO u n t s o -UNTS u n t s -Unt u n t -UNT u n t -U.N. u n -UNU u n u -UNV u n v -UNWE u n w e -UNWTO u n w t o -Unz u n z -UOCl u o c l -UODA u o d a -UofM u o f m -UOHI u o h i -Uoho u o h o -UOJCA u o j c a -UOL u o l -UOMINI u o m i n i -UoMs u o m's -UOP u o p -uORF u o r f -UOR u o r -UO's u o's -UO u o -UoW u o w -UPABA u p a b a -UPBs u p b's -UPCI u p c i -UPC u p c -UPDRS u p d r s -UPDS u p d s -Upd u p d -UPD u p d -UPEC u p e c -UPFA u p f a -UPF's u p f's -Upf u p f -UPF u p f -UPGMA u p g m a -UPHSD u p h s d -UPIN u p i n -Upir u p i r -UPI's u p i's -UPI u p i -UPLA u p l a -UPLB u p l b -UPL u p l -UPMC u p m c -UPMSS u p m s s -UPND u p n d -UPNE u p n e -UPnP u p n p -UPN u p n -UPOV u p o v -UPPP u p p p -Uppu u p p u -UPRR u p r r -UPR u p r -UPSC u p s c -U.P.S.E.B. u p s e b -UPSIDC u p s i d c -UPSID u p s i d -UPSI u p s i -UPSMF u p s m f -UPTI u p t i -UPTU u p t u -U.P. u p -UPW u p w -UPX u p x -UPyD u p y d -UQAIB u q a i b -UQAM's u q a m's -UQC u q c -U.Q.P. u q p -UQP u q p -uq u q -UQ u q -URAA u r a a -URAC u r a c -URAP u r a p -URBACT u r b a c t -URBED u r b e d -Urbz u r b z -URCL u r c l -URCSA u r c s a -URCs u r c's -URC u r c -Urdd u r d d -Urei u r e i -urf u r f -Urla u r l a -URLhttp u r l h t t p -URLs u r l's -URL u r l -URNU u r n u -UROC u r o c -URRACA u r r a c a -URSB u r s b -URSEC u r s e c -URSS u r s s -URW's u r w's -URW u r w -URZ u r z -USAACE u s a a c e -USAAC u s a a c -U.S.A.A.F. u s a a f -USAAF u s a a f -USAB u s a b -USACE u s a c e -USAC u s a c -USAFE u s a f e -USAF u s a f -USAHA u s a h a -USAID's u s a i d's -USAID u s a i d -Usal u s a l -usan u s a n -Usan u s a n -USAN u s a n -usao u s a o -USAO u s a o -USAPA u s a p a -USARPS u s a r p s -USASA u s a s a -USA's u s a's -usata u s a t a -USATF u s a t f -USAT u s a t -usa u s a -.USA u s a -U.S.A. u s a -U.S.A u s a -USA u s a -USAya u s a y a -USBA u s b a -USBC's u s b c's -USBC u s b c -USBs u s b's -USB u s b -USBWA u s b w a -USCCB u s c c b -USCF u s c f -USCGAUX u s c g a u x -USCGC u s c g c -USCG u s c g -USCHS u s c h s -Uscie u s c i e -USCIRF u s c i r f -USCIS u s c i s -USCITA u s c i t a -USCOB u s c o b -USCRP u s c r p -U.S.C.'s u s c's -USC's u s c's -USCT u s c t -U.S.C. u s c -USC u s c -USDA's u s d a's -U.S.D.A. u s d a -USDA u s d a -USDoE u s d o e -USDOJ u s d o j -USDP u s d p -USDTV u s d t v -usd u s d -USD u s d -USEER u s e e r -USENIX u s e n i x -USFbA u s f b a -USFE u s f e -USFF u s f f -USFLPA u s f l p a -USFL u s f l -USFS u s f s -USF u s f -USF&WS u s f and w s -USFWS u s f w s -USFW u s f w -USGA u s g a -U.S.G.S. u s g s -USGS u s g s -U.S. H.R. u s h r -UShs u s h's -Usia u s i a -USIA u s i a -usih u s i h -USIP's u s i p's -USIP u s i p -USISL u s i s l -USIS u s i s -USIU u s i u -USJA u s j a -USJ u s j -USLES u s l e s -USLHE u s l h e -USLMRA u s l m r a -USLTA u s l t a -USL u s l -Uslu u s l u -Usmar u s m a r -USMA u s m a -USMC M u s m c -USMCR u s m c r -USMC's u s m c's -USMC u s m c -USMLE u s m l e -USML u s m l -USMMA u s m m a -USM u s m -Usna u s n a -USNA u s n a -USNG u s n g -Usnic u s n i c -USNM u s n m -USNO u s n o -USNR u s n r -USNSCS u s n s c s -USNS u s n s -USNTDP u s n t d p -U.S.N. u s n -USN u s n -USOC's u s o c's -USOC u s o c -Usoi u s o i -Usos u s o's -Uso u s o -USO u s o -USPHL u s p h l -USPO u s p o -USPPD u s p p d -U.S.P.Q. u s p q -USPSA u s p s a -USPs u s p's -USPS u s p s -USPTA u s p t a -USPTO u s p t o -U.S.P. u s p -USP u s p -USRA u s r a -USRC u s r c -USSA u s s a -USSBA u s s b a -USSB u s s b -USSD u s s d -USSF's u s s f's -USSF u s s f -USSR's u s s r's -USSR u s s r -U.S.S.R u s s r -U.S.'s u s's -US's u s's -U.S.S. u s s -USS u s s -Usti u s t i -Ustka u s t k a -USTR's u s t r's -USTR u s t r -UST's u s t's -Usui u s u i -usum u s u m -U. S. u s -U.S. u s -Usut u s u t -USVC u s v c -Usvit u s v i t -USVI u s v i -U.S.V. u s v -USWA u s w a -USWNT's u s w n t's -USWNT u s w n t -U.S.W. u s w -USW u s w -Uta's u t a's -uta u t a -Uta u t a -UTA u t a -UTB u t b -Utca u t c a -UTC u t c -Utd's u t d's -Utd u t d -utea u t e a -UTEP u t e p -Utes u t e's -UTET u t e t -UTF u t f -Uth u t h -uti u t i -Uti u t i -UTJ u t j -UTMB u t m b -UTMF u t m f -UTM u t m -Utne u t n e -Utnur u t n u r -Uto u t o -UTO u t o -UTPB u t p b -UTP u t p -utrci u t r c i -UTRGV u t r g v -UTR u t r -utsav u t s a v -Utsav u t s a v -UTSC u t s c -UTSI u t s i -UT's u t's -UTS u t s -Utsu u t s u -UTTR u t t r -U.T. u t -Utu u t u -Utva u t v a -UTVA u t v a -UTV u t v -UUA u u a -UUCP u u c p -Uuh u u h -UUKKY u u k k y -Uul u u l -Uulu u u l u -UUP u u p -Uusi u u s i -UUs u u's -Uuto u u t o -UUT u u t -Uvac u v a c -UVB u v b -UVC u v c -Uvea u v e a -UVF u v f -UVIMB u v i m b -UVI u v i -uvnitr u v n i t r -Uvo u v o -UVT u v t -UVU u v u -U.V. u v -UV u v -UWAP u w a p -Uwasa u w a s a -UWASA u w a s a -U.W.A. u w a -UWA u w a -UWB u w b -UWC u w c -UWFi u w f i -UWF u w f -UWG u w g -UWH u w h -UWI u w i -UWM's u w m's -UWP u w p -UWRF u w r f -UWSP's u w s p's -UWSU u w s u -UW's u w's -UWS u w s -UW u w -UWW u w w -VASP v a s p -VA's v a's -V. A. v a -V.A. v a -VA v a -V&A v and a -Vav v a v -VAV v a v -Vay v a y -VBA v b a -VBBS v b b s -VBE v b e -VBI v b i -VBM v b m -VBR v b r -vb v b -V. B. v b -V.B. v b -VB v b -VCA's v c a's -VCA v c a -VCCS v c c s -VCDs v c d's -VCD v c d -VCE v c e -VCH v c h -VCIT v c i t -VCI v c i -VCJ v c j -V. C. M. v c m -VCO v c o -VCP v c p -VCQ v c q -VCRs v c r's -VCR v c r -VCSELs v c s e l's -VCSEL v c s e l -VCs v c's -VCS v c s -VCTs v c t's -VCT v c t -VCU v c u -vc v c -V. C. v c -V.C. v c -VC v c -VCXIV v c x i v -VCY v c y -VDAC v d a c -vda v d a -Vda v d a -VDCs v d c's -VDC v d c -vdiq v d i q -VDJ v d j -VDL's v d l's -VDL v d l -vdm v d m -VDM v d m -VDP v d p -VDR v d r -VDSL v d s l -VDUP v d u p -VDU v d u -V. D. v d -V.D. v d -VD v d -VDV v d v -V. D. W. v d w -vez v e z -Vez v e z -VEZ v e z -V.F.A. v f a -VFA v f a -VFC v f c -VFDS v f d s -V.F.D. v f d -VFD v f d -VFIL v f i l -VFLI v f l i -VFL's v f l's -VFL v f l -VFMC v f m c -VFM v f m -vfp v f p -vfr v f r -VFR v f r -VF's v f's -VFS v f s -VFTS v f t s -VFTX v f t x -VFU v f u -V. F. v f -V.F. v f -VF v f -VFW v f w -VFX v f x -VGA v g a -V'Ger v g e r -VGIK v g i k -VGKO v g k o -VGMA v g m a -vgmdb v g m d b -VGMDB v g m d b -VGM v g m -VGo v g o -VGP v g p -VGSCs v g s c's -VGSoM v g s o m -VGTU v g t u -VGU v g u -V. G. v g -V.G. v g -VG v g -VGV v g v -VGX v g x -VHB v h b -VHC v h c -VHD v h d -VHF v h f -VHL v h l -VHP v h p -VHR v h r -VHSL v h s l -VHS v h s -V. H. v h -VH v h -V.I.C.'s v i c's -Vict v i c t -VICT v i c t -viita v i i t a -vijf v i j f -vij v i j -Vij v i j -V.I.P.s v i p's -VIPs v i p's -V.I.P. v i p -VIP v i p -V. I. v i -V.I. v i -V. J. J. v j j -VJL v j l -VJs v j's -VJTF v j t f -V. J. v j -V.J. v j -VJ v j -VKG v k g -VKIBC's v k i b c's -V. K. N. v k n -VKOS v k o s -VKS v k s -V. K. v k -V.K. v k -VK v k -Vlah v l a h -VLA v l a -VLBA v l b a -VLBI v l b i -VLB v l b -VLCCs v l c c's -VLCS v l c s -VLC v l c -VLDB v l d b -VLDL v l d l -vlei v l e i -VLE v l e -VLEX v l e x -VLF v l f -Vlijt v l i j t -VLN v l n -VLQ v l q -VLR v l r -VLSI v l s i -VLS v l s -VLT v l t -V. L. v l -V.L. v l -VL v l -VMAs v m a's -VMAT v m a t -VMA v m a -VMCAS v m c a s -VMCM v m c m -VME v m e -VMFM v m f m -VMF v m f -VMG v m g -VMI's v m i's -VMI v m i -VMK v m k -VMM v m m -VMPS v m p s -VMS v m s -VMT v m t -vm v m -V. M. v m -V.M. v m -VM v m -VNAF v n a f -VNAV v n a v -VNCH v n c h -VNC v n c -vner v n e r -V.N.E. v n e -VNI v n i -VNO v n o -VNPT v n p t -VNQDD v n q d d -VNR v n r -VNSA v n s a -VNS v n s -VNTH v n t h -VNTR v n t r -VNU v n u -V. N. v n -V.N. v n -VN v n -V.O. v o -VO v o -Vov v o v -VOX's v o x's -Voz v o z -VPAL v p a l -VPD v p d -VPH v p h -vpis v p i s -V. P. I. v p i -VPI v p i -VPLS v p l s -VPL v p l -VPM v p m -VPNs v p n's -VPN v p n -VPO's v p o's -VPP v p p -VPRO's v p r o's -VPRO v p r o -VPS v p s -vpu v p u -V. P. v p -V.P. v p -VP v p -VQT v q t -vq v q -VQ v q -vrak v r a k -VRA v r a -Vrba v r b a -Vrbuv v r b u v -VRD v r d -Vrej v r e j -vrem v r e m -VRE v r e -VRF v r f -Vrin v r i n -VRI v r i -vrj v r j -VRLA v r l a -vrn v r n -vroee v r o e e -vrou v r o u -vrouw v r o u w -Vrouw v r o u w -VRO v r o -VRR v r r -Vrsac v r s a c -VRSA v r s a -VR's v r's -VRS v r s -Vrtis v r t i's -VRT's v r t's -VRT v r t -V&R v and r -vr v r -V. R. v r -V.R. v r -VR v r -VRV v r v -VSANs v s a n's -VSAN v s a n -VSAP's v s a p's -VSATs v s a t's -VSB's v s b's -VSB v s b -VSCP v s c p -VSC v s c -VSD v s d -Vsekh v s e k h -vse v s e -VSE v s e -VSFV v s f v -VSG v s g -VSI v s i -VSM v s m -VSNL v s n l -vso v s o -VSO v s o -VSPs v s p's -VSP v s p -VSS v s s -VSTM v s t m -VST v s t -VSU v s u -vs. versus -_vs._ versus -VSV v s v -VSW v s w -VSX v s x -vsyo v s y o -VSZ v s z -VTA v t a -VTB v t b -VTCO v t c o -VTD v t d -VTEC v t e c -VTE v t eL -Vtic v t i c -VTi v t i -VTL v t l -VTM v t m -VTR v t r -VTSK v t s k -V&T's v and t's -VTS v t s -VTU v t u -V&T v and t -VTVL v t v l -V.T. v t -VT v t -VTV v t v -Vuur v u u r -VUU v u u -V.V.B. v v b -VVCS v v c s -VVD v v d -VVIPs v v i p's -VVI v v i -VVMC v v m c -VVO v v o -VVS v v s -VVT v v t -V. V. v v -V.V. v v -VV v v -VWM v w m -VWR v w r -VW's v w's -VWs v w's -VWS v w s -VW v w -VXL v x l -VXR v x r -VX v x -Vyg v y g -vyr v y r -vy v y -VY v y -vz v z -V. Z. v z -WAAAAAGH w a a a a a g h -WAAAF w a a a f -WAAC w a a c -WAAF w a a f -WAAI w a a i -WAAV w a a v -Waay w a a y -WABB w a b b -WABC w a b c -WABD w a b d -WABG's w a b g's -WABG w a b g -W. A. C. w a c -W.A.C. w a c -Wa'il w a i l -WAIO w a i o -W.A.J. w a j -Wakf w a k f -W.A.K.O. w a k o -wa'l w a l -WANFL w a n f l -WAOK w a o k -waqf w a q f -waqt w a q t -Waqt w a q t -WAQZ w a q z -WARH w a r h -W.A.R. w a r -WASC w a s c -Wasl w a s l -WASL w a s l -W. A. S. w a s -W.A.S. w a s -Watfa w a t f a -WATL w a t l -WATW w a t w -wau w a u -Wau w a u -WAU w a u -WAVF w a v f -WAVM w a v m -W. A. w a -W.A. w a -WA w a -WAWLI w a w l i -waw w a w -WAWZ w a w z -WAYH w a y h -waza w a z a -Waza w a z a -WBAL's w b a l's -WBAM w b a m -WBA w b a -WBBL w b b l -WBBM w b b m -WBBP w b b p -WBCA w b c a -WBCN w b c n -W.B.C. w b c -WBC w b c -WBCY w b c y -WBEV w b e v -WBEZ w b e z -WBFJ w b f j -WBFO w b f o -WBF w b f -WBG w b g -WBHY w b h y -WBIC w b i c -WBIL w b i l -WBJEE w b j e e -WBKO w b k o -WBK w b k -WBLQ w b l q -WBME w b m e -WBNI w b n i -WBNX w b n x -WBON w b o n -WBO w b o -WBQC w b q c -WBRC w b r c -WBRE w b r e -WBRO w b r o -WBRZ w b r z -WBs w b's -WBS w b s -WBTI w b t i -WBT's w b t's -WBT w b t -WBTW w b t w -WBTZ w b t z -WBUR w b u r -WBVE w b v e -WBV w b v -W. B. w b -W.B. w b -WB w b -WBXH w b x h -WBZB w b z b -WBZ w b z -WCAA w c a a -WCAG w c a g -WCAU w c a u -WCA w c a -WCBA w c b a -WCBN w c b n -W&CBR w and c b r -WCBR w c b r -WCBS w c b s -WCB w c b -WCCES w c c e s -WCCG w c c g -WCCO w c c o -WCC's w c c's -WCC w c c -WCDA w c d a -WCEO w c e o -WCFL w c f l -WCF w c f -WCG w c g -WCHA w c h a -WCHL's w c h l's -WCHL w c h l -WCHS w c h s -WCHV w c h v -WCIU w c i u -WCKD w c k d -WCKY w c k y -WCLN w c l n -WCLU w c l u -WCLV w c l v -WCL w c l -WCMA w c m a -WCMC w c m c -WCMFA w c m f a -WCMH w c m h -WCMR w c m r -WCM w c m -WCNB w c n b -WCOZ w c o z -WCPO w c p o -WCPW w c p w -WCRC w c r c -WCRE w c r e -WCRL w c r l -WCSA w c s a -WCSM w c s m -WCS w c s -WCTD w c t d -WCTG w c t g -W.C.T.U. w c t u -WCTU w c t u -WCTV w c t v -WCT w c t -WCTX w c t x -WCVB's w c v b's -WCVB w c v b -WCVE w c v e -WCWA w c w a -wc w c -W. C. w c -W.C. w c -WC w c -WCWC w c w c -WCW w c w -WCXR w c x r -WCYB w c y b -WCZE w c z e -WDAF w d a f -WDA w d a -WDC w d c -WDDM w d d m -WDFN w d f n -WDF w d f -WDGY w d g y -WDH w d h -WDIA w d i a -WDIF w d i f -WDIG w d i g -WDIS w d i s -WDIV w d i v -WDJT w d j t -WDLA w d l a -WDL w d l -WDM w d m -WDNN w d n n -WDNS w d n s -WDNT w d n t -WDOK w d o k -WDO w d o -WDRE w d r e -WDR w d r -WDSE w d s e -WDSN w d s n -WDSO w d s o -WDSU w d s u -WDS w d s -WDTM w d t m -WDUQ w d u q -WDVE w d v e -WDVR w d v r -W. D. w d -W.D. w d -WDWS w d w s -WDW w d w -WDXZ w d x z -WDYZ w d y z -W. E. B. w e b -W.E.B. w e b -W. E. H. w e h -W.E.H. w e h -WEVD w e v d -WEVV w e v v -W. E. w e -W.E. w e -WEZQ w e z q -WFAA w f a a -WFAL w f a l -WFAN w f a n -WFB w f b -WFCA w f c a -WFC w f c -WFDC w f d c -WFDD w f d d -WFDF w f d f -WFDU w f d u -WFD w f d -WFGF w f g f -WFHE w f h e -W.F.H. w f h -WFH w f h -WFIKKN w f i k k n -WFIL w f i l -WFIRST w f i r s t -WFL's w f l's -WFL w f l -WFLX w f l x -WFMT w f m t -WFMU w f m u -W. F. M. w f m -WFM w f m -WF&NW w f and n w -WFNZ w f n z -WFOY w f o y -WFPC w f p c -WFPF w f p f -WFPMA w f p m a -W.F.P. w f p -WFP w f p -WFSBP w f s b p -WFS w f s -WFTDA w f t d a -WFTM w f t m -WFTV w f t v -WFT w f t -WFVA w f v a -W&F w and f -WFWA w f w a -W. F. w f -W.F. w f -WF w f -WFWM w f w m -WFXR w f x r -wga w g a -WGA w g a -WGBH w g b h -WGBI w g b i -W. G. B. w g b -WGB w g b -WGCB w g c b -W.G.C. w g c -WGC w g c -WGEM w g e m -WGFT w g f t -WGGH w g g h -WGHP w g h p -WGH w g h -WGHW w g h w -WGI w g i -WGN's w g n's -WGNT w g n t -wgn w g n -WGN w g n -WGOK w g o k -WGO w g o -WGP w g p -WGPX w g p x -WGRP w g r p -WGRT w g r t -WGRV w g r v -WGSA w g s a -WGSS w g s s -WGS w g s -WGUN w g u n -wg w g -W. G. w g -W.G. w g -WG w g -WGWW w g w w -WGZR w g z r -W.H.B. w h b -WHCA w h c a -WHCB w h c b -WHCC w h c c -W. H. C. w h c -W.H.C. w h c -WHC w h c -WHDG w h d g -WHDI w h d i -W.H.D. w h d -WHEC w h e c -WHFA w h f a -WHFM w h f m -WHFS w h f s -WHHS w h h s -W.H.H. w h h -WHJA w h j a -W.H.J. w h j -WHJY w h j y -WHKT w h k t -WHL's w h l's -WHL w h l -WHNO w h n o -WHP w h p -WHRC w h r c -WHSN w h s n -WHSS w h s s -W.H.S. w h s -WHS w h s -W. H. T. w h t -WHTZ w h t z -W&H w and h -W. H. w h -W.H. w h -WH w h -Whyld w h y l d -WHYT w h y t -W.I.B.C. w i b c -Wica w i c a -wici w i c i -WIC's w i c's -WICU w i c u -Wif w i f -WIF w i f -WIJD w i j d -Wijk w i j k -WIP w i p -W.I.S.E. w i s e -W.I.T.C.H. w i t c h -Wiwa w i w a -W. I. w i -WIXY's w i x y's -WJAL w j a l -WJAR w j a r -wjaz w j a z -WJBC w j b c -WJBF w j b f -WJBK w j b k -WJBR w j b r -WJCI w j c i -WJC w j c -WJEC w j e c -WJEF w j e f -WJER w j e r -WJET w j e t -W. J. J. O. w j j o -W.J.J.O. w j j o -WJJZ w j j z -WJKA's w j k a's -WJKA w j k a -WJKS w j k s -WJLA w j l a -WJMK w j m k -WJM w j m -WJOI w j o i -WJRD w j r d -WJR w j r -WJSC w j s c -W&J's w and j's -WJTD w j t d -WJUX w j u x -W&J w and j -W. J. w j -W.J. w j -WJ w j -WJXX w j x x -WJYL w j y l -WJYM w j y m -WJZA w j z a -WJZJ w j z j -WJZ w j z -WKAG w k a g -WKAQ w k a q -WKAR w k a r -WKA w k a -WKBD w k b d -WKBF's w k b f's -WKB w k b -WKBW w k b w -W. K. C. w k c -WKDM w k d m -WKDN w k d n -WKDZ w k d z -WKFS w k f s -W.K.H. w k h -WKH w k h -WKIK w k i k -WKIP w k i p -WKKB w k k b -WKKD w k k d -WKKZ w k k z -WKLH w k l h -WKNDS w k n d s -WKN w k n -WKQI w k q i -WKRR w k r r -WKSE w k s e -WKSM w k s m -WKSU w k s u -WKTU's w k t u's -WKTU w k t u -W.K.V. w k v -W. K. w k -W.K. w k -WKXJ w k x j -WKX w k x -WKYS's w k y s's -WKYT w k y t -WKY w k y -W.L.A.K. w l a k -WLB w l b -WLCH w l c h -W&LE w and l e -Wley w l e y -WLGH w l g h -WLH w l h -WLII w l i i -WLIR w l i r -WLJY w l j y -WLKT w l k t -WLKY w l k y -WLLM w l l m -WLNP w l n p -WLNQ w l n q -WLNS w l n s -WLPA w l p a -WLPR w l p r -WLPWR w l p w r -wlrs w l r s -WLSG w l s g -WLS w l s -WLTM w l t m -WLUK's w l u k's -WLUK w l u k -WLWC w l w c -W. L. w l -W.L. w l -WL w l -WLW w l w -WLYH's w l y h's -WLYN w l y n -WLY w l y -WLZK w l z k -WMAC w m a c -WMAG w m a g -WMAP w m a p -WMAQ w m a q -WMATA's w m a t a's -WMATA w m a t a -W.M.A. w m a -WMA w m a -WMAZ w m a z -WMBG w m b g -WMCAT w m c a t -WMCA w m c a -WMDB w m d b -WMDI w m d i -WMD w m d -WMEE w m e e -WMEN w m e n -WMET w m e t -WME w m e -WMEX w m e x -WMFC w m f c -WMFM w m f m -WMFP w m f p -W.M.F. w m f -WMF w m f -WMGF w m g f -WMG w m g -WMGY w m g y -WMHG w m h g -WMHT w m h t -WMIX w m i x -WMJR w m j r -WMJZ w m j z -WMKQ w m k q -WMKW w m k w -wml w m l -WMLW w m l w -WMLY w m l y -WMMS w m m s -W. M. M. w m m -WMNF w m n f -WMN w m n -WMOB w m o b -WMO w m o -WMRA w m r a -WMRO w m r o -WMSG w m s g -W.M.S. w m s -WMS w m s -WMTS w m t s -WMT w m t -WMTW w m t w -WMUB w m u b -WMU w m u -WMVM w m v m -WMV w m v -W&M w and m -W. M. w m -W.M. w m -WM w m -WMWM w m w m -WMXB w m x b -WMX w m x -WMYE w m y e -WMYL w m y l -WNAK w n a k -W.N.B.A. w n b a -WNBA w n b a -WNBC w n b c -WNBL w n b l -WNBR w n b r -WNB w n b -WNCN w n c n -WNC w n c -WNCX w n c x -WND w n d -WNED w n e d -WNEL w n e l -WNEM w n e m -WNEP w n e p -WNET w n e t -WNEW's w n e w's -WNEW w n e w -WNFM w n f m -WNGL w n g l -WNIT w n i t -WNJN w n j n -WNJO w n j o -WNJY w n j y -WNK w n k -WNLO w n l o -WNLU w n l u -WNL w n l -WNMX w n m x -WNO w n o -WNPT w n p t -WNRN w n r n -WNR's w n r's -WNRV w n r v -WNSH w n s h -WNSR w n s r -WNTM w n t m -WNT w n t -WNUA w n u a -WNUF w n u f -WNUSP w n u s p -WNWBL w n w b l -W. N. w n -W.N. w n -WN w n -WNWO w n w o -WNWS w n w s -WNW w n w -WNYA w n y a -WNYC's w n y c's -WNYC w n y c -WNYM w n y m -WNY w n y -WNYZ w n y z -wnzaa w n z a a -WOAA w o a a -WOAK w o a k -WOA w o a -WOC w o c -W&OD w and o d -W.O.G. w o g -WOGX's w o g x's -WOJG w o j g -WOLH w o l h -WOOM w o o m -WOPC w o p c -Worh w o r h -WOSM w o s m -W. O. w o -W.O. w o -WOWOW w o w o w -WOXY w o x y -WOZN w o z n -WPAC w p a c -WPA w p a -WPBC w p b c -WPBSA w p b s a -WPBS w p b s -WPBT w p b t -W. P. C. w p c -WPC w p c -WPDH w p d h -WPD w p d -WPFF w p f f -WPFL w p f l -WPF w p f -WPGC w p g c -WPHL w p h l -WPH w p h -WPIAL w p i a l -WPI w p i -WPIX w p i x -WPLA w p l a -WPLG w p l g -WPLS w p l s -WPMW w p m w -WPO w p o -WPPT w p p t -WPP w p p -WPRI w p r i -WPRO w p r o -WPRP w p r p -WPSC w p s c -WPSL w p s l -WPS w p s -WPTB w p t b -WPTD's w p t d's -wpt w p t -WPT w p t -WPTY w p t y -W. P. U. w p u -wp w p -W. P. w p -W.P. w p -WP w p -WPXN w p x n -WPYR w p y r -WQDE w q d e -WQHT w q h t -WQIV w q i v -WQLR w q l r -WQLZ w q l z -WQMS w q m s -WQOK w q o k -WQSO w q s o -WQSX w q s x -WQ w q -WQXI w q x i -WQXR w q x r -W. R. A. S. w r a s -WRAT w r a t -WRBU w r b u -WRCB w r c b -WRCN w r c n -WRC w r c -WRDL w r d l -Wrec w r e c -WRFD w r f d -WRFK w r f k -WRFM w r f m -WRFX w r f x -WRGO w r g o -WRGP w r g p -W. R. G. w r g -WRHA w r h a -WRHC w r h c -WRHI w r h i -W.R.I. w r i -WRKA w r k a -WRKO w r k o -WRKT w r k t -W.R.K. w r k -WRKY w r k y -WRNS w r n s -WRN w r n -WRNY w r n y -WRNZ w r n z -WROJ w r o j -WROK w r o k -WROO w r o o -WRPT w r p t -WRQQ w r q q -WRTA w r t a -WRTC w r t c -WRUV w r u v -WRU w r u -WRVL w r v l -WRVS w r v s -WRWB w r w b -W. R. w r -W.R. w r -WR w r -W.R.W. w r w -WRXT w r x t -WSAR w s a r -WSAV w s a v -W.S.A. w s a -WSA w s a -WSAZ w s a z -WSBG w s b g -WSBM w s b m -WSBT w s b t -WSB w s b -WSCA's w s c a's -WSCR w s c r -W. S. C. w s c -WSC w s c -WSDD w s d d -WSDG w s d g -WSDOT w s d o t -WSDP w s d p -WSDR w s d r -WSEG w s e g -WSEK w s e k -WSE w s e -WSFA w s f a -WSFL w s f l -WSFM w s f m -WSFS w s f s -WSFX w s f x -WSGE w s g e -WSGW w s g w -WSHL w s h l -WSHU w s h u -WSH w s h -WSIPC w s i p c -WSIS w s i s -WSJM w s j m -WSJO w s j o -WSJ w s j -WSLU w s l u -WSL w s l -WSMK w s m k -W.S.M. w s m -WSM w s m -WSNJ w s n j -WSNS w s n s -WSNT w s n t -WSN w s n -WSOF w s o f -WSOPE w s o p e -WSOP's w s o p's -WSOP w s o p -WSORR w s o r r -WSO w s o -WSOY w s o y -WSPA w s p a -WSPC w s p c -WSPD w s p d -WSPN w s p n -WSPS w s p s -WSPU w s p u -WSP w s p -WSRA w s r a -WSRE's w s r e's -WSRF w s r f -WSSA w s s a -WSSCC w s s c c -WSSSA w s s s a -WSS w s s -WSTE w s t e -WSTR w s t r -WSUA w s u a -WSUD w s u d -WSUE w s u e -WSUS w s u s -WSU w s u -WSV w s v -WSVZ w s v z -WSWI w s w i -ws w s -W. S. w s -W.S. w s -WS w s -WSW w s w -WSYN w s y n -WSYX w s y x -WTAA w t a a -WTAE w t a e -WTAF w t a f -WTAG w t a g -WTAM's w t a m's -W. T. A. w t a -WTA w t a -WTAW w t a w -WTCC w t c c -W. T. C. w t c -W.T.C. w t c -WTC w t c -WTDY w t d y -WTEL w t e l -WTEV's w t e v's -WTEV w t e v -WTF w t f -WTGB w t g b -WTHR's w t h r's -WTHS w t h s -WTIU w t i u -WTI w t i -WTIX w t i x -WTKG w t k g -WTKO w t k o -WTKR w t k r -WTKS w t k s -WTLS w t l s -WTMA w t m a -WTNH w t n h -WTN w t n -WTOP w t o p -WTO's w t o's -WTOS w t o s -WTO w t o -WTPA w t p a -WTPQ w t p q -WTR w t r -WTs w t's -WTS w t s -WTTF w t t f -WTTM w t t m -WTTs w t t's -WTT w t t -WTTW w t t w -WTTZ w t t z -WTVA w t v a -WTVC w t v c -WTVD w t v d -WTVI w t v i -WTVM w t v m -WTVU w t v u -WTVW w t v w -WTVX w t v x -WTWF w t w f -W. T. w t -W.T. w t -WT w t -WTX w t x -WUAB w u a b -WUAP w u a p -WUAs w u a's -WUC w u c -Wudl w u d l -Wuhr w u h r -Wuhu w u h u -WUKB w u k b -WUPG w u p g -WUPN w u p n -WUPZ w u p z -Wu's w u's -WUSW w u s w -WUTK w u t k -WUVC w u v c -wuv w u v -W. U. w u -Wuz w u z -WVa w v a -WVBX w v b x -WVCA w v c a -WVIT w v i t -WVJC w v j c -WVJP w v j p -WVLZ w v l z -WVNI w v n i -WVNY w v n y -W. V. O. w v o -WVO w v o -WVPA w v p a -WVPO w v p o -WVSSAC w v s s a c -WVSU w v s u -WVTU's w v t u's -WVTU w v t u -WVUE w v u e -WVU w v u -WVUW w v u w -W. V. w v -W.V. w v -WV w v -WWAA w w a a -WWAMI w w a m i -WWASP w w a s p -WWA w w a -WWAX w w a x -WWBZ w w b z -WWCD w w c d -WWC w w c -WWDB's w w d b's -WWDC w w d c -WWDR w w d r -WWD w w d -WWE's w w e's -Wwe w w e -WWE w w e -WWF's w w f's -WWF w w f -WWGC w w g c -WWHT w w h t -WWHW w w h w -WWIS w w i s -WWJP w w j p -WWKB w w k b -WWKL w w k l -WWML w w m l -WWMM w w m m -WWMX w w m x -WWMY w w m y -WWN w w n -WWNW w w n w -WWNY w w n y -WWOX w w o x -WWPG w w p g -WWP w w p -WWPW w w p w -WWRFC w w r f c -WWRV w w r v -WWSS w w s s -WWS w w s -WWTI's w w t i's -WWTI w w t i -WWTN w w t n -WWU w w u -WWVA w w v a -WWVR w w v r -WWV w w v -WWWF w w w f -WWWQ's w w w q's -W. W. w w -W.W. w w -WW w w -WWW w w w -WWWW w w w w -WWYD w w y d -WXB w x b -WXCN w x c n -WXDU w x d u -WXEL w x e l -WXIL w x i l -WXIN's w x i n's -WXIN w x i n -WXJM's w x j m's -WXJ w x j -WXN w x n -WXQW w x q w -WXTG w x t g -WXW w x w -wx w x -WX w x -W.Y. w y -WY w y -wyzc w y z c -WZBC w z b c -WZFG w z f g -WZFT w z f t -WZGC w z g c -WZJQ w z j q -WZKC w z k c -WZLR w z l r -WZLX w z l x -WZRB w z r b -WZRD w z r d -WZST w z s t -W. Z. w z -WZ w z -WZX w z x -WZZM w z z m -WZZX w z z x -xbg x b g -XBMC x b m c -XBM x b m -Xbra x b r a -XBRL x b r l -XBV x b v -XCB x c b -XCE x c e -XCMS x c m s -XCOM x c o m -XCOR x c o r -xCo x c o -XCR x c r -XCT x c t -XCVI x c v i -XCV x c v -X. C. x c -XC x c -XCX x c x -xda x d a -XDDM x d d m -XDH x d h -XDK x d k -XDRs x d r's -XDR x d r -XD's x d's -XDS x d s -X. D. x d -XD x d -Xfce x f c e -XFC x f c -XFDL x f d l -XFD x f d -XFL x f l -XFM x f m -XFS x f s -XFU x f u -xf x f -X.F. x f -XF x f -XHVFC x h v f c -xh x h -X. H. x h -XH x h -XJD x j d -XJ x j -XKE x k e -XKL x k l -xk x k -XK x k -XL x l -XMB x m b -xmc x m c -xml x m l -XML x m l -XMMS x m m s -XMPP x m p p -XMP x m p -XMRV x m r v -XMSN x m s n -XM's x m's -XMU x m u -X.M. x m -XM x m -XN x n -xO x o -X.O. x o -XO x o -XPA x p a -XPD x p d -XPe x p e -XPL x p l -XPN x p n -XP's x p's -XPS x p s -XPT x p t -XPW x p w -XP x p -X.Q. x q -XQ x q -XRCC x r c c -XRCO x r c o -XRDS x r d s -XRD x r d -XRE x r e -XR x r -XSD x s d -XSi x s i -XSI x s i -XSLT x s l t -xsr x s r -XS x s -XTB x t b -XTC x t c -XTG x t g -XTwas x t w a's -xt x t -XT x t -XVAS x v a -XV x v -XWA x w a -XWB x w b -XWF x w f -XWIS x w i s -X. W. x w -XYNU x y n u -XYP x y p -xy x y -XY x y -xyz x y z -xyZ x y z -XYZ x y z -XZ x z -Y. A. y a -Y.A. y a -YBA y b a -YBL y b l -YBNL y b n l -YBN y b n -YBR y b r -YBX y b x -Y. B. y b -Y.B. y b -YB y b -YBYS y b y s -YCC y c c -YCD y c d -ycia y c i a -ycie y c i e -YCL y c l -YCO y c o -YCU y c u -YCV y c v -yc y c -Y. 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Z. z z -Z.Z. z z diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/ipa_symbols.tsv b/nemo_text_processing/text_normalization/en/data/whitelist/ipa_symbols.tsv deleted file mode 100644 index f5559c711630..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/ipa_symbols.tsv +++ /dev/null @@ -1,521 +0,0 @@ -a -aoj -aəj -aː -aːʲ -aː͡j -aː͡ɨ̯ -aˤ -aˤː -a̠ -a̠ː -a̰ -a͡e -a͡i -a͡iː -a͡i̯ -a͡j -a͡o -a͡u -a͡uː -a͡u̯ -a͡w -a͡ə -a͡ɨ̯ -a͡ɪ -a͡ʊ -b -bʱ -bʲ -bː -b̥ -c -cʰ -cː -ç -d -dʲ -dː -d̥ -d̪ -d̪ʱ -d͡z -d͡zʷ -d͡zː -d͡ʑ -d͡ʒ -d͡ʒʱ -d͡ʒʲ -d͡ʒː -e -eː -eːʲ -eː͡j -ẽː -ẽ͡j̃ -e̞ -e̞ː -e̯ -e͡i -e͡iː -e͡ɨ̯ -f -fʲ -fː -h -hː -i -iəj -iəw -iʲ -iː -iːʲ -ĩː -i̥ -i̯ -i͡u -i͡ə -i͡ɛ -j -jː -j̃ -k -kʰ -kʰː -kʲ -kʲʼ -kʷ -kʷʼ -kʼ -kː -k̚ -k̚ʲ -k̟̚ -k͈ -k͡p̚ -l -lʲ -lː -l̥ -l̩ -m -mʲ -mʲː -mː -m̥ -m̩ -n -nʲ -nː -n̥ -n̩ -o -oʲ -oː -oːʲ -ò -õ͡j̃ -õ͡w̃ -o̝ -o̞ -o̞ː -o̯ -o̰ -o͡u -o͡uː -p -pʰ -pʰː -pʲ -pʷʼ -pʼ -pː -p̚ -p̚ʲ -p͈ -p͜f -p͡f -q -qʷ -qʼ -r -rʲ -rː -r̂ -r̂ː -r̥ -r̩ -s -sʰ -sʲ -sʼ -sː -s͈ -t -tʰ -tʰː -tʲ -tʷʼ -tʼ -tː -t̚ -t̪ -t̪ʰ -t͈ -t͜s -t͡s -t͡sʰ -t͡sʰː -t͡sʲ -t͡sʷ -t͡sʼ -t͡sː -t͡ɕ -t͡ɕʰ -t͡ɕ͈ -t͡ʂ -t͡ʂʼ -t͡ʃ -t͡ʃʰ -t͡ʃʰː -t͡ʃʲ -t͡ʃʷ -t͡ʃʼ -t͡ʃː -u -uəj -uʲ -uː -uːʲ -ũː -ũ͡j̃ -u̯ -u͡e -u͡i -u͡j -u͡ɔ -u͡ə -v -vʲ -vː -w -w̃ -x -xʷ -xː -y -yː -yːʲ -y̯ -z -zʲ -zː -z̥ -à -àː -á -áː -â -âː -ã -ã̠ -æ -æː -æ̀ -æ̀ː -æ̂ -æ̂ː -æ͡ɪ -æ͡ʉ -ç -è -èː -é -éː -ê -êː -ì -ìː -í -íː -î -îː -ï -ð -ò -òː -ó -óː -ô -ôː -õ -õː -õ̞ -ø -øː -øːʲ -ø̯ -ù -ùː -ú -úː -û -ûː -ā -āː -ē -ēː -ĕ -ĕ͡ə -ě -ěː -ħ -ĩ -ĩː -ī -īː -ŋ -ŋʲ -ŋ̊ -ŋ̍ -ŋ̟ -ŋ̩ -ŋ͡m -ō -ŏ -ŏ͡ə -œ -œː -œ̃ -œ͡i -œ͡iː -œ͡ʏ -ř -řː -ũ -ũː -ū -ūː -ŭ -ŭ͡ə -ǎ -ǎː -ǐ -ǐː -ǒ -ǒː -ǔ -ǔː -ǣ -ǣː -ɐ -ɐː -ɐ̃ -ɐ̃͡j̃ -ɐ̃͡w̃ -ɐ̯ -ɐ̯̯ -ɑ -ɑː -ɑ̃ -ɑ̃ː -ɒ -ɒʲ -ɒː -ɓ -ɔ -ɔː -ɔˤː -ɔ̀ -ɔ̀ː -ɔ́ -ɔ́ː -ɔ̃ -ɔ̃ː -ɔ̰ -ɔ͡i̯ -ɔ͡ə -ɔ͡ɨ̯ -ɔ͡ɪ -ɔ͡ʊ -ɕ -ɕʰ -ɕː -ɕ͈ -ɖ -ɖʱ -ɗ -ɘ -ɘː -ə -əː -əˤ -ə̀ -ə́ -ə̃ -ə̯ -ə͡u̯ -ə͡w -ə͡ɨ -ə͡ɨ̯ -ɚ -ɛ -ɛʲ -ɛː -ɛˤː -ɛ̀ -ɛ̀ː -ɛ́ -ɛ́ː -ɛ̂ -ɛ̂ː -ɛ̃ -ɛ̃ː -ɛ̄ -ɛ̄ː -ɛ̰ -ɛ͡i -ɛ͡i̯ -ɛ͡u -ɛ͡u̯ -ɛ͡ɪ -ɛ͡ʊ -ɜ -ɜː -ɝ -ɝː -ɟ -ɟː -ɟ͡ʝ -ɡ -ɡʱ -ɡʲ -ɡʷ -ɡː -ɡ̊ -ɣ -ɤ -ɥ -ɦ -ɨ -ɨəj -ɨː -ɨ̃ᵝ -ɨ̞ -ɨ̥ᵝ -ɨ̯ -ɨ͡u̯ -ɨ͡w -ɨ͡ə -ɨᵝ -ɨᵝː -ɪ -ɪː -ɪ̀ -ɪ́ -ɪ̃ -ɪ̯ -ɪ̰ -ɪ͡u̯ -ɪ͡ʊ -ɫ -ɫː -ɬ -ɬʼ -ɭ -ɮ -ɯ -ɯː -ɯ̟̃ᵝ -ɯ̟̊ᵝ -ɯ̟ᵝ -ɯ̟ᵝː -ɰ -ɰ̃ -ɰᵝ -ɱ -ɱ̩ -ɲ -ɲː -ɲ̊ -ɲ̟ -ɳ -ɴ -ɸ -ɸʷ -ɹ -ɻ -ɽ -ɽʱ -ɾ -ɾʲ -ɾː -ɾ̝̊ -ʀ -ʁ -ʁʷ -ʁː -ʂ -ʂʷ -ʃ -ʃʰ -ʃʲ -ʃʷ -ʃʷʼ -ʃʼ -ʃː -ʈ -ʈʰ -ʉ -ʉː -ʊ -ʊ̀ -ʊ́ -ʊ̃ -ʊ̯ -ʊ̯͡i -ʊ̯͡ɨ -ʊ̰ -ʋ -ʌ -ʌ̹ -ʍ -ʎ -ʏ -ʏː -ʏ̯ -ʐ -ʐʷ -ʑ -ʒ -ʒʲ -ʒʷ -ʒː -ʔ -ʔʲ -ʔʷ -ʝ -˦ˀ˥ -˦˥ -˦˧˥ -˦˩ -˧ˀ˨ -˧˦ -˧˧ -˧˨ -˧˩ -˨˩ -˨˩˦ -˨˩˨ -β -θ -χ -χʷ -χː -ḛ -ḭ -ṵ -ẽ -ẽː -ẽ̞ -‿ \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv b/nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv deleted file mode 100644 index a55a04b9ab68..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv +++ /dev/null @@ -1,21 +0,0 @@ -Mr. mister -Mrs. misses -Dr. doctor -Drs. doctors -Co. company -Lt. lieutenant -Sgt. sergeant -St. saint -Jr. junior -Maj. major -Hon. honorable -Gov. governor -Capt. captain -Esq. esquire -Gen. general -Ltd. limited -Rev. reverend -Col. colonel -Mt. mount -Ft. fort -etc. et cetera diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/symbol.tsv b/nemo_text_processing/text_normalization/en/data/whitelist/symbol.tsv deleted file mode 100644 index 6f2f8c69a8e6..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/symbol.tsv +++ /dev/null @@ -1,23 +0,0 @@ -& and -# hash -@ at -§ section -™ trademark -® registered trademark -© copyright -_ underscore -% percent sign -* asterisk -+ plus -/ slash -= equal sign -^ circumflex -| vertical bar -~ tilde -$ dollar -£ pound -€ euro -₩ won -¥ yen -° degree -º degree diff --git a/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv b/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv deleted file mode 100644 index e81924755d2e..000000000000 --- a/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv +++ /dev/null @@ -1,3851 +0,0 @@ -Ph.D. PHD -Hon. honorable -Mt. 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WO -W.O. WO -wpt WPT -wp WP -W. P. WP -W.P. WP -Wrec WREC -W. R. WR -W.R. WR -ws WS -W. S. WS -W.S. WS -WTs WT's -WTTs WTT's -W. T. WT -W.T. WT -WUAs WUA's -Wudl WUDL -Wuhr WUHR -Wuhu WUHU -Wu's WU's -wuv WUV -W. U. WU -Wuz WUZ -WVa WVA -W. V. WV -W.V. WV -Wwe WWE -W. W. WW -W.W. WW -wx WX -W.Y. WY -wyzc WYZC -W. Z. WZ -xbg XBG -Xbra XBRA -xCo XCO -X. C. XC -xda XDA -XDRs XDR's -X. D. XD -Xfce XFCE -xf XF -X.F. XF -xh XH -X. H. XH -xk XK -xmc XMC -xml XML -X.M. XM -xO XO -X.O. XO -XPe XPE -X.Q. XQ -XSi XSI -xsr XSR -XTwas XTWA's -xt XT -X. W. XW -xy XY -xyz XYZ -xyZ XYZ -Y. A. YA -Y.A. YA -Y. B. YB -Y.B. YB -ycia YCIA -ycie YCIE -yc YC -Y. C. YC -Y.C. YC -Ydby YDBY -Yde YDE -YdiB YDIB -yd YD -Y. D. YD -Y.D. YD -Y.E. YE -YFCs YFC's -yfle YFLE -YF&R YF and R -yg YG -Y. G. YG -Y.G. YG -Y. H. YH -Y. I. YI -Y.I. YI -yj YJ -Y. J. YJ -Ykt YKT -Y. K. YK -Y.K. YK -Yle YLE -yl YL -Y. L. YL -Ymke YMKE -ym YM -Y. M. YM -yndi YNDI -Yndi YNDI -yne YNE -Yngve YNGVE -Ynis YNI's -yn YN -Yn YN -Y. N. YN -Y.N. YN -Y.O. YO -ypa YPA -Y.P. YP -Y. Q. YQ -yra YRA -Yra YRA -Y&R Y and R -YSK'da YSKDA -YSK'ya YSKYA -Ys Y's -Y.S. YS -yta YTA -Ytre YTRE -Y&T Y and T -Y. T. YT -Y.T. YT -Y. V. YV -Y. W. YW -Y.Y. YY -Z. A. ZA -Z.A. ZA -Zdar ZDAR -zda ZDA -zg ZG -Z.G. ZG -zh ZH -Z. H. ZH -Z.H. ZH -zijn ZIJN -zij ZIJ -Zij ZIJ -Z. I. ZI -Z. J. ZJ -Z.K. ZK -Z.L. ZL -Z.M. ZM -ZnO ZNO -Zpav ZPAV -Z.P. ZP -ZrI ZRI -Zsuzsa ZSUZSA -Z.W. ZW -Z.X. ZX -Z. Y. ZY -Z.Y. ZY -Z. Z. ZZ -Z.Z. ZZ diff --git a/nemo_text_processing/text_normalization/en/graph_utils.py b/nemo_text_processing/text_normalization/en/graph_utils.py deleted file mode 100644 index 33c512f24109..000000000000 --- a/nemo_text_processing/text_normalization/en/graph_utils.py +++ /dev/null @@ -1,196 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os -import string -from pathlib import Path -from typing import Dict - -import pynini -from nemo_text_processing.text_normalization.en.utils import get_abs_path -from pynini import Far -from pynini.examples import plurals -from pynini.export import export -from pynini.lib import byte, pynutil, utf8 - -NEMO_CHAR = utf8.VALID_UTF8_CHAR - -NEMO_DIGIT = byte.DIGIT -NEMO_LOWER = pynini.union(*string.ascii_lowercase).optimize() -NEMO_UPPER = pynini.union(*string.ascii_uppercase).optimize() -NEMO_ALPHA = pynini.union(NEMO_LOWER, NEMO_UPPER).optimize() -NEMO_ALNUM = pynini.union(NEMO_DIGIT, NEMO_ALPHA).optimize() -NEMO_HEX = pynini.union(*string.hexdigits).optimize() -NEMO_NON_BREAKING_SPACE = u"\u00A0" -NEMO_SPACE = " " -NEMO_WHITE_SPACE = pynini.union(" ", "\t", "\n", "\r", u"\u00A0").optimize() -NEMO_NOT_SPACE = pynini.difference(NEMO_CHAR, NEMO_WHITE_SPACE).optimize() -NEMO_NOT_QUOTE = pynini.difference(NEMO_CHAR, r'"').optimize() - -NEMO_PUNCT = pynini.union(*map(pynini.escape, string.punctuation)).optimize() -NEMO_GRAPH = pynini.union(NEMO_ALNUM, NEMO_PUNCT).optimize() - -NEMO_SIGMA = pynini.closure(NEMO_CHAR) - -delete_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE)) -delete_zero_or_one_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE, 0, 1)) -insert_space = pynutil.insert(" ") -delete_extra_space = pynini.cross(pynini.closure(NEMO_WHITE_SPACE, 1), " ") -delete_preserve_order = pynini.closure( - pynutil.delete(" preserve_order: true") - | (pynutil.delete(" field_order: \"") + NEMO_NOT_QUOTE + pynutil.delete("\"")) -) - -suppletive = pynini.string_file(get_abs_path("data/suppletive.tsv")) -# _v = pynini.union("a", "e", "i", "o", "u") -_c = pynini.union( - "b", "c", "d", "f", "g", "h", "j", "k", "l", "m", "n", "p", "q", "r", "s", "t", "v", "w", "x", "y", "z" -) -_ies = NEMO_SIGMA + _c + pynini.cross("y", "ies") -_es = NEMO_SIGMA + pynini.union("s", "sh", "ch", "x", "z") + pynutil.insert("es") -_s = NEMO_SIGMA + pynutil.insert("s") - -graph_plural = plurals._priority_union( - suppletive, plurals._priority_union(_ies, plurals._priority_union(_es, _s, NEMO_SIGMA), NEMO_SIGMA), NEMO_SIGMA -).optimize() - -SINGULAR_TO_PLURAL = graph_plural -PLURAL_TO_SINGULAR = pynini.invert(graph_plural) -TO_LOWER = pynini.union(*[pynini.cross(x, y) for x, y in zip(string.ascii_uppercase, string.ascii_lowercase)]) -TO_UPPER = pynini.invert(TO_LOWER) -MIN_NEG_WEIGHT = -0.0001 -MIN_POS_WEIGHT = 0.0001 - - -def generator_main(file_name: str, graphs: Dict[str, 'pynini.FstLike']): - """ - Exports graph as OpenFst finite state archive (FAR) file with given file name and rule name. - - Args: - file_name: exported file name - graphs: Mapping of a rule name and Pynini WFST graph to be exported - """ - exporter = export.Exporter(file_name) - for rule, graph in graphs.items(): - exporter[rule] = graph.optimize() - exporter.close() - print(f'Created {file_name}') - - -def get_plurals(fst): - """ - Given singular returns plurals - - Args: - fst: Fst - - Returns plurals to given singular forms - """ - return SINGULAR_TO_PLURAL @ fst - - -def get_singulars(fst): - """ - Given plural returns singulars - - Args: - fst: Fst - - Returns singulars to given plural forms - """ - return PLURAL_TO_SINGULAR @ fst - - -def convert_space(fst) -> 'pynini.FstLike': - """ - Converts space to nonbreaking space. - Used only in tagger grammars for transducing token values within quotes, e.g. name: "hello kitty" - This is making transducer significantly slower, so only use when there could be potential spaces within quotes, otherwise leave it. - - Args: - fst: input fst - - Returns output fst where breaking spaces are converted to non breaking spaces - """ - return fst @ pynini.cdrewrite(pynini.cross(NEMO_SPACE, NEMO_NON_BREAKING_SPACE), "", "", NEMO_SIGMA) - - -class GraphFst: - """ - Base class for all grammar fsts. - - Args: - name: name of grammar class - kind: either 'classify' or 'verbalize' - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, name: str, kind: str, deterministic: bool = True): - self.name = name - self.kind = kind - self._fst = None - self.deterministic = deterministic - - self.far_path = Path(os.path.dirname(__file__) + '/grammars/' + kind + '/' + name + '.far') - if self.far_exist(): - self._fst = Far(self.far_path, mode="r", arc_type="standard", far_type="default").get_fst() - - def far_exist(self) -> bool: - """ - Returns true if FAR can be loaded - """ - return self.far_path.exists() - - @property - def fst(self) -> 'pynini.FstLike': - return self._fst - - @fst.setter - def fst(self, fst): - self._fst = fst - - def add_tokens(self, fst) -> 'pynini.FstLike': - """ - Wraps class name around to given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - return pynutil.insert(f"{self.name} {{ ") + fst + pynutil.insert(" }") - - def delete_tokens(self, fst) -> 'pynini.FstLike': - """ - Deletes class name wrap around output of given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - res = ( - pynutil.delete(f"{self.name}") - + delete_space - + pynutil.delete("{") - + delete_space - + fst - + delete_space - + pynutil.delete("}") - ) - return res @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) diff --git a/nemo_text_processing/text_normalization/en/taggers/__init__.py b/nemo_text_processing/text_normalization/en/taggers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/taggers/abbreviation.py b/nemo_text_processing/text_normalization/en/taggers/abbreviation.py deleted file mode 100644 index 640bb487d0f8..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/abbreviation.py +++ /dev/null @@ -1,50 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_UPPER, GraphFst, insert_space -from pynini.lib import pynutil - - -class AbbreviationFst(GraphFst): - """ - Finite state transducer for classifying electronic: as URLs, email addresses, etc. - e.g. "ABC" -> tokens { abbreviation { value: "A B C" } } - - Args: - whitelist: whitelist FST - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, whitelist: 'pynini.FstLike', deterministic: bool = True): - super().__init__(name="abbreviation", kind="classify", deterministic=deterministic) - - dot = pynini.accep(".") - # A.B.C. -> A. B. C. - graph = NEMO_UPPER + dot + pynini.closure(insert_space + NEMO_UPPER + dot, 1) - # A.B.C. -> A.B.C. - graph |= NEMO_UPPER + dot + pynini.closure(NEMO_UPPER + dot, 1) - # ABC -> A B C - graph |= NEMO_UPPER + pynini.closure(insert_space + NEMO_UPPER, 1) - - # exclude words that are included in the whitelist - graph = pynini.compose( - pynini.difference(pynini.project(graph, "input"), pynini.project(whitelist.graph, "input")), graph - ) - - graph = pynutil.insert("value: \"") + graph.optimize() + pynutil.insert("\"") - graph = self.add_tokens(graph) - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/cardinal.py b/nemo_text_processing/text_normalization/en/taggers/cardinal.py deleted file mode 100644 index 9b94143412ab..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/cardinal.py +++ /dev/null @@ -1,138 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - insert_space, -) -from nemo_text_processing.text_normalization.en.taggers.date import get_four_digit_year_graph -from nemo_text_processing.text_normalization.en.utils import get_abs_path -from pynini.examples import plurals -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals, e.g. - -23 -> cardinal { negative: "true" integer: "twenty three" } } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="cardinal", kind="classify", deterministic=deterministic) - - self.lm = lm - self.deterministic = deterministic - # TODO replace to have "oh" as a default for "0" - graph = pynini.Far(get_abs_path("data/number/cardinal_number_name.far")).get_fst() - self.graph_hundred_component_at_least_one_none_zero_digit = ( - pynini.closure(NEMO_DIGIT, 2, 3) | pynini.difference(NEMO_DIGIT, pynini.accep("0")) - ) @ graph - - graph_digit = pynini.string_file(get_abs_path("data/number/digit.tsv")) - graph_zero = pynini.string_file(get_abs_path("data/number/zero.tsv")) - - single_digits_graph = pynini.invert(graph_digit | graph_zero) - self.single_digits_graph = single_digits_graph + pynini.closure(insert_space + single_digits_graph) - - if not deterministic: - # for a single token allow only the same normalization - # "007" -> {"oh oh seven", "zero zero seven"} not {"oh zero seven"} - single_digits_graph_zero = pynini.invert(graph_digit | graph_zero) - single_digits_graph_oh = pynini.invert(graph_digit) | pynini.cross("0", "oh") - - self.single_digits_graph = single_digits_graph_zero + pynini.closure( - insert_space + single_digits_graph_zero - ) - self.single_digits_graph |= single_digits_graph_oh + pynini.closure(insert_space + single_digits_graph_oh) - - single_digits_graph_with_commas = pynini.closure( - self.single_digits_graph + insert_space, 1, 3 - ) + pynini.closure( - pynutil.delete(",") - + single_digits_graph - + insert_space - + single_digits_graph - + insert_space - + single_digits_graph, - 1, - ) - - optional_minus_graph = pynini.closure(pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1) - - graph = ( - pynini.closure(NEMO_DIGIT, 1, 3) - + (pynini.closure(pynutil.delete(",") + NEMO_DIGIT ** 3) | pynini.closure(NEMO_DIGIT ** 3)) - ) @ graph - - self.graph = graph - self.graph_with_and = self.add_optional_and(graph) - - if deterministic: - long_numbers = pynini.compose(NEMO_DIGIT ** (5, ...), self.single_digits_graph).optimize() - final_graph = plurals._priority_union(long_numbers, self.graph_with_and, NEMO_SIGMA).optimize() - cardinal_with_leading_zeros = pynini.compose( - pynini.accep("0") + pynini.closure(NEMO_DIGIT), self.single_digits_graph - ) - final_graph |= cardinal_with_leading_zeros - else: - leading_zeros = pynini.compose(pynini.closure(pynini.accep("0"), 1), self.single_digits_graph) - cardinal_with_leading_zeros = ( - leading_zeros + pynutil.insert(" ") + pynini.compose(pynini.closure(NEMO_DIGIT), self.graph_with_and) - ) - - # add small weight to non-default graphs to make sure the deterministic option is listed first - final_graph = ( - self.graph_with_and - | pynutil.add_weight(self.single_digits_graph, 0.0001) - | get_four_digit_year_graph() # allows e.g. 4567 be pronouced as forty five sixty seven - | pynutil.add_weight(single_digits_graph_with_commas, 0.0001) - | cardinal_with_leading_zeros - ) - - final_graph = optional_minus_graph + pynutil.insert("integer: \"") + final_graph + pynutil.insert("\"") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() - - def add_optional_and(self, graph): - graph_with_and = graph - - if not self.lm: - graph_with_and = pynutil.add_weight(graph, 0.00001) - not_quote = pynini.closure(NEMO_NOT_QUOTE) - no_thousand_million = pynini.difference( - not_quote, not_quote + pynini.union("thousand", "million") + not_quote - ).optimize() - integer = ( - not_quote + pynutil.add_weight(pynini.cross("hundred ", "hundred and ") + no_thousand_million, -0.0001) - ).optimize() - - no_hundred = pynini.difference(NEMO_SIGMA, not_quote + pynini.accep("hundred") + not_quote).optimize() - integer |= ( - not_quote + pynutil.add_weight(pynini.cross("thousand ", "thousand and ") + no_hundred, -0.0001) - ).optimize() - - optional_hundred = pynini.compose((NEMO_DIGIT - "0") ** 3, graph).optimize() - optional_hundred = pynini.compose(optional_hundred, NEMO_SIGMA + pynini.cross(" hundred", "") + NEMO_SIGMA) - graph_with_and |= pynini.compose(graph, integer).optimize() - graph_with_and |= optional_hundred - return graph_with_and diff --git a/nemo_text_processing/text_normalization/en/taggers/date.py b/nemo_text_processing/text_normalization/en/taggers/date.py deleted file mode 100644 index 45031b6e54de..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/date.py +++ /dev/null @@ -1,368 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - NEMO_LOWER, - NEMO_SIGMA, - TO_LOWER, - GraphFst, - delete_extra_space, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.en.utils import ( - augment_labels_with_punct_at_end, - get_abs_path, - load_labels, -) -from pynini.examples import plurals -from pynini.lib import pynutil - -graph_teen = pynini.invert(pynini.string_file(get_abs_path("data/number/teen.tsv"))).optimize() -graph_digit = pynini.invert(pynini.string_file(get_abs_path("data/number/digit.tsv"))).optimize() -ties_graph = pynini.invert(pynini.string_file(get_abs_path("data/number/ty.tsv"))).optimize() -year_suffix = load_labels(get_abs_path("data/date/year_suffix.tsv")) -year_suffix.extend(augment_labels_with_punct_at_end(year_suffix)) -year_suffix = pynini.string_map(year_suffix).optimize() - - -def get_ties_graph(deterministic: bool = True): - """ - Returns two digit transducer, e.g. - 03 -> o three - 12 -> thirteen - 20 -> twenty - """ - graph = graph_teen | ties_graph + pynutil.delete("0") | ties_graph + insert_space + graph_digit - - if deterministic: - graph = graph | pynini.cross("0", "oh") + insert_space + graph_digit - else: - graph = graph | (pynini.cross("0", "oh") | pynini.cross("0", "zero")) + insert_space + graph_digit - - return graph.optimize() - - -def get_four_digit_year_graph(deterministic: bool = True): - """ - Returns a four digit transducer which is combination of ties/teen or digits - (using hundred instead of thousand format), e.g. - 1219 -> twelve nineteen - 3900 -> thirty nine hundred - """ - graph_ties = get_ties_graph(deterministic) - - graph_with_s = ( - (graph_ties + insert_space + graph_ties) - | (graph_teen + insert_space + (ties_graph | pynini.cross("1", "ten"))) - ) + pynutil.delete("0s") - - graph_with_s |= (graph_teen | graph_ties) + insert_space + pynini.cross("00", "hundred") + pynutil.delete("s") - graph_with_s = graph_with_s @ pynini.cdrewrite( - pynini.cross("y", "ies") | pynutil.insert("s"), "", "[EOS]", NEMO_SIGMA - ) - - graph = graph_ties + insert_space + graph_ties - graph |= (graph_teen | graph_ties) + insert_space + pynini.cross("00", "hundred") - - thousand_graph = ( - graph_digit - + insert_space - + pynini.cross("00", "thousand") - + (pynutil.delete("0") | insert_space + graph_digit) - ) - thousand_graph |= ( - graph_digit - + insert_space - + pynini.cross("000", "thousand") - + pynini.closure(pynutil.delete(" "), 0, 1) - + pynini.accep("s") - ) - - graph |= graph_with_s - if deterministic: - graph = plurals._priority_union(thousand_graph, graph, NEMO_SIGMA) - else: - graph |= thousand_graph - - return graph.optimize() - - -def _get_two_digit_year_with_s_graph(): - # to handle '70s -> seventies - graph = ( - pynini.closure(pynutil.delete("'"), 0, 1) - + pynini.compose( - ties_graph + pynutil.delete("0s"), pynini.cdrewrite(pynini.cross("y", "ies"), "", "[EOS]", NEMO_SIGMA) - ) - ).optimize() - return graph - - -def _get_year_graph(cardinal_graph, deterministic: bool = True): - """ - Transducer for year, only from 1000 - 2999 e.g. - 1290 -> twelve nineteen - 2000 - 2009 will be verbalized as two thousand. - - Transducer for 3 digit year, e.g. 123-> one twenty three - - Transducer for year with suffix - 123 A.D., 4200 B.C - """ - graph = get_four_digit_year_graph(deterministic) - graph = (pynini.union("1", "2") + (NEMO_DIGIT ** 3) + pynini.closure(pynini.cross(" s", "s") | "s", 0, 1)) @ graph - - graph |= _get_two_digit_year_with_s_graph() - - three_digit_year = (NEMO_DIGIT @ cardinal_graph) + insert_space + (NEMO_DIGIT ** 2) @ cardinal_graph - year_with_suffix = ( - (get_four_digit_year_graph(deterministic=True) | three_digit_year) + delete_space + insert_space + year_suffix - ) - graph |= year_with_suffix - return graph.optimize() - - -def _get_two_digit_year(cardinal_graph, single_digits_graph): - wo_digit_year = NEMO_DIGIT ** (2) @ plurals._priority_union(cardinal_graph, single_digits_graph, NEMO_SIGMA) - return wo_digit_year - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, e.g. - jan. 5, 2012 -> date { month: "january" day: "five" year: "twenty twelve" preserve_order: true } - jan. 5 -> date { month: "january" day: "five" preserve_order: true } - 5 january 2012 -> date { day: "five" month: "january" year: "twenty twelve" preserve_order: true } - 2012-01-05 -> date { year: "twenty twelve" month: "january" day: "five" } - 2012.01.05 -> date { year: "twenty twelve" month: "january" day: "five" } - 2012/01/05 -> date { year: "twenty twelve" month: "january" day: "five" } - 2012 -> date { year: "twenty twelve" } - - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool, lm: bool = False): - super().__init__(name="date", kind="classify", deterministic=deterministic) - - # january - month_graph = pynini.string_file(get_abs_path("data/date/month_name.tsv")).optimize() - # January, JANUARY - month_graph |= pynini.compose(TO_LOWER + pynini.closure(NEMO_CHAR), month_graph) | pynini.compose( - TO_LOWER ** (2, ...), month_graph - ) - - # jan - month_abbr_graph = pynini.string_file(get_abs_path("data/date/month_abbr.tsv")).optimize() - # jan, Jan, JAN - month_abbr_graph = ( - month_abbr_graph - | pynini.compose(TO_LOWER + pynini.closure(NEMO_LOWER, 1), month_abbr_graph).optimize() - | pynini.compose(TO_LOWER ** (2, ...), month_abbr_graph).optimize() - ) + pynini.closure(pynutil.delete("."), 0, 1) - month_graph |= month_abbr_graph.optimize() - - month_numbers_labels = pynini.string_file(get_abs_path("data/date/month_number.tsv")).optimize() - cardinal_graph = cardinal.graph_hundred_component_at_least_one_none_zero_digit - - year_graph = _get_year_graph(cardinal_graph=cardinal_graph, deterministic=deterministic) - - # three_digit_year = (NEMO_DIGIT @ cardinal_graph) + insert_space + (NEMO_DIGIT ** 2) @ cardinal_graph - # year_graph |= three_digit_year - - month_graph = pynutil.insert("month: \"") + month_graph + pynutil.insert("\"") - month_numbers_graph = pynutil.insert("month: \"") + month_numbers_labels + pynutil.insert("\"") - - endings = ["rd", "th", "st", "nd"] - endings += [x.upper() for x in endings] - endings = pynini.union(*endings) - - day_graph = ( - pynutil.insert("day: \"") - + pynini.closure(pynutil.delete("the "), 0, 1) - + ( - ((pynini.union("1", "2") + NEMO_DIGIT) | NEMO_DIGIT | (pynini.accep("3") + pynini.union("0", "1"))) - + pynini.closure(pynutil.delete(endings), 0, 1) - ) - @ cardinal_graph - + pynutil.insert("\"") - ) - - two_digit_year = _get_two_digit_year( - cardinal_graph=cardinal_graph, single_digits_graph=cardinal.single_digits_graph - ) - two_digit_year = pynutil.insert("year: \"") + two_digit_year + pynutil.insert("\"") - - # if lm: - # two_digit_year = pynini.compose(pynini.difference(NEMO_DIGIT, "0") + NEMO_DIGIT ** (3), two_digit_year) - # year_graph = pynini.compose(pynini.difference(NEMO_DIGIT, "0") + NEMO_DIGIT ** (2), year_graph) - # year_graph |= pynini.compose(pynini.difference(NEMO_DIGIT, "0") + NEMO_DIGIT ** (4, ...), year_graph) - - graph_year = pynutil.insert(" year: \"") + pynutil.delete(" ") + year_graph + pynutil.insert("\"") - graph_year |= ( - pynutil.insert(" year: \"") - + pynini.accep(",") - + pynini.closure(pynini.accep(" "), 0, 1) - + year_graph - + pynutil.insert("\"") - ) - optional_graph_year = pynini.closure(graph_year, 0, 1) - - year_graph = pynutil.insert("year: \"") + year_graph + pynutil.insert("\"") - - graph_mdy = month_graph + ( - (delete_extra_space + day_graph) - | (pynini.accep(" ") + day_graph) - | graph_year - | (delete_extra_space + day_graph + graph_year) - ) - - graph_mdy |= ( - month_graph - + pynini.cross("-", " ") - + day_graph - + pynini.closure(((pynini.cross("-", " ") + NEMO_SIGMA) @ graph_year), 0, 1) - ) - - for x in ["-", "/", "."]: - delete_sep = pynutil.delete(x) - graph_mdy |= ( - month_numbers_graph - + delete_sep - + insert_space - + pynini.closure(pynutil.delete("0"), 0, 1) - + day_graph - + delete_sep - + insert_space - + (year_graph | two_digit_year) - ) - - graph_dmy = day_graph + delete_extra_space + month_graph + optional_graph_year - day_ex_month = (NEMO_DIGIT ** 2 - pynini.project(month_numbers_graph, "input")) @ day_graph - for x in ["-", "/", "."]: - delete_sep = pynutil.delete(x) - graph_dmy |= ( - day_ex_month - + delete_sep - + insert_space - + month_numbers_graph - + delete_sep - + insert_space - + (year_graph | two_digit_year) - ) - - graph_ymd = pynini.accep("") - for x in ["-", "/", "."]: - delete_sep = pynutil.delete(x) - graph_ymd |= ( - (year_graph | two_digit_year) - + delete_sep - + insert_space - + month_numbers_graph - + delete_sep - + insert_space - + pynini.closure(pynutil.delete("0"), 0, 1) - + day_graph - ) - - final_graph = graph_mdy | graph_dmy - - if not deterministic or lm: - final_graph += pynini.closure(pynutil.insert(" preserve_order: true"), 0, 1) - m_sep_d = ( - month_numbers_graph - + pynutil.delete(pynini.union("-", "/")) - + insert_space - + pynini.closure(pynutil.delete("0"), 0, 1) - + day_graph - ) - final_graph |= m_sep_d - else: - final_graph += pynutil.insert(" preserve_order: true") - - final_graph |= graph_ymd | year_graph - - if not deterministic or lm: - ymd_to_mdy_graph = None - ymd_to_dmy_graph = None - mdy_to_dmy_graph = None - md_to_dm_graph = None - - for month in [x[0] for x in load_labels(get_abs_path("data/date/month_name.tsv"))]: - for day in [x[0] for x in load_labels(get_abs_path("data/date/day.tsv"))]: - ymd_to_mdy_curr = ( - pynutil.insert("month: \"" + month + "\" day: \"" + day + "\" ") - + pynini.accep('year:') - + NEMO_SIGMA - + pynutil.delete(" month: \"" + month + "\" day: \"" + day + "\"") - ) - - # YY-MM-DD -> MM-DD-YY - ymd_to_mdy_curr = pynini.compose(graph_ymd, ymd_to_mdy_curr) - ymd_to_mdy_graph = ( - ymd_to_mdy_curr - if ymd_to_mdy_graph is None - else pynini.union(ymd_to_mdy_curr, ymd_to_mdy_graph) - ) - - ymd_to_dmy_curr = ( - pynutil.insert("day: \"" + day + "\" month: \"" + month + "\" ") - + pynini.accep('year:') - + NEMO_SIGMA - + pynutil.delete(" month: \"" + month + "\" day: \"" + day + "\"") - ) - - # YY-MM-DD -> MM-DD-YY - ymd_to_dmy_curr = pynini.compose(graph_ymd, ymd_to_dmy_curr).optimize() - ymd_to_dmy_graph = ( - ymd_to_dmy_curr - if ymd_to_dmy_graph is None - else pynini.union(ymd_to_dmy_curr, ymd_to_dmy_graph) - ) - - mdy_to_dmy_curr = ( - pynutil.insert("day: \"" + day + "\" month: \"" + month + "\" ") - + pynutil.delete("month: \"" + month + "\" day: \"" + day + "\" ") - + pynini.accep('year:') - + NEMO_SIGMA - ).optimize() - # MM-DD-YY -> verbalize as MM-DD-YY (February fourth 1991) or DD-MM-YY (the fourth of February 1991) - mdy_to_dmy_curr = pynini.compose(graph_mdy, mdy_to_dmy_curr).optimize() - mdy_to_dmy_graph = ( - mdy_to_dmy_curr - if mdy_to_dmy_graph is None - else pynini.union(mdy_to_dmy_curr, mdy_to_dmy_graph).optimize() - ).optimize() - - md_to_dm_curr = pynutil.insert("day: \"" + day + "\" month: \"" + month + "\"") + pynutil.delete( - "month: \"" + month + "\" day: \"" + day + "\"" - ) - md_to_dm_curr = pynini.compose(m_sep_d, md_to_dm_curr).optimize() - - md_to_dm_graph = ( - md_to_dm_curr - if md_to_dm_graph is None - else pynini.union(md_to_dm_curr, md_to_dm_graph).optimize() - ).optimize() - - final_graph |= mdy_to_dmy_graph | md_to_dm_graph | ymd_to_mdy_graph | ymd_to_dmy_graph - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/decimal.py b/nemo_text_processing/text_normalization/en/taggers/decimal.py deleted file mode 100644 index 2486b5f8c1ce..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/decimal.py +++ /dev/null @@ -1,129 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, TO_UPPER, GraphFst, get_abs_path -from pynini.lib import pynutil - -delete_space = pynutil.delete(" ") -quantities = pynini.string_file(get_abs_path("data/number/thousand.tsv")) -quantities_abbr = pynini.string_file(get_abs_path("data/number/quantity_abbr.tsv")) -quantities_abbr |= TO_UPPER @ quantities_abbr - - -def get_quantity( - decimal: 'pynini.FstLike', cardinal_up_to_hundred: 'pynini.FstLike', include_abbr: bool -) -> 'pynini.FstLike': - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. 1 million -> integer_part: "one" quantity: "million" - e.g. 1.5 million -> integer_part: "one" fractional_part: "five" quantity: "million" - - Args: - decimal: decimal FST - cardinal_up_to_hundred: cardinal FST - """ - quantity_wo_thousand = pynini.project(quantities, "input") - pynini.union("k", "K", "thousand") - if include_abbr: - quantity_wo_thousand |= pynini.project(quantities_abbr, "input") - pynini.union("k", "K", "thousand") - res = ( - pynutil.insert("integer_part: \"") - + cardinal_up_to_hundred - + pynutil.insert("\"") - + pynini.closure(pynutil.delete(" "), 0, 1) - + pynutil.insert(" quantity: \"") - + (quantity_wo_thousand @ (quantities | quantities_abbr)) - + pynutil.insert("\"") - ) - if include_abbr: - quantity = quantities | quantities_abbr - else: - quantity = quantities - res |= ( - decimal - + pynini.closure(pynutil.delete(" "), 0, 1) - + pynutil.insert("quantity: \"") - + quantity - + pynutil.insert("\"") - ) - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal, e.g. - -12.5006 billion -> decimal { negative: "true" integer_part: "12" fractional_part: "five o o six" quantity: "billion" } - 1 billion -> decimal { integer_part: "one" quantity: "billion" } - - cardinal: CardinalFst - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - - cardinal_graph = cardinal.graph_with_and - cardinal_graph_hundred_component_at_least_one_none_zero_digit = ( - cardinal.graph_hundred_component_at_least_one_none_zero_digit - ) - - self.graph = cardinal.single_digits_graph.optimize() - - if not deterministic: - self.graph = self.graph | cardinal_graph - - point = pynutil.delete(".") - optional_graph_negative = pynini.closure(pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1) - - self.graph_fractional = pynutil.insert("fractional_part: \"") + self.graph + pynutil.insert("\"") - self.graph_integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - final_graph_wo_sign = ( - pynini.closure(self.graph_integer + pynutil.insert(" "), 0, 1) - + point - + pynutil.insert(" ") - + self.graph_fractional - ) - - quantity_w_abbr = get_quantity( - final_graph_wo_sign, cardinal_graph_hundred_component_at_least_one_none_zero_digit, include_abbr=True - ) - quantity_wo_abbr = get_quantity( - final_graph_wo_sign, cardinal_graph_hundred_component_at_least_one_none_zero_digit, include_abbr=False - ) - self.final_graph_wo_negative_w_abbr = final_graph_wo_sign | quantity_w_abbr - self.final_graph_wo_negative = final_graph_wo_sign | quantity_wo_abbr - - # reduce options for non_deterministic and allow either "oh" or "zero", but not combination - if not deterministic: - no_oh_zero = pynini.difference( - NEMO_SIGMA, - (NEMO_SIGMA + "oh" + NEMO_SIGMA + "zero" + NEMO_SIGMA) - | (NEMO_SIGMA + "zero" + NEMO_SIGMA + "oh" + NEMO_SIGMA), - ).optimize() - no_zero_oh = pynini.difference( - NEMO_SIGMA, NEMO_SIGMA + pynini.accep("zero") + NEMO_SIGMA + pynini.accep("oh") + NEMO_SIGMA - ).optimize() - - self.final_graph_wo_negative |= pynini.compose( - self.final_graph_wo_negative, - pynini.cdrewrite( - pynini.cross("integer_part: \"zero\"", "integer_part: \"oh\""), NEMO_SIGMA, NEMO_SIGMA, NEMO_SIGMA - ), - ) - self.final_graph_wo_negative = pynini.compose(self.final_graph_wo_negative, no_oh_zero).optimize() - self.final_graph_wo_negative = pynini.compose(self.final_graph_wo_negative, no_zero_oh).optimize() - - final_graph = optional_graph_negative + self.final_graph_wo_negative - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/electronic.py b/nemo_text_processing/text_normalization/en/taggers/electronic.py deleted file mode 100644 index 243c0653f6a1..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/electronic.py +++ /dev/null @@ -1,87 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - get_abs_path, - insert_space, -) -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic: as URLs, email addresses, etc. - e.g. cdf1@abc.edu -> tokens { electronic { username: "cdf1" domain: "abc.edu" } } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="classify", deterministic=deterministic) - - accepted_symbols = pynini.project(pynini.string_file(get_abs_path("data/electronic/symbol.tsv")), "input") - accepted_common_domains = pynini.project( - pynini.string_file(get_abs_path("data/electronic/domain.tsv")), "input" - ) - all_accepted_symbols = NEMO_ALPHA + pynini.closure(NEMO_ALPHA | NEMO_DIGIT | accepted_symbols) - graph_symbols = pynini.string_file(get_abs_path("data/electronic/symbol.tsv")).optimize() - - username = ( - pynutil.insert("username: \"") + all_accepted_symbols + pynutil.insert("\"") + pynini.cross('@', ' ') - ) - domain_graph = all_accepted_symbols + pynini.accep('.') + all_accepted_symbols + NEMO_ALPHA - protocol_symbols = pynini.closure((graph_symbols | pynini.cross(":", "semicolon")) + pynutil.insert(" ")) - protocol_start = (pynini.cross("https", "HTTPS ") | pynini.cross("http", "HTTP ")) + ( - pynini.accep("://") @ protocol_symbols - ) - protocol_file_start = pynini.accep("file") + insert_space + (pynini.accep(":///") @ protocol_symbols) - - protocol_end = pynini.cross("www", "WWW ") + pynini.accep(".") @ protocol_symbols - protocol = protocol_file_start | protocol_start | protocol_end | (protocol_start + protocol_end) - - domain_graph = ( - pynutil.insert("domain: \"") - + pynini.difference(domain_graph, pynini.project(protocol, "input") + NEMO_SIGMA) - + pynutil.insert("\"") - ) - domain_common_graph = ( - pynutil.insert("domain: \"") - + pynini.difference( - all_accepted_symbols - + accepted_common_domains - + pynini.closure(accepted_symbols + pynini.closure(NEMO_ALPHA | NEMO_DIGIT | accepted_symbols), 0, 1), - pynini.project(protocol, "input") + NEMO_SIGMA, - ) - + pynutil.insert("\"") - ) - - protocol = pynutil.insert("protocol: \"") + protocol + pynutil.insert("\"") - # email - graph = username + domain_graph - # abc.com, abc.com/123-sm - graph |= domain_common_graph - # www.abc.com/sdafsdf, or https://www.abc.com/asdfad or www.abc.abc/asdfad - graph |= protocol + pynutil.insert(" ") + domain_graph - - final_graph = self.add_tokens(graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/fraction.py b/nemo_text_processing/text_normalization/en/taggers/fraction.py deleted file mode 100644 index ac6877c22950..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/fraction.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, get_abs_path -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for classifying fraction - "23 4/5" -> - tokens { fraction { integer: "twenty three" numerator: "four" denominator: "five" } } - "23 4/5th" -> - tokens { fraction { integer: "twenty three" numerator: "four" denominator: "five" } } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal, deterministic: bool = True): - super().__init__(name="fraction", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph - - integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") - numerator = ( - pynutil.insert("numerator: \"") + cardinal_graph + (pynini.cross("/", "\" ") | pynini.cross(" / ", "\" ")) - ) - - endings = ["rd", "th", "st", "nd"] - endings += [x.upper() for x in endings] - optional_end = pynini.closure(pynini.cross(pynini.union(*endings), ""), 0, 1) - - denominator = pynutil.insert("denominator: \"") + cardinal_graph + optional_end + pynutil.insert("\"") - - graph = pynini.closure(integer + pynini.accep(" "), 0, 1) + (numerator + denominator) - graph |= pynini.closure(integer + (pynini.accep(" ") | pynutil.insert(" ")), 0, 1) + pynini.compose( - pynini.string_file(get_abs_path("data/number/fraction.tsv")), (numerator + denominator) - ) - - self.graph = graph - final_graph = self.add_tokens(self.graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/measure.py b/nemo_text_processing/text_normalization/en/taggers/measure.py deleted file mode 100644 index 3861f9168a07..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/measure.py +++ /dev/null @@ -1,304 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_NON_BREAKING_SPACE, - NEMO_SIGMA, - NEMO_SPACE, - NEMO_UPPER, - SINGULAR_TO_PLURAL, - TO_LOWER, - GraphFst, - convert_space, - delete_space, - delete_zero_or_one_space, - insert_space, -) -from nemo_text_processing.text_normalization.en.taggers.ordinal import OrdinalFst as OrdinalTagger -from nemo_text_processing.text_normalization.en.taggers.whitelist import get_formats -from nemo_text_processing.text_normalization.en.utils import get_abs_path, load_labels -from nemo_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst as OrdinalVerbalizer -from pynini.examples import plurals -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure, suppletive aware, e.g. - -12kg -> measure { negative: "true" cardinal { integer: "twelve" } units: "kilograms" } - 1kg -> measure { cardinal { integer: "one" } units: "kilogram" } - .5kg -> measure { decimal { fractional_part: "five" } units: "kilograms" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - fraction: FractionFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, fraction: GraphFst, deterministic: bool = True): - super().__init__(name="measure", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph_with_and | self.get_range(cardinal.graph_with_and) - - graph_unit = pynini.string_file(get_abs_path("data/measure/unit.tsv")) - if not deterministic: - graph_unit |= pynini.string_file(get_abs_path("data/measure/unit_alternatives.tsv")) - - graph_unit |= pynini.compose( - pynini.closure(TO_LOWER, 1) + (NEMO_ALPHA | TO_LOWER) + pynini.closure(NEMO_ALPHA | TO_LOWER), graph_unit - ).optimize() - - graph_unit_plural = convert_space(graph_unit @ SINGULAR_TO_PLURAL) - graph_unit = convert_space(graph_unit) - - optional_graph_negative = pynini.closure(pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1) - - graph_unit2 = ( - pynini.cross("/", "per") + delete_zero_or_one_space + pynutil.insert(NEMO_NON_BREAKING_SPACE) + graph_unit - ) - - optional_graph_unit2 = pynini.closure( - delete_zero_or_one_space + pynutil.insert(NEMO_NON_BREAKING_SPACE) + graph_unit2, 0, 1, - ) - - unit_plural = ( - pynutil.insert("units: \"") - + (graph_unit_plural + optional_graph_unit2 | graph_unit2) - + pynutil.insert("\"") - ) - - unit_singular = ( - pynutil.insert("units: \"") + (graph_unit + optional_graph_unit2 | graph_unit2) + pynutil.insert("\"") - ) - - subgraph_decimal = ( - pynutil.insert("decimal { ") - + optional_graph_negative - + decimal.final_graph_wo_negative - + delete_space - + pynutil.insert(" } ") - + unit_plural - ) - - # support radio FM/AM - subgraph_decimal |= ( - pynutil.insert("decimal { ") - + decimal.final_graph_wo_negative - + delete_space - + pynutil.insert(" } ") - + pynutil.insert("units: \"") - + pynini.union("AM", "FM") - + pynutil.insert("\"") - ) - - subgraph_cardinal = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + ((NEMO_SIGMA - "1") @ cardinal_graph) - + delete_space - + pynutil.insert("\"") - + pynutil.insert(" } ") - + unit_plural - ) - - subgraph_cardinal |= ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + pynini.cross("1", "one") - + delete_space - + pynutil.insert("\"") - + pynutil.insert(" } ") - + unit_singular - ) - - unit_graph = ( - pynutil.insert("cardinal { integer: \"-\" } units: \"") - + pynini.cross(pynini.union("/", "per"), "per") - + delete_zero_or_one_space - + pynutil.insert(NEMO_NON_BREAKING_SPACE) - + graph_unit - + pynutil.insert("\" preserve_order: true") - ) - - decimal_dash_alpha = ( - pynutil.insert("decimal { ") - + decimal.final_graph_wo_negative - + pynini.cross('-', '') - + pynutil.insert(" } units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.insert("\"") - ) - - decimal_times = ( - pynutil.insert("decimal { ") - + decimal.final_graph_wo_negative - + pynutil.insert(" } units: \"") - + pynini.cross(pynini.union('x', "X"), 'x') - + pynutil.insert("\"") - ) - - alpha_dash_decimal = ( - pynutil.insert("units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynini.accep('-') - + pynutil.insert("\"") - + pynutil.insert(" decimal { ") - + decimal.final_graph_wo_negative - + pynutil.insert(" } preserve_order: true") - ) - - subgraph_fraction = ( - pynutil.insert("fraction { ") + fraction.graph + delete_space + pynutil.insert(" } ") + unit_plural - ) - - address = self.get_address_graph(cardinal) - address = ( - pynutil.insert("units: \"address\" cardinal { integer: \"") - + address - + pynutil.insert("\" } preserve_order: true") - ) - - math_operations = pynini.string_file(get_abs_path("data/measure/math_operation.tsv")) - delimiter = pynini.accep(" ") | pynutil.insert(" ") - - math = ( - (cardinal_graph | NEMO_ALPHA) - + delimiter - + math_operations - + (delimiter | NEMO_ALPHA) - + cardinal_graph - + delimiter - + pynini.cross("=", "equals") - + delimiter - + (cardinal_graph | NEMO_ALPHA) - ) - - math |= ( - (cardinal_graph | NEMO_ALPHA) - + delimiter - + pynini.cross("=", "equals") - + delimiter - + (cardinal_graph | NEMO_ALPHA) - + delimiter - + math_operations - + delimiter - + cardinal_graph - ) - - math = ( - pynutil.insert("units: \"math\" cardinal { integer: \"") - + math - + pynutil.insert("\" } preserve_order: true") - ) - final_graph = ( - subgraph_decimal - | subgraph_cardinal - | unit_graph - | decimal_dash_alpha - | decimal_times - | alpha_dash_decimal - | subgraph_fraction - | address - | math - ) - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() - - def get_range(self, cardinal: GraphFst): - """ - Returns range forms for measure tagger, e.g. 2-3, 2x3, 2*2 - - Args: - cardinal: cardinal GraphFst - """ - range_graph = cardinal + pynini.cross(pynini.union("-", " - "), " to ") + cardinal - - for x in [" x ", "x"]: - range_graph |= cardinal + pynini.cross(x, " by ") + cardinal - if not self.deterministic: - range_graph |= cardinal + pynini.cross(x, " times ") + cardinal - - for x in ["*", " * "]: - range_graph |= cardinal + pynini.cross(x, " times ") + cardinal - return range_graph.optimize() - - def get_address_graph(self, cardinal): - """ - Finite state transducer for classifying serial. - The serial is a combination of digits, letters and dashes, e.g.: - 2788 San Tomas Expy, Santa Clara, CA 95051 -> - units: "address" cardinal - { integer: "two seven eight eight San Tomas Expressway Santa Clara California nine five zero five one" } - preserve_order: true - """ - ordinal_verbalizer = OrdinalVerbalizer().graph - ordinal_tagger = OrdinalTagger(cardinal=cardinal).graph - ordinal_num = pynini.compose( - pynutil.insert("integer: \"") + ordinal_tagger + pynutil.insert("\""), ordinal_verbalizer - ) - - address_num = NEMO_DIGIT ** (1, 2) @ cardinal.graph_hundred_component_at_least_one_none_zero_digit - address_num += insert_space + NEMO_DIGIT ** 2 @ ( - pynini.closure(pynini.cross("0", "zero "), 0, 1) - + cardinal.graph_hundred_component_at_least_one_none_zero_digit - ) - # to handle the rest of the numbers - address_num = pynini.compose(NEMO_DIGIT ** (3, 4), address_num) - address_num = plurals._priority_union(address_num, cardinal.graph, NEMO_SIGMA) - - direction = ( - pynini.cross("E", "East") - | pynini.cross("S", "South") - | pynini.cross("W", "West") - | pynini.cross("N", "North") - ) + pynini.closure(pynutil.delete("."), 0, 1) - - direction = pynini.closure(pynini.accep(NEMO_SPACE) + direction, 0, 1) - address_words = get_formats(get_abs_path("data/address/address_word.tsv")) - address_words = ( - pynini.accep(NEMO_SPACE) - + (pynini.closure(ordinal_num, 0, 1) | NEMO_UPPER + pynini.closure(NEMO_ALPHA, 1)) - + NEMO_SPACE - + pynini.closure(NEMO_UPPER + pynini.closure(NEMO_ALPHA) + NEMO_SPACE) - + address_words - ) - - city = pynini.closure(NEMO_ALPHA | pynini.accep(NEMO_SPACE), 1) - city = pynini.closure(pynini.accep(",") + pynini.accep(NEMO_SPACE) + city, 0, 1) - - states = load_labels(get_abs_path("data/address/state.tsv")) - - additional_options = [] - for x, y in states: - additional_options.append((x, f"{y[0]}.{y[1:]}")) - states.extend(additional_options) - state_graph = pynini.string_map(states) - state = pynini.invert(state_graph) - state = pynini.closure(pynini.accep(",") + pynini.accep(NEMO_SPACE) + state, 0, 1) - - zip_code = pynini.compose(NEMO_DIGIT ** 5, cardinal.single_digits_graph) - zip_code = pynini.closure(pynini.closure(pynini.accep(","), 0, 1) + pynini.accep(NEMO_SPACE) + zip_code, 0, 1,) - - address = address_num + direction + address_words + pynini.closure(city + state + zip_code, 0, 1) - - address |= address_num + direction + address_words + pynini.closure(pynini.cross(".", ""), 0, 1) - - return address diff --git a/nemo_text_processing/text_normalization/en/taggers/money.py b/nemo_text_processing/text_normalization/en/taggers/money.py deleted file mode 100644 index 43e26bda7b4d..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/money.py +++ /dev/null @@ -1,192 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - SINGULAR_TO_PLURAL, - GraphFst, - convert_space, - insert_space, -) -from nemo_text_processing.text_normalization.en.utils import get_abs_path, load_labels -from pynini.lib import pynutil - -min_singular = pynini.string_file(get_abs_path("data/money/currency_minor_singular.tsv")) -min_plural = pynini.string_file(get_abs_path("data/money/currency_minor_plural.tsv")) -maj_singular = pynini.string_file((get_abs_path("data/money/currency_major.tsv"))) - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money, suppletive aware, e.g. - $12.05 -> money { integer_part: "twelve" currency_maj: "dollars" fractional_part: "five" currency_min: "cents" preserve_order: true } - $12.0500 -> money { integer_part: "twelve" currency_maj: "dollars" fractional_part: "five" currency_min: "cents" preserve_order: true } - $1 -> money { currency_maj: "dollar" integer_part: "one" } - $1.00 -> money { currency_maj: "dollar" integer_part: "one" } - $0.05 -> money { fractional_part: "five" currency_min: "cents" preserve_order: true } - $1 million -> money { currency_maj: "dollars" integer_part: "one" quantity: "million" } - $1.2 million -> money { currency_maj: "dollars" integer_part: "one" fractional_part: "two" quantity: "million" } - $1.2320 -> money { currency_maj: "dollars" integer_part: "one" fractional_part: "two three two" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph_with_and - graph_decimal_final = decimal.final_graph_wo_negative_w_abbr - - maj_singular_labels = load_labels(get_abs_path("data/money/currency_major.tsv")) - maj_unit_plural = convert_space(maj_singular @ SINGULAR_TO_PLURAL) - maj_unit_singular = convert_space(maj_singular) - - graph_maj_singular = pynutil.insert("currency_maj: \"") + maj_unit_singular + pynutil.insert("\"") - graph_maj_plural = pynutil.insert("currency_maj: \"") + maj_unit_plural + pynutil.insert("\"") - - optional_delete_fractional_zeros = pynini.closure( - pynutil.delete(".") + pynini.closure(pynutil.delete("0"), 1), 0, 1 - ) - - graph_integer_one = pynutil.insert("integer_part: \"") + pynini.cross("1", "one") + pynutil.insert("\"") - # only for decimals where third decimal after comma is non-zero or with quantity - decimal_delete_last_zeros = ( - pynini.closure(NEMO_DIGIT | pynutil.delete(",")) - + pynini.accep(".") - + pynini.closure(NEMO_DIGIT, 2) - + (NEMO_DIGIT - "0") - + pynini.closure(pynutil.delete("0")) - ) - decimal_with_quantity = NEMO_SIGMA + NEMO_ALPHA - - graph_decimal = ( - graph_maj_plural + insert_space + (decimal_delete_last_zeros | decimal_with_quantity) @ graph_decimal_final - ) - - graph_integer = ( - pynutil.insert("integer_part: \"") + ((NEMO_SIGMA - "1") @ cardinal_graph) + pynutil.insert("\"") - ) - - graph_integer_only = graph_maj_singular + insert_space + graph_integer_one - graph_integer_only |= graph_maj_plural + insert_space + graph_integer - - final_graph = (graph_integer_only + optional_delete_fractional_zeros) | graph_decimal - - # remove trailing zeros of non zero number in the first 2 digits and fill up to 2 digits - # e.g. 2000 -> 20, 0200->02, 01 -> 01, 10 -> 10 - # not accepted: 002, 00, 0, - two_digits_fractional_part = ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(pynutil.delete("0")) - ) @ ( - (pynutil.delete("0") + (NEMO_DIGIT - "0")) - | ((NEMO_DIGIT - "0") + pynutil.insert("0")) - | ((NEMO_DIGIT - "0") + NEMO_DIGIT) - ) - - graph_min_singular = pynutil.insert(" currency_min: \"") + min_singular + pynutil.insert("\"") - graph_min_plural = pynutil.insert(" currency_min: \"") + min_plural + pynutil.insert("\"") - # format ** dollars ** cent - decimal_graph_with_minor = None - integer_graph_reordered = None - decimal_default_reordered = None - for curr_symbol, _ in maj_singular_labels: - preserve_order = pynutil.insert(" preserve_order: true") - integer_plus_maj = graph_integer + insert_space + pynutil.insert(curr_symbol) @ graph_maj_plural - integer_plus_maj |= graph_integer_one + insert_space + pynutil.insert(curr_symbol) @ graph_maj_singular - - integer_plus_maj_with_comma = pynini.compose( - NEMO_DIGIT - "0" + pynini.closure(NEMO_DIGIT | pynutil.delete(",")), integer_plus_maj - ) - integer_plus_maj = pynini.compose(pynini.closure(NEMO_DIGIT) - "0", integer_plus_maj) - integer_plus_maj |= integer_plus_maj_with_comma - - graph_fractional_one = two_digits_fractional_part @ pynini.cross("1", "one") - graph_fractional_one = pynutil.insert("fractional_part: \"") + graph_fractional_one + pynutil.insert("\"") - graph_fractional = ( - two_digits_fractional_part - @ (pynini.closure(NEMO_DIGIT, 1, 2) - "1") - @ cardinal.graph_hundred_component_at_least_one_none_zero_digit - ) - graph_fractional = pynutil.insert("fractional_part: \"") + graph_fractional + pynutil.insert("\"") - - fractional_plus_min = graph_fractional + insert_space + pynutil.insert(curr_symbol) @ graph_min_plural - fractional_plus_min |= ( - graph_fractional_one + insert_space + pynutil.insert(curr_symbol) @ graph_min_singular - ) - - decimal_graph_with_minor_curr = integer_plus_maj + pynini.cross(".", " ") + fractional_plus_min - - if not deterministic: - decimal_graph_with_minor_curr |= pynutil.add_weight( - integer_plus_maj - + pynini.cross(".", " ") - + pynutil.insert("fractional_part: \"") - + two_digits_fractional_part @ cardinal.graph_hundred_component_at_least_one_none_zero_digit - + pynutil.insert("\""), - weight=0.0001, - ) - default_fraction_graph = (decimal_delete_last_zeros | decimal_with_quantity) @ graph_decimal_final - decimal_graph_with_minor_curr |= ( - pynini.closure(pynutil.delete("0"), 0, 1) + pynutil.delete(".") + fractional_plus_min - ) - decimal_graph_with_minor_curr = ( - pynutil.delete(curr_symbol) + decimal_graph_with_minor_curr + preserve_order - ) - - decimal_graph_with_minor = ( - decimal_graph_with_minor_curr - if decimal_graph_with_minor is None - else pynini.union(decimal_graph_with_minor, decimal_graph_with_minor_curr).optimize() - ) - - if not deterministic: - integer_graph_reordered_curr = ( - pynutil.delete(curr_symbol) + integer_plus_maj + preserve_order - ).optimize() - - integer_graph_reordered = ( - integer_graph_reordered_curr - if integer_graph_reordered is None - else pynini.union(integer_graph_reordered, integer_graph_reordered_curr).optimize() - ) - decimal_default_reordered_curr = ( - pynutil.delete(curr_symbol) - + default_fraction_graph - + insert_space - + pynutil.insert(curr_symbol) @ graph_maj_plural - ) - - decimal_default_reordered = ( - decimal_default_reordered_curr - if decimal_default_reordered is None - else pynini.union(decimal_default_reordered, decimal_default_reordered_curr) - ).optimize() - - # weight for SH - final_graph |= pynutil.add_weight(decimal_graph_with_minor, -0.0001) - - if not deterministic: - final_graph |= integer_graph_reordered | decimal_default_reordered - # to handle "$2.00" cases - final_graph |= pynini.compose( - NEMO_SIGMA + pynutil.delete(".") + pynini.closure(pynutil.delete("0"), 1), integer_graph_reordered - ) - final_graph = self.add_tokens(final_graph.optimize()) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/ordinal.py b/nemo_text_processing/text_normalization/en/taggers/ordinal.py deleted file mode 100644 index 1ea56c917011..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/ordinal.py +++ /dev/null @@ -1,61 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal, e.g. - 13th -> ordinal { integer: "thirteen" } - - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="ordinal", kind="classify", deterministic=deterministic) - - cardinal_graph = cardinal.graph - cardinal_format = pynini.closure(NEMO_DIGIT | pynini.accep(",")) - st_format = ( - pynini.closure(cardinal_format + (NEMO_DIGIT - "1"), 0, 1) - + pynini.accep("1") - + pynutil.delete(pynini.union("st", "ST")) - ) - nd_format = ( - pynini.closure(cardinal_format + (NEMO_DIGIT - "1"), 0, 1) - + pynini.accep("2") - + pynutil.delete(pynini.union("nd", "ND")) - ) - rd_format = ( - pynini.closure(cardinal_format + (NEMO_DIGIT - "1"), 0, 1) - + pynini.accep("3") - + pynutil.delete(pynini.union("rd", "RD")) - ) - th_format = pynini.closure( - (NEMO_DIGIT - "1" - "2" - "3") - | (cardinal_format + "1" + NEMO_DIGIT) - | (cardinal_format + (NEMO_DIGIT - "1") + (NEMO_DIGIT - "1" - "2" - "3")), - 1, - ) + pynutil.delete(pynini.union("th", "TH")) - self.graph = (st_format | nd_format | rd_format | th_format) @ cardinal_graph - final_graph = pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/punctuation.py b/nemo_text_processing/text_normalization/en/taggers/punctuation.py deleted file mode 100644 index 769b020ce382..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/punctuation.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import sys -from unicodedata import category - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_SPACE, NEMO_SIGMA, GraphFst -from nemo_text_processing.text_normalization.en.utils import get_abs_path, load_labels -from pynini.examples import plurals -from pynini.lib import pynutil - - -class PunctuationFst(GraphFst): - """ - Finite state transducer for classifying punctuation - e.g. a, -> tokens { name: "a" } tokens { name: "," } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="punctuation", kind="classify", deterministic=deterministic) - s = "!#%&\'()*+,-./:;<=>?@^_`{|}~\"" - - punct_symbols_to_exclude = ["[", "]"] - punct_unicode = [ - chr(i) - for i in range(sys.maxunicode) - if category(chr(i)).startswith("P") and chr(i) not in punct_symbols_to_exclude - ] - - whitelist_symbols = load_labels(get_abs_path("data/whitelist/symbol.tsv")) - whitelist_symbols = [x[0] for x in whitelist_symbols] - self.punct_marks = [p for p in punct_unicode + list(s) if p not in whitelist_symbols] - - punct = pynini.union(*self.punct_marks) - punct = pynini.closure(punct, 1) - - emphasis = ( - pynini.accep("<") - + ( - (pynini.closure(NEMO_NOT_SPACE - pynini.union("<", ">"), 1) + pynini.closure(pynini.accep("/"), 0, 1)) - | (pynini.accep("/") + pynini.closure(NEMO_NOT_SPACE - pynini.union("<", ">"), 1)) - ) - + pynini.accep(">") - ) - punct = plurals._priority_union(emphasis, punct, NEMO_SIGMA) - - self.graph = punct - self.fst = (pynutil.insert("name: \"") + self.graph + pynutil.insert("\"")).optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/range.py b/nemo_text_processing/text_normalization/en/taggers/range.py deleted file mode 100644 index 9c237f9c28c8..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/range.py +++ /dev/null @@ -1,102 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst, convert_space -from pynini.lib import pynutil - - -class RangeFst(GraphFst): - """ - This class is a composite class of two other class instances - - Args: - time: composed tagger and verbalizer - date: composed tagger and verbalizer - cardinal: tagger - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - lm: whether to use for hybrid LM - """ - - def __init__( - self, time: GraphFst, date: GraphFst, cardinal: GraphFst, deterministic: bool = True, lm: bool = False, - ): - super().__init__(name="range", kind="classify", deterministic=deterministic) - - delete_space = pynini.closure(pynutil.delete(" "), 0, 1) - - approx = pynini.cross("~", "approximately") - - # TIME - time_graph = time + delete_space + pynini.cross("-", " to ") + delete_space + time - self.graph = time_graph | (approx + time) - - cardinal = cardinal.graph_with_and - # YEAR - date_year_four_digit = (NEMO_DIGIT ** 4 + pynini.closure(pynini.accep("s"), 0, 1)) @ date - date_year_two_digit = (NEMO_DIGIT ** 2 + pynini.closure(pynini.accep("s"), 0, 1)) @ date - year_to_year_graph = ( - date_year_four_digit - + delete_space - + pynini.cross("-", " to ") - + delete_space - + (date_year_four_digit | date_year_two_digit | (NEMO_DIGIT ** 2 @ cardinal)) - ) - mid_year_graph = pynini.accep("mid") + pynini.cross("-", " ") + (date_year_four_digit | date_year_two_digit) - - self.graph |= year_to_year_graph - self.graph |= mid_year_graph - - # ADDITION - range_graph = cardinal + pynini.closure(pynini.cross("+", " plus ") + cardinal, 1) - range_graph |= cardinal + pynini.closure(pynini.cross(" + ", " plus ") + cardinal, 1) - range_graph |= approx + cardinal - range_graph |= cardinal + (pynini.cross("...", " ... ") | pynini.accep(" ... ")) + cardinal - - if not deterministic or lm: - # cardinal ---- - cardinal_to_cardinal_graph = ( - cardinal + delete_space + pynini.cross("-", pynini.union(" to ", " minus ")) + delete_space + cardinal - ) - - range_graph |= cardinal_to_cardinal_graph | ( - cardinal + delete_space + pynini.cross(":", " to ") + delete_space + cardinal - ) - - # MULTIPLY - for x in [" x ", "x"]: - range_graph |= cardinal + pynini.closure( - pynini.cross(x, pynini.union(" by ", " times ")) + cardinal, 1 - ) - - for x in ["*", " * "]: - range_graph |= cardinal + pynini.closure(pynini.cross(x, " times ") + cardinal, 1) - - # supports "No. 12" -> "Number 12" - range_graph |= ( - (pynini.cross(pynini.union("NO", "No"), "Number") | pynini.cross("no", "number")) - + pynini.closure(pynini.union(". ", " "), 0, 1) - + cardinal - ) - - for x in ["/", " / "]: - range_graph |= cardinal + pynini.closure(pynini.cross(x, " divided by ") + cardinal, 1) - - self.graph |= range_graph - - self.graph = self.graph.optimize() - graph = pynutil.insert("name: \"") + convert_space(self.graph).optimize() + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/roman.py b/nemo_text_processing/text_normalization/en/taggers/roman.py deleted file mode 100644 index e12ee4a2b1ed..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/roman.py +++ /dev/null @@ -1,114 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_ALPHA, NEMO_SIGMA, GraphFst -from nemo_text_processing.text_normalization.en.utils import get_abs_path, load_labels -from pynini.lib import pynutil - - -class RomanFst(GraphFst): - """ - Finite state transducer for classifying roman numbers: - e.g. "IV" -> tokens { roman { integer: "four" } } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="roman", kind="classify", deterministic=deterministic) - - roman_dict = load_labels(get_abs_path("data/roman/roman_to_spoken.tsv")) - default_graph = pynini.string_map(roman_dict).optimize() - default_graph = pynutil.insert("integer: \"") + default_graph + pynutil.insert("\"") - ordinal_limit = 19 - - if deterministic: - # exclude "I" - start_idx = 1 - else: - start_idx = 0 - - graph_teens = pynini.string_map([x[0] for x in roman_dict[start_idx:ordinal_limit]]).optimize() - - # roman numerals up to ordinal_limit with a preceding name are converted to ordinal form - names = get_names() - graph = ( - pynutil.insert("key_the_ordinal: \"") - + names - + pynutil.insert("\"") - + pynini.accep(" ") - + graph_teens @ default_graph - ).optimize() - - # single symbol roman numerals with preceding key words (multiple formats) are converted to cardinal form - key_words = [] - for k_word in load_labels(get_abs_path("data/roman/key_word.tsv")): - key_words.append(k_word) - key_words.append([k_word[0][0].upper() + k_word[0][1:]]) - key_words.append([k_word[0].upper()]) - - key_words = pynini.string_map(key_words).optimize() - graph |= ( - pynutil.insert("key_cardinal: \"") + key_words + pynutil.insert("\"") + pynini.accep(" ") + default_graph - ).optimize() - - if deterministic or lm: - # two digit roman numerals up to 49 - roman_to_cardinal = pynini.compose( - pynini.closure(NEMO_ALPHA, 2), - ( - pynutil.insert("default_cardinal: \"default\" ") - + (pynini.string_map([x[0] for x in roman_dict[:50]]).optimize()) @ default_graph - ), - ) - graph |= roman_to_cardinal - elif not lm: - # two or more digit roman numerals - roman_to_cardinal = pynini.compose( - pynini.difference(NEMO_SIGMA, "I"), - ( - pynutil.insert("default_cardinal: \"default\" integer: \"") - + pynini.string_map(roman_dict).optimize() - + pynutil.insert("\"") - ), - ).optimize() - graph |= roman_to_cardinal - - # convert three digit roman or up with suffix to ordinal - roman_to_ordinal = pynini.compose( - pynini.closure(NEMO_ALPHA, 3), - (pynutil.insert("default_ordinal: \"default\" ") + graph_teens @ default_graph + pynutil.delete("th")), - ) - - graph |= roman_to_ordinal - graph = self.add_tokens(graph.optimize()) - - self.fst = graph.optimize() - - -def get_names(): - """ - Returns the graph that matched common male and female names. - """ - male_labels = load_labels(get_abs_path("data/roman/male.tsv")) - female_labels = load_labels(get_abs_path("data/roman/female.tsv")) - male_labels.extend([[x[0].upper()] for x in male_labels]) - female_labels.extend([[x[0].upper()] for x in female_labels]) - names = pynini.string_map(male_labels).optimize() - names |= pynini.string_map(female_labels).optimize() - return names diff --git a/nemo_text_processing/text_normalization/en/taggers/serial.py b/nemo_text_processing/text_normalization/en/taggers/serial.py deleted file mode 100644 index 669fd95a0569..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/serial.py +++ /dev/null @@ -1,136 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_NOT_SPACE, - NEMO_SIGMA, - GraphFst, - convert_space, -) -from nemo_text_processing.text_normalization.en.utils import get_abs_path, load_labels -from pynini.examples import plurals -from pynini.lib import pynutil - - -class SerialFst(GraphFst): - """ - This class is a composite class of two other class instances - - Args: - time: composed tagger and verbalizer - date: composed tagger and verbalizer - cardinal: tagger - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - lm: whether to use for hybrid LM - """ - - def __init__(self, cardinal: GraphFst, ordinal: GraphFst, deterministic: bool = True, lm: bool = False): - super().__init__(name="integer", kind="classify", deterministic=deterministic) - - """ - Finite state transducer for classifying serial (handles only cases without delimiters, - values with delimiters are handled by default). - The serial is a combination of digits, letters and dashes, e.g.: - c325b -> tokens { cardinal { integer: "c three two five b" } } - """ - num_graph = pynini.compose(NEMO_DIGIT ** (6, ...), cardinal.single_digits_graph).optimize() - num_graph |= pynini.compose(NEMO_DIGIT ** (1, 5), cardinal.graph).optimize() - # to handle numbers starting with zero - num_graph |= pynini.compose( - pynini.accep("0") + pynini.closure(NEMO_DIGIT), cardinal.single_digits_graph - ).optimize() - # TODO: "#" doesn't work from the file - symbols_graph = pynini.string_file(get_abs_path("data/whitelist/symbol.tsv")).optimize() | pynini.cross( - "#", "hash" - ) - num_graph |= symbols_graph - - if not self.deterministic and not lm: - num_graph |= cardinal.single_digits_graph - # also allow double digits to be pronounced as integer in serial number - num_graph |= pynutil.add_weight( - NEMO_DIGIT ** 2 @ cardinal.graph_hundred_component_at_least_one_none_zero_digit, weight=0.0001 - ) - - # add space between letter and digit/symbol - symbols = [x[0] for x in load_labels(get_abs_path("data/whitelist/symbol.tsv"))] - symbols = pynini.union(*symbols) - digit_symbol = NEMO_DIGIT | symbols - - graph_with_space = pynini.compose( - pynini.cdrewrite(pynutil.insert(" "), NEMO_ALPHA | symbols, digit_symbol, NEMO_SIGMA), - pynini.cdrewrite(pynutil.insert(" "), digit_symbol, NEMO_ALPHA | symbols, NEMO_SIGMA), - ) - - # serial graph with delimiter - delimiter = pynini.accep("-") | pynini.accep("/") | pynini.accep(" ") - if not deterministic: - delimiter |= pynini.cross("-", " dash ") | pynini.cross("/", " slash ") - - alphas = pynini.closure(NEMO_ALPHA, 1) - letter_num = alphas + delimiter + num_graph - num_letter = pynini.closure(num_graph + delimiter, 1) + alphas - next_alpha_or_num = pynini.closure(delimiter + (alphas | num_graph)) - next_alpha_or_num |= pynini.closure( - delimiter - + num_graph - + plurals._priority_union(pynini.accep(" "), pynutil.insert(" "), NEMO_SIGMA).optimize() - + alphas - ) - - serial_graph = letter_num + next_alpha_or_num - serial_graph |= num_letter + next_alpha_or_num - # numbers only with 2+ delimiters - serial_graph |= ( - num_graph + delimiter + num_graph + delimiter + num_graph + pynini.closure(delimiter + num_graph) - ) - # 2+ symbols - serial_graph |= pynini.compose(NEMO_SIGMA + symbols + NEMO_SIGMA, num_graph + delimiter + num_graph) - - # exclude ordinal numbers from serial options - serial_graph = pynini.compose( - pynini.difference(NEMO_SIGMA, pynini.project(ordinal.graph, "input")), serial_graph - ).optimize() - - serial_graph = pynutil.add_weight(serial_graph, 0.0001) - serial_graph |= ( - pynini.closure(NEMO_NOT_SPACE, 1) - + (pynini.cross("^2", " squared") | pynini.cross("^3", " cubed")).optimize() - ) - - # at least one serial graph with alpha numeric value and optional additional serial/num/alpha values - serial_graph = ( - pynini.closure((serial_graph | num_graph | alphas) + delimiter) - + serial_graph - + pynini.closure(delimiter + (serial_graph | num_graph | alphas)) - ) - - serial_graph |= pynini.compose(graph_with_space, serial_graph.optimize()).optimize() - serial_graph = pynini.compose(pynini.closure(NEMO_NOT_SPACE, 2), serial_graph).optimize() - - # this is not to verbolize "/" as "slash" in cases like "import/export" - serial_graph = pynini.compose( - pynini.difference( - NEMO_SIGMA, pynini.closure(NEMO_ALPHA, 1) + pynini.accep("/") + pynini.closure(NEMO_ALPHA, 1) - ), - serial_graph, - ) - self.graph = serial_graph.optimize() - graph = pynutil.insert("name: \"") + convert_space(self.graph).optimize() + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/telephone.py b/nemo_text_processing/text_normalization/en/taggers/telephone.py deleted file mode 100644 index 1caedffddde5..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/telephone.py +++ /dev/null @@ -1,133 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - delete_extra_space, - delete_space, - insert_space, - plurals, -) -from nemo_text_processing.text_normalization.en.utils import get_abs_path -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone, and IP, and SSN which includes country code, number part and extension - country code optional: +*** - number part: ***-***-****, or (***) ***-**** - extension optional: 1-9999 - E.g - +1 123-123-5678-1 -> telephone { country_code: "one" number_part: "one two three, one two three, five six seven eight" extension: "one" } - 1-800-GO-U-HAUL -> telephone { country_code: "one" number_part: "one, eight hundred GO U HAUL" } - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="telephone", kind="classify", deterministic=deterministic) - - add_separator = pynutil.insert(", ") # between components - zero = pynini.cross("0", "zero") - if not deterministic: - zero |= pynini.cross("0", pynini.union("o", "oh")) - digit = pynini.invert(pynini.string_file(get_abs_path("data/number/digit.tsv"))).optimize() | zero - - telephone_prompts = pynini.string_file(get_abs_path("data/telephone/telephone_prompt.tsv")) - country_code = ( - pynini.closure(telephone_prompts + delete_extra_space, 0, 1) - + pynini.closure(pynini.cross("+", "plus "), 0, 1) - + pynini.closure(digit + insert_space, 0, 2) - + digit - + pynutil.insert(",") - ) - country_code |= telephone_prompts - country_code = pynutil.insert("country_code: \"") + country_code + pynutil.insert("\"") - country_code = country_code + pynini.closure(pynutil.delete("-"), 0, 1) + delete_space + insert_space - - area_part_default = pynini.closure(digit + insert_space, 2, 2) + digit - area_part = pynini.cross("800", "eight hundred") | pynini.compose( - pynini.difference(NEMO_SIGMA, "800"), area_part_default - ) - - area_part = ( - (area_part + (pynutil.delete("-") | pynutil.delete("."))) - | ( - pynutil.delete("(") - + area_part - + ((pynutil.delete(")") + pynini.closure(pynutil.delete(" "), 0, 1)) | pynutil.delete(")-")) - ) - ) + add_separator - - del_separator = pynini.closure(pynini.union("-", " ", "."), 0, 1) - number_length = ((NEMO_DIGIT + del_separator) | (NEMO_ALPHA + del_separator)) ** 7 - number_words = pynini.closure( - (NEMO_DIGIT @ digit) + (insert_space | (pynini.cross("-", ', '))) - | NEMO_ALPHA - | (NEMO_ALPHA + pynini.cross("-", ' ')) - ) - number_words |= pynini.closure( - (NEMO_DIGIT @ digit) + (insert_space | (pynini.cross(".", ', '))) - | NEMO_ALPHA - | (NEMO_ALPHA + pynini.cross(".", ' ')) - ) - number_words = pynini.compose(number_length, number_words) - number_part = area_part + number_words - number_part = pynutil.insert("number_part: \"") + number_part + pynutil.insert("\"") - extension = ( - pynutil.insert("extension: \"") + pynini.closure(digit + insert_space, 0, 3) + digit + pynutil.insert("\"") - ) - extension = pynini.closure(insert_space + extension, 0, 1) - - graph = plurals._priority_union(country_code + number_part, number_part, NEMO_SIGMA).optimize() - graph = plurals._priority_union(country_code + number_part + extension, graph, NEMO_SIGMA).optimize() - graph = plurals._priority_union(number_part + extension, graph, NEMO_SIGMA).optimize() - - # ip - ip_prompts = pynini.string_file(get_abs_path("data/telephone/ip_prompt.tsv")) - digit_to_str_graph = digit + pynini.closure(pynutil.insert(" ") + digit, 0, 2) - ip_graph = digit_to_str_graph + (pynini.cross(".", " dot ") + digit_to_str_graph) ** 3 - graph |= ( - pynini.closure( - pynutil.insert("country_code: \"") + ip_prompts + pynutil.insert("\"") + delete_extra_space, 0, 1 - ) - + pynutil.insert("number_part: \"") - + ip_graph.optimize() - + pynutil.insert("\"") - ) - # ssn - ssn_prompts = pynini.string_file(get_abs_path("data/telephone/ssn_prompt.tsv")) - three_digit_part = digit + (pynutil.insert(" ") + digit) ** 2 - two_digit_part = digit + pynutil.insert(" ") + digit - four_digit_part = digit + (pynutil.insert(" ") + digit) ** 3 - ssn_separator = pynini.cross("-", ", ") - ssn_graph = three_digit_part + ssn_separator + two_digit_part + ssn_separator + four_digit_part - - graph |= ( - pynini.closure( - pynutil.insert("country_code: \"") + ssn_prompts + pynutil.insert("\"") + delete_extra_space, 0, 1 - ) - + pynutil.insert("number_part: \"") - + ssn_graph.optimize() - + pynutil.insert("\"") - ) - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/time.py b/nemo_text_processing/text_normalization/en/taggers/time.py deleted file mode 100644 index 4020996cc449..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/time.py +++ /dev/null @@ -1,132 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - GraphFst, - convert_space, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.en.utils import ( - augment_labels_with_punct_at_end, - get_abs_path, - load_labels, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time, e.g. - 12:30 a.m. est -> time { hours: "twelve" minutes: "thirty" suffix: "a m" zone: "e s t" } - 2.30 a.m. -> time { hours: "two" minutes: "thirty" suffix: "a m" } - 02.30 a.m. -> time { hours: "two" minutes: "thirty" suffix: "a m" } - 2.00 a.m. -> time { hours: "two" suffix: "a m" } - 2 a.m. -> time { hours: "two" suffix: "a m" } - 02:00 -> time { hours: "two" } - 2:00 -> time { hours: "two" } - 10:00:05 a.m. -> time { hours: "ten" minutes: "zero" seconds: "five" suffix: "a m" } - - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="time", kind="classify", deterministic=deterministic) - suffix_labels = load_labels(get_abs_path("data/time/suffix.tsv")) - suffix_labels.extend(augment_labels_with_punct_at_end(suffix_labels)) - suffix_graph = pynini.string_map(suffix_labels) - - time_zone_graph = pynini.string_file(get_abs_path("data/time/zone.tsv")) - - # only used for < 1000 thousand -> 0 weight - cardinal = cardinal.graph - - labels_hour = [str(x) for x in range(0, 24)] - labels_minute_single = [str(x) for x in range(1, 10)] - labels_minute_double = [str(x) for x in range(10, 60)] - - delete_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | ( - pynini.closure(pynutil.delete("0"), 0, 1) + NEMO_DIGIT - ) - - graph_hour = delete_leading_zero_to_double_digit @ pynini.union(*labels_hour) @ cardinal - - graph_minute_single = pynini.union(*labels_minute_single) @ cardinal - graph_minute_double = pynini.union(*labels_minute_double) @ cardinal - - final_graph_hour = pynutil.insert("hours: \"") + graph_hour + pynutil.insert("\"") - final_graph_minute = ( - pynutil.insert("minutes: \"") - + (pynini.cross("0", "o") + insert_space + graph_minute_single | graph_minute_double) - + pynutil.insert("\"") - ) - final_graph_second = ( - pynutil.insert("seconds: \"") - + (pynini.cross("0", "o") + insert_space + graph_minute_single | graph_minute_double) - + pynutil.insert("\"") - ) - final_suffix = pynutil.insert("suffix: \"") + convert_space(suffix_graph) + pynutil.insert("\"") - final_suffix_optional = pynini.closure(delete_space + insert_space + final_suffix, 0, 1) - final_time_zone_optional = pynini.closure( - delete_space - + insert_space - + pynutil.insert("zone: \"") - + convert_space(time_zone_graph) - + pynutil.insert("\""), - 0, - 1, - ) - - # 2:30 pm, 02:30, 2:00 - graph_hm = ( - final_graph_hour - + pynutil.delete(":") - + (pynutil.delete("00") | insert_space + final_graph_minute) - + final_suffix_optional - + final_time_zone_optional - ) - - # 10:30:05 pm, - graph_hms = ( - final_graph_hour - + pynutil.delete(":") - + (pynini.cross("00", " minutes: \"zero\"") | insert_space + final_graph_minute) - + pynutil.delete(":") - + (pynini.cross("00", " seconds: \"zero\"") | insert_space + final_graph_second) - + final_suffix_optional - + final_time_zone_optional - ) - - # 2.xx pm/am - graph_hm2 = ( - final_graph_hour - + pynutil.delete(".") - + (pynutil.delete("00") | insert_space + final_graph_minute) - + delete_space - + insert_space - + final_suffix - + final_time_zone_optional - ) - # 2 pm est - graph_h = final_graph_hour + delete_space + insert_space + final_suffix + final_time_zone_optional - final_graph = (graph_hm | graph_h | graph_hm2 | graph_hms).optimize() - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify.py b/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify.py deleted file mode 100644 index d37b39cfaacd..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,215 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os -import time - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_WHITE_SPACE, - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.taggers.abbreviation import AbbreviationFst -from nemo_text_processing.text_normalization.en.taggers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.en.taggers.date import DateFst -from nemo_text_processing.text_normalization.en.taggers.decimal import DecimalFst -from nemo_text_processing.text_normalization.en.taggers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.en.taggers.fraction import FractionFst -from nemo_text_processing.text_normalization.en.taggers.measure import MeasureFst -from nemo_text_processing.text_normalization.en.taggers.money import MoneyFst -from nemo_text_processing.text_normalization.en.taggers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.text_normalization.en.taggers.range import RangeFst as RangeFst -from nemo_text_processing.text_normalization.en.taggers.roman import RomanFst -from nemo_text_processing.text_normalization.en.taggers.serial import SerialFst -from nemo_text_processing.text_normalization.en.taggers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.en.taggers.time import TimeFst -from nemo_text_processing.text_normalization.en.taggers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.en.taggers.word import WordFst -from nemo_text_processing.text_normalization.en.verbalizers.date import DateFst as vDateFst -from nemo_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst as vOrdinalFst -from nemo_text_processing.text_normalization.en.verbalizers.time import TimeFst as vTimeFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence including punctuation. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - """ - - def __init__( - self, - input_case: str, - deterministic: bool = True, - cache_dir: str = None, - overwrite_cache: bool = False, - whitelist: str = None, - ): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - whitelist_file = os.path.basename(whitelist) if whitelist else "" - far_file = os.path.join( - cache_dir, f"en_tn_{deterministic}_deterministic_{input_case}_{whitelist_file}_tokenize.far" - ) - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f'ClassifyFst.fst was restored from {far_file}.') - else: - logging.info(f"Creating ClassifyFst grammars.") - - start_time = time.time() - cardinal = CardinalFst(deterministic=deterministic) - cardinal_graph = cardinal.fst - logging.debug(f"cardinal: {time.time() - start_time: .2f}s -- {cardinal_graph.num_states()} nodes") - - start_time = time.time() - ordinal = OrdinalFst(cardinal=cardinal, deterministic=deterministic) - ordinal_graph = ordinal.fst - logging.debug(f"ordinal: {time.time() - start_time: .2f}s -- {ordinal_graph.num_states()} nodes") - - start_time = time.time() - decimal = DecimalFst(cardinal=cardinal, deterministic=deterministic) - decimal_graph = decimal.fst - logging.debug(f"decimal: {time.time() - start_time: .2f}s -- {decimal_graph.num_states()} nodes") - - start_time = time.time() - fraction = FractionFst(deterministic=deterministic, cardinal=cardinal) - fraction_graph = fraction.fst - logging.debug(f"fraction: {time.time() - start_time: .2f}s -- {fraction_graph.num_states()} nodes") - - start_time = time.time() - measure = MeasureFst(cardinal=cardinal, decimal=decimal, fraction=fraction, deterministic=deterministic) - measure_graph = measure.fst - logging.debug(f"measure: {time.time() - start_time: .2f}s -- {measure_graph.num_states()} nodes") - - start_time = time.time() - date_graph = DateFst(cardinal=cardinal, deterministic=deterministic).fst - logging.debug(f"date: {time.time() - start_time: .2f}s -- {date_graph.num_states()} nodes") - - start_time = time.time() - time_graph = TimeFst(cardinal=cardinal, deterministic=deterministic).fst - logging.debug(f"time: {time.time() - start_time: .2f}s -- {time_graph.num_states()} nodes") - - start_time = time.time() - telephone_graph = TelephoneFst(deterministic=deterministic).fst - logging.debug(f"telephone: {time.time() - start_time: .2f}s -- {telephone_graph.num_states()} nodes") - - start_time = time.time() - electonic_graph = ElectronicFst(deterministic=deterministic).fst - logging.debug(f"electronic: {time.time() - start_time: .2f}s -- {electonic_graph.num_states()} nodes") - - start_time = time.time() - money_graph = MoneyFst(cardinal=cardinal, decimal=decimal, deterministic=deterministic).fst - logging.debug(f"money: {time.time() - start_time: .2f}s -- {money_graph.num_states()} nodes") - - start_time = time.time() - whitelist_graph = WhiteListFst( - input_case=input_case, deterministic=deterministic, input_file=whitelist - ).fst - logging.debug(f"whitelist: {time.time() - start_time: .2f}s -- {whitelist_graph.num_states()} nodes") - - start_time = time.time() - punctuation = PunctuationFst(deterministic=deterministic) - punct_graph = punctuation.fst - logging.debug(f"punct: {time.time() - start_time: .2f}s -- {punct_graph.num_states()} nodes") - - start_time = time.time() - word_graph = WordFst(punctuation=punctuation, deterministic=deterministic).fst - logging.debug(f"word: {time.time() - start_time: .2f}s -- {word_graph.num_states()} nodes") - - start_time = time.time() - serial_graph = SerialFst(cardinal=cardinal, ordinal=ordinal, deterministic=deterministic).fst - logging.debug(f"serial: {time.time() - start_time: .2f}s -- {serial_graph.num_states()} nodes") - - start_time = time.time() - v_time_graph = vTimeFst(deterministic=deterministic).fst - v_ordinal_graph = vOrdinalFst(deterministic=deterministic) - v_date_graph = vDateFst(ordinal=v_ordinal_graph, deterministic=deterministic).fst - time_final = pynini.compose(time_graph, v_time_graph) - date_final = pynini.compose(date_graph, v_date_graph) - range_graph = RangeFst( - time=time_final, date=date_final, cardinal=cardinal, deterministic=deterministic - ).fst - logging.debug(f"range: {time.time() - start_time: .2f}s -- {range_graph.num_states()} nodes") - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.1) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.1) - | pynutil.add_weight(measure_graph, 1.1) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electonic_graph, 1.1) - | pynutil.add_weight(fraction_graph, 1.1) - | pynutil.add_weight(range_graph, 1.1) - | pynutil.add_weight(serial_graph, 1.1001) # should be higher than the rest of the classes - ) - - roman_graph = RomanFst(deterministic=deterministic).fst - classify |= pynutil.add_weight(roman_graph, 1.1) - - if not deterministic: - abbreviation_graph = AbbreviationFst(deterministic=deterministic).fst - classify |= pynutil.add_weight(abbreviation_graph, 100) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=2.1) + pynutil.insert(" }") - punct = pynini.closure( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct), - 1, - ) - - classify |= pynutil.add_weight(word_graph, 100) - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure( - ( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct + pynutil.insert(" ")) - ) - + token_plus_punct - ) - - graph = delete_space + graph + delete_space - graph |= punct - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify_lm.py b/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify_lm.py deleted file mode 100644 index fa48c3784998..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify_lm.py +++ /dev/null @@ -1,228 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - NEMO_NOT_SPACE, - NEMO_SIGMA, - NEMO_WHITE_SPACE, - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.taggers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.en.taggers.date import DateFst -from nemo_text_processing.text_normalization.en.taggers.decimal import DecimalFst -from nemo_text_processing.text_normalization.en.taggers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.en.taggers.fraction import FractionFst -from nemo_text_processing.text_normalization.en.taggers.measure import MeasureFst -from nemo_text_processing.text_normalization.en.taggers.money import MoneyFst -from nemo_text_processing.text_normalization.en.taggers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.text_normalization.en.taggers.range import RangeFst as RangeFst -from nemo_text_processing.text_normalization.en.taggers.roman import RomanFst -from nemo_text_processing.text_normalization.en.taggers.serial import SerialFst -from nemo_text_processing.text_normalization.en.taggers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.en.taggers.time import TimeFst -from nemo_text_processing.text_normalization.en.taggers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.en.taggers.word import WordFst -from nemo_text_processing.text_normalization.en.verbalizers.cardinal import CardinalFst as vCardinal -from nemo_text_processing.text_normalization.en.verbalizers.date import DateFst as vDate -from nemo_text_processing.text_normalization.en.verbalizers.decimal import DecimalFst as vDecimal -from nemo_text_processing.text_normalization.en.verbalizers.electronic import ElectronicFst as vElectronic -from nemo_text_processing.text_normalization.en.verbalizers.fraction import FractionFst as vFraction -from nemo_text_processing.text_normalization.en.verbalizers.measure import MeasureFst as vMeasure -from nemo_text_processing.text_normalization.en.verbalizers.money import MoneyFst as vMoney -from nemo_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst as vOrdinal -from nemo_text_processing.text_normalization.en.verbalizers.roman import RomanFst as vRoman -from nemo_text_processing.text_normalization.en.verbalizers.telephone import TelephoneFst as vTelephone -from nemo_text_processing.text_normalization.en.verbalizers.time import TimeFst as vTime -from nemo_text_processing.text_normalization.en.verbalizers.word import WordFst as vWord -from pynini.examples import plurals -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence including punctuation. - For deployment, this grammar will be compiled and exported to OpenFst Finite State Archive (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - """ - - def __init__( - self, - input_case: str, - deterministic: bool = True, - cache_dir: str = None, - overwrite_cache: bool = True, - whitelist: str = None, - ): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != 'None': - os.makedirs(cache_dir, exist_ok=True) - whitelist_file = os.path.basename(whitelist) if whitelist else "" - far_file = os.path.join( - cache_dir, f"_{input_case}_en_tn_{deterministic}_deterministic{whitelist_file}_lm.far" - ) - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode='r')['tokenize_and_classify'] - no_digits = pynini.closure(pynini.difference(NEMO_CHAR, NEMO_DIGIT)) - self.fst_no_digits = pynini.compose(self.fst, no_digits).optimize() - logging.info(f'ClassifyFst.fst was restored from {far_file}.') - else: - logging.info(f'Creating ClassifyFst grammars. This might take some time...') - # TAGGERS - cardinal = CardinalFst(deterministic=True, lm=True) - cardinal_tagger = cardinal - cardinal_graph = cardinal.fst - - ordinal = OrdinalFst(cardinal=cardinal, deterministic=True) - ordinal_graph = ordinal.fst - - decimal = DecimalFst(cardinal=cardinal, deterministic=True) - decimal_graph = decimal.fst - fraction = FractionFst(deterministic=True, cardinal=cardinal) - fraction_graph = fraction.fst - - measure = MeasureFst(cardinal=cardinal, decimal=decimal, fraction=fraction, deterministic=True) - measure_graph = measure.fst - date = DateFst(cardinal=cardinal, deterministic=True, lm=True) - date_graph = date.fst - punctuation = PunctuationFst(deterministic=True) - punct_graph = punctuation.graph - word_graph = WordFst(punctuation=punctuation, deterministic=deterministic).graph - time_graph = TimeFst(cardinal=cardinal, deterministic=True).fst - telephone_graph = TelephoneFst(deterministic=True).fst - electronic_graph = ElectronicFst(deterministic=True).fst - money_graph = MoneyFst(cardinal=cardinal, decimal=decimal, deterministic=False).fst - whitelist = WhiteListFst(input_case=input_case, deterministic=False, input_file=whitelist) - whitelist_graph = whitelist.graph - serial_graph = SerialFst(cardinal=cardinal, ordinal=ordinal, deterministic=deterministic, lm=True).fst - - # VERBALIZERS - cardinal = vCardinal(deterministic=True) - v_cardinal_graph = cardinal.fst - decimal = vDecimal(cardinal=cardinal, deterministic=True) - v_decimal_graph = decimal.fst - ordinal = vOrdinal(deterministic=True) - v_ordinal_graph = ordinal.fst - fraction = vFraction(deterministic=True, lm=True) - v_fraction_graph = fraction.fst - v_telephone_graph = vTelephone(deterministic=True).fst - v_electronic_graph = vElectronic(deterministic=True).fst - measure = vMeasure(decimal=decimal, cardinal=cardinal, fraction=fraction, deterministic=False) - v_measure_graph = measure.fst - v_time_graph = vTime(deterministic=True).fst - v_date_graph = vDate(ordinal=ordinal, deterministic=deterministic, lm=True).fst - v_money_graph = vMoney(decimal=decimal, deterministic=deterministic).fst - v_roman_graph = vRoman(deterministic=deterministic).fst - v_word_graph = vWord(deterministic=deterministic).fst - - cardinal_or_date_final = plurals._priority_union(date_graph, cardinal_graph, NEMO_SIGMA) - cardinal_or_date_final = pynini.compose(cardinal_or_date_final, (v_cardinal_graph | v_date_graph)) - - time_final = pynini.compose(time_graph, v_time_graph) - ordinal_final = pynini.compose(ordinal_graph, v_ordinal_graph) - sem_w = 1 - word_w = 100 - punct_w = 2 - classify_and_verbalize = ( - pynutil.add_weight(time_final, sem_w) - | pynutil.add_weight(pynini.compose(decimal_graph, v_decimal_graph), sem_w) - | pynutil.add_weight(pynini.compose(measure_graph, v_measure_graph), sem_w) - | pynutil.add_weight(ordinal_final, sem_w) - | pynutil.add_weight(pynini.compose(telephone_graph, v_telephone_graph), sem_w) - | pynutil.add_weight(pynini.compose(electronic_graph, v_electronic_graph), sem_w) - | pynutil.add_weight(pynini.compose(fraction_graph, v_fraction_graph), sem_w) - | pynutil.add_weight(pynini.compose(money_graph, v_money_graph), sem_w) - | pynutil.add_weight(cardinal_or_date_final, sem_w) - | pynutil.add_weight(whitelist_graph, sem_w) - | pynutil.add_weight( - pynini.compose(serial_graph, v_word_graph), 1.1001 - ) # should be higher than the rest of the classes - ).optimize() - - roman_graph = RomanFst(deterministic=deterministic, lm=True).fst - # the weight matches the word_graph weight for "I" cases in long sentences with multiple semiotic tokens - classify_and_verbalize |= pynutil.add_weight(pynini.compose(roman_graph, v_roman_graph), sem_w) - - date_final = pynini.compose(date_graph, v_date_graph) - range_graph = RangeFst( - time=time_final, cardinal=cardinal_tagger, date=date_final, deterministic=deterministic - ).fst - classify_and_verbalize |= pynutil.add_weight(pynini.compose(range_graph, v_word_graph), sem_w) - classify_and_verbalize = pynutil.insert("< ") + classify_and_verbalize + pynutil.insert(" >") - classify_and_verbalize |= pynutil.add_weight(word_graph, word_w) - - punct_only = pynutil.add_weight(punct_graph, weight=punct_w) - punct = pynini.closure( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct_only), - 1, - ) - - def get_token_sem_graph(classify_and_verbalize): - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) - + classify_and_verbalize - + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure( - ( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct + pynutil.insert(" ")) - ) - + token_plus_punct - ) - - graph |= punct_only + pynini.closure(punct) - graph = delete_space + graph + delete_space - - remove_extra_spaces = pynini.closure(NEMO_NOT_SPACE, 1) + pynini.closure( - delete_extra_space + pynini.closure(NEMO_NOT_SPACE, 1) - ) - remove_extra_spaces |= ( - pynini.closure(pynutil.delete(" "), 1) - + pynini.closure(NEMO_NOT_SPACE, 1) - + pynini.closure(delete_extra_space + pynini.closure(NEMO_NOT_SPACE, 1)) - ) - - graph = pynini.compose(graph.optimize(), remove_extra_spaces).optimize() - return graph - - self.fst = get_token_sem_graph(classify_and_verbalize) - no_digits = pynini.closure(pynini.difference(NEMO_CHAR, NEMO_DIGIT)) - self.fst_no_digits = pynini.compose(self.fst, no_digits).optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f'ClassifyFst grammars are saved to {far_file}.') diff --git a/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify_with_audio.py b/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify_with_audio.py deleted file mode 100644 index d9adc4c907e7..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/tokenize_and_classify_with_audio.py +++ /dev/null @@ -1,229 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - NEMO_NOT_SPACE, - NEMO_WHITE_SPACE, - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.taggers.abbreviation import AbbreviationFst -from nemo_text_processing.text_normalization.en.taggers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.en.taggers.date import DateFst -from nemo_text_processing.text_normalization.en.taggers.decimal import DecimalFst -from nemo_text_processing.text_normalization.en.taggers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.en.taggers.fraction import FractionFst -from nemo_text_processing.text_normalization.en.taggers.measure import MeasureFst -from nemo_text_processing.text_normalization.en.taggers.money import MoneyFst -from nemo_text_processing.text_normalization.en.taggers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.text_normalization.en.taggers.range import RangeFst as RangeFst -from nemo_text_processing.text_normalization.en.taggers.roman import RomanFst -from nemo_text_processing.text_normalization.en.taggers.serial import SerialFst -from nemo_text_processing.text_normalization.en.taggers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.en.taggers.time import TimeFst -from nemo_text_processing.text_normalization.en.taggers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.en.taggers.word import WordFst -from nemo_text_processing.text_normalization.en.verbalizers.abbreviation import AbbreviationFst as vAbbreviation -from nemo_text_processing.text_normalization.en.verbalizers.cardinal import CardinalFst as vCardinal -from nemo_text_processing.text_normalization.en.verbalizers.date import DateFst as vDate -from nemo_text_processing.text_normalization.en.verbalizers.decimal import DecimalFst as vDecimal -from nemo_text_processing.text_normalization.en.verbalizers.electronic import ElectronicFst as vElectronic -from nemo_text_processing.text_normalization.en.verbalizers.fraction import FractionFst as vFraction -from nemo_text_processing.text_normalization.en.verbalizers.measure import MeasureFst as vMeasure -from nemo_text_processing.text_normalization.en.verbalizers.money import MoneyFst as vMoney -from nemo_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst as vOrdinal -from nemo_text_processing.text_normalization.en.verbalizers.roman import RomanFst as vRoman -from nemo_text_processing.text_normalization.en.verbalizers.telephone import TelephoneFst as vTelephone -from nemo_text_processing.text_normalization.en.verbalizers.time import TimeFst as vTime -from nemo_text_processing.text_normalization.en.verbalizers.word import WordFst as vWord -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence including punctuation. - For deployment, this grammar will be compiled and exported to OpenFst Finite State Archive (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - """ - - def __init__( - self, - input_case: str, - deterministic: bool = True, - cache_dir: str = None, - overwrite_cache: bool = True, - whitelist: str = None, - ): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != 'None': - os.makedirs(cache_dir, exist_ok=True) - whitelist_file = os.path.basename(whitelist) if whitelist else "" - far_file = os.path.join( - cache_dir, f"_{input_case}_en_tn_{deterministic}_deterministic{whitelist_file}.far" - ) - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode='r')['tokenize_and_classify'] - no_digits = pynini.closure(pynini.difference(NEMO_CHAR, NEMO_DIGIT)) - self.fst_no_digits = pynini.compose(self.fst, no_digits).optimize() - logging.info(f'ClassifyFst.fst was restored from {far_file}.') - else: - logging.info(f'Creating ClassifyFst grammars. This might take some time...') - # TAGGERS - cardinal = CardinalFst(deterministic=deterministic) - cardinal_graph = cardinal.fst - - ordinal = OrdinalFst(cardinal=cardinal, deterministic=deterministic) - deterministic_ordinal = OrdinalFst(cardinal=cardinal, deterministic=True) - ordinal_graph = ordinal.fst - - decimal = DecimalFst(cardinal=cardinal, deterministic=deterministic) - decimal_graph = decimal.fst - fraction = FractionFst(deterministic=deterministic, cardinal=cardinal) - fraction_graph = fraction.fst - - measure = MeasureFst(cardinal=cardinal, decimal=decimal, fraction=fraction, deterministic=deterministic) - measure_graph = measure.fst - date_graph = DateFst(cardinal=cardinal, deterministic=deterministic).fst - punctuation = PunctuationFst(deterministic=True) - punct_graph = punctuation.graph - word_graph = WordFst(punctuation=punctuation, deterministic=deterministic).graph - time_graph = TimeFst(cardinal=cardinal, deterministic=deterministic).fst - telephone_graph = TelephoneFst(deterministic=deterministic).fst - electronic_graph = ElectronicFst(deterministic=deterministic).fst - money_graph = MoneyFst(cardinal=cardinal, decimal=decimal, deterministic=deterministic).fst - whitelist = WhiteListFst(input_case=input_case, deterministic=deterministic, input_file=whitelist) - whitelist_graph = whitelist.graph - serial_graph = SerialFst(cardinal=cardinal, ordinal=deterministic_ordinal, deterministic=deterministic).fst - - # VERBALIZERS - cardinal = vCardinal(deterministic=deterministic) - v_cardinal_graph = cardinal.fst - decimal = vDecimal(cardinal=cardinal, deterministic=deterministic) - v_decimal_graph = decimal.fst - ordinal = vOrdinal(deterministic=deterministic) - v_ordinal_graph = ordinal.fst - fraction = vFraction(deterministic=deterministic) - v_fraction_graph = fraction.fst - v_telephone_graph = vTelephone(deterministic=deterministic).fst - v_electronic_graph = vElectronic(deterministic=deterministic).fst - measure = vMeasure(decimal=decimal, cardinal=cardinal, fraction=fraction, deterministic=deterministic) - v_measure_graph = measure.fst - v_time_graph = vTime(deterministic=deterministic).fst - v_date_graph = vDate(ordinal=ordinal, deterministic=deterministic).fst - v_money_graph = vMoney(decimal=decimal, deterministic=deterministic).fst - v_roman_graph = vRoman(deterministic=deterministic).fst - v_abbreviation = vAbbreviation(deterministic=deterministic).fst - - det_v_time_graph = vTime(deterministic=True).fst - det_v_date_graph = vDate(ordinal=vOrdinal(deterministic=True), deterministic=True).fst - time_final = pynini.compose(time_graph, det_v_time_graph) - date_final = pynini.compose(date_graph, det_v_date_graph) - range_graph = RangeFst( - time=time_final, date=date_final, cardinal=CardinalFst(deterministic=True), deterministic=deterministic - ).fst - v_word_graph = vWord(deterministic=deterministic).fst - - sem_w = 1 - word_w = 100 - punct_w = 2 - classify_and_verbalize = ( - pynutil.add_weight(whitelist_graph, sem_w) - | pynutil.add_weight(pynini.compose(time_graph, v_time_graph), sem_w) - | pynutil.add_weight(pynini.compose(decimal_graph, v_decimal_graph), sem_w) - | pynutil.add_weight(pynini.compose(measure_graph, v_measure_graph), sem_w) - | pynutil.add_weight(pynini.compose(cardinal_graph, v_cardinal_graph), sem_w) - | pynutil.add_weight(pynini.compose(ordinal_graph, v_ordinal_graph), sem_w) - | pynutil.add_weight(pynini.compose(telephone_graph, v_telephone_graph), sem_w) - | pynutil.add_weight(pynini.compose(electronic_graph, v_electronic_graph), sem_w) - | pynutil.add_weight(pynini.compose(fraction_graph, v_fraction_graph), sem_w) - | pynutil.add_weight(pynini.compose(money_graph, v_money_graph), sem_w) - | pynutil.add_weight(word_graph, word_w) - | pynutil.add_weight(pynini.compose(date_graph, v_date_graph), sem_w - 0.01) - | pynutil.add_weight(pynini.compose(range_graph, v_word_graph), sem_w) - | pynutil.add_weight( - pynini.compose(serial_graph, v_word_graph), 1.1001 - ) # should be higher than the rest of the classes - ).optimize() - - if not deterministic: - roman_graph = RomanFst(deterministic=deterministic).fst - # the weight matches the word_graph weight for "I" cases in long sentences with multiple semiotic tokens - classify_and_verbalize |= pynutil.add_weight(pynini.compose(roman_graph, v_roman_graph), word_w) - - abbreviation_graph = AbbreviationFst(whitelist=whitelist, deterministic=deterministic).fst - classify_and_verbalize |= pynutil.add_weight( - pynini.compose(abbreviation_graph, v_abbreviation), word_w - ) - - punct_only = pynutil.add_weight(punct_graph, weight=punct_w) - punct = pynini.closure( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct_only), - 1, - ) - - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) - + classify_and_verbalize - + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure( - ( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct + pynutil.insert(" ")) - ) - + token_plus_punct - ) - - graph |= punct_only + pynini.closure(punct) - graph = delete_space + graph + delete_space - - remove_extra_spaces = pynini.closure(NEMO_NOT_SPACE, 1) + pynini.closure( - delete_extra_space + pynini.closure(NEMO_NOT_SPACE, 1) - ) - remove_extra_spaces |= ( - pynini.closure(pynutil.delete(" "), 1) - + pynini.closure(NEMO_NOT_SPACE, 1) - + pynini.closure(delete_extra_space + pynini.closure(NEMO_NOT_SPACE, 1)) - ) - - graph = pynini.compose(graph.optimize(), remove_extra_spaces).optimize() - self.fst = graph - no_digits = pynini.closure(pynini.difference(NEMO_CHAR, NEMO_DIGIT)) - self.fst_no_digits = pynini.compose(graph, no_digits).optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f'ClassifyFst grammars are saved to {far_file}.') diff --git a/nemo_text_processing/text_normalization/en/taggers/whitelist.py b/nemo_text_processing/text_normalization/en/taggers/whitelist.py deleted file mode 100644 index 01d102da9a3c..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/whitelist.py +++ /dev/null @@ -1,150 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_NOT_SPACE, - NEMO_SIGMA, - NEMO_UPPER, - SINGULAR_TO_PLURAL, - GraphFst, - convert_space, -) -from nemo_text_processing.text_normalization.en.taggers.roman import get_names -from nemo_text_processing.text_normalization.en.utils import ( - augment_labels_with_punct_at_end, - get_abs_path, - load_labels, -) -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelist, e.g. - misses -> tokens { name: "mrs" } - for non-deterministic case: "Dr. Abc" -> - tokens { name: "drive" } tokens { name: "Abc" } - tokens { name: "doctor" } tokens { name: "Abc" } - tokens { name: "Dr." } tokens { name: "Abc" } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - input_file: path to a file with whitelist replacements - """ - - def __init__(self, input_case: str, deterministic: bool = True, input_file: str = None): - super().__init__(name="whitelist", kind="classify", deterministic=deterministic) - - def _get_whitelist_graph(input_case, file, keep_punct_add_end: bool = False): - whitelist = load_labels(file) - if input_case == "lower_cased": - whitelist = [[x.lower(), y] for x, y in whitelist] - else: - whitelist = [[x, y] for x, y in whitelist] - - if keep_punct_add_end: - whitelist.extend(augment_labels_with_punct_at_end(whitelist)) - - graph = pynini.string_map(whitelist) - return graph - - graph = _get_whitelist_graph(input_case, get_abs_path("data/whitelist/tts.tsv")) - graph |= pynini.compose( - pynini.difference(NEMO_SIGMA, pynini.accep("/")).optimize(), - _get_whitelist_graph(input_case, get_abs_path("data/whitelist/symbol.tsv")), - ).optimize() - - if deterministic: - names = get_names() - graph |= ( - pynini.cross(pynini.union("st", "St", "ST"), "Saint") - + pynini.closure(pynutil.delete(".")) - + pynini.accep(" ") - + names - ) - else: - graph |= _get_whitelist_graph( - input_case, get_abs_path("data/whitelist/alternatives.tsv"), keep_punct_add_end=True - ) - - for x in [".", ". "]: - graph |= ( - NEMO_UPPER - + pynini.closure(pynutil.delete(x) + NEMO_UPPER, 2) - + pynini.closure(pynutil.delete("."), 0, 1) - ) - - if not deterministic: - multiple_forms_whitelist_graph = get_formats(get_abs_path("data/whitelist/alternatives_all_format.tsv")) - graph |= multiple_forms_whitelist_graph - - graph_unit = pynini.string_file(get_abs_path("data/measure/unit.tsv")) | pynini.string_file( - get_abs_path("data/measure/unit_alternatives.tsv") - ) - graph_unit_plural = graph_unit @ SINGULAR_TO_PLURAL - units_graph = pynini.compose(NEMO_CHAR ** (3, ...), convert_space(graph_unit | graph_unit_plural)) - graph |= units_graph - - # convert to states only if comma is present before the abbreviation to avoid converting all caps words, - # e.g. "IN", "OH", "OK" - # TODO or only exclude above? - states = load_labels(get_abs_path("data/address/state.tsv")) - additional_options = [] - for x, y in states: - if input_case == "lower_cased": - x = x.lower() - additional_options.append((x, f"{y[0]}.{y[1:]}")) - if not deterministic: - additional_options.append((x, f"{y[0]}.{y[1:]}.")) - - states.extend(additional_options) - state_graph = pynini.string_map(states) - graph |= pynini.closure(NEMO_NOT_SPACE, 1) + pynini.union(", ", ",") + pynini.invert(state_graph).optimize() - - if input_file: - whitelist_provided = _get_whitelist_graph(input_case, input_file) - if not deterministic: - graph |= whitelist_provided - else: - graph = whitelist_provided - - self.graph = (convert_space(graph)).optimize() - - self.fst = (pynutil.insert("name: \"") + self.graph + pynutil.insert("\"")).optimize() - - -def get_formats(input_f, input_case="cased", is_default=True): - """ - Adds various abbreviation format options to the list of acceptable input forms - """ - multiple_formats = load_labels(input_f) - additional_options = [] - for x, y in multiple_formats: - if input_case == "lower_cased": - x = x.lower() - additional_options.append((f"{x}.", y)) # default "dr" -> doctor, this includes period "dr." -> doctor - additional_options.append((f"{x[0].upper() + x[1:]}", f"{y[0].upper() + y[1:]}")) # "Dr" -> Doctor - additional_options.append((f"{x[0].upper() + x[1:]}.", f"{y[0].upper() + y[1:]}")) # "Dr." -> Doctor - multiple_formats.extend(additional_options) - - if not is_default: - multiple_formats = [(x, f"|raw_start|{x}|raw_end||norm_start|{y}|norm_end|") for (x, y) in multiple_formats] - - multiple_formats = pynini.string_map(multiple_formats) - return multiple_formats diff --git a/nemo_text_processing/text_normalization/en/taggers/word.py b/nemo_text_processing/text_normalization/en/taggers/word.py deleted file mode 100644 index fa6a965aab2e..000000000000 --- a/nemo_text_processing/text_normalization/en/taggers/word.py +++ /dev/null @@ -1,90 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - MIN_NEG_WEIGHT, - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_NOT_SPACE, - NEMO_SIGMA, - GraphFst, - convert_space, - get_abs_path, -) -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from pynini.examples import plurals -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying word. Considers sentence boundary exceptions. - e.g. sleep -> tokens { name: "sleep" } - - Args: - punctuation: PunctuationFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, punctuation: GraphFst, deterministic: bool = True): - super().__init__(name="word", kind="classify", deterministic=deterministic) - - punct = PunctuationFst().graph - default_graph = pynini.closure(pynini.difference(NEMO_NOT_SPACE, punct.project("input")), 1) - symbols_to_exclude = (pynini.union("$", "€", "₩", "£", "¥", "#", "%") | NEMO_DIGIT).optimize() - graph = pynini.closure(pynini.difference(NEMO_NOT_SPACE, symbols_to_exclude), 1) - graph = pynutil.add_weight(graph, MIN_NEG_WEIGHT) | default_graph - - # leave phones of format [HH AH0 L OW1] untouched - phoneme_unit = pynini.closure(NEMO_ALPHA, 1) + pynini.closure(NEMO_DIGIT) - phoneme = ( - pynini.accep(pynini.escape("[")) - + pynini.closure(phoneme_unit + pynini.accep(" ")) - + phoneme_unit - + pynini.accep(pynini.escape("]")) - ) - - # leave IPA phones of format [ˈdoʊv] untouched, single words and sentences with punctuation marks allowed - punct_marks = pynini.union(*punctuation.punct_marks).optimize() - stress = pynini.union("ˈ", "'", "ˌ") - ipa_phoneme_unit = pynini.string_file(get_abs_path("data/whitelist/ipa_symbols.tsv")) - # word in ipa form - ipa_phonemes = ( - pynini.closure(stress, 0, 1) - + pynini.closure(ipa_phoneme_unit, 1) - + pynini.closure(stress | ipa_phoneme_unit) - ) - # allow sentences of words in IPA format separated with spaces or punct marks - delim = (punct_marks | pynini.accep(" ")) ** (1, ...) - ipa_phonemes = ipa_phonemes + pynini.closure(delim + ipa_phonemes) + pynini.closure(delim, 0, 1) - ipa_phonemes = (pynini.accep(pynini.escape("[")) + ipa_phonemes + pynini.accep(pynini.escape("]"))).optimize() - - if not deterministic: - phoneme = ( - pynini.accep(pynini.escape("[")) - + pynini.closure(pynini.accep(" "), 0, 1) - + pynini.closure(phoneme_unit + pynini.accep(" ")) - + phoneme_unit - + pynini.closure(pynini.accep(" "), 0, 1) - + pynini.accep(pynini.escape("]")) - ).optimize() - ipa_phonemes = ( - pynini.accep(pynini.escape("[")) + ipa_phonemes + pynini.accep(pynini.escape("]")) - ).optimize() - - phoneme |= ipa_phonemes - self.graph = plurals._priority_union(convert_space(phoneme.optimize()), graph, NEMO_SIGMA) - self.fst = (pynutil.insert("name: \"") + self.graph + pynutil.insert("\"")).optimize() diff --git a/nemo_text_processing/text_normalization/en/utils.py b/nemo_text_processing/text_normalization/en/utils.py deleted file mode 100644 index 31d9ec635a15..000000000000 --- a/nemo_text_processing/text_normalization/en/utils.py +++ /dev/null @@ -1,60 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import csv -import os - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + '/' + rel_path - - -def load_labels(abs_path): - """ - loads relative path file as dictionary - - Args: - abs_path: absolute path - - Returns dictionary of mappings - """ - with open(abs_path, encoding="utf-8") as label_tsv: - labels = list(csv.reader(label_tsv, delimiter="\t")) - return labels - - -def augment_labels_with_punct_at_end(labels): - """ - augments labels: if key ends on a punctuation that value does not have, add a new label - where the value maintains the punctuation - - Args: - labels : input labels - Returns: - additional labels - """ - res = [] - for label in labels: - if len(label) > 1: - if label[0][-1] == "." and label[1][-1] != ".": - res.append([label[0], label[1] + "."] + label[2:]) - return res diff --git a/nemo_text_processing/text_normalization/en/verbalizers/__init__.py b/nemo_text_processing/text_normalization/en/verbalizers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/en/verbalizers/abbreviation.py b/nemo_text_processing/text_normalization/en/verbalizers/abbreviation.py deleted file mode 100644 index 191792431c18..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/abbreviation.py +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class AbbreviationFst(GraphFst): - """ - Finite state transducer for verbalizing abbreviations - e.g. tokens { abbreviation { value: "A B C" } } -> "ABC" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="abbreviation", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete("value: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/cardinal.py b/nemo_text_processing/text_normalization/en/verbalizers/cardinal.py deleted file mode 100644 index 99531a0962d9..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/cardinal.py +++ /dev/null @@ -1,45 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinal, e.g. - cardinal { negative: "true" integer: "23" } -> minus twenty three - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="cardinal", kind="verbalize", deterministic=deterministic) - - self.optional_sign = pynini.cross("negative: \"true\"", "minus ") - if not deterministic: - self.optional_sign |= pynini.cross("negative: \"true\"", "negative ") - self.optional_sign = pynini.closure(self.optional_sign + delete_space, 0, 1) - - integer = pynini.closure(NEMO_NOT_QUOTE) - - self.integer = delete_space + pynutil.delete("\"") + integer + pynutil.delete("\"") - integer = pynutil.delete("integer:") + self.integer - - self.numbers = self.optional_sign + integer - delete_tokens = self.delete_tokens(self.numbers) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/date.py b/nemo_text_processing/text_normalization/en/verbalizers/date.py deleted file mode 100644 index 191d0106343d..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/date.py +++ /dev/null @@ -1,101 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_extra_space, - delete_space, -) -from pynini.examples import plurals -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { month: "february" day: "five" year: "twenty twelve" preserve_order: true } -> february fifth twenty twelve - date { day: "five" month: "february" year: "twenty twelve" preserve_order: true } -> the fifth of february twenty twelve - - Args: - ordinal: OrdinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, ordinal: GraphFst, deterministic: bool = True, lm: bool = False): - super().__init__(name="date", kind="verbalize", deterministic=deterministic) - - month = pynini.closure(NEMO_NOT_QUOTE, 1) - day_cardinal = ( - pynutil.delete("day:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - day = day_cardinal @ ordinal.suffix - - month = pynutil.delete("month:") + delete_space + pynutil.delete("\"") + month + pynutil.delete("\"") - - year = ( - pynutil.delete("year:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + delete_space - + pynutil.delete("\"") - ) - - # month (day) year - graph_mdy = ( - month + pynini.closure(delete_extra_space + day, 0, 1) + pynini.closure(delete_extra_space + year, 0, 1) - ) - # may 5 -> may five - if not deterministic and not lm: - graph_mdy |= ( - month - + pynini.closure(delete_extra_space + day_cardinal, 0, 1) - + pynini.closure(delete_extra_space + year, 0, 1) - ) - - # day month year - graph_dmy = ( - pynutil.insert("the ") - + day - + delete_extra_space - + pynutil.insert("of ") - + month - + pynini.closure(delete_extra_space + year, 0, 1) - ) - - optional_preserve_order = pynini.closure( - pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - | pynutil.delete("field_order:") - + delete_space - + pynutil.delete("\"") - + NEMO_NOT_QUOTE - + pynutil.delete("\"") - + delete_space - ) - - final_graph = ( - (plurals._priority_union(graph_mdy, pynutil.add_weight(graph_dmy, 0.0001), NEMO_SIGMA) | year) - + delete_space - + optional_preserve_order - ) - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/decimal.py b/nemo_text_processing/text_normalization/en/verbalizers/decimal.py deleted file mode 100644 index 787bcea63536..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/decimal.py +++ /dev/null @@ -1,67 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, e.g. - decimal { negative: "true" integer_part: "twelve" fractional_part: "five o o six" quantity: "billion" } -> minus twelve point five o o six billion - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal, deterministic: bool = True): - super().__init__(name="decimal", kind="verbalize", deterministic=deterministic) - self.optional_sign = pynini.cross("negative: \"true\"", "minus ") - if not deterministic: - self.optional_sign |= pynini.cross("negative: \"true\"", "negative ") - self.optional_sign = pynini.closure(self.optional_sign + delete_space, 0, 1) - self.integer = pynutil.delete("integer_part:") + cardinal.integer - self.optional_integer = pynini.closure(self.integer + delete_space + insert_space, 0, 1) - self.fractional_default = ( - pynutil.delete("fractional_part:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - self.fractional = pynutil.insert("point ") + self.fractional_default - - self.quantity = ( - delete_space - + insert_space - + pynutil.delete("quantity:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - self.optional_quantity = pynini.closure(self.quantity, 0, 1) - - graph = self.optional_sign + ( - self.integer - | (self.integer + self.quantity) - | (self.optional_integer + self.fractional + self.optional_quantity) - ) - - self.numbers = graph - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/electronic.py b/nemo_text_processing/text_normalization/en/verbalizers/electronic.py deleted file mode 100644 index 884f125b0913..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/electronic.py +++ /dev/null @@ -1,97 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_NOT_SPACE, - NEMO_SIGMA, - TO_UPPER, - GraphFst, - delete_extra_space, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.en.utils import get_abs_path -from pynini.examples import plurals -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. tokens { electronic { username: "cdf1" domain: "abc.edu" } } -> c d f one at a b c dot e d u - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="verbalize", deterministic=deterministic) - graph_digit_no_zero = pynini.invert(pynini.string_file(get_abs_path("data/number/digit.tsv"))).optimize() - graph_zero = pynini.cross("0", "zero") - - if not deterministic: - graph_zero |= pynini.cross("0", "o") | pynini.cross("0", "oh") - - graph_digit = graph_digit_no_zero | graph_zero - graph_symbols = pynini.string_file(get_abs_path("data/electronic/symbol.tsv")).optimize() - - default_chars_symbols = pynini.cdrewrite( - pynutil.insert(" ") + (graph_symbols | graph_digit) + pynutil.insert(" "), "", "", NEMO_SIGMA - ) - default_chars_symbols = pynini.compose( - pynini.closure(NEMO_NOT_SPACE), default_chars_symbols.optimize() - ).optimize() - - user_name = ( - pynutil.delete("username:") - + delete_space - + pynutil.delete("\"") - + default_chars_symbols - + pynutil.delete("\"") - ) - - domain_common = pynini.string_file(get_abs_path("data/electronic/domain.tsv")) - - domain = ( - default_chars_symbols - + insert_space - + plurals._priority_union( - domain_common, pynutil.add_weight(pynini.cross(".", "dot"), weight=0.0001), NEMO_SIGMA - ) - + pynini.closure( - insert_space + (pynini.cdrewrite(TO_UPPER, "", "", NEMO_SIGMA) @ default_chars_symbols), 0, 1 - ) - ) - domain = ( - pynutil.delete("domain:") - + delete_space - + pynutil.delete("\"") - + domain - + delete_space - + pynutil.delete("\"") - ).optimize() - - protocol = pynutil.delete("protocol: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - graph = ( - pynini.closure(protocol + delete_space, 0, 1) - + pynini.closure(user_name + delete_space + pynutil.insert(" at ") + delete_space, 0, 1) - + domain - + delete_space - ).optimize() @ pynini.cdrewrite(delete_extra_space, "", "", NEMO_SIGMA) - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/fraction.py b/nemo_text_processing/text_normalization/en/verbalizers/fraction.py deleted file mode 100644 index d0c5dc2b1648..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/fraction.py +++ /dev/null @@ -1,88 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, NEMO_SIGMA, GraphFst, insert_space -from nemo_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst -from pynini.examples import plurals -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for verbalizing fraction - e.g. tokens { fraction { integer: "twenty three" numerator: "four" denominator: "five" } } -> - twenty three and four fifth - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="fraction", kind="verbalize", deterministic=deterministic) - suffix = OrdinalFst().suffix - - integer = pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\" ") - denominator_one = pynini.cross("denominator: \"one\"", "over one") - denominator_half = pynini.cross("denominator: \"two\"", "half") - denominator_quarter = pynini.cross("denominator: \"four\"", "quarter") - - denominator_rest = ( - pynutil.delete("denominator: \"") + pynini.closure(NEMO_NOT_QUOTE) @ suffix + pynutil.delete("\"") - ) - - denominators = plurals._priority_union( - denominator_one, - plurals._priority_union( - denominator_half, - plurals._priority_union(denominator_quarter, denominator_rest, NEMO_SIGMA), - NEMO_SIGMA, - ), - NEMO_SIGMA, - ).optimize() - if not deterministic: - denominators |= pynutil.delete("denominator: \"") + (pynini.accep("four") @ suffix) + pynutil.delete("\"") - - numerator_one = pynutil.delete("numerator: \"") + pynini.accep("one") + pynutil.delete("\" ") - numerator_one = numerator_one + insert_space + denominators - numerator_rest = ( - pynutil.delete("numerator: \"") - + (pynini.closure(NEMO_NOT_QUOTE) - pynini.accep("one")) - + pynutil.delete("\" ") - ) - numerator_rest = numerator_rest + insert_space + denominators - numerator_rest @= pynini.cdrewrite( - plurals._priority_union(pynini.cross("half", "halves"), pynutil.insert("s"), NEMO_SIGMA), - "", - "[EOS]", - NEMO_SIGMA, - ) - - graph = numerator_one | numerator_rest - - conjunction = pynutil.insert("and ") - if not deterministic and not lm: - conjunction = pynini.closure(conjunction, 0, 1) - - integer = pynini.closure(integer + insert_space + conjunction, 0, 1) - - graph = integer + graph - graph @= pynini.cdrewrite( - pynini.cross("and one half", "and a half") | pynini.cross("over ones", "over one"), "", "[EOS]", NEMO_SIGMA - ) - - self.graph = graph - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/measure.py b/nemo_text_processing/text_normalization/en/verbalizers/measure.py deleted file mode 100644 index e4a23b3ff6f4..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/measure.py +++ /dev/null @@ -1,102 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { negative: "true" cardinal { integer: "twelve" } units: "kilograms" } -> minus twelve kilograms - measure { decimal { integer_part: "twelve" fractional_part: "five" } units: "kilograms" } -> twelve point five kilograms - tokens { measure { units: "covid" decimal { integer_part: "nineteen" fractional_part: "five" } } } -> covid nineteen point five - - Args: - decimal: DecimalFst - cardinal: CardinalFst - fraction: FractionFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst, fraction: GraphFst, deterministic: bool = True): - super().__init__(name="measure", kind="verbalize", deterministic=deterministic) - optional_sign = cardinal.optional_sign - unit = ( - pynutil.delete("units: \"") - + pynini.difference(pynini.closure(NEMO_NOT_QUOTE, 1), pynini.union("address", "math")) - + pynutil.delete("\"") - + delete_space - ) - - if not deterministic: - unit |= pynini.compose(unit, pynini.cross(pynini.union("inch", "inches"), "\"")) - - graph_decimal = ( - pynutil.delete("decimal {") - + delete_space - + optional_sign - + delete_space - + decimal.numbers - + delete_space - + pynutil.delete("}") - ) - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + delete_space - + cardinal.numbers - + delete_space - + pynutil.delete("}") - ) - - graph_fraction = ( - pynutil.delete("fraction {") + delete_space + fraction.graph + delete_space + pynutil.delete("}") - ) - - graph = (graph_cardinal | graph_decimal | graph_fraction) + delete_space + insert_space + unit - - # SH adds "preserve_order: true" by default - preserve_order = pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - graph |= unit + insert_space + (graph_cardinal | graph_decimal) + delete_space + pynini.closure(preserve_order) - # for only unit - graph |= ( - pynutil.delete("cardinal { integer: \"-\"") - + delete_space - + pynutil.delete("}") - + delete_space - + unit - + pynini.closure(preserve_order) - ) - address = ( - pynutil.delete("units: \"address\" ") - + delete_space - + graph_cardinal - + delete_space - + pynini.closure(preserve_order) - ) - math = ( - pynutil.delete("units: \"math\" ") - + delete_space - + graph_cardinal - + delete_space - + pynini.closure(preserve_order) - ) - graph |= address | math - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/money.py b/nemo_text_processing/text_normalization/en/verbalizers/money.py deleted file mode 100644 index b3cbc4a31494..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/money.py +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_extra_space, - delete_preserve_order, -) -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { integer_part: "twelve" fractional_part: "o five" currency: "dollars" } -> twelve o five dollars - - Args: - decimal: DecimalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="verbalize", deterministic=deterministic) - keep_space = pynini.accep(" ") - maj = pynutil.delete("currency_maj: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - min = pynutil.delete("currency_min: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - fractional_part = ( - pynutil.delete("fractional_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) - - integer_part = decimal.integer - - # *** currency_maj - graph_integer = integer_part + keep_space + maj - - # *** currency_maj + (***) | ((and) *** current_min) - fractional = fractional_part + delete_extra_space + min - - if not deterministic: - fractional |= pynutil.insert("and ") + fractional - - graph_integer_with_minor = integer_part + keep_space + maj + keep_space + fractional + delete_preserve_order - - # *** point *** currency_maj - graph_decimal = decimal.numbers + keep_space + maj - - # *** current_min - graph_minor = fractional_part + delete_extra_space + min + delete_preserve_order - - graph = graph_integer | graph_integer_with_minor | graph_decimal | graph_minor - - if not deterministic: - graph |= graph_integer + delete_preserve_order - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/ordinal.py b/nemo_text_processing/text_normalization/en/verbalizers/ordinal.py deleted file mode 100644 index c64579ae5b46..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/ordinal.py +++ /dev/null @@ -1,53 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, NEMO_SIGMA, GraphFst, delete_space -from nemo_text_processing.text_normalization.en.utils import get_abs_path -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinal, e.g. - ordinal { integer: "thirteen" } } -> thirteenth - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="ordinal", kind="verbalize", deterministic=deterministic) - - graph_digit = pynini.string_file(get_abs_path("data/ordinal/digit.tsv")).invert() - graph_teens = pynini.string_file(get_abs_path("data/ordinal/teen.tsv")).invert() - - graph = ( - pynutil.delete("integer:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - convert_rest = pynutil.insert("th") - - suffix = pynini.cdrewrite( - graph_digit | graph_teens | pynini.cross("ty", "tieth") | convert_rest, "", "[EOS]", NEMO_SIGMA, - ).optimize() - self.graph = pynini.compose(graph, suffix) - self.suffix = suffix - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/post_processing.py b/nemo_text_processing/text_normalization/en/verbalizers/post_processing.py deleted file mode 100644 index f3da3c97f2e3..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/post_processing.py +++ /dev/null @@ -1,182 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - MIN_NEG_WEIGHT, - NEMO_ALPHA, - NEMO_CHAR, - NEMO_SIGMA, - NEMO_SPACE, - generator_main, -) -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class PostProcessingFst: - """ - Finite state transducer that post-processing an entire sentence after verbalization is complete, e.g. - removes extra spaces around punctuation marks " ( one hundred and twenty three ) " -> "(one hundred and twenty three)" - - Args: - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, cache_dir: str = None, overwrite_cache: bool = False): - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, "en_tn_post_processing.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["post_process_graph"] - logging.info(f'Post processing graph was restored from {far_file}.') - else: - self.set_punct_dict() - self.fst = self.get_punct_postprocess_graph() - - if far_file: - generator_main(far_file, {"post_process_graph": self.fst}) - - def set_punct_dict(self): - self.punct_marks = { - "'": [ - "'", - '´', - 'ʹ', - 'ʻ', - 'ʼ', - 'ʽ', - 'ʾ', - 'ˈ', - 'ˊ', - 'ˋ', - '˴', - 'ʹ', - '΄', - '՚', - '՝', - 'י', - '׳', - 'ߴ', - 'ߵ', - 'ᑊ', - 'ᛌ', - '᾽', - '᾿', - '`', - '´', - '῾', - '‘', - '’', - '‛', - '′', - '‵', - 'ꞌ', - '＇', - '｀', - '𖽑', - '𖽒', - ], - } - - def get_punct_postprocess_graph(self): - """ - Returns graph to post process punctuation marks. - - {``} quotes are converted to {"}. Note, if there are spaces around single quote {'}, they will be kept. - By default, a space is added after a punctuation mark, and spaces are removed before punctuation marks. - """ - punct_marks_all = PunctuationFst().punct_marks - - # no_space_before_punct assume no space before them - quotes = ["'", "\"", "``", "«"] - dashes = ["-", "—"] - brackets = ["<", "{", "("] - open_close_single_quotes = [ - ("`", "`"), - ] - - open_close_double_quotes = [('"', '"'), ("``", "``"), ("“", "”")] - open_close_symbols = open_close_single_quotes + open_close_double_quotes - allow_space_before_punct = ["&"] + quotes + dashes + brackets + [k[0] for k in open_close_symbols] - - no_space_before_punct = [m for m in punct_marks_all if m not in allow_space_before_punct] - no_space_before_punct = pynini.union(*no_space_before_punct) - no_space_after_punct = pynini.union(*brackets) - delete_space = pynutil.delete(" ") - delete_space_optional = pynini.closure(delete_space, 0, 1) - - # non_punct allows space - # delete space before no_space_before_punct marks, if present - non_punct = pynini.difference(NEMO_CHAR, no_space_before_punct).optimize() - graph = ( - pynini.closure(non_punct) - + pynini.closure( - no_space_before_punct | pynutil.add_weight(delete_space + no_space_before_punct, MIN_NEG_WEIGHT) - ) - + pynini.closure(non_punct) - ) - graph = pynini.closure(graph).optimize() - graph = pynini.compose( - graph, pynini.cdrewrite(pynini.cross("``", '"'), "", "", NEMO_SIGMA).optimize() - ).optimize() - - # remove space after no_space_after_punct (even if there are no matching closing brackets) - no_space_after_punct = pynini.cdrewrite(delete_space, no_space_after_punct, NEMO_SIGMA, NEMO_SIGMA).optimize() - graph = pynini.compose(graph, no_space_after_punct).optimize() - - # remove space around text in quotes - single_quote = pynutil.add_weight(pynini.accep("`"), MIN_NEG_WEIGHT) - double_quotes = pynutil.add_weight(pynini.accep('"'), MIN_NEG_WEIGHT) - quotes_graph = ( - single_quote + delete_space_optional + NEMO_ALPHA + NEMO_SIGMA + delete_space_optional + single_quote - ).optimize() - - # this is to make sure multiple quotes are tagged from right to left without skipping any quotes in the left - not_alpha = pynini.difference(NEMO_CHAR, NEMO_ALPHA).optimize() | pynutil.add_weight( - NEMO_SPACE, MIN_NEG_WEIGHT - ) - end = pynini.closure(pynutil.add_weight(not_alpha, MIN_NEG_WEIGHT)) - quotes_graph |= ( - double_quotes - + delete_space_optional - + NEMO_ALPHA - + NEMO_SIGMA - + delete_space_optional - + double_quotes - + end - ) - - quotes_graph = pynutil.add_weight(quotes_graph, MIN_NEG_WEIGHT) - quotes_graph = NEMO_SIGMA + pynini.closure(NEMO_SIGMA + quotes_graph + NEMO_SIGMA) - - graph = pynini.compose(graph, quotes_graph).optimize() - - # remove space between a word and a single quote followed by s - remove_space_around_single_quote = pynini.cdrewrite( - delete_space_optional + pynini.union(*self.punct_marks["'"]) + delete_space, - NEMO_ALPHA, - pynini.union("s ", "s[EOS]"), - NEMO_SIGMA, - ) - - graph = pynini.compose(graph, remove_space_around_single_quote).optimize() - return graph diff --git a/nemo_text_processing/text_normalization/en/verbalizers/roman.py b/nemo_text_processing/text_normalization/en/verbalizers/roman.py deleted file mode 100644 index 43faebe769c1..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/roman.py +++ /dev/null @@ -1,68 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from nemo_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst -from pynini.lib import pynutil - - -class RomanFst(GraphFst): - """ - Finite state transducer for verbalizing roman numerals - e.g. tokens { roman { integer: "one" } } -> one - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="roman", kind="verbalize", deterministic=deterministic) - suffix = OrdinalFst().suffix - - cardinal = pynini.closure(NEMO_NOT_QUOTE) - ordinal = pynini.compose(cardinal, suffix) - - graph = ( - pynutil.delete("key_cardinal: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + pynini.accep(" ") - + pynutil.delete("integer: \"") - + cardinal - + pynutil.delete("\"") - ).optimize() - - graph |= ( - pynutil.delete("default_cardinal: \"default\" integer: \"") + cardinal + pynutil.delete("\"") - ).optimize() - - graph |= ( - pynutil.delete("default_ordinal: \"default\" integer: \"") + ordinal + pynutil.delete("\"") - ).optimize() - - graph |= ( - pynutil.delete("key_the_ordinal: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + pynini.accep(" ") - + pynutil.delete("integer: \"") - + pynini.closure(pynutil.insert("the "), 0, 1) - + ordinal - + pynutil.delete("\"") - ).optimize() - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/telephone.py b/nemo_text_processing/text_normalization/en/verbalizers/telephone.py deleted file mode 100644 index 4af7bbb8771a..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/telephone.py +++ /dev/null @@ -1,63 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone numbers, e.g. - telephone { country_code: "one" number_part: "one two three, one two three, five six seven eight" extension: "one" } - -> one, one two three, one two three, five six seven eight, one - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="telephone", kind="verbalize", deterministic=deterministic) - - optional_country_code = pynini.closure( - pynutil.delete("country_code: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + delete_space - + insert_space, - 0, - 1, - ) - - number_part = ( - pynutil.delete("number_part: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynini.closure(pynutil.add_weight(pynutil.delete(" "), -0.0001), 0, 1) - + pynutil.delete("\"") - ) - - optional_extension = pynini.closure( - delete_space - + insert_space - + pynutil.delete("extension: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\""), - 0, - 1, - ) - - graph = optional_country_code + number_part + optional_extension - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/time.py b/nemo_text_processing/text_normalization/en/verbalizers/time.py deleted file mode 100644 index 518c7dfa2186..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/time.py +++ /dev/null @@ -1,102 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_space, - insert_space, -) -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, e.g. - time { hours: "twelve" minutes: "thirty" suffix: "a m" zone: "e s t" } -> twelve thirty a m e s t - time { hours: "twelve" } -> twelve o'clock - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="time", kind="verbalize", deterministic=deterministic) - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - minute = ( - pynutil.delete("minutes:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - suffix = ( - pynutil.delete("suffix:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_suffix = pynini.closure(delete_space + insert_space + suffix, 0, 1) - zone = ( - pynutil.delete("zone:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_zone = pynini.closure(delete_space + insert_space + zone, 0, 1) - second = ( - pynutil.delete("seconds:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - graph_hms = ( - hour - + pynutil.insert(" hours ") - + delete_space - + minute - + pynutil.insert(" minutes and ") - + delete_space - + second - + pynutil.insert(" seconds") - + optional_suffix - + optional_zone - ) - graph_hms @= pynini.cdrewrite( - pynutil.delete("o ") - | pynini.cross("one minutes", "one minute") - | pynini.cross("one seconds", "one second") - | pynini.cross("one hours", "one hour"), - pynini.union(" ", "[BOS]"), - "", - NEMO_SIGMA, - ) - graph = hour + delete_space + insert_space + minute + optional_suffix + optional_zone - graph |= hour + insert_space + pynutil.insert("o'clock") + optional_zone - graph |= hour + delete_space + insert_space + suffix + optional_zone - graph |= graph_hms - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/verbalize.py b/nemo_text_processing/text_normalization/en/verbalizers/verbalize.py deleted file mode 100644 index cd3b1404aa05..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/verbalize.py +++ /dev/null @@ -1,82 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.en.verbalizers.abbreviation import AbbreviationFst -from nemo_text_processing.text_normalization.en.verbalizers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.en.verbalizers.date import DateFst -from nemo_text_processing.text_normalization.en.verbalizers.decimal import DecimalFst -from nemo_text_processing.text_normalization.en.verbalizers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.en.verbalizers.fraction import FractionFst -from nemo_text_processing.text_normalization.en.verbalizers.measure import MeasureFst -from nemo_text_processing.text_normalization.en.verbalizers.money import MoneyFst -from nemo_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.en.verbalizers.roman import RomanFst -from nemo_text_processing.text_normalization.en.verbalizers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.en.verbalizers.time import TimeFst -from nemo_text_processing.text_normalization.en.verbalizers.whitelist import WhiteListFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="verbalize", kind="verbalize", deterministic=deterministic) - cardinal = CardinalFst(deterministic=deterministic) - cardinal_graph = cardinal.fst - decimal = DecimalFst(cardinal=cardinal, deterministic=deterministic) - decimal_graph = decimal.fst - ordinal = OrdinalFst(deterministic=deterministic) - ordinal_graph = ordinal.fst - fraction = FractionFst(deterministic=deterministic) - fraction_graph = fraction.fst - telephone_graph = TelephoneFst(deterministic=deterministic).fst - electronic_graph = ElectronicFst(deterministic=deterministic).fst - measure = MeasureFst(decimal=decimal, cardinal=cardinal, fraction=fraction, deterministic=deterministic) - measure_graph = measure.fst - time_graph = TimeFst(deterministic=deterministic).fst - date_graph = DateFst(ordinal=ordinal, deterministic=deterministic).fst - money_graph = MoneyFst(decimal=decimal, deterministic=deterministic).fst - whitelist_graph = WhiteListFst(deterministic=deterministic).fst - - graph = ( - time_graph - | date_graph - | money_graph - | measure_graph - | ordinal_graph - | decimal_graph - | cardinal_graph - | telephone_graph - | electronic_graph - | fraction_graph - | whitelist_graph - ) - - roman_graph = RomanFst(deterministic=deterministic).fst - graph |= roman_graph - - if not deterministic: - abbreviation_graph = AbbreviationFst(deterministic=deterministic).fst - graph |= abbreviation_graph - - self.fst = graph diff --git a/nemo_text_processing/text_normalization/en/verbalizers/verbalize_final.py b/nemo_text_processing/text_normalization/en/verbalizers/verbalize_final.py deleted file mode 100644 index cbb61156ba47..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/verbalize_final.py +++ /dev/null @@ -1,76 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.verbalizers.verbalize import VerbalizeFst -from nemo_text_processing.text_normalization.en.verbalizers.word import WordFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "twelve" minutes: "thirty" } } tokens { name: "now" } tokens { name: "." } -> its twelve thirty now . - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, deterministic: bool = True, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="verbalize_final", kind="verbalize", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, f"en_tn_{deterministic}_deterministic_verbalizer.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["verbalize"] - logging.info(f'VerbalizeFinalFst graph was restored from {far_file}.') - else: - verbalize = VerbalizeFst(deterministic=deterministic).fst - word = WordFst(deterministic=deterministic).fst - types = verbalize | word - - if deterministic: - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - else: - graph = delete_space + types + delete_space - - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - - self.fst = graph.optimize() - if far_file: - generator_main(far_file, {"verbalize": self.fst}) - logging.info(f"VerbalizeFinalFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/en/verbalizers/whitelist.py b/nemo_text_processing/text_normalization/en/verbalizers/whitelist.py deleted file mode 100644 index 96aa2075b2e1..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/whitelist.py +++ /dev/null @@ -1,39 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for verbalizing whitelist - e.g. tokens { name: "misses" } } -> misses - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="whitelist", kind="verbalize", deterministic=deterministic) - graph = ( - pynutil.delete("name:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_CHAR - " ", 1) - + pynutil.delete("\"") - ) - graph = graph @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/en/verbalizers/word.py b/nemo_text_processing/text_normalization/en/verbalizers/word.py deleted file mode 100644 index e124f42ff16e..000000000000 --- a/nemo_text_processing/text_normalization/en/verbalizers/word.py +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, NEMO_SIGMA, GraphFst, delete_space -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for verbalizing word - e.g. tokens { name: "sleep" } -> sleep - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="word", kind="verbalize", deterministic=deterministic) - chars = pynini.closure(NEMO_CHAR - " ", 1) - char = pynutil.delete("name:") + delete_space + pynutil.delete("\"") + chars + pynutil.delete("\"") - graph = char @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/README.md b/nemo_text_processing/text_normalization/es/README.md deleted file mode 100644 index ec946a614da8..000000000000 --- a/nemo_text_processing/text_normalization/es/README.md +++ /dev/null @@ -1,22 +0,0 @@ -# Localization Note - -Depending on locale, Spanish number strings will vary in formatting. In the EU and South American countries, it is common to use a period (".") or space to delineate groupings of three -digits. e.g. - `1.000.000` -> "un millón" - `1 000 000` -> "un millón" - -and commas (",") to seperate cardinal and decimal strings. e.g. - - `1,00` -> "uno coma cero cero" - -While Central and Northern America will use commas (",") to delineate groupings of three digits, e.g. - `1,000,000` -> "un millón" - -and periods (".") to seperate cardinal and decimal strings. e.g. - - `1.00` -> "uno coma cero cero" - -As inclusion of both forms will create inherrent ambiguity for verbalization, this module defaults to the former formatting (periods for cardinal delineation and commas for decimals). - -To toggle the alternate formatting, you may edit the `LOCALIZATION` variable in `nemo_text_processing.text_normalization.es.__init__` with the value of `'am'`. This will perform necessary -adjustments to all affected classes. \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/__init__.py b/nemo_text_processing/text_normalization/es/data/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/dates/__init__.py b/nemo_text_processing/text_normalization/es/data/dates/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/dates/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/dates/months.tsv b/nemo_text_processing/text_normalization/es/data/dates/months.tsv deleted file mode 100644 index 7cfdf329aa5b..000000000000 --- a/nemo_text_processing/text_normalization/es/data/dates/months.tsv +++ /dev/null @@ -1,12 +0,0 @@ -1 enero -2 febrero -3 marzo -4 abril -5 mayo -6 junio -7 julio -8 agosto -9 septiembre -10 octubre -11 noviembre -12 diciembre \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/electronic/__init__.py b/nemo_text_processing/text_normalization/es/data/electronic/__init__.py deleted file mode 100644 index 2db92b257416..000000000000 --- a/nemo_text_processing/text_normalization/es/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/electronic/domain.tsv b/nemo_text_processing/text_normalization/es/data/electronic/domain.tsv deleted file mode 100644 index 9d71632ea9ce..000000000000 --- a/nemo_text_processing/text_normalization/es/data/electronic/domain.tsv +++ /dev/null @@ -1,14 +0,0 @@ -.com punto com -.org punto org -.gov punto gov -.uk punto uk -.fr punto fr -.net punto net -.br punto br -.in punto in -.ru punto ru -.de punto de -.it punto it -.es punto es -.mx punto mx -.us punto us \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/electronic/server_name.tsv b/nemo_text_processing/text_normalization/es/data/electronic/server_name.tsv deleted file mode 100644 index 9a0c75629486..000000000000 --- a/nemo_text_processing/text_normalization/es/data/electronic/server_name.tsv +++ /dev/null @@ -1,11 +0,0 @@ -gmail -nvidia -outlook -hotmail -yahoo -live -yandex -orange -wanadoo -web -comcast \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/electronic/symbols.tsv b/nemo_text_processing/text_normalization/es/data/electronic/symbols.tsv deleted file mode 100644 index c7790c3014c6..000000000000 --- a/nemo_text_processing/text_normalization/es/data/electronic/symbols.tsv +++ /dev/null @@ -1,22 +0,0 @@ -. punto -- guión -_ barra baja -! signo de exclamación -# almohadilla -$ signo de dólar -% signo de porcentaje -& et -' comilla -* asterisco -+ signo más -/ barra -= signo igual -? signo de interrogación -^ acento circunflej -` acento grave -{ llave izquierda -| pleca -} llave derecha -~ tilde -, coma -: dos puntos \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/fractions/__init__.py b/nemo_text_processing/text_normalization/es/data/fractions/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/fractions/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/fractions/ordinal_exceptions.tsv b/nemo_text_processing/text_normalization/es/data/fractions/ordinal_exceptions.tsv deleted file mode 100644 index 32cc3930a0e6..000000000000 --- a/nemo_text_processing/text_normalization/es/data/fractions/ordinal_exceptions.tsv +++ /dev/null @@ -1,2 +0,0 @@ -segundo medio -tercero tercio \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/fractions/powers_of_ten.tsv b/nemo_text_processing/text_normalization/es/data/fractions/powers_of_ten.tsv deleted file mode 100644 index 021dc0a101e0..000000000000 --- a/nemo_text_processing/text_normalization/es/data/fractions/powers_of_ten.tsv +++ /dev/null @@ -1,9 +0,0 @@ -millón millonésimo -millones millonésimo -billón billonésimo -billones billonésimo -trillón trillonésimo -trillones trillonésimo -mil millones mil millonésimo -mil billones mil billonésimo -mil trillones mil trillonésimo \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/fractions/powers_of_ten_fem.tsv b/nemo_text_processing/text_normalization/es/data/fractions/powers_of_ten_fem.tsv deleted file mode 100644 index 9e1a4ca4ce9f..000000000000 --- a/nemo_text_processing/text_normalization/es/data/fractions/powers_of_ten_fem.tsv +++ /dev/null @@ -1,6 +0,0 @@ -décimo décima -centésimo centésima -milésimo milésima -millonésimo millonésima -billonésimo billonésima -trillonésimo trillonésima \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/measures/__init__.py b/nemo_text_processing/text_normalization/es/data/measures/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/measures/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/measures/measurements.tsv b/nemo_text_processing/text_normalization/es/data/measures/measurements.tsv deleted file mode 100644 index 13b00f4ca227..000000000000 --- a/nemo_text_processing/text_normalization/es/data/measures/measurements.tsv +++ /dev/null @@ -1,17 +0,0 @@ -cm centímetro -g gramo -h hora -kg kilogramo -km kilómetro -km² kilómetro cuadrado -l litro -m metro -m² metro cuadrado -m³ metro cubico -mph milla por hora -ml mililitro -mm milímetro -ms milisegundo -min minuto -% por ciento -s segundo \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/measures/measurements_plural_fem.tsv b/nemo_text_processing/text_normalization/es/data/measures/measurements_plural_fem.tsv deleted file mode 100644 index e8158d7e9f8c..000000000000 --- a/nemo_text_processing/text_normalization/es/data/measures/measurements_plural_fem.tsv +++ /dev/null @@ -1,3 +0,0 @@ -hora horas -milla por hora millas por hora -milla millas \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/measures/measurements_plural_masc.tsv b/nemo_text_processing/text_normalization/es/data/measures/measurements_plural_masc.tsv deleted file mode 100644 index 8376ad2e5acb..000000000000 --- a/nemo_text_processing/text_normalization/es/data/measures/measurements_plural_masc.tsv +++ /dev/null @@ -1,15 +0,0 @@ -centímetro centímetros -gramo gramos -kilogramo kilogramos -kilómetro kilómetros -kilómetro cuadrado kilómetros cuadrados -litro litros -metro metros -metro cuadrado metros cuadrados -metro cubico metros cubicos -mililitro mililitros -milímetro milímetros -milisegundo milisegundos -minuto minutos -segundo segundos -por ciento por ciento \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/money/__init__.py b/nemo_text_processing/text_normalization/es/data/money/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/money/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/money/currency_major.tsv b/nemo_text_processing/text_normalization/es/data/money/currency_major.tsv deleted file mode 100644 index 5950aab5ed91..000000000000 --- a/nemo_text_processing/text_normalization/es/data/money/currency_major.tsv +++ /dev/null @@ -1,29 +0,0 @@ -€ euro -$ dólar -£ libra -₩ won -nzd dólar de Nueva Zelanda -rs rupia -chf franco suizo -fr franco -dkk corona danesa -kr corona -fim marco finlandes -mk marco -aed dírham -dh dírham -dhs dírham -¥ yen -czk corona checa -kč corona checa -crc colón costarricense -₡ colón -hkd dólar de Hong Kong -awg florín -nok corona noruega -sek corona sueca -R$ real -BRL real -ESP peseta -₧ peseta -Ptas peseta \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/money/currency_minor.tsv b/nemo_text_processing/text_normalization/es/data/money/currency_minor.tsv deleted file mode 100644 index 2d559e1f9125..000000000000 --- a/nemo_text_processing/text_normalization/es/data/money/currency_minor.tsv +++ /dev/null @@ -1,4 +0,0 @@ -$ centavo -€ céntimo -£ penique -¥ centavo \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/money/currency_plural_fem.tsv b/nemo_text_processing/text_normalization/es/data/money/currency_plural_fem.tsv deleted file mode 100644 index c412456e03eb..000000000000 --- a/nemo_text_processing/text_normalization/es/data/money/currency_plural_fem.tsv +++ /dev/null @@ -1,8 +0,0 @@ -rupia rupias -libra libras -corona danesa coronas danesas -corona coronas -corona checa coronas checas -corona noruega coronas noruegas -corona sueca coronas suecas -peseta pesetas \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/money/currency_plural_masc.tsv b/nemo_text_processing/text_normalization/es/data/money/currency_plural_masc.tsv deleted file mode 100644 index 08c25eeab1b2..000000000000 --- a/nemo_text_processing/text_normalization/es/data/money/currency_plural_masc.tsv +++ /dev/null @@ -1,19 +0,0 @@ -euro euros -dólar dólares -dólar estadounidense dólares estadounidenses -won wones -dólar de Nueva Zelanda dólares de Nueva Zelanda -franco suizo francos suizos -franco francos -marco finlandes marcos finlandeses -marco marcos -dírham dírhams -dírham dírhams -dírham dírhams -yen yenes -colón costarricense colónes costarricenses -colón colónes -dólar de Hong Kong dólares de Hong Kong -centavo centavos -céntimo céntimos -penique peniques \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/numbers/__init__.py b/nemo_text_processing/text_normalization/es/data/numbers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/numbers/digit.tsv b/nemo_text_processing/text_normalization/es/data/numbers/digit.tsv deleted file mode 100644 index 462803637ed5..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/digit.tsv +++ /dev/null @@ -1,9 +0,0 @@ -un 1 -dos 2 -tres 3 -cuatro 4 -cinco 5 -seis 6 -siete 7 -ocho 8 -nueve 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/numbers/hundreds.tsv b/nemo_text_processing/text_normalization/es/data/numbers/hundreds.tsv deleted file mode 100644 index bf651cd0a978..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/hundreds.tsv +++ /dev/null @@ -1,8 +0,0 @@ -doscientos 2 -trescientos 3 -cuatrocientos 4 -quinientos 5 -seiscientos 6 -setecientos 7 -ochocientos 8 -novecientos 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/numbers/quantities.tsv b/nemo_text_processing/text_normalization/es/data/numbers/quantities.tsv deleted file mode 100644 index 58bce3e5dcff..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/quantities.tsv +++ /dev/null @@ -1,6 +0,0 @@ -millón -millones -billón -billones -trillón -trillones \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/numbers/teen.tsv b/nemo_text_processing/text_normalization/es/data/numbers/teen.tsv deleted file mode 100644 index 370526ea57c3..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/teen.tsv +++ /dev/null @@ -1,10 +0,0 @@ -diez 10 -once 11 -doce 12 -trece 13 -catorce 14 -quince 15 -dieciséis 16 -diecisiete 17 -dieciocho 18 -diecinueve 19 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/numbers/ties.tsv b/nemo_text_processing/text_normalization/es/data/numbers/ties.tsv deleted file mode 100644 index 51b21081b3e3..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/ties.tsv +++ /dev/null @@ -1,7 +0,0 @@ -treinta 3 -cuarenta 4 -cincuenta 5 -sesenta 6 -setenta 7 -ochenta 8 -noventa 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/numbers/twenties.tsv b/nemo_text_processing/text_normalization/es/data/numbers/twenties.tsv deleted file mode 100644 index c378a3ad9817..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/twenties.tsv +++ /dev/null @@ -1,10 +0,0 @@ -veinte 20 -veintiún 21 -veintidós 22 -veintitrés 23 -veinticuatro 24 -veinticinco 25 -veintiséis 26 -veintisiete 27 -veintiocho 28 -veintinueve 29 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/numbers/zero.tsv b/nemo_text_processing/text_normalization/es/data/numbers/zero.tsv deleted file mode 100644 index 945785283a51..000000000000 --- a/nemo_text_processing/text_normalization/es/data/numbers/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -cero 0 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/ordinals/__init__.py b/nemo_text_processing/text_normalization/es/data/ordinals/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/ordinals/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/ordinals/digit.tsv b/nemo_text_processing/text_normalization/es/data/ordinals/digit.tsv deleted file mode 100644 index 08d86ac928b4..000000000000 --- a/nemo_text_processing/text_normalization/es/data/ordinals/digit.tsv +++ /dev/null @@ -1,11 +0,0 @@ -primero uno -primera una -primero un -segundo dos -tercero tres -cuarto cuatro -quinto cinco -sexto seis -séptimo siete -octavo ocho -noveno nueve \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/ordinals/hundreds.tsv b/nemo_text_processing/text_normalization/es/data/ordinals/hundreds.tsv deleted file mode 100644 index 65867fd84eca..000000000000 --- a/nemo_text_processing/text_normalization/es/data/ordinals/hundreds.tsv +++ /dev/null @@ -1,18 +0,0 @@ -centésimo ciento -centésimo cien -ducentésimo doscientos -ducentésima doscientas -tricentésimo trescientos -tricentésima trescientas -cuadringentésimo cuatrocientos -cuadringentésima cuatrocientas -quingentésimo quinientos -quingentésima quinientas -sexcentésimo seiscientos -sexcentésima seiscientas -septingentésimo setecientos -septingentésima setecientas -octingentésimo ochocientos -octingentésima ochocientas -noningentésimo novecientos -noningentésima novecientas \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/ordinals/teen.tsv b/nemo_text_processing/text_normalization/es/data/ordinals/teen.tsv deleted file mode 100644 index 1ffcfb2697d4..000000000000 --- a/nemo_text_processing/text_normalization/es/data/ordinals/teen.tsv +++ /dev/null @@ -1,10 +0,0 @@ -décimo diez -undécimo once -duodécimo doce -decimotercero trece -decimocuarto catorce -decimoquinto quince -decimosexto dieciséis -decimoséptimo diecisiete -decimooctavo dieciocho -decimonoveno diecinueve \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/ordinals/ties.tsv b/nemo_text_processing/text_normalization/es/data/ordinals/ties.tsv deleted file mode 100644 index 21c488ef2ab8..000000000000 --- a/nemo_text_processing/text_normalization/es/data/ordinals/ties.tsv +++ /dev/null @@ -1,8 +0,0 @@ -vigésimo veinte -trigésimo treinta -cuadragésimo cuarenta -quincuagésimo cincuenta -sexagésimo sesenta -septuagésimo setenta -octogésimo ochenta -nonagésimo noventa \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/ordinals/twenties.tsv b/nemo_text_processing/text_normalization/es/data/ordinals/twenties.tsv deleted file mode 100644 index e63a3e5825a3..000000000000 --- a/nemo_text_processing/text_normalization/es/data/ordinals/twenties.tsv +++ /dev/null @@ -1,11 +0,0 @@ -vigesimoprimero veintiuno -vigesimoprimera veintiuna -vigesimoprimero veintiún -vigesimosegundo veintidós -vigesimotercero veintitrés -vigesimocuarto veinticuatro -vigesimoquinto veinticinco -vigesimosexto veintiséis -vigesimoséptimo veintisiete -vigesimooctavo veintiocho -vigesimonoveno veintinueve \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/roman/__init__.py b/nemo_text_processing/text_normalization/es/data/roman/__init__.py deleted file mode 100644 index 2db92b257416..000000000000 --- a/nemo_text_processing/text_normalization/es/data/roman/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/roman/digit.tsv b/nemo_text_processing/text_normalization/es/data/roman/digit.tsv deleted file mode 100644 index 0610b4a54ff3..000000000000 --- a/nemo_text_processing/text_normalization/es/data/roman/digit.tsv +++ /dev/null @@ -1,9 +0,0 @@ -i 1 -ii 2 -iii 3 -iv 4 -v 5 -vi 6 -vii 7 -viii 8 -ix 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/roman/hundreds.tsv b/nemo_text_processing/text_normalization/es/data/roman/hundreds.tsv deleted file mode 100644 index cdbdb6814726..000000000000 --- a/nemo_text_processing/text_normalization/es/data/roman/hundreds.tsv +++ /dev/null @@ -1,9 +0,0 @@ -c 1 -cc 2 -ccc 3 -cd 4 -d 5 -dc 6 -dcc 7 -dccc 8 -cm 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/roman/ties.tsv b/nemo_text_processing/text_normalization/es/data/roman/ties.tsv deleted file mode 100644 index ac043aa146bf..000000000000 --- a/nemo_text_processing/text_normalization/es/data/roman/ties.tsv +++ /dev/null @@ -1,9 +0,0 @@ -x 1 -xx 2 -xxx 3 -xl 4 -l 5 -lx 6 -lxx 7 -lxxx 8 -xc 9 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/__init__.py b/nemo_text_processing/text_normalization/es/data/time/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/data/time/afternoon_times.tsv b/nemo_text_processing/text_normalization/es/data/time/afternoon_times.tsv deleted file mode 100644 index 25e75c8b30ec..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/afternoon_times.tsv +++ /dev/null @@ -1,4 +0,0 @@ -una -dos -tres -cuatro \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/alt_minutes.tsv b/nemo_text_processing/text_normalization/es/data/time/alt_minutes.tsv deleted file mode 100644 index 6bdff30993d4..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/alt_minutes.tsv +++ /dev/null @@ -1,2 +0,0 @@ -quince cuarto -treinta media \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/evening_times.tsv b/nemo_text_processing/text_normalization/es/data/time/evening_times.tsv deleted file mode 100644 index c77d4c7f1e25..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/evening_times.tsv +++ /dev/null @@ -1,7 +0,0 @@ -cinco -seis -siete -ocho -nueve -diez -once \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/hour_to_12.tsv b/nemo_text_processing/text_normalization/es/data/time/hour_to_12.tsv deleted file mode 100644 index e681afc6c25c..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/hour_to_12.tsv +++ /dev/null @@ -1,12 +0,0 @@ -1 12 -2 1 -3 2 -4 3 -5 4 -6 5 -7 6 -8 7 -9 8 -10 9 -11 10 -12 11 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/hour_to_24.tsv b/nemo_text_processing/text_normalization/es/data/time/hour_to_24.tsv deleted file mode 100644 index 13f43dc5b9b9..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/hour_to_24.tsv +++ /dev/null @@ -1,25 +0,0 @@ -1 0 -2 1 -3 2 -4 3 -5 4 -6 5 -7 6 -8 7 -9 8 -10 9 -11 10 -12 11 -13 12 -14 13 -15 14 -16 15 -17 16 -18 17 -19 18 -20 19 -21 20 -22 21 -23 22 -0 23 -1 24 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/hour_to_night.tsv b/nemo_text_processing/text_normalization/es/data/time/hour_to_night.tsv deleted file mode 100644 index b7765ac2a3c6..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/hour_to_night.tsv +++ /dev/null @@ -1,13 +0,0 @@ -12 0 -1 13 -2 14 -3 15 -4 16 -5 17 -6 18 -7 19 -8 20 -9 21 -10 22 -11 23 -12 24 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/minute_to.tsv b/nemo_text_processing/text_normalization/es/data/time/minute_to.tsv deleted file mode 100644 index edab4d5b03d6..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/minute_to.tsv +++ /dev/null @@ -1,59 +0,0 @@ -1 59 -2 58 -3 57 -4 56 -5 55 -6 54 -7 53 -8 52 -9 51 -10 50 -11 49 -12 48 -13 47 -14 46 -15 45 -16 44 -17 43 -18 42 -19 41 -20 40 -21 39 -22 38 -23 37 -24 36 -25 35 -26 34 -27 33 -28 32 -29 31 -30 30 -31 29 -32 28 -33 27 -34 26 -35 25 -36 24 -37 23 -38 22 -39 21 -40 20 -41 19 -42 18 -43 17 -44 16 -45 15 -46 14 -47 13 -48 12 -49 11 -50 10 -51 9 -52 8 -53 7 -54 6 -55 5 -56 4 -57 3 -58 2 -59 1 diff --git a/nemo_text_processing/text_normalization/es/data/time/morning_times.tsv b/nemo_text_processing/text_normalization/es/data/time/morning_times.tsv deleted file mode 100644 index e329184d2bd0..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/morning_times.tsv +++ /dev/null @@ -1,12 +0,0 @@ -un -una -dos -tres -cuatro -cinco -seis -siete -ocho -nueve -diez -once \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/time_suffix.tsv b/nemo_text_processing/text_normalization/es/data/time/time_suffix.tsv deleted file mode 100644 index 9ba6b1ceb170..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/time_suffix.tsv +++ /dev/null @@ -1,20 +0,0 @@ -p.m. pm -p. m. pm -p.m pm -p m. pm -pm pm -P.M. pm -P.M pm -P M. pm -P. M. pm -PM pm -a.m. am -a.m. am -a.m am -a m. am -am am -A.M. am -A.M am -A M. am -A. M. am -AM am \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/time/time_zone.tsv b/nemo_text_processing/text_normalization/es/data/time/time_zone.tsv deleted file mode 100644 index e310d8f3b921..000000000000 --- a/nemo_text_processing/text_normalization/es/data/time/time_zone.tsv +++ /dev/null @@ -1,7 +0,0 @@ -cst c s t -cet c e t -pst p s t -est e s t -pt p t -et e t -gmt g m t \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/data/whitelist.tsv b/nemo_text_processing/text_normalization/es/data/whitelist.tsv deleted file mode 100644 index ecf6dcfbb2d2..000000000000 --- a/nemo_text_processing/text_normalization/es/data/whitelist.tsv +++ /dev/null @@ -1,42 +0,0 @@ -ud. usted -Ud. usted -uds. ustedes -Uds. ustedes -Vd. vosotros -Vds. vosotros -vd. vosotros -vds. vosotros -D. Don -Da. Donna -Dr. Doctor -Dra. Doctora -dr. doctor -dra. doctora -d. don -da. donna -E este -EE. Estados Unidos -ee. estados unidos -Gob. gobierno -gob. gobierno -esq. esquina -Av. avenida -Avda. avenida -av. avenida -avda. avenida -O oeste -pág. página -p.ej. por ejemplo -Prof. profesor -Profa. profesora -prof. profesor -profa. profesora -S sur -N norte -Sr. señor -sr. señor -Sra. señora -sra. señora -Srta. señorita -srta. señorita -tel. teléfono \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/es/graph_utils.py b/nemo_text_processing/text_normalization/es/graph_utils.py deleted file mode 100644 index 7f0a7a34c939..000000000000 --- a/nemo_text_processing/text_normalization/es/graph_utils.py +++ /dev/null @@ -1,174 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, NEMO_SPACE -from nemo_text_processing.text_normalization.es import LOCALIZATION -from nemo_text_processing.text_normalization.es.utils import get_abs_path, load_labels -from pynini.lib import pynutil - -digits = pynini.project(pynini.string_file(get_abs_path("data/numbers/digit.tsv")), "input") -tens = pynini.project(pynini.string_file(get_abs_path("data/numbers/ties.tsv")), "input") -teens = pynini.project(pynini.string_file(get_abs_path("data/numbers/teen.tsv")), "input") -twenties = pynini.project(pynini.string_file(get_abs_path("data/numbers/twenties.tsv")), "input") -hundreds = pynini.project(pynini.string_file(get_abs_path("data/numbers/hundreds.tsv")), "input") - -accents = pynini.string_map([("á", "a"), ("é", "e"), ("í", "i"), ("ó", "o"), ("ú", "u")]) - -if LOCALIZATION == "am": # Setting localization for central and northern america formatting - cardinal_separator = pynini.string_map([",", NEMO_SPACE]) - decimal_separator = pynini.accep(".") -else: - cardinal_separator = pynini.string_map([".", NEMO_SPACE]) - decimal_separator = pynini.accep(",") - -ones = pynini.union("un", "ún") -fem_ones = pynini.union(pynini.cross("un", "una"), pynini.cross("ún", "una"), pynini.cross("uno", "una")) -one_to_one_hundred = pynini.union(digits, "uno", tens, teens, twenties, tens + pynini.accep(" y ") + digits) -fem_hundreds = hundreds @ pynini.cdrewrite(pynini.cross("ientos", "ientas"), "", "", NEMO_SIGMA) - - -def strip_accent(fst: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Converts all accented vowels to non-accented equivalents - - Args: - fst: Any fst. Composes vowel conversion onto fst's output strings - """ - return fst @ pynini.cdrewrite(accents, "", "", NEMO_SIGMA) - - -def shift_cardinal_gender(fst: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Applies gender conversion rules to a cardinal string. These include: rendering all masculine forms of "uno" (including apocopated forms) as "una" and - Converting all gendered numbers in the hundreds series (200,300,400...) to feminine equivalent (e.g. "doscientos" -> "doscientas"). Conversion only applies - to value place for <1000 and multiple of 1000. (e.g. "doscientos mil doscientos" -> "doscientas mil doscientas".) For place values greater than the thousands, there - is no gender shift as the higher powers of ten ("millones", "billones") are masculine nouns and any conversion would be formally - ungrammatical. - e.g. - "doscientos" -> "doscientas" - "doscientos mil" -> "doscientas mil" - "doscientos millones" -> "doscientos millones" - "doscientos mil millones" -> "doscientos mil millones" - "doscientos millones doscientos mil doscientos" -> "doscientos millones doscientas mil doscientas" - - Args: - fst: Any fst. Composes conversion onto fst's output strings - """ - before_mil = ( - NEMO_SPACE - + (pynini.accep("mil") | pynini.accep("milésimo")) - + pynini.closure(NEMO_SPACE + hundreds, 0, 1) - + pynini.closure(NEMO_SPACE + one_to_one_hundred, 0, 1) - + pynini.union(pynini.accep("[EOS]"), pynini.accep("\""), decimal_separator) - ) - before_double_digits = pynini.closure(NEMO_SPACE + one_to_one_hundred, 0, 1) + pynini.union( - pynini.accep("[EOS]"), pynini.accep("\"") - ) - - fem_allign = pynini.cdrewrite(fem_hundreds, "", before_mil, NEMO_SIGMA) # doscientas mil dosciento - fem_allign @= pynini.cdrewrite(fem_hundreds, "", before_double_digits, NEMO_SIGMA) # doscientas mil doscienta - - fem_allign @= pynini.cdrewrite( - fem_ones, "", pynini.union("[EOS]", "\"", decimal_separator), NEMO_SIGMA - ) # If before a quote or EOS, we know it's the end of a string - - return fst @ fem_allign - - -def shift_number_gender(fst: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Performs gender conversion on all verbalized numbers in output. All values in the hundreds series (200,300,400) are changed to - feminine gender (e.g. "doscientos" -> "doscientas") and all forms of "uno" (including apocopated forms) are converted to "una". - This has no boundary restriction and will perform shift across all values in output string. - e.g. - "doscientos" -> "doscientas" - "doscientos millones" -> "doscientas millones" - "doscientos millones doscientos" -> "doscientas millones doscientas" - - Args: - fst: Any fst. Composes conversion onto fst's output strings - """ - fem_allign = pynini.cdrewrite(fem_hundreds, "", "", NEMO_SIGMA) - fem_allign @= pynini.cdrewrite( - fem_ones, "", pynini.union(NEMO_SPACE, pynini.accep("[EOS]"), pynini.accep("\"")), NEMO_SIGMA - ) # If before a quote or EOS, we know it's the end of a string - - return fst @ fem_allign - - -def strip_cardinal_apocope(fst: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Reverts apocope on cardinal strings in line with formation rules. e.g. "un" -> "uno". Due to cardinal formation rules, this in effect only - affects strings where the final value is a variation of "un". - e.g. - "un" -> "uno" - "veintiún" -> "veintiuno" - - Args: - fst: Any fst. Composes conversion onto fst's output strings - """ - # Since cardinals use apocope by default for large values (e.g. "millón"), this only needs to act on the last instance of one - strip = pynini.cross("un", "uno") | pynini.cross("ún", "uno") - strip = pynini.cdrewrite(strip, "", pynini.union("[EOS]", "\""), NEMO_SIGMA) - return fst @ strip - - -def add_cardinal_apocope_fem(fst: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Adds apocope on cardinal strings in line with stressing rules. e.g. "una" -> "un". This only occurs when "una" precedes a stressed "a" sound in formal speech. This is not predictable - with text string, so is included for non-deterministic cases. - e.g. - "una" -> "un" - "veintiuna" -> "veintiun" - - Args: - fst: Any fst. Composes conversion onto fst's output strings - """ - # Since the stress trigger follows the cardinal string and only affects the preceding sound, this only needs to act on the last instance of one - strip = pynini.cross("una", "un") | pynini.cross("veintiuna", "veintiún") - strip = pynini.cdrewrite(strip, "", pynini.union("[EOS]", "\""), NEMO_SIGMA) - return fst @ strip - - -def roman_to_int(fst: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Alters given fst to convert Roman integers (lower and upper cased) into Arabic numerals. Valid for values up to 1000. - e.g. - "V" -> "5" - "i" -> "1" - - Args: - fst: Any fst. Composes fst onto Roman conversion outputs. - """ - - def _load_roman(file: str): - roman = load_labels(get_abs_path(file)) - roman_numerals = [(x, y) for x, y in roman] + [(x.upper(), y) for x, y in roman] - return pynini.string_map(roman_numerals) - - digit = _load_roman("data/roman/digit.tsv") - ties = _load_roman("data/roman/ties.tsv") - hundreds = _load_roman("data/roman/hundreds.tsv") - - graph = ( - digit - | ties + (digit | pynutil.add_weight(pynutil.insert("0"), 0.01)) - | ( - hundreds - + (ties | pynutil.add_weight(pynutil.insert("0"), 0.01)) - + (digit | pynutil.add_weight(pynutil.insert("0"), 0.01)) - ) - ).optimize() - - return graph @ fst diff --git a/nemo_text_processing/text_normalization/es/taggers/__init__.py b/nemo_text_processing/text_normalization/es/taggers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/taggers/cardinal.py b/nemo_text_processing/text_normalization/es/taggers/cardinal.py deleted file mode 100644 index c535100f7934..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/cardinal.py +++ /dev/null @@ -1,176 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - NEMO_SPACE, - NEMO_WHITE_SPACE, - GraphFst, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es.graph_utils import cardinal_separator -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -zero = pynini.invert(pynini.string_file(get_abs_path("data/numbers/zero.tsv"))) -digit = pynini.invert(pynini.string_file(get_abs_path("data/numbers/digit.tsv"))) -teen = pynini.invert(pynini.string_file(get_abs_path("data/numbers/teen.tsv"))) -ties = pynini.invert(pynini.string_file(get_abs_path("data/numbers/ties.tsv"))) -twenties = pynini.invert(pynini.string_file(get_abs_path("data/numbers/twenties.tsv"))) -hundreds = pynini.invert(pynini.string_file(get_abs_path("data/numbers/hundreds.tsv"))) - - -def filter_punctuation(fst: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Helper function for parsing number strings. Converts common cardinal strings (groups of three digits delineated by 'cardinal_separator' - see graph_utils) - and converts to a string of digits: - "1 000" -> "1000" - "1.000.000" -> "1000000" - Args: - fst: Any pynini.FstLike object. Function composes fst onto string parser fst - - Returns: - fst: A pynini.FstLike object - """ - exactly_three_digits = NEMO_DIGIT ** 3 # for blocks of three - up_to_three_digits = pynini.closure(NEMO_DIGIT, 1, 3) # for start of string - - cardinal_string = pynini.closure( - NEMO_DIGIT, 1 - ) # For string w/o punctuation (used for page numbers, thousand series) - - cardinal_string |= ( - up_to_three_digits - + pynutil.delete(cardinal_separator) - + pynini.closure(exactly_three_digits + pynutil.delete(cardinal_separator)) - + exactly_three_digits - ) - - return cardinal_string @ fst - - -class CardinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals, e.g. - "1000" -> cardinal { integer: "mil" } - "2.000.000" -> cardinal { integer: "dos millones" } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="cardinal", kind="classify", deterministic=deterministic) - - # Any single digit - graph_digit = digit - digits_no_one = (NEMO_DIGIT - "1") @ graph_digit - - # Any double digit - graph_tens = teen - graph_tens |= ties + (pynutil.delete('0') | (pynutil.insert(" y ") + graph_digit)) - graph_tens |= twenties - - self.tens = graph_tens.optimize() - - self.two_digit_non_zero = pynini.union( - graph_digit, graph_tens, (pynini.cross("0", NEMO_SPACE) + graph_digit) - ).optimize() - - # Three digit strings - graph_hundreds = hundreds + pynini.union( - pynutil.delete("00"), (insert_space + graph_tens), (pynini.cross("0", NEMO_SPACE) + graph_digit) - ) - graph_hundreds |= pynini.cross("100", "cien") - graph_hundreds |= ( - pynini.cross("1", "ciento") + insert_space + pynini.union(graph_tens, pynutil.delete("0") + graph_digit) - ) - - self.hundreds = graph_hundreds.optimize() - - # For all three digit strings with leading zeroes (graph appends '0's to manage place in string) - graph_hundreds_component = pynini.union(graph_hundreds, pynutil.delete("0") + graph_tens) - - graph_hundreds_component_at_least_one_none_zero_digit = graph_hundreds_component | ( - pynutil.delete("00") + graph_digit - ) - graph_hundreds_component_at_least_one_none_zero_digit_no_one = graph_hundreds_component | ( - pynutil.delete("00") + digits_no_one - ) - - graph_thousands_component_at_least_one_none_zero_digit = pynini.union( - pynutil.delete("000") + graph_hundreds_component_at_least_one_none_zero_digit, - graph_hundreds_component_at_least_one_none_zero_digit_no_one - + pynutil.insert(" mil") - + ((insert_space + graph_hundreds_component_at_least_one_none_zero_digit) | pynutil.delete("000")), - pynini.cross("001", "mil") - + ((insert_space + graph_hundreds_component_at_least_one_none_zero_digit) | pynutil.delete("000")), - ) - - graph_thousands_component_at_least_one_none_zero_digit_no_one = pynini.union( - pynutil.delete("000") + graph_hundreds_component_at_least_one_none_zero_digit_no_one, - graph_hundreds_component_at_least_one_none_zero_digit_no_one - + pynutil.insert(" mil") - + ((insert_space + graph_hundreds_component_at_least_one_none_zero_digit) | pynutil.delete("000")), - pynini.cross("001", "mil") - + ((insert_space + graph_hundreds_component_at_least_one_none_zero_digit) | pynutil.delete("000")), - ) - - graph_million = pynutil.add_weight(pynini.cross("000001", "un millón"), -0.001) - graph_million |= graph_thousands_component_at_least_one_none_zero_digit_no_one + pynutil.insert(" millones") - graph_million |= pynutil.delete("000000") - graph_million += insert_space - - graph_billion = pynutil.add_weight(pynini.cross("000001", "un billón"), -0.001) - graph_billion |= graph_thousands_component_at_least_one_none_zero_digit_no_one + pynutil.insert(" billones") - graph_billion |= pynutil.delete("000000") - graph_billion += insert_space - - graph_trillion = pynutil.add_weight(pynini.cross("000001", "un trillón"), -0.001) - graph_trillion |= graph_thousands_component_at_least_one_none_zero_digit_no_one + pynutil.insert(" trillones") - graph_trillion |= pynutil.delete("000000") - graph_trillion += insert_space - - graph = ( - graph_trillion - + graph_billion - + graph_million - + (graph_thousands_component_at_least_one_none_zero_digit | pynutil.delete("000000")) - ) - - self.graph = ( - ((NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT, 0)) - @ pynini.cdrewrite(pynini.closure(pynutil.insert("0")), "[BOS]", "", NEMO_SIGMA) - @ NEMO_DIGIT ** 24 - @ graph - @ pynini.cdrewrite(delete_space, "[BOS]", "", NEMO_SIGMA) - @ pynini.cdrewrite(delete_space, "", "[EOS]", NEMO_SIGMA) - @ pynini.cdrewrite( - pynini.cross(pynini.closure(NEMO_WHITE_SPACE, 2), NEMO_SPACE), NEMO_ALPHA, NEMO_ALPHA, NEMO_SIGMA - ) - ) - self.graph |= zero - - self.graph = filter_punctuation(self.graph).optimize() - - optional_minus_graph = pynini.closure(pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1) - - final_graph = optional_minus_graph + pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"") - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/date.py b/nemo_text_processing/text_normalization/es/taggers/date.py deleted file mode 100644 index 4f40e83a8031..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/date.py +++ /dev/null @@ -1,96 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, NEMO_SPACE, GraphFst, delete_extra_space -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -articles = pynini.union("de", "del", "el", "del año") -delete_leading_zero = (pynutil.delete("0") | (NEMO_DIGIT - "0")) + NEMO_DIGIT -month_numbers = pynini.string_file(get_abs_path("data/dates/months.tsv")) - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, e.g. - "01.04.2010" -> date { day: "un" month: "enero" year: "dos mil diez" preserve_order: true } - "marzo 4 2000" -> date { month: "marzo" day: "cuatro" year: "dos mil" } - "1990-20-01" -> date { year: "mil novecientos noventa" day: "veinte" month: "enero" } - - Args: - cardinal: cardinal GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool): - super().__init__(name="date", kind="classify", deterministic=deterministic) - - number_to_month = month_numbers.optimize() - month_graph = pynini.project(number_to_month, "output") - - numbers = cardinal.graph - optional_leading_zero = delete_leading_zero | NEMO_DIGIT - - # 01, 31, 1 - digit_day = optional_leading_zero @ pynini.union(*[str(x) for x in range(1, 32)]) @ numbers - day = (pynutil.insert("day: \"") + digit_day + pynutil.insert("\"")).optimize() - - digit_month = optional_leading_zero @ pynini.union(*[str(x) for x in range(1, 13)]) - number_to_month = digit_month @ number_to_month - - month_name = (pynutil.insert("month: \"") + month_graph + pynutil.insert("\"")).optimize() - month_number = (pynutil.insert("month: \"") + number_to_month + pynutil.insert("\"")).optimize() - - # prefer cardinal over year - year = (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT, 1, 3) # 90, 990, 1990 - year @= numbers - self.year = year - - year_only = pynutil.insert("year: \"") + year + pynutil.insert("\"") - year_with_articles = ( - pynutil.insert("year: \"") + pynini.closure(articles + NEMO_SPACE, 0, 1) + year + pynutil.insert("\"") - ) - - graph_dmy = ( - day - + pynini.closure(pynutil.delete(" de")) - + NEMO_SPACE - + month_name - + pynini.closure(NEMO_SPACE + year_with_articles, 0, 1) - ) - - graph_mdy = ( # English influences on language - month_name + delete_extra_space + day + pynini.closure(NEMO_SPACE + year_with_articles, 0, 1) - ) - - separators = [".", "-", "/"] - for sep in separators: - year_optional = pynini.closure(pynini.cross(sep, NEMO_SPACE) + year_only, 0, 1) - new_graph = day + pynini.cross(sep, NEMO_SPACE) + month_number + year_optional - graph_dmy |= new_graph - if not deterministic: - new_graph = month_number + pynini.cross(sep, NEMO_SPACE) + day + year_optional - graph_mdy |= new_graph - - dash = "-" - day_optional = pynini.closure(pynini.cross(dash, NEMO_SPACE) + day, 0, 1) - graph_ymd = NEMO_DIGIT ** 4 @ year_only + pynini.cross(dash, NEMO_SPACE) + month_number + day_optional - - final_graph = graph_dmy + pynutil.insert(" preserve_order: true") - final_graph |= graph_ymd - final_graph |= graph_mdy - - self.final_graph = final_graph.optimize() - self.fst = self.add_tokens(self.final_graph).optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/decimals.py b/nemo_text_processing/text_normalization/es/taggers/decimals.py deleted file mode 100644 index 4d6e6e2f3598..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/decimals.py +++ /dev/null @@ -1,127 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es.graph_utils import ( - cardinal_separator, - decimal_separator, - strip_cardinal_apocope, -) -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -quantities = pynini.string_file(get_abs_path("data/numbers/quantities.tsv")) -digit = pynini.invert(pynini.string_file(get_abs_path("data/numbers/digit.tsv"))) -zero = pynini.invert(pynini.string_file(get_abs_path("data/numbers/zero.tsv"))) - - -def get_quantity(decimal_graph: 'pynini.FstLike', cardinal_graph: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral, - e.g. 2 millones -> integer_part: "dos" quantity: "millones" - e.g. 2,4 millones -> integer_part: "dos" fractional_part: "quatro" quantity: "millones" - e.g. 2,400 millones -> integer_part: "dos mil cuatrocientos" fractional_part: "quatro" quantity: "millones" - - Args: - decimal_graph: DecimalFST - cardinal_graph: CardinalFST - """ - numbers = pynini.closure(NEMO_DIGIT, 1, 6) @ cardinal_graph - numbers = pynini.cdrewrite(pynutil.delete(cardinal_separator), "", "", NEMO_SIGMA) @ numbers - - res = ( - pynutil.insert("integer_part: \"") - + numbers # The cardinal we're passing only produces 'un' for one, so gender agreement is safe (all quantities are masculine). Limit to 10^6 power. - + pynutil.insert("\"") - + NEMO_SPACE - + pynutil.insert("quantity: \"") - + quantities - + pynutil.insert("\"") - ) - res |= decimal_graph + NEMO_SPACE + pynutil.insert("quantity: \"") + quantities + pynutil.insert("\"") - return res - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal, e.g. - -11,4006 billones -> decimal { negative: "true" integer_part: "once" fractional_part: "cuatro cero cero seis" quantity: "billones" preserve_order: true } - 1 billón -> decimal { integer_part: "un" quantity: "billón" preserve_order: true } - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - graph_digit = digit | zero - - if not deterministic: - graph = pynini.union(graph_digit, cardinal.hundreds, cardinal.tens) - graph += pynini.closure(insert_space + graph) - - else: - # General pattern seems to be 1-3 digits: map as cardinal, default to digits otherwise \ - graph = pynini.union( - graph_digit, - cardinal.tens, - cardinal.hundreds, - graph_digit + pynini.closure(insert_space + graph_digit, 3), - zero - + pynini.closure(insert_space + zero) - + pynini.closure(insert_space + graph_digit), # For cases such as "1,010" - ) - - # Need to strip apocope everywhere BUT end of string - reverse_apocope = pynini.string_map([("un", "uno"), ("ún", "uno")]) - apply_reverse_apocope = pynini.cdrewrite(reverse_apocope, "", NEMO_SPACE, NEMO_SIGMA) - graph @= apply_reverse_apocope - - # Technically decimals should be space delineated groups of three, e.g. (1,333 333). This removes any possible spaces - strip_formatting = pynini.cdrewrite(delete_space, "", "", NEMO_SIGMA) - graph = strip_formatting @ graph - - self.graph = graph.optimize() - - graph_separator = pynutil.delete(decimal_separator) - optional_graph_negative = pynini.closure(pynutil.insert("negative: ") + pynini.cross("-", "\"true\" "), 0, 1) - - self.graph_fractional = pynutil.insert("fractional_part: \"") + self.graph + pynutil.insert("\"") - - # Integer graph maintains apocope except for ones place - graph_integer = ( - strip_cardinal_apocope(cardinal.graph) - if deterministic - else pynini.union(cardinal.graph, strip_cardinal_apocope(cardinal.graph)) - ) # Gives us forms w/ and w/o apocope - self.graph_integer = pynutil.insert("integer_part: \"") + graph_integer + pynutil.insert("\"") - final_graph_wo_sign = self.graph_integer + graph_separator + insert_space + self.graph_fractional - - self.final_graph_wo_negative = ( - final_graph_wo_sign | get_quantity(final_graph_wo_sign, cardinal.graph).optimize() - ) - final_graph = optional_graph_negative + self.final_graph_wo_negative - - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/electronic.py b/nemo_text_processing/text_normalization/es/taggers/electronic.py deleted file mode 100644 index 13833bbe03ae..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/electronic.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_ALPHA, NEMO_DIGIT, GraphFst, insert_space -from nemo_text_processing.text_normalization.es.utils import get_abs_path, load_labels -from pynini.lib import pynutil - -common_domains = [x[0] for x in load_labels(get_abs_path("data/electronic/domain.tsv"))] -symbols = [x[0] for x in load_labels(get_abs_path("data/electronic/symbols.tsv"))] - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic: email addresses - e.g. "abc@hotmail.com" -> electronic { username: "abc" domain: "hotmail.com" preserve_order: true } - e.g. "www.abc.com/123" -> electronic { protocol: "www." domain: "abc.com/123" preserve_order: true } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="classify", deterministic=deterministic) - - dot = pynini.accep(".") - accepted_common_domains = pynini.union(*common_domains) - accepted_symbols = pynini.union(*symbols) - dot - accepted_characters = pynini.closure(NEMO_ALPHA | NEMO_DIGIT | accepted_symbols) - acceepted_characters_with_dot = pynini.closure(NEMO_ALPHA | NEMO_DIGIT | accepted_symbols | dot) - - # email - username = ( - pynutil.insert("username: \"") - + acceepted_characters_with_dot - + pynutil.insert("\"") - + pynini.cross('@', ' ') - ) - domain_graph = accepted_characters + dot + accepted_characters - domain_graph = pynutil.insert("domain: \"") + domain_graph + pynutil.insert("\"") - domain_common_graph = ( - pynutil.insert("domain: \"") - + accepted_characters - + accepted_common_domains - + pynini.closure((accepted_symbols | dot) + pynini.closure(accepted_characters, 1), 0, 1) - + pynutil.insert("\"") - ) - graph = (username + domain_graph) | domain_common_graph - - # url - protocol_start = pynini.accep("https://") | pynini.accep("http://") - protocol_end = ( - pynini.accep("www.") - if deterministic - else pynini.accep("www.") | pynini.cross("www.", "doble ve doble ve doble ve.") - ) - protocol = protocol_start | protocol_end | (protocol_start + protocol_end) - protocol = pynutil.insert("protocol: \"") + protocol + pynutil.insert("\"") - graph |= protocol + insert_space + (domain_graph | domain_common_graph) - self.graph = graph - - final_graph = self.add_tokens(self.graph + pynutil.insert(" preserve_order: true")) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/fraction.py b/nemo_text_processing/text_normalization/es/taggers/fraction.py deleted file mode 100644 index c52e8eafc4cd..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/fraction.py +++ /dev/null @@ -1,114 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_DIGIT, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, -) -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -ordinal_exceptions = pynini.string_file(get_abs_path("data/fractions/ordinal_exceptions.tsv")) -higher_powers_of_ten = pynini.string_file(get_abs_path("data/fractions/powers_of_ten.tsv")) - - -class FractionFst(GraphFst): - """ - Finite state transducer for classifying fraction - "23 4/5" -> - tokens { fraction { integer: "veintitrés" numerator: "cuatro" denominator: "quinto" mophosyntactic_features: "ordinal" } } - - Args: - cardinal: CardinalFst - ordinal: OrdinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, ordinal: GraphFst, deterministic: bool = True): - super().__init__(name="fraction", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph - ordinal_graph = ordinal.graph - - # 2-10 are all ordinals - three_to_ten = pynini.string_map(["2", "3", "4", "5", "6", "7", "8", "9", "10",]) - block_three_to_ten = pynutil.delete(three_to_ten) # To block cardinal productions - if not deterministic: # Multiples of tens are sometimes rendered as ordinals - three_to_ten |= pynini.string_map(["20", "30", "40", "50", "60", "70", "80", "90",]) - graph_three_to_ten = three_to_ten @ ordinal_graph - graph_three_to_ten @= pynini.cdrewrite(ordinal_exceptions, "", "", NEMO_SIGMA) - - # Higher powers of tens (and multiples) are converted to ordinals. - hundreds = pynini.string_map(["100", "200", "300", "400", "500", "600", "700", "800", "900",]) - graph_hundreds = hundreds @ ordinal_graph - - multiples_of_thousand = ordinal.multiples_of_thousand # So we can have X milésimos - - graph_higher_powers_of_ten = ( - pynini.closure(ordinal.one_to_one_thousand + NEMO_SPACE, 0, 1) - + pynini.closure("mil ", 0, 1) - + pynini.closure(ordinal.one_to_one_thousand + NEMO_SPACE, 0, 1) - ) # x millones / x mil millones / x mil z millones - graph_higher_powers_of_ten += higher_powers_of_ten - graph_higher_powers_of_ten = cardinal_graph @ graph_higher_powers_of_ten - graph_higher_powers_of_ten @= pynini.cdrewrite( - pynutil.delete("un "), pynini.accep("[BOS]"), pynini.project(higher_powers_of_ten, "output"), NEMO_SIGMA - ) # we drop 'un' from these ordinals (millionths, not one-millionths) - - graph_higher_powers_of_ten = multiples_of_thousand | graph_hundreds | graph_higher_powers_of_ten - block_higher_powers_of_ten = pynutil.delete( - pynini.project(graph_higher_powers_of_ten, "input") - ) # For cardinal graph - - graph_fractions_ordinals = graph_higher_powers_of_ten | graph_three_to_ten - graph_fractions_ordinals += pynutil.insert( - "\" morphosyntactic_features: \"ordinal\"" - ) # We note the root for processing later - - # Blocking the digits and hundreds from Cardinal graph - graph_fractions_cardinals = pynini.cdrewrite( - block_three_to_ten | block_higher_powers_of_ten, pynini.accep("[BOS]"), pynini.accep("[EOS]"), NEMO_SIGMA - ) - graph_fractions_cardinals @= NEMO_CHAR.plus @ pynini.cdrewrite( - pynutil.delete("0"), pynini.accep("[BOS]"), pynini.accep("[EOS]"), NEMO_SIGMA - ) # Empty characters become '0' for NEMO_CHAR fst, so need to block - graph_fractions_cardinals @= cardinal_graph - graph_fractions_cardinals += pynutil.insert( - "\" morphosyntactic_features: \"add_root\"" - ) # blocking these entries to reduce erroneous possibilities in debugging - - if deterministic: - graph_fractions_cardinals = ( - pynini.closure(NEMO_DIGIT, 1, 2) @ graph_fractions_cardinals - ) # Past hundreds the conventional scheme can be hard to read. For determinism we stop here - - graph_denominator = pynini.union( - graph_fractions_ordinals, - graph_fractions_cardinals, - pynutil.add_weight(cardinal_graph + pynutil.insert("\""), 0.001), - ) # Last form is simply recording the cardinal. Weighting so last resort - - integer = pynutil.insert("integer_part: \"") + cardinal_graph + pynutil.insert("\"") + NEMO_SPACE - numerator = ( - pynutil.insert("numerator: \"") + cardinal_graph + (pynini.cross("/", "\" ") | pynini.cross(" / ", "\" ")) - ) - denominator = pynutil.insert("denominator: \"") + graph_denominator - - self.graph = pynini.closure(integer, 0, 1) + numerator + denominator - - final_graph = self.add_tokens(self.graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/measure.py b/nemo_text_processing/text_normalization/es/taggers/measure.py deleted file mode 100644 index 8335a6b853da..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/measure.py +++ /dev/null @@ -1,173 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_NON_BREAKING_SPACE, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - convert_space, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es.graph_utils import strip_cardinal_apocope -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -unit = pynini.string_file(get_abs_path("data/measures/measurements.tsv")) -unit_plural_fem = pynini.string_file(get_abs_path("data/measures/measurements_plural_fem.tsv")) -unit_plural_masc = pynini.string_file(get_abs_path("data/measures/measurements_plural_masc.tsv")) - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure, e.g. - "2,4 g" -> measure { cardinal { integer_part: "dos" fractional_part: "cuatro" units: "gramos" preserve_order: true } } - "1 g" -> measure { cardinal { integer: "un" units: "gramo" preserve_order: true } } - "1 millón g" -> measure { cardinal { integer: "un quantity: "millón" units: "gramos" preserve_order: true } } - e.g. "a-8" —> "a ocho" - e.g. "1,2-a" —> "uno coma dos a" - This class also converts words containing numbers and letters - e.g. "a-8" —> "a ocho" - e.g. "1,2-a" —> "uno coma dos a" - - - Args: - cardinal: CardinalFst - decimal: DecimalFst - fraction: FractionFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, fraction: GraphFst, deterministic: bool = True): - super().__init__(name="measure", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph - - unit_singular = unit - unit_plural = unit_singular @ (unit_plural_fem | unit_plural_masc) - - graph_unit_singular = convert_space(unit_singular) - graph_unit_plural = convert_space(unit_plural) - - optional_graph_negative = pynini.closure("-", 0, 1) - - graph_unit_denominator = ( - pynini.cross("/", "por") + pynutil.insert(NEMO_NON_BREAKING_SPACE) + graph_unit_singular - ) - - optional_unit_denominator = pynini.closure( - pynutil.insert(NEMO_NON_BREAKING_SPACE) + graph_unit_denominator, 0, 1, - ) - - unit_plural = ( - pynutil.insert("units: \"") - + ((graph_unit_plural + optional_unit_denominator) | graph_unit_denominator) - + pynutil.insert("\"") - ) - - unit_singular_graph = ( - pynutil.insert("units: \"") - + ((graph_unit_singular + optional_unit_denominator) | graph_unit_denominator) - + pynutil.insert("\"") - ) - - subgraph_decimal = decimal.fst + insert_space + pynini.closure(NEMO_SPACE, 0, 1) + unit_plural - - subgraph_cardinal = ( - (optional_graph_negative + (NEMO_SIGMA - "1")) @ cardinal.fst - + insert_space - + pynini.closure(delete_space, 0, 1) - + unit_plural - ) - - subgraph_cardinal |= ( - (optional_graph_negative + pynini.accep("1")) @ cardinal.fst - + insert_space - + pynini.closure(delete_space, 0, 1) - + unit_singular_graph - ) - - subgraph_fraction = fraction.fst + insert_space + pynini.closure(delete_space, 0, 1) + unit_singular_graph - - decimal_times = ( - pynutil.insert("decimal { ") - + decimal.final_graph_wo_negative - + pynutil.insert(" } units: \"") - + pynini.union('x', 'X') - + pynutil.insert("\"") - ) - - cardinal_times = ( - pynutil.insert("cardinal { integer: \"") - + strip_cardinal_apocope(cardinal_graph) - + pynutil.insert("\" } units: \"") - + pynini.union('x', 'X') - + pynutil.insert("\"") - ) - - cardinal_dash_alpha = ( - pynutil.insert("cardinal { integer: \"") - + strip_cardinal_apocope(cardinal_graph) - + pynutil.delete('-') - + pynutil.insert("\" } units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.insert("\"") - ) - - decimal_dash_alpha = ( - pynutil.insert("decimal { ") - + decimal.final_graph_wo_negative - + pynutil.delete('-') - + pynutil.insert(" } units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.insert("\"") - ) - - alpha_dash_cardinal = ( - pynutil.insert("units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.delete('-') - + pynutil.insert("\"") - + pynutil.insert(" cardinal { integer: \"") - + cardinal_graph - + pynutil.insert("\" } preserve_order: true") - ) - - alpha_dash_decimal = ( - pynutil.insert("units: \"") - + pynini.closure(NEMO_ALPHA, 1) - + pynutil.delete('-') - + pynutil.insert("\"") - + pynutil.insert(" decimal { ") - + decimal.final_graph_wo_negative - + pynutil.insert(" } preserve_order: true") - ) - - final_graph = ( - subgraph_decimal - | subgraph_cardinal - | cardinal_dash_alpha - | alpha_dash_cardinal - | decimal_dash_alpha - | subgraph_fraction - | decimal_times - | cardinal_times - | alpha_dash_decimal - ) - final_graph += pynutil.insert(" preserve_order: true") - final_graph = self.add_tokens(final_graph) - - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/money.py b/nemo_text_processing/text_normalization/es/taggers/money.py deleted file mode 100644 index 3cb074550097..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/money.py +++ /dev/null @@ -1,181 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es.graph_utils import decimal_separator -from nemo_text_processing.text_normalization.es.utils import get_abs_path, load_labels -from pynini.lib import pynutil - -maj_singular_labels = load_labels(get_abs_path("data/money/currency_major.tsv")) -maj_singular = pynini.string_file((get_abs_path("data/money/currency_major.tsv"))) -min_singular = pynini.string_file(get_abs_path("data/money/currency_minor.tsv")) -fem_plural = pynini.string_file((get_abs_path("data/money/currency_plural_fem.tsv"))) -masc_plural = pynini.string_file((get_abs_path("data/money/currency_plural_masc.tsv"))) - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money, e.g. - "€1" -> money { currency_maj: "euro" integer_part: "un"} - "€1,000" -> money { currency_maj: "euro" integer_part: "un" } - "€1,001" -> money { currency_maj: "euro" integer_part: "un" fractional_part: "cero cero un" } - "£1,4" -> money { integer_part: "una" currency_maj: "libra" fractional_part: "cuarenta" preserve_order: true } - -> money { integer_part: "una" currency_maj: "libra" fractional_part: "cuarenta" currency_min: "penique" preserve_order: true } - "0,01 £" -> money { fractional_part: "un" currency_min: "penique" preserve_order: true } - "0,02 £" -> money { fractional_part: "dos" currency_min: "peniques" preserve_order: true } - "£0,01 million" -> money { currency_maj: "libra" integer_part: "cero" fractional_part: "cero un" quantity: "million" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.graph - graph_decimal_final = decimal.final_graph_wo_negative - - maj_singular_graph = maj_singular - min_singular_graph = min_singular - maj_plural_graph = maj_singular @ (fem_plural | masc_plural) - min_plural_graph = min_singular @ (fem_plural | masc_plural) - - graph_maj_singular = pynutil.insert("currency_maj: \"") + maj_singular_graph + pynutil.insert("\"") - graph_maj_plural = pynutil.insert("currency_maj: \"") + maj_plural_graph + pynutil.insert("\"") - - graph_integer_one = pynutil.insert("integer_part: \"") + pynini.cross("1", "un") + pynutil.insert("\"") - - decimal_with_quantity = (NEMO_SIGMA + NEMO_ALPHA) @ graph_decimal_final - - graph_decimal_plural = pynini.union( - graph_maj_plural + pynini.closure(delete_space, 0, 1) + insert_space + graph_decimal_final, # $1,05 - graph_decimal_final + pynini.closure(delete_space, 0, 1) + insert_space + graph_maj_plural, # 1,05 $ - ) - graph_decimal_plural = ( - (NEMO_SIGMA - "1") + decimal_separator + NEMO_SIGMA - ) @ graph_decimal_plural # Can't have "un euros" - - graph_decimal_singular = pynini.union( - graph_maj_singular + pynini.closure(delete_space, 0, 1) + insert_space + graph_decimal_final, # $1,05 - graph_decimal_final + pynini.closure(delete_space, 0, 1) + insert_space + graph_maj_singular, # 1,05 $ - ) - graph_decimal_singular = (pynini.accep("1") + decimal_separator + NEMO_SIGMA) @ graph_decimal_singular - - graph_decimal = pynini.union( - graph_decimal_singular, - graph_decimal_plural, - graph_maj_plural + pynini.closure(delete_space, 0, 1) + insert_space + decimal_with_quantity, - ) - - graph_integer = ( - pynutil.insert("integer_part: \"") + ((NEMO_SIGMA - "1") @ cardinal_graph) + pynutil.insert("\"") - ) - - graph_integer_only = pynini.union( - graph_maj_singular + pynini.closure(delete_space, 0, 1) + insert_space + graph_integer_one, - graph_integer_one + pynini.closure(delete_space, 0, 1) + insert_space + graph_maj_singular, - ) - graph_integer_only |= pynini.union( - graph_maj_plural + pynini.closure(delete_space, 0, 1) + insert_space + graph_integer, - graph_integer + pynini.closure(delete_space, 0, 1) + insert_space + graph_maj_plural, - ) - - graph = graph_integer_only | graph_decimal - - # remove trailing zeros of non zero number in the first 2 digits and fill up to 2 digits - # e.g. 2000 -> 20, 0200->02, 01 -> 01, 10 -> 10 - # not accepted: 002, 00, 0, - two_digits_fractional_part = ( - pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(pynutil.delete("0")) - ) @ ( - (pynutil.delete("0") + (NEMO_DIGIT - "0")) - | ((NEMO_DIGIT - "0") + pynutil.insert("0")) - | ((NEMO_DIGIT - "0") + NEMO_DIGIT) - ) - - graph_min_singular = pynutil.insert("currency_min: \"") + min_singular_graph + pynutil.insert("\"") - graph_min_plural = pynutil.insert("currency_min: \"") + min_plural_graph + pynutil.insert("\"") - - # format ** euro ** cent - decimal_graph_with_minor = None - for curr_symbol, _ in maj_singular_labels: - preserve_order = pynutil.insert(" preserve_order: true") - - integer_plus_maj = pynini.union( - graph_integer + insert_space + pynutil.insert(curr_symbol) @ graph_maj_plural, - graph_integer_one + insert_space + pynutil.insert(curr_symbol) @ graph_maj_singular, - ) - # non zero integer part - integer_plus_maj = (pynini.closure(NEMO_DIGIT) - "0") @ integer_plus_maj - - graph_fractional_one = ( - pynutil.insert("fractional_part: \"") - + two_digits_fractional_part @ pynini.cross("1", "un") - + pynutil.insert("\"") - ) - - graph_fractional = ( - two_digits_fractional_part @ (pynini.closure(NEMO_DIGIT, 1, 2) - "1") @ cardinal.two_digit_non_zero - ) - graph_fractional = pynutil.insert("fractional_part: \"") + graph_fractional + pynutil.insert("\"") - - fractional_plus_min = pynini.union( - graph_fractional + insert_space + pynutil.insert(curr_symbol) @ graph_min_plural, - graph_fractional_one + insert_space + pynutil.insert(curr_symbol) @ graph_min_singular, - ) - - decimal_graph_with_minor_curr = ( - integer_plus_maj + pynini.cross(decimal_separator, NEMO_SPACE) + fractional_plus_min - ) - decimal_graph_with_minor_curr |= pynutil.add_weight( - integer_plus_maj - + pynini.cross(decimal_separator, NEMO_SPACE) - + pynutil.insert("fractional_part: \"") - + two_digits_fractional_part @ cardinal.two_digit_non_zero - + pynutil.insert("\""), - weight=0.0001, - ) - - decimal_graph_with_minor_curr |= pynutil.delete("0,") + fractional_plus_min - decimal_graph_with_minor_curr = pynini.union( - pynutil.delete(curr_symbol) - + pynini.closure(delete_space, 0, 1) - + decimal_graph_with_minor_curr - + preserve_order, - decimal_graph_with_minor_curr - + preserve_order - + pynini.closure(delete_space, 0, 1) - + pynutil.delete(curr_symbol), - ) - - decimal_graph_with_minor = ( - decimal_graph_with_minor_curr - if decimal_graph_with_minor is None - else pynini.union(decimal_graph_with_minor, decimal_graph_with_minor_curr) - ) - - final_graph = graph | pynutil.add_weight(decimal_graph_with_minor, -0.001) - - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/ordinal.py b/nemo_text_processing/text_normalization/es/taggers/ordinal.py deleted file mode 100644 index a22fd191fc0b..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/ordinal.py +++ /dev/null @@ -1,175 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_space, -) -from nemo_text_processing.text_normalization.es.graph_utils import roman_to_int, strip_accent -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -digit = pynini.invert(pynini.string_file(get_abs_path("data/ordinals/digit.tsv"))) -teens = pynini.invert(pynini.string_file(get_abs_path("data/ordinals/teen.tsv"))) -twenties = pynini.invert(pynini.string_file(get_abs_path("data/ordinals/twenties.tsv"))) -ties = pynini.invert(pynini.string_file(get_abs_path("data/ordinals/ties.tsv"))) -hundreds = pynini.invert(pynini.string_file(get_abs_path("data/ordinals/hundreds.tsv"))) - - -def get_one_to_one_thousand(cardinal: 'pynini.FstLike') -> 'pynini.FstLike': - """ - Produces an acceptor for verbalizations of all numbers from 1 to 1000. Needed for ordinals and fractions. - - Args: - cardinal: CardinalFst - - Returns: - fst: A pynini.FstLike object - """ - numbers = pynini.string_map([str(_) for _ in range(1, 1000)]) @ cardinal - return pynini.project(numbers, "output").optimize() - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying ordinal - "21.º" -> ordinal { integer: "vigésimo primero" morphosyntactic_features: "gender_masc" } - This class converts ordinal up to the millionth (millonésimo) order (exclusive). - - This FST also records the ending of the ordinal (called "morphosyntactic_features"): - either as gender_masc, gender_fem, or apocope. Also introduces plural feature for non-deterministic graphs. - - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="ordinal", kind="classify") - cardinal_graph = cardinal.graph - - graph_digit = digit.optimize() - graph_teens = teens.optimize() - graph_ties = ties.optimize() - graph_twenties = twenties.optimize() - graph_hundreds = hundreds.optimize() - - if not deterministic: - # Some alternative derivations - graph_ties = graph_ties | pynini.cross("sesenta", "setuagésimo") - - graph_teens = graph_teens | pynini.cross("once", "decimoprimero") - graph_teens |= pynini.cross("doce", "decimosegundo") - - graph_digit = graph_digit | pynini.cross("nueve", "nono") - graph_digit |= pynini.cross("siete", "sétimo") - - graph_tens_component = ( - graph_teens - | (graph_ties + pynini.closure(pynini.cross(" y ", NEMO_SPACE) + graph_digit, 0, 1)) - | graph_twenties - ) - - graph_hundred_component = pynini.union( - graph_hundreds + pynini.closure(NEMO_SPACE + pynini.union(graph_tens_component, graph_digit), 0, 1), - graph_tens_component, - graph_digit, - ) - - # Need to go up to thousands for fractions - self.one_to_one_thousand = get_one_to_one_thousand(cardinal_graph) - - thousands = pynini.cross("mil", "milésimo") - - graph_thousands = ( - strip_accent(self.one_to_one_thousand) + NEMO_SPACE + thousands - ) # Cardinals become prefix for thousands series. Snce accent on the powers of ten we strip accent from leading words - graph_thousands @= pynini.cdrewrite(delete_space, "", "milésimo", NEMO_SIGMA) # merge as a prefix - graph_thousands |= thousands - - self.multiples_of_thousand = (cardinal_graph @ graph_thousands).optimize() - - if ( - not deterministic - ): # Formally the words preceding the power of ten should be a prefix, but some maintain word boundaries. - graph_thousands |= (self.one_to_one_thousand @ graph_hundred_component) + NEMO_SPACE + thousands - - graph_thousands += pynini.closure(NEMO_SPACE + graph_hundred_component, 0, 1) - - ordinal_graph = graph_thousands | graph_hundred_component - ordinal_graph = cardinal_graph @ ordinal_graph - - if not deterministic: - # The 10's and 20's series can also be two words - split_words = pynini.cross("decimo", "décimo ") | pynini.cross("vigesimo", "vigésimo ") - split_words = pynini.cdrewrite(split_words, "", NEMO_CHAR, NEMO_SIGMA) - ordinal_graph |= ordinal_graph @ split_words - - # If "octavo" is preceeded by the "o" within string, it needs deletion - ordinal_graph @= pynini.cdrewrite(pynutil.delete("o"), "", "octavo", NEMO_SIGMA) - - self.graph = ordinal_graph.optimize() - - masc = pynini.accep("gender_masc") - fem = pynini.accep("gender_fem") - apocope = pynini.accep("apocope") - - delete_period = pynini.closure(pynutil.delete("."), 0, 1) # Sometimes the period is omitted f - - accept_masc = delete_period + pynini.cross("º", masc) - accep_fem = delete_period + pynini.cross("ª", fem) - accep_apocope = delete_period + pynini.cross("ᵉʳ", apocope) - - # Managing Romanization - graph_roman = pynutil.insert("integer: \"") + roman_to_int(ordinal_graph) + pynutil.insert("\"") - if not deterministic: - # Introduce plural - plural = pynini.closure(pynutil.insert("/plural"), 0, 1) - accept_masc += plural - accep_fem += plural - - # Romanizations have no morphology marker, so in non-deterministic case we provide option for all - insert_morphology = pynutil.insert(pynini.union(masc, fem)) + plural - insert_morphology |= pynutil.insert(apocope) - insert_morphology = ( - pynutil.insert(" morphosyntactic_features: \"") + insert_morphology + pynutil.insert("\"") - ) - - graph_roman += insert_morphology - - else: - # We insert both genders as default - graph_roman += pynutil.insert(" morphosyntactic_features: \"gender_masc\"") | pynutil.insert( - " morphosyntactic_features: \"gender_fem\"" - ) - - # Rest of graph - convert_abbreviation = accept_masc | accep_fem | accep_apocope - - graph = ( - pynutil.insert("integer: \"") - + ordinal_graph - + pynutil.insert("\"") - + pynutil.insert(" morphosyntactic_features: \"") - + convert_abbreviation - + pynutil.insert("\"") - ) - graph = pynini.union(graph, graph_roman) - - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/telephone.py b/nemo_text_processing/text_normalization/es/taggers/telephone.py deleted file mode 100644 index f97207c9696b..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/telephone.py +++ /dev/null @@ -1,144 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, GraphFst, insert_space -from nemo_text_processing.text_normalization.es.graph_utils import ones -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")) -graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv")) -graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")) -graph_twenties = pynini.string_file(get_abs_path("data/numbers/twenties.tsv")) - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone numbers, e.g. - 123-123-5678 -> { number_part: "uno dos tres uno dos tres cinco seis siete ocho" }. - In Spanish, digits are generally read individually, or as 2-digit numbers, - eg. "123" = "uno dos tres", - "1234" = "doce treinta y cuatro". - This will verbalize sequences of 10 (3+3+4 e.g. 123-456-7890). - 9 (3+3+3 e.g. 123-456-789) and 8 (4+4 e.g. 1234-5678) digits. - - (we ignore more complicated cases such as "doscientos y dos" or "tres nueves"). - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="telephone", kind="classify") - - # create `single_digits` and `double_digits` graphs as these will be - # the building blocks of possible telephone numbers - single_digits = pynini.invert(graph_digit).optimize() | pynini.cross("0", "cero") - - double_digits = pynini.union( - graph_twenties, - graph_teen, - (graph_ties + pynutil.delete("0")), - (graph_ties + insert_space + pynutil.insert("y") + insert_space + graph_digit), - ) - double_digits = pynini.invert(double_digits) - - # define `ten_digit_graph`, `nine_digit_graph`, `eight_digit_graph` - # which produces telephone numbers spoken (1) only with single digits, - # or (2) spoken with double digits (and sometimes single digits) - - # 10-digit option (1): all single digits - ten_digit_graph = ( - pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + single_digits - ) - - # 9-digit option (1): all single digits - nine_digit_graph = ( - pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 2, 2) - + single_digits - ) - - # 8-digit option (1): all single digits - eight_digit_graph = ( - pynini.closure(single_digits + insert_space, 4, 4) - + pynutil.delete("-") - + pynini.closure(single_digits + insert_space, 3, 3) - + single_digits - ) - - if not deterministic: - # 10-digit option (2): (1+2) + (1+2) + (2+2) digits - ten_digit_graph |= ( - single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - # 9-digit option (2): (1+2) + (1+2) + (1+2) digits - nine_digit_graph |= ( - single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + single_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + single_digits - + insert_space - + double_digits - ) - - # 8-digit option (2): (2+2) + (2+2) digits - eight_digit_graph |= ( - double_digits - + insert_space - + double_digits - + insert_space - + pynutil.delete("-") - + double_digits - + insert_space - + double_digits - ) - - number_part = pynini.union(ten_digit_graph, nine_digit_graph, eight_digit_graph) - number_part @= pynini.cdrewrite(pynini.cross(ones, "uno"), "", "", NEMO_SIGMA) - - number_part = pynutil.insert("number_part: \"") + number_part + pynutil.insert("\"") - - graph = number_part - final_graph = self.add_tokens(graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/time.py b/nemo_text_processing/text_normalization/es/taggers/time.py deleted file mode 100644 index 06c9fd452ce3..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/time.py +++ /dev/null @@ -1,208 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_SIGMA, - GraphFst, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -time_zone_graph = pynini.string_file(get_abs_path("data/time/time_zone.tsv")) -suffix = pynini.string_file(get_abs_path("data/time/time_suffix.tsv")) - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time, e.g. - "02:15 est" -> time { hours: "dos" minutes: "quince" zone: "e s t"} - "2 h" -> time { hours: "dos" } - "9 h" -> time { hours: "nueve" } - "02:15:10 h" -> time { hours: "dos" minutes: "quince" seconds: "diez"} - - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = True): - super().__init__(name="time", kind="classify", deterministic=deterministic) - - delete_time_delimiter = pynutil.delete(pynini.union(".", ":")) - - one = pynini.string_map([("un", "una"), ("ún", "una")]) - change_one = pynini.cdrewrite(one, "", "", NEMO_SIGMA) - cardinal_graph = cardinal.graph @ change_one - - day_suffix = pynutil.insert("suffix: \"") + suffix + pynutil.insert("\"") - day_suffix = delete_space + insert_space + day_suffix - - delete_hora_suffix = delete_space + insert_space + pynutil.delete("h") - delete_minute_suffix = delete_space + insert_space + pynutil.delete("min") - delete_second_suffix = delete_space + insert_space + pynutil.delete("s") - - labels_hour_24 = [ - str(x) for x in range(0, 25) - ] # Can see both systems. Twelve hour requires am/pm for ambiguity resolution - labels_hour_12 = [str(x) for x in range(1, 13)] - labels_minute_single = [str(x) for x in range(1, 10)] - labels_minute_double = [str(x) for x in range(10, 60)] - - delete_leading_zero_to_double_digit = ( - pynini.closure(pynutil.delete("0") | (NEMO_DIGIT - "0"), 0, 1) + NEMO_DIGIT - ) - - graph_24 = ( - pynini.closure(NEMO_DIGIT, 1, 2) @ delete_leading_zero_to_double_digit @ pynini.union(*labels_hour_24) - ) - graph_12 = ( - pynini.closure(NEMO_DIGIT, 1, 2) @ delete_leading_zero_to_double_digit @ pynini.union(*labels_hour_12) - ) - - graph_hour_24 = graph_24 @ cardinal_graph - graph_hour_12 = graph_12 @ cardinal_graph - - graph_minute_single = delete_leading_zero_to_double_digit @ pynini.union(*labels_minute_single) - graph_minute_double = pynini.union(*labels_minute_double) - - graph_minute = pynini.union(graph_minute_single, graph_minute_double) @ cardinal_graph - - final_graph_hour_only_24 = ( - pynutil.insert("hours: \"") + graph_hour_24 + pynutil.insert("\"") + delete_hora_suffix - ) - final_graph_hour_only_12 = pynutil.insert("hours: \"") + graph_hour_12 + pynutil.insert("\"") + day_suffix - - final_graph_hour_24 = pynutil.insert("hours: \"") + graph_hour_24 + pynutil.insert("\"") - final_graph_hour_12 = pynutil.insert("hours: \"") + graph_hour_12 + pynutil.insert("\"") - - final_graph_minute = pynutil.insert("minutes: \"") + graph_minute + pynutil.insert("\"") - final_graph_second = pynutil.insert("seconds: \"") + graph_minute + pynutil.insert("\"") - final_time_zone_optional = pynini.closure( - delete_space + insert_space + pynutil.insert("zone: \"") + time_zone_graph + pynutil.insert("\""), 0, 1, - ) - - # 02.30 h - graph_hm = ( - final_graph_hour_24 - + delete_time_delimiter - + (pynutil.delete("00") | (insert_space + final_graph_minute)) - + pynini.closure( - delete_time_delimiter + (pynini.cross("00", " seconds: \"0\"") | (insert_space + final_graph_second)), - 0, - 1, - ) # For seconds 2.30.35 h - + pynini.closure(delete_hora_suffix, 0, 1) # 2.30 is valid if unambiguous - + final_time_zone_optional - ) - - # 2 h 30 min - graph_hm |= ( - final_graph_hour_24 - + delete_hora_suffix - + delete_space - + (pynutil.delete("00") | (insert_space + final_graph_minute)) - + delete_minute_suffix - + pynini.closure( - delete_space - + (pynini.cross("00", " seconds: \"0\"") | (insert_space + final_graph_second)) - + delete_second_suffix, - 0, - 1, - ) # For seconds - + final_time_zone_optional - ) - - # 2.30 a. m. (Only for 12 hour clock) - graph_hm |= ( - final_graph_hour_12 - + delete_time_delimiter - + (pynutil.delete("00") | (insert_space + final_graph_minute)) - + pynini.closure( - delete_time_delimiter + (pynini.cross("00", " seconds: \"0\"") | (insert_space + final_graph_second)), - 0, - 1, - ) # For seconds 2.30.35 a. m. - + day_suffix - + final_time_zone_optional - ) - - graph_h = ( - pynini.union(final_graph_hour_only_24, final_graph_hour_only_12) + final_time_zone_optional - ) # Should always have a time indicator, else we'll pass to cardinals - - if not deterministic: - # This includes alternate vocalization (hour menos min, min para hour), here we shift the times and indicate a `style` tag - hour_shift_24 = pynini.invert(pynini.string_file(get_abs_path("data/time/hour_to_24.tsv"))) - hour_shift_12 = pynini.invert(pynini.string_file(get_abs_path("data/time/hour_to_12.tsv"))) - minute_shift = pynini.string_file(get_abs_path("data/time/minute_to.tsv")) - - graph_hour_to_24 = graph_24 @ hour_shift_24 @ cardinal_graph - graph_hour_to_12 = graph_12 @ hour_shift_12 @ cardinal_graph - - graph_minute_to = pynini.union(graph_minute_single, graph_minute_double) @ minute_shift @ cardinal_graph - - final_graph_hour_to_24 = pynutil.insert("hours: \"") + graph_hour_to_24 + pynutil.insert("\"") - final_graph_hour_to_12 = pynutil.insert("hours: \"") + graph_hour_to_12 + pynutil.insert("\"") - - final_graph_minute_to = pynutil.insert("minutes: \"") + graph_minute_to + pynutil.insert("\"") - - graph_menos = pynutil.insert(" style: \"1\"") - graph_para = pynutil.insert(" style: \"2\"") - - final_graph_style = graph_menos | graph_para - - # 02.30 h (omitting seconds since a bit awkward) - graph_hm |= ( - final_graph_hour_to_24 - + delete_time_delimiter - + insert_space - + final_graph_minute_to - + pynini.closure(delete_hora_suffix, 0, 1) # 2.30 is valid if unambiguous - + final_time_zone_optional - + final_graph_style - ) - - # 2 h 30 min - graph_hm |= ( - final_graph_hour_to_24 - + delete_hora_suffix - + delete_space - + insert_space - + final_graph_minute_to - + delete_minute_suffix - + final_time_zone_optional - + final_graph_style - ) - - # 2.30 a. m. (Only for 12 hour clock) - graph_hm |= ( - final_graph_hour_to_12 - + delete_time_delimiter - + insert_space - + final_graph_minute_to - + day_suffix - + final_time_zone_optional - + final_graph_style - ) - - final_graph = graph_hm | graph_h - if deterministic: - final_graph = final_graph + pynutil.insert(" preserve_order: true") - final_graph = final_graph.optimize() - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/tokenize_and_classify.py b/nemo_text_processing/text_normalization/es/taggers/tokenize_and_classify.py deleted file mode 100644 index c754fd1935dc..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,150 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_WHITE_SPACE, - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.text_normalization.es.taggers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.es.taggers.date import DateFst -from nemo_text_processing.text_normalization.es.taggers.decimals import DecimalFst -from nemo_text_processing.text_normalization.es.taggers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.es.taggers.fraction import FractionFst -from nemo_text_processing.text_normalization.es.taggers.measure import MeasureFst -from nemo_text_processing.text_normalization.es.taggers.money import MoneyFst -from nemo_text_processing.text_normalization.es.taggers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.es.taggers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.es.taggers.time import TimeFst -from nemo_text_processing.text_normalization.es.taggers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.es.taggers.word import WordFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is - lower cased. For deployment, this grammar will be compiled and exported to OpenFst finite-state archive (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - """ - - def __init__( - self, - input_case: str, - deterministic: bool = False, - cache_dir: str = None, - overwrite_cache: bool = False, - whitelist: str = None, - ): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - whitelist_file = os.path.basename(whitelist) if whitelist else "" - far_file = os.path.join( - cache_dir, f"_{input_case}_es_tn_{deterministic}_deterministic{whitelist_file}.far" - ) - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars. This might take some time...") - - self.cardinal = CardinalFst(deterministic=deterministic) - cardinal_graph = self.cardinal.fst - - self.ordinal = OrdinalFst(cardinal=self.cardinal, deterministic=deterministic) - ordinal_graph = self.ordinal.fst - - self.decimal = DecimalFst(cardinal=self.cardinal, deterministic=deterministic) - decimal_graph = self.decimal.fst - - self.fraction = FractionFst(cardinal=self.cardinal, ordinal=self.ordinal, deterministic=deterministic) - fraction_graph = self.fraction.fst - self.measure = MeasureFst( - cardinal=self.cardinal, decimal=self.decimal, fraction=self.fraction, deterministic=deterministic - ) - measure_graph = self.measure.fst - self.date = DateFst(cardinal=self.cardinal, deterministic=deterministic) - date_graph = self.date.fst - word_graph = WordFst(deterministic=deterministic).fst - self.time = TimeFst(self.cardinal, deterministic=deterministic) - time_graph = self.time.fst - self.telephone = TelephoneFst(deterministic=deterministic) - telephone_graph = self.telephone.fst - self.electronic = ElectronicFst(deterministic=deterministic) - electronic_graph = self.electronic.fst - self.money = MoneyFst(cardinal=self.cardinal, decimal=self.decimal, deterministic=deterministic) - money_graph = self.money.fst - self.whitelist = WhiteListFst(input_case=input_case, deterministic=deterministic, input_file=whitelist) - whitelist_graph = self.whitelist.fst - punct_graph = PunctuationFst(deterministic=deterministic).fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.09) - | pynutil.add_weight(measure_graph, 1.08) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(fraction_graph, 1.09) - | pynutil.add_weight(date_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(decimal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 200) - ) - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=2.1) + pynutil.insert(" }") - punct = pynini.closure( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct), - 1, - ) - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure( - ( - pynini.compose(pynini.closure(NEMO_WHITE_SPACE, 1), delete_extra_space) - | (pynutil.insert(" ") + punct + pynutil.insert(" ")) - ) - + token_plus_punct - ) - - graph = delete_space + graph + delete_space - graph |= punct - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/es/taggers/whitelist.py b/nemo_text_processing/text_normalization/es/taggers/whitelist.py deleted file mode 100644 index 9f6c6d99b458..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/whitelist.py +++ /dev/null @@ -1,62 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, convert_space -from nemo_text_processing.text_normalization.es.utils import get_abs_path, load_labels -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelist, e.g. - "sr." -> tokens { name: "señor" } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - input_file: path to a file with whitelist replacements - """ - - def __init__(self, input_case: str, deterministic: bool = True, input_file: str = None): - super().__init__(name="whitelist", kind="classify", deterministic=deterministic) - - def _get_whitelist_graph(input_case, file): - whitelist = load_labels(file) - if input_case == "lower_cased": - whitelist = [[x[0].lower()] + x[1:] for x in whitelist] - graph = pynini.string_map(whitelist) - return graph - - graph = _get_whitelist_graph(input_case, get_abs_path("data/whitelist.tsv")) - if not deterministic and input_case != "lower_cased": - graph |= pynutil.add_weight( - _get_whitelist_graph("lower_cased", get_abs_path("data/whitelist.tsv")), weight=0.0001 - ) - - if input_file: - whitelist_provided = _get_whitelist_graph(input_case, input_file) - if not deterministic: - graph |= whitelist_provided - else: - graph = whitelist_provided - - if not deterministic: - units_graph = _get_whitelist_graph(input_case, file=get_abs_path("data/measures/measurements.tsv")) - graph |= units_graph - - self.graph = graph - self.final_graph = convert_space(self.graph).optimize() - self.fst = (pynutil.insert("name: \"") + self.final_graph + pynutil.insert("\"")).optimize() diff --git a/nemo_text_processing/text_normalization/es/taggers/word.py b/nemo_text_processing/text_normalization/es/taggers/word.py deleted file mode 100644 index 90ecbc99c041..000000000000 --- a/nemo_text_processing/text_normalization/es/taggers/word.py +++ /dev/null @@ -1,32 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying word. - e.g. dormir -> tokens { name: "dormir" } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="word", kind="classify") - word = pynutil.insert("name: \"") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert("\"") - self.fst = word.optimize() diff --git a/nemo_text_processing/text_normalization/es/utils.py b/nemo_text_processing/text_normalization/es/utils.py deleted file mode 100644 index 375bc1fb1f3e..000000000000 --- a/nemo_text_processing/text_normalization/es/utils.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import csv -import os - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + '/' + rel_path - - -def load_labels(abs_path): - """ - loads relative path file as dictionary - - Args: - abs_path: absolute path - - Returns dictionary of mappings - """ - with open(abs_path, encoding="utf-8") as label_tsv: - labels = list(csv.reader(label_tsv, delimiter="\t")) - return labels diff --git a/nemo_text_processing/text_normalization/es/verbalizers/__init__.py b/nemo_text_processing/text_normalization/es/verbalizers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/es/verbalizers/cardinal.py b/nemo_text_processing/text_normalization/es/verbalizers/cardinal.py deleted file mode 100644 index 1806d147785d..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/cardinal.py +++ /dev/null @@ -1,60 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from nemo_text_processing.text_normalization.es.graph_utils import ( - add_cardinal_apocope_fem, - shift_cardinal_gender, - strip_cardinal_apocope, -) -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinals - e.g. cardinal { integer: "dos" } -> "dos" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="cardinal", kind="verbalize", deterministic=deterministic) - optional_sign = pynini.closure(pynini.cross("negative: \"true\" ", "menos "), 0, 1) - self.optional_sign = optional_sign - - integer = pynini.closure(NEMO_NOT_QUOTE, 1) - self.integer = pynutil.delete(" \"") + integer + pynutil.delete("\"") - - integer = pynutil.delete("integer:") + self.integer - - graph_masc = optional_sign + integer - graph_fem = shift_cardinal_gender(graph_masc) - - self.graph_masc = pynini.optimize(graph_masc) - self.graph_fem = pynini.optimize(graph_fem) - - # Adding adjustment for fem gender (choice of gender will be random) - graph = graph_masc | graph_fem - - if not deterministic: - # For alternate renderings when apocope is omitted (i.e. cardinal stands alone) - graph |= strip_cardinal_apocope(graph_masc) - # "una" will drop to "un" in unique contexts - graph |= add_cardinal_apocope_fem(graph_fem) - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/date.py b/nemo_text_processing/text_normalization/es/verbalizers/date.py deleted file mode 100644 index c9f135ab6bd4..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/date.py +++ /dev/null @@ -1,79 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_preserve_order, -) -from nemo_text_processing.text_normalization.es.graph_utils import strip_cardinal_apocope -from nemo_text_processing.text_normalization.es.taggers.date import articles -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - date { day: "treinta y uno" month: "marzo" year: "dos mil" } -> "treinta y uno de marzo de dos mil" - date { day: "uno" month: "mayo" year: "del mil novecientos noventa" } -> "primero de mayo del mil novecientos noventa" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="date", kind="verbalize", deterministic=deterministic) - - day_cardinal = pynutil.delete("day: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - day = strip_cardinal_apocope(day_cardinal) - - primero = pynini.cdrewrite(pynini.cross("uno", "primero"), "[BOS]", "[EOS]", NEMO_SIGMA) - day = ( - (day @ primero) if deterministic else pynini.union(day, day @ primero) - ) # Primero for first day is traditional, but will vary depending on region - - month = pynutil.delete("month: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - year = ( - pynutil.delete("year: \"") - + articles - + NEMO_SPACE - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - # Insert preposition if wasn't originally with the year. This would mean a space was present - year = pynutil.add_weight(year, -0.001) - year |= ( - pynutil.delete("year: \"") - + pynutil.insert("de ") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - # day month year - graph_dmy = day + pynini.cross(NEMO_SPACE, " de ") + month + pynini.closure(pynini.accep(" ") + year, 0, 1) - - graph_mdy = month + NEMO_SPACE + day + pynini.closure(NEMO_SPACE + year, 0, 1) - if deterministic: - graph_mdy += pynutil.delete(" preserve_order: true") # Only accepts this if was explicitly passed - - self.graph = graph_dmy | graph_mdy - final_graph = self.graph + delete_preserve_order - - delete_tokens = self.delete_tokens(final_graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/decimals.py b/nemo_text_processing/text_normalization/es/verbalizers/decimals.py deleted file mode 100644 index 643c9a5dd865..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/decimals.py +++ /dev/null @@ -1,88 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - GraphFst, - delete_preserve_order, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es import LOCALIZATION -from nemo_text_processing.text_normalization.es.graph_utils import ( - add_cardinal_apocope_fem, - shift_cardinal_gender, - shift_number_gender, - strip_cardinal_apocope, -) -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal, e.g. - decimal { negative: "true" integer_part: "dos" fractional_part: "cuatro cero" quantity: "billones" } -> menos dos coma quatro cero billones - decimal { integer_part: "un" quantity: "billón" } -> un billón - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - - optional_sign = pynini.closure(pynini.cross("negative: \"true\"", "menos ") + delete_space, 0, 1) - integer = pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - fractional_default = ( - pynutil.delete("fractional_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) - - conjunction = pynutil.insert(" punto ") if LOCALIZATION == "am" else pynutil.insert(" coma ") - if not deterministic: - conjunction |= pynutil.insert(pynini.union(" con ", " y ")) - fractional_default |= strip_cardinal_apocope(fractional_default) - fractional = conjunction + fractional_default - - quantity = ( - delete_space - + insert_space - + pynutil.delete("quantity: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_quantity = pynini.closure(quantity, 0, 1) - - graph_masc = optional_sign + pynini.union( - (integer + quantity), (integer + delete_space + fractional + optional_quantity) - ) - - # Allowing permutation for fem gender, don't include quantity since "million","billion", etc.. are masculine - graph_fem = optional_sign + (shift_cardinal_gender(integer) + delete_space + shift_number_gender(fractional)) - if not deterministic: # "una" will drop to "un" in certain cases - graph_fem |= add_cardinal_apocope_fem(graph_fem) - - self.numbers_only_quantity = ( - optional_sign - + pynini.union((integer + quantity), (integer + delete_space + fractional + quantity)).optimize() - ) - - self.graph_masc = (graph_masc + delete_preserve_order).optimize() - self.graph_fem = (graph_fem + delete_preserve_order).optimize() - - graph = graph_masc | graph_fem - - graph += delete_preserve_order - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/electronic.py b/nemo_text_processing/text_normalization/es/verbalizers/electronic.py deleted file mode 100644 index 0c866c550d59..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/electronic.py +++ /dev/null @@ -1,77 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_preserve_order, - insert_space, -) -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -digit_no_zero = pynini.invert(pynini.string_file(get_abs_path("data/numbers/digit.tsv"))) -zero = pynini.invert(pynini.string_file(get_abs_path("data/numbers/zero.tsv"))) - -graph_symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")) -server_common = pynini.string_file(get_abs_path("data/electronic/server_name.tsv")) -domain_common = pynini.string_file(get_abs_path("data/electronic/domain.tsv")) - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. electronic { username: "abc" domain: "hotmail.com" } -> "a b c arroba hotmail punto com" - -> "a b c arroba h o t m a i l punto c o m" - -> "a b c arroba hotmail punto c o m" - -> "a b c at h o t m a i l punto com" - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="verbalize", deterministic=deterministic) - - graph_digit_no_zero = ( - digit_no_zero @ pynini.cdrewrite(pynini.cross("un", "uno"), "", "", NEMO_SIGMA).optimize() - ) - graph_digit = graph_digit_no_zero | zero - - def add_space_after_char(): - return pynini.closure(NEMO_NOT_QUOTE - pynini.accep(" ") + insert_space) + ( - NEMO_NOT_QUOTE - pynini.accep(" ") - ) - - verbalize_characters = pynini.cdrewrite(graph_symbols | graph_digit, "", "", NEMO_SIGMA) - - user_name = pynutil.delete("username: \"") + add_space_after_char() + pynutil.delete("\"") - user_name @= verbalize_characters - - convert_defaults = pynutil.add_weight(NEMO_NOT_QUOTE, weight=0.0001) | domain_common | server_common - domain = convert_defaults + pynini.closure(insert_space + convert_defaults) - domain @= verbalize_characters - - domain = pynutil.delete("domain: \"") + domain + pynutil.delete("\"") - protocol = ( - pynutil.delete("protocol: \"") - + add_space_after_char() @ pynini.cdrewrite(graph_symbols, "", "", NEMO_SIGMA) - + pynutil.delete("\"") - ) - self.graph = (pynini.closure(protocol + pynini.accep(" "), 0, 1) + domain) | ( - user_name + pynini.accep(" ") + pynutil.insert("arroba ") + domain - ) - delete_tokens = self.delete_tokens(self.graph + delete_preserve_order) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/fraction.py b/nemo_text_processing/text_normalization/es/verbalizers/fraction.py deleted file mode 100644 index de2cbb9741f1..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/fraction.py +++ /dev/null @@ -1,192 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_CHAR, - NEMO_NOT_QUOTE, - NEMO_NOT_SPACE, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es.graph_utils import ( - accents, - shift_cardinal_gender, - strip_cardinal_apocope, -) -from pynini.lib import pynutil - - -class FractionFst(GraphFst): - """ - Finite state transducer for verbalizing fraction - e.g. tokens { fraction { integer: "treinta y tres" numerator: "cuatro" denominator: "quinto" } } -> - treinta y tres y cuatro quintos - - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="fraction", kind="verbalize", deterministic=deterministic) - - # Derivational strings append 'avo' as a suffix. Adding space for processing aid - fraction_stem = pynutil.insert(" avo") - plural = pynutil.insert("s") - conjunction = pynutil.insert(" y ") - - integer = ( - pynutil.delete("integer_part: \"") - + strip_cardinal_apocope(pynini.closure(NEMO_NOT_QUOTE)) - + pynutil.delete("\"") - ) - - numerator_one = pynutil.delete("numerator: \"") + pynini.accep("un") + pynutil.delete("\" ") - numerator = ( - pynutil.delete("numerator: \"") - + pynini.difference(pynini.closure(NEMO_NOT_QUOTE), "un") - + pynutil.delete("\" ") - ) - - denominator_add_stem = pynutil.delete("denominator: \"") + ( - pynini.closure(NEMO_NOT_QUOTE) - + fraction_stem - + pynutil.delete("\" morphosyntactic_features: \"add_root\"") - ) - denominator_ordinal = pynutil.delete("denominator: \"") + ( - pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\" morphosyntactic_features: \"ordinal\"") - ) - denominator_cardinal = pynutil.delete("denominator: \"") + ( - pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\"") - ) - - denominator_singular = pynini.union(denominator_add_stem, denominator_ordinal) - if not deterministic: - # Occasional exceptions - denominator_singular |= denominator_add_stem @ pynini.string_map( - [("once avo", "undécimo"), ("doce avo", "duodécimo")] - ) - denominator_plural = denominator_singular + plural - - # Merging operations - merge = pynini.cdrewrite( - pynini.cross(" y ", "i"), "", "", NEMO_SIGMA - ) # The denominator must be a single word, with the conjunction "y" replaced by i - merge @= pynini.cdrewrite(delete_space, "", pynini.difference(NEMO_CHAR, "parte"), NEMO_SIGMA) - - # The merger can produce duplicate vowels. This is not allowed in orthography - delete_duplicates = pynini.string_map([("aa", "a"), ("oo", "o")]) # Removes vowels - delete_duplicates = pynini.cdrewrite(delete_duplicates, "", "", NEMO_SIGMA) - - remove_accents = pynini.cdrewrite( - accents, - pynini.union(NEMO_SPACE, pynini.accep("[BOS]")) + pynini.closure(NEMO_NOT_SPACE), - pynini.closure(NEMO_NOT_SPACE) + pynini.union("avo", "ava", "ésimo", "ésima"), - NEMO_SIGMA, - ) - merge_into_single_word = merge @ remove_accents @ delete_duplicates - - fraction_default = numerator + delete_space + insert_space + (denominator_plural @ merge_into_single_word) - - fraction_with_one = ( - numerator_one + delete_space + insert_space + (denominator_singular @ merge_into_single_word) - ) - - fraction_with_cardinal = strip_cardinal_apocope(numerator | numerator_one) - fraction_with_cardinal += ( - delete_space + pynutil.insert(" sobre ") + strip_cardinal_apocope(denominator_cardinal) - ) - - if not deterministic: - # There is an alternative rendering where ordinals act as adjectives for 'parte'. This requires use of the feminine - # Other rules will manage use of "un" at end, so just worry about endings - exceptions = pynini.string_map([("tercia", "tercera")]) - apply_exceptions = pynini.cdrewrite(exceptions, "", "", NEMO_SIGMA) - vowel_change = pynini.cdrewrite(pynini.cross("o", "a"), "", pynini.accep("[EOS]"), NEMO_SIGMA) - - denominator_singular_fem = shift_cardinal_gender(denominator_singular) @ vowel_change @ apply_exceptions - denominator_plural_fem = denominator_singular_fem + plural - - numerator_one_fem = shift_cardinal_gender(numerator_one) - numerator_fem = shift_cardinal_gender(numerator) - - fraction_with_cardinal |= ( - (numerator_one_fem | numerator_fem) - + delete_space - + pynutil.insert(" sobre ") - + shift_cardinal_gender(denominator_cardinal) - ) - - # Still need to manage stems - merge_stem = pynini.cdrewrite( - delete_space, "", pynini.union("avo", "ava", "avos", "avas"), NEMO_SIGMA - ) # For managing alternative spacing - merge_stem @= remove_accents @ delete_duplicates - - fraction_with_one_fem = numerator_one_fem + delete_space + insert_space - fraction_with_one_fem += pynini.union( - denominator_singular_fem @ merge_stem, denominator_singular_fem @ merge_into_single_word - ) # Both forms exists - fraction_with_one_fem += pynutil.insert(" parte") - fraction_with_one_fem @= pynini.cdrewrite( - pynini.cross("una media", "media"), "", "", NEMO_SIGMA - ) # "media" not "una media" - - fraction_default_fem = numerator_fem + delete_space + insert_space - fraction_default_fem += pynini.union( - denominator_plural_fem @ merge_stem, denominator_plural_fem @ merge_into_single_word - ) - fraction_default_fem += pynutil.insert(" partes") - - fraction_default |= ( - numerator + delete_space + insert_space + denominator_plural @ merge_stem - ) # Case of no merger - fraction_default |= fraction_default_fem - - fraction_with_one |= numerator_one + delete_space + insert_space + denominator_singular @ merge_stem - fraction_with_one |= fraction_with_one_fem - - fraction_with_one @= pynini.cdrewrite( - pynini.cross("un medio", "medio"), "", "", NEMO_SIGMA - ) # "medio" not "un medio" - - fraction = fraction_with_one | fraction_default | fraction_with_cardinal - graph_masc = pynini.closure(integer + delete_space + conjunction, 0, 1) + fraction - - # Manage cases of fem gender (only shows on integer except for "medio") - integer_fem = shift_cardinal_gender(integer) - fraction_default |= ( - shift_cardinal_gender(numerator) - + delete_space - + insert_space - + (denominator_plural @ pynini.cross("medios", "medias")) - ) - fraction_with_one |= ( - pynutil.delete(numerator_one) + delete_space + (denominator_singular @ pynini.cross("medio", "media")) - ) - - fraction_fem = fraction_with_one | fraction_default | fraction_with_cardinal - graph_fem = pynini.closure(integer_fem + delete_space + conjunction, 0, 1) + fraction_fem - - self.graph_masc = pynini.optimize(graph_masc) - self.graph_fem = pynini.optimize(graph_fem) - - self.graph = graph_masc | graph_fem - - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/measure.py b/nemo_text_processing/text_normalization/es/verbalizers/measure.py deleted file mode 100644 index b04dd5bf9fe3..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/measure.py +++ /dev/null @@ -1,108 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - NEMO_SPACE, - NEMO_WHITE_SPACE, - GraphFst, - delete_extra_space, - delete_preserve_order, -) -from nemo_text_processing.text_normalization.es.graph_utils import ones -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -unit_plural_fem = pynini.string_file(get_abs_path("data/measures/measurements_plural_fem.tsv")) -unit_plural_masc = pynini.string_file(get_abs_path("data/measures/measurements_plural_masc.tsv")) - -unit_singular_fem = pynini.project(unit_plural_fem, "input") -unit_singular_masc = pynini.project(unit_plural_masc, "input") - -unit_plural_fem = pynini.project(unit_plural_fem, "output") -unit_plural_masc = pynini.project(unit_plural_masc, "output") - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { cardinal { integer: "dos" units: "gramos" } } -> "dos gramos" - measure { decimal { integer_part: "dos" quantity: "millones" units: "gramos" } } -> "dos millones de gramos" - - Args: - decimal: DecimalFst - cardinal: CardinalFst - fraction: FractionFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, decimal: GraphFst, cardinal: GraphFst, fraction: GraphFst, deterministic: bool): - super().__init__(name="measure", kind="verbalize", deterministic=deterministic) - - graph_decimal_masc = decimal.delete_tokens(decimal.graph_masc) - graph_decimal_fem = decimal.delete_tokens(decimal.graph_fem) - graph_cardinal_masc = cardinal.delete_tokens(cardinal.graph_masc) - graph_cardinal_fem = cardinal.delete_tokens(cardinal.graph_fem) - graph_fraction_fem = fraction.delete_tokens(fraction.graph_fem) - graph_fraction_masc = fraction.delete_tokens(fraction.graph_masc) - - unit_masc = (unit_plural_masc | unit_singular_masc) + pynini.closure( - NEMO_WHITE_SPACE + "por" + pynini.closure(NEMO_NOT_QUOTE, 1), 0, 1 - ) - unit_masc |= "por" + pynini.closure(NEMO_NOT_QUOTE, 1) - unit_masc = pynutil.delete("units: \"") + (pynini.closure(NEMO_NOT_QUOTE) @ unit_masc) + pynutil.delete("\"") - - unit_fem = (unit_plural_fem | unit_singular_fem) + pynini.closure( - NEMO_WHITE_SPACE + "por" + pynini.closure(NEMO_NOT_QUOTE, 1), 0, 1 - ) - unit_fem = pynutil.delete("units: \"") + (pynini.closure(NEMO_NOT_QUOTE) @ unit_fem) + pynutil.delete("\"") - - graph_masc = (graph_cardinal_masc | graph_decimal_masc) + NEMO_WHITE_SPACE + unit_masc - graph_masc |= graph_fraction_masc + NEMO_WHITE_SPACE + pynutil.insert("de ") + unit_masc - graph_masc |= pynutil.add_weight( - graph_fraction_masc @ (NEMO_SIGMA + pynini.union("medio", "medios")) + NEMO_WHITE_SPACE + unit_masc, -0.001 - ) # "medio litro" not "medio de litro" - - graph_fem = (graph_cardinal_fem | graph_decimal_fem) + NEMO_WHITE_SPACE + unit_fem - graph_fem |= graph_fraction_fem + NEMO_WHITE_SPACE + pynutil.insert("de ") + unit_fem - graph_fem |= pynutil.add_weight( - graph_fraction_fem @ (NEMO_SIGMA + pynini.union("media", "medias")) + NEMO_WHITE_SPACE + unit_fem, -0.001 - ) - - graph = graph_masc | graph_fem - - graph = ( - pynini.cdrewrite( - pynutil.insert(" de"), "quantity: \"" + pynini.closure(NEMO_NOT_QUOTE, 1), "\"", NEMO_SIGMA - ) - @ graph - ) # billones de xyz - - graph @= pynini.cdrewrite(pynini.cross(ones, "uno"), "", NEMO_WHITE_SPACE + "por", NEMO_SIGMA) - - # To manage alphanumeric combonations ("a-8, 5x"), we let them use a weighted default path. - alpha_num_unit = pynutil.delete("units: \"") + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\"") - graph_alpha_num = pynini.union( - (graph_cardinal_masc | graph_decimal_masc) + NEMO_SPACE + alpha_num_unit, - alpha_num_unit + delete_extra_space + (graph_cardinal_masc | graph_decimal_masc), - ) - - graph |= pynutil.add_weight(graph_alpha_num, 0.01) - - graph += delete_preserve_order - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/money.py b/nemo_text_processing/text_normalization/es/verbalizers/money.py deleted file mode 100644 index d2ba9c707f78..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/money.py +++ /dev/null @@ -1,166 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - NEMO_SPACE, - GraphFst, - delete_preserve_order, -) -from nemo_text_processing.text_normalization.es.graph_utils import shift_cardinal_gender, strip_cardinal_apocope -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -fem = pynini.string_file((get_abs_path("data/money/currency_plural_fem.tsv"))) -masc = pynini.string_file((get_abs_path("data/money/currency_plural_masc.tsv"))) - -fem_singular = pynini.project(fem, "input") -masc_singular = pynini.project(masc, "input") - -fem_plural = pynini.project(fem, "output") -masc_plural = pynini.project(masc, "output") - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { currency_maj: "euro" integer_part: "un"} -> "un euro" - money { currency_maj: "euro" integer_part: "un" fractional_part: "cero cero un"} -> "uno coma cero cero uno euros" - money { integer_part: "un" currency_maj: "libra" fractional_part: "cuarenta" preserve_order: true} -> "una libra cuarenta" - money { integer_part: "un" currency_maj: "libra" fractional_part: "cuarenta" currency_min: "peniques" preserve_order: true} -> "una libra con cuarenta peniques" - money { fractional_part: "un" currency_min: "penique" preserve_order: true} -> "un penique" - - Args: - decimal: GraphFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="verbalize", deterministic=deterministic) - - maj_singular_masc = ( - pynutil.delete("currency_maj: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ masc_singular) - + pynutil.delete("\"") - ) - maj_singular_fem = ( - pynutil.delete("currency_maj: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ fem_singular) - + pynutil.delete("\"") - ) - - maj_plural_masc = ( - pynutil.delete("currency_maj: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ masc_plural) - + pynutil.delete("\"") - ) - maj_plural_fem = ( - pynutil.delete("currency_maj: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ fem_plural) - + pynutil.delete("\"") - ) - - maj_masc = maj_plural_masc | maj_singular_masc # Tagger kept quantity resolution stable - maj_fem = maj_plural_fem | maj_singular_fem - - min_singular_masc = ( - pynutil.delete("currency_min: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ masc_singular) - + pynutil.delete("\"") - ) - min_singular_fem = ( - pynutil.delete("currency_min: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ fem_singular) - + pynutil.delete("\"") - ) - - min_plural_masc = ( - pynutil.delete("currency_min: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ masc_plural) - + pynutil.delete("\"") - ) - min_plural_fem = ( - pynutil.delete("currency_min: \"") - + (pynini.closure(NEMO_NOT_QUOTE, 1) @ fem_plural) - + pynutil.delete("\"") - ) - - min_masc = min_plural_masc | min_singular_masc - min_fem = min_plural_fem | min_singular_fem - - fractional_part = ( - pynutil.delete("fractional_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - ) - - integer_part = pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - optional_add_and = pynini.closure(pynutil.insert(pynini.union("con ", "y ")), 0, 1) - - # *** currency_maj - graph_integer_masc = integer_part + NEMO_SPACE + maj_masc - graph_integer_fem = shift_cardinal_gender(integer_part) + NEMO_SPACE + maj_fem - - graph_integer = graph_integer_fem | graph_integer_masc - - # *** currency_maj + (***) | ((con) *** current_min) - graph_integer_with_minor_masc = ( - graph_integer_masc - + NEMO_SPACE - + pynini.union( - optional_add_and + strip_cardinal_apocope(fractional_part), - (optional_add_and + fractional_part + NEMO_SPACE + min_masc), - (optional_add_and + shift_cardinal_gender(fractional_part) + NEMO_SPACE + min_fem), - ) # Could be minor currency that is different gender - + delete_preserve_order - ) - - graph_integer_with_minor_fem = ( - graph_integer_fem - + NEMO_SPACE - + pynini.union( - optional_add_and + shift_cardinal_gender(fractional_part), - (optional_add_and + fractional_part + NEMO_SPACE + min_masc), - (optional_add_and + shift_cardinal_gender(fractional_part) + NEMO_SPACE + min_fem), - ) # Could be minor currency that is different gender - + delete_preserve_order - ) - - graph_integer_with_minor = graph_integer_with_minor_fem | graph_integer_with_minor_masc - - ## *** coma *** currency_maj - graph_decimal_masc = decimal.graph_masc + NEMO_SPACE + maj_masc - - graph_decimal_fem = decimal.graph_fem - graph_decimal_fem |= decimal.numbers_only_quantity # can still have "x billions" with fem currency - graph_decimal_fem += NEMO_SPACE + maj_fem - - graph_decimal = graph_decimal_fem | graph_decimal_masc - graph_decimal = ( - pynini.cdrewrite( - pynutil.insert(" de"), "quantity: \"" + pynini.closure(NEMO_NOT_QUOTE, 1), "\"", NEMO_SIGMA - ) - @ graph_decimal - ) # formally it's millones/billones de *** - - # *** current_min - graph_minor_masc = fractional_part + NEMO_SPACE + min_masc + delete_preserve_order - graph_minor_fem = shift_cardinal_gender(fractional_part) + NEMO_SPACE + min_fem + delete_preserve_order - - graph_minor = graph_minor_fem | graph_minor_masc - - graph = graph_integer | graph_integer_with_minor | graph_decimal | graph_minor - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/ordinal.py b/nemo_text_processing/text_normalization/es/verbalizers/ordinal.py deleted file mode 100644 index 009cdf34352a..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/ordinal.py +++ /dev/null @@ -1,69 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, NEMO_SIGMA, NEMO_SPACE, GraphFst -from nemo_text_processing.text_normalization.es.graph_utils import shift_number_gender -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing ordinals - e.g. ordinal { integer: "tercer" } } -> "tercero" - -> "tercera" - -> "tercer" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="ordinal", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete("integer: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - - # masculne gender we leave as is - graph_masc = graph + pynutil.delete(" morphosyntactic_features: \"gender_masc") - - # shift gender - graph_fem_ending = graph @ pynini.cdrewrite( - pynini.cross("o", "a"), "", NEMO_SPACE | pynini.accep("[EOS]"), NEMO_SIGMA - ) - graph_fem = shift_number_gender(graph_fem_ending) + pynutil.delete(" morphosyntactic_features: \"gender_fem") - - # Apocope just changes tercero and primero. May occur if someone wrote 11.er (uncommon) - graph_apocope = ( - pynini.cross("tercero", "tercer") - | pynini.cross("primero", "primer") - | pynini.cross("undécimo", "decimoprimer") - ) # In case someone wrote 11.er with deterministic - graph_apocope = (graph @ pynini.cdrewrite(graph_apocope, "", "", NEMO_SIGMA)) + pynutil.delete( - " morphosyntactic_features: \"apocope" - ) - - graph = graph_apocope | graph_masc | graph_fem - - if not deterministic: - # Plural graph - graph_plural = pynini.cdrewrite( - pynutil.insert("s"), pynini.union("o", "a"), NEMO_SPACE | pynini.accep("[EOS]"), NEMO_SIGMA - ) - - graph |= (graph @ graph_plural) + pynutil.delete("/plural") - - self.graph = graph + pynutil.delete("\"") - - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/telephone.py b/nemo_text_processing/text_normalization/es/verbalizers/telephone.py deleted file mode 100644 index 8e8932ea2cc2..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/telephone.py +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { number_part: "uno dos tres uno dos tres cinco seis siete ocho" } - -> uno dos tres uno dos tres cinco seis siete ocho - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="telephone", kind="verbalize") - - number_part = pynutil.delete("number_part: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(number_part) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/time.py b/nemo_text_processing/text_normalization/es/verbalizers/time.py deleted file mode 100644 index 23fa1d180d61..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/time.py +++ /dev/null @@ -1,256 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_preserve_order, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.es.utils import get_abs_path -from pynini.lib import pynutil - -alt_minutes = pynini.string_file(get_abs_path("data/time/alt_minutes.tsv")) - -morning_times = pynini.string_file(get_abs_path("data/time/morning_times.tsv")) -afternoon_times = pynini.string_file(get_abs_path("data/time/afternoon_times.tsv")) -evening_times = pynini.string_file(get_abs_path("data/time/evening_times.tsv")) - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing time, e.g. - time { hours: "doce" minutes: "media" suffix: "a m" } -> doce y media de la noche - time { hours: "doce" } -> twelve o'clock - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="time", kind="verbalize", deterministic=deterministic) - - change_minutes = pynini.cdrewrite(alt_minutes, pynini.accep("[BOS]"), pynini.accep("[EOS]"), NEMO_SIGMA) - - morning_phrases = pynini.cross("am", "de la mañana") - afternoon_phrases = pynini.cross("pm", "de la tarde") - evening_phrases = pynini.cross("pm", "de la noche") - - # For the 12's - mid_times = pynini.accep("doce") - mid_phrases = ( - pynini.string_map([("pm", "del mediodía"), ("am", "de la noche")]) - if deterministic - else pynini.string_map( - [ - ("pm", "de la mañana"), - ("pm", "del día"), - ("pm", "del mediodía"), - ("am", "de la noche"), - ("am", "de la medianoche"), - ] - ) - ) - - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - minute = ( - pynutil.delete("minutes:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - minute = (minute @ change_minutes) if deterministic else pynini.union(minute, minute @ change_minutes) - - suffix = ( - pynutil.delete("suffix:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - zone = ( - pynutil.delete("zone:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - optional_zone = pynini.closure(delete_space + insert_space + zone, 0, 1) - second = ( - pynutil.delete("seconds:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - graph_hms = ( - hour - + pynutil.insert(" horas ") - + delete_space - + minute - + pynutil.insert(" minutos y ") - + delete_space - + second - + pynutil.insert(" segundos") - ) - - graph_hm = hour + delete_space + pynutil.insert(" y ") + minute - graph_hm |= pynini.union( - (hour @ morning_times) - + delete_space - + pynutil.insert(" y ") - + minute - + delete_space - + insert_space - + (suffix @ morning_phrases), - (hour @ afternoon_times) - + delete_space - + pynutil.insert(" y ") - + minute - + delete_space - + insert_space - + (suffix @ afternoon_phrases), - (hour @ evening_times) - + delete_space - + pynutil.insert(" y ") - + minute - + delete_space - + insert_space - + (suffix @ evening_phrases), - (hour @ mid_times) - + delete_space - + pynutil.insert(" y ") - + minute - + delete_space - + insert_space - + (suffix @ mid_phrases), - ) - - graph_h = pynini.union( - hour, - (hour @ morning_times) + delete_space + insert_space + (suffix @ morning_phrases), - (hour @ afternoon_times) + delete_space + insert_space + (suffix @ afternoon_phrases), - (hour @ evening_times) + delete_space + insert_space + (suffix @ evening_phrases), - (hour @ mid_times) + delete_space + insert_space + (suffix @ mid_phrases), - ) - - graph = (graph_hms | graph_hm | graph_h) + optional_zone - - if not deterministic: - graph_style_1 = pynutil.delete(" style: \"1\"") - graph_style_2 = pynutil.delete(" style: \"2\"") - - graph_menos = hour + delete_space + pynutil.insert(" menos ") + minute + graph_style_1 - graph_menos |= ( - (hour @ morning_times) - + delete_space - + pynutil.insert(" menos ") - + minute - + delete_space - + insert_space - + (suffix @ morning_phrases) - + graph_style_1 - ) - graph_menos |= ( - (hour @ afternoon_times) - + delete_space - + pynutil.insert(" menos ") - + minute - + delete_space - + insert_space - + (suffix @ afternoon_phrases) - + graph_style_1 - ) - graph_menos |= ( - (hour @ evening_times) - + delete_space - + pynutil.insert(" menos ") - + minute - + delete_space - + insert_space - + (suffix @ evening_phrases) - + graph_style_1 - ) - graph_menos |= ( - (hour @ mid_times) - + delete_space - + pynutil.insert(" menos ") - + minute - + delete_space - + insert_space - + (suffix @ mid_phrases) - + graph_style_1 - ) - graph_menos += optional_zone - - graph_para = minute + pynutil.insert(" para las ") + delete_space + hour + graph_style_2 - graph_para |= ( - minute - + pynutil.insert(" para las ") - + delete_space - + (hour @ morning_times) - + delete_space - + insert_space - + (suffix @ morning_phrases) - + graph_style_2 - ) - graph_para |= ( - minute - + pynutil.insert(" para las ") - + delete_space - + (hour @ afternoon_times) - + delete_space - + insert_space - + (suffix @ afternoon_phrases) - + graph_style_2 - ) - graph_para |= ( - minute - + pynutil.insert(" para las ") - + delete_space - + (hour @ evening_times) - + delete_space - + insert_space - + (suffix @ evening_phrases) - + graph_style_2 - ) - graph_para |= ( - minute - + pynutil.insert(" para las ") - + delete_space - + (hour @ mid_times) - + delete_space - + insert_space - + (suffix @ mid_phrases) - + graph_style_2 - ) - graph_para += optional_zone - graph_para @= pynini.cdrewrite( - pynini.cross(" las ", " la "), "para", "una", NEMO_SIGMA - ) # Need agreement with one - - graph |= graph_menos | graph_para - delete_tokens = self.delete_tokens(graph + delete_preserve_order) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/es/verbalizers/verbalize.py b/nemo_text_processing/text_normalization/es/verbalizers/verbalize.py deleted file mode 100644 index 28810d67f897..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/verbalize.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.en.verbalizers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.es.verbalizers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.es.verbalizers.date import DateFst -from nemo_text_processing.text_normalization.es.verbalizers.decimals import DecimalFst -from nemo_text_processing.text_normalization.es.verbalizers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.es.verbalizers.fraction import FractionFst -from nemo_text_processing.text_normalization.es.verbalizers.measure import MeasureFst -from nemo_text_processing.text_normalization.es.verbalizers.money import MoneyFst -from nemo_text_processing.text_normalization.es.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.es.verbalizers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.es.verbalizers.time import TimeFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="verbalize", kind="verbalize", deterministic=deterministic) - cardinal = CardinalFst(deterministic=deterministic) - cardinal_graph = cardinal.fst - ordinal = OrdinalFst(deterministic=deterministic) - ordinal_graph = ordinal.fst - decimal = DecimalFst(deterministic=deterministic) - decimal_graph = decimal.fst - fraction = FractionFst(deterministic=deterministic) - fraction_graph = fraction.fst - date = DateFst(deterministic=deterministic) - date_graph = date.fst - measure = MeasureFst(cardinal=cardinal, decimal=decimal, fraction=fraction, deterministic=deterministic) - measure_graph = measure.fst - electronic = ElectronicFst(deterministic=deterministic) - electronic_graph = electronic.fst - whitelist_graph = WhiteListFst(deterministic=deterministic).fst - money_graph = MoneyFst(decimal=decimal, deterministic=deterministic).fst - telephone_graph = TelephoneFst(deterministic=deterministic).fst - time_graph = TimeFst(deterministic=deterministic).fst - - graph = ( - cardinal_graph - | measure_graph - | decimal_graph - | ordinal_graph - | date_graph - | electronic_graph - | money_graph - | fraction_graph - | whitelist_graph - | telephone_graph - | time_graph - ) - self.fst = graph diff --git a/nemo_text_processing/text_normalization/es/verbalizers/verbalize_final.py b/nemo_text_processing/text_normalization/es/verbalizers/verbalize_final.py deleted file mode 100644 index fe35f769c3d7..000000000000 --- a/nemo_text_processing/text_normalization/es/verbalizers/verbalize_final.py +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.verbalizers.word import WordFst -from nemo_text_processing.text_normalization.es.verbalizers.verbalize import VerbalizeFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, deterministic: bool = True, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="verbalize_final", kind="verbalize", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, f"es_tn_{deterministic}_deterministic_verbalizer.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["verbalize"] - logging.info(f'VerbalizeFinalFst graph was restored from {far_file}.') - else: - - verbalize = VerbalizeFst(deterministic=deterministic).fst - word = WordFst(deterministic=deterministic).fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - - self.fst = graph.optimize() - if far_file: - generator_main(far_file, {"verbalize": self.fst}) - logging.info(f"VerbalizeFinalFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/normalize.py b/nemo_text_processing/text_normalization/normalize.py deleted file mode 100644 index e1a57e01d5bf..000000000000 --- a/nemo_text_processing/text_normalization/normalize.py +++ /dev/null @@ -1,543 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import itertools -import os -import re -from argparse import ArgumentParser -from collections import OrderedDict -from math import factorial -from time import perf_counter -from typing import Dict, List, Union - -import pynini -import regex -from joblib import Parallel, delayed -from nemo_text_processing.text_normalization.data_loader_utils import ( - load_file, - post_process_punct, - pre_process, - write_file, -) -from nemo_text_processing.text_normalization.token_parser import PRESERVE_ORDER_KEY, TokenParser -from pynini.lib.rewrite import top_rewrite -from tqdm import tqdm - -try: - from nemo.collections.common.tokenizers.moses_tokenizers import MosesProcessor - - NLP_AVAILABLE = True -except (ModuleNotFoundError, ImportError) as e: - NLP_AVAILABLE = False - -SPACE_DUP = re.compile(' {2,}') - - -class Normalizer: - """ - Normalizer class that converts text from written to spoken form. - Useful for TTS preprocessing. - - Args: - input_case: expected input capitalization - lang: language specifying the TN rules, by default: English - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - post_process: WFST-based post-processing, e.g. to remove extra spaces added during TN. - Note: punct_post_process flag in normalize() supports all languages. - """ - - def __init__( - self, - input_case: str, - lang: str = 'en', - deterministic: bool = True, - cache_dir: str = None, - overwrite_cache: bool = False, - whitelist: str = None, - lm: bool = False, - post_process: bool = True, - ): - assert input_case in ["lower_cased", "cased"] - - self.post_processor = None - - if lang == "en": - from nemo_text_processing.text_normalization.en.verbalizers.post_processing import PostProcessingFst - from nemo_text_processing.text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst - - if post_process: - self.post_processor = PostProcessingFst(cache_dir=cache_dir, overwrite_cache=overwrite_cache) - - if deterministic: - from nemo_text_processing.text_normalization.en.taggers.tokenize_and_classify import ClassifyFst - else: - if lm: - from nemo_text_processing.text_normalization.en.taggers.tokenize_and_classify_lm import ClassifyFst - else: - from nemo_text_processing.text_normalization.en.taggers.tokenize_and_classify_with_audio import ( - ClassifyFst, - ) - elif lang == 'ru': - # Ru TN only support non-deterministic cases and produces multiple normalization options - # use normalize_with_audio.py - from nemo_text_processing.text_normalization.ru.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.text_normalization.ru.verbalizers.verbalize_final import VerbalizeFinalFst - elif lang == 'de': - from nemo_text_processing.text_normalization.de.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.text_normalization.de.verbalizers.verbalize_final import VerbalizeFinalFst - elif lang == 'es': - from nemo_text_processing.text_normalization.es.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.text_normalization.es.verbalizers.verbalize_final import VerbalizeFinalFst - elif lang == 'zh': - from nemo_text_processing.text_normalization.zh.taggers.tokenize_and_classify import ClassifyFst - from nemo_text_processing.text_normalization.zh.verbalizers.verbalize_final import VerbalizeFinalFst - else: - raise NotImplementedError(f"Language {lang} has not been supported yet.") - - self.tagger = ClassifyFst( - input_case=input_case, - deterministic=deterministic, - cache_dir=cache_dir, - overwrite_cache=overwrite_cache, - whitelist=whitelist, - ) - - self.verbalizer = VerbalizeFinalFst( - deterministic=deterministic, cache_dir=cache_dir, overwrite_cache=overwrite_cache - ) - - self.parser = TokenParser() - self.lang = lang - - if NLP_AVAILABLE: - self.processor = MosesProcessor(lang_id=lang) - else: - self.processor = None - print("NeMo NLP is not available. Moses de-tokenization will be skipped.") - - def normalize_list( - self, - texts: List[str], - verbose: bool = False, - punct_pre_process: bool = False, - punct_post_process: bool = False, - batch_size: int = 1, - n_jobs: int = 1, - ): - """ - NeMo text normalizer - - Args: - texts: list of input strings - verbose: whether to print intermediate meta information - punct_pre_process: whether to do punctuation pre-processing - punct_post_process: whether to do punctuation post-processing - n_jobs: the maximum number of concurrently running jobs. If -1 all CPUs are used. If 1 is given, - no parallel computing code is used at all, which is useful for debugging. For n_jobs below -1, - (n_cpus + 1 + n_jobs) are used. Thus for n_jobs = -2, all CPUs but one are used. - batch_size: Number of examples for each process - - Returns converted list input strings - """ - - # to save intermediate results to a file - batch = min(len(texts), batch_size) - - try: - normalized_texts = Parallel(n_jobs=n_jobs)( - delayed(self.process_batch)(texts[i : i + batch], verbose, punct_pre_process, punct_post_process) - for i in range(0, len(texts), batch) - ) - except BaseException as e: - raise e - - normalized_texts = list(itertools.chain(*normalized_texts)) - return normalized_texts - - def process_batch(self, batch, verbose, punct_pre_process, punct_post_process): - """ - Normalizes batch of text sequences - Args: - batch: list of texts - verbose: whether to print intermediate meta information - punct_pre_process: whether to do punctuation pre-processing - punct_post_process: whether to do punctuation post-processing - """ - normalized_lines = [ - self.normalize( - text, verbose=verbose, punct_pre_process=punct_pre_process, punct_post_process=punct_post_process - ) - for text in tqdm(batch) - ] - return normalized_lines - - def _estimate_number_of_permutations_in_nested_dict( - self, token_group: Dict[str, Union[OrderedDict, str, bool]] - ) -> int: - num_perms = 1 - for k, inner in token_group.items(): - if isinstance(inner, dict): - num_perms *= self._estimate_number_of_permutations_in_nested_dict(inner) - num_perms *= factorial(len(token_group)) - return num_perms - - def _split_tokens_to_reduce_number_of_permutations( - self, tokens: List[dict], max_number_of_permutations_per_split: int = 729 - ) -> List[List[dict]]: - """ - Splits a sequence of tokens in a smaller sequences of tokens in a way that maximum number of composite - tokens permutations does not exceed ``max_number_of_permutations_per_split``. - - For example, - - .. code-block:: python - tokens = [ - {"tokens": {"date": {"year": "twenty eighteen", "month": "december", "day": "thirty one"}}}, - {"tokens": {"date": {"year": "twenty eighteen", "month": "january", "day": "eight"}}}, - ] - split = normalizer._split_tokens_to_reduce_number_of_permutations( - tokens, max_number_of_permutations_per_split=6 - ) - assert split == [ - [{"tokens": {"date": {"year": "twenty eighteen", "month": "december", "day": "thirty one"}}}], - [{"tokens": {"date": {"year": "twenty eighteen", "month": "january", "day": "eight"}}}], - ] - - Date tokens contain 3 items each which gives 6 permutations for every date. Since there are 2 dates, total - number of permutations would be ``6 * 6 == 36``. Parameter ``max_number_of_permutations_per_split`` equals 6, - so input sequence of tokens is split into 2 smaller sequences. - - Args: - tokens (:obj:`List[dict]`): a list of dictionaries, possibly nested. - max_number_of_permutations_per_split (:obj:`int`, `optional`, defaults to :obj:`243`): a maximum number - of permutations which can be generated from input sequence of tokens. - - Returns: - :obj:`List[List[dict]]`: a list of smaller sequences of tokens resulting from ``tokens`` split. - """ - splits = [] - prev_end_of_split = 0 - current_number_of_permutations = 1 - for i, token_group in enumerate(tokens): - n = self._estimate_number_of_permutations_in_nested_dict(token_group) - if n * current_number_of_permutations > max_number_of_permutations_per_split: - splits.append(tokens[prev_end_of_split:i]) - prev_end_of_split = i - current_number_of_permutations = 1 - if n > max_number_of_permutations_per_split: - raise ValueError( - f"Could not split token list with respect to condition that every split can generate number of " - f"permutations less or equal to " - f"`max_number_of_permutations_per_split={max_number_of_permutations_per_split}`. " - f"There is an unsplittable token group that generates more than " - f"{max_number_of_permutations_per_split} permutations. Try to increase " - f"`max_number_of_permutations_per_split` parameter." - ) - current_number_of_permutations *= n - splits.append(tokens[prev_end_of_split:]) - assert sum([len(s) for s in splits]) == len(tokens) - return splits - - def normalize( - self, text: str, verbose: bool = False, punct_pre_process: bool = False, punct_post_process: bool = False - ) -> str: - """ - Main function. Normalizes tokens from written to spoken form - e.g. 12 kg -> twelve kilograms - - Args: - text: string that may include semiotic classes - verbose: whether to print intermediate meta information - punct_pre_process: whether to perform punctuation pre-processing, for example, [25] -> [ 25 ] - punct_post_process: whether to normalize punctuation - - Returns: spoken form - """ - if len(text.split()) > 500: - print( - "WARNING! Your input is too long and could take a long time to normalize." - "Use split_text_into_sentences() to make the input shorter and then call normalize_list()." - ) - - original_text = text - if punct_pre_process: - text = pre_process(text) - text = text.strip() - if not text: - if verbose: - print(text) - return text - text = pynini.escape(text) - tagged_lattice = self.find_tags(text) - tagged_text = Normalizer.select_tag(tagged_lattice) - if verbose: - print(tagged_text) - self.parser(tagged_text) - tokens = self.parser.parse() - split_tokens = self._split_tokens_to_reduce_number_of_permutations(tokens) - output = "" - for s in split_tokens: - tags_reordered = self.generate_permutations(s) - verbalizer_lattice = None - for tagged_text in tags_reordered: - tagged_text = pynini.escape(tagged_text) - - verbalizer_lattice = self.find_verbalizer(tagged_text) - if verbalizer_lattice.num_states() != 0: - break - if verbalizer_lattice is None: - raise ValueError(f"No permutations were generated from tokens {s}") - output += ' ' + Normalizer.select_verbalizer(verbalizer_lattice) - output = SPACE_DUP.sub(' ', output[1:]) - - if self.lang == "en" and hasattr(self, 'post_processor'): - output = self.post_process(output) - - if punct_post_process: - # do post-processing based on Moses detokenizer - if self.processor: - output = self.processor.moses_detokenizer.detokenize([output], unescape=False) - output = post_process_punct(input=original_text, normalized_text=output) - else: - print("NEMO_NLP collection is not available: skipping punctuation post_processing") - - return output - - def split_text_into_sentences(self, text: str) -> List[str]: - """ - Split text into sentences. - - Args: - text: text - - Returns list of sentences - """ - lower_case_unicode = '' - upper_case_unicode = '' - if self.lang == "ru": - lower_case_unicode = '\u0430-\u04FF' - upper_case_unicode = '\u0410-\u042F' - - # Read and split transcript by utterance (roughly, sentences) - split_pattern = rf"(? List[str]: - """ - Creates reorderings of dictionary elements and serializes as strings - - Args: - d: (nested) dictionary of key value pairs - - Return permutations of different string serializations of key value pairs - """ - l = [] - if PRESERVE_ORDER_KEY in d.keys(): - d_permutations = [d.items()] - else: - d_permutations = itertools.permutations(d.items()) - for perm in d_permutations: - subl = [""] - for k, v in perm: - if isinstance(v, str): - subl = ["".join(x) for x in itertools.product(subl, [f"{k}: \"{v}\" "])] - elif isinstance(v, OrderedDict): - rec = self._permute(v) - subl = ["".join(x) for x in itertools.product(subl, [f" {k} {{ "], rec, [f" }} "])] - elif isinstance(v, bool): - subl = ["".join(x) for x in itertools.product(subl, [f"{k}: true "])] - else: - raise ValueError() - l.extend(subl) - return l - - def generate_permutations(self, tokens: List[dict]): - """ - Generates permutations of string serializations of list of dictionaries - - Args: - tokens: list of dictionaries - - Returns string serialization of list of dictionaries - """ - - def _helper(prefix: str, token_list: List[dict], idx: int): - """ - Generates permutations of string serializations of given dictionary - - Args: - token_list: list of dictionaries - prefix: prefix string - idx: index of next dictionary - - Returns string serialization of dictionary - """ - if idx == len(token_list): - yield prefix - return - token_options = self._permute(token_list[idx]) - for token_option in token_options: - yield from _helper(prefix + token_option, token_list, idx + 1) - - return _helper("", tokens, 0) - - def find_tags(self, text: str) -> 'pynini.FstLike': - """ - Given text use tagger Fst to tag text - - Args: - text: sentence - - Returns: tagged lattice - """ - lattice = text @ self.tagger.fst - return lattice - - @staticmethod - def select_tag(lattice: 'pynini.FstLike') -> str: - """ - Given tagged lattice return shortest path - - Args: - lattice: pynini.FstLike tag lattice - - Returns: shortest path - """ - tagged_text = pynini.shortestpath(lattice, nshortest=1, unique=True).string() - return tagged_text - - def find_verbalizer(self, tagged_text: str) -> 'pynini.FstLike': - """ - Given tagged text creates verbalization lattice - This is context-independent. - - Args: - tagged_text: input text - - Returns: verbalized lattice - """ - lattice = tagged_text @ self.verbalizer.fst - return lattice - - @staticmethod - def select_verbalizer(lattice: 'pynini.FstLike') -> str: - """ - Given verbalized lattice return shortest path - - Args: - lattice: verbalization lattice - - Returns: shortest path - """ - output = pynini.shortestpath(lattice, nshortest=1, unique=True).string() - # lattice = output @ self.verbalizer.punct_graph - # output = pynini.shortestpath(lattice, nshortest=1, unique=True).string() - return output - - def post_process(self, normalized_text: 'pynini.FstLike') -> str: - """ - Runs post-processing graph on normalized text - - Args: - normalized_text: normalized text - - Returns: shortest path - """ - normalized_text = normalized_text.strip() - if not normalized_text: - return normalized_text - normalized_text = pynini.escape(normalized_text) - - if self.post_processor is not None: - normalized_text = top_rewrite(normalized_text, self.post_processor.fst) - return normalized_text - - -def parse_args(): - parser = ArgumentParser() - input = parser.add_mutually_exclusive_group() - input.add_argument("--text", dest="input_string", help="input string", type=str) - input.add_argument("--input_file", dest="input_file", help="input file path", type=str) - parser.add_argument('--output_file', dest="output_file", help="output file path", type=str) - parser.add_argument("--language", help="language", choices=["en", "de", "es", "zh"], default="en", type=str) - parser.add_argument( - "--input_case", help="input capitalization", choices=["lower_cased", "cased"], default="cased", type=str - ) - parser.add_argument("--verbose", help="print info for debugging", action='store_true') - parser.add_argument( - "--punct_post_process", - help="set to True to enable punctuation post processing to match input.", - action="store_true", - ) - parser.add_argument( - "--punct_pre_process", help="set to True to enable punctuation pre processing", action="store_true" - ) - parser.add_argument("--overwrite_cache", help="set to True to re-create .far grammar files", action="store_true") - parser.add_argument("--whitelist", help="path to a file with with whitelist", default=None, type=str) - parser.add_argument( - "--cache_dir", - help="path to a dir with .far grammar file. Set to None to avoid using cache", - default=None, - type=str, - ) - return parser.parse_args() - - -if __name__ == "__main__": - start_time = perf_counter() - - args = parse_args() - whitelist = os.path.abspath(args.whitelist) if args.whitelist else None - - if not args.input_string and not args.input_file: - raise ValueError("Either `--text` or `--input_file` required") - - normalizer = Normalizer( - input_case=args.input_case, - cache_dir=args.cache_dir, - overwrite_cache=args.overwrite_cache, - whitelist=whitelist, - lang=args.language, - ) - if args.input_string: - print( - normalizer.normalize( - args.input_string, - verbose=args.verbose, - punct_pre_process=args.punct_pre_process, - punct_post_process=args.punct_post_process, - ) - ) - elif args.input_file: - print("Loading data: " + args.input_file) - data = load_file(args.input_file) - - print("- Data: " + str(len(data)) + " sentences") - normalizer_prediction = normalizer.normalize_list( - data, - verbose=args.verbose, - punct_pre_process=args.punct_pre_process, - punct_post_process=args.punct_post_process, - ) - if args.output_file: - write_file(args.output_file, normalizer_prediction) - print(f"- Normalized. Writing out to {args.output_file}") - else: - print(normalizer_prediction) - - print(f"Execution time: {perf_counter() - start_time:.02f} sec") diff --git a/nemo_text_processing/text_normalization/normalize_with_audio.py b/nemo_text_processing/text_normalization/normalize_with_audio.py deleted file mode 100644 index 27fcaa1e5f87..000000000000 --- a/nemo_text_processing/text_normalization/normalize_with_audio.py +++ /dev/null @@ -1,554 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import json -import os -import time -from argparse import ArgumentParser -from glob import glob -from typing import List, Optional, Tuple - -import pynini -from joblib import Parallel, delayed -from nemo_text_processing.text_normalization.data_loader_utils import post_process_punct, pre_process -from nemo_text_processing.text_normalization.normalize import Normalizer -from pynini.lib import rewrite -from tqdm import tqdm - -try: - from nemo.collections.asr.metrics.wer import word_error_rate - from nemo.collections.asr.models import ASRModel - - ASR_AVAILABLE = True -except (ModuleNotFoundError, ImportError): - ASR_AVAILABLE = False - - -""" -The script provides multiple normalization options and chooses the best one that minimizes CER of the ASR output -(most of the semiotic classes use deterministic=False flag). - -To run this script with a .json manifest file, the manifest file should contain the following fields: - "audio_data" - path to the audio file - "text" - raw text - "pred_text" - ASR model prediction - - See https://github.com/NVIDIA/NeMo/blob/main/examples/asr/transcribe_speech.py on how to add ASR predictions - - When the manifest is ready, run: - python normalize_with_audio.py \ - --audio_data PATH/TO/MANIFEST.JSON \ - --language en - - -To run with a single audio file, specify path to audio and text with: - python normalize_with_audio.py \ - --audio_data PATH/TO/AUDIO.WAV \ - --language en \ - --text raw text OR PATH/TO/.TXT/FILE - --model QuartzNet15x5Base-En \ - --verbose - -To see possible normalization options for a text input without an audio file (could be used for debugging), run: - python python normalize_with_audio.py --text "RAW TEXT" - -Specify `--cache_dir` to generate .far grammars once and re-used them for faster inference -""" - - -class NormalizerWithAudio(Normalizer): - """ - Normalizer class that converts text from written to spoken form. - Useful for TTS preprocessing. - - Args: - input_case: expected input capitalization - lang: language - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - post_process: WFST-based post processing, e.g. to remove extra spaces added during TN. - Note: punct_post_process flag in normalize() supports all languages. - """ - - def __init__( - self, - input_case: str, - lang: str = 'en', - cache_dir: str = None, - overwrite_cache: bool = False, - whitelist: str = None, - lm: bool = False, - post_process: bool = True, - ): - - super().__init__( - input_case=input_case, - lang=lang, - deterministic=False, - cache_dir=cache_dir, - overwrite_cache=overwrite_cache, - whitelist=whitelist, - lm=lm, - post_process=post_process, - ) - self.lm = lm - - def normalize(self, text: str, n_tagged: int, punct_post_process: bool = True, verbose: bool = False,) -> str: - """ - Main function. Normalizes tokens from written to spoken form - e.g. 12 kg -> twelve kilograms - - Args: - text: string that may include semiotic classes - n_tagged: number of tagged options to consider, -1 - to get all possible tagged options - punct_post_process: whether to normalize punctuation - verbose: whether to print intermediate meta information - - Returns: - normalized text options (usually there are multiple ways of normalizing a given semiotic class) - """ - - if len(text.split()) > 500: - raise ValueError( - "Your input is too long. Please split up the input into sentences, " - "or strings with fewer than 500 words" - ) - - original_text = text - text = pre_process(text) # to handle [] - - text = text.strip() - if not text: - if verbose: - print(text) - return text - text = pynini.escape(text) - print(text) - - if self.lm: - if self.lang not in ["en"]: - raise ValueError(f"{self.lang} is not supported in LM mode") - - if self.lang == "en": - # this to keep arpabet phonemes in the list of options - if "[" in text and "]" in text: - - lattice = rewrite.rewrite_lattice(text, self.tagger.fst) - else: - try: - lattice = rewrite.rewrite_lattice(text, self.tagger.fst_no_digits) - except pynini.lib.rewrite.Error: - lattice = rewrite.rewrite_lattice(text, self.tagger.fst) - lattice = rewrite.lattice_to_nshortest(lattice, n_tagged) - tagged_texts = [(x[1], float(x[2])) for x in lattice.paths().items()] - tagged_texts.sort(key=lambda x: x[1]) - tagged_texts, weights = list(zip(*tagged_texts)) - else: - tagged_texts = self._get_tagged_text(text, n_tagged) - # non-deterministic Eng normalization uses tagger composed with verbalizer, no permutation in between - if self.lang == "en": - normalized_texts = tagged_texts - normalized_texts = [self.post_process(text) for text in normalized_texts] - else: - normalized_texts = [] - for tagged_text in tagged_texts: - self._verbalize(tagged_text, normalized_texts, verbose=verbose) - - if len(normalized_texts) == 0: - raise ValueError() - - if punct_post_process: - # do post-processing based on Moses detokenizer - if self.processor: - normalized_texts = [self.processor.detokenize([t]) for t in normalized_texts] - normalized_texts = [ - post_process_punct(input=original_text, normalized_text=t) for t in normalized_texts - ] - - if self.lm: - remove_dup = sorted(list(set(zip(normalized_texts, weights))), key=lambda x: x[1]) - normalized_texts, weights = zip(*remove_dup) - return list(normalized_texts), weights - - normalized_texts = set(normalized_texts) - return normalized_texts - - def _get_tagged_text(self, text, n_tagged): - """ - Returns text after tokenize and classify - Args; - text: input text - n_tagged: number of tagged options to consider, -1 - return all possible tagged options - """ - if n_tagged == -1: - if self.lang == "en": - # this to keep arpabet phonemes in the list of options - if "[" in text and "]" in text: - tagged_texts = rewrite.rewrites(text, self.tagger.fst) - else: - try: - tagged_texts = rewrite.rewrites(text, self.tagger.fst_no_digits) - except pynini.lib.rewrite.Error: - tagged_texts = rewrite.rewrites(text, self.tagger.fst) - else: - tagged_texts = rewrite.rewrites(text, self.tagger.fst) - else: - if self.lang == "en": - # this to keep arpabet phonemes in the list of options - if "[" in text and "]" in text: - tagged_texts = rewrite.top_rewrites(text, self.tagger.fst, nshortest=n_tagged) - else: - try: - # try self.tagger graph that produces output without digits - tagged_texts = rewrite.top_rewrites(text, self.tagger.fst_no_digits, nshortest=n_tagged) - except pynini.lib.rewrite.Error: - tagged_texts = rewrite.top_rewrites(text, self.tagger.fst, nshortest=n_tagged) - else: - tagged_texts = rewrite.top_rewrites(text, self.tagger.fst, nshortest=n_tagged) - return tagged_texts - - def _verbalize(self, tagged_text: str, normalized_texts: List[str], verbose: bool = False): - """ - Verbalizes tagged text - - Args: - tagged_text: text with tags - normalized_texts: list of possible normalization options - verbose: if true prints intermediate classification results - """ - - def get_verbalized_text(tagged_text): - return rewrite.rewrites(tagged_text, self.verbalizer.fst) - - self.parser(tagged_text) - tokens = self.parser.parse() - tags_reordered = self.generate_permutations(tokens) - for tagged_text_reordered in tags_reordered: - try: - tagged_text_reordered = pynini.escape(tagged_text_reordered) - normalized_texts.extend(get_verbalized_text(tagged_text_reordered)) - if verbose: - print(tagged_text_reordered) - - except pynini.lib.rewrite.Error: - continue - - def select_best_match( - self, - normalized_texts: List[str], - input_text: str, - pred_text: str, - verbose: bool = False, - remove_punct: bool = False, - cer_threshold: int = 100, - ): - """ - Selects the best normalization option based on the lowest CER - - Args: - normalized_texts: normalized text options - input_text: input text - pred_text: ASR model transcript of the audio file corresponding to the normalized text - verbose: whether to print intermediate meta information - remove_punct: whether to remove punctuation before calculating CER - cer_threshold: if CER for pred_text is above the cer_threshold, no normalization will be performed - - Returns: - normalized text with the lowest CER and CER value - """ - if pred_text == "": - return input_text, cer_threshold - - normalized_texts_cer = calculate_cer(normalized_texts, pred_text, remove_punct) - normalized_texts_cer = sorted(normalized_texts_cer, key=lambda x: x[1]) - normalized_text, cer = normalized_texts_cer[0] - - if cer > cer_threshold: - return input_text, cer - - if verbose: - print('-' * 30) - for option in normalized_texts: - print(option) - print('-' * 30) - return normalized_text, cer - - -def calculate_cer(normalized_texts: List[str], pred_text: str, remove_punct=False) -> List[Tuple[str, float]]: - """ - Calculates character error rate (CER) - - Args: - normalized_texts: normalized text options - pred_text: ASR model output - - Returns: normalized options with corresponding CER - """ - normalized_options = [] - for text in normalized_texts: - text_clean = text.replace('-', ' ').lower() - if remove_punct: - for punct in "!?:;,.-()*+-/<=>@^_": - text_clean = text_clean.replace(punct, "") - cer = round(word_error_rate([pred_text], [text_clean], use_cer=True) * 100, 2) - normalized_options.append((text, cer)) - return normalized_options - - -def get_asr_model(asr_model): - """ - Returns ASR Model - - Args: - asr_model: NeMo ASR model - """ - if os.path.exists(args.model): - asr_model = ASRModel.restore_from(asr_model) - elif args.model in ASRModel.get_available_model_names(): - asr_model = ASRModel.from_pretrained(asr_model) - else: - raise ValueError( - f'Provide path to the pretrained checkpoint or choose from {ASRModel.get_available_model_names()}' - ) - return asr_model - - -def parse_args(): - parser = ArgumentParser() - parser.add_argument("--text", help="input string or path to a .txt file", default=None, type=str) - parser.add_argument( - "--input_case", help="input capitalization", choices=["lower_cased", "cased"], default="cased", type=str - ) - parser.add_argument( - "--language", help="Select target language", choices=["en", "ru", "de", "es"], default="en", type=str - ) - parser.add_argument("--audio_data", default=None, help="path to an audio file or .json manifest") - parser.add_argument( - "--output_filename", - default=None, - help="Path of where to save .json manifest with normalization outputs." - " It will only be saved if --audio_data is a .json manifest.", - type=str, - ) - parser.add_argument( - '--model', type=str, default='QuartzNet15x5Base-En', help='Pre-trained model name or path to model checkpoint' - ) - parser.add_argument( - "--n_tagged", - type=int, - default=30, - help="number of tagged options to consider, -1 - return all possible tagged options", - ) - parser.add_argument("--verbose", help="print info for debugging", action="store_true") - parser.add_argument( - "--no_remove_punct_for_cer", - help="Set to True to NOT remove punctuation before calculating CER", - action="store_true", - ) - parser.add_argument( - "--no_punct_post_process", help="set to True to disable punctuation post processing", action="store_true" - ) - parser.add_argument("--overwrite_cache", help="set to True to re-create .far grammar files", action="store_true") - parser.add_argument("--whitelist", help="path to a file with with whitelist", default=None, type=str) - parser.add_argument( - "--cache_dir", - help="path to a dir with .far grammar file. Set to None to avoid using cache", - default=None, - type=str, - ) - parser.add_argument("--n_jobs", default=-2, type=int, help="The maximum number of concurrently running jobs") - parser.add_argument( - "--lm", action="store_true", help="Set to True for WFST+LM. Only available for English right now." - ) - parser.add_argument( - "--cer_threshold", - default=100, - type=int, - help="if CER for pred_text is above the cer_threshold, no normalization will be performed", - ) - parser.add_argument("--batch_size", default=200, type=int, help="Number of examples for each process") - return parser.parse_args() - - -def _normalize_line( - normalizer: NormalizerWithAudio, n_tagged, verbose, line: str, remove_punct, punct_post_process, cer_threshold -): - line = json.loads(line) - pred_text = line["pred_text"] - - normalized_texts = normalizer.normalize( - text=line["text"], verbose=verbose, n_tagged=n_tagged, punct_post_process=punct_post_process, - ) - - normalized_texts = set(normalized_texts) - normalized_text, cer = normalizer.select_best_match( - normalized_texts=normalized_texts, - input_text=line["text"], - pred_text=pred_text, - verbose=verbose, - remove_punct=remove_punct, - cer_threshold=cer_threshold, - ) - line["nemo_normalized"] = normalized_text - line["CER_nemo_normalized"] = cer - return line - - -def normalize_manifest( - normalizer, - audio_data: str, - n_jobs: int, - n_tagged: int, - remove_punct: bool, - punct_post_process: bool, - batch_size: int, - cer_threshold: int, - output_filename: Optional[str] = None, -): - """ - Args: - args.audio_data: path to .json manifest file. - """ - - def __process_batch(batch_idx: int, batch: List[str], dir_name: str): - """ - Normalizes batch of text sequences - Args: - batch: list of texts - batch_idx: batch index - dir_name: path to output directory to save results - """ - normalized_lines = [ - _normalize_line( - normalizer, - n_tagged, - verbose=False, - line=line, - remove_punct=remove_punct, - punct_post_process=punct_post_process, - cer_threshold=cer_threshold, - ) - for line in tqdm(batch) - ] - - with open(f"{dir_name}/{batch_idx:05}.json", "w") as f_out: - for line in normalized_lines: - f_out.write(json.dumps(line, ensure_ascii=False) + '\n') - - print(f"Batch -- {batch_idx} -- is complete") - - if output_filename is None: - output_filename = audio_data.replace('.json', '_normalized.json') - - with open(audio_data, 'r') as f: - lines = f.readlines() - - print(f'Normalizing {len(lines)} lines of {audio_data}...') - - # to save intermediate results to a file - batch = min(len(lines), batch_size) - - tmp_dir = output_filename.replace(".json", "_parts") - os.makedirs(tmp_dir, exist_ok=True) - - Parallel(n_jobs=n_jobs)( - delayed(__process_batch)(idx, lines[i : i + batch], tmp_dir) - for idx, i in enumerate(range(0, len(lines), batch)) - ) - - # aggregate all intermediate files - with open(output_filename, "w") as f_out: - for batch_f in sorted(glob(f"{tmp_dir}/*.json")): - with open(batch_f, "r") as f_in: - lines = f_in.read() - f_out.write(lines) - - print(f'Normalized version saved at {output_filename}') - - -if __name__ == "__main__": - args = parse_args() - - if not ASR_AVAILABLE and args.audio_data: - raise ValueError("NeMo ASR collection is not installed.") - start = time.time() - args.whitelist = os.path.abspath(args.whitelist) if args.whitelist else None - if args.text is not None: - normalizer = NormalizerWithAudio( - input_case=args.input_case, - lang=args.language, - cache_dir=args.cache_dir, - overwrite_cache=args.overwrite_cache, - whitelist=args.whitelist, - lm=args.lm, - ) - - if os.path.exists(args.text): - with open(args.text, 'r') as f: - args.text = f.read().strip() - normalized_texts = normalizer.normalize( - text=args.text, - verbose=args.verbose, - n_tagged=args.n_tagged, - punct_post_process=not args.no_punct_post_process, - ) - - if not normalizer.lm: - normalized_texts = set(normalized_texts) - if args.audio_data: - asr_model = get_asr_model(args.model) - pred_text = asr_model.transcribe([args.audio_data])[0] - normalized_text, cer = normalizer.select_best_match( - normalized_texts=normalized_texts, - pred_text=pred_text, - input_text=args.text, - verbose=args.verbose, - remove_punct=not args.no_remove_punct_for_cer, - cer_threshold=args.cer_threshold, - ) - print(f"Transcript: {pred_text}") - print(f"Normalized: {normalized_text}") - else: - print("Normalization options:") - for norm_text in normalized_texts: - print(norm_text) - elif not os.path.exists(args.audio_data): - raise ValueError(f"{args.audio_data} not found.") - elif args.audio_data.endswith('.json'): - normalizer = NormalizerWithAudio( - input_case=args.input_case, - lang=args.language, - cache_dir=args.cache_dir, - overwrite_cache=args.overwrite_cache, - whitelist=args.whitelist, - ) - normalize_manifest( - normalizer=normalizer, - audio_data=args.audio_data, - n_jobs=args.n_jobs, - n_tagged=args.n_tagged, - remove_punct=not args.no_remove_punct_for_cer, - punct_post_process=not args.no_punct_post_process, - batch_size=args.batch_size, - cer_threshold=args.cer_threshold, - output_filename=args.output_filename, - ) - else: - raise ValueError( - "Provide either path to .json manifest in '--audio_data' OR " - + "'--audio_data' path to audio file and '--text' path to a text file OR" - "'--text' string text (for debugging without audio)" - ) - print(f'Execution time: {round((time.time() - start)/60, 2)} min.') diff --git a/nemo_text_processing/text_normalization/ru/__init__.py b/nemo_text_processing/text_normalization/ru/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/alphabet.py b/nemo_text_processing/text_normalization/ru/alphabet.py deleted file mode 100644 index 3df59f4688c0..000000000000 --- a/nemo_text_processing/text_normalization/ru/alphabet.py +++ /dev/null @@ -1,57 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# Copyright 2017 Google Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Adapted from https://github.com/google/TextNormalizationCoveringGrammars -# Russian minimally supervised number grammar. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NON_BREAKING_SPACE, NEMO_SPACE -from nemo_text_processing.text_normalization.ru.utils import get_abs_path - -RU_LOWER_ALPHA = "абвгдеёжзийклмнопрстуфхцчшщъыьэюя" -RU_UPPER_ALPHA = RU_LOWER_ALPHA.upper() -RU_LOWER_ALPHA = pynini.union(*RU_LOWER_ALPHA).optimize() -RU_UPPER_ALPHA = pynini.union(*RU_UPPER_ALPHA).optimize() -RU_ALPHA = (RU_LOWER_ALPHA | RU_UPPER_ALPHA).optimize() - -RU_STRESSED_MAP = [ - ("А́", "А'"), - ("Е́", "Е'"), - ("Ё́", "Е'"), - ("И́", "И'"), - ("О́", "О'"), - ("У́", "У'"), - ("Ы́", "Ы'"), - ("Э́", "Э'"), - ("Ю́", "Ю'"), - ("Я́", "Я'"), - ("а́", "а'"), - ("е́", "е'"), - ("ё́", "е'"), - ("и́", "и'"), - ("о́", "о'"), - ("у́", "у'"), - ("ы́", "ы'"), - ("э́", "э'"), - ("ю́", "ю'"), - ("я́", "я'"), - ("ё", "е"), - ("Ё", "Е"), -] - -REWRITE_STRESSED = pynini.closure(pynini.string_map(RU_STRESSED_MAP).optimize() | RU_ALPHA).optimize() -TO_CYRILLIC = pynini.string_file(get_abs_path("data/latin_to_cyrillic.tsv")).optimize() -TO_LATIN = pynini.invert(TO_CYRILLIC).optimize() -RU_ALPHA_OR_SPACE = pynini.union(RU_ALPHA, NEMO_SPACE, NEMO_NON_BREAKING_SPACE).optimize() diff --git a/nemo_text_processing/text_normalization/ru/data/__init__.py b/nemo_text_processing/text_normalization/ru/data/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/data/currency/__init__.py b/nemo_text_processing/text_normalization/ru/data/currency/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/currency/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/data/currency/currency_plural.tsv b/nemo_text_processing/text_normalization/ru/data/currency/currency_plural.tsv deleted file mode 100644 index c1d281590e33..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/currency/currency_plural.tsv +++ /dev/null @@ -1,53 +0,0 @@ -р. рубли 0.1 -р. рубля 0.1 -р. рублей 0.1 -р. рублям 0.1 -р. рублями 0.1 -р. рублях 0.1 -руб. рубли -0.1 -руб. рубля -0.1 -руб. рублей -0.1 -руб. рублям -0.1 -руб. рублями -0.1 -руб. рублях -0.1 -₽ рубли 0.1 -₽ рубля 0.1 -₽ рублей 0.1 -₽ рублям 0.1 -₽ рублями 0.1 -₽ рублях 0.1 -RUB рубли 0.1 -RUB рублей 0.1 -RUB рубля 0.1 -RUB рублям 0.1 -RUB рублями 0.1 -RUB рублях 0.1 -$ доллары 0.1 -$ долларов 0.1 -$ доллара 0.1 -$ долларам 0.1 -$ доллары 0.1 -$ долларами 0.1 -USD доллары -0.1 -USD долларов -0.1 -USD долларам -0.1 -USD долларах -0.1 -USD долларами -0.1 -USD американские доллары 0.1 -USD американских долларов 0.1 -USD американским долларам 0.1 -USD американскими долларами 0.1 -USD американских долларах 0.1 -долл. США долларов сэ ш а 0.1 -долл. США долларов с ш а 0.1 -долл. США долларов сша -0.1 -долл. США доллара сша -0.1 -£ фунта 0.1 -£ фунтов 0.1 -€ евро 0.1 -€ евро 0.1 -коп. копейки -коп. копеек -коп. копейкам -коп. копейками -коп. копейках \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/currency/currency_singular.tsv b/nemo_text_processing/text_normalization/ru/data/currency/currency_singular.tsv deleted file mode 100644 index de7d1c7ebed0..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/currency/currency_singular.tsv +++ /dev/null @@ -1,48 +0,0 @@ -р. рубль 1 -р. рубля 1 -р. рублю 1 -р. рублем 1 -р. рубле 1 -руб. рубль -1 -руб. рубля -1 -руб. рублю -1 -руб. рублем -1 -руб. рубле -1 -₽ рубль 1 -₽ рубля 1 -₽ рублю 1 -₽ рублем 1 -₽ рубле 1 -RUB рубль 1 -RUB рубль 1 -RUB рубля 1 -RUB рублю 1 -RUB рублем 1 -RUB рубле 1 -USD доллар -1 -USD доллара -1 -USD доллару -1 -USD долларом -1 -USD долларе -1 -USD американский доллар 1 -USD американского доллара 1 -USD американскому доллару 1 -USD американским долларом 1 -USD американском долларе 1 -$ доллар 1 -$ доллар сэ ш а -$ доллар с ш а -$ доллар 1 -$ доллара 1 -$ доллару 1 -$ долларом 1 -$ долларе 1 -£ фунт -€ евро -коп. копейка -коп. копейки -коп. копейке -коп. копейку -коп. копейкой -коп. копейкою -коп. копейке \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/electronic/__init__.py b/nemo_text_processing/text_normalization/ru/data/electronic/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/electronic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/data/electronic/domain.tsv b/nemo_text_processing/text_normalization/ru/data/electronic/domain.tsv deleted file mode 100644 index c208e05595b8..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/electronic/domain.tsv +++ /dev/null @@ -1,9 +0,0 @@ -com ком -uk -fr -net нет -br -in -ru ру -de -it \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/electronic/server_name.tsv b/nemo_text_processing/text_normalization/ru/data/electronic/server_name.tsv deleted file mode 100644 index 5d885db1c955..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/electronic/server_name.tsv +++ /dev/null @@ -1,17 +0,0 @@ -gmail джи мейл -n vidia н видия -n vidia эн видия -n vidia энвидия -n vidia нвидия -outlook аутлук -hotmail хот мейл -yahoo яху -aol -gmx -msn -live лайв -yandex яндекс -orange орандж -wanadoo ванаду -web веб -comcast комкаст \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/electronic/symbols.tsv b/nemo_text_processing/text_normalization/ru/data/electronic/symbols.tsv deleted file mode 100644 index e772ad912c73..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/electronic/symbols.tsv +++ /dev/null @@ -1,28 +0,0 @@ -. точка -- тире -- дефис -- минус -_ нижнее подчеркивание -_ знак подчеркивания -! восклицательный знак -# решетка -$ доллар -% процент -& энд -& амперсанд -' кавычка -* звездочка -* знак умножения -+ плюс -/ слэш -/ косая черта -\ бэк слэш -\ обратная косая черта -= равно -? вопросительный знак -^ знак вставки -` кавычка -{ открытая фигурная скобка -| вертикальный слэш -} закрытая фигурная скобка -~ тильда \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/latin_to_cyrillic.tsv b/nemo_text_processing/text_normalization/ru/data/latin_to_cyrillic.tsv deleted file mode 100644 index 8e0c8f569955..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/latin_to_cyrillic.tsv +++ /dev/null @@ -1,38 +0,0 @@ -a эй -b би -b бэ -c си -d ди -e и -f эф -f ф -h эйч -h х -i ай -g джи -j джей -k кей -k к -l л -l эл -m эм -n н -n эн -o оу -o о -p пи -q кью -r а -r ар -r р -s эс -t ти -u ю -v ви -w дабл ю -w дабл в -x экс -y уай -z з -z зед -z зи \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/measurements.tsv b/nemo_text_processing/text_normalization/ru/data/measurements.tsv deleted file mode 100644 index a48079dd2268..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/measurements.tsv +++ /dev/null @@ -1,321 +0,0 @@ -°F Фаренгейт -°F градусов Фаренгейта -°F градусов по Фаренгейту -°F фаренгейт -°F градусов фаренгейта -°F градусов по фаренгейту -°C цельсия -°C градусов цельсия -°C градусов по цельсию -°C Цельсия -°C градусов цельсия -°C градусов по цельсию -° градус -° градуса -° градусу -° градусом -° градусе -° градусы -° градусов -° градусам -° градусы -° градусами -° градусах -рад радиан -рад радиана -рад радиану -рад радианом -рад радиане -рад радианы -рад радианов -рад радианам -рад радианами -рад радианах -км километр -км километры -км километра -км километров -км километру -км километрам -км километром -км километрами -км километре -км километрах -м метр -м метра -м метру -м метра -м метром -м метре -м метры -м метров -м метрам -м метров -м метрами -м метрах -см сантиметр -см сантиметры -см сантиметра -см сантиметров -см сантиметру -см сантиметрам -см сантиметром -см сантиметрами -см сантиметре -см сантиметрах -мм миллиметр -мм миллиметры -мм миллиметра -мм миллиметров -мм миллиметру -мм миллиметрам -мм миллиметр -мм миллиметром -мм миллиметрами -мм миллиметре -мм миллиметрах -га гектар -га гектары -га гектара -га гектаров -га гектару -га гектарам -га гектаром -га гектарами -га гектаре -га гектарах -м² квадратный метр -0.11 -м² квадратные метры -0.11 -м² квадратного метра -0.11 -м² квадратных метров -0.11 -м² квадратному метру -0.11 -м² квадратным метрам -0.11 -м² квадратные метры -0.11 -м² квадратным метром -0.11 -м² квадратными метрами -0.11 -м² квадратном метре -0.11 -м² квадратных метрах -0.11 -кв. м. квадратный метр -0.1 -кв. м. квадратные метры -0.1 -кв. м. квадратного метра -0.1 -кв. м. квадратных метров -0.1 -кв. м. квадратному метру -0.1 -кв. м. квадратным метрам -0.1 -кв. м. квадратные метры -0.1 -кв. м. квадратным метром -0.1 -кв. м. квадратными метрами -0.1 -кв. м. квадратном метре -0.1 -кв.м. квадратных метрах -0.1 -кв.м. квадратный метр -0.1 -кв.м. квадратные метры -0.1 -кв.м. квадратного метра -0.1 -кв.м. квадратных метров -0.1 -кв.м. квадратному метру -0.1 -кв.м. квадратным метрам -0.1 -кв.м. квадратные метры -0.1 -кв.м. квадратным метром -0.1 -кв.м. квадратными метрами -0.1 -кв.м. квадратном метре -0.1 -кв.м. квадратных метрах -0.1 -м2 квадратный метр 0.1 -м2 квадратные метры 0.1 -м2 квадратного метра 0.1 -м2 квадратных метров 0.1 -м2 квадратному метру 0.1 -м2 квадратным метрам 0.1 -м2 квадратные метры 0.1 -м2 квадратным метром 0.1 -м2 квадратными метрами 0.1 -м2 квадратном метре 0.1 -м2 квадратных метрах 0.1 -₽ рублей 0.1 -₽ рубля 0.1 -₽ рубль 0.1 -RUB рублей 0.1 -RUB рубля 0.1 -RUB рубль 0.1 -pуб. рублей -0.1 -pуб. рубля -0.1 -pуб. рубль -0.1 -pуб рублей 0.1 -pуб рубля 0.1 -pуб рубль 0.1 -км² квадратный километр -0.1 -км2 квадратный километр 0.1 -% процент -% проценты -% процента -% процентов -% проценту -% процентам -% процентом -% процентами -% проценте -% процентах -кВт киловатт -л. с. лошадиная сила -л. с. лошадиные силы -л. с. лошадиной силы -л. с. лошадиных сил -л. с. лошадиной силе -л. с. лошадиным силам -л. с. лошадиную силу -л. с. лошадиные силы -л. с. лошадиной силой -л. с. лошадиной силою -л. с. лошадиными силами -л. с. лошадиных силах -мг миллиграм -кг килограм -кг килограма -кг килограму -кг килограм -кг килограмом -кг килограме -кг килограмы -кг килограмов -кг килограмам -кг килограмы -кг килограмами -кг килограмах -л литр -л литры -л литра -л литров -л литру -л литрам -л литры -л литром -л литрами -л литре -л литрах -л литре -кл килолитр -гл гектолитр -Мл мегалитр -Гл гигалитр -мл миллиитр -ч час -сек. секунд -0.1 -сек. секунда -0.1 -сек. секунды -0.1 -сек. секунды -0.1 -сек. секунд -0.1 -сек. секунде -0.1 -сек. секундам -0.1 -сек. секунду -0.1 -сек. секунды -0.1 -сек. секундой -0.1 -сек. секундами -0.1 -сек. секунде -0.1 -сек. секундах -0.1 -сек секунд 0.1 -сек секунда 0.1 -сек секунды 0.1 -сек секунды 0.1 -сек секунд 0.1 -сек секунде 0.1 -сек секундам 0.1 -сек секунду 0.1 -сек секунды 0.1 -сек секундой 0.1 -сек секундами 0.1 -сек секунде 0.1 -сек секундах 0.1 -с секунд 0.1 -с секунда 0.1 -с секунды 0.1 -с секунды 0.1 -с секунд 0.1 -с секунде 0.1 -с секундам 0.1 -с секунду 0.1 -с секунды 0.1 -с секундой 0.1 -с секундами 0.1 -с секунде 0.1 -с секундах 0.1 -дас декасекунда -кс килосекунда -Мс мегасекунда -мс миллисекунда -нм нанометр -нм нанометра -нм нанометров -нм нанометры -А ампер -К кельвин -кд кандела -мА миллиампер -кВт⋅ч киловатт час -м³ кубический метр -0.1 -м³ кубический метров -0.1 -м3 кубический метр 0.1 -м3 кубический метров 0.1 -м³ кубометр -0.1 -м³ кубометров -0.1 -км/ч километров в час -км/ч километра в час -В вольт -гВ гектовольт -кВ киловольт -МВ мегавольт -мВ милливольт -мВт мегаватт -ТВт тераватт -мкм микрометр -г грамм -г граммов -дБ децибел -Б байт -Кбайт килобайт -Мбайт мегабайт -Пбайт петабайт -Тбайт терабайт 0.1 -ТБ терабайт -0.1 -Гбайт гигабайт 0.1 -Гб гигабайт -0.1 -Гц герц -даГц декагерц -дГц децигерц -гГц гектогерц -сГц сантигерц -кГц килогерц -мГц миллигерц -МГц мегагерц -мкГц микрогерц -ГГц гигагерц -нГц наногерц -ТГц терагерц -пГц пикогерц -ПГц петагерц -фГц фемтогерц -ЭГц эксагерц -аГц аттогерц -ЗГц зеттагерц -зГц зептогерц -ИГц иоттагерц -иГц иоктогерц -кбит килобит -Мбит мегабит -Гбит гигабит -Тбит терабит -бит/с бит в секунду -кбит/с килобит в секунду -Мбит/с мегабит в секунду -Гбит/с гигабит в секунду -нс наносекунда -нс наносекунды -нс наносекунд -мм² квадратный миллиметр -0.1 -мм² квадратных миллиметров -0.1 -мм² квадратных миллиметра -0.1 -мм2 квадратный миллиметр 0.1 -мм2 квадратных миллимета 0.1 -мм2 квадратных миллиметров 0.1 -см² квадратный сантиметр -0.1 -см² квадратных сантимета -0.1 -см² квадратных сантиметров -0.1 -см2 квадратный сантиметр 0.1 -см2 квадратных сантиметра 0.1 -см2 квадратных сантиметров 0.1 diff --git a/nemo_text_processing/text_normalization/ru/data/months/__init__.py b/nemo_text_processing/text_normalization/ru/data/months/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/months/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/data/months/abbr.tsv b/nemo_text_processing/text_normalization/ru/data/months/abbr.tsv deleted file mode 100644 index cd51fe389b09..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/months/abbr.tsv +++ /dev/null @@ -1,12 +0,0 @@ -янв январь -фев февраль -мар март -апр апрель -май май -июнь июнь -июль июль -авг август -сент сентябрь -окт октябрь -нояб ноябрь -дек декабрь \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/months/abbr_to_name.tsv b/nemo_text_processing/text_normalization/ru/data/months/abbr_to_name.tsv deleted file mode 100644 index 7a4c61b21582..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/months/abbr_to_name.tsv +++ /dev/null @@ -1,62 +0,0 @@ -янв январь 0.1 -янв января -0.1 -янв январю 0.1 -янв январем 0.1 -янв январе 0.1 -фев февраль 0.1 -фев февраль 0.1 -фев февраля -0.1 -фев февралю 0.1 -фев февралем 0.1 -фев феврале 0.1 -мар март 0.1 -мар марта -0.1 -мар марту 0.1 -мар мартом 0.1 -мар марте 0.1 -апр апрель 0.1 -апр апреля -0.1 -апр апрелю 0.1 -апр апрелем 0.1 -апр апреле 0.1 -май май 0.1 -май мая -0.1 -май маю 0.1 -май маем 0.1 -май мае 0.1 -июнь июнь 0.1 -июнь июня -0.1 -июнь июню 0.1 -июнь июнем 0.1 -июнь июне 0.1 -июль июль 0.1 -июль июля -0.1 -июль июлю 0.1 -июль июлем 0.1 -июль июле 0.1 -авг август 0.1 -авг августа -0.1 -авг августу 0.1 -авг август 0.1 -авг августом 0.1 -авг августе 0.1 -сент сентябрь 0.1 -сент сентября -0.1 -сент сентябрю 0.1 -сент сентябрем 0.1 -сент сентябре 0.1 -окт октябрь 0.1 -окт октября -0.1 -окт октябрю 0.1 -окт октябрем 0.1 -окт октябре 0.1 -нояб ноябрь 0.1 -нояб ноября -0.1 -нояб ноябрю 0.1 -нояб ноябрем 0.1 -нояб ноябре 0.1 -дек декабрь 0.1 -дек декабря -0.1 -дек декабрю 0.1 -дек декабрем 0.1 -дек декабре 0.1 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/months/numbers.tsv b/nemo_text_processing/text_normalization/ru/data/months/numbers.tsv deleted file mode 100644 index 16256a59d9f6..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/months/numbers.tsv +++ /dev/null @@ -1,21 +0,0 @@ -1 янв -2 фев -3 мар -4 апр -5 май -6 июнь -7 июль -8 авг -9 сент -10 окт -11 нояб -12 дек -01 янв -02 фев -03 мар -04 апр -05 май -06 июнь -07 июль -08 авг -09 сент \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/1_cardinals_nominative.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/1_cardinals_nominative.tsv deleted file mode 100644 index 58c543af2a75..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/1_cardinals_nominative.tsv +++ /dev/null @@ -1,50 +0,0 @@ -0 ноль -1 один -1 одна -1 одно -1 одни -2 два -2 две -3 три -4 четыре -5 пять -6 шесть -7 семь -8 восемь -9 девять -10 десять -11 одиннадцать -12 двенадцать -13 тринадцать -14 четырнадцать -15 пятнадцать -16 шестнадцать -17 семнадцать -18 восемнадцать -19 девятнадцать -20 двадцать -30 тридцать -40 сорок -50 пятьдесят -60 шестьдесят -70 семьдесят -80 восемьдесят -90 девяносто -100 сто -200 двести -300 триста -400 четыреста -500 пятьсот -600 шестьсот -700 семьсот -800 восемьсот -900 девятьсот -1000 тысяч -1000 тысяча -1000 тысячи -1000000 миллион -1000000 миллиона -1000000 миллионов -1000000000 миллиард -1000000000 миллиарда -1000000000 миллиардов \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/2_cardinals_genitive.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/2_cardinals_genitive.tsv deleted file mode 100644 index d46d6a10b01a..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/2_cardinals_genitive.tsv +++ /dev/null @@ -1,45 +0,0 @@ -0 ноля -1 одного -1 одной -1 одних -2 двух -3 трех -4 четырех -5 пяти -6 шести -7 семи -8 восьми -9 девяти -10 десяти -11 одиннадцати -12 двенадцати -13 тринадцати -14 четырнадцати -15 пятнадцати -16 шестнадцати -17 семнадцати -18 восемнадцати -19 девятнадцати -20 двадцати -30 тридцати -40 сорока -50 пятидесяти -60 шестидесяти -70 семидесяти -80 восьмидесяти -90 девяноста -100 ста -200 двухсот -300 трехсот -400 четырехсот -500 пятисот -600 шестисот -700 семисот -800 восьмисот -900 девятисот -1000 тысячи -1000 тысяч -1000000 миллиона -1000000 миллионов -1000000000 миллиарда -1000000000 миллиардов diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/3_cardinals_dative.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/3_cardinals_dative.tsv deleted file mode 100644 index 85d335fdeb47..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/3_cardinals_dative.tsv +++ /dev/null @@ -1,45 +0,0 @@ -0 нолем -1 одним -1 одному -1 одной -2 двум -3 трем -4 четырем -5 пяти -6 шести -7 семи -8 восьми -9 девяти -10 десяти -11 одиннадцати -12 двенадцати -13 тринадцати -14 четырнадцати -15 пятнадцати -16 шестнадцати -17 семнадцати -18 восемнадцати -19 девятнадцати -20 двадцати -30 тридцати -40 сорока -50 пятидесяти -60 шестидесяти -70 семидесяти -80 восьмидесяти -90 девяноста -100 ста -200 двумстам -300 тремстам -400 четыремстам -500 пятистам -600 шестистам -700 семистам -800 восьмистам -900 девятистам -1000 тысяче -1000 тысячам -1000000 миллиону -1000000 миллионам -1000000000 миллиарду -1000000000 миллиардам diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/4_cardinals_accusative.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/4_cardinals_accusative.tsv deleted file mode 100644 index 51617a408422..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/4_cardinals_accusative.tsv +++ /dev/null @@ -1,48 +0,0 @@ -0 ноль -1 один -1 одного -1 одни -1 одно -1 одну -2 два -2 две -3 трех -4 четырех -5 пять -6 шесть -7 семь -8 восемь -9 девять -10 десять -11 одиннадцать -12 двенадцать -13 тринадцать -14 четырнадцать -15 пятнадцать -16 шестнадцать -17 семнадцать -18 восемнадцать -19 девятнадцать -20 двадцать -30 тридцать -40 сорок -50 пятьдесят -60 шестьдесят -70 семьдесят -80 восемьдесят -90 девяносто -100 сто -200 двести -300 триста -400 четыреста -500 пятьсот -600 шестьсот -700 семьсот -800 восемьсот -900 девятьсот -1000 тысячи -1000 тысячу -1000000 миллион -1000000 миллионы -1000000000 миллиард -1000000000 миллиарды \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/5_cardinals_instrumental.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/5_cardinals_instrumental.tsv deleted file mode 100644 index a86f304347f0..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/5_cardinals_instrumental.tsv +++ /dev/null @@ -1,47 +0,0 @@ -0 нолем -1 одним -1 одними -1 одной -1 одною -1 одну -2 двумя -3 тремя -4 четырьмя -5 пятью -6 шестью -7 семью -8 восемью -8 восьмью -9 девятью -10 десятью -11 одиннадцатью -12 двенадцатью -13 тринадцатью -14 четырнадцатью -15 пятнадцатью -16 шестнадцатью -17 семнадцатью -18 восемнадцатью -19 девятнадцатью -20 двадцатью -30 тридцатью -40 сорока -50 пятьюдесятью -60 шестьюдесятью -70 семьюдесятью -80 восьмьюдесятью -90 девяноста -100 ста -200 двумястами -300 тремястами -400 четырьмястами -500 пятьюстами -600 шестьюстами -700 семьюстами -800 восемьюстами -900 девятьюстами -1000000 миллионами -1000000 миллионом -1000000 миллиону -1000000 миллионы -1000000000 миллиардом diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/6_cardinals_prepositional.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/6_cardinals_prepositional.tsv deleted file mode 100644 index 6a10bc16aab8..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/6_cardinals_prepositional.tsv +++ /dev/null @@ -1,46 +0,0 @@ -0 ноле -0 нуле -1 одной -1 одном -2 двух -3 трех -4 четырех -5 пяти -6 шести -7 семи -8 восьми -9 девяти -10 десяти -11 одиннадцати -12 двенадцати -13 тринадцати -14 четырнадцати -15 пятнадцати -16 шестнадцати -17 семнадцати -18 восемнадцати -19 девятнадцати -20 двадцати -30 тридцати -40 сорока -50 пятидесяти -60 шестидесяти -70 семидесяти -90 девяноста -100 ста -200 двухстах -300 трехстах -400 четырехстах -500 пятистах -600 шестистах -700 семистах -800 восьмистах -900 девятистах -900 девятьсот -900 девятьюстами -1000 тысячах -1000 тысяче -1000000 миллионах -1000000 миллионе -1000000000 миллиардах -1000000000 миллиарде diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/__init__.py b/nemo_text_processing/text_normalization/ru/data/numbers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/cardinals_alternatives.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/cardinals_alternatives.tsv deleted file mode 100644 index 5afd1d6f5465..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/cardinals_alternatives.tsv +++ /dev/null @@ -1,16 +0,0 @@ -1т одна тысяча -1т одной тысячи -1т одной тысяче -1т одну тысячу -1т одной тысячей -1т одной тысяче -1млн один миллион -1млн одного миллиона -1млн одному миллиону -1млн одним миллионом -1млн одном миллионе -1млрд один миллиард -1млрд одного миллиарда -1млрд одному миллиарду -1млрд одним миллиардом -1млрд одном миллиарде \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/cardinals_nominative_case.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/cardinals_nominative_case.tsv deleted file mode 100644 index 83cfb227e2aa..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/cardinals_nominative_case.tsv +++ /dev/null @@ -1,37 +0,0 @@ -0 ноль -1 один -2 два -3 три -4 четыре -5 пять -6 шесть -7 семь -8 восемь -9 девять -10 десять -11 одиннадцать -12 двенадцать -13 тринадцать -14 четырнадцать -15 пятнадцать -16 шестнадцать -17 семнадцать -18 восемнадцать -19 девятнадцать -20 двадцать -30 тридцать -40 сорок -50 пятьдесят -60 шестьдесят -70 семьдесят -80 восемьдесят -90 девяносто -100 сто -200 двести -300 триста -400 четыреста -500 пятьсот -600 шестьсот -700 семьсот -800 восемьсот -900 девятьсот \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/decimal_delimiter.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/decimal_delimiter.tsv deleted file mode 100644 index fb796cfa1a73..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/decimal_delimiter.tsv +++ /dev/null @@ -1,15 +0,0 @@ -@@decimal_delimiter@@ целого 0.1 -@@decimal_delimiter@@ целому 0.1 -@@decimal_delimiter@@ целый 0.1 -@@decimal_delimiter@@ целого 0.1 -@@decimal_delimiter@@ целым 0.1 -@@decimal_delimiter@@ целом 0.1 -@@decimal_delimiter@@ целая -0.1 -@@decimal_delimiter@@ целой 0.1 -@@decimal_delimiter@@ целую 0.1 -@@decimal_delimiter@@ целою 0.1 -@@decimal_delimiter@@ целые -0.1 -@@decimal_delimiter@@ целых -0.1 -@@decimal_delimiter@@ целым 0.1 -@@decimal_delimiter@@ целые 0.1 -@@decimal_delimiter@@ целыми 0.1 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/decimal_endings.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/decimal_endings.tsv deleted file mode 100644 index d2c30e146bee..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/decimal_endings.tsv +++ /dev/null @@ -1,37 +0,0 @@ -10 десятая -0.1 -10 десятой 0.1 -10 десятой 0.1 -10 десятую 0.1 -10 десятою 0.1 -10 десятой 0.1 -10 десятые 0.1 -10 десятых -0.1 -10 десятым 0.1 -10 десятыми 0.1 -100 сотые -0.1 -100 сотых -0.1 -100 сотым 0.1 -100 сотыми 0.1 -100 сотая -0.1 -100 сотой 0.1 -100 сотую 0.1 -100 сотою 0.1 -1000 тысячные -0.1 -1000 тысячных -0.1 -1000 тысячным 0.1 -1000 тысячными 0.1 -1000 тысячная -0.1 -1000 тысячной 0.1 -1000 тысячную 0.1 -1000 тысячною 0.1 -10000 десятитысячная -0.1 -10000 десятитысячной 0.1 -10000 десятитысячной 0.1 -10000 десятитысячную 0.1 -10000 десятитысячною 0.1 -10000 десятитысячной 0.1 -10000 десятитысячные 0.1 -10000 десятитысячных -0.1 -10000 десятитысячным 0.1 -10000 десятитысячные 0.1 -10000 десятитысячными 0.1 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/digits_nominative_case.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/digits_nominative_case.tsv deleted file mode 100644 index c6663fb395b7..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/digits_nominative_case.tsv +++ /dev/null @@ -1,10 +0,0 @@ -0 ноль -1 один -2 два -3 три -4 четыре -5 пять -6 шесть -7 семь -8 восемь -9 девять \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/ordinal_endings.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/ordinal_endings.tsv deleted file mode 100644 index 7f37fdcf9525..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/ordinal_endings.tsv +++ /dev/null @@ -1,40 +0,0 @@ -ая-ая -ого-го -ьего-го -ьего-его -ьей-ей -ьему-ему -ьем-ем -ое-е -ые-е -ье-е -ий-ий -ьими-ими -ьим-им -ьих-их -ьи-и -ий-й -ой-й -ый-й -ыми-ми -ьими-ми -ому-му -ьему-му -ого-ого -ое-ое -ой-ой -ом-ом -ому-ому -ую-ую -ых-х -ьих-х -ые-ые -ый-ый -ыми-ыми -ым-ым -ых-ых -ую-ю -ью-ю -ая-я -ья-я -ом-м diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/ordinals.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/ordinals.tsv deleted file mode 100644 index 32b418b2e344..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/ordinals.tsv +++ /dev/null @@ -1,752 +0,0 @@ -0 нулевая 0.1 -0 нулевого 0.1 -0 нулевое 0.1 -0 нулевой 0.1 -0 нулевом 0.1 -0 нулевому 0.1 -0 нулевую 0.1 -0 нулевые -0.01 -0 нулевым 0.1 -0 нулевыми 0.1 -0 нулевых 0.1 -1 первая -0.01 -1 первого -0.01 -1 первое -0.01 -1 первой 0.1 -1 первом 0.1 -1 первому 0.1 -1 первую 0.1 -1 первые 0.1 -1 первый -0.01 -1 первым 0.1 -1 первыми 0.1 -1 первых 0.1 -2 вторая -0.01 -2 второго 0.1 -2 второе -0.01 -2 второй -0.01 -2 втором 0.1 -2 второму 0.1 -2 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-20000 двадцатитысячному -20000 двадцатитысячное -20000 двадцатитысячные -20000 двадцатитысячных -20000 двадцатитысячную diff --git a/nemo_text_processing/text_normalization/ru/data/numbers/quantity.tsv b/nemo_text_processing/text_normalization/ru/data/numbers/quantity.tsv deleted file mode 100644 index 3dca7725dc89..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/numbers/quantity.tsv +++ /dev/null @@ -1,16 +0,0 @@ -тысяч тысяч 0.1 -тысяча тысяча 0.1 -тысячи тысячи 0.1 -тыс. тысячи 0.1 -тыс тысячи -0.1 -миллион миллион 0.1 -миллионов миллионов 0.1 -миллиона миллиона 0.1 -миллиона миллиона 0.1 -млн. миллиона 0.1 -млн миллиона -0.1 -миллиарда миллиарда 0.1 -миллиард миллиард 0.1 -миллиардов миллиардов 0.1 -млрд. миллиарда 0.1 -млрд миллиарда -0.1 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/time/__init__.py b/nemo_text_processing/text_normalization/ru/data/time/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/data/time/increment_hour_cardinal.tsv b/nemo_text_processing/text_normalization/ru/data/time/increment_hour_cardinal.tsv deleted file mode 100644 index 96fd67729b88..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/time/increment_hour_cardinal.tsv +++ /dev/null @@ -1,24 +0,0 @@ -00 час -0.1 -01 два -0.1 -02 три -0.1 -03 четыре -0.1 -04 пять -0.1 -05 шесть -0.1 -06 семь -0.1 -07 восемь -0.1 -08 девять -0.1 -09 десять -0.1 -10 одиннадцать 0.1 -11 двенадцать 0.1 -12 час 0.1 -13 два 0.1 -14 три 0.1 -15 четыре 0.1 -16 пять 0.1 -17 шесть 0.1 -18 семь 0.1 -19 восемь 0.1 -20 девять 0.1 -21 десять 0.1 -22 одиннадцать 0.1 -23 двенадцать 0.1 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/time/increment_hour_ordinal.tsv b/nemo_text_processing/text_normalization/ru/data/time/increment_hour_ordinal.tsv deleted file mode 100644 index 83583e14dbb5..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/time/increment_hour_ordinal.tsv +++ /dev/null @@ -1,24 +0,0 @@ -00 первого 0.1 -01 второго -0.1 -02 третьего -0.1 -03 четвертого -0.1 -04 пятого -0.1 -05 шестого -0.1 -06 седьмого -0.1 -07 восьмого -0.1 -08 девятого -0.1 -09 десятого -0.1 -10 одиннадцатого -0.1 -11 двенадцатого -0.1 -12 первого -0.1 -13 второго 0.1 -14 третьего 0.1 -15 четвертого 0.1 -16 пятого 0.1 -17 шестого 0.1 -18 седьмого 0.1 -19 восьмого 0.1 -20 девятого 0.1 -21 десятого 0.1 -22 одиннадцатого 0.1 -23 двенадцатого 0.1 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/time/minutes_to_hour.tsv b/nemo_text_processing/text_normalization/ru/data/time/minutes_to_hour.tsv deleted file mode 100644 index 50ab97133dde..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/time/minutes_to_hour.tsv +++ /dev/null @@ -1,25 +0,0 @@ -59 одной минуты -58 двух минут -57 трех минут -56 четырех минут -55 пяти минут -54 шести минут -53 семи минут -52 восеми минут -51 девяти минут -50 десяти минут -49 одиннадцати минут -48 двенадцати минут -47 тринадцати минут -46 четырнадцати минут -45 пятнадцати минут -44 шестнадцати минут -43 семнадцати минут -42 восемьнадцати минут -41 девятнадцати минут -40 двадцати минут -39 двадцати одной минуты -38 двадцати двух минут -37 двадцати трех минут -36 двадцати четырех минут -35 двадцать пяти минут diff --git a/nemo_text_processing/text_normalization/ru/data/time/time_convert.tsv b/nemo_text_processing/text_normalization/ru/data/time/time_convert.tsv deleted file mode 100644 index b10345c4faaa..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/time/time_convert.tsv +++ /dev/null @@ -1,12 +0,0 @@ -13 1 -14 2 -15 3 -16 4 -17 5 -18 6 -19 7 -20 8 -21 9 -22 10 -23 11 -24 12 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/ru/data/utils/__init__.py b/nemo_text_processing/text_normalization/ru/data/utils/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/data/utils/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. 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integer: "тысяча один" } - - Args: - number_names: number_names for cardinal and ordinal numbers - alternative_formats: alternative number formats - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, number_names: dict, alternative_formats: dict, deterministic: bool = False): - super().__init__(name="cardinal", kind="classify", deterministic=deterministic) - - self.cardinal_numbers_default = self.get_cardinal_numbers(number_names, alternative_formats, mode="all") - self.cardinal_numbers_nominative = self.get_cardinal_numbers( - number_names, alternative_formats, mode="nominative" - ) - self.optional_graph_negative = pynini.closure( - pynutil.insert("negative: ") + pynini.cross("-", "\"true\"") + insert_space, 0, 1 - ) - - self.cardinal_numbers_with_optional_negative = ( - self.optional_graph_negative - + pynutil.insert("integer: \"") - + self.cardinal_numbers_default - + pynutil.insert("\"") - ) - - # "03" -> remove leading zeros and verbalize - leading_zeros = pynini.closure(pynini.cross("0", "")) - self.cardinal_numbers_with_leading_zeros = (leading_zeros + self.cardinal_numbers_default).optimize() - - # "123" -> "один два три" - single_digits_graph = pynini.string_file(get_abs_path("data/numbers/cardinals_nominative_case.tsv")).optimize() - single_digits_graph = pynini.compose(NEMO_DIGIT, single_digits_graph) - self.single_digits_graph = single_digits_graph + pynini.closure(insert_space + single_digits_graph) - - optional_quantity = pynini.string_file(get_abs_path("data/numbers/quantity.tsv")).optimize() - optional_quantity = pynutil.insert("quantity: \"") + optional_quantity + pynutil.insert("\"") - optional_quantity = pynini.closure( - (pynutil.add_weight(pynini.accep(NEMO_SPACE), -0.1) | insert_space) + optional_quantity, 0, 1 - ) - - serial_graph = self.get_serial_graph() - - final_graph = ( - self.optional_graph_negative - + pynutil.insert("integer: \"") - + self.cardinal_numbers_with_leading_zeros - + pynutil.insert("\"") - + optional_quantity - ).optimize() - - final_graph = pynutil.add_weight(final_graph, -0.1) - final_graph |= pynutil.insert("integer: \"") + pynutil.add_weight(serial_graph, 10) + pynutil.insert("\"") - self.final_graph = final_graph - - # to cover cases "2-х" -> "двух" (this is not covered by ordinal endings) - final_graph |= pynini.compose( - pynini.compose(NEMO_DIGIT ** (1, ...) + pynini.cross('-х', ''), final_graph), - NEMO_SIGMA + pynini.accep("х\"") + NEMO_SIGMA, - ) - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() - - def get_cardinal_numbers(self, number_names: dict, alternative_formats: dict, mode: str = "all"): - """Returns cardinal numbers names graph. - - Args: - number_names: number_names for cardinal and ordinal numbers - alternative_formats: alternative number formats - mode: "all" - to return graph that includes all Ru cases, "nominative" to return only the nominative form - """ - if mode == "all": - cardinal_names = number_names['cardinal_number_names'] - elif mode == "nominative": - cardinal_names = number_names['cardinal_names_nominative'] - else: - raise ValueError(f'{mode} is not supported.') - one_thousand_alternative = alternative_formats['one_thousand_alternative'] - separators = alternative_formats['separators'] - - cardinal_numbers = cardinal_names | pynini.compose(cardinal_names, one_thousand_alternative) - cardinal_numbers = pynini.compose(separators, cardinal_numbers) - return cardinal_numbers - - def get_serial_graph(self): - """ - Finite state transducer for classifying serial. - The serial is a combination of digits, letters and dashes, e.g.: - c325-b -> tokens { cardinal { integer: "си три два пять би" } } - """ - num_graph = self.single_digits_graph - - alpha = TO_CYRILLIC | RU_ALPHA - - delimiter = insert_space | pynini.cross("-", " ") | pynini.cross("/", " ") - letter_num = pynini.closure(alpha + delimiter, 1) + num_graph - num_letter = pynini.closure(num_graph + delimiter, 1) + alpha - num_delimiter_num = pynini.closure(num_graph + delimiter, 1) + num_graph - next_alpha_or_num = pynini.closure(delimiter + (alpha | num_graph)) - serial_graph = (letter_num | num_letter | num_delimiter_num) + next_alpha_or_num - - # at least 1 alpha and 1 digit is present - at_least_one_alpha_num = ( - NEMO_SIGMA + (RU_ALPHA | pynini.project(TO_CYRILLIC, "input")) + NEMO_SIGMA + NEMO_DIGIT + NEMO_SIGMA - ) | (NEMO_SIGMA + NEMO_DIGIT + NEMO_SIGMA + (RU_ALPHA | pynini.project(TO_CYRILLIC, "input")) + NEMO_SIGMA) - serial_graph = pynini.compose(at_least_one_alpha_num, serial_graph.optimize()).optimize() - # numbers only with 2+ delimiters - serial_graph |= ( - num_graph + delimiter + num_graph + delimiter + num_graph + pynini.closure(delimiter + num_graph) - ).optimize() - return serial_graph.optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/date.py b/nemo_text_processing/text_normalization/ru/taggers/date.py deleted file mode 100644 index d4ce6a64601b..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/date.py +++ /dev/null @@ -1,136 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_DIGIT, - NEMO_NOT_QUOTE, - NEMO_SIGMA, - GraphFst, - delete_extra_space, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for classifying date, e.g. - "01.05" -> tokens { date { day: "первое мая" } } - - Args: - number_names: number_names for cardinal and ordinal numbers - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, number_names: dict, deterministic: bool): - super().__init__(name="date", kind="classify", deterministic=deterministic) - - # Ru format: DD-MM-YYYY or DD-MM-YY - month_abbr_to_names = pynini.string_file(get_abs_path("data/months/abbr_to_name.tsv")).optimize() - - delete_sep = pynutil.add_weight(pynini.cross(".", " "), 1.09) | pynutil.add_weight( - pynini.cross(pynini.union("/", "-"), " "), 1.1 - ) - - numbers = number_names['ordinal_number_names'] - - zero = (pynutil.add_weight(pynini.cross("0", ""), -0.1)) | ( - pynutil.add_weight(pynini.cross("0", "ноль "), 0.1) - ) - zero_digit = zero + pynini.compose(NEMO_DIGIT, numbers) - digit_day = (pynini.union("1", "2", "3") + NEMO_DIGIT) | NEMO_DIGIT - digit_day = pynini.compose(digit_day, numbers) - - day = zero_digit | digit_day - day = pynini.compose( - day, pynini.difference(NEMO_SIGMA, NEMO_SIGMA + pynini.union("ой", "ая", "ых", "ые", "ыми")) - ) - day = (pynutil.insert("day: \"") + day + pynutil.insert("\"")).optimize() - - digit_month = zero_digit | pynini.compose(pynini.accep("1") + NEMO_DIGIT, numbers) - month_number_to_abbr = pynini.string_file(get_abs_path("data/months/numbers.tsv")).optimize() - month_number_to_abbr = ( - ( - ((pynutil.add_weight(pynini.cross("0", ""), -0.1) | pynini.accep("1")) + NEMO_DIGIT) | NEMO_DIGIT - ).optimize() - @ month_number_to_abbr - ).optimize() - - month_name = ( - (month_number_to_abbr @ month_abbr_to_names) | pynutil.add_weight(month_abbr_to_names, 0.1) - ).optimize() - month = ( - pynutil.insert("month: \"") + (month_name | pynutil.add_weight(digit_month, 0.1)) + pynutil.insert("\"") - ).optimize() - year = pynini.compose(((NEMO_DIGIT ** 4) | (NEMO_DIGIT ** 2)), numbers).optimize() - year |= zero_digit - - # reduce year options - year_wrong_endings = ["ую", "ая"] - year_wrong_beginning = ["две тысяча", "два тысяч", "два тысячи", "две тысяч "] - year = pynini.compose( - year, pynini.difference(NEMO_SIGMA, NEMO_SIGMA + pynini.union("ой", "ого")) - ) | pynutil.add_weight(pynini.compose(year, NEMO_SIGMA + pynini.union("ой", "ого")), -0.1) - - year_restrict1 = pynini.difference(NEMO_SIGMA, pynini.union(*year_wrong_beginning) + NEMO_SIGMA) - year_restrict2 = pynini.difference(NEMO_SIGMA, NEMO_SIGMA + pynini.union(*year_wrong_endings)) - year = pynini.compose(pynini.compose(year, year_restrict1), year_restrict2) - - year_word_singular = ["год", "года", "году", "годом", "годе"] - year_word_plural = ["годы", "годов", "годам", "годами", "годам", "годах"] - - year_word = pynini.cross("г.", pynini.union(*year_word_singular)) - year_word |= pynini.cross("гг.", pynini.union(*year_word_plural)) - year_word = (pynutil.add_weight(insert_space, -0.1) | pynutil.add_weight(pynini.accep(" "), 0.1)) + year_word - - year_optional = pynutil.insert("year: \"") + year + pynini.closure(year_word, 0, 1) + pynutil.insert("\"") - year_optional = pynini.closure(delete_sep + year_optional, 0, 1).optimize() - year_only = pynutil.insert("year: \"") + year + year_word + pynutil.insert("\"") - - tagger_graph = (day + delete_sep + month + year_optional) | year_only - - # Verbalizer - day = ( - pynutil.delete("day:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - month = ( - pynutil.delete("month:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - year = ( - pynutil.delete("year:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + delete_space - + pynutil.delete("\"") - ) - year_optional = pynini.closure(delete_extra_space + year, 0, 1) - graph_dmy = day + delete_extra_space + month + year_optional - verbalizer_graph = (graph_dmy | year) + delete_space - - self.final_graph = pynini.compose(tagger_graph, verbalizer_graph).optimize() - self.fst = pynutil.insert("day: \"") + self.final_graph + pynutil.insert("\"") - self.fst = self.add_tokens(self.fst).optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/decimals.py b/nemo_text_processing/text_normalization/ru/taggers/decimals.py deleted file mode 100644 index de29513a388c..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/decimals.py +++ /dev/null @@ -1,107 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from collections import defaultdict - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, NEMO_SPACE, GraphFst, insert_space -from nemo_text_processing.text_normalization.en.utils import load_labels -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - -delete_space = pynutil.delete(" ") - - -def prepare_labels_for_insertion(file_path: str): - """ - Read the file and creates a union insertion graph - - Args: - file_path: path to a file (3 columns: a label type e.g. - "@@decimal_delimiter@@", a label e.g. "целого", and a weight e.g. "0.1"). - - Returns dictionary mapping from label type to an fst that inserts the labels with the specified weights. - - """ - labels = load_labels(file_path) - mapping = defaultdict(list) - for k, v, w in labels: - mapping[k].append((v, w)) - - for k in mapping: - mapping[k] = ( - insert_space - + pynini.union(*[pynutil.add_weight(pynutil.insert(end), weight) for end, weight in mapping[k]]) - ).optimize() - return mapping - - -class DecimalFst(GraphFst): - """ - Finite state transducer for classifying decimal, e.g. - "1,08" -> tokens { decimal { integer_part: "одно целая" fractional_part: "восемь сотых} } - - Args: - cardinal: CardinalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, deterministic: bool = False): - super().__init__(name="decimal", kind="classify", deterministic=deterministic) - - integer_part = cardinal.cardinal_numbers_default - cardinal_numbers_with_leading_zeros = cardinal.cardinal_numbers_with_leading_zeros - - delimiter_map = prepare_labels_for_insertion(get_abs_path("data/numbers/decimal_delimiter.tsv")) - delimiter = ( - pynini.cross(",", "") - + delimiter_map['@@decimal_delimiter@@'] - + pynini.closure(pynutil.add_weight(pynutil.insert(" и"), 0.5), 0, 1) - ).optimize() - - decimal_endings_map = prepare_labels_for_insertion(get_abs_path("data/numbers/decimal_endings.tsv")) - - self.integer_part = integer_part + delimiter - graph_integer = pynutil.insert("integer_part: \"") + self.integer_part + pynutil.insert("\"") - - graph_fractional = NEMO_DIGIT @ cardinal_numbers_with_leading_zeros + decimal_endings_map['10'] - graph_fractional |= (NEMO_DIGIT + NEMO_DIGIT) @ cardinal_numbers_with_leading_zeros + decimal_endings_map[ - '100' - ] - graph_fractional |= ( - NEMO_DIGIT + NEMO_DIGIT + NEMO_DIGIT - ) @ cardinal_numbers_with_leading_zeros + decimal_endings_map['1000'] - graph_fractional |= ( - NEMO_DIGIT + NEMO_DIGIT + NEMO_DIGIT + NEMO_DIGIT - ) @ cardinal_numbers_with_leading_zeros + decimal_endings_map['10000'] - - self.optional_quantity = pynini.string_file(get_abs_path("data/numbers/quantity.tsv")).optimize() - - self.graph_fractional = graph_fractional - graph_fractional = pynutil.insert("fractional_part: \"") + graph_fractional + pynutil.insert("\"") - optional_quantity = pynini.closure( - (pynutil.add_weight(pynini.accep(NEMO_SPACE), -0.1) | insert_space) - + pynutil.insert("quantity: \"") - + self.optional_quantity - + pynutil.insert("\""), - 0, - 1, - ) - self.final_graph = ( - cardinal.optional_graph_negative + graph_integer + insert_space + graph_fractional + optional_quantity - ) - - self.final_graph = self.add_tokens(self.final_graph) - self.fst = self.final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/electronic.py b/nemo_text_processing/text_normalization/ru/taggers/electronic.py deleted file mode 100644 index 22530a28b80a..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/electronic.py +++ /dev/null @@ -1,111 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_NOT_QUOTE, - GraphFst, - delete_space, - insert_space, -) -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA, TO_CYRILLIC -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for classifying electronic: email addresses - e.g. "ab@nd.ru" -> electronic { username: "эй би собака эн ди точка ру" } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="classify", deterministic=deterministic) - - # tagger - accepted_symbols = [] - with open(get_abs_path("data/electronic/symbols.tsv"), 'r', encoding='utf-8') as f: - for line in f: - symbol, _ = line.split('\t') - accepted_symbols.append(pynini.accep(symbol)) - username = ( - pynutil.insert("username: \"") - + NEMO_ALPHA - + pynini.closure(NEMO_ALPHA | NEMO_DIGIT | pynini.union(*accepted_symbols)) - + pynutil.insert("\"") - + pynini.cross('@', ' ') - ) - domain_graph = ( - NEMO_ALPHA - + (pynini.closure(NEMO_ALPHA | NEMO_DIGIT | pynini.accep('-') | pynini.accep('.'))) - + (NEMO_ALPHA | NEMO_DIGIT) - ) - domain_graph = pynutil.insert("domain: \"") + domain_graph + pynutil.insert("\"") - tagger_graph = (username + domain_graph).optimize() - - # verbalizer - graph_digit = pynini.string_file(get_abs_path("data/numbers/digits_nominative_case.tsv")).optimize() - graph_symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")).optimize() - user_name = ( - pynutil.delete("username:") - + delete_space - + pynutil.delete("\"") - + ( - pynini.closure( - pynutil.add_weight(graph_digit + insert_space, 1.09) - | pynutil.add_weight(pynini.closure(graph_symbols + pynutil.insert(" ")), 1.09) - | pynutil.add_weight(NEMO_NOT_QUOTE + insert_space, 1.1) - ) - ) - + pynutil.delete("\"") - ) - - domain_default = ( - pynini.closure(NEMO_NOT_QUOTE + insert_space) - + pynini.cross(".", "точка ") - + NEMO_NOT_QUOTE - + pynini.closure(insert_space + NEMO_NOT_QUOTE) - ) - - server_default = ( - pynini.closure((graph_digit | NEMO_ALPHA) + insert_space, 1) - + pynini.closure(graph_symbols + insert_space) - + pynini.closure((graph_digit | NEMO_ALPHA) + insert_space, 1) - ) - server_common = pynini.string_file(get_abs_path("data/electronic/server_name.tsv")) + insert_space - domain_common = pynini.cross(".", "точка ") + pynini.string_file(get_abs_path("data/electronic/domain.tsv")) - domain = ( - pynutil.delete("domain:") - + delete_space - + pynutil.delete("\"") - + (pynutil.add_weight(server_common, 1.09) | pynutil.add_weight(server_default, 1.1)) - + (pynutil.add_weight(domain_common, 1.09) | pynutil.add_weight(domain_default, 1.1)) - + delete_space - + pynutil.delete("\"") - ) - - graph = user_name + delete_space + pynutil.insert("собака ") + delete_space + domain + delete_space - # replace all latin letters with their Ru verbalization - verbalizer_graph = (graph.optimize() @ (pynini.closure(TO_CYRILLIC | RU_ALPHA | pynini.accep(" ")))).optimize() - verbalizer_graph = verbalizer_graph.optimize() - - self.final_graph = (tagger_graph @ verbalizer_graph).optimize() - self.fst = self.add_tokens(pynutil.insert("username: \"") + self.final_graph + pynutil.insert("\"")).optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/measure.py b/nemo_text_processing/text_normalization/ru/taggers/measure.py deleted file mode 100644 index a4c60f49ce03..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/measure.py +++ /dev/null @@ -1,170 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NON_BREAKING_SPACE, - NEMO_NOT_QUOTE, - NEMO_SPACE, - GraphFst, - insert_space, -) -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for classifying measure, e.g. - "2 кг" -> measure { cardinal { integer: "два килограма" } } - This class also converts words containing numbers and letters - e.g. "тест-8" —> "тест восемь" - e.g. "тест-1,02" —> "тест одна целая две сотых" - - Args: - cardinal: CardinalFst - decimal: DecimalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="measure", kind="classify", deterministic=deterministic) - - # adding weight to make sure the space is preserved for ITN - delete_space = pynini.closure( - pynutil.add_weight(pynutil.delete(pynini.union(NEMO_SPACE, NEMO_NON_BREAKING_SPACE)), -1), 0, 1 - ) - - cardinal_graph = cardinal.cardinal_numbers_default - cardinal_graph_nominative = cardinal.cardinal_numbers_nominative - graph_unit = pynini.string_file(get_abs_path("data/measurements.tsv")) - optional_graph_negative = cardinal.optional_graph_negative - - space_for_units = ( - pynutil.add_weight(pynutil.insert(NEMO_NON_BREAKING_SPACE), -0.1) - | pynutil.add_weight(pynutil.insert(NEMO_SPACE), 0.1) - ).optimize() - slash_unit = (pynini.cross("/", "в") | pynini.cross("/", "за")) + space_for_units + graph_unit - - unit_slash_unit = pynutil.add_weight(graph_unit + space_for_units + slash_unit, -0.1) - default_units = pynutil.insert("units: \"") + (graph_unit | unit_slash_unit) + pynutil.insert("\"") - slash_units = pynutil.insert("units: \"") + slash_unit + pynutil.insert("\"") - subgraph_decimal = decimal.final_graph + ((delete_space + default_units) | slash_units) - - cardinal_space = ( - pynutil.insert("cardinal { ") - + optional_graph_negative - + pynutil.insert("integer: \"") - + cardinal_graph - + ( - (delete_space + pynutil.insert("\"") + pynutil.insert(" } ") + default_units) - | (pynutil.insert("\"") + pynutil.insert(" } ") + slash_units) - ) - ) - - cardinal_optional_dash_alpha = ( - pynutil.insert("cardinal { integer: \"") - + cardinal_graph - + pynini.closure(pynini.cross('-', ''), 0, 1) - + pynutil.insert("\" } units: \"") - + pynini.closure(RU_ALPHA, 1) - + pynutil.insert("\"") - ) - - alpha_optional_dash_cardinal = ( - pynutil.insert("units: \"") - + pynini.closure(RU_ALPHA, 1) - + pynini.closure(pynini.cross('-', ''), 0, 1) - + pynutil.insert("\"") - + pynutil.insert(" cardinal { integer: \"") - + cardinal_graph_nominative - + pynutil.insert("\" } preserve_order: true") - ) - - decimal_dash_alpha = ( - decimal.final_graph - + pynini.cross('-', '') - + pynutil.insert(" units: \"") - + pynini.closure(RU_ALPHA, 1) - + pynutil.insert("\"") - ) - - alpha_dash_decimal = ( - pynutil.insert("units: \"") - + pynini.closure(RU_ALPHA, 1) - + pynini.cross('-', '') - + pynutil.insert("\" ") - + decimal.final_graph - + pynutil.insert(" preserve_order: true") - ) - - self.tagger_graph_default = (subgraph_decimal | cardinal_space).optimize() - - tagger_graph = ( - self.tagger_graph_default - | cardinal_optional_dash_alpha - | alpha_optional_dash_cardinal - | decimal_dash_alpha - | alpha_dash_decimal - ).optimize() - - # verbalizer - unit = pynutil.delete("units: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") + delete_space - - optional_sign = pynini.closure(pynini.cross("negative: \"true\" ", "минус "), 0, 1) - integer = pynutil.delete(" \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - integer_part = pynutil.delete("integer_part:") + integer - fractional_part = pynutil.delete("fractional_part:") + integer - optional_quantity_part = pynini.closure( - pynini.accep(" ") - + pynutil.delete("quantity: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\""), - 0, - 1, - ) - graph_decimal = optional_sign + integer_part + pynini.accep(" ") + fractional_part + optional_quantity_part - - graph_decimal = pynutil.delete("decimal {") + delete_space + graph_decimal + delete_space + pynutil.delete("}") - - graph_cardinal = ( - pynutil.delete("cardinal {") - + delete_space - + optional_sign - + pynutil.delete("integer: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + delete_space - + pynutil.delete("}") - ) - - verbalizer_graph = (graph_cardinal | graph_decimal) + delete_space + insert_space + unit - - # SH adds "preserve_order: true" by default - preserve_order = pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space - verbalizer_graph |= ( - unit - + insert_space - + (graph_cardinal | graph_decimal) - + delete_space - + pynini.closure(preserve_order, 0, 1) - ) - self.verbalizer_graph = verbalizer_graph.optimize() - - final_graph = (tagger_graph @ verbalizer_graph).optimize() - self.fst = self.add_tokens( - pynutil.insert("cardinal { integer: \"") + final_graph + pynutil.insert("\" }") - ).optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/money.py b/nemo_text_processing/text_normalization/ru/taggers/money.py deleted file mode 100644 index c08723ae8c3c..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/money.py +++ /dev/null @@ -1,95 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, NEMO_SIGMA, NEMO_SPACE, GraphFst -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for classifying money, e.g. - "5руб." -> money { "пять рублей" } - - Args: - cardinal: CardinalFst - decimal: DecimalFst - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, cardinal: GraphFst, decimal: GraphFst, deterministic: bool = True): - super().__init__(name="money", kind="classify", deterministic=deterministic) - cardinal_graph = cardinal.cardinal_numbers_default - decimal_graph = decimal.final_graph - - unit_singular = pynini.string_file(get_abs_path("data/currency/currency_singular.tsv")) - unit_plural = pynini.string_file(get_abs_path("data/currency/currency_plural.tsv")) - - # adding weight to make sure the space is preserved for ITN - optional_delimiter = pynini.closure(pynutil.add_weight(pynini.cross(NEMO_SPACE, ""), -100), 0, 1) - graph_unit_singular = ( - optional_delimiter + pynutil.insert(" currency: \"") + unit_singular + pynutil.insert("\"") - ) - graph_unit_plural = optional_delimiter + pynutil.insert(" currency: \"") + unit_plural + pynutil.insert("\"") - - one = pynini.compose(pynini.accep("1"), cardinal_graph).optimize() - singular_graph = pynutil.insert("integer_part: \"") + one + pynutil.insert("\"") + graph_unit_singular - - graph_decimal = decimal_graph + graph_unit_plural - - graph_integer = ( - pynutil.insert("integer_part: \"") - + ((NEMO_SIGMA - "1") @ cardinal_graph) - + pynutil.insert("\"") - + (graph_unit_plural) - ) - - graph_integer |= singular_graph - tagger_graph = (graph_integer.optimize() | graph_decimal.optimize()).optimize() - - # verbalizer - integer = pynutil.delete("\"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - integer_part = pynutil.delete("integer_part: ") + integer - - unit = ( - pynutil.delete("currency: ") - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - unit = pynini.accep(NEMO_SPACE) + unit - - verbalizer_graph_cardinal = (integer_part + unit).optimize() - - fractional_part = pynutil.delete("fractional_part: ") + integer - optional_quantity = pynini.closure(pynini.accep(NEMO_SPACE) + pynutil.delete("quantity: ") + integer, 0, 1) - - verbalizer_graph_decimal = ( - pynutil.delete('decimal { ') - + integer_part - + pynini.accep(" ") - + fractional_part - + optional_quantity - + pynutil.delete(" }") - + unit - ) - - verbalizer_graph = (verbalizer_graph_cardinal | verbalizer_graph_decimal).optimize() - - self.final_graph = (tagger_graph @ verbalizer_graph).optimize() - self.fst = self.add_tokens( - pynutil.insert("integer_part: \"") + self.final_graph + pynutil.insert("\"") - ).optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/number_names.py b/nemo_text_processing/text_normalization/ru/taggers/number_names.py deleted file mode 100644 index 048b5f43ecb9..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/number_names.py +++ /dev/null @@ -1,138 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# Copyright 2017 Google Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Adapted from https://github.com/google/TextNormalizationCoveringGrammars -# Russian minimally supervised number grammar. -# -# Supports cardinals and ordinals in all inflected forms. -# -# The language-specific acceptor G was compiled with digit, teen, decade, -# century, and big power-of-ten preterminals. The lexicon transducer is -# highly ambiguous, but no LM is used. - -# Intersects the universal factorization transducer (F) with language-specific -# acceptor (G). - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA -from nemo_text_processing.text_normalization.ru.utils import get_abs_path, load_labels -from pynini.lib import pynutil, rewrite - - -def get_number_names(): - """ - Creates numbers names. - - Based on: 1) Gorman, K., and Sproat, R. 2016. Minimally supervised number normalization. - Transactions of the Association for Computational Linguistics 4: 507-519. - and 2) Ng, A. H., Gorman, K., and Sproat, R. 2017. - Minimally supervised written-to-spoken text normalization. In ASRU, pages 665-670. - """ - a = pynini.Far(get_abs_path('data/utils/util_arithmetic.far'), mode='r') - d = a['DELTA_STAR'] - f = a['IARITHMETIC_RESTRICTED'] - g = pynini.Fst.read(get_abs_path('data/utils/g.fst')) - fg = (d @ (f @ (f @ (f @ g).optimize()).optimize()).optimize()).optimize() - assert rewrite.top_rewrite("230", fg) == "(+ 200 30 +)" - - # Compiles lexicon transducers (L). - cardinal_name_nominative = pynini.string_file(get_abs_path("data/numbers/1_cardinals_nominative.tsv")).optimize() - cardinal_name_genitive = pynini.string_file(get_abs_path("data/numbers/2_cardinals_genitive.tsv")).optimize() - cardinal_name_dative = pynini.string_file(get_abs_path("data/numbers/3_cardinals_dative.tsv")).optimize() - cardinal_name_accusative = pynini.string_file(get_abs_path("data/numbers/4_cardinals_accusative.tsv")).optimize() - cardinal_name_instrumental = pynini.string_file( - get_abs_path("data/numbers/5_cardinals_instrumental.tsv") - ).optimize() - cardinal_name_prepositional = pynini.string_file( - get_abs_path("data/numbers/6_cardinals_prepositional.tsv") - ).optimize() - - cardinal_name_nominative = ( - pynini.closure(cardinal_name_nominative + pynini.accep(" ")) + cardinal_name_nominative - ).optimize() - cardinal_l = pynutil.add_weight(cardinal_name_nominative, -0.1) - for case in [ - pynutil.add_weight(cardinal_name_genitive, 0.1).optimize(), - pynutil.add_weight(cardinal_name_dative, 0.1).optimize(), - pynutil.add_weight(cardinal_name_accusative, 0.1).optimize(), - pynutil.add_weight(cardinal_name_instrumental, 0.1).optimize(), - pynutil.add_weight(cardinal_name_prepositional, 0.1).optimize(), - ]: - cardinal_l |= (pynini.closure(case + pynini.accep(" ")) + case).optimize() - - # Numbers in nominative case (to use, for example, with telephone or serial_graph (in cardinals)) - cardinal_names_nominative_l = ( - pynini.closure(cardinal_name_nominative + pynini.accep(" ")) + cardinal_name_nominative - ).optimize() - - # Convert e.g. "(* 5 1000 *)" back to "5000" so complex ordinals will be formed correctly, - # e.g. "пятитысячный" will eventually be formed. (If we didn't do this, the incorrect phrase - # "пять тысячный" would be formed). - # We do this for all thousands from "(*2 1000 *)" —> "2000" to "(*20 1000 *)" —> "20000". - # We do not go higher, in order to prevent the WFST graph becoming even larger. - complex_numbers = pynini.cross("(* 2 1000 *)", "2000") - for number in range(3, 21): - complex_numbers |= pynini.cross(f"(* {number} 1000 *)", f"{number}000") - - complex_numbers = ( - NEMO_SIGMA + pynutil.add_weight(complex_numbers, -1) + pynini.closure(pynini.union(" ", ")", "(", "+", "*")) - ).optimize() - fg_ordinal = pynutil.add_weight(pynini.compose(fg, complex_numbers), -1) | fg - ordinal_name = pynini.string_file(get_abs_path("data/numbers/ordinals.tsv")) - ordinal_l = (pynini.closure(cardinal_name_nominative + pynini.accep(" ")) + ordinal_name).optimize() - - # Composes L with the leaf transducer (P), then composes that with FG. - p = a['LEAVES'] - number_names = {} - number_names['ordinal_number_names'] = (fg_ordinal @ (p @ ordinal_l)).optimize() - number_names['cardinal_number_names'] = (fg @ (p @ cardinal_l)).optimize() - number_names['cardinal_names_nominative'] = (fg @ (p @ cardinal_names_nominative_l)).optimize() - return number_names - - -def get_alternative_formats(): - """ - Utils to get alternative formats for numbers. - """ - one_alternatives = load_labels(get_abs_path('data/numbers/cardinals_alternatives.tsv')) - one_thousand_map = [] - for k in one_alternatives: - default, alternative = k - one_thousand_map.append((alternative.split()[1], alternative)) - one_thousand_map = pynini.string_map(one_thousand_map) - - one_thousand_alternative = pynini.cdrewrite(one_thousand_map, "[BOS]", "", NEMO_SIGMA) - - # Adapted from - # https://github.com/google/TextNormalizationCoveringGrammars/blob/master/src/universal/thousands_punct.grm - # Specifies common ways of delimiting thousands in digit strings. - t = pynini.Far(get_abs_path('data/utils/universal_thousands_punct.far')) - separators = ( - pynutil.add_weight(t['dot_thousands'], 0.1) - | pynutil.add_weight(t['no_delimiter'], -0.1) - | pynutil.add_weight(t['space_thousands'], 0.1) - ) - alternative_formats = {} - alternative_formats['one_thousand_alternative'] = one_thousand_alternative.optimize() - alternative_formats['separators'] = separators.optimize() - return alternative_formats - - -if __name__ == '__main__': - from nemo_text_processing.text_normalization.en.graph_utils import generator_main - - numbers = get_number_names() - for k, v in numbers.items(): - generator_main(f'{k}.far', {k: v}) diff --git a/nemo_text_processing/text_normalization/ru/taggers/ordinal.py b/nemo_text_processing/text_normalization/ru/taggers/ordinal.py deleted file mode 100644 index 9a09e40636d8..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/ordinal.py +++ /dev/null @@ -1,66 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Adapted from https://github.com/google/TextNormalizationCoveringGrammars -# Russian minimally supervised number grammar. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_SIGMA, GraphFst -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for classifying cardinals, e.g. - "2" -> ordinal { integer: "второе" } } - - Args: - number_names: number_names for cardinal and ordinal numbers - alternative_formats: alternative format for cardinal and ordinal numbers - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, number_names: dict, alternative_formats: dict, deterministic=False): - super().__init__(name="ordinal", kind="classify", deterministic=deterministic) - - one_thousand_alternative = alternative_formats['one_thousand_alternative'] - separators = alternative_formats['separators'] - - ordinal = number_names['ordinal_number_names'] - - ordinal |= ordinal @ one_thousand_alternative - ordinal_numbers = separators @ ordinal - - # to handle cases like 2-ая - endings = pynini.string_file(get_abs_path("data/numbers/ordinal_endings.tsv")) - not_dash = pynini.closure(pynini.difference(NEMO_SIGMA, "-")) - del_ending = pynini.cdrewrite(pynini.cross("-" + not_dash, ""), "", "[EOS]", NEMO_SIGMA) - ordinal_numbers_marked = ( - ((separators @ ordinal).optimize() + pynini.accep("-") + not_dash).optimize() - @ (NEMO_SIGMA + endings).optimize() - @ del_ending - ).optimize() - - self.ordinal_numbers = ordinal_numbers - # "03" -> remove leading zeros and verbalize - leading_zeros = pynini.closure(pynini.cross("0", "")) - self.ordinal_numbers_with_leading_zeros = (leading_zeros + ordinal_numbers).optimize() - - final_graph = (ordinal_numbers | ordinal_numbers_marked).optimize() - final_graph = pynutil.insert("integer: \"") + final_graph + pynutil.insert("\"") - final_graph = self.add_tokens(final_graph) - self.fst = final_graph.optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/telephone.py b/nemo_text_processing/text_normalization/ru/taggers/telephone.py deleted file mode 100644 index 142242e8a4b7..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/telephone.py +++ /dev/null @@ -1,78 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_DIGIT, GraphFst, delete_space, insert_space -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA_OR_SPACE -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for classifying telephone, which includes country code, number part and extension - - E.g - "8-913-983-56-01" -> telephone { number_part: "восемь девятьсот тринадцать девятьсот восемьдесят три пятьдесят шесть ноль один" } - - Args: - number_names: number_names for cardinal and ordinal numbers - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, number_names: dict, deterministic: bool = True): - super().__init__(name="telephone", kind="classify", deterministic=deterministic) - - separator = pynini.cross("-", " ") # between components - number = number_names["cardinal_names_nominative"] - - country_code = ( - pynutil.insert("country_code: \"") - + pynini.closure(pynutil.add_weight(pynutil.delete("+"), 0.1), 0, 1) - + number - + separator - + pynutil.insert("\"") - ) - optional_country_code = pynini.closure(country_code + insert_space, 0, 1) - - number_part = ( - NEMO_DIGIT ** 3 @ number - + separator - + NEMO_DIGIT ** 3 @ number - + separator - + NEMO_DIGIT ** 2 @ number - + separator - + NEMO_DIGIT ** 2 @ (pynini.closure(pynini.cross("0", "ноль ")) + number) - ) - number_part = pynutil.insert("number_part: \"") + number_part + pynutil.insert("\"") - tagger_graph = (optional_country_code + number_part).optimize() - - # verbalizer - verbalizer_graph = pynini.closure( - pynutil.delete("country_code: \"") - + pynini.closure(RU_ALPHA_OR_SPACE, 1) - + pynutil.delete("\"") - + delete_space, - 0, - 1, - ) - verbalizer_graph += ( - pynutil.delete("number_part: \"") + pynini.closure(RU_ALPHA_OR_SPACE, 1) + pynutil.delete("\"") - ) - verbalizer_graph = verbalizer_graph.optimize() - - self.final_graph = (tagger_graph @ verbalizer_graph).optimize() - self.fst = self.add_tokens( - pynutil.insert("number_part: \"") + self.final_graph + pynutil.insert("\"") - ).optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/time.py b/nemo_text_processing/text_normalization/ru/taggers/time.py deleted file mode 100644 index bb97f36ea31f..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/time.py +++ /dev/null @@ -1,111 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.ru.utils import get_abs_path -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for classifying time, e.g. - "02:15" -> time { hours: "два часа пятнадцать минут" } - - Args: - number_names: number_names for cardinal and ordinal numbers - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, number_names: dict, deterministic: bool = True): - super().__init__(name="time", kind="classify", deterministic=deterministic) - - increment_hour_ordinal = pynini.string_file(get_abs_path("data/time/increment_hour_ordinal.tsv")) - increment_hour_cardinal = pynini.string_file(get_abs_path("data/time/increment_hour_cardinal.tsv")) - convert_hour = pynini.string_file(get_abs_path("data/time/time_convert.tsv")) - - number = pynini.closure(pynini.cross("0", ""), 0, 1) + number_names['cardinal_names_nominative'] - hour_options = pynini.project(increment_hour_ordinal, "input") - hour_options = hour_options | pynini.project(convert_hour, "output") - - hour_exeption_ends_with_one = pynini.union(*["01", "21"]) - hour_exeption_ends_rest = pynini.union(*["02", "03", "04", "22", "23"]) - hour_other = ( - pynini.difference(hour_options, pynini.union(hour_exeption_ends_with_one, hour_exeption_ends_rest)) - ).optimize() - - hour = hour_exeption_ends_with_one @ number + pynutil.insert(" час") - hour |= hour_exeption_ends_rest @ number + pynutil.insert(" часа") - hour |= hour_other @ number + pynutil.insert(" часов") - - optional_and = pynini.closure(pynutil.insert("и "), 0, 1) - digits = pynini.union(*[str(x) for x in range(10)]) - mins_start = pynini.union(*"012345") - mins_options = mins_start + digits - mins_exception_ends_with_one = mins_start + pynini.accep("1") - mins_exception_ends_rest = pynini.difference( - mins_start + pynini.union(*"234"), pynini.union(*["12", "13", "14"]) - ) - mins_other = pynini.difference( - mins_options, pynini.union(mins_exception_ends_with_one, mins_exception_ends_rest) - ) - - minutes = mins_exception_ends_with_one @ number + pynutil.insert(" минута") - minutes |= mins_exception_ends_rest @ number + pynutil.insert(" минуты") - minutes |= mins_other @ number + pynutil.insert(" минут") - self.minutes = minutes.optimize() - # 17:15 -> "семнадцать часов и пятнадцать минут" - hm = ( - pynutil.insert("hours: \"") - + hour.optimize() - + pynutil.insert("\"") - + (pynini.cross(":", " ") + pynutil.insert("minutes: \"") + optional_and + minutes.optimize()) - + pynutil.insert("\"") - + pynutil.insert(" preserve_order: true") - ) - h = pynutil.insert("hours: \"") + hour + pynutil.insert("\"") + pynutil.delete(":00") - self.graph_preserve_order = (hm | h).optimize() - - # 17:15 -> "пятнадцать минут шестого" - # Requires permutations for the correct verbalization - self.increment_hour_ordinal = pynini.compose(hour_options, increment_hour_ordinal).optimize() - m_next_h = ( - pynutil.insert("hours: \"") - + self.increment_hour_ordinal - + pynutil.insert("\"") - + pynini.cross(":", " ") - + pynutil.insert("minutes: \"") - + minutes - + pynutil.insert("\"") - ) - - # 17:45 -> "без пятнадцати минут шесть" - # Requires permutations for the correct verbalization - self.mins_to_h = pynini.string_file(get_abs_path("data/time/minutes_to_hour.tsv")).optimize() - self.increment_hour_cardinal = pynini.compose(hour_options, increment_hour_cardinal).optimize() - m_to_h = ( - pynutil.insert("hours: \"") - + self.increment_hour_cardinal - + pynutil.insert("\"") - + pynini.cross(":", " ") - + pynutil.insert("minutes: \"без ") - + self.mins_to_h - + pynutil.insert("\"") - ) - - self.final_graph = m_next_h | self.graph_preserve_order | m_to_h - self.fst = self.add_tokens(self.final_graph) - self.fst = self.fst.optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/tokenize_and_classify.py b/nemo_text_processing/text_normalization/ru/taggers/tokenize_and_classify.py deleted file mode 100644 index 676bc575511b..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,142 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.taggers.punctuation import PunctuationFst -from nemo_text_processing.text_normalization.ru.taggers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.ru.taggers.date import DateFst -from nemo_text_processing.text_normalization.ru.taggers.decimals import DecimalFst -from nemo_text_processing.text_normalization.ru.taggers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.ru.taggers.measure import MeasureFst -from nemo_text_processing.text_normalization.ru.taggers.money import MoneyFst -from nemo_text_processing.text_normalization.ru.taggers.number_names import get_alternative_formats, get_number_names -from nemo_text_processing.text_normalization.ru.taggers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.ru.taggers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.ru.taggers.time import TimeFst -from nemo_text_processing.text_normalization.ru.taggers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.ru.taggers.word import WordFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased. - For deployment, this grammar will be compiled and exported to OpenFst Finite State Archive (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - """ - - def __init__( - self, - input_case: str, - deterministic: bool = False, - cache_dir: str = None, - overwrite_cache: bool = False, - whitelist: str = None, - ): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - if deterministic: - raise ValueError( - 'Ru TN only supports non-deterministic cases and produces multiple normalization options.' - ) - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - whitelist_file = os.path.basename(whitelist) if whitelist else "" - far_file = os.path.join( - cache_dir, f"_{input_case}_ru_tn_{deterministic}_deterministic{whitelist_file}.far" - ) - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - logging.info(f"ClassifyFst.fst was restored from {far_file}.") - else: - logging.info(f"Creating ClassifyFst grammars. This might take some time...") - number_names = get_number_names() - alternative_formats = get_alternative_formats() - - self.cardinal = CardinalFst( - number_names=number_names, alternative_formats=alternative_formats, deterministic=deterministic - ) - cardinal_graph = self.cardinal.fst - - self.ordinal = OrdinalFst( - number_names=number_names, alternative_formats=alternative_formats, deterministic=deterministic - ) - ordinal_graph = self.ordinal.fst - - self.decimal = DecimalFst(cardinal=self.cardinal, deterministic=deterministic) - decimal_graph = self.decimal.fst - - self.measure = MeasureFst(cardinal=self.cardinal, decimal=self.decimal, deterministic=deterministic) - measure_graph = self.measure.fst - self.date = DateFst(number_names=number_names, deterministic=deterministic) - date_graph = self.date.fst - word_graph = WordFst(deterministic=deterministic).fst - self.time = TimeFst(number_names=number_names, deterministic=deterministic) - time_graph = self.time.fst - self.telephone = TelephoneFst(number_names=number_names, deterministic=deterministic) - telephone_graph = self.telephone.fst - self.electronic = ElectronicFst(deterministic=deterministic) - electronic_graph = self.electronic.fst - self.money = MoneyFst(cardinal=self.cardinal, decimal=self.decimal, deterministic=deterministic) - money_graph = self.money.fst - self.whitelist = WhiteListFst(input_case=input_case, deterministic=deterministic, input_file=whitelist) - whitelist_graph = self.whitelist.fst - punct_graph = PunctuationFst(deterministic=deterministic).fst - - classify = ( - pynutil.add_weight(whitelist_graph, 1.01) - | pynutil.add_weight(time_graph, 1.1) - | pynutil.add_weight(date_graph, 1.09) - | pynutil.add_weight(decimal_graph, 1.1) - | pynutil.add_weight(measure_graph, 0.9) - | pynutil.add_weight(cardinal_graph, 1.1) - | pynutil.add_weight(ordinal_graph, 1.1) - | pynutil.add_weight(money_graph, 1.1) - | pynutil.add_weight(telephone_graph, 1.1) - | pynutil.add_weight(electronic_graph, 1.1) - | pynutil.add_weight(word_graph, 100) - ) - - punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }") - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }") - token_plus_punct = ( - pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct) - ) - - graph = token_plus_punct + pynini.closure(pynutil.add_weight(delete_extra_space, 1.1) + token_plus_punct) - graph = delete_space + graph + delete_space - - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"tokenize_and_classify": self.fst}) - logging.info(f"ClassifyFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/ru/taggers/whitelist.py b/nemo_text_processing/text_normalization/ru/taggers/whitelist.py deleted file mode 100644 index 85182920806b..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/whitelist.py +++ /dev/null @@ -1,63 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_CHAR, GraphFst, convert_space -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA, TO_CYRILLIC -from nemo_text_processing.text_normalization.ru.utils import get_abs_path, load_labels -from pynini.lib import pynutil - - -class WhiteListFst(GraphFst): - """ - Finite state transducer for classifying whitelist, e.g. - misses -> tokens { name: "mrs" } - for non-deterministic case: "Dr. Abc" -> - tokens { name: "drive" } tokens { name: "Abc" } - tokens { name: "doctor" } tokens { name: "Abc" } - tokens { name: "Dr." } tokens { name: "Abc" } - This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv". - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - input_file: path to a file with whitelist replacements - """ - - def __init__(self, input_case: str, deterministic: bool = True, input_file: str = None): - super().__init__(name="whitelist", kind="classify", deterministic=deterministic) - - def _get_whitelist_graph(input_case, file): - whitelist = load_labels(file) - if input_case == "lower_cased": - whitelist = [[x[0].lower()] + x[1:] for x in whitelist] - else: - whitelist = [[x[0].lower()] + x[1:] for x in whitelist] - graph = pynini.string_map(whitelist) - return graph - - graph = _get_whitelist_graph(input_case, get_abs_path("data/whitelist.tsv")) - - if input_file: - graph = _get_whitelist_graph(input_case, input_file) - - units_graph = _get_whitelist_graph(input_case, file=get_abs_path("data/measurements.tsv")) - # do not replace single letter units, like `м`, `°` and `%` will be replaced - units_graph = pynini.compose((NEMO_CHAR ** (2, ...) | pynini.difference(NEMO_CHAR, RU_ALPHA)), units_graph) - graph |= units_graph.optimize() - graph |= TO_CYRILLIC + pynini.closure(pynutil.insert(" ") + TO_CYRILLIC) - - self.final_graph = convert_space(graph) - self.fst = (pynutil.insert("name: \"") + self.final_graph + pynutil.insert("\"")).optimize() diff --git a/nemo_text_processing/text_normalization/ru/taggers/word.py b/nemo_text_processing/text_normalization/ru/taggers/word.py deleted file mode 100644 index 16743d28b574..000000000000 --- a/nemo_text_processing/text_normalization/ru/taggers/word.py +++ /dev/null @@ -1,33 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_SPACE, GraphFst -from pynini.lib import pynutil - - -class WordFst(GraphFst): - """ - Finite state transducer for classifying word. - e.g. sleep -> tokens { name: "sleep" } - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="word", kind="classify") - word = pynutil.insert("name: \"") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert("\"") - self.fst = word.optimize() diff --git a/nemo_text_processing/text_normalization/ru/utils.py b/nemo_text_processing/text_normalization/ru/utils.py deleted file mode 100644 index aeb332d0ef5b..000000000000 --- a/nemo_text_processing/text_normalization/ru/utils.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import csv -import os - -from nemo.utils import logging - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - abs_path = os.path.dirname(os.path.abspath(__file__)) + os.sep + rel_path - - if not os.path.exists(abs_path): - logging.warning(f'{abs_path} does not exist') - return abs_path - - -def load_labels(abs_path): - """ - loads relative path file as dictionary - - Args: - abs_path: absolute path - - Returns dictionary of mappings - """ - with open(abs_path, encoding='utf-8') as label_tsv: - labels = list(csv.reader(label_tsv, delimiter="\t")) - return labels diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/__init__.py b/nemo_text_processing/text_normalization/ru/verbalizers/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/cardinal.py b/nemo_text_processing/text_normalization/ru/verbalizers/cardinal.py deleted file mode 100644 index 4bff9ed3f168..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/cardinal.py +++ /dev/null @@ -1,44 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class CardinalFst(GraphFst): - """ - Finite state transducer for verbalizing cardinals - e.g. cardinal { integer: "тысяча один" } -> "тысяча один" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="cardinal", kind="verbalize", deterministic=deterministic) - optional_sign = pynini.closure(pynini.cross("negative: \"true\" ", "минус "), 0, 1) - optional_quantity_part = pynini.closure( - pynini.accep(" ") - + pynutil.delete("quantity: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\""), - 0, - 1, - ) - integer = pynutil.delete("integer: \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - self.graph = optional_sign + integer + optional_quantity_part - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/date.py b/nemo_text_processing/text_normalization/ru/verbalizers/date.py deleted file mode 100644 index 52a69b0c9a36..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/date.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA -from pynini.lib import pynutil - - -class DateFst(GraphFst): - """ - Finite state transducer for verbalizing date, e.g. - tokens { date { day: "первое мая" } } -> "первое мая" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="date", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete("day: \"") + pynini.closure(RU_ALPHA | " ", 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/decimal.py b/nemo_text_processing/text_normalization/ru/verbalizers/decimal.py deleted file mode 100644 index c3006fe3d535..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/decimal.py +++ /dev/null @@ -1,51 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class DecimalFst(GraphFst): - """ - Finite state transducer for verbalizing decimal, e.g. - tokens { decimal { integer_part: "одно целая" fractional_part: "восемь сотых} } -> - "одно целая восемь сотых" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="decimal", kind="verbalize", deterministic=deterministic) - - optional_sign = pynini.closure(pynini.cross("negative: \"true\" ", "минус "), 0, 1) - integer = pynutil.delete(" \"") + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete("\"") - integer_part = pynutil.delete("integer_part:") + integer - fractional_part = pynutil.delete("fractional_part:") + integer - optional_quantity_part = pynini.closure( - pynini.accep(" ") - + pynutil.delete("quantity: \"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\""), - 0, - 1, - ) - - self.graph = ( - optional_sign + integer_part + pynini.accep(" ") + fractional_part + optional_quantity_part + delete_space - ) - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/electronic.py b/nemo_text_processing/text_normalization/ru/verbalizers/electronic.py deleted file mode 100644 index 5bbfe008d6c5..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/electronic.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA -from pynini.lib import pynutil - - -class ElectronicFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. electronic { username: "эй би собака эн ди точка ру" } -> "эй би собака эн ди точка ру" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="electronic", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete("username: \"") + pynini.closure(RU_ALPHA | " ") + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/measure.py b/nemo_text_processing/text_normalization/ru/verbalizers/measure.py deleted file mode 100644 index 27c95b9ee71e..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/measure.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - NEMO_NON_BREAKING_SPACE, - NEMO_SPACE, - GraphFst, - delete_space, -) -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA -from pynini.lib import pynutil - - -class MeasureFst(GraphFst): - """ - Finite state transducer for verbalizing measure, e.g. - measure { cardinal { integer: "два килограма" } } -> "два килограма" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="measure", kind="verbalize", deterministic=deterministic) - - graph = ( - pynutil.delete(" cardinal { integer: \"") - + pynini.closure(RU_ALPHA | NEMO_SPACE | NEMO_NON_BREAKING_SPACE) - + pynutil.delete("\"") - + delete_space - + pynutil.delete("}") - ) - - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/money.py b/nemo_text_processing/text_normalization/ru/verbalizers/money.py deleted file mode 100644 index 3f5a5e9365e1..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/money.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA -from pynini.lib import pynutil - - -class MoneyFst(GraphFst): - """ - Finite state transducer for verbalizing money, e.g. - money { "пять рублей" } -> пять рублей - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="money", kind="verbalize", deterministic=deterministic) - - graph = pynini.closure(RU_ALPHA | " ") - delete_tokens = self.delete_tokens(pynutil.delete("integer_part: \"") + graph + pynutil.delete("\"")) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/ordinal.py b/nemo_text_processing/text_normalization/ru/verbalizers/ordinal.py deleted file mode 100644 index 00700d9ec984..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/ordinal.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class OrdinalFst(GraphFst): - """ - Finite state transducer for verbalizing roman numerals - e.g. ordinal { integer: "второе" } } -> "второе" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="ordinal", kind="verbalize", deterministic=deterministic) - - value = pynini.closure(NEMO_NOT_QUOTE) - graph = pynutil.delete("integer: \"") + value + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/telephone.py b/nemo_text_processing/text_normalization/ru/verbalizers/telephone.py deleted file mode 100644 index bbd2d29f0e5e..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/telephone.py +++ /dev/null @@ -1,36 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.ru.alphabet import RU_ALPHA -from pynini.lib import pynutil - - -class TelephoneFst(GraphFst): - """ - Finite state transducer for verbalizing telephone, e.g. - telephone { number_part: "восемь девятьсот тринадцать девятьсот восемьдесят три пятьдесят шесть ноль один" } -> "восемь девятьсот тринадцать девятьсот восемьдесят три пятьдесят шесть ноль один" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="telephone", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete("number_part: \"") + pynini.closure(RU_ALPHA | " ", 1) + pynutil.delete("\"") - delete_tokens = self.delete_tokens(graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/time.py b/nemo_text_processing/text_normalization/ru/verbalizers/time.py deleted file mode 100644 index 4f72879d2d48..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/time.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space, insert_space -from pynini.lib import pynutil - - -class TimeFst(GraphFst): - """ - Finite state transducer for verbalizing electronic - e.g. time { hours: "два часа пятнадцать минут" } -> "два часа пятнадцать минут" - - Args: - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="time", kind="verbalize", deterministic=deterministic) - - hour = ( - pynutil.delete("hours:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - minutes = ( - pynutil.delete("minutes:") - + delete_space - + pynutil.delete("\"") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - ) - - self.graph = ( - hour + delete_space + insert_space + minutes + delete_space + pynutil.delete("preserve_order: true") - ) - self.graph |= hour + delete_space - self.graph |= minutes + delete_space + insert_space + hour + delete_space - - delete_tokens = self.delete_tokens(self.graph) - self.fst = delete_tokens.optimize() diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/verbalize.py b/nemo_text_processing/text_normalization/ru/verbalizers/verbalize.py deleted file mode 100644 index 0780c855b438..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/verbalize.py +++ /dev/null @@ -1,69 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from nemo_text_processing.text_normalization.en.graph_utils import GraphFst -from nemo_text_processing.text_normalization.en.verbalizers.whitelist import WhiteListFst -from nemo_text_processing.text_normalization.ru.verbalizers.cardinal import CardinalFst -from nemo_text_processing.text_normalization.ru.verbalizers.date import DateFst -from nemo_text_processing.text_normalization.ru.verbalizers.decimal import DecimalFst -from nemo_text_processing.text_normalization.ru.verbalizers.electronic import ElectronicFst -from nemo_text_processing.text_normalization.ru.verbalizers.measure import MeasureFst -from nemo_text_processing.text_normalization.ru.verbalizers.money import MoneyFst -from nemo_text_processing.text_normalization.ru.verbalizers.ordinal import OrdinalFst -from nemo_text_processing.text_normalization.ru.verbalizers.telephone import TelephoneFst -from nemo_text_processing.text_normalization.ru.verbalizers.time import TimeFst - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="verbalize", kind="verbalize", deterministic=deterministic) - cardinal = CardinalFst() - cardinal_graph = cardinal.fst - ordinal_graph = OrdinalFst().fst - decimal = DecimalFst() - decimal_graph = decimal.fst - date = DateFst() - date_graph = date.fst - measure = MeasureFst() - measure_graph = measure.fst - electronic = ElectronicFst() - electronic_graph = electronic.fst - whitelist_graph = WhiteListFst().fst - money_graph = MoneyFst().fst - telephone_graph = TelephoneFst().fst - time_graph = TimeFst().fst - - graph = ( - measure_graph - | cardinal_graph - | decimal_graph - | ordinal_graph - | date_graph - | electronic_graph - | money_graph - | whitelist_graph - | telephone_graph - | time_graph - ) - self.fst = graph diff --git a/nemo_text_processing/text_normalization/ru/verbalizers/verbalize_final.py b/nemo_text_processing/text_normalization/ru/verbalizers/verbalize_final.py deleted file mode 100644 index 9c0c5f2eab68..000000000000 --- a/nemo_text_processing/text_normalization/ru/verbalizers/verbalize_final.py +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import os - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import ( - GraphFst, - delete_extra_space, - delete_space, - generator_main, -) -from nemo_text_processing.text_normalization.en.verbalizers.word import WordFst -from nemo_text_processing.text_normalization.ru.verbalizers.verbalize import VerbalizeFst -from pynini.lib import pynutil - -from nemo.utils import logging - - -class VerbalizeFinalFst(GraphFst): - """ - Finite state transducer that verbalizes an entire sentence, e.g. - tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now - - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - """ - - def __init__(self, deterministic: bool = True, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="verbalize_final", kind="verbalize", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, f"ru_tn_{deterministic}_deterministic_verbalizer.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["verbalize"] - logging.info(f'VerbalizeFinalFst graph was restored from {far_file}.') - else: - - verbalize = VerbalizeFst().fst - word = WordFst().fst - types = verbalize | word - graph = ( - pynutil.delete("tokens") - + delete_space - + pynutil.delete("{") - + delete_space - + types - + delete_space - + pynutil.delete("}") - ) - graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space - self.fst = graph.optimize() - - if far_file: - generator_main(far_file, {"verbalize": self.fst}) - logging.info(f"VerbalizeFinalFst grammars are saved to {far_file}.") diff --git a/nemo_text_processing/text_normalization/run_evaluate.py b/nemo_text_processing/text_normalization/run_evaluate.py deleted file mode 100644 index 5f23dbd7f8af..000000000000 --- a/nemo_text_processing/text_normalization/run_evaluate.py +++ /dev/null @@ -1,117 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from argparse import ArgumentParser - -from nemo_text_processing.text_normalization.data_loader_utils import ( - evaluate, - known_types, - load_files, - training_data_to_sentences, - training_data_to_tokens, -) -from nemo_text_processing.text_normalization.normalize import Normalizer - - -''' -Runs Evaluation on data in the format of : \t\t<`self` if trivial class or normalized text> -like the Google text normalization data https://www.kaggle.com/richardwilliamsproat/text-normalization-for-english-russian-and-polish -''' - - -def parse_args(): - parser = ArgumentParser() - parser.add_argument("--input", help="input file path", type=str) - parser.add_argument("--lang", help="language", choices=['en'], default="en", type=str) - parser.add_argument( - "--input_case", help="input capitalization", choices=["lower_cased", "cased"], default="cased", type=str - ) - parser.add_argument( - "--cat", - dest="category", - help="focus on class only (" + ", ".join(known_types) + ")", - type=str, - default=None, - choices=known_types, - ) - parser.add_argument("--filter", action='store_true', help="clean data for normalization purposes") - return parser.parse_args() - - -if __name__ == "__main__": - # Example usage: - # python run_evaluate.py --input= --cat= --filter - args = parse_args() - if args.lang == 'en': - from nemo_text_processing.text_normalization.en.clean_eval_data import filter_loaded_data - file_path = args.input - normalizer = Normalizer(input_case=args.input_case, lang=args.lang) - - print("Loading training data: " + file_path) - training_data = load_files([file_path]) - - if args.filter: - training_data = filter_loaded_data(training_data) - - if args.category is None: - print("Sentence level evaluation...") - sentences_un_normalized, sentences_normalized, _ = training_data_to_sentences(training_data) - print("- Data: " + str(len(sentences_normalized)) + " sentences") - sentences_prediction = normalizer.normalize_list(sentences_un_normalized) - print("- Normalized. Evaluating...") - sentences_accuracy = evaluate( - preds=sentences_prediction, labels=sentences_normalized, input=sentences_un_normalized - ) - print("- Accuracy: " + str(sentences_accuracy)) - - print("Token level evaluation...") - tokens_per_type = training_data_to_tokens(training_data, category=args.category) - token_accuracy = {} - for token_type in tokens_per_type: - print("- Token type: " + token_type) - tokens_un_normalized, tokens_normalized = tokens_per_type[token_type] - print(" - Data: " + str(len(tokens_normalized)) + " tokens") - tokens_prediction = normalizer.normalize_list(tokens_un_normalized) - print(" - Denormalized. Evaluating...") - token_accuracy[token_type] = evaluate( - preds=tokens_prediction, labels=tokens_normalized, input=tokens_un_normalized - ) - print(" - Accuracy: " + str(token_accuracy[token_type])) - token_count_per_type = {token_type: len(tokens_per_type[token_type][0]) for token_type in tokens_per_type} - token_weighted_accuracy = [ - token_count_per_type[token_type] * accuracy for token_type, accuracy in token_accuracy.items() - ] - print("- Accuracy: " + str(sum(token_weighted_accuracy) / sum(token_count_per_type.values()))) - print(" - Total: " + str(sum(token_count_per_type.values())), '\n') - - print(" - Total: " + str(sum(token_count_per_type.values())), '\n') - - for token_type in token_accuracy: - if token_type not in known_types: - raise ValueError("Unexpected token type: " + token_type) - - if args.category is None: - c1 = ['Class', 'sent level'] + known_types - c2 = ['Num Tokens', len(sentences_normalized)] + [ - token_count_per_type[known_type] if known_type in tokens_per_type else '0' for known_type in known_types - ] - c3 = ['Normalization', sentences_accuracy] + [ - token_accuracy[known_type] if known_type in token_accuracy else '0' for known_type in known_types - ] - - for i in range(len(c1)): - print(f'{str(c1[i]):10s} | {str(c2[i]):10s} | {str(c3[i]):5s}') - else: - print(f'numbers\t{token_count_per_type[args.category]}') - print(f'Normalization\t{token_accuracy[args.category]}') diff --git a/nemo_text_processing/text_normalization/token_parser.py b/nemo_text_processing/text_normalization/token_parser.py deleted file mode 100644 index 638b71bbf142..000000000000 --- a/nemo_text_processing/text_normalization/token_parser.py +++ /dev/null @@ -1,193 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import string -from collections import OrderedDict -from typing import Dict, List, Union - -PRESERVE_ORDER_KEY = "preserve_order" -EOS = "" - - -class TokenParser: - """ - Parses tokenized/classified text, e.g. 'tokens { money { integer: "20" currency: "$" } } tokens { name: "left"}' - - Args - text: tokenized text - """ - - def __call__(self, text): - """ - Setup function - - Args: - text: text to be parsed - - """ - self.text = text - self.len_text = len(text) - self.char = text[0] # cannot handle empty string - self.index = 0 - - def parse(self) -> List[dict]: - """ - Main function. Implements grammar: - A -> space F space F space F ... space - - Returns list of dictionaries - """ - l = list() - while self.parse_ws(): - token = self.parse_token() - if not token: - break - l.append(token) - return l - - def parse_token(self) -> Dict[str, Union[str, dict]]: - """ - Implements grammar: - F-> no_space KG no_space - - Returns: K, G as dictionary values - """ - d = OrderedDict() - key = self.parse_string_key() - if key is None: - return None - self.parse_ws() - if key == PRESERVE_ORDER_KEY: - self.parse_char(":") - self.parse_ws() - value = self.parse_chars("true") - else: - value = self.parse_token_value() - - d[key] = value - return d - - def parse_token_value(self) -> Union[str, dict]: - """ - Implements grammar: - G-> no_space :"VALUE" no_space | no_space {A} no_space - - Returns: string or dictionary - """ - if self.char == ":": - self.parse_char(":") - self.parse_ws() - self.parse_char("\"") - value_string = self.parse_string_value() - self.parse_char("\"") - return value_string - elif self.char == "{": - d = OrderedDict() - self.parse_char("{") - list_token_dicts = self.parse() - # flatten tokens - for tok_dict in list_token_dicts: - for k, v in tok_dict.items(): - d[k] = v - self.parse_char("}") - return d - else: - raise ValueError() - - def parse_char(self, exp) -> bool: - """ - Parses character - - Args: - exp: character to read in - - Returns true if successful - """ - assert self.char == exp - self.read() - return True - - def parse_chars(self, exp) -> bool: - """ - Parses characters - - Args: - exp: characters to read in - - Returns true if successful - """ - ok = False - for x in exp: - ok |= self.parse_char(x) - return ok - - def parse_string_key(self) -> str: - """ - Parses string key, can only contain ascii and '_' characters - - Returns parsed string key - """ - assert self.char not in string.whitespace and self.char != EOS - incl_criterium = string.ascii_letters + "_" - l = [] - while self.char in incl_criterium: - l.append(self.char) - if not self.read(): - raise ValueError() - - if not l: - return None - return "".join(l) - - def parse_string_value(self) -> str: - """ - Parses string value, ends with quote followed by space - - Returns parsed string value - """ - # assert self.char not in string.whitespace and self.char != EOS - assert self.char != EOS - l = [] - while self.char != "\"" or self.text[self.index + 1] != " ": - l.append(self.char) - if not self.read(): - raise ValueError() - - if not l: - return None - return "".join(l) - - def parse_ws(self): - """ - Deletes whitespaces. - - Returns true if not EOS after parsing - """ - not_eos = self.char != EOS - while not_eos and self.char == " ": - not_eos = self.read() - return not_eos - - def read(self): - """ - Reads in next char. - - Returns true if not EOS - """ - if self.index < self.len_text - 1: # should be unique - self.index += 1 - self.char = self.text[self.index] - return True - self.char = EOS - return False diff --git a/nemo_text_processing/text_normalization/zh/README.md b/nemo_text_processing/text_normalization/zh/README.md deleted file mode 100644 index 0eedd574d839..000000000000 --- a/nemo_text_processing/text_normalization/zh/README.md +++ /dev/null @@ -1,138 +0,0 @@ -# Chinese Text Normalization - -## 1. How To Use -``` -python normalize.py --language "zh" --text "text to be normalized" -``` - -## 2. TN Pipeline -There are 3 components in TN pipeline: -* pre-processing (before tagger) -* non-standard word normalization -* post-processing (after verbalizer) - -### 2.1 Pre-Processing -#### Char Width Conversion (全角 -> 半角) -``` -苹果ＣＥＯ宣布发布新ＩＰＨＯＮＥ -> 苹果CEO宣布发布新IPHONE -他说：“我们已经吃过了！”。 -> 他说:"我们已经吃过了!". -``` -* covers English letters, digits, punctuations and some symbols -* the complete mapping table `data/char/fullwidth_to_halfwidth.tsv` - -#### Denylist (Removal) -Sometime you may want to remove certain things like interjections/fillers "啊", "呃" etc -``` -呃这个呃啊我不知道 -> 这个我不知道 -``` -* customizable via `data/denylist/denylist.tsv` - - -### 2.2 Non-Standard-Words(NSW) normalization -#### Numbers -``` -共465篇，约315万字 -> 共四百六十五篇，约三百一十五万字 -共计6.42万人 -> 共计六点四二万人 -同比升高0.6个百分点 -> 同比升高零点六个百分点 -``` - -#### Fraction -``` -总量的1/5以上 -> 总量的五分之一以上 -相当于头发丝的1/16 -> 相当于头发丝的十六分之一 -3/2是一个假分数 -> 二分之三是一个假分数 -``` - -#### Percentage -``` -同比增长6.3% -> 同比增长百分之六点三 -增幅0.4% -> 增幅百分之零点四 -``` - -#### Date -``` -2002/01/28 -> 二零零二年一月二十八日 -2002-01-28 -> 二零零二年一月二十八日 -2002.01.28 -> 二零零二年一月二十八日 -2002/01 -> 二零零二年一月 -``` - -#### Time -``` -8月16号12:00之前 -> 八月十六号十二点之前 -我是5:02开始的 -> 我是五点零二分开始的 -于5:35:36发射 -> 于五点三十五分三十六秒发射 -8:00am准时开会 -> 上午八点准时开会 -``` - -#### Math -``` -比分定格在78:96 -> 比分定格在七十八比九十六 -计算-2的绝对值是2 -> 计算负二的绝对值是二 -±2的平方都是4 -> 正负二的平方都是四 -``` - -#### Money -``` -价格是￥13.5 -> 价格是十三点五元 -价格是$13.5 -> 价格是十三点五美元 -价格是A$13.5 -> 价格是十三点五澳元 -价格是HKD13.5 -> 价格是十三点五港元 -``` - -#### Measure -``` -重达25kg -> 二十五千克 -最高气温38°C -> 最高气温三十八摄氏度 -实际面积120m² -> 实际面积一百二十平方米 -渲染速度10ms一帧 -> 渲染速度十毫秒一帧 -``` - -#### Number series (phone, mobile numbers) -``` -可以打我手机13501234567 -> 可以打我手机一三五零一二三四五六七 -可以拨打12306来咨询 -> 可以拨打一二三零六来咨询 -``` - -#### Erhua(儿化音) Removal -``` -这儿有只鸟儿 -> 这有只鸟 -这事儿好办 -> 这事好办 -我儿子喜欢这地儿 -> 我儿子喜欢这地 -``` -* erhua whitelist is customizable via `data/erhua/whitelist.tsv` - -#### Whitelist(Replacement) -a set of user-defined hard mapping, i.e. exact-string matching & replacement -``` -C E O -> CEO -G P U -> GPU -O2O -> O to O -B2B -> B to B -``` -* customizable via `data/whitelist/default.tsv` - -### 2.3 Post-Processing -#### Punctuation Removal -If enabled, punctuations are removed. - -#### Uppercase or Lowercase Conversion -If enabled, English letters are converted to uppercases / lowercases - -#### Out-Of-Vocabulary(OOV) Tagger -If enabled, OOV chars are tagged with `` and ``, e.g.: -``` -我们안녕 -> 我们안녕 -雪の花 -> 雪の花 -``` -* default charset (national standard) [通用规范汉字表](https://zh.wikipedia.org/wiki/通用规范汉字表) -* you can extend charset via `data/char/charset_extension.tsv` - -## 3. Credits -Author: Zhenxiang MA @ Tsinghua University - -Advisors: [SpeechColab](https://github.com/SpeechColab) organization - -The authors of this work would like to thank: -* The authors of foundational libraries like OpenFst & Pynini -* NeMo team and NeMo open-source community diff --git a/nemo_text_processing/text_normalization/zh/__init__.py b/nemo_text_processing/text_normalization/zh/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/__init__.py b/nemo_text_processing/text_normalization/zh/data/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/char/__init__.py b/nemo_text_processing/text_normalization/zh/data/char/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/char/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/char/charset_extension.tsv b/nemo_text_processing/text_normalization/zh/data/char/charset_extension.tsv deleted file mode 100644 index de3ac0a83e76..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/char/charset_extension.tsv +++ /dev/null @@ -1,6 +0,0 @@ -吶 -诶 -屌 -囧 -飚 -屄 diff --git a/nemo_text_processing/text_normalization/zh/data/char/charset_national_standard_2013_8105.tsv b/nemo_text_processing/text_normalization/zh/data/char/charset_national_standard_2013_8105.tsv deleted file mode 100644 index 06b46c630588..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/char/charset_national_standard_2013_8105.tsv +++ /dev/null @@ -1,8105 +0,0 @@ -一 -丁 -七 -万 -丈 -三 -上 -下 -不 -与 -丏 -丐 -丑 -专 -且 -丕 -世 -丘 -丙 -业 -丛 -东 -丝 -丞 -丢 -两 -严 -丧 -个 -丫 -中 -丰 -串 -临 -丸 -丹 -为 -主 -丽 -举 -乂 -乃 -久 -么 -义 -之 -乌 -乍 -乎 -乏 -乐 -乒 -乓 -乔 -乖 -乘 -乙 -乜 -九 -乞 -也 -习 -乡 -书 -乩 -买 -乱 -乳 -乸 -乾 -了 -予 -争 -事 -二 -亍 -于 -亏 -云 -互 -亓 -五 -井 -亘 -亚 -些 -亟 -亡 -亢 -交 -亥 -亦 -产 -亨 -亩 -享 -京 -亭 -亮 -亲 -亳 -亵 -亶 -亸 -亹 -人 -亿 -什 -仁 -仂 -仃 -仄 -仅 -仆 -仇 -仉 -今 -介 -仍 -从 -仑 -仓 -仔 -仕 -他 -仗 -付 -仙 -仝 -仞 -仟 -仡 -代 -令 -以 -仨 -仪 -仫 -们 -仰 -仲 -仳 -仵 -件 -价 -任 -份 -仿 -企 -伈 -伉 -伊 -伋 -伍 -伎 -伏 -伐 -休 -众 -优 -伙 -会 -伛 -伞 -伟 -传 -伢 -伣 -伤 -伥 -伦 -伧 -伪 -伫 -伭 -伯 -估 -伲 -伴 -伶 -伸 -伺 -似 -伽 -伾 -佁 -佃 -但 -位 -低 -住 -佐 -佑 -体 -何 -佖 -佗 -佘 -余 -佚 -佛 -作 -佝 -佞 -佟 -你 -佣 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a/nemo_text_processing/text_normalization/zh/data/char/fullwidth_to_halfwidth.tsv +++ /dev/null @@ -1,92 +0,0 @@ -！ ! -＂ " -＃ # -＄ $ -％ % -＆ & -＇ ' -（ ( -） ) -＊ * -＋ + -， , -－ - -． . -／ / -０ 0 -１ 1 -２ 2 -３ 3 -４ 4 -５ 5 -６ 6 -７ 7 -８ 8 -９ 9 -； ; -＜ < -＝ = -＞ > -？ ? -＠ @ -Ａ A -Ｂ B -Ｃ C -Ｄ D -Ｅ E -Ｆ F -Ｇ G -Ｈ H -Ｉ I -Ｊ J -Ｋ K -Ｌ L -Ｍ M -Ｎ N -Ｏ O -Ｐ P -Ｑ Q -Ｒ R -Ｓ S -Ｔ T -Ｕ U -Ｖ V -Ｗ W -Ｘ X -Ｙ Y -Ｚ Z -＼ \ -＾ ^ -＿ _ -｀ ` -ａ a -ｂ b -ｃ c -ｄ d -ｅ e -ｆ f -ｇ g -ｈ h -ｉ i -ｊ j -ｋ k -ｌ l -ｍ m -ｎ n -ｏ o -ｐ p -ｑ q -ｒ r -ｓ s -ｔ t -ｕ u -ｖ v -ｗ w -ｘ x -ｙ y -ｚ z -｛ { -｜ | -： : -｝ } -～ ~ diff --git a/nemo_text_processing/text_normalization/zh/data/char/oov_tags.tsv b/nemo_text_processing/text_normalization/zh/data/char/oov_tags.tsv deleted file mode 100644 index cd6c56f53700..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/char/oov_tags.tsv +++ /dev/null @@ -1 +0,0 @@ - diff --git a/nemo_text_processing/text_normalization/zh/data/char/punctuations_zh.tsv b/nemo_text_processing/text_normalization/zh/data/char/punctuations_zh.tsv deleted file mode 100644 index 963b07d12b44..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/char/punctuations_zh.tsv +++ /dev/null @@ -1,72 +0,0 @@ -！ -？ -｡ -。 -＂ -＃ -＄ -％ -＆ -＇ -（ -） -＊ -＋ -， -－ -／ -： -； -＜ -＝ -＞ -＠ -［ -＼ -］ -＾ -＿ -｀ -｛ -｜ -｝ -～ -｟ -｠ -｢ -｣ -､ -、 -〃 -》 -「 -」 -『 -』 -【 -】 -〔 -〕 -〖 -〗 -〘 -〙 -〚 -〛 -〜 -〝 -〞 -〟 -〰 -– -— -‘ -’ -‛ -“ -” -„ -‟ -… -‧ -﹏ diff --git a/nemo_text_processing/text_normalization/zh/data/char/upper_to_lower.tsv b/nemo_text_processing/text_normalization/zh/data/char/upper_to_lower.tsv deleted file mode 100644 index 1b603c530f08..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/char/upper_to_lower.tsv +++ /dev/null @@ -1,9 +0,0 @@ -壹 一 -贰 二 -叁 三 -肆 四 -伍 五 -陆 六 -柒 七 -捌 八 -玖 九 diff --git a/nemo_text_processing/text_normalization/zh/data/date/__init__.py b/nemo_text_processing/text_normalization/zh/data/date/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/date/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/date/year_suffix.tsv b/nemo_text_processing/text_normalization/zh/data/date/year_suffix.tsv deleted file mode 100644 index 2ae02ddf63e5..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/date/year_suffix.tsv +++ /dev/null @@ -1,6 +0,0 @@ -来 -前 -后 -内 -之后 - diff --git a/nemo_text_processing/text_normalization/zh/data/denylist/__init__.py b/nemo_text_processing/text_normalization/zh/data/denylist/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/denylist/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/denylist/denylist.tsv b/nemo_text_processing/text_normalization/zh/data/denylist/denylist.tsv deleted file mode 100644 index b419181407b9..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/denylist/denylist.tsv +++ /dev/null @@ -1,2 +0,0 @@ -啊 -呃 \ No newline at end of file diff --git a/nemo_text_processing/text_normalization/zh/data/erhua/__init__.py b/nemo_text_processing/text_normalization/zh/data/erhua/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/erhua/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/erhua/whitelist.tsv b/nemo_text_processing/text_normalization/zh/data/erhua/whitelist.tsv deleted file mode 100644 index f00ae31a5bff..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/erhua/whitelist.tsv +++ /dev/null @@ -1,35 +0,0 @@ -儿女 -儿子 -儿孙 -女儿 -儿媳 -妻儿 -胎儿 -婴儿 -新生儿 -婴幼儿 -幼儿 -少儿 -小儿 -儿歌 -儿童 -儿科 -托儿所 -孤儿 -儿戏 -儿化 -台儿庄 -鹿儿岛 -正儿八经 -吊儿郎当 -生儿育女 -托儿带女 -养儿防老 -痴儿呆女 -佳儿佳妇 -儿怜兽扰 -儿无常父 -儿不嫌母丑 -儿行千里母担忧 -儿大不由爷 -苏乞儿 diff --git a/nemo_text_processing/text_normalization/zh/data/math/__init__.py b/nemo_text_processing/text_normalization/zh/data/math/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/math/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/math/score.tsv b/nemo_text_processing/text_normalization/zh/data/math/score.tsv deleted file mode 100644 index 0647248d5c49..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/math/score.tsv +++ /dev/null @@ -1,2 +0,0 @@ -: 比 -： 比 diff --git a/nemo_text_processing/text_normalization/zh/data/math/symbol.tsv b/nemo_text_processing/text_normalization/zh/data/math/symbol.tsv deleted file mode 100644 index 7f16f52a486d..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/math/symbol.tsv +++ /dev/null @@ -1,7 +0,0 @@ -+ 加 -~ 到 -± 正负 -= 等于 -× 乘 -÷ 除 -° 度 diff --git a/nemo_text_processing/text_normalization/zh/data/measure/__init__.py b/nemo_text_processing/text_normalization/zh/data/measure/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/measure/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/measure/units_en.tsv b/nemo_text_processing/text_normalization/zh/data/measure/units_en.tsv deleted file mode 100644 index 09c62fb5757f..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/measure/units_en.tsv +++ /dev/null @@ -1,90 +0,0 @@ -amu 原子质量 -bar 巴 -° 度 -º 度 -°c 摄氏度 -°C 摄氏度 -ºc 摄氏度 -ºC 摄氏度 -℃ 摄氏度 -cm2 平方厘米 -cm² 平方厘米 -cm3 立方厘米 -cm³ 立方厘米 -cm 厘米 -cwt 美担 -db 分贝 -dm3 立方分米 -dm³ 立方分米 -dm 分米 -ds 毫秒 -°f 华氏度 -°F 华氏度 -℉ 华氏度 -ft 英尺 -ghz 吉赫兹 -gw 吉瓦 -gwh 吉瓦时 -hz 赫兹 -kbps 千比特每秒 -kcal 千卡 -kgf 千克力 -kg 千克 -khz 千赫兹 -km2 平方千米 -km² 平方千米 -km 千米 -kpa 千帕 -kwh 千瓦时 -kw 千瓦 -kW 千瓦 -lb 磅 -lbs 磅 -m2 平方米 -m² 平方米 -m3 立方米 -m³ 立方米 -mbps 兆比特每秒 -mg 毫克 -mhz 兆赫兹 -mi2 平方英里 -mi² 平方英里 -mi 英里 -min 分钟哦 -ml 毫升 -mm2 平方毫米 -mm² 平方毫米 -mol 摩尔 -mpa 兆帕 -mph 英里每小时 -ng 纳克 -nm 纳米 -ns 纳秒 -oz 盎司 -pa 帕斯卡 -rad 弧度 -rpm 转每分 -sq ft 平方英尺 -sq mi 平方英里 -sv 系沃特 -tb 太字节 -tj 万亿焦耳 -tl 台两 -v 伏特 -yd 码 -μg 微克 -μm 微米 -μs 微秒 -ω 欧米茄 -gb 吉字节 -gpa 吉帕斯卡 -gy 戈瑞 -ha 公顷 -m 米 -mm 毫米 -ms 毫秒 -mv 毫伏 -mw 毫瓦 -pg 皮克 -ps 皮秒 -s 秒 diff --git a/nemo_text_processing/text_normalization/zh/data/measure/units_zh.tsv b/nemo_text_processing/text_normalization/zh/data/measure/units_zh.tsv deleted file mode 100644 index 5ca1dd9ab9a1..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/measure/units_zh.tsv +++ /dev/null @@ -1,211 +0,0 @@ -匹 -张 -座 -回 -场 -尾 -条 -个 -首 -阙 -阵 -网 -炮 -顶 -丘 -棵 -只 -支 -袭 -辆 -挑 -担 -颗 -壳 -窠 -曲 -墙 -群 -腔 -砣 -座 -客 -贯 -扎 -捆 -刀 -令 -打 -手 -罗 -坡 -山 -岭 -江 -溪 -钟 -队 -单 -双 -对 -口 -头 -脚 -板 -跳 -枝 -件 -贴 -针 -线 -管 -名 -位 -身 -堂 -课 -本 -页 -家 -户 -层 -丝 -毫 -厘 -分 -钱 -两 -斤 -担 -铢 -石 -钧 -锱 -忽 -克 -毫 -厘 -分 -寸 -尺 -丈 -里 -寻 -常 -铺 -程 -米 -撮 -勺 -合 -升 -斗 -石 -盘 -碗 -碟 -叠 -桶 -笼 -盆 -盒 -杯 -钟 -斛 -锅 -簋 -篮 -盘 -桶 -罐 -瓶 -壶 -卮 -盏 -箩 -箱 -煲 -啖 -袋 -钵 -年 -月 -日 -季 -刻 -时 -周 -天 -秒 -分 -旬 -纪 -岁 -世 -更 -夜 -春 -夏 -秋 -冬 -代 -伏 -辈 -丸 -泡 -粒 -颗 -幢 -堆 -条 -根 -支 -道 -面 -片 -张 -颗 -块 -架 -千米 -分米 -厘米 -毫米 -微米 -纳米 -亿 -千万 -百万 -万 -千 -百 -亿块 -千万块 -百万块 -万块 -千块 -百块 -亿角 -千万角 -百万角 -万角 -千角 -百角 -亿毛 -千万毛 -百万毛 -万毛 -千毛 -百毛 -亿分 -千万分 -百万分 -万分 -千分 -百分 -亿元 -千万元 -百万元 -万元 -千元 -百元 diff --git a/nemo_text_processing/text_normalization/zh/data/money/__init__.py b/nemo_text_processing/text_normalization/zh/data/money/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/money/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/money/currency_code.tsv b/nemo_text_processing/text_normalization/zh/data/money/currency_code.tsv deleted file mode 100644 index 238c01b48456..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/money/currency_code.tsv +++ /dev/null @@ -1,117 +0,0 @@ -ALL 阿尔巴尼亚列克 -AFN 阿富汗 阿富汗尼 -ARS 阿根廷比索 -AWG 阿鲁巴盾 -AUD 澳元 -AZN 阿塞拜疆马纳特 -BSD 巴哈马元 -BBD 巴巴多斯元 -BYN 白俄罗斯卢布 -BZD 伯利兹元 -BMD 百慕大元 -BOB 玻利维亚玻利维亚诺 -BAM 波斯尼亚和黑塞哥维那可兑换马克 -BWP 博茨瓦纳普拉 -BGN 保加利亚列弗 -BRL 巴西雷亚尔 -BND 文莱达鲁萨兰国元 -KHR 柬埔寨瑞尔 -CAD 加元 -KYD 开曼群岛元 -CLP 智利比索 -CNY 人民币 -COP 哥伦比亚比索 -CRC 哥斯达黎加科隆 -HRK 克罗地亚库纳 -CUP 古巴比索 -CZK 捷克克朗 -DKK 丹麦克朗 -DOP 多米尼加共和国比索 -XCD 东加勒比元 -EGP 埃及镑 -SVC 萨尔瓦多科隆 -EUR 欧元成员国 -FKP 福克兰群岛（马尔维纳斯）镑 -FJD 斐济元 -GHS 加纳塞地 -GIP 直布罗陀镑 -GTQ 危地马拉格查尔 -GGP 根西岛镑 -GYD 圭亚那元 -HNL 洪都拉斯伦皮拉 -HKD 港元 -HUF 匈牙利福林 -ISK 冰岛克朗 -INR 印度卢比 -IDR 印尼盾 -IRR 伊朗里亚尔 -IMP 马恩岛英镑 -ILS 以色列谢克尔 -JMD 牙买加元 -JPY 日元 -JEP 泽西镑 -KZT 哈萨克斯坦腾格 -KPW 朝鲜园 -KRW 韩元 -KGS 吉尔吉斯斯坦索姆 -LAK 老挝基普 -LBP 黎巴嫩镑 -LRD 利比里亚元 -MKD 马其顿代纳尔 -MYR 马来西亚令吉 -MUR 毛里求斯卢比 -MXN 墨西哥比索 -MNT 蒙古图格里克 -MNT 摩洛哥迪拉姆 -MZN 莫桑比克梅蒂卡尔 -NAD 纳米比亚元 -NPR 尼泊尔卢比 -ANG 荷属安的列斯盾 -NZD 新西兰元 -NIO 尼加拉瓜科尔多瓦 -NGN 尼日利亚奈拉 -NOK 挪威克朗 -OMR 阿曼里亚尔 -PKR 巴基斯坦卢比 -PAB 巴拿马巴尔博亚 -PYG 巴拉圭瓜拉尼 -PEN 秘鲁索尔 -PHP 菲律宾比索 -PLN 波兰兹罗提 -QAR 卡塔尔里亚尔 -RON 罗马尼亚列伊 -RUB 俄罗斯卢布 -SHP 圣赫勒拿镑 -SAR 沙特阿拉伯里亚尔 -RSD 塞尔维亚第纳尔 -SCR 塞舌尔卢比 -SGD 新加坡元 -SBD 所罗门群岛元 -SOS 索马里先令 -KRW 韩元 -ZAR 南非兰特 -LKR 斯里兰卡卢比 -SEK 瑞典克朗 -CHF 瑞士法郎 -SRD 苏里南元 -SYP 叙利亚镑 -TWD 新台币 -THB 泰铢 -TTD 特立尼达和多巴哥元 -TRY 土耳其里拉 -TVD 图瓦卢元 -UAH 乌克兰格里夫纳 -AED 阿联酋迪拉姆 -GBP 英镑 -USD 美元 -UYU 乌拉圭比索 -UZS 乌兹别克斯坦索姆 -VEF 委内瑞拉玻利瓦尔 -VND 越南东 -YER 也门里亚尔 -ZWD 津巴布韦元 -J￥ 日元 -JPY￥ 日元 -HK＄ 港元 -A$ 澳元 -CAD$ 加元 diff --git a/nemo_text_processing/text_normalization/zh/data/money/currency_symbol.tsv b/nemo_text_processing/text_normalization/zh/data/money/currency_symbol.tsv deleted file mode 100644 index 18e2af41e3a1..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/money/currency_symbol.tsv +++ /dev/null @@ -1,63 +0,0 @@ -Lek 阿尔巴尼亚列克 -ƒ 阿鲁巴盾 -Br 白俄罗斯卢布 -BZ$ 伯利兹元 -$b 玻利维亚玻利维亚诺 -KM 波斯尼亚和黑塞哥维那可兑换马克 -P 博茨瓦纳普拉 -лв 保加利亚列弗 -R$ 巴西雷亚尔 -៛ 柬埔寨瑞尔 -¥ 人民币 -₡ 哥斯达黎加科隆 -kn 克罗地亚库纳 -₱ 古巴比索 -Kč 捷克克朗 -kr 丹麦克朗 -RD$ 多米尼加共和国比索 -€ 欧元 -¢ 加纳塞地 -Q 危地马拉格查尔 -L 洪都拉斯伦皮拉 -Ft 匈牙利福林 -₹ 印度卢比 -Rp 印尼盾 -£ 英镑 -￡ 英镑 -₪ 以色列谢克尔 -J$ 牙买加元 -лв 哈萨克斯坦腾格 -₩ 朝鲜园 -лв 吉尔吉斯斯坦索姆 -₭ 老挝基普 -ден 马其顿代纳尔 -RM 马来西亚令吉 -₨ 毛里求斯卢比 -₮ 蒙古图格里克 -MT 莫桑比克梅蒂卡尔 -C$ 尼加拉瓜科尔多瓦 -₦ 尼日利亚奈拉 -₨ 巴基斯坦卢比 -B/. 巴拿马巴尔博亚 -Gs 巴拉圭瓜拉尼 -S/. 秘鲁索尔 -₱ 菲律宾比索 -zł 波兰兹罗提 -lei 罗马尼亚列伊 -₽ 卢布 -Дин. 塞尔维亚第纳尔 -S 索马里先令 -R 南非兰特 -CHF 瑞士法郎 -NT$ 新台币 -฿ 泰铢 -TT$ 特立尼达和多巴哥元 -₺ 土耳其里拉 -₴ 乌克兰格里夫纳 -$ 美元 -$U 乌拉圭比索 -лв 乌兹别克斯坦索姆 -Bs 委内瑞拉玻利瓦尔 -₫ 越南东 -Z$ 津巴布韦元 -￥ 人民币 diff --git a/nemo_text_processing/text_normalization/zh/data/number/__init__.py b/nemo_text_processing/text_normalization/zh/data/number/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/number/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/number/digit.tsv b/nemo_text_processing/text_normalization/zh/data/number/digit.tsv deleted file mode 100644 index 3a578d35897c..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/number/digit.tsv +++ /dev/null @@ -1,9 +0,0 @@ -1 一 -2 二 -3 三 -4 四 -5 五 -6 六 -7 七 -8 八 -9 九 diff --git a/nemo_text_processing/text_normalization/zh/data/number/digit_teen.tsv b/nemo_text_processing/text_normalization/zh/data/number/digit_teen.tsv deleted file mode 100644 index 04c85dd7885a..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/number/digit_teen.tsv +++ /dev/null @@ -1,9 +0,0 @@ -1 -2 二 -3 三 -4 四 -5 五 -6 六 -7 七 -8 八 -9 九 diff --git a/nemo_text_processing/text_normalization/zh/data/number/sign.tsv b/nemo_text_processing/text_normalization/zh/data/number/sign.tsv deleted file mode 100644 index 645adbdf1996..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/number/sign.tsv +++ /dev/null @@ -1,2 +0,0 @@ -- 负 -+ 正 diff --git a/nemo_text_processing/text_normalization/zh/data/number/zero.tsv b/nemo_text_processing/text_normalization/zh/data/number/zero.tsv deleted file mode 100644 index d6b9cece55a4..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/number/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -0 零 diff --git a/nemo_text_processing/text_normalization/zh/data/time/__init__.py b/nemo_text_processing/text_normalization/zh/data/time/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/time/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/time/digit.tsv b/nemo_text_processing/text_normalization/zh/data/time/digit.tsv deleted file mode 100644 index c0ce4d77693c..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/time/digit.tsv +++ /dev/null @@ -1,10 +0,0 @@ -1 -2 -3 -4 -5 -6 -7 -8 -9 - diff --git a/nemo_text_processing/text_normalization/zh/data/time/hour.tsv b/nemo_text_processing/text_normalization/zh/data/time/hour.tsv deleted file mode 100644 index 7ed2844ca58a..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/time/hour.tsv +++ /dev/null @@ -1,24 +0,0 @@ -1 -2 -3 -4 -5 -6 -7 -8 -9 -10 -11 -12 -13 -14 -15 -16 -17 -18 -19 -20 -21 -22 -23 -24 diff --git a/nemo_text_processing/text_normalization/zh/data/time/suffix.tsv b/nemo_text_processing/text_normalization/zh/data/time/suffix.tsv deleted file mode 100644 index 68ced35e3915..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/time/suffix.tsv +++ /dev/null @@ -1,10 +0,0 @@ -am 上午 -a.m. 上午 -a m 上午 -AM 上午 -A M 上午 -pm 下午 -p.m. 下午 -p m 下午 -P M 下午 -PM 下午 diff --git a/nemo_text_processing/text_normalization/zh/data/time/tens.tsv b/nemo_text_processing/text_normalization/zh/data/time/tens.tsv deleted file mode 100644 index 09c277aa6689..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/time/tens.tsv +++ /dev/null @@ -1,7 +0,0 @@ -0 -1 -2 -3 -4 -5 -6 diff --git a/nemo_text_processing/text_normalization/zh/data/time/zero.tsv b/nemo_text_processing/text_normalization/zh/data/time/zero.tsv deleted file mode 100644 index 573541ac9702..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/time/zero.tsv +++ /dev/null @@ -1 +0,0 @@ -0 diff --git a/nemo_text_processing/text_normalization/zh/data/whitelist/__init__.py b/nemo_text_processing/text_normalization/zh/data/whitelist/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/whitelist/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv b/nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv deleted file mode 100644 index fd7b54dfffda..000000000000 --- a/nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv +++ /dev/null @@ -1,79 +0,0 @@ -O 2 O O to O -O2O O to O -P 2 P P to P -P2P P to P -CD C D -a.m. AM -am. AM -A M AM -Am AM - am AM -p.m. PM -pm. PM -Pm PM - pm PM -atm ATM -A T M ATM -Atm ATM -ufo UFO -Ufo UFO -U F O UFO -u f o UFO -m v MV -mv MV -MV MV -F I F A fifa -f i f a fifa -FIFA fifa -nba NBA -Nba NBA -NBA NBA -n b a NBA -x L XL -X L XL -x x L XXL -X X L XXL -x x x L XXXL -X X X L XXXL -Q Q QQ -qq QQ -Qq QQ -gpu GPU -GPU GPU -cpu CPU -C P U CPU -WIFI wifi -ms MS -ceo CEO -c e o CEO -C E O CEO -dv DV -d v DV -D V DV -wto WTO -w t o WTO -W T O WTO -pc PC -p c PC -P C PC -gps GPS -G P S GPS -M.V.P MVP -mvp MVP -M V P MVP -vip VIP -V I P VIP -cba CBA -c b a CBA -CBA CBA -mba MBA -m b a MBA -M B A MBA -iq IQ -IQ IQ -EQ EQ -cctv CCTV -C C t v CCTV -kfc KFC -K F C KFC -Steam steam diff --git a/nemo_text_processing/text_normalization/zh/graph_utils.py b/nemo_text_processing/text_normalization/zh/graph_utils.py deleted file mode 100644 index 4ca62dbe63e6..000000000000 --- a/nemo_text_processing/text_normalization/zh/graph_utils.py +++ /dev/null @@ -1,128 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import os -import string -from pathlib import Path -from typing import Dict - -import pynini -from pynini import Far -from pynini.export import export -from pynini.lib import byte, pynutil, utf8 - -NEMO_CHAR = utf8.VALID_UTF8_CHAR - -NEMO_DIGIT = byte.DIGIT -NEMO_LOWER = pynini.union(*string.ascii_lowercase).optimize() -NEMO_UPPER = pynini.union(*string.ascii_uppercase).optimize() -NEMO_ALPHA = pynini.union(NEMO_LOWER, NEMO_UPPER).optimize() - -NEMO_SPACE = " " -NEMO_WHITE_SPACE = pynini.union(" ", "\t", "\n", "\r", u"\u00A0").optimize() -NEMO_NOT_SPACE = pynini.difference(NEMO_CHAR, NEMO_WHITE_SPACE).optimize() -NEMO_NOT_QUOTE = pynini.difference(NEMO_CHAR, r'"').optimize() - -NEMO_PUNCT = pynini.union(*map(pynini.escape, string.punctuation)).optimize() - - -NEMO_SIGMA = pynini.closure(NEMO_CHAR) - -delete_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE)) -delete_zero_or_one_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE, 0, 1)) -insert_space = pynutil.insert(" ") -delete_extra_space = pynini.cross(pynini.closure(NEMO_WHITE_SPACE, 1), " ") - - -def generator_main(file_name: str, graphs: Dict[str, 'pynini.FstLike']): - """ - Exports graph as OpenFst finite state archive (FAR) file with given file name and rule name. - - Args: - file_name: exported file name - graphs: Mapping of a rule name and Pynini WFST graph to be exported - """ - exporter = export.Exporter(file_name) - for rule, graph in graphs.items(): - exporter[rule] = graph.optimize() - exporter.close() - print(f'Created {file_name}') - - -class GraphFst: - """ - Base class for all grammar fsts. - - Args: - name: name of grammar class - kind: either 'classify' or 'verbalize' - deterministic: if True will provide a single transduction option, - for False multiple transduction are generated (used for audio-based normalization) - """ - - def __init__(self, name: str, kind: str, deterministic: bool = True): - self.name = name - self.kind = kind - self._fst = None - self.deterministic = deterministic - - self.far_path = Path(os.path.dirname(__file__) + '/grammars/' + kind + '/' + name + '.far') - if self.far_exist(): - self._fst = Far(self.far_path, mode="r", arc_type="standard", far_type="default").get_fst() - - def far_exist(self) -> bool: - """ - Returns true if FAR can be loaded - """ - return self.far_path.exists() - - @property - def fst(self) -> 'pynini.FstLike': - return self._fst - - @fst.setter - def fst(self, fst): - self._fst = fst - - def add_tokens(self, fst) -> 'pynini.FstLike': - """ - Wraps class name around to given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - return pynutil.insert(f"{self.name} {{ ") + fst + pynutil.insert(" }") - - def delete_tokens(self, fst) -> 'pynini.FstLike': - """ - Deletes class name wrap around output of given fst - - Args: - fst: input fst - - Returns: - Fst: fst - """ - res = ( - pynutil.delete(f"{self.name}") - + delete_space - + pynutil.delete("{") - + delete_space - + fst - + delete_space - + pynutil.delete("}") - ) - return res @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA) diff --git a/nemo_text_processing/text_normalization/zh/taggers/__init__.py b/nemo_text_processing/text_normalization/zh/taggers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/taggers/cardinal.py b/nemo_text_processing/text_normalization/zh/taggers/cardinal.py deleted file mode 100644 index c593340c6e7a..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/cardinal.py +++ /dev/null @@ -1,107 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst -from nemo_text_processing.text_normalization.zh.utils import UNIT_1e01, UNIT_1e02, UNIT_1e03, UNIT_1e04, get_abs_path -from pynini.lib import pynutil - - -class Cardinal(GraphFst): - ''' - self.graph_cardinal: - 5 -> 五 - 12 -> 十二 - 213 -> 二百一十三 - 3123 -> 三千一百二十三 - 51234 -> 五万一千二百三十四 - 51,234 -> 五万一千二百三十四 - 0.125 -> 零点一二五 - self.fst: - 123 -> cardinal{ integer: "一二三" } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="cardinal", kind="classify", deterministic=deterministic) - # base cardinal from digit to chinese - graph_digit = pynini.string_file(get_abs_path("data/number/digit.tsv")) - graph_zero = pynini.string_file(get_abs_path("data/number/zero.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/number/digit_teen.tsv")) - graph_sign = pynini.string_file(get_abs_path("data/number/sign.tsv")) - - graph_digit_with_zero = graph_digit | graph_zero # from 0(read out) to 9 - graph_no_zero = pynini.cross("0", "") # cardinalzero,in some case we don't read it out - graph_digit_no_zero = graph_digit | graph_no_zero # from 0(not read out) to 9 - insert_zero = pynutil.insert('零') - delete_punct = pynutil.delete(",") # to deal with 5,000,cardinalin english form - - # 15 in 215 - graph_ten_u = (graph_digit + pynutil.insert(UNIT_1e01) + graph_digit_no_zero) | (graph_zero + graph_digit) - # 15 only - graph_ten = (graph_teen + pynutil.insert(UNIT_1e01) + graph_digit_no_zero) | (graph_zero + graph_digit) - # 215 or 200 - graph_hundred = (graph_digit + pynutil.insert(UNIT_1e02) + graph_ten_u) | ( - graph_digit + pynutil.insert(UNIT_1e02) + graph_no_zero ** 2 - ) - # 3000 or 3002 or 3012 or 3123 - # both with 3,000 or 3,002 or 3,012 or 3,123 - graph_thousand_sign = ( - (graph_digit + pynutil.insert(UNIT_1e03) + delete_punct + graph_hundred) - | ( - graph_digit - + pynutil.insert(UNIT_1e03) - + delete_punct.ques - + graph_zero - + graph_digit - + pynutil.insert(UNIT_1e01) - + graph_digit_no_zero - ) - | (graph_digit + pynutil.insert(UNIT_1e03) + delete_punct.ques + graph_zero + graph_no_zero + graph_digit) - | (graph_digit + pynutil.insert(UNIT_1e03) + delete_punct.ques + graph_no_zero ** 3) - ) - # 20001234 or 2001234 or 201234 or 21234 or 20234 or 20023 or 20002 or 20000 - # 8 digits max supported,for 9 digits cardinal,often write with unit instead of read it in only cardinalform - graph_ten_thousand_sign = ( - (graph_thousand_sign | graph_hundred | graph_ten | graph_digit_no_zero) - + pynutil.insert(UNIT_1e04) - + ( - graph_thousand_sign - | (graph_no_zero + delete_punct.ques + insert_zero + graph_hundred) - | ( - graph_no_zero - + delete_punct.ques - + graph_no_zero - + insert_zero - + (graph_digit + pynutil.insert(UNIT_1e01) + graph_digit_no_zero) - ) - | (graph_no_zero + delete_punct.ques + graph_no_zero ** 2 + insert_zero + graph_digit) - | (graph_no_zero ** 4) - ) - ) - - # cardinalstring like 123 or 123.456,used in phone cardinal,ID cardinal,etc. - graph_numstring = pynini.closure(graph_digit_with_zero, 1) | ( - pynini.closure(graph_digit_with_zero, 1) - + pynini.cross(".", "点") - + pynini.closure(graph_digit_with_zero, 1) - ) - - graph = graph_hundred | graph_ten | graph_digit_with_zero | graph_thousand_sign | graph_ten_thousand_sign - # 456.123 - graph_decimal = graph + pynini.cross('.', '点') + pynini.closure(graph_digit_with_zero, 1) - graph_cardinal = graph | graph_decimal - signed_cardinal = graph_sign + graph_cardinal - self.graph_cardinal = (graph_cardinal | signed_cardinal).optimize() - - graph_numstring = self.add_tokens(pynutil.insert("integer: \"") + graph_numstring + pynutil.insert("\"")) - self.fst = graph_numstring.optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/char.py b/nemo_text_processing/text_normalization/zh/taggers/char.py deleted file mode 100644 index f9ec516f39e6..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/char.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_CHAR, GraphFst -from pynini.lib import pynutil - - -class Char(GraphFst): - ''' - 你 -> char { name: "你" } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="char", kind="classify", deterministic=deterministic) - - graph = pynutil.insert("name: \"") + NEMO_CHAR + pynutil.insert("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/date.py b/nemo_text_processing/text_normalization/zh/taggers/date.py deleted file mode 100644 index 965f4db57dce..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/date.py +++ /dev/null @@ -1,105 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_CHAR, NEMO_DIGIT, GraphFst, insert_space -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil - - -class Date(GraphFst): - ''' - 2002年 -> tokens { date { year: "2002" } } - 2002-01-28 -> tokens { date { year: "2002" month: "01" day: "28"} } - 2002/01/28 -> tokens { date { year: "2002" month: "01" day: "28"} } - 2002.01.28 -> tokens { date { year: "2002" month: "01" day: "28"} } - 2002/02 -> tokens { date { year: "2002" month "02"} } - 02/11 -> tokens { date { year: "02" month "11"} } different with case "fraction 2/11" - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="date", kind="classify", deterministic=deterministic) - graph_digit = pynini.string_file(get_abs_path("data/number/digit.tsv")) - graph_zero = pynini.string_file(get_abs_path("data/number/zero.tsv")) - year_whitelist = pynini.string_file(get_abs_path("data/date/year_suffix.tsv")) - - delete_date_sign = pynutil.delete("/") | pynutil.delete('-') | pynutil.delete('.') - - # 2012年 - date_type0 = ( - pynutil.insert("year: \"") - + pynini.closure(graph_digit | graph_zero, 2, 4) - + "年" - + pynini.difference(NEMO_CHAR, year_whitelist) - + pynutil.insert("\"") - ) - - year_2_4_digit = pynini.closure(NEMO_DIGIT, 2, 4) + delete_date_sign - year_4_digit = pynini.closure(NEMO_DIGIT, 4, 4) + delete_date_sign - year_2_digit_with_zero = "0" + NEMO_DIGIT + delete_date_sign - month_no_day_with_zero = "0" + NEMO_DIGIT - month_no_day = pynini.closure(NEMO_DIGIT, 2, 2) - month = pynini.closure(NEMO_DIGIT, 1, 2) + delete_date_sign - day = pynini.closure(NEMO_DIGIT, 1, 2) - - # 2012/01/28 - date_type1 = ( - pynutil.insert("year: \"") - + year_2_4_digit - + pynutil.insert("\"") - + insert_space - + pynutil.insert("month: \"") - + month - + pynutil.insert("\"") - + insert_space - + pynutil.insert("day: \"") - + day - + pynutil.insert("\"") - ) - - # 12/01 - date_type2 = ( - pynutil.insert("year: \"") - + year_2_4_digit - + pynutil.insert("\"") - + insert_space - + pynutil.insert("month: \"") - + month_no_day_with_zero - + pynutil.insert("\"") - ) - - # 2012/11 - date_type3 = ( - pynutil.insert("year: \"") - + year_4_digit - + pynutil.insert("\"") - + insert_space - + pynutil.insert("month: \"") - + month_no_day - + pynutil.insert("\"") - ) - - # 02/05 - date_type4 = ( - pynutil.insert("year: \"") - + year_2_digit_with_zero - + pynutil.insert("\"") - + insert_space - + pynutil.insert("month: \"") - + month_no_day - + pynutil.insert("\"") - ) - # add your date type as date_typex here. - graph = date_type0 | date_type1 | date_type2 | date_type3 | date_type4 - - self.fst = self.add_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/fraction.py b/nemo_text_processing/text_normalization/zh/taggers/fraction.py deleted file mode 100644 index bfae533a1fda..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/fraction.py +++ /dev/null @@ -1,39 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_DIGIT, GraphFst, insert_space -from pynini.lib import pynutil - - -class Fraction(GraphFst): - ''' - 1/5 -> tokens { fraction { numerator: "1" denominator: "5" } } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="fraction", kind="classify", deterministic=deterministic) - - numerator = pynini.closure(NEMO_DIGIT, 1) + pynutil.delete('/') - denominator = pynini.closure(NEMO_DIGIT, 1) - graph = ( - pynutil.insert("numerator: \"") - + numerator - + pynutil.insert("\"") - + insert_space - + pynutil.insert("denominator: \"") - + denominator - + pynutil.insert("\"") - ) - - self.fst = self.add_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/math_symbol.py b/nemo_text_processing/text_normalization/zh/taggers/math_symbol.py deleted file mode 100644 index 28d223ae36e5..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/math_symbol.py +++ /dev/null @@ -1,41 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst -from nemo_text_processing.text_normalization.zh.taggers.cardinal import Cardinal -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil - - -class MathSymbol(GraphFst): - ''' - + -> tokens { sign: "加" } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="sign", kind="classify", deterministic=deterministic) - ''' - add your sign in data/math/symbol.tsv,this graph just convert sigh to character,you can add more - cases with detailed cases - ''' - score_sign = pynini.string_file(get_abs_path("data/math/score.tsv")) - score = ( - pynutil.insert("score: \"") - + Cardinal().graph_cardinal - + score_sign - + Cardinal().graph_cardinal - + pynutil.insert("\"") - ) - graph = score - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/measure.py b/nemo_text_processing/text_normalization/zh/taggers/measure.py deleted file mode 100644 index 503bd2b3f5eb..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/measure.py +++ /dev/null @@ -1,52 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst, insert_space -from nemo_text_processing.text_normalization.zh.taggers.cardinal import Cardinal -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil - - -class Measure(GraphFst): - ''' - 1kg -> tokens { measure { cardinal { integer: "一" } units: "千克" } } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="measure", kind="classify", deterministic=deterministic) - - units_en = pynini.string_file(get_abs_path("data/measure/units_en.tsv")) - units_zh = pynini.string_file(get_abs_path("data/measure/units_zh.tsv")) - graph = ( - pynutil.insert("cardinal { ") - + pynutil.insert("integer: \"") - + Cardinal().graph_cardinal - + pynutil.insert("\"") - + pynutil.insert(" }") - + insert_space - + pynutil.insert("units: \"") - + (units_en | units_zh) - + pynutil.insert("\"") - ) - percent_graph = ( - pynutil.insert("decimal { ") - + pynutil.insert("integer_part: \"") - + Cardinal().graph_cardinal - + pynutil.delete("%") - + pynutil.insert("\"") - + pynutil.insert(" }") - ) - graph |= percent_graph - - self.fst = self.add_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/money.py b/nemo_text_processing/text_normalization/zh/taggers/money.py deleted file mode 100644 index c81dae22626b..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/money.py +++ /dev/null @@ -1,41 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst, insert_space -from nemo_text_processing.text_normalization.zh.taggers.cardinal import Cardinal -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil - - -class Money(GraphFst): - ''' - ￥1.25 -> tokens { money { fractional_part: "元" integer_part: "一点五" } } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="money", kind="classify", deterministic=deterministic) - - currency_code = pynini.string_file(get_abs_path("data/money/currency_code.tsv")) - currency_symbol = pynini.string_file(get_abs_path("data/money/currency_symbol.tsv")) - graph = ( - pynutil.insert("fractional_part: \"") - + (currency_code | currency_symbol) - + pynutil.insert("\"") - + insert_space - + pynutil.insert("integer_part: \"") - + Cardinal().graph_cardinal - + pynutil.insert("\"") - ) - - self.fst = self.add_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/preprocessor.py b/nemo_text_processing/text_normalization/zh/taggers/preprocessor.py deleted file mode 100644 index 57d672dc62e1..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/preprocessor.py +++ /dev/null @@ -1,46 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_SIGMA, GraphFst -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil - - -class PreProcessor(GraphFst): - ''' - Preprocessing of TN: - 1. interjections removal such as '啊, 呃' - 2. fullwidth -> halfwidth char conversion - 好啊 -> 好 - 呃对 -> 对 - ： -> : - ； -> ; - ''' - - def __init__( - self, remove_interjections: bool = True, fullwidth_to_halfwidth: bool = True, - ): - super().__init__(name="PreProcessor", kind="processor") - - graph = pynini.cdrewrite('', '', '', NEMO_SIGMA) - - if remove_interjections: - remove_interjections_graph = pynutil.delete(pynini.string_file(get_abs_path('data/denylist/denylist.tsv'))) - graph @= pynini.cdrewrite(remove_interjections_graph, '', '', NEMO_SIGMA) - - if fullwidth_to_halfwidth: - fullwidth_to_halfwidth_graph = pynini.string_file(get_abs_path('data/char/fullwidth_to_halfwidth.tsv')) - graph @= pynini.cdrewrite(fullwidth_to_halfwidth_graph, '', '', NEMO_SIGMA) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/time.py b/nemo_text_processing/text_normalization/zh/taggers/time.py deleted file mode 100644 index f9fadccb9027..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/time.py +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst, insert_space -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil - - -class Time(GraphFst): - ''' - 1:02 -> tokens { time { hours: "1" minitus: "02" } } - 1:02:36 -> tokens { time { hours: "1" minutes: "02" seconds: "36" } } - 1:02 am -> tokens { time { hours: "1" minutes: "02" seconds: "36" suffix "am" } } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="time", kind="classify", deterministic=deterministic) - - h = pynini.string_file(get_abs_path("data/time/hour.tsv")) - time_tens = pynini.string_file(get_abs_path("data/time/tens.tsv")) - time_digit = pynini.string_file(get_abs_path("data/time/digit.tsv")) - time_zero = pynini.string_file(get_abs_path("data/time/zero.tsv")) - time_digit = time_digit | time_zero - time_suffix = pynini.string_file(get_abs_path("data/time/suffix.tsv")) - - m = time_tens + time_digit - s = (time_tens + time_digit) | time_digit - - delete_colon = pynini.cross(':', ' ') - - # 5:05, 14:30 - h_m = ( - pynutil.insert('hours: \"') - + h - + pynutil.insert('\"') - + delete_colon - + pynutil.insert('minutes: \"') - + m - + pynutil.insert('\"') - ) - - # 1:30:15 - h_m_s = ( - pynutil.insert('hours: \"') - + h - + pynutil.insert('\"') - + delete_colon - + pynutil.insert('minutes: \"') - + m - + pynutil.insert('\"') - + delete_colon - + pynutil.insert('seconds: \"') - + s - + pynutil.insert('\"') - ) - - graph = h_m | h_m_s - graph_suffix = graph + insert_space + pynutil.insert('suffix: \"') + time_suffix + pynutil.insert('\"') - graph |= graph_suffix - self.fst = self.add_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/taggers/tokenize_and_classify.py b/nemo_text_processing/text_normalization/zh/taggers/tokenize_and_classify.py deleted file mode 100644 index 2d3c13e0acbb..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/tokenize_and_classify.py +++ /dev/null @@ -1,92 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import os - -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst -from nemo_text_processing.text_normalization.zh.taggers.cardinal import Cardinal -from nemo_text_processing.text_normalization.zh.taggers.char import Char -from nemo_text_processing.text_normalization.zh.taggers.date import Date -from nemo_text_processing.text_normalization.zh.taggers.fraction import Fraction -from nemo_text_processing.text_normalization.zh.taggers.math_symbol import MathSymbol -from nemo_text_processing.text_normalization.zh.taggers.measure import Measure -from nemo_text_processing.text_normalization.zh.taggers.money import Money -from nemo_text_processing.text_normalization.zh.taggers.preprocessor import PreProcessor -from nemo_text_processing.text_normalization.zh.taggers.time import Time -from nemo_text_processing.text_normalization.zh.taggers.whitelist import Whitelist -from pynini.lib import pynutil - - -class ClassifyFst(GraphFst): - """ - Final class that composes all other classification grammars. This class can process an entire sentence including punctuation. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - - Args: - input_case: accepting either "lower_cased" or "cased" input. - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache. - overwrite_cache: set to True to overwrite .far files - whitelist: path to a file with whitelist replacements - """ - - def __init__( - self, - input_case: str, - deterministic: bool = True, - cache_dir: str = None, - overwrite_cache: bool = False, - whitelist: str = None, - ): - super().__init__(name="tokenize_and_classify", kind="classify", deterministic=deterministic) - - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - whitelist_file = os.path.basename(whitelist) if whitelist else "" - far_file = os.path.join( - cache_dir, f"zh_tn_{deterministic}_deterministic_{input_case}_{whitelist_file}_tokenize.far" - ) - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"] - else: - date = Date(deterministic=deterministic) - cardinal = Cardinal(deterministic=deterministic) - char = Char(deterministic=deterministic) - fraction = Fraction(deterministic=deterministic) - math_symbol = MathSymbol(deterministic=deterministic) - money = Money(deterministic=deterministic) - measure = Measure(deterministic=deterministic) - time = Time(deterministic=deterministic) - whitelist = Whitelist(deterministic=deterministic) - - classify = pynini.union( - pynutil.add_weight(date.fst, 1.02), - pynutil.add_weight(fraction.fst, 1.05), - pynutil.add_weight(money.fst, 1.05), - pynutil.add_weight(measure.fst, 1.05), - pynutil.add_weight(time.fst, 1.05), - pynutil.add_weight(whitelist.fst, 1.03), - pynutil.add_weight(cardinal.fst, 1.06), - pynutil.add_weight(math_symbol.fst, 1.08), - pynutil.add_weight(char.fst, 100), - ) - token = pynutil.insert("tokens { ") + classify + pynutil.insert(" } ") - - tagger = token.optimize().star - - preprocessor = PreProcessor(remove_interjections=True, fullwidth_to_halfwidth=True,) - self.fst = preprocessor.fst @ tagger diff --git a/nemo_text_processing/text_normalization/zh/taggers/whitelist.py b/nemo_text_processing/text_normalization/zh/taggers/whitelist.py deleted file mode 100644 index 4bcfa37a7d97..000000000000 --- a/nemo_text_processing/text_normalization/zh/taggers/whitelist.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil - - -class Whitelist(GraphFst): - ''' - ATM -> tokens { whitelist: "ATM" } - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="whitelist", kind="classify", deterministic=deterministic) - - whitelist = pynini.string_file(get_abs_path("data/whitelist/default.tsv")) - erhua = pynutil.insert("erhua: \"") + pynini.accep('儿') + pynutil.insert("\"") - sign = pynini.string_file(get_abs_path("data/math/symbol.tsv")) - whitelist = ( - pynutil.insert("name: \"") - + (pynini.string_file(get_abs_path("data/erhua/whitelist.tsv")) | whitelist | sign) - + pynutil.insert("\"") - ) - graph = pynutil.add_weight(erhua, 0.1) | whitelist - - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/utils.py b/nemo_text_processing/text_normalization/zh/utils.py deleted file mode 100644 index 707949ac7f0d..000000000000 --- a/nemo_text_processing/text_normalization/zh/utils.py +++ /dev/null @@ -1,64 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import csv -import os - -UNIT_1e01 = '十' -UNIT_1e02 = '百' -UNIT_1e03 = '千' -UNIT_1e04 = '万' - - -def get_abs_path(rel_path): - """ - Get absolute path - - Args: - rel_path: relative path to this file - - Returns absolute path - """ - return os.path.dirname(os.path.abspath(__file__)) + '/' + rel_path - - -def load_labels(abs_path): - """ - loads relative path file as dictionary - - Args: - abs_path: absolute path - - Returns dictionary of mappings - """ - with open(abs_path, encoding="utf-8") as label_tsv: - labels = list(csv.reader(label_tsv, delimiter="\t")) - return labels - - -def augment_labels_with_punct_at_end(labels): - """ - augments labels: if key ends on a punctuation that value does not have, add a new label - where the value maintains the punctuation - - Args: - labels : input labels - Returns: - additional labels - """ - res = [] - for label in labels: - if len(label) > 1: - if label[0][-1] == "." and label[1][-1] != ".": - res.append([label[0], label[1] + "."] + label[2:]) - return res diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/__init__.py b/nemo_text_processing/text_normalization/zh/verbalizers/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/cardinal.py b/nemo_text_processing/text_normalization/zh/verbalizers/cardinal.py deleted file mode 100644 index e60b6c341039..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/cardinal.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class Cardinal(GraphFst): - ''' - tokens { cardinal { integer: "一二三" } } -> 一二三 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="cardinal", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete('integer: \"') + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete('\"') - - self.fst = self.delete_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/char.py b/nemo_text_processing/text_normalization/zh/verbalizers/char.py deleted file mode 100644 index 5f241f476b56..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/char.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class Char(GraphFst): - ''' - tokens { char: "你" } -> 你 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="char", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete("name: \"") + NEMO_NOT_QUOTE + pynutil.delete("\"") - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/date.py b/nemo_text_processing/text_normalization/zh/verbalizers/date.py deleted file mode 100644 index f808ae4033f6..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/date.py +++ /dev/null @@ -1,70 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from nemo_text_processing.text_normalization.zh.utils import UNIT_1e01, get_abs_path -from pynini.lib import pynutil - - -class Date(GraphFst): - ''' - tokens { date { year: "2002" month: "01" day: "28"} } -> 二零零二年一月二十八日 - tokens { date { year: "2002" } } -> 二零零八年 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="date", kind="verbalize", deterministic=deterministic) - date_type0 = pynutil.delete('year: \"') + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete('\"') - graph_digit = pynini.string_file(get_abs_path("data/number/digit.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/number/digit_teen.tsv")) - graph_zero = pynini.string_file(get_abs_path("data/number/zero.tsv")) - graph_no_zero = pynini.cross("0", "") - graph_year = pynini.closure(graph_digit | graph_zero, 2, 4) - graph_digit_no_zero = graph_digit | graph_no_zero - graph_2_digit_date = (graph_teen + pynutil.insert(UNIT_1e01) + graph_digit_no_zero) | ( - graph_no_zero + graph_digit - ) - - date_type1 = ( - pynutil.delete("year: \"") - + graph_year - + pynutil.insert("年") - + pynutil.delete("\"") - + delete_space - + pynutil.delete("month: \"") - + graph_2_digit_date - + pynutil.insert("月") - + pynutil.delete("\"") - + delete_space - + pynutil.delete("day: \"") - + graph_2_digit_date - + pynutil.insert("日") - + pynutil.delete("\"") - ) - - date_type2 = ( - pynutil.delete("year: \"") - + graph_year - + pynutil.insert("年") - + pynutil.delete("\"") - + delete_space - + pynutil.delete("month: \"") - + graph_2_digit_date - + pynutil.insert("月") - + pynutil.delete("\"") - ) - - graph = date_type0 | date_type1 | date_type2 - - self.fst = self.delete_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/fraction.py b/nemo_text_processing/text_normalization/zh/verbalizers/fraction.py deleted file mode 100644 index ba7b0bc0998e..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/fraction.py +++ /dev/null @@ -1,31 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst -from nemo_text_processing.text_normalization.zh.taggers.cardinal import Cardinal -from pynini.lib import pynutil - - -class Fraction(GraphFst): - ''' - tokens { fraction { denominator: "5" numerator: "1" } } -> 五分之一 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="fraction", kind="verbalize", deterministic=deterministic) - - denominator = pynutil.delete("denominator: \"") + Cardinal().graph_cardinal + pynutil.delete("\"") - numerator = pynutil.delete("numerator: \"") + Cardinal().graph_cardinal + pynutil.delete("\"") - graph = denominator + pynutil.delete(" ") + pynutil.insert("分之") + numerator - - self.fst = self.delete_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/math_symbol.py b/nemo_text_processing/text_normalization/zh/verbalizers/math_symbol.py deleted file mode 100644 index 924f9b5abdb9..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/math_symbol.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class MathSymbol(GraphFst): - ''' - tokens { sign: "加" } -> 加 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="sign", kind="verbalize", deterministic=deterministic) - - graph = pynutil.delete('score: \"') + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete('\"') - - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/measure.py b/nemo_text_processing/text_normalization/zh/verbalizers/measure.py deleted file mode 100644 index b7e0d156f848..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/measure.py +++ /dev/null @@ -1,50 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class Measure(GraphFst): - ''' - tokens { measure { cardinal: "一" } units: "千克" } } -> 一千克 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="measure", kind="verbalize", deterministic=deterministic) - - graph = ( - pynutil.delete("cardinal {") - + delete_space - + pynutil.delete("integer: \"") - + pynini.closure(NEMO_NOT_QUOTE) - + pynutil.delete("\"") - + delete_space - + pynutil.delete("}") - + delete_space - + pynutil.delete("units: \"") - + pynini.closure(NEMO_NOT_QUOTE) - + pynutil.delete("\"") - ) - percent_graph = ( - pynutil.delete("decimal { ") - + pynutil.delete("integer_part: \"") - + pynutil.insert("百分之") - + pynini.closure(NEMO_NOT_QUOTE, 1) - + pynutil.delete("\"") - + delete_space - + pynutil.delete("}") - ) - graph |= percent_graph - self.fst = self.delete_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/money.py b/nemo_text_processing/text_normalization/zh/verbalizers/money.py deleted file mode 100644 index 301b7db03638..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/money.py +++ /dev/null @@ -1,31 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from pynini.lib import pynutil - - -class Money(GraphFst): - ''' - tokens { money { integer_part: "一点五" fractional_part: "元" } } -> 一点五元 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="money", kind="verbalize", deterministic=deterministic) - - cur = pynutil.delete("fractional_part: \"") + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\"") - num = pynutil.delete("integer_part: \"") + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\"") + delete_space - graph = num + cur - - self.fst = self.delete_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/postprocessor.py b/nemo_text_processing/text_normalization/zh/verbalizers/postprocessor.py deleted file mode 100644 index 67b0b1954200..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/postprocessor.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import ( - NEMO_ALPHA, - NEMO_DIGIT, - NEMO_PUNCT, - NEMO_SIGMA, - NEMO_WHITE_SPACE, - GraphFst, -) -from nemo_text_processing.text_normalization.zh.utils import get_abs_path -from pynini.lib import pynutil, utf8 - - -class PostProcessor(GraphFst): - ''' - Postprocessing of TN, now contains: - 1. punctuation removal - 2. letter case conversion - 3. oov tagger - ''' - - def __init__( - self, remove_puncts: bool = False, to_upper: bool = False, to_lower: bool = False, tag_oov: bool = False, - ): - super().__init__(name="PostProcessor", kind="processor") - - graph = pynini.cdrewrite('', '', '', NEMO_SIGMA) - if remove_puncts: - remove_puncts_graph = pynutil.delete( - pynini.union(NEMO_PUNCT, pynini.string_file(get_abs_path('data/char/punctuations_zh.tsv'))) - ) - graph @= pynini.cdrewrite(remove_puncts_graph, "", "", NEMO_SIGMA).optimize() - - if to_upper or to_lower: - if to_upper: - conv_cases_graph = pynini.inverse(pynini.string_file(get_abs_path('data/char/upper_to_lower.tsv'))) - else: - conv_cases_graph = pynini.string_file(get_abs_path('data/char/upper_to_lower.tsv')) - - graph @= pynini.cdrewrite(conv_cases_graph, "", "", NEMO_SIGMA).optimize() - - if tag_oov: - zh_charset_std = pynini.string_file(get_abs_path("data/char/charset_national_standard_2013_8105.tsv")) - zh_charset_ext = pynini.string_file(get_abs_path("data/char/charset_extension.tsv")) - - zh_charset = ( - zh_charset_std | zh_charset_ext | pynini.string_file(get_abs_path("data/char/punctuations_zh.tsv")) - ) - en_charset = NEMO_DIGIT | NEMO_ALPHA | NEMO_PUNCT | NEMO_WHITE_SPACE - charset = zh_charset | en_charset - - with open(get_abs_path("data/char/oov_tags.tsv"), "r") as f: - tags = f.readline().strip().split('\t') - assert len(tags) == 2 - ltag, rtag = tags - - oov_charset = pynini.difference(utf8.VALID_UTF8_CHAR, charset) - tag_oov_graph = pynutil.insert(ltag) + oov_charset + pynutil.insert(rtag) - graph @= pynini.cdrewrite(tag_oov_graph, "", "", NEMO_SIGMA).optimize() - - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/time.py b/nemo_text_processing/text_normalization/zh/verbalizers/time.py deleted file mode 100644 index 5784d1a693a9..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/time.py +++ /dev/null @@ -1,93 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst, delete_space -from nemo_text_processing.text_normalization.zh.utils import UNIT_1e01, get_abs_path -from pynini.lib import pynutil - - -class Time(GraphFst): - ''' - tokens { time { h: "1" m: "02" s: "36" } } -> 一点零二分三十六秒 - tokens { time { suffix "am" hours: "1" minutes: "02" seconds: "36" } } -> 上午一点零二分三十六秒 - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="time", kind="verbalize", deterministic=deterministic) - graph_digit = pynini.string_file(get_abs_path("data/number/digit.tsv")) - graph_teen = pynini.string_file(get_abs_path("data/number/digit_teen.tsv")) - graph_zero = pynini.string_file(get_abs_path("data/number/zero.tsv")) - graph_no_zero = pynini.cross("0", "") - - graph_digit_no_zero = graph_digit | graph_no_zero - - graph_2_digit_zero_none = pynini.cross("0", "") + pynini.cross("0", "") - graph_2_digit_zero = pynini.cross("00", "零") - - graph_2_digit_time = (graph_teen + pynutil.insert(UNIT_1e01) + graph_digit_no_zero) | ( - graph_zero + graph_digit - ) - h = graph_2_digit_time | graph_2_digit_zero | graph_digit - m = graph_2_digit_time | graph_2_digit_zero - s = graph_2_digit_time | graph_2_digit_zero - - # 6:25 - h_m = ( - pynutil.delete("hours: \"") - + h - + pynutil.insert("点") - + pynutil.delete("\"") - + delete_space - + pynutil.delete("minutes: \"") - + (graph_2_digit_time) - + pynutil.insert("分") - + pynutil.delete("\"") - ) - - # 23:00 - h_00 = ( - pynutil.delete("hours: \"") - + h - + pynutil.insert("点") - + pynutil.delete("\"") - + delete_space - + pynutil.delete("minutes: \"") - + (graph_2_digit_zero_none) - + pynutil.delete("\"") - ) - - # 9:12:52 - h_m_s = ( - pynutil.delete("hours: \"") - + h - + pynutil.insert("点") - + pynutil.delete("\"") - + delete_space - + pynutil.delete("minutes: \"") - + m - + pynutil.insert("分") - + pynutil.delete("\"") - + delete_space - + pynutil.delete("seconds: \"") - + s - + pynutil.insert("秒") - + pynutil.delete("\"") - ) - - graph = h_m | h_m_s | h_00 - graph_suffix = ( - pynutil.delete("suffix: \"") + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\"") + delete_space + graph - ) - graph |= graph_suffix - self.fst = self.delete_tokens(graph).optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/verbalize.py b/nemo_text_processing/text_normalization/zh/verbalizers/verbalize.py deleted file mode 100644 index dd01e63ca162..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/verbalize.py +++ /dev/null @@ -1,62 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst -from nemo_text_processing.text_normalization.zh.verbalizers.cardinal import Cardinal -from nemo_text_processing.text_normalization.zh.verbalizers.char import Char -from nemo_text_processing.text_normalization.zh.verbalizers.date import Date -from nemo_text_processing.text_normalization.zh.verbalizers.fraction import Fraction -from nemo_text_processing.text_normalization.zh.verbalizers.math_symbol import MathSymbol -from nemo_text_processing.text_normalization.zh.verbalizers.measure import Measure -from nemo_text_processing.text_normalization.zh.verbalizers.money import Money -from nemo_text_processing.text_normalization.zh.verbalizers.time import Time -from nemo_text_processing.text_normalization.zh.verbalizers.whitelist import Whitelist - - -class VerbalizeFst(GraphFst): - """ - Composes other verbalizer grammars. - For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. - More details to deployment at NeMo/tools/text_processing_deployment. - Args: - deterministic: if True will provide a single transduction option, - for False multiple options (used for audio-based normalization) - """ - - def __init__(self, deterministic: bool = True): - super().__init__(name="verbalize", kind="verbalize", deterministic=deterministic) - - date = Date(deterministic=deterministic) - cardinal = Cardinal(deterministic=deterministic) - char = Char(deterministic=deterministic) - fraction = Fraction(deterministic=deterministic) - math_symbol = MathSymbol(deterministic=deterministic) - money = Money(deterministic=deterministic) - measure = Measure(deterministic=deterministic) - time = Time(deterministic=deterministic) - whitelist = Whitelist(deterministic=deterministic) - - graph = pynini.union( - date.fst, - cardinal.fst, - fraction.fst, - char.fst, - math_symbol.fst, - money.fst, - measure.fst, - time.fst, - whitelist.fst, - ) - - self.fst = graph.optimize() diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/verbalize_final.py b/nemo_text_processing/text_normalization/zh/verbalizers/verbalize_final.py deleted file mode 100644 index 2be00adecd25..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/verbalize_final.py +++ /dev/null @@ -1,49 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import os - -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import GraphFst, delete_space, generator_main -from nemo_text_processing.text_normalization.zh.verbalizers.postprocessor import PostProcessor -from nemo_text_processing.text_normalization.zh.verbalizers.verbalize import VerbalizeFst -from pynini.lib import pynutil - -# from nemo.utils import logging - - -class VerbalizeFinalFst(GraphFst): - """ - - """ - - def __init__(self, deterministic: bool = True, cache_dir: str = None, overwrite_cache: bool = False): - super().__init__(name="verbalize_final", kind="verbalize", deterministic=deterministic) - far_file = None - if cache_dir is not None and cache_dir != "None": - os.makedirs(cache_dir, exist_ok=True) - far_file = os.path.join(cache_dir, f"zh_tn_{deterministic}_deterministic_verbalizer.far") - if not overwrite_cache and far_file and os.path.exists(far_file): - self.fst = pynini.Far(far_file, mode="r")["verbalize"] - else: - token_graph = VerbalizeFst(deterministic=deterministic) - token_verbalizer = ( - pynutil.delete("tokens {") + delete_space + token_graph.fst + delete_space + pynutil.delete(" }") - ) - verbalizer = pynini.closure(delete_space + token_verbalizer + delete_space) - - postprocessor = PostProcessor(remove_puncts=False, to_upper=False, to_lower=False, tag_oov=False,) - - self.fst = (verbalizer @ postprocessor.fst).optimize() - if far_file: - generator_main(far_file, {"verbalize": self.fst}) diff --git a/nemo_text_processing/text_normalization/zh/verbalizers/whitelist.py b/nemo_text_processing/text_normalization/zh/verbalizers/whitelist.py deleted file mode 100644 index e9780744f07a..000000000000 --- a/nemo_text_processing/text_normalization/zh/verbalizers/whitelist.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import pynini -from nemo_text_processing.text_normalization.zh.graph_utils import NEMO_NOT_QUOTE, GraphFst -from pynini.lib import pynutil - - -class Whitelist(GraphFst): - ''' - tokens { whitelist: "ATM" } -> A T M - ''' - - def __init__(self, deterministic: bool = True, lm: bool = False): - super().__init__(name="whitelist", kind="verbalize", deterministic=deterministic) - remove_erhua = pynutil.delete("erhua: \"") + pynutil.delete("儿") + pynutil.delete("\"") - whitelist = pynutil.delete("name: \"") + pynini.closure(NEMO_NOT_QUOTE) + pynutil.delete("\"") - graph = remove_erhua | whitelist - self.fst = graph.optimize() diff --git a/reinstall.sh b/reinstall.sh index b4c532037c3b..f89d86141b62 100755 --- a/reinstall.sh +++ b/reinstall.sh @@ -37,7 +37,4 @@ else ${PIP} install "${DIST_FILE}[all]" fi -echo 'Installing additional pynini dependency' -bash nemo_text_processing/install_pynini.sh > /dev/null 2>&1 && echo "nemo_text_processing installed!" || echo "nemo_text_processing could not be installed!" - echo 'All done!' diff --git a/requirements/requirements_nemo_text_processing.txt b/requirements/requirements_nemo_text_processing.txt index 9b7085f3ede7..989ce0ac03b0 100644 --- a/requirements/requirements_nemo_text_processing.txt +++ b/requirements/requirements_nemo_text_processing.txt @@ -1,2 +1 @@ -inflect -regex +nemo_text_processing==0.1.6rc0 diff --git a/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py b/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py index 0819dc8384ce..28f9cdd4e499 100644 --- a/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py +++ b/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py @@ -125,8 +125,8 @@ def correct_wikihomograph_data(sentence: str, start: int = None, end: int = None if sentence in corrections: start, end = corrections[sentence] - sentence = sentence.replace("2014Coordinate", "2014 Coordinate") # for normalized data for G2P OOV models - sentence = sentence.replace("AAA", "triple A") # for normalized data for G2P OOV models + sentence = sentence.replace("2014Coordinate", "2014 Coordinate") # for normalized data for G2P_paper OOV models + sentence = sentence.replace("AAA", "triple A") # for normalized data for G2P_paper OOV models return sentence, start, end diff --git a/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py b/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py index f81726d44b06..54fc0f061ca8 100644 --- a/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py +++ b/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py @@ -13,7 +13,7 @@ # limitations under the License. import pytest -from nemo_text_processing.g2p.modules import IPAG2P +from nemo.collections.tts.g2p.modules import IPAG2P from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import ( EnglishCharsTokenizer, diff --git a/tests/nemo_text_processing/g2p/data/test_data_utils.py b/tests/collections/tts/g2p/data/test_data_utils.py similarity index 93% rename from tests/nemo_text_processing/g2p/data/test_data_utils.py rename to tests/collections/tts/g2p/data/test_data_utils.py index c04a4d0f0e13..49faa857526d 100644 --- a/tests/nemo_text_processing/g2p/data/test_data_utils.py +++ b/tests/collections/tts/g2p/data/test_data_utils.py @@ -13,10 +13,10 @@ # limitations under the License. import pytest -from nemo_text_processing.g2p.data.data_utils import ( +from nemo.collections.tts.g2p.data.data_utils import ( any_locale_word_tokenize, english_word_tokenize, - get_homograph_spans, + get_heteronym_spans, ) @@ -124,8 +124,8 @@ def test_any_locale_word_tokenize_with_numbers(self): @pytest.mark.run_only_on('CPU') @pytest.mark.unit - def test_get_homograph_spans(self): - supported_homographs = ["live", "read", "protest", "diffuse", "desert"] + def test_get_heteronym_spans(self): + supported_heteronyms = ["live", "read", "protest", "diffuse", "desert"] sentences = [ "I live in California. I READ a book. Only people who have already gained something are willing to protest. He reads a book!", "Yesterday, I read a book.", @@ -139,13 +139,13 @@ def test_get_homograph_spans(self): [(3, 7), (34, 41), (46, 50), (64, 70)], [(25, 31), (35, 41)], ] - expected_homographs = [ + expected_heteronyms = [ ["live", "read", "protest"], ['read'], ['read', 'diffuse', 'live', 'desert'], ['desert', 'desert'], ] - out_start_end, out_homographs = get_homograph_spans(sentences, supported_homographs) + out_start_end, out_heteronyms = get_heteronym_spans(sentences, supported_heteronyms) assert out_start_end == expected_start_end, "start-end spans do not match" - assert out_homographs == expected_homographs, "homograph spans do not match" + assert out_heteronyms == expected_heteronyms, "heteronym spans do not match" diff --git a/tests/nemo_text_processing/g2p/phoneme_dict/test_dict_de.txt b/tests/collections/tts/g2p/phoneme_dict/test_dict_de.txt similarity index 100% rename from tests/nemo_text_processing/g2p/phoneme_dict/test_dict_de.txt rename to tests/collections/tts/g2p/phoneme_dict/test_dict_de.txt diff --git a/tests/nemo_text_processing/g2p/phoneme_dict/test_dict_en.txt b/tests/collections/tts/g2p/phoneme_dict/test_dict_en.txt similarity index 100% rename from tests/nemo_text_processing/g2p/phoneme_dict/test_dict_en.txt rename to tests/collections/tts/g2p/phoneme_dict/test_dict_en.txt diff --git a/tests/nemo_text_processing/g2p/phoneme_dict/test_dict_es.txt b/tests/collections/tts/g2p/phoneme_dict/test_dict_es.txt similarity index 100% rename from tests/nemo_text_processing/g2p/phoneme_dict/test_dict_es.txt rename to tests/collections/tts/g2p/phoneme_dict/test_dict_es.txt diff --git a/tests/nemo_text_processing/g2p/test_modules.py b/tests/collections/tts/g2p/test_modules.py similarity index 99% rename from tests/nemo_text_processing/g2p/test_modules.py rename to tests/collections/tts/g2p/test_modules.py index 130eb79eb36f..196239c65f7f 100644 --- a/tests/nemo_text_processing/g2p/test_modules.py +++ b/tests/collections/tts/g2p/test_modules.py @@ -16,8 +16,8 @@ import unicodedata import pytest -from nemo_text_processing.g2p.data.data_utils import GRAPHEME_CASE_LOWER, GRAPHEME_CASE_MIXED, GRAPHEME_CASE_UPPER -from nemo_text_processing.g2p.modules import IPAG2P +from nemo.collections.tts.g2p.data.data_utils import GRAPHEME_CASE_LOWER, GRAPHEME_CASE_MIXED, GRAPHEME_CASE_UPPER +from nemo.collections.tts.g2p.modules import IPAG2P class TestIPAG2P: diff --git a/tests/collections/tts/test_torch_tts.py b/tests/collections/tts/test_torch_tts.py index f99ebda8880d..4a1c2a4e0990 100644 --- a/tests/collections/tts/test_torch_tts.py +++ b/tests/collections/tts/test_torch_tts.py @@ -18,7 +18,7 @@ import pytest import torch -from nemo_text_processing.g2p.modules import EnglishG2p +from nemo.collections.tts.g2p.modules import EnglishG2p from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import EnglishPhonemesTokenizer from nemo.collections.tts.torch.data import TTSDataset diff --git a/tests/conftest.py b/tests/conftest.py index 206dad62f939..5987416e22e3 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -55,15 +55,6 @@ def pytest_addoption(parser): help="numba compatibility checks will be relaxed to just availability of cuda, " "without cuda compatibility matrix check", ) - parser.addoption( - '--tn_cache_dir', - type=str, - default=None, - help="path to a directory with .far grammars for CPU TN/ITN tests, (DEFAULT: None, i.e. no cache)", - ) - parser.addoption( - '--run_audio_based', action='store_true', help="pass this argument to run audio-based TN tests", - ) @pytest.fixture @@ -231,9 +222,3 @@ def pytest_configure(config): print("Setting numba compat :", config.option.relax_numba_compat) numba_utils.set_numba_compat_strictness(strict=config.option.relax_numba_compat) - - # Set cache directory for TN/ITN tests - from .nemo_text_processing.utils import set_audio_based_tests, set_cache_dir - - set_cache_dir(config.option.tn_cache_dir) - set_audio_based_tests(config.option.run_audio_based) diff --git a/tests/nemo_text_processing/__init__.py b/tests/nemo_text_processing/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/tests/nemo_text_processing/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/de/__init__.py b/tests/nemo_text_processing/de/__init__.py deleted file mode 100644 index 9e3250071955..000000000000 --- a/tests/nemo_text_processing/de/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index 0b2064296162..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,62 +0,0 @@ -ein hundert~100 -einhundert~100 -ein hundert und zwei~102 -einhundertzwei~102 -ein hundert und zwanzig~120 -ein hundert und elf~111 -ein tausend~1000 -eintausend~1000 -ein hundert zwanzig~120 -ein tausend zwanzig~1020 -eintausendzwanzig~1020 -neun billionen sieben hundert neun und achtzig milliarden drei hundert zwei und achtzig millionen fünf hundert sechs und dreißig tausend ein hundert dreißig~9789382536130 -zwei hundert vier und fünfzig~254 -ein hundert sieben und vierzig tausend vier hundert ein und fünfzig~147451 -eine million ein hundert sechs und fünfzig tausend ein hundert drei und siebzig~1156173 -eine milliarde fünf hundert drei und neunzig millionen zwei und siebzig tausend neun hundert ein und sechzig~1593072961 -sieben und neunzig billiarden acht hundert acht billionen zwei hundert vier und sechzig milliarden sieben hundert zwei und siebzig millionen sieben hundert zwei und neunzig tausend fünf~97808264772792005 -zehn billiarden zehn billionen zehn millionen ein hundert tausend zehn~10010000010100010 -zehn billiarden zehn billionen zehn millionen einhunderttausendzehn~10010000010100010 -minus fünf und zwanzig tausend sieben und dreißig~-25037 -minus fünf und zwanzig tausend sieben und dreißig~-25037 -minus fünfundzwanzigtausendsiebenunddreißig~-25037 -eine billiarde zwei hundert vier und sechzig billionen drei hundert eins milliarden neun hundert acht und dreißig millionen ein hundert vier~1264301938000104 -eine billiarde zweihundertvierundsechzig billionen dreihunderteins milliarden neunhundertachtunddreißig millionen einhundertvier~1264301938000104 -minus sechzig~-60 -sechs und vierzig tausend sechs hundert vier und sechzig~46664 -sechzig~60 -null~null -eins~eins -ein~ein -eine~eine -einer~einer -zwei~zwei -neun~neun -zehn~10 -elf~11 -zwölf~12 -dreizehn~13 -vierzehn~14 -fünfzehn~15 -sechzehn~16 -siebzehn~17 -achtzehn~18 -zwanzig~20 -dreißig~30 -vierzig~40 -fünfzig~50 -sechzig~60 -siebzig~70 -achtzig~80 -neunzig~90 -zwei millionen drei~2000003 -ein tausend dreizehn~1013 -ein tausend eins~1001 -ein tausend ein hundert~1100 -ein tausend sechs und zwanzig~1026 -ein tausend ein hundert sechs und zwanzig~1126 -achtzehn millionen vier hundert fünfzig tausend neun hundert neunzig~18450990 -achtzehn millionen neun hundert vierzig tausend sieben hundert zwei und zwanzig~18940722 -achtzehn millionen sechs hundert neunzig tausend neun hundert sechzehn~18690916 -achtzehn millionen sechshundertneunzigtausendneunhundertsechzehn~18690916 -achtzehn tausend acht hundert achtzig~18880 diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_date.txt deleted file mode 100644 index e994b936d850..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,22 +0,0 @@ -vierundzwanzigster juli zwei tausend dreizehn~24. Jul. 2013 -vier und zwanzigster juli zwei tausend dreizehn~24. Jul. 2013 -neunzehn achtzig~1980 -neunzehnachtzig~1980 -neunzehnhundertachtzig~1980 -neunzehn hundert achtzig~1980 -neunzehn achtziger~19 achtziger -zwei tausend zwanzig~2020 -zwanzig zwanzig~2020 -zwei tausend neun~2009 -vierzehnter januar~14. Jan. -januarzweitausendneun~januarzweitausendneun -januar zweitausendneun~Jan. 2009 -erster januar~1. Jan. -dreißigster juni~30. Jun. -neunzehn siebzehn~1917 -neunzehn hundert siebzehn~1917 -neunzehn hundert vierundneunzig~1994 -neunzehn hundert vier und neunzig~1994 -neunzehn vierundneunzig~1994 -zwei tausend drei~2003 -ein tausend acht~1008 diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 9db4974a3007..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,10 +0,0 @@ -null komma zwei millionen~0,2 millionen -eine million~1 million -eins komma zwei millionen~1,2 millionen -achtzehn milliarden~18 milliarden -vier hundert sechzig millionen~460 millionen -ein hundert zwanzig millionen~120 millionen -zehn millionen~10 millionen -minus sechzig komma zwei vier null null~-60,2400 -acht hundert achtzehn komma drei null drei~818,303 -achthundertachtzehn komma drei null drei~818,303 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_electronic.txt deleted file mode 100644 index fc9b0fc6666b..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,9 +0,0 @@ -c d f at a b c punkt e d u~cdf@abc.edu -a b c at g mail punkt a b c~abc@gmail.abc -a b c at a b c punkt com~abc@abc.com -a s d f eins zwei drei at a b c punkt com~asdf123@abc.com -a eins b zwei at a b c punkt com~a1b2@abc.com -a b drei bindestrich s d d bindestrich drei at g mail punkt com~ab3-sdd-3@gmail.com -h t t p s doppelpunkt slash slash w w w punkt a b c punkt com~https://www.abc.com -w w w punkt a b c punkt com~www.abc.com -h t t p s doppelpunkt slash slash w w w punkt a b c punkt com slash a b fragezeichen gleichheitszeichen drei bindestrich slash a b s slash eins~https://www.abc.com/ab?=3-/abs/1 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_fraction.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_fraction.txt deleted file mode 100644 index 5802cd481248..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_fraction.txt +++ /dev/null @@ -1,34 +0,0 @@ -null nulltel~0/0 -ein halb~1/2 -vier halbe~4/2 -ein drittel~1/3 -ein viertel~1/4 -ein fünftel~1/5 -ein sechstel~1/6 -ein siebtel~1/7 -ein achtel~1/8 -zwei neuntel~2/9 -ein ein halb~1 1/2 -ein sechstel~1/6 -ein zehntel~1/10 -ein elftel~1/11 -ein zehntel~1/10 -ein zwölftel~1/12 -ein dreizehntel~1/13 -ein vierzehntel~1/14 -ein fünfzehntel~1/15 -ein sechzehntel~1/16 -ein siebzehntel~1/17 -ein achtzehntel~1/18 -ein neunzehntel~1/19 -ein zwanzigstel~1/20 -ein dreißigstel~1/30 -ein vierzigstel~1/40 -ein fünfzigstel~1/50 -ein sechzigstel~1/60 -ein siebzigstel~1/70 -ein achtzigstel~1/80 -ein neunzigstel~1/90 -ein ein hundertstel~1/100 -ein zwei und zwanzigstel~1/22 -minus ein zwei und zwanzigstel~-1/22 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_measure.txt deleted file mode 100644 index f454760917e4..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,28 +0,0 @@ -zwei hundert meter~200 m -sechs und fünfzig komma drei pro quadrat kilometer~56,3 /km² -zwei hundert kilometer pro stunde~200 km/h -zwei und vierzig tausend zwei hundert neun und fünfzig pro quadrat meter~42259 /m² -minus sechs und sechzig kilogramm~-66 kg -minus sechsundsechzig kilogramm~-66 kg -zwei kilowattstunden~2 kwh -eins komma null null null null zwei acht kubik zentimeter~1,000028 cm³ -eins komma eins zentimeter~1,1 cm -drei stunden~3 h -eine stunde~1 h -ein millivolt~1 mv -eine million millivolt~1 million mv -zwei kubik meter~2 m³ -neunzig gramm~90 g -neunzig millionen gramm~90 millionen g -neunzig komma vier millionen gramm~90,4 millionen g -vier hundert vierzig milliliter~440 ml -drei hundert mikrometer~300 μm -fünf und sechzig tausend quadrat kilometer~65000 km² -zwei kilometer pro stunde~2 km/h -zwei millionen kilometer pro stunde~2 millionen km/h -zwei komma zwei millionen kilometer pro stunde~2,2 millionen km/h -sechzig komma zwei vier null null kilogramm~60,2400 kg -null fuß~0 ft -ein halb fuß~1/2 ft -ein ein halb fuß~1 1/2 ft -minus ein ein halb fuß~-1 1/2 ft \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_money.txt deleted file mode 100644 index 6e236d81792a..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,23 +0,0 @@ -zwei dollar~$2 -ein dollar~$1 -eine million dollar~$1 million -zwei komma null null null eins dollar~$2,0001 -zwei komma null eins dollar~$2,01 -zwei komma null null dollar~$2,00 -ein cent~€0,01 -zwei cent~€0,02 -zwanzig cent~€0,20 -zweiundzwanzig cent~€0,22 -einhundert cent~100 cent -zwei dollar zwanzig~$2,20 -zweidollarzwanzig~zweidollarzwanzig -zwei dollar und zwanzig cent~$2,20 -zwei euro und zwanzig cent~€2,20 -zwei pfund und zwanzig pence~£2,20 -zwei euro zwanzig cent~€2,20 -zwei millionen euro~€2 millionen -zwei komma zwei null null millionen euro~€2,200 millionen -zwei komma zwei null eins millionen euro~€2,201 millionen -zwei komma zwei eins millionen euro~€2,21 millionen -zwei pfund und ein penny~£2,01 -zwei pfund und ein hundert penny~£2 und 100 penny \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index c85bb289de15..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,20 +0,0 @@ -ein hundertste~100. -fünf und zwanzig tausend ein hundert elftem~25111. -fünfundzwanzigtausendeinhundertelftem~25111. -zweite~zweite -nullte~nullte -erster~erster -zweiter~zweiter -dritter~dritter -vierter~vierter -zehnter~10. -elftem~11. -dreizehntem~13. -ein und zwanzigstes~21. -drei und zwanzigstes~23. -dreiundzwanzigstes~23. -ein hundert elftes~111. -ein tausendstem~1000. -dem ein tausendstem~dem 1000. -ein hundert ein und zwanzigste~121. -einhunderteinundzwanzigste~121. diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_telephone.txt deleted file mode 100644 index 204d3e487d39..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1 +0,0 @@ -null vier eins eins eins zwei drei vier eins zwei drei vier~(0411) 1234-1234 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_time.txt deleted file mode 100644 index 0eb0bdbfee8b..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,24 +0,0 @@ -acht uhr~8 Uhr -vier und zwanzig uhr~24 Uhr -vierundzwanziguhr~24 Uhr -vierundzwanzig uhr~24 Uhr -vierundzwanziguhrzweiundzwanzigest~24:22 Uhr est -vierundzwanziguhrzweiundzwanzig e s t~24:22 Uhr est -zwölf uhr mittags~12 Uhr mittags -achtzehn uhr~18 Uhr -acht uhr sieben~08:07 Uhr -null uhr siebzehn~00:17 Uhr -halb zwölf~11:30 Uhr -viertel vor zwölf~11:45 Uhr -drei vor zwölf~11:57 Uhr -zwei und zwanzig vor zwölf~11:38 Uhr -zweiundzwanzig vor zwölf~11:38 Uhr -drei nach zwölf~12:03 Uhr -viertel nach zwölf~12:15 Uhr -zehn nach zwölf~12:10 Uhr -zehn vor zwölf~11:50 Uhr -viertel nach zwölf nachts~12:15 Uhr nachts -null uhr null minuten null sekunden~00:00:00 Uhr -ein uhr eine minute eine sekunde e s t~01:01:01 Uhr est -zwei uhr zwei minuten drei und zwanzig sekunden~02:02:23 Uhr -zwei uhr zwei minuten dreiundzwanzig sekunden~02:02:23 Uhr \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 4f3767f623c5..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,6 +0,0 @@ -doktor dao~Dr. dao -miss smith~Ms. smith -misses smith~Mrs. smith -mister dao~Mr. dao -ich mag essen zum beispiel eis~ich mag essen z.B. eis -Chanel nummer fünf~Chanel Nr. fünf diff --git a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_word.txt deleted file mode 100644 index 98ddaf3df23a..000000000000 --- a/tests/nemo_text_processing/de/data_inverse_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,49 +0,0 @@ -~ -yahoo!~yahoo! -zwanzig!~20 ! -x ~x -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index a2d211f4c86d..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,50 +0,0 @@ -null~0 -eins~1 -zwei~2 -drei~3 -vier~4 -sechs~6 -zehn~10 -elf~11 -zwölf~12 -dreizehn~13 -vierzehn~14 -fünfzehn~15 -sechzehn~16 -siebzehn~17 -achtzehn~18 -zwanzig~20 -dreißig~30 -vierzig~40 -fünfzig~50 -sechzig~60 -siebzig~70 -achtzig~80 -neunzig~90 -drei und zwanzig~23 -ein hundert~100 -ein hundert drei und zwanzig~123 -ein hundert eins~101 -ein tausend~1000 -ein hundert tausend~100000 -eine million~1000000 -zehn millionen~10000000 -ein hundert millionen~100000000 -neun billionen sieben hundert neun und achtzig milliarden drei hundert zwei und achtzig millionen fünf hundert sechs und dreißig tausend ein hundert dreißig~9789382536130 -ein hundert sieben und vierzig tausend vier hundert ein und fünfzig~147451 -eine million ein hundert sechs und fünfzig tausend ein hundert drei und siebzig~1156173 -eine milliarde fünf hundert drei und neunzig millionen zwei und siebzig tausend neun hundert ein und sechzig~1593072961 -sieben und neunzig billiarden acht hundert acht billionen zwei hundert vier und sechzig milliarden sieben hundert zwei und siebzig millionen sieben hundert zwei und neunzig tausend fünf~97808264772792005 -zehn billiarden zehn billionen zehn millionen ein hundert tausend zehn~10010000010100010 -minus fünf und zwanzig tausend sieben und dreißig~-25037 -minus fünf und zwanzig tausend sieben und dreißig~-25037 -eine billiarde zwei hundert vier und sechzig billionen drei hundert eins milliarden~1264301000000000 -minus sechzig~-60 -sechs und vierzig tausend sechs hundert vier und sechzig~46664 -zwei millionen drei~2000003 -ein tausend sechs und zwanzig~1026 -ein tausend ein hundert sechs und zwanzig~1126 -achtzehn millionen vier hundert fünfzig tausend neun hundert neunzig~18450990 -achtzehn millionen neun hundert vierzig tausend sieben hundert zwei und zwanzig~18940722 -achtzehn millionen sechs hundert neunzig tausend neun hundert sechzehn~18690916 -achtzehn tausend acht hundert achtzig~18880 diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_date.txt deleted file mode 100644 index 7de5cb7d782c..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,16 +0,0 @@ -vier und zwanzigster juli zwei tausend dreizehn~24. juli 2013 -vierzehnter januar~14. januar -erster januar~1. januar -dreißigster juni~30. juni -zweiter märz zwei tausend drei~02.03.2003 -zweiter märz zwei tausend drei~02.03.2003 -zweiter märz zwei tausend drei~2.3.2003 -zweiter märz~2.3 -zweiter märz~02.03 -zweiter märz zwei tausend drei~2. März 2003 -zweiter märz zwei tausend drei~2. Mär. 2003 -zweiter märz zwei tausend drei~2. mär. 2003 -zweiter märz zwei tausend drei~2. März 2003 -zweiter märz zwei tausend drei~2003-03-02 -märz zwei tausend drei~2003-03 -zweiter märz zwei tausend drei~2003-3-2 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 551114d8ee85..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,7 +0,0 @@ -null komma zwei millionen~0,2 millionen -achtzehn milliarden~18 milliarden -vier hundert sechzig millionen~460 millionen -ein hundert zwanzig millionen~120 millionen -zehn millionen~10 millionen -minus sechzig komma zwei vier null null~-60,2400 -acht hundert achtzehn komma drei null drei~818,303 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_electronic.txt deleted file mode 100644 index fc9b0fc6666b..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,9 +0,0 @@ -c d f at a b c punkt e d u~cdf@abc.edu -a b c at g mail punkt a b c~abc@gmail.abc -a b c at a b c punkt com~abc@abc.com -a s d f eins zwei drei at a b c punkt com~asdf123@abc.com -a eins b zwei at a b c punkt com~a1b2@abc.com -a b drei bindestrich s d d bindestrich drei at g mail punkt com~ab3-sdd-3@gmail.com -h t t p s doppelpunkt slash slash w w w punkt a b c punkt com~https://www.abc.com -w w w punkt a b c punkt com~www.abc.com -h t t p s doppelpunkt slash slash w w w punkt a b c punkt com slash a b fragezeichen gleichheitszeichen drei bindestrich slash a b s slash eins~https://www.abc.com/ab?=3-/abs/1 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_fraction.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_fraction.txt deleted file mode 100644 index 5802cd481248..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_fraction.txt +++ /dev/null @@ -1,34 +0,0 @@ -null nulltel~0/0 -ein halb~1/2 -vier halbe~4/2 -ein drittel~1/3 -ein viertel~1/4 -ein fünftel~1/5 -ein sechstel~1/6 -ein siebtel~1/7 -ein achtel~1/8 -zwei neuntel~2/9 -ein ein halb~1 1/2 -ein sechstel~1/6 -ein zehntel~1/10 -ein elftel~1/11 -ein zehntel~1/10 -ein zwölftel~1/12 -ein dreizehntel~1/13 -ein vierzehntel~1/14 -ein fünfzehntel~1/15 -ein sechzehntel~1/16 -ein siebzehntel~1/17 -ein achtzehntel~1/18 -ein neunzehntel~1/19 -ein zwanzigstel~1/20 -ein dreißigstel~1/30 -ein vierzigstel~1/40 -ein fünfzigstel~1/50 -ein sechzigstel~1/60 -ein siebzigstel~1/70 -ein achtzigstel~1/80 -ein neunzigstel~1/90 -ein ein hundertstel~1/100 -ein zwei und zwanzigstel~1/22 -minus ein zwei und zwanzigstel~-1/22 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_measure.txt deleted file mode 100644 index faa5ca074789..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,29 +0,0 @@ -zwei hundert meter~200 m -sechs und fünfzig komma drei pro quadrat kilometer~56,3 /km² -zwei hundert kilometer pro stunde~200 km/h -zwei und vierzig tausend zwei hundert neun und fünfzig pro quadrat meter~42259 /m² -zwei und vierzig tausend zwei hundert neun und fünfzig pro quadrat meter~42259/m² -minus sechs und sechzig kilogramm~-66 kg -zwei kilowattstunden~2 kwh -eins komma null null null null zwei acht kubik zentimeter~1,000028 cm³ -eins komma eins zentimeter~1,1 cm -drei stunden~3 h -ein stunde~1 h -ein millivolt~1 mv -eins million millivolt~1 million mv -zwei kubik meter~2 m³ -neunzig gramm~90 g -neunzig millionen gramm~90 millionen g -neunzig komma vier millionen gramm~90,4 millionen g -vier hundert vierzig milliliter~440 ml -drei hundert mikrometer~300 μm -fünf und sechzig tausend quadrat kilometer~65000 km² -zwei kilometer pro stunde~2 km/h -zwei kilometer pro stunde~2km/h -zwei millionen kilometer pro stunde~2 millionen km/h -zwei komma zwei millionen kilometer pro stunde~2,2 millionen km/h -sechzig komma zwei vier null null kilogramm~60,2400 kg -null fuß~0 ft -ein halb fuß~1/2 ft -ein ein halb fuß~1 1/2 ft -minus ein ein halb fuß~-1 1/2 ft \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_money.txt deleted file mode 100644 index f487ff8d31bd..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,21 +0,0 @@ -zwei dollar~$2 -zwei dollar~$2,000 -zwei dollar~$2,0 -zwei dollar~$2,00 -zwei komma null null null eins dollar~$2,0001 -eins million euro~€1 million -ein cent~€0,01 -zwei cent~€0,02 -zwanzig cent~€0,20 -zwei dollar zwanzig cent~$2,20 -zwei dollar zwanzig cent~$2,20000 -zwei dollar zwanzig cent~$2,200 -zwei komma zwei null eins dollar~$2,2010 -zwei komma zwei null eins dollar~$2,201 -zwei euro zwanzig cent~€2,20 -zwei euro zwanzig cent~€2,200 -zwei komma zwei null null millionen euro~€2,200 millionen -zwei komma zwei null eins millionen euro~€2,201 millionen -zwei komma zwei eins millionen euro~€2,21 millionen -zwei pfund ein penny~£2,01 -zwei pfund zwanzig pence~£2,20 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_normalize_with_audio.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_normalize_with_audio.txt deleted file mode 100644 index 08c54738837a..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_normalize_with_audio.txt +++ /dev/null @@ -1,131 +0,0 @@ -~123 -ein hundert drei und zwanzig -ein hundert und drei und zwanzig -123 -~101 -ein hundert eins -ein hundert eine -ein hundert ein -ein hundert und eins -ein hundert und ein -101 -ein hundert und eine -~1001 -zehn hundert eins -ein tausend eine -eine tausend eins -zehn eins -1001 -ein tausend ein -ein tausend eins -eine tausend eine -eine tausend ein -~1101 -ein tausend ein hundert und eins -ein tausend ein hundert eine -ein tausend ein hundert und ein -eine tausend ein hundert und ein -elf hundert eins -eine tausend ein hundert eine -elf eins -eine tausend ein hundert und eine -ein tausend ein hundert und eine -eine tausend ein hundert und eins -ein tausend ein hundert ein -1101 -eine tausend ein hundert eins -eine tausend ein hundert ein -ein tausend ein hundert eins -~1000000 -eine million -1000000 -ein million -ein millionen -eine millionen -eins million -~t-0t25d12-f -t-0t25d12-f -~133-A -133-A -ein hundert drei und dreißig A -ein hundert und drei und dreißig A -~B2A23C -B2A23C -~25d08A -25d08A -~C24 -C24 -~1970-2010 -1970-2010 -~W26s -W26s -~5-3-Ws -5-3-Ws -~401-ks -401-ks -~The box was 25 x 7 m. -The box was 25 x 7 m. -~4567 -4567 -~$2,20 -zwei us dollar zwanzig -zwei dollar und zwanzig cent -zwei us dollar und zwanzig cent -zwei us dollar zwanzig cent -zwei dollar zwanzig -zwei dollar zwanzig cent -~25.] -25 . ] -25. ] -fünf und zwanzigster ] -~Francis I--test -Francis I--test -~librivox.com -librivox.com -l i b r i v o x punkt com -l i b r i v o x punkt c o m -~1,000,123 -1,000,123 -~1980 -neunzehn achtzig -ein tausend neun hundert achtzig -neunzehn hundert achtzig -eine tausend neun hundert achtzig -ein tausend neun hundert und achtzig -eine tausend neun hundert und achtzig -~02.03.2003 -zweiter dritter zwanzig drei -zweiter märz zwei tausend drei -zweiter dritter zwei tausend drei -zweiter märz zwanzig drei -~abc@gmail.abc -a b c at g mail punkt a b c -a b c at g m a i l punkt a b c -~1 1/2 -1 ein halb -eins ein halb -ein ein halb -ein und ein halb -eins 1/2 -~11:30 Uhr -halb zwölf -elf uhr dreißig -dreißig nach elf -~11:45 Uhr -fünfzehn vor zwölf -elf uhr fünf und vierzig -viertel vor zwölf -~11:57 Uhr -elf uhr sieben und fünfzig -drei vor zwölf -~12:03 Uhr -drei nach zwölf -zwölf uhr drei -~12:15 Uhr -fünfzehn nach zwölf -zwölf uhr fünfzehn -viertel nach zwölf -~24:15 Uhr -viertel nach zwölf -fünfzehn nach zwölf -vier und zwanzig uhr fünfzehn diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index 89bbbf1ec71f..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,19 +0,0 @@ -ein hundertster Geburtstag~100. Geburtstag -fünf und zwanzig tausend ein hundert elfter~25111. -zweiter~2. -nullter~0. -erster~1. -zweiter~2. -dritter~3. -vierter~4. -elfter~11. -dreizehnter~13. -ein und zwanzigster~21. -drei und zwanzigster~23. -ein hundert elfter~111. -ein tausendster~1000. -dem ein tausendstem~dem 1000. -ein hundert erster~101. -eine millionster~1000000. -ein hundert ein und zwanzigster~121. -ein hundert ein und zwanzigstem~121tem diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_telephone.txt deleted file mode 100644 index e7bb731bba44..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,4 +0,0 @@ -null vier eins eins eins zwei drei vier eins zwei drei vier~(0411) 1234-1234 -null vier eins eins null zwei drei vier eins zwei drei vier~(0411) 0234-1234 -plus neun und vierzig eins zwei drei vier eins zwei drei vier~+49 1234-1234 -plus neun und vierzig eins zwei drei vier eins zwei drei vier~+49 12341234 \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_time.txt deleted file mode 100644 index 2b5216d2051e..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,26 +0,0 @@ -acht uhr~08:00 Uhr -acht uhr~08:00 Uhr -null uhr~00:00 Uhr -null uhr fünfzehn~00:15 Uhr -acht uhr~08:00 Uhr -zwanzig uhr~20:00 Uhr -vier und zwanzig uhr~24:00 Uhr -vierzehn uhr~14:00 Uhr -zwölf uhr~12:00 Uhr -elf uhr dreißig~11:30 Uhr -achtzehn uhr~18:00 Uhr -acht uhr sieben~08:07 Uhr -null uhr siebzehn~00:17 Uhr -zwölf uhr~12:00 Uhr -elf uhr fünf und vierzig~11:45 Uhr -elf uhr sieben und fünfzig~11:57 Uhr -zwölf uhr drei~12:03 Uhr -zwölf uhr zehn~12:10 Uhr -elf uhr fünfzig~11:50 Uhr -drei und zwanzig uhr dreißig~23:30 Uhr -drei und zwanzig uhr fünfzehn~23:15 Uhr -vier und zwanzig uhr fünf und vierzig~24:45 Uhr -vier und zwanzig uhr fünfzehn~24:15 Uhr -null uhr null minuten null sekunden~00:00:00 Uhr -ein uhr eine minute eine sekunde e s t~01:01:01 Uhr est -zwei uhr zwei minuten drei und zwanzig sekunden~02:02:23 Uhr \ No newline at end of file diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index b2df1dd46148..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,6 +0,0 @@ -doktor dao~Dr. dao -miss smith~Ms. smith -misses smith~Mrs. smith -mister dao~Mr. dao -ich mag essen zum beispiel eis~ich mag essen z.B. eis -Chanel nummer fünf~Chanel Nr. 5 diff --git a/tests/nemo_text_processing/de/data_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/de/data_text_normalization/test_cases_word.txt deleted file mode 100644 index 014a93282e19..000000000000 --- a/tests/nemo_text_processing/de/data_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,49 +0,0 @@ -~ -yahoo!~yahoo! -zwanzig !~20! -x~ x -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/de/test_cardinal.py b/tests/nemo_text_processing/de/test_cardinal.py deleted file mode 100644 index 6aac6435244d..000000000000 --- a/tests/nemo_text_processing/de/test_cardinal.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestCardinal: - - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_date.py b/tests/nemo_text_processing/de/test_date.py deleted file mode 100644 index f01bd1a9be05..000000000000 --- a/tests/nemo_text_processing/de/test_date.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDate: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_decimal.py b/tests/nemo_text_processing/de/test_decimal.py deleted file mode 100644 index 0ff1b783ac86..000000000000 --- a/tests/nemo_text_processing/de/test_decimal.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDecimal: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_electronic.py b/tests/nemo_text_processing/de/test_electronic.py deleted file mode 100644 index bbd7c1bd82fc..000000000000 --- a/tests/nemo_text_processing/de/test_electronic.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestElectronic: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_fraction.py b/tests/nemo_text_processing/de/test_fraction.py deleted file mode 100644 index f2d886f723f2..000000000000 --- a/tests/nemo_text_processing/de/test_fraction.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestFraction: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_fraction.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_fraction.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_measure.py b/tests/nemo_text_processing/de/test_measure.py deleted file mode 100644 index a93deaa209b2..000000000000 --- a/tests/nemo_text_processing/de/test_measure.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMeasure: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_money.py b/tests/nemo_text_processing/de/test_money.py deleted file mode 100644 index 9160ba10bda0..000000000000 --- a/tests/nemo_text_processing/de/test_money.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMoney: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_normalization_with_audio.py b/tests/nemo_text_processing/de/test_normalization_with_audio.py deleted file mode 100644 index 032d0ebf555f..000000000000 --- a/tests/nemo_text_processing/de/test_normalization_with_audio.py +++ /dev/null @@ -1,52 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from nemo.utils import logging - -from ..utils import CACHE_DIR, get_test_cases_multiple - -try: - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestNormalizeWithAudio: - - normalizer_de = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(get_test_cases_multiple('de/data_text_normalization/test_cases_normalize_with_audio.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_de.normalize(test_input, n_tagged=1000, punct_post_process=False) - logging.info(expected) - logging.info("pred") - logging.info(pred) - assert len(set(pred).intersection(set(expected))) == len( - expected - ), f'missing: {set(expected).difference(set(pred))}' diff --git a/tests/nemo_text_processing/de/test_ordinal.py b/tests/nemo_text_processing/de/test_ordinal.py deleted file mode 100644 index 8a45b8853d48..000000000000 --- a/tests/nemo_text_processing/de/test_ordinal.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestOrdinal: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_sparrowhawk_inverse_text_normalization.sh b/tests/nemo_text_processing/de/test_sparrowhawk_inverse_text_normalization.sh deleted file mode 100644 index d7aba4c020c4..000000000000 --- a/tests/nemo_text_processing/de/test_sparrowhawk_inverse_text_normalization.sh +++ /dev/null @@ -1,84 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1 | sed 's/\xC2\xA0/ /g') - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$spoken" "$written" "$denorm_pred" - done < "$input" -} - -testITNCardinal() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testITNDate() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_date.txt - runtest $input -} - -testITNDecimal() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_decimal.txt - runtest $input -} - -testITNOrdinal() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testITNFraction() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_fraction.txt - runtest $input -} - -testITNTime() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_time.txt - runtest $input -} - -testITNMeasure() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_measure.txt - runtest $input -} - -testITNMoney() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_money.txt - runtest $input -} - -testITNWhitelist() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testITNTelephone() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_telephone.txt - runtest $input -} - -testITNElectronic() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_electronic.txt - runtest $input -} - -testITNWord() { - input=$PROJECT_DIR/de/data_inverse_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/de/test_sparrowhawk_normalization.sh b/tests/nemo_text_processing/de/test_sparrowhawk_normalization.sh deleted file mode 100644 index 3dfdfe9f3cba..000000000000 --- a/tests/nemo_text_processing/de/test_sparrowhawk_normalization.sh +++ /dev/null @@ -1,84 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1 | sed 's/\xC2\xA0/ /g') - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$written" "$spoken" "$denorm_pred" - done < "$input" -} - -testTNCardinal() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testTNDate() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_date.txt - runtest $input -} - -testTNDecimal() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_decimal.txt - runtest $input -} - -testTNOrdinal() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testTNFraction() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_fraction.txt - runtest $input -} - -testTNTime() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_time.txt - runtest $input -} - -testTNMeasure() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_measure.txt - runtest $input -} - -testTNMoney() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_money.txt - runtest $input -} - -testTNWhitelist() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testTNTelephone() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_telephone.txt - runtest $input -} - -testTNElectronic() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_electronic.txt - runtest $input -} - -testTNWord() { - input=$PROJECT_DIR/de/data_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/de/test_telephone.py b/tests/nemo_text_processing/de/test_telephone.py deleted file mode 100644 index d26dbeb8e989..000000000000 --- a/tests/nemo_text_processing/de/test_telephone.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTelephone: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_time.py b/tests/nemo_text_processing/de/test_time.py deleted file mode 100644 index b3fd8b1604a4..000000000000 --- a/tests/nemo_text_processing/de/test_time.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTime: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_whitelist.py b/tests/nemo_text_processing/de/test_whitelist.py deleted file mode 100644 index b340fb79d44b..000000000000 --- a/tests/nemo_text_processing/de/test_whitelist.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWhitelist: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/de/test_word.py b/tests/nemo_text_processing/de/test_word.py deleted file mode 100644 index 2c66d58a287e..000000000000 --- a/tests/nemo_text_processing/de/test_word.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWord: - inverse_normalizer = ( - InverseNormalizer(lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('de/data_inverse_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='de', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('de/data_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, expected, test_input): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=1000, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/__init__.py b/tests/nemo_text_processing/en/__init__.py deleted file mode 100644 index 9e3250071955..000000000000 --- a/tests/nemo_text_processing/en/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index d865e7eafa67..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,28 +0,0 @@ -nine trillion seven hundred eighty nine billion three hundred eighty two million five hundred thirty six thousand one hundred thirty~9789382536130 -two hundred and fifty four~254 -one hundred forty seven thousand four hundred fifty one~147451 -one million one hundred fifty six thousand one hundred seventy three~1156173 -one billion five hundred ninety three million seventy two thousand nine hundred sixty one~1593072961 -ninety seven quadrillion eight hundred eight trillion two hundred sixty four billion seven hundred seventy two million seven hundred ninety two thousand five~97808264772792005 -seventeen sextillion eight hundred fifty five quintillion thirty six quadrillion six hundred fifty seven trillion seven billion five hundred ninety six million one hundred ten thousand nine hundred forty nine~17855036657007596110949 -ten quadrillion ten trillion ten million one hundred thousand ten~10010000010100010 -minus twenty five thousand thirty seven~-25037 -one quadrillion two hundred sixty four trillion three hundred one billion nine hundred thirty eight million one hundred four~1264301938000104 -minus sixty~-60 -forty six thousand six hundred sixty four~46664 -sixty~60 -zero~zero -two million three~2000003 -one thousand thirteen~1013 -one thousand one~1001 -one thousand one hundred~1100 -one thousand twenty six~1026 -one thousand one hundred twenty six~1126 -eighteen million four hundred fifty thousand nine hundred ninety~18450990 -eighteen million nine hundred forty thousand seven hundred twenty two~18940722 -eighteen million six hundred ninety thousand nine hundred sixteen~18690916 -eighteen thousand eight hundred eighty~18880 -eleven hundred~1100 -twenty one hundred~2100 -twenty one hundred and eleven~2111 -eleven hundred twenty one~1121 diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_date.txt deleted file mode 100644 index 3ec42681447a..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,34 +0,0 @@ -july twenty fifth two thousand twelve~july 25 2012 -nineteen eighties~1980s -two thousand and twenty~2020 -two thousand and nine~2009 -the twenty fifth of july twenty twelve~25 july 2012 -the twenty fifth of july two thousand twelve~25 july 2012 -the twenty second of july twenty twelve~22 july 2012 -the fifteenth of january~15 january -the seventeenth of may twenty ten~17 may 2010 -january first~january 1 -july twenty second two thousand eight~july 22 2008 -june thirty~june 30 -july twenty fifth twenty twelve~july 25 2012 -nineteen seventeen~1917 -twenty twelve~2012 -march sixteen sixty five~march 1665 -sixteen sixty five~1665 -july two thousand twelve~july 2012 -october nineteen oh five~october 1905 -july fifteen o six~july 1506 -the twenty fifth of july twenty twelve~25 july 2012 -july twenty fifth twenty twelve~july 25 2012 -july twenty fifth two thousand twelve~july 25 2012 -july one thousand eight hundred seventy six~july 1876 -february twenty fifth twenty sixteen~february 25 2016 -november twenty fourth twenty fourteen~november 24 2014 -nineteen ninety four~1994 -two thousand three~2003 -one thousand eight~1008 -nineteen seventy six~1976 -june twentieth twenty fourteen~june 20 2014 -nineteen seventy three~1973 -nineteen seventy five~1975 -eleven fifty five~1155 \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 2cd2272837ef..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,63 +0,0 @@ -five point two million~5.2 million -one hundred sixty four point five eight thousand~164.58 thousand -four hundred million~400 million -fifty billion~50 billion -four hundred five billion~405 billion -four point eight five billion~4.85 billion -one hundred billion~100 billion -one hundred ten billion~110 billion -one hundred thirty two billion~132 billion -one point eight four billion~1.84 billion -one point eight one billion~1.81 billion -one point five nine billion~1.59 billion -one point four five three billion~1.453 billion -one point seven two billion~1.72 billion -one point two five billion~1.25 billion -thirteen billion~13 billion -thirty billion~30 billion -two thousand eight hundred five point eight seven three billion~2805.873 billion -seventy trillion~70 trillion -thirteen million~13 million -eighteen billion~18 billion -four hundred fifty million~450 million -one hundred thirty million~130 million -ten million~10 million -four hundred million~400 million -five million~5 million -five hundred million~500 million -twelve million~12 million -thirteen million~13 million -four million~4 million -forty five million~45 million -fifteen million~15 million -fifteen trillion~15 trillion -fifteen billion~15 billion -two million~2 million -eight million~8 million -point one two o five~.1205 -minus sixty point two four zero zero~-60.2400 -zero point two six~0.26 -point zero two~.02 -sixty point two~60.2 -eighteen~18 -eighteen point eight five~18.85 -eighteen point five o~18.50 -eighteen point five six~18.56 -eighteen point nine~18.9 -eighteen point o five~18.05 -eighteen point one two~18.12 -eighteen point o one~18.01 -eighteen point o o o~18.000 -eighteen point six~18.6 -eighteen point three o o~18.300 -eighteen point three six~18.36 -eighteen point two five~18.25 -eighteen point two two~18.22 -eight hundred eighteen point three o three~818.303 -eight hundred eight point eight~808.8 -eight hundred eight point zero~808.0 -eight hundred eighty eight point one~888.1 -eight hundred eighty four point three~884.3 -eight hundred eighty two point eight~882.8 -eight hundred eighty two point zero~882.0 -eight hundred forty five point nine four~845.94 \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_electronic.txt deleted file mode 100644 index 2efa54aea236..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,25 +0,0 @@ -a dot b c at g mail dot com~a.bc@gmail.com -a at gmail dot com~a@gmail.com -a at m s n dot fr~a@msn.fr -a at a o l dot com~a@aol.com -a at m s n dot com~a@msn.com -a at nvidia dot com~a@nvidia.com -a dot b c at nvidia dot com~a.bc@nvidia.com -c d f at a b c dot e d u~cdf@abc.edu -a b c at g mail dot a b c~abc@gmail.abc -a b c at a b c dot com~abc@abc.com -a s d f one two three at a b c dot com~asdf123@abc.com -a one b two at a b c dot com~a1b2@abc.com -a b three dot s d d dot three at g mail dot com~ab3.sdd.3@gmail.com -dot three at g mail dot com~dot 3@gmail.com -one three at g mail dot com~13@gmail.com -a b three hyphen s d d dash three at g mail dot com~ab3-sdd-3@gmail.com -h t t p colon slash slash w w w dot o u r d a i l y n e w s dot com dot s m~http://www.ourdailynews.com.sm -h t t p colon slash slash w w w dot c o m d a i l y n e w s dot a b dot s m~http://www.comdailynews.ab.sm -h t t p colon slash slash w w w dot c o m d a i l y n e w s dot a b slash s m~http://www.comdailynews.ab/sm -w w w dot c o m d a i l y n e w s dot a b slash s m~www.comdailynews.ab/sm -c o m d a i l y n e w s dot a b slash s m~comdailynews.ab/sm -n vidia dot com~nvidia.com -abc at gmail dot com~abc@gmail.com -athreed at gmail dot com~athreed@gmail.com -kore dot ai~kore.ai diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_measure.txt deleted file mode 100644 index 4f6f540e6da4..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,112 +0,0 @@ -two hundred meters~200 m -fifty six point three per square kilometer~56.3 /km² -two hundred kilometers per hour~200 km/h -twenty eight kilograms force per square centimeter~28 kgf/cm² -forty two thousand two hundred fifty nine per square meter~42259 /m² -minus two thousand twelve kilo liters~-2012 kl -minus sixty six kilograms~-66 kg -two kilo watt hours~2 kwh -one point o o o o two eight cubic deci meters~1.000028 dm³ -seven point five peta bytes~7.5 pb -three hours~3 h -one milli volt~1 mv -two cubic meters~2 m³ -ninety grams~90 g -one hundred twenty four point three lumens~124.3 lm -four hundred forty milliliters~440 ml -thirty one thousand four hundred eighty square feet~31480 sq ft -one thousand six hundred hours~1600 h -thirty one thousand four hundred eighty square feet~31480 sq ft -two square miles~2 sq mi -zero point one nine square miles~0.19 sq mi -one thousand five hundred thirty one c c~1531 cc -three hundred micrometers~300 μm -sixty five thousand square kilometers~65000 km² -two miles per hour~2 mph -two hundred forty five miles per hour~245 mph -one hundred fifty c c~150 cc -sixty point two four zero zero kilograms~60.2400 kg -zero feet~0 ft -zero foot~zero foot -two feet~2 ft -twenty foot~20 foot -point two meters~.2 m -two square meters~2 m² -eighteen feet~18 ft -eighteen mega siemens~18 ms -eighteen ounces~18 oz -eighteen point five kilometers~18.5 km -eighteen point five two square kilometers~18.52 km² -eighteen point nine one square kilometers~18.91 km² -eighteen point one four percent~18.14 % -eighteen point one six percent~18.16 % -eighteen point one square kilometers~18.1 km² -eighteen point six percent~18.6 % -eighteen point two two kilometers~18.22 km -eighteen point zero kilometers~18.0 km -eighteen point zero percent~18.0 % -eighteen square kilometers~18 km² -eighteen thousand eight hundred giga watt hours~18800 gwh -eighteen thousand seven hundred hectares~18700 ha -eight hectares~8 ha -eight hundred eighty five astronomical units~885 au -eight hundred eighty hectares~880 ha -eight hundred eighty kilobytes~880 kb -eight hundred eighty kilometers~880 km -eight hundred eighty nine feet~889 ft -eight hundred eighty six kilometers~886 km -eight hundred eighty two megawatts~882 mw -eight hundred feet~800 ft -eight hundred fifty five square kilometers~855 km² -eight hundred fifty megahertz~850 mhz -eight hundred fifty meters~850 m -eight hundred fifty nanometers~850 nm -eight hundred fifty one meters~851 m -eight hundred fifty seven square kilometers~857 km² -eight hundred fifty three meters~853 m -eight hundred fifty three point six meters~853.6 m -eight hundred five point four six square kilometers~805.46 km² -eight hundred forty two point nine meters~842.9 m -eight hundred forty two square kilometers~842 km² -eight hundred gigabytes~800 gb -eight hundred horsepower~800 hp -eight hundred kilograms~800 kg -eight hundred kilo watt hours~800 kwh -eight hundred kilowatts~800 kw -eight hundred megahertz~800 mhz -eight hundred ninety four c c~894 cc -eight hundred ninety kilowatts~890 kw -eight hundred ninety millimeters~890 mm -eight hundred ninety two square kilometers~892 km² -eight hundred seventy horsepower~870 hp -eight hundred seventy meters~870 m -eight hundred sixty kilograms~860 kg -eight hundred sixty kilometers~860 km -eight hundred sixty miles~860 mi -eight hundred sixty six feet~866 ft -eight hundred ten hectares~810 ha -eight hundred ten kilohertz~810 khz -eight hundred thirty eight point two millimeters~838.2 mm -eight hundred thirty five kilometers~835 km -eight hundred thirty kilohertz~830 khz -eight hundred thirty megawatts~830 mw -eight hundred thirty nine kilometers~839 km -eight hundred thirty six meters~836 m -eight hundred twenty feet~820 ft -eight hundred twenty kilometers~820 km -eight hundred twenty meters~820 m -eight hundred twenty one point zero feet~821.0 ft -eight hundred two point eight nine kilometers~802.89 km -eight hundred volts~800 v -eight kilobits~8 kb -eight kilograms~8 kg -eight million two hundred thousand feet~8200000 ft -eight point eight kilometers~8.8 km -eight point eight meters~8.8 m -eight point eight miles~8.8 mi -eight point five centimeters~8.5 cm -eight point five five percent~8.55 % -eight point five megawatts~8.5 mw -eight point five meters~8.5 m -eight point five two percent~8.52 % -eight point four four percent~8.44 % diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_money.txt deleted file mode 100644 index 3fbb895f96ec..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,52 +0,0 @@ -two dollars~$2 -one cent~$0.01 -four united states dollars and sixty nine cents~$4.69 -seventy five dollars sixty three~$75.63 -twenty nine dollars fifty cents~$29.50 -eleven dollars and fifty one cents~$11.51 -nine hundred ninety three dollars and ninety two cents~$993.92 -four hundred sixty billion won~₩460 billion -thirty billion yen~¥30 billion -two point five billion dollars~$2.5 billion -forty five billion dollars~$45 billion -fifty million dollars~$50 million -fifty billion dollars~$50 billion -zero point two million dollars~$0.2 million -fifteen point two billion dollars~$15.2 billion -one point six nine billion yuan~1.69 billion yuan -one point four three six billion yuan~1.436 billion yuan -four million yuan~4 million yuan -one dollar~$1 -fifteen thousand dollars~$15000 -one dollars~one dollars -twenty dollar~20 dollar -twenty point five o six dollars~$20.506 -point five o six dollars~$.506 -eighteen dollars~$18 -eighteen million nine hundred twenty five thousand dollars~$18925000 -eighteen thousand eight hundred fifty four dollars~$18854 -eighteen thousand eight hundred one dollars~$18801 -eighteen thousand eight hundred seventy five dollars~$18875 -eighteen thousand eighty one dollars~$18081 -eighteen thousand fifty two dollars~$18052 -eighteen thousand five hundred forty two dollars~$18542 -eighteen thousand five hundred nineteen dollars~$18519 -eighteen thousand five hundred seventy dollars~$18570 -eighteen thousand five hundred seventy eight dollars~$18578 -eighteen thousand five hundred sixteen dollars~$18516 -eighteen thousand four hundred eighty two dollars~$18482 -eighteen thousand four hundred seventy eight dollars~$18478 -eighteen thousand four hundred sixty eight dollars~$18468 -eighteen thousand nine hundred three dollars~$18903 -eighteen thousand nine hundred twenty nine dollars~$18929 -eighteen thousand ninety five dollars~$18095 -eighteen thousand one hundred seventeen dollars~$18117 -eighteen thousand one hundred twenty eight dollars~$18128 -eighteen thousand one hundred twenty five dollars~$18125 -eighteen thousand one hundred twenty four dollars~$18124 -eighteen thousand one hundred twenty nine dollars~$18129 -one thousand fifty five dollars~$1055 -one fifty five dollars~$155 -fifteen hundred dollars~$1500 -ninety nine hundred dollars~$9900 -ninety nine hundred and fifteen dollars and one cent~$9915.01 diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index f701a68bb798..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,34 +0,0 @@ -one hundredth~100th -twenty five thousand one hundred eleventh~25111th -second~2nd -zeroth~0th -first~1st -second~2nd -third~3rd -fourth~4th -eleventh~11th -twelfth~12th -thirteenth~13th -twenty first~21st -twenty third~23rd -one hundred eleventh~111th -one thousandth~1000th -one hundred twenty first~121st -eleven hundred twenty first~1121st -second~2nd -tenth~10th -sixth~6th -third~3rd -nineteenth~19th -third~3rd -twelfth~12th -forty eighth~48th -seventy first~71st -third~3rd -forty second~42nd -seventeenth~17th -twentieth~20th -twenty first~21st -seventh~7th -second~2nd -fifth~5th \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_telephone.txt deleted file mode 100644 index 92e2d6c3cacf..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,18 +0,0 @@ -one two three one two three five six seven eight~123-123-5678 -plus nine one one two three one two three five six seven eight~+91 123-123-5678 -plus forty four one two three one two three five six seven eight~+44 123-123-5678 -four one two three one two three five six seven eight~4 123-123-5678 -zero two three one two three five six seven eight~023-123-5678 -o two three one two three five six seven eight~023-123-5678 -oh two three one two three five six seven eight~023-123-5678 -double oh three one two three five six seven eight~003-123-5678 -four three two double seven three two one four three two one four three double zero five~four 3277 3214 3214 3005 -one two three dot one two three dot o dot four o~123.123.0.40 -one twenty three dot one two three dot o dot four o~123.123.0.40 -two two five dot double five dot o dot four o~225.55.0.40 -two two five dot double five dot o dot forty five~225.55.0.45 -ssn is seven double nine one two three double one three~ssn is 799-12-3113 -seven nine nine~799 -a b nine~ab9 -a b c~a b c -five w k r a three one~5wkra31 diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_time.txt deleted file mode 100644 index 18f8d789b660..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,29 +0,0 @@ -eight oclock g m t~08:00 gmt -seven a m e s t~07:00 a.m. est -two p m~02:00 p.m. -two thirty~02:30 -three o'clock~03:00 -quarter past one~01:15 -half past three~03:30 -eight fifty one~08:51 -eight fifty two~08:52 -eight forty~08:40 -eight nineteen~08:19 -eight o six~08:06 -eight thirty eight~08:38 -eight thirty two~08:32 -eight twenty nine~08:29 -eleven fifty five p m~11:55 p.m. -eleven fifty three p m~11:53 p.m. -eleven forty a m~11:40 a.m. -eleven forty five a m~11:45 a.m. -eleven forty p m~11:40 p.m. -eleven forty six a m~11:46 a.m. -eleven o six p m~11:06 p.m. -eleven thirteen a m~11:13 a.m. -half past twelve~12:30 -quarter past one~01:15 -quarter to one~12:45 -quarter to twelve~11:45 -set alarm at ten to eleven pm~set alarm at 10:50 p.m. -one min to one am~12:59 a.m. diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index d8fa65ad33aa..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,7 +0,0 @@ -doctor dao~dr. dao -misses smith~mrs. smith -mister dao~mr. dao -saint george~st. george -i like for example ice cream~i like e.g. ice cream -s and p five hundred~s&p 500 -seven eleven stores~7-eleven stores diff --git a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_word.txt deleted file mode 100644 index c21423e68ae9..000000000000 --- a/tests/nemo_text_processing/en/data_inverse_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,52 +0,0 @@ -~ -, one~, one -, one , two , three , four~, one , two , three , four -e s three~es3 -yahoo!~yahoo! -twenty!~20 ! -x ~x -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_address.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_address.txt deleted file mode 100644 index bd9394163d4d..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_address.txt +++ /dev/null @@ -1,9 +0,0 @@ -2788 San Tomas Expy, Santa Clara, CA 95051~twenty seven eighty eight San Tomas Expressway, Santa Clara, California nine five zero five one -2 San Tomas hwy, Santa, FL, 95051~two San Tomas Highway, Santa, Florida, nine five zero five one -123 Smth St, City, NY~one twenty three Smth Street, City, New York -123 Laguna Ct, Town~one twenty three Laguna Court, Town -1211 E Arques Ave~twelve eleven East Arques Avenue -708 N 1st St, San City~seven zero eight North first Street, San City -12 S 1st st~twelve South first Street -1990 for the Ata ST~nineteen ninety for the Ata ST -Main St.~Main St. diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index ea8af1b6a806..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,17 +0,0 @@ -1~one -2~two --2~minus two -3~three -123~one hundred and twenty three -13,000~thirteen thousand -13000~one three zero zero zero -9000~nine thousand -9,000~nine thousand -123,000~one hundred twenty three thousand -123000~one two three zero zero zero -123,123,000~one hundred twenty three million one hundred twenty three thousand -123,000,012~one hundred twenty three million twelve -1,000,000~one million -1234567890123124~one two three four five six seven eight nine zero one two three one two four -978-0~nine hundred and seventy eight - zero -004~zero zero four diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_date.txt deleted file mode 100644 index 8b97fce4a5f2..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,53 +0,0 @@ -july 25 2012~july twenty fifth twenty twelve -jul 25 2012~july twenty fifth twenty twelve -1980s~nineteen eighties -1980 s~nineteen eighties -25 july 2012~the twenty fifth of july twenty twelve -25 jul 2012~the twenty fifth of july twenty twelve -22 july 2012~the twenty second of july twenty twelve -25th july 2012~the twenty fifth of july twenty twelve -25th jul 2012~the twenty fifth of july twenty twelve -22nd july 2012~the twenty second of july twenty twelve -15 january~the fifteenth of january -17 may 2010~the seventeenth of may twenty ten -january 1~january first -june 30~june thirtieth -2012~twenty twelve -july 1506~july fifteen oh six -july 1876~july eighteen seventy six -1994~nineteen ninety four -1976~nineteen seventy six -june 20 2014~june twentieth twenty fourteen -1973~nineteen seventy three -1975~nineteen seventy five -1155~eleven fifty five -2006-08-05~august fifth two thousand six -august 23 2002~august twenty third two thousand two -16 July 1943~the sixteenth of july nineteen forty three -20 january~the twentieth of january -2016-11-03~november third twenty sixteen -2016/07/03~july third twenty sixteen -1980s~nineteen eighties -01.10.2010~january tenth twenty ten -10/06/2005~october sixth two thousand five -1910s~nineteen tens -2000s~two thousands -25 sept.~the twenty fifth of september -1000~one thousand -SEPT. 15~september fifteenth -JAN. 15 2020~january fifteenth twenty twenty -Jan. 15 2020~january fifteenth twenty twenty -Jan 15 2020~january fifteenth twenty twenty -jan. 15~january fifteenth -JAN 15 2020~january fifteenth twenty twenty -SEPTEMBER 15 twenty twenty~september fifteenth twenty twenty -11/17/05~november seventeenth zero five -01/07/98~january seventh ninety eight -One should go to the store on the 26th May in the evening~One should go to the store on the twenty sixth of may in the evening -'80s~eighties -Jan-15-2020~january fifteenth twenty twenty -Jan-15~january fifteenth -15-01-2020~the fifteenth of january twenty twenty -15.01.2020~the fifteenth of january twenty twenty -340 A.D~three forty AD -1998/2/30~february thirtieth nineteen ninety eight \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 9fa615018985..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,12 +0,0 @@ -.1665~point one six six five -2.0~two point zero -2.00~two point zero zero -2.050~two point zero five zero -100 million~one hundred million -0.1 billion~zero point one billion -.1 trillion~point one trillion --0.1~minus zero point one -0.004~zero point zero zero four -0.1 M~zero point one M -0.1 B~zero point one B -0.1 K~zero point one K diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_electronic.txt deleted file mode 100644 index 61d94180dccf..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,29 +0,0 @@ -a.bc@gmail.com~a dot bc at gmail dot com -a@hotmail.de~a at hotmail dot DE -a@hotmail.fr~a at hotmail dot FR -a@hotmail.it~a at hotmail dot IT -a@aol.it~a at aol dot IT -a@msn.it~a at msn dot IT -cdf@abc.edu~cdf at abc dot EDU -abc@gmail.abc~abc at gmail dot ABC -abc@abc.com~abc at abc dot com -asdf123@abc.com~asdf one two three at abc dot com -a1b2@abc.com~a one b two at abc dot com -ab3.sdd.3@gmail.com~ab three dot sdd dot three at gmail dot com -email is abc1@gmail.com~email is abc one at gmail dot com -abs@nvidia.com~abs at nvidia dot com -email is a-1.b3_c&-d@gma4i-l.com test~email is a dash one dot b three underscore c ampersand dash d at gma four i dash l dot com test -nvidia.com~nvidia dot com -test.com~test dot com -http://www.ourdailynews.com.sm~HTTP semicolon slash slash WWW dot ourdailynews dot com dot SM -https://www.ourdailynews.com.sm~HTTPS semicolon slash slash WWW dot ourdailynews dot com dot SM -www.ourdailynews.com.sm~WWW dot ourdailynews dot com dot SM -www.ourdailynews.com/123-sm~WWW dot ourdailynews dot com slash one two three dash SM -sdf@gmail.com.sm~sdf at gmail dot com dot SM -sdf@gmail.com/123-sm~sdf at gmail dot com slash one two three dash SM -sdf@gmail.abc/123-sm~sdf at gmail dot ABC slash one two three dash SM -ourdailynews.com/123-sm~ourdailynews dot com slash one two three dash SM -ourdailynews.abc~ourdailynews.abc -file:///c/code/NeMo/docs/build/html/processing/intro.html~file semicolon slash slash slash c slash code slash NeMo slash docs slash build slash html slash processing slash intro dot HTML -file:///photos/image.jpg~file semicolon slash slash slash photos slash image dot jpeg -electronic test.com and test2.uk~electronic test dot com and test two dot UK \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_fraction.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_fraction.txt deleted file mode 100644 index 3c2316cb3fc2..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_fraction.txt +++ /dev/null @@ -1,16 +0,0 @@ -1/2007~one two thousand seventh -12639/12640~twelve thousand six hundred thirty nine twelve thousand six hundred fortieths -3 2/4~three and two quarters -1/4~one quarter -1/4th~one quarter -2/4th~two quarters -1/4TH~one quarter -1/3RD~one third -31/32~thirty one thirty seconds -22/3~twenty two thirds -1/3~one third -2 142/1~two and one hundred forty two over one -1/2~one half -2 1/2~two and a half -3 5/2~three and five halves -1795 / 1805~one thousand seven hundred ninety five one thousand eight hundred fifths \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_math.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_math.txt deleted file mode 100644 index 4975d6fdab0d..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_math.txt +++ /dev/null @@ -1,4 +0,0 @@ -1-2=5~one minus two equals five -1- 2 = 5~one minus two equals five -y=x +1~y equals x plus one -x +1 = y~x plus one equals y diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_measure.txt deleted file mode 100644 index 4d16a18eda89..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,19 +0,0 @@ -12kg~twelve kilograms -12KG~twelve kilograms -12/kg~twelve per kilogram -12kg/kg~twelve kilograms per kilogram -1 mbps~one megabit per second -3 mbps~three megabits per second -3 cc/s~three CC per S -100 million kg~one hundred million kilograms -a 123.2-millimeters long~a one hundred and twenty three point two millimeters long -covid-19.5~covid- nineteen point five -7.2-millimeter bullet~seven point two millimeter bullet -4 1/2 lbs~four and a half pounds -4.4x~four point four x -80 s~eighty S -2°C~two degrees Celsius -1°C~one degree Celsius -1234-123kg~one thousand two hundred and thirty four to one hundred and twenty three kilograms -45º&C~forty five degree and C -41,459.00 km³~forty one thousand four hundred and fifty nine point zero zero cubic kilometers diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_money.txt deleted file mode 100644 index d1218e8bd758..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,65 +0,0 @@ -$2~two dollars -$2.00~two dollars -₩460 billion~four hundred sixty billion won -¥30 billion~thirty billion yen -¥30 b~thirty billion yen -¥30b~thirty billion yen -¥30B~thirty billion yen -$45 billion~forty five billion dollars -$0.2 million~zero point two million dollars -$2.5 million~two point five million dollars -$15.2 billion~fifteen point two billion dollars -1.436 billion yuan~one point four three six billion yuan -4 million yuan~four million yuan -$15000~fifteen thousand dollars -$1~one dollar -$1.00~one dollar -$1.00~one dollar -$2~two dollars -$2.00~two dollars -$2.000~two dollars -$20~twenty dollars -$20.506~twenty point five zero six dollars -$20.50~twenty dollars fifty cents -$20.500~twenty dollars fifty cents -$20.5~twenty dollars fifty cents -$20.01~twenty dollars one cent -$20.010~twenty dollars one cent -$0.010~one cent -$0.02~two cents -$0.20~twenty cents -$.01~one cent -$.506~point five zero six dollars -$18~eighteen dollars -$18925000~eighteen million nine hundred twenty five thousand dollars -$18,925,000~eighteen million nine hundred twenty five thousand dollars -$18854~eighteen thousand eight hundred and fifty four dollars -$18801~eighteen thousand eight hundred and one dollars -$18875~eighteen thousand eight hundred and seventy five dollars -$18081~eighteen thousand and eighty one dollars -$18052~eighteen thousand and fifty two dollars -$18542~eighteen thousand five hundred and forty two dollars -$18519~eighteen thousand five hundred and nineteen dollars -$18570~eighteen thousand five hundred and seventy dollars -$18578~eighteen thousand five hundred and seventy eight dollars -$18516~eighteen thousand five hundred and sixteen dollars -$18482~eighteen thousand four hundred and eighty two dollars -$18478~eighteen thousand four hundred and seventy eight dollars -$18468~eighteen thousand four hundred and sixty eight dollars -$18903~eighteen thousand nine hundred and three dollars -$18929~eighteen thousand nine hundred and twenty nine dollars -$18095~eighteen thousand and ninety five dollars -$18117~eighteen thousand one hundred and seventeen dollars -$18128~eighteen thousand one hundred and twenty eight dollars -$18125~eighteen thousand one hundred and twenty five dollars -$18124~eighteen thousand one hundred and twenty four dollars -$18129~eighteen thousand one hundred and twenty nine dollars -£18000~eighteen thousand pounds -£1.20~one pound twenty pence -£1.111~one point one one one pounds -£2.01~two pounds one penny -$50.00-$100.00~fifty dollars - one hundred dollars -$1,925.21~one thousand nine hundred and twenty five dollars twenty one cents -$1,234.123~one thousand two hundred and thirty four point one two three dollars -US $76.3 trillion~US seventy six point three trillion dollars -US$76.3 trillion~seventy six point three trillion us dollars diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_normalize_with_audio.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_normalize_with_audio.txt deleted file mode 100644 index e012cd3c3255..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_normalize_with_audio.txt +++ /dev/null @@ -1,165 +0,0 @@ -~123 -one two three -one twenty three -one hundred twenty three -one hundred and twenty three -~$123 -one hundred twenty three dollars -one hundred and twenty three dollars -~They bought 23 books for $123.02. -They bought twenty three books for one hundred twenty three dollars and two cents. -They bought twenty three books for one hundred twenty three dollars two cents. -~$1.01 -one dollar and one cent -one us dollar one cent -~1.24 -one point two four -one point twenty four -~~1/24 -january twenty four -the twenty fourth of january -january twenty fourth -~$1.21 -one dollar and twenty one cents -one dollar twenty one cents -~£1.00 -one pound -~t-0t25d12-f -t-oh t twenty five d one two-f -t-oh t two five d one two-f -t-zero t twenty five d twelve-f -~133-A -one hundred thirty three-A -~B2A23C -B two A twenty three C -~25d08A -twenty five d zero eight A -two five d zero eight A -~C24 -C twenty four -~It seemed to her that the jacket Oswald wore was darker than Commission Exhibit No. 162. -It seemed to her that the jacket Oswald wore was darker than Commission Exhibit number one hundred sixty two. -It seemed to her that the jacket Oswald wore was darker than Commission Exhibit number one hundred and sixty two. -It seemed to her that the jacket Oswald wore was darker than Commission Exhibit number one six two. -~"Father, let this cup pass." He prayed was heard. What cup was it that passed away from him? Sure not the death-cup, now filled to the brim! There was no quailing in the awful word; He still was king of kings, of lords the lord: He feared lest, in the suffering waste and grim, His faith might grow too faint and sickly dim." -"Father, let this cup pass." He prayed was heard. What cup was it that passed away from him? Sure not the death-cup, now filled to the brim! There was no quailing in the awful word; He still was king of kings, of lords the lord: He feared lest, in the suffering waste and grim, His faith might grow too faint and sickly dim." -~1970-2010 -nineteen seventy-twenty ten -one thousand nine hundred and seventy-two thousand ten -one thousand nine hundred and seventy-twenty ten -nineteen seventy to twenty ten -one thousand nine hundred seventy to two thousand ten -~W26s -W twenty six s -W two six s -~5-3-Ws -five-three-Ws -~401-ks -four oh one-ks -four hundred one-ks -~The box was 25 x 7 m. -The box was twenty five by seven meters. -~4567 -four thousand five hundred sixty seven -four five six seven -forty five sixty seven -four thousand five hundred and sixty seven -~This example number 15,000 can be a very long one, and can fail to produce valid normalization for such an easy number like 10,125 or dollar value $5349.01, and can fail to terminate, and can fail to terminate, and can fail to terminate, and can fail to terminate, and can fail to terminate, 452. -This example number fifteen thousand can be a very long one, and can fail to produce valid normalization for such an easy number like ten thousand one hundred twenty five or dollar value five thousand three hundred and forty nine dollars and one cent, and can fail to terminate, and can fail to terminate, and can fail to terminate, and can fail to terminate, and can fail to terminate, four fifty two. -~$1.01 -one dollar one cent -one dollar and one cent -~$.02 -two cents -~$17.31 -seventeen dollars and thirty one cents -~$17.312 -seventeen point three one two dollars -~25.] -two five.] -twenty five.] -~Francis I--test -Francis the first--test -Francis first--test -~13000 -one three zero zero zero -one three oh oh oh -thirteen thousand -~11/17/05 -november seventeenth zero five -november seventeenth oh five -the seventeenth of november oh five -~05 -oh five -zero five -~0063 -zero zero six three -oh oh sixty three -~ABC -ABC -A B C -~Test -Test -~2006-08-05 -august fifth two thousand six -the fifth of august two thousand six -~2-5 -two to five -two-five -~627 -six hundred twenty seven -six twenty seven -six two seven -~3/4 -the fourth of march -march fourth -three quarters -three fourths -~3/4/1998 -march four nineteen ninety eight -the fourth of march nineteen ninety eight -three/four/one nine nine eight -march fourth nineteen ninety eight -~1998-3-4 -nineteen ninety eight - march four -nineteen ninety eight - march fourth -nineteen ninety eight - the fourth of march -one nine nine eight-three-four -march fourth nineteen ninety eight -~0.004 -zero point zero zero four -oh point oh oh four -~[0.4] and [5 and 4] -[zero point four] and [five and four] -~Henry III. -Henry three. -Henry the third. -~for Tu (2/22) at 5 pm. -for Tuesday (the twenty second of february) at five PM. -for Tuesday (two divided by twenty two) at five PM. -for Tuesday (february twenty second) at five PM. -for Tuesday (two/two two) at five PM. -for Tuesday (two twenty seconds) at five PM. -for Tuesday (two/twenty two) at five PM. -for Tuesday (february twenty two) at five PM. -~12" -twelve inches -twelve" -~Sam I -Sam first -Sam the first -~2*8 -two times eight -two asterisk eight -~2-8 -two minus eight -two to eight -~2:8 -two to eight -~2/8 -two divided by eight -~[YI1] -[YI1] -[YI one] -~/ and $ -/ and dollar diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index 2e1b5ec7e0ef..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,27 +0,0 @@ -0th~zeroth -11th~eleventh -23rd~twenty third -1000th~one thousandth -1,000th~one thousandth -1000000th~one millionth -9,000,000th~nine millionth -1st~first -1th~one th -2nd~second -2th~two th -3rd~third -3th~three th -4th~fourth -4rd~four rd -11th~eleventh -11st~eleven st -20th~twentieth -12th~twelfth -13th~thirteenth -12nd~twelve nd -13rd~thirteen rd -21st~twenty first -21th~twenty one th -121st~one hundred twenty first -111th~one hundred eleventh -111st~one hundred eleven st \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_punctuation.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_punctuation.txt deleted file mode 100644 index 5f5b249c15fe..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_punctuation.txt +++ /dev/null @@ -1,64 +0,0 @@ -a `quote` example~a `quote` example -a `25` example~a `twenty five` example -single quote.'~single quote.' -single quote. '4~single quote. ' four -company's results,' said he:~company's results,' said he: -test -~test - --5 test -~minus five test - -abbreviation USA.~abbreviation USA. -abbreviation U.S.A.~abbreviation USA -abbreviation. U.S.A..~abbreviation. USA.. -1-4=5~one minus four equals five -&hi;&hi;~and hi; and hi; -abbreviation USA,~abbreviation USA, -23rd july, 1998~the twenty third of july, nineteen ninety eight -April 29th’s meeting~april twenty ninth’s meeting -?,~?, -?,no~?,no -I've 20' and 14/ they're I'm 16c.~I've twenty ' and fourteen slash they're I'm sixteen c. -He's and I'm and Müller's and d'être~He's and I'm and Müller's and d'être -here (4 June 2014). and~here (the fourth of june twenty fourteen). and -``He's 50 and 2010``.~"He's fifty and twenty ten". -"He's 50 and 2010".~"He's fifty and twenty ten". -``test``.~"test". -This (12 species) and...~This (twelve species) and... -animals: ``cat``, ``dog``, ``lion``~animals: "cat", "dog", "lion" -animals: (1), (2), (3)~animals: (one), (two), (three) -animals: ``cat~animals: "cat -animals: ``4~animals: " four -non matching quotes?" "12text"~non matching quotes?" "twelve text" -12"~twelve inches -"12's and 3'sssssss"~"twelve's and three ' sssssss" -This is ABC 'second ~This is ABC 'second -``text 7`` text ``.~"text seven" text ". -"text 7" text ".~"text seven inches text". -"And now," he said, "He,~"And now," he said, "He, -a: "b", "c", "d", "e", "f" or "g".~a: "b", "c", "d", "e", "f" or "g". -a: "b" "c" "d" "e" "f" or "g".~a: "b" "c" "d" "e" "f" or "g". -a: ``b``, ``c``, ``d``, ``e``, ``f`` or ``g``.~a: "b", "c", "d", "e", "f" or "g". -"And now," he said, "He,~"And now," he said, "He, -80's~eighty's -test .b@gmail.com~test. b at gmail dot com -ourdailynews.abc/123-sm~ourdailynews. abc/one hundred twenty three-sm -123,000012~one hundred and twenty three, zero zero zero zero one two -9000,000th~nine thousand, zero zero zero th -16 July, 1943~the sixteenth of july, nineteen forty three -April 29th’s meeting~april twenty ninth’s meeting -august 23, 2002~august twenty third, two thousand two -11:30EST~eleven: thirty EST -11:30...~eleven thirty... -11:20AM,2:40PM and 10:10PM.~eleven twenty AM, two forty PM and ten ten PM. -dr. Evil~dr. Evil -1961–1965 and (2006–2012)~nineteen sixty one– nineteen sixty five and (two thousand six– twenty twelve) -114...48~one hundred and fourteen... forty eight -12kg.~twelve kilograms. -123?123~ one hundred and twenty three? one hundred and twenty three -2!~two! -1!hello~one! hello -1, ~one, -1!!!!~one!!!! -(1)Hello~(one) Hello -ÀÁÂÃ check §- and ƛ, also ɧ~ÀÁÂÃ check section - and ƛ, also ɧ -Hi it's 5pm,4A.M.?-34. Hi,no,yes,34! 12,again,4 and NO?17 and $.01,here & there--0.004kg~Hi it's five PM, four AM.? minus thirty four. Hi,no,yes, thirty four! twelve, again, four and NO? seventeen and one cent, here and there - minus zero point zero zero four kilograms -1°C.~one degree Celsius. -my email is myemail@gmail.com!~my email is myemail at gmail dot com! diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_punctuation_match_input.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_punctuation_match_input.txt deleted file mode 100644 index 51d4aceb503f..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_punctuation_match_input.txt +++ /dev/null @@ -1,13 +0,0 @@ -&hi;&hi;~and hi;and hi; -23rd july,1998~the twenty third of july,nineteen ninety eight -I've 20' and 14/ they're I'm 16c.~I've twenty' and fourteen slash they're I'm sixteen c. -He's and I'm and Müller's and d'être~He's and I'm and Müller's and d'être -here (4 June 2014).and~here (the fourth of june twenty fourteen).and -This (12 species) and ...~This (twelve species) and ... -"12's and 3'sssssss"~"twelve's and three'sssssss" -a: ``b``,``c``, ``d``, ``e``, ``f`` or ``g``.~a: "b","c", "d", "e", "f" or "g". -1!hello~one!hello -1 ,~one , -(1)Hello~(one)Hello -ÀÁÂÃ check §- and ƛ, also ɧ~ÀÁÂÃ check section- and ƛ, also ɧ -Hi it's 5pm,4A.M.?-34. Hi,no,yes,34! 12,again,4 and NO?17 and $.01,here & there--0.004kg~Hi it's five PM,four AM.?minus thirty four. Hi,no,yes,thirty four! twelve,again,four and NO?seventeen and one cent,here and there - minus zero point zero zero four kilograms \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_range.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_range.txt deleted file mode 100644 index 3110928062f3..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_range.txt +++ /dev/null @@ -1,18 +0,0 @@ -1980-1986~nineteen eighty to nineteen eighty six -from 2-10~from two - ten -2-5lb~two to five pounds -2-5~two - five -2x8 m2~two by eight square meters -2x8~two x eight -2+3~two plus three -2+3 m2~two plus three m two -170 - 45190~one hundred and seventy - four five one nine zero -1980-1970 kg~one thousand nine hundred and eighty to one thousand nine hundred and seventy kilograms -5pm-7 pm~five PM to seven PM -4:00 am - 8:12 pm~four AM to eight twelve PM -978-0~nine hundred and seventy eight - zero -1960s-80s~nineteen sixties to eighties -1960s-1980s~nineteen sixties to nineteen eighties -1960-80~nineteen sixty to eighty -mid-1980s~mid nineteen eighties -mid-80s~mid eighties \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_roman.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_roman.txt deleted file mode 100644 index 2e3790361a65..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_roman.txt +++ /dev/null @@ -1,4 +0,0 @@ -Sam II~Sam second -Chapter IV~Chapter four -PART XL~PART forty -Sam and I~Sam and I diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_serial.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_serial.txt deleted file mode 100644 index 4007bf5c0105..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_serial.txt +++ /dev/null @@ -1,31 +0,0 @@ -t-0t25d12-f~t-zero t twenty five d twelve-f -133-ABC~one hundred thirty three-ABC -B2A23C~B two A twenty three C -25d08A~twenty five d zero eight A -C24~C twenty four -W2s~W two s -1-413-te-b-1-5~one-four hundred thirteen-te-b-one-five -b-c-1-5-b-s-b~b-c-one-five-b-s-b -MIG-25/235212-asdg~MIG-twenty five/two three five two one two-asdg -1/f-4s~one/f-four s -1/f~one per F -4s~four S -7-eleven~seven-eleven -2x~two x -31/31/100~thirty one/thirty one/one hundred -1-8090~one - eight thousand and ninety -f++~f plus plus -dfsd#sfgsfd$~dfsd hash sfgsfd dollar -dfsd$$sfgsfd$~dfsd dollar dollar sfgsfd dollar -$12@12%~dollar twelve at twelve percent sign -@12~at twelve -12@~twelve at -@mypizza~at mypizza -#mytext#~hash mytext hash -test$~test dollar -covid-19~covid-nineteen -55-millimeters long~fifty five-millimeters long -a 4-kilogram bag~a four-kilogram bag -100-car~one hundred-car -123/261788/2021~one hundred twenty three/two six one seven eight eight/two thousand twenty one -2*8~two asterisk eight diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_special_text.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_special_text.txt deleted file mode 100644 index c32983d90a45..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_special_text.txt +++ /dev/null @@ -1,10 +0,0 @@ -[HH AH0 L OW1]~[HH AH0 L OW1] -[nəkɫudɔf ˈfɫəʃt... ənd ˈfɛɫt - ˈɔɫˌweɪz ˈdɪd!]~[nəkɫudɔf ˈfɫəʃt... ənd ˈfɛɫt - ˈɔɫˌweɪz ˈdɪd!] -[poʊstˌmɑɹk]~[poʊstˌmɑɹk] -~ -go home~go home -gohome~gohome -~ -~ -123 123~ one hundred and twenty three one hundred and twenty three - haleluja ~ haleluja \ No newline at end of file diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_telephone.txt deleted file mode 100644 index fd51e9f5afbc..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,20 +0,0 @@ -+1 123-123-5678~plus one, one two three, one two three, five six seven eight -123-123-5678~one two three, one two three, five six seven eight -+1-123-123-5678~plus one, one two three, one two three, five six seven eight -+1 (123)-123-5678~plus one, one two three, one two three, five six seven eight -+1(123) 123-5678~plus one, one two three, one two three, five six seven eight -(123)-123-5678~one two three, one two three, five six seven eight -(123) 123-5678~one two three, one two three, five six seven eight -123-123-5678-1111~one two three, one two three, five six seven eight, one one one one -123-123-5678-1~one two three, one two three, five six seven eight, one -1-800-GO-U-HAUL~one, eight hundred, GO U HAUL -1-800-GO-2-HAUL~one, eight hundred, GO two, HAUL -987.987.0.40~nine eight seven dot nine eight seven dot zero dot four zero -call me at +1 123-123-5678~call me at plus one, one two three, one two three, five six seven eight -call me at 123-123-5678~call me at one two three, one two three, five six seven eight -123.123.0.40~one two three dot one two three dot zero dot four zero -IP address is 123.123.0.40~IP address is one two three dot one two three dot zero dot four zero -111-11-1111~one one one, one one, one one one one -my ssn is 111-11-1111~my SSN is one one one, one one, one one one one -555.555.5555~five five five, five five five, five five five five -(555)555-5555~five five five, five five five, five five five five diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_time.txt deleted file mode 100644 index e7f1d53e404c..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,19 +0,0 @@ -01:00~one o'clock -01:00 am~one AM -01:00 a.m.~one AM -01:00 a.m~one AM -1 a.m.~one AM -23:00~twenty three o'clock -1:00 a.m.~one AM -1:00a.m.~one AM -1.59 p.m.~one fifty nine PM -01:59 p.m.~one fifty nine PM -1:59 p.m.~one fifty nine PM -1:59 p.m. est~one fifty nine PM EST -1:59 p.m.est~one fifty nine PM EST -1:59 p.m. e.s.t~one fifty nine PM EST -10:00:00 p.m. e.s.t~ten hours zero minutes and zero seconds PM EST -1:01:01~one hour one minute and one second -14:10:30~fourteen hours ten minutes and thirty seconds -2pm-5pm~two PM to five PM -5pm~five PM diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 7fafb9d77152..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,6 +0,0 @@ -Dr. Evil~doctor Evil -Mrs. Norris~misses Norris -DNA is~DNA is -C. S. Lewis~CS Lewis -tv~TV -and/or~and/or diff --git a/tests/nemo_text_processing/en/data_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/en/data_text_normalization/test_cases_word.txt deleted file mode 100644 index 3fb24ebcc202..000000000000 --- a/tests/nemo_text_processing/en/data_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,38 +0,0 @@ -~ - ~ - 1~one - no~no -May I come in?~May I come in? -Yes you may.~Yes you may. -On the mar.~On the mar. -es3~es three -x ~x -X!~X! -—~— -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aalem~aalem -a'ali~a'ali -aaliyan's~aaliyan's -mother-in-law~mother-in-law -there -0.4kg~there minus zero point four kilograms -there- -0.4kg~there- minus zero point four kilograms -$ and 5% or %~dollar and five percent or percent sign - 1~one -1~one -!1~! one -mar~mar -/$€₩£BB¥#%AA and $€₩£¥#%~slash dollar euro won pound BB yen hash percent sign AA and dollar euro won pound yen hash percent sign -love him while we may,~love him while we may, -mar~mar diff --git a/tests/nemo_text_processing/en/test_address.py b/tests/nemo_text_processing/en/test_address.py deleted file mode 100644 index d2a246faa523..000000000000 --- a/tests/nemo_text_processing/en/test_address.py +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestAddress: - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False, post_process=True) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - # address is tagged by the measure class - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_address.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_cardinal.py b/tests/nemo_text_processing/en/test_cardinal.py deleted file mode 100644 index 4b5507869546..000000000000 --- a/tests/nemo_text_processing/en/test_cardinal.py +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestCardinal: - inverse_normalizer_en = ( - (InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False)) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False, post_process=True) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False, punct_post_process=False) - assert pred == expected, f"input: {test_input}" - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic, f"input: {test_input}" diff --git a/tests/nemo_text_processing/en/test_date.py b/tests/nemo_text_processing/en/test_date.py deleted file mode 100644 index 01bfa50158f1..000000000000 --- a/tests/nemo_text_processing/en/test_date.py +++ /dev/null @@ -1,96 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDate: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False, post_process=True) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/install_pynini.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_uncased(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, punct_post_process=False, n_tagged=100 - ) - assert expected in pred_non_deterministic, f"INPUT: {test_input}" - - normalizer_uppercased = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - cases_uppercased = {"Aug. 8": "august eighth", "8 Aug.": "the eighth of august", "aug. 8": "august eighth"} - - @parameterized.expand(cases_uppercased.items()) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/install_pynini.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_cased(self, test_input, expected): - pred = self.normalizer_uppercased.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, punct_post_process=False, n_tagged=30 - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_decimal.py b/tests/nemo_text_processing/en/test_decimal.py deleted file mode 100644 index 51a180251ba5..000000000000 --- a/tests/nemo_text_processing/en/test_decimal.py +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDecimal: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case="cased", cache_dir=CACHE_DIR, overwrite_cache=False, post_process=True) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_electronic.py b/tests/nemo_text_processing/en/test_electronic.py deleted file mode 100644 index 06edfe15370e..000000000000 --- a/tests/nemo_text_processing/en/test_electronic.py +++ /dev/null @@ -1,70 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestElectronic: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case="cased", cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=100, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_fraction.py b/tests/nemo_text_processing/en/test_fraction.py deleted file mode 100644 index 647bad02a4ac..000000000000 --- a/tests/nemo_text_processing/en/test_fraction.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestFraction: - normalizer_en = ( - Normalizer(input_case="cased", cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_fraction.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_math.py b/tests/nemo_text_processing/en/test_math.py deleted file mode 100644 index 25a608bfd840..000000000000 --- a/tests/nemo_text_processing/en/test_math.py +++ /dev/null @@ -1,57 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMath: - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - # math is tagged by the measure class - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_math.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_measure.py b/tests/nemo_text_processing/en/test_measure.py deleted file mode 100644 index 6261f2e5da66..000000000000 --- a/tests/nemo_text_processing/en/test_measure.py +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMeasure: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case="cased", cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_money.py b/tests/nemo_text_processing/en/test_money.py deleted file mode 100644 index f9b37d7e6dda..000000000000 --- a/tests/nemo_text_processing/en/test_money.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMoney: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected, f"input: {test_input}" - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected, f"input: {test_input}" - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_normalization_with_audio.py b/tests/nemo_text_processing/en/test_normalization_with_audio.py deleted file mode 100644 index 37a22b7b1070..000000000000 --- a/tests/nemo_text_processing/en/test_normalization_with_audio.py +++ /dev/null @@ -1,47 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, get_test_cases_multiple - -try: - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestNormalizeWithAudio: - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', lm=False, cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(get_test_cases_multiple('en/data_text_normalization/test_cases_normalize_with_audio.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - if self.normalizer_with_audio_en: - pred = self.normalizer_with_audio_en.normalize(test_input, n_tagged=30, punct_post_process=True) - assert len(set(pred).intersection(set(expected))) == len( - expected - ), f'missing: {set(expected).difference(set(pred))}' diff --git a/tests/nemo_text_processing/en/test_ordinal.py b/tests/nemo_text_processing/en/test_ordinal.py deleted file mode 100644 index 641ff6f045e3..000000000000 --- a/tests/nemo_text_processing/en/test_ordinal.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestOrdinal: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_punctuation.py b/tests/nemo_text_processing/en/test_punctuation.py deleted file mode 100644 index 8bda062400df..000000000000 --- a/tests/nemo_text_processing/en/test_punctuation.py +++ /dev/null @@ -1,56 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestPunctuation: - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False, post_process=True,) - if PYNINI_AVAILABLE - else None - ) - - # address is tagged by the measure class - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_punctuation.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=True, punct_post_process=False) - assert pred == expected, f"input: {test_input} != {expected}" - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_punctuation_match_input.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_python_punct_post_process(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=True, punct_post_process=True) - assert pred == expected, f"input: {test_input} != {expected}" diff --git a/tests/nemo_text_processing/en/test_range.py b/tests/nemo_text_processing/en/test_range.py deleted file mode 100644 index 97213b37f1ac..000000000000 --- a/tests/nemo_text_processing/en/test_range.py +++ /dev/null @@ -1,57 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestRange: - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - # address is tagged by the measure class - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_range.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_roman.py b/tests/nemo_text_processing/en/test_roman.py deleted file mode 100644 index ae6ce0842bcd..000000000000 --- a/tests/nemo_text_processing/en/test_roman.py +++ /dev/null @@ -1,57 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestRoman: - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - # address is tagged by the measure class - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_roman.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_serial.py b/tests/nemo_text_processing/en/test_serial.py deleted file mode 100644 index 4f25cbbaac13..000000000000 --- a/tests/nemo_text_processing/en/test_serial.py +++ /dev/null @@ -1,56 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestSerial: - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_serial.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False, punct_post_process=False) - assert pred == expected, f"input: {test_input}" - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=30, punct_post_process=False, - ) - assert expected in pred_non_deterministic, f"input: {test_input}" diff --git a/tests/nemo_text_processing/en/test_sparrowhawk_inverse_text_normalization.sh b/tests/nemo_text_processing/en/test_sparrowhawk_inverse_text_normalization.sh deleted file mode 100644 index 2633670c0637..000000000000 --- a/tests/nemo_text_processing/en/test_sparrowhawk_inverse_text_normalization.sh +++ /dev/null @@ -1,79 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1) - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$spoken" "$written" "$denorm_pred" - done < "$input" -} - -testITNCardinal() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testITNDate() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_date.txt - runtest $input -} - -testITNDecimal() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_decimal.txt - runtest $input -} - -testITNElectronic() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_electronic.txt - runtest $input -} - -testITNOrdinal() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testITNTime() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_time.txt - runtest $input -} - -testITNMeasure() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_measure.txt - runtest $input -} - -testITNMoney() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_money.txt - runtest $input -} - -testITNWhitelist() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testITNTelephone() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_telephone.txt - runtest $input -} - -testITNWord() { - input=$PROJECT_DIR/en/data_inverse_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/en/test_sparrowhawk_normalization.sh b/tests/nemo_text_processing/en/test_sparrowhawk_normalization.sh deleted file mode 100644 index 7baa7c198ae9..000000000000 --- a/tests/nemo_text_processing/en/test_sparrowhawk_normalization.sh +++ /dev/null @@ -1,115 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read written spoken <<< $testcase - # replace non breaking space with breaking space - denorm_pred=$(echo $written | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1 | sed 's/\xC2\xA0/ /g') - - # trim white space - spoken="$(echo -e "${spoken}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$written" "$spoken" "$denorm_pred" - done < "$input" -} - -testTNSpecialText() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_special_text.txt - runtest $input -} - -testTNCardinal() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testTNDate() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_date.txt - runtest $input -} - -testTNDecimal() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_decimal.txt - runtest $input -} - -testTNRange() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_range.txt - runtest $input -} - -testTNSerial() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_serial.txt - runtest $input -} - -#testTNRoman() { -# input=$PROJECT_DIR/en/data_text_normalization/test_cases_roman.txt -# runtest $input -#} - -testTNElectronic() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_electronic.txt - runtest $input -} - -testTNFraction() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_fraction.txt - runtest $input -} - -testTNMoney() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_money.txt - runtest $input -} - -testTNOrdinal() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testTNTelephone() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_telephone.txt - runtest $input -} - -testTNTime() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_time.txt - runtest $input -} - -testTNMeasure() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_measure.txt - runtest $input -} - -testTNWhitelist() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testTNWord() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_word.txt - runtest $input -} - -testTNAddress() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_address.txt - runtest $input -} - -testTNMath() { - input=$PROJECT_DIR/en/data_text_normalization/test_cases_math.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/en/test_special_text.py b/tests/nemo_text_processing/en/test_special_text.py deleted file mode 100644 index 4a73bbcbead0..000000000000 --- a/tests/nemo_text_processing/en/test_special_text.py +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestSpecialText: - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_special_text.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - # if self.normalizer_with_audio_en: - # pred_non_deterministic = self.normalizer_with_audio_en.normalize( - # test_input, n_tagged=30, punct_post_process=False, - # ) - # assert expected in pred_non_deterministic, f"input: {test_input}" diff --git a/tests/nemo_text_processing/en/test_telephone.py b/tests/nemo_text_processing/en/test_telephone.py deleted file mode 100644 index c0db058fc9fb..000000000000 --- a/tests/nemo_text_processing/en/test_telephone.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTelephone: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=10, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_text_split.py b/tests/nemo_text_processing/en/test_text_split.py deleted file mode 100644 index 4241914ea5fa..000000000000 --- a/tests/nemo_text_processing/en/test_text_split.py +++ /dev/null @@ -1,50 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest - -from ..utils import CACHE_DIR - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTextSentenceSplit: - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False, post_process=True) - if PYNINI_AVAILABLE - else None - ) - - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - def test_text_sentence_split(self): - text = "This happened in 1918 when Mrs. and Mr. Smith paid $111.12 in U.S.A. at 9 a.m. on Dec. 1. 2020. And Jan. 17th. This is an example. He paid $123 for this desk. 123rd, St. Patrick." - gt_sentences = [ - 'This happened in 1918 when Mrs. and Mr. Smith paid $111.12 in U.S.A. at 9 a.m. on Dec. 1. 2020.', - 'And Jan. 17th.', - 'This is an example.', - 'He paid $123 for this desk.', - '123rd, St. Patrick.', - ] - sentences = self.normalizer_en.split_text_into_sentences(text) - assert gt_sentences == sentences diff --git a/tests/nemo_text_processing/en/test_time.py b/tests/nemo_text_processing/en/test_time.py deleted file mode 100644 index aff02d57a786..000000000000 --- a/tests/nemo_text_processing/en/test_time.py +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTime: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=10, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_whitelist.py b/tests/nemo_text_processing/en/test_whitelist.py deleted file mode 100644 index 7364b90b5387..000000000000 --- a/tests/nemo_text_processing/en/test_whitelist.py +++ /dev/null @@ -1,91 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWhitelist: - inverse_normalizer_en = ( - (InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False)) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case='cased', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=10, punct_post_process=False - ) - assert expected in pred_non_deterministic - - normalizer_uppercased = Normalizer(input_case='cased', lang='en') if PYNINI_AVAILABLE else None - cases_uppercased = {"Dr. Evil": "doctor Evil", "dr. Evil": "dr. Evil", "no. 4": "no. four"} - - @parameterized.expand(cases_uppercased.items()) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_cased(self, test_input, expected): - pred = self.normalizer_uppercased.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=10, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/en/test_word.py b/tests/nemo_text_processing/en/test_word.py deleted file mode 100644 index b5e798d0c4bf..000000000000 --- a/tests/nemo_text_processing/en/test_word.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWord: - inverse_normalizer_en = ( - InverseNormalizer(lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('en/data_inverse_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer_en.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_en = ( - Normalizer(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False, post_process=True) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_en = ( - NormalizerWithAudio(input_case='cased', lang='en', cache_dir=CACHE_DIR, overwrite_cache=False) - if RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('en/data_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_en.normalize(test_input, verbose=False) - assert pred == expected, f"input: {test_input} != {expected}" - - if self.normalizer_with_audio_en: - pred_non_deterministic = self.normalizer_with_audio_en.normalize( - test_input, n_tagged=3, punct_post_process=False - ) - assert expected in pred_non_deterministic, f"input: {test_input}" diff --git a/tests/nemo_text_processing/es/__init__.py b/tests/nemo_text_processing/es/__init__.py deleted file mode 100644 index 7d200df57afe..000000000000 --- a/tests/nemo_text_processing/es/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index 7cd24635c5eb..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,50 +0,0 @@ -(non-ideal case) entre dieciséis mil y dieciocho mil~(non-ideal case) entre 16018 1000 -doscientos cincuenta y uno~251 -novecientos noventa y nueve millones novecientos noventa y nueve mil novecientos noventa y nueve~999999999 -cero~cero -uno~uno -una~una -dos~dos -nueve~nueve -diez~10 -, uno~, uno -, diez~, 10 -menos veintitrés~-23 -cien~100 -ciento uno~101 -ciento un~101 -ciento una~101 -mil y uno~1001 -mil uno~1001 -nueve billones setecientos ochenta y nueve mil trescientos ochenta y dos millones quinientos treinta y seis mil ciento treinta~9789382536130 -doscientos cincuenta y cuatro~254 -ciento cuarenta y siete mil cuatrocientos cincuenta y uno~147451 -un millón ciento cincuenta y seis mil ciento setenta y tres~1156173 -mil quinientos noventa y tres millones setenta y dos mil novecientos sesenta y uno~1593072961 -noventa y siete mil ochocientos ocho billones doscientos sesenta y cuatro mil setecientos setenta y dos millones setecientos noventa y dos mil cinco~97808264772792005 -diecisiete mil ochocientos cincuenta y cinco trillones treinta y seis mil seiscientos cincuenta y siete billones siete mil quinientos noventa y seis millones ciento diez mil novecientos cuarenta y nueve~17855036657007596110949 -diez mil diez billones diez millones cien mil diez~10010000010100010 -menos veinticinco mil treinta y siete~-25037 -mil doscientos sesenta y cuatro billones trescientos un mil novecientos treinta y ocho millones ciento cuatro~1264301938000104 -menos sesenta~-60 -cuarenta y seis mil seiscientos sesenta y cuatro~46664 -sesenta~60 -dos millones tres~2000003 -mil trece~1013 -mil cien~1100 -mil veintiséis~1026 -mil ciento veintiséis~1126 -dieciocho millones cuatrocientos cincuenta mil novecientos noventa~18450990 -dieciocho millones novecientos cuarenta mil setecientos veintidós~18940722 -dieciocho millones seiscientos noventa mil novecientos dieciséis~18690916 -dieciocho mil ochocientos ochenta~18880 -un millardo uno~1000000001 -mil millones uno~1000000001 -mil millones ciento uno~1000000101 -mil millones mil ciento uno~1000001101 -mil millones diez mil ciento uno~1000010101 -mil un millón diez mil ciento uno~1001010101 -dos millardos cincuenta y dos~2000000052 -muchas millones~muchas millones -mil billones uno~1000000000000001 -mil trillones uno~1000000000000000000001 \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_date.txt deleted file mode 100644 index f3de84bf416b..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,6 +0,0 @@ -primero de enero~1 de enero -uno de enero~1 de enero -el uno de diciembre~el 1 de diciembre -el primero de diciembre~el 1 de diciembre -domingo veintiséis de octubre~domingo 26 de octubre -treinta y uno de diciembre de mil novecientos noventa y dos~31 de diciembre de 1992 \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 3aa1005275a2..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,29 +0,0 @@ -uno coma dos seis~1,26 -menos uno coma dos seis~-1,26 -uno coma veintiséis~1,26 -cero coma dos seis~0,26 -cero coma veintiséis~0,26 -tres coma ciento cuarenta y uno~3,141 -tres coma cero ciento cuarenta y uno~3,0141 -tres coma ciento cuarenta y uno cincuenta y nueve~3,14159 -tres coma catorce ciento cincuenta y nueve~3,14159 -tres coma catorce quince noventa y dos sesenta cinco treinta y cinco~3,1415926535 -tres coma catorce quince cero noventa y dos sesenta cinco treinta y cinco~3,14150926535 -tres coma catorce quince cero novecientos veintiséis cero quinientos treinta y cinco~3,141509260535 -cuatrocientos millones~400 millones -uno punto treinta y tres~1.33 -uno punto treinta y tres millones~1.33 millones -cero coma seis millones~0,6 millones -mil ochocientos veinticuatro millón~1824 millón -mil ochocientos veinticuatro millones~1824 millones -punto dos seis~.26 -un millón~1 millón -dos millones~2 millones -un millardo~1 millardo -dos millardos~2 millardos -un billón~1 billón -dos billones~2 billones -un trillón~1 trillón -dos trillones~2 trillones -un cuatrillón~1 cuatrillón -dos cuatrillones~2 cuatrillones diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_electronic.txt deleted file mode 100644 index fd9387f63d78..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,13 +0,0 @@ -a punto b c arroba g mail punto com~a.bc@gmail.com -c d f arroba a b c punto e d u~cdf@abc.edu -a b c arroba g mail punto a b c~abc@gmail.abc -a b c arroba a b c punto com~abc@abc.com -a s d f uno dos tres arroba a b c punto com~asdf123@abc.com -a uno b dos arroba a b c punto com~a1b2@abc.com -a b tres punto s d d punto tres arroba g mail punto com~ab3.sdd.3@gmail.com -hache te te pe ese dos puntos barra barra doble ve doble ve doble ve punto n vidia punto com~https://www.nvidia.com -doble ve doble ve doble ve punto n vidia punto com~www.nvidia.com -doble ve doble ve doble ve punto nvidia punto com~www.nvidia.com -w w w punto nvidia punto com~www.nvidia.com -doble ve doble ve doble ve punto a b c punto es barra e f g~www.abc.es/efg -doble ve doble ve doble ve punto a b c punto es~www.abc.es \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_measure.txt deleted file mode 100644 index 582a0d69c695..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,13 +0,0 @@ -doscientos metros~200 m -tres horas~3 h -una hora~1 h -doscientos cuarenta y cinco millas por hora~245 mph -dos kilos~2 kg -sesenta coma dos cuatro cero cero kilogramos~60,2400 kg -menos sesenta coma veinticuatro cero cero kilogramos~-60,2400 kg -ocho coma cinco dos por ciento~8,52 % -menos ocho coma cinco dos por ciento~-8,52 % -uno porciento~1 % -tres centímetros~3 cm -cuatro segundos~4 s -cinco litros~5 l \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_money.txt deleted file mode 100644 index c9c8892257cd..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,15 +0,0 @@ -doce dólares y cinco centavos~$12,05 -doce dólares y cinco céntimos~$12,05 -setenta y cinco dólares sesenta y tres~$75,63 -setenta y cinco dólares y sesenta y tres centavos~$75,63 -setenta y cinco dólares con sesenta y tres centavos~$75,63 -setenta y cinco dólares con sesenta y tres~$75,63 -veintinueve dólares cincuenta centavos~$29,50 -un dólar~$1 -veinticinco centavos~$0,25 -veinticinco céntimos~$0,25 -doce euros y cinco centavos~€12,05 -doce dólares estadounidenses y cinco centavos~US$12,05 -doce dólares americanos y cinco centavos~US$12,05 -doce pesos y cinco centavos~$12,05 -doce yenes y cinco centavos~¥12,05 \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index 18830c934767..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,29 +0,0 @@ -primero~primero -tercera~tercera -primer~primer -tercer~tercer -noveno~noveno -novena~novena -décimo~10.º -décima~10.ª -undécimo~11.º -undécima~11.ª -decimoprimero~11.º -décimo primero~11.º -decimoprimer~11.ᵉʳ -décimo primer~11.ᵉʳ -decimoprimera~11.ª -décima primera~11.ª -(technically ungrammatical) décimo primera~(technically ungrammatical) 11.ª -decimotercero~13.º -vigésimo primero~21.º -vigésima primera~21.ª -(technically ungrammatical) vigésimo primera~(technically ungrammatical) 21.ª -vigésimo primer~21.ᵉʳ -vigésimosegundo~22.º -vigésimo segundo~22.º -vigésimosegunda~22.ª -vigésima segunda~22.ª -vigésimo tercero~23.º -centésimo undécimo~111.º -centésimo trigésimo cuarto~134.º diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_telephone.txt deleted file mode 100644 index 8a536301e1f8..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,6 +0,0 @@ -uno dos tres uno dos tres cinco seis siete ocho~123-123-5678 -uno veintitrés uno veintitrés cincuenta y seis setenta y ocho~123-123-5678 -uno dos tres cuatro cinco seis siete ocho nueve~123-456-789 -uno veintitrés cuatro cincuenta y seis siete ochenta y nueve~123-456-789 -uno dos tres cuatro cinco seis siete ocho~1234-5678 -doce treinta y cuatro cincuenta y seis setenta y ocho~1234-5678 \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_time.txt deleted file mode 100644 index ed554fc266ac..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,19 +0,0 @@ -las dieciséis cincuenta~las 16:50 -la una~la una -las dos~las dos -las tres personas~las tres personas -las dos a eme~las 2:00 a.m. -la una pe eme~la 1:00 p.m. -la una y diez~la 1:10 -la una y diez a eme~la 1:10 a.m. -la una y diez pe eme~la 1:10 p.m. -la una diez~la 1:10 -la una con diez~la 1:10 -la una y cuarto~la 1:15 -la una y media~la 1:30 -las dos menos veinte~la 1:40 -las dos menos cuarto~la 1:45 -cuarto para las dos~la 1:45 -un cuarto para las dos~la 1:45 -las veintitrés y media~las 23:30 -las veintitrés y cincuenta y nueve~las 23:59 \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 849a5a428a3d..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,4 +0,0 @@ -usted~ud. -ustedes~uds. -habla usted español~habla ud. español -hablan ustedes español~hablan uds. español \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_word.txt deleted file mode 100644 index 80b5275d40e5..000000000000 --- a/tests/nemo_text_processing/es/data_inverse_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,49 +0,0 @@ -~ -yahoo!~yahoo! -veinte!~20 ! -x ~x -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index e12b3f115504..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,69 +0,0 @@ -2~dos -3~tres -4~cuatro -5~cinco -6~seis -7~siete -8~ocho -9~nueve -10~diez -11~once -12~doce -13~trece -14~catorce -15~quince -16~dieciséis -17~diecisiete -18~dieciocho -19~diecinueve -20~veinte -22~veintidós -23~veintitrés -24~veinticuatro -25~veinticinco -26~veintiséis -27~veintisiete -28~veintiocho -29~veintinueve -30~treinta -40~cuarenta -50~cincuenta -60~sesenta -70~setenta -80~ochenta -90~noventa -100~cien -102~ciento dos -120~ciento veinte -130~ciento treinta -1000~mil -1 000~mil -1.000~mil -1010~mil diez -1020~mil veinte -1100~mil cien -1110~mil ciento diez -1111~mil ciento once -2000~dos mil -2002~dos mil dos -2010~dos mil diez -2020~dos mil veinte -2100~dos mil cien -2110~dos mil ciento diez -2111~dos mil ciento once -10000~diez mil -10 000~diez mil -10.000~diez mil -100000~cien mil -100 000~cien mil -100.000~cien mil -1 000 000~un millón -1.000.000~un millón -1 034 068~un millón treinta y cuatro mil sesenta y ocho -2.000.000~dos millones -1.000.000.000~mil millones -2.000.000.000~dos mil millones -3 000 000 000 000~tres billones -3.000.000.000.000~tres billones -100 000 000 000 000 000 000 000~cien mil trillones -100 000 000 000 000 000 000 002~cien mil trillones dos diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_date.txt deleted file mode 100644 index bccdca7ec552..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,13 +0,0 @@ -1 enero~primero de enero -5 febrero~cinco de febrero -20 de marzo~veinte de marzo -abril 30~treinta de abril -31 marzo~treinta y uno de marzo -10 mayo 1990~diez de mayo de mil novecientos noventa -junio 11 2000~once de junio de dos mil -30 julio del 2020~treinta de julio del dos mil veinte -30-2-1990~treinta de febrero de mil novecientos noventa -30/2/1990~treinta de febrero de mil novecientos noventa -30.2.1990~treinta de febrero de mil novecientos noventa -1990-2-30~treinta de febrero de mil novecientos noventa -1990-02-30~treinta de febrero de mil novecientos noventa \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 39df4d89d935..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,19 +0,0 @@ -33,32~treinta y tres coma treinta y dos -32,22 millones~treinta y dos coma veintidós millones -320 320,22 millones~trescientos veinte mil trescientos veinte coma veintidós millones -5.002,132~cinco mil dos coma ciento treinta y dos -3,2 trillones~tres coma dos trillones -3 millones~tres millones -3 000 millones~tres mil millones -3000 millones~tres mil millones -3.000 millones~tres mil millones -3.001 millones~tres mil un millones -1 millón~un millón -1 000 millones~mil millones -1000 millones~mil millones -1.000 millones~mil millones -2,33302 millones~dos coma tres tres tres cero dos millones -1,5332 millón~uno coma cinco tres tres dos millón -1,53322 millón~uno coma cinco tres tres dos dos millón -1,53321 millón~uno coma cinco tres tres dos un millón -101,010101 millones~ciento uno coma cero uno cero uno cero un millones \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_electronic.txt deleted file mode 100644 index 0ac0b0bbd4fb..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,12 +0,0 @@ -a.bc@gmail.com~a punto b c arroba gmail punto com -cdf@abc.edu~c d f arroba a b c punto e d u -abc@gmail.abc~a b c arroba gmail punto a b c -abc@abc.com~a b c arroba a b c punto com -asdf123@abc.com~a s d f uno dos tres arroba a b c punto com -a1b2@abc.com~a uno b dos arroba a b c punto com -ab3.sdd.3@gmail.com~a b tres punto s d d punto tres arroba gmail punto com -https://www.nvidia.com~h t t p s dos puntos barra barra w w w punto nvidia punto com -www.nvidia.com~w w w punto nvidia punto com -www.abc.es/efg~w w w punto a b c punto es barra e f g -www.abc.es~w w w punto a b c punto es -http://www.ourdailynews.com.sm~h t t p dos puntos barra barra w w w punto o u r d a i l y n e w s punto com punto s m \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_fraction.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_fraction.txt deleted file mode 100644 index 1260c898d61a..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_fraction.txt +++ /dev/null @@ -1,72 +0,0 @@ -1/3~un tercio -2/3~dos tercios -1/4~un cuarto -2/4~dos cuartos -1/5~un quinto -2/5~dos quintos -1/6~un sexto -2/6~dos sextos -1/7~un séptimo -2/7~dos séptimos -1/8~un octavo -2/8~dos octavos -1/9~un noveno -2/9~dos novenos -1/10~un décimo -2/10~dos décimos -1/11~un onceavo -1/12~un doceavo -1/13~un treceavo -1/14~un catorceavo -1/15~un quinceavo -1/16~un dieciseisavo -1/17~un diecisieteavo -1/18~un dieciochoavo -1/19~un diecinueveavo -1/20~un veinteavo -1/21~un veintiunavo -1/22~un veintidosavo -1/30~un treintavo -1/31~un treintaiunavo -1/40~un cuarentavo -1/41~un cuarentaiunavo -1/50~un cincuentavo -1/60~un sesentavo -1/70~un setentavo -1/80~un ochentavo -1/90~un noventavo -1/100~un centésimo -2/100~dos centésimos -3 2/100~tres y dos centésimos -1/101~uno sobre ciento uno -1/110~uno sobre ciento diez -1/111~uno sobre ciento once -1/112~uno sobre ciento doce -1/123~uno sobre ciento veintitrés -1/134~uno sobre ciento treinta y cuatro -1/200~un ducentésimo -1/201~uno sobre doscientos uno -1/234~uno sobre doscientos treinta y cuatro -1/300~un tricentésimo -1/345~uno sobre trescientos cuarenta y cinco -1/400~un cuadringentésimo -1/456~uno sobre cuatrocientos cincuenta y seis -1/500~un quingentésimo -1/600~un sexcentésimo -1/700~un septingentésimo -1/800~un octingentésimo -1/900~un noningentésimo -1/1000~un milésimo -2/1000~dos milésimos -2 2/1000~dos y dos milésimos -1/1001~uno sobre mil uno -1/1100~uno sobre mil cien -1/1200~uno sobre mil doscientos -1/1234~uno sobre mil doscientos treinta y cuatro -1/2000~un dosmilésimo -1/5000~un cincomilésimo -1/10000~un diezmilésimo -1/100.000~un cienmilésimo -1/1.000.000~un millonésimo -1/100.000.000~un cienmillonésimo -1/1.200.000.000~un mildoscientosmillonésimo \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_measure.txt deleted file mode 100644 index a456ee3eda31..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,24 +0,0 @@ -1,2-a~uno coma dos a -a-5~a cinco -200 m~doscientos metros -3 3/5 m~tres y tres quintos de metro -3 h~tres horas -1 h~una hora -245 mph~doscientas cuarenta y cinco millas por hora -200.045 mph~doscientas mil cuarenta y cinco millas por hora -1,01 mph~una coma cero una millas por hora -1 1/2 mph~una y media milla por hora -1 1/2 m~uno y medio metro -1 3/5 mph~una y tres quintos de milla por hora -3/5 mph~tres quintos de milla por hora -2 kg~dos kilogramos -60,2400 kg~sesenta coma dos cuatro cero cero kilogramos --60,2400 kg~menos sesenta coma dos cuatro cero cero kilogramos -8,52 %~ocho coma cincuenta y dos por ciento --8,52 %~menos ocho coma cincuenta y dos por ciento -1 %~uno por ciento -3 cm~tres centímetros -4 s~cuatro segundos -5 l~cinco litros -4,51/s~cuatro coma cincuenta y uno por segundo -0,0101 s~cero coma cero uno cero un segundos \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_money.txt deleted file mode 100644 index 0a8706ecf502..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,25 +0,0 @@ -$1~un dólar -1 $~un dólar -$1,50~un dólar cincuenta centavos -1,50 $~un dólar cincuenta centavos -£200.000.001~doscientos millones una libras -200.000.001 £~doscientos millones una libras -2 billones de euros~dos billones de euros -€2 billones~dos billones de euros -€ 2 billones~dos billones de euros -€ 2,3 billones~dos coma tres billones de euros -2,3 billones de euros~dos coma tres billones de euros -€5,50~cinco euros cincuenta céntimos -5,50 €~cinco euros cincuenta céntimos -5,01 €~cinco euros un céntimo -5,01 £~cinco libras un penique -21 czk~veintiuna coronas checas -czk21~veintiuna coronas checas -czk21,1 millones~veintiuno coma un millones de coronas checas -czk 5,50 billones~cinco coma cincuenta billones de coronas checas -rs 5,50 billones~cinco coma cincuenta billones de rupias -czk5,50 billones~cinco coma cincuenta billones de coronas checas -0,55 $~cincuenta y cinco centavos -1,01 $~un dólar un centavo -¥12,05~doce yenes cinco centavos -£200.000.001~doscientos millones una libras \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_normalize_with_audio.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_normalize_with_audio.txt deleted file mode 100644 index f118673ad173..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_normalize_with_audio.txt +++ /dev/null @@ -1,162 +0,0 @@ -~1,0101 -uno coma cero uno cero un -uno coma cero uno cero uno -una coma cero una cero una -~21 -veintiún -veintiuno -veintiuna -~201 -doscientos un -doscientos uno -doscientas una -doscientas un -~1 -un -uno -una -~121 -ciento veintiún -ciento veintiuno -ciento veintiuna -121 -~200 -doscientos -doscientas -200 -~201 -doscientos un -doscientos uno -doscientas una -201 -~221 -doscientos veintiún -doscientas veintiún -doscientos veintiuno -doscientas veintiuna -~1 -un -uno -una -1 -~550.000.001 -quinientos cincuenta millones un -quinientos cincuenta millones una -quinientos cincuenta millones uno -550.000.001 -~500.501 -quinientos mil quinientos un -quinientos mil quinientos uno -quinientas mil quinientas una -quinientas mil quinientas un -500.501 -~500.001.º -quinientosmilésimo primero -quingentésimo milésimo primero -quinientosmilésimos primeros -quingentésimos milésimos primeros -500.001.º -~500.001.ª -quinientasmilésima primera -quingentésima milésima primera -quinientasmilésimas primeras -quingentésimas milésimas primeras -500.001.ª -~11.ª -décima primera -decimoprimera -décimas primeras -decimoprimeras -undécima -undécimas -11.ª -~11.º -décimo primero -decimoprimero -décimos primeros -decimoprimeros -undécimo -undécimos -11.º -~12.º -décimo segundo -decimosegundo -décimos segundos -decimosegundos -duodécimo -duodécimos -12.º -~200,0101 -doscientos coma cero uno cero un -doscientos coma cero uno cero uno -doscientas coma cero una cero una -doscientas coma cero una cero un -200,0101 -~1.000.200,21 -un millón doscientos coma veintiún -un millón doscientas coma veintiún -un millón doscientos coma veintiuno -un millón doscientas coma veintiuna -un millón doscientas y veintiún -un millón doscientos coma dos un -un millón doscientos coma dos uno -un millón doscientas coma dos una -un millón doscientas coma dos un -1.000.200,21 -~1/12 -un doceavo -una doceava parte -un duodécimo -una duodécima parte -uno sobre doce -1/12 -~5/200 -cinco ducentésimos -cinco ducentésimas partes -cinco sobre doscientos -5/200 -~1 5/3 -uno y cinco tercios -una y cinco terceras partes -uno y cinco sobre tres -una y cinco sobre tres -~1/5/2020 -primero de mayo de dos mil veinte -uno de mayo de dos mil veinte -cinco de enero de dos mil veinte -~$5,50 -cinco dólares con cincuenta -cinco dólares y cincuenta -cinco dólares cincuenta -cinco dólares con cincuenta centavos -cinco dólares y cincuenta centavos -cinco dólares cincuenta centavos -~2.30 h -dos y treinta -dos y media -tres menos treinta -tres menos media -treinta para las tres -~cmxcix -noningentésimo nonagésimo noveno -noningentésima nonagésima novena -~1/2 -medio -media parte -media -~1 1/2 -uno y medio -una y media parte -una y media -~3/2 -tres medios -tres medias -tres medias partes -~12.30 a.m. -doce y treinta de la medianoche -doce y treinta de la noche -doce y media de la medianoche -doce y media de la noche -una menos treinta de la mañana -una menos media de la mañana -treinta para la una de la mañana \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index 77c084cf8e37..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,107 +0,0 @@ -1.ᵉʳ~primer -1.º~primero -1.ª~primera -2.º~segundo -2.ª~segunda -3.ᵉʳ~tercer -3.º~tercero -3.ª~tercera -4.º~cuarto -4.ª~cuarta -5.º~quinto -5.ª~quinta -6.º~sexto -6.ª~sexta -7.º~séptimo -7.ª~séptima -8.º~octavo -8.ª~octava -9.º~noveno -9.ª~novena -10.º~décimo -10.ª~décima -11.ᵉʳ~decimoprimer -11.º~undécimo -11.ª~undécima -12.º~duodécimo -12.ª~duodécima -13.ᵉʳ~decimotercer -13.º~decimotercero -13.ª~decimotercera -14.º~decimocuarto -14.ª~decimocuarta -15.º~decimoquinto -15.ª~decimoquinta -16.º~decimosexto -16.ª~decimosexta -17.º~decimoséptimo -17.ª~decimoséptima -18.º~decimoctavo -18.ª~decimoctava -19.º~decimonoveno -19.ª~decimonovena -20.º~vigésimo -20.ª~vigésima -21.ᵉʳ~vigesimoprimer -21.º~vigesimoprimero -21.ª~vigesimoprimera -30.º~trigésimo -30.ª~trigésima -31.ᵉʳ~trigésimo primer -31.º~trigésimo primero -31.ª~trigésima primera -40.º~cuadragésimo -40.ª~cuadragésima -41.ᵉʳ~cuadragésimo primer -41.º~cuadragésimo primero -41.ª~cuadragésima primera -50.º~quincuagésimo -50.ª~quincuagésima -51.ᵉʳ~quincuagésimo primer -51.º~quincuagésimo primero -51.ª~quincuagésima primera -60.º~sexagésimo -60.ª~sexagésima -70.º~septuagésimo -70.ª~septuagésima -80.º~octogésimo -80.ª~octogésima -90.º~nonagésimo -90.ª~nonagésima -100.º~centésimo -100.ª~centésima -101.ᵉʳ~centésimo primer -101.º~centésimo primero -101.ª~centésima primera -134.º~centésimo trigésimo cuarto -134.ª~centésima trigésima cuarta -200.º~ducentésimo -200.ª~ducentésima -300.º~tricentésimo -300.ª~tricentésima -400.º~cuadringentésimo -400.ª~cuadringentésima -500.º~quingentésimo -500.ª~quingentésima -600.º~sexcentésimo -600.ª~sexcentésima -700.º~septingentésimo -700.ª~septingentésima -800.º~octingentésimo -800.ª~octingentésima -900.º~noningentésimo -900.ª~noningentésima -1000.º~milésimo -1000.ª~milésima -1001.ᵉʳ~milésimo primer -1 000.º~milésimo -1 000.ª~milésima -1 001.ᵉʳ~milésimo primer -1.000.º~milésimo -1.000.ª~milésima -1.001.ᵉʳ~milésimo primer -1248.º~milésimo ducentésimo cuadragésimo octavo -1248.ª~milésima ducentésima cuadragésima octava -2000.º~dosmilésimo -100 000.º~cienmilésimo -999.º~noningentésimo nonagésimo noveno \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_telephone.txt deleted file mode 100644 index a6aa6928b6ec..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,3 +0,0 @@ -123-123-5678~uno dos tres uno dos tres cinco seis siete ocho -123-456-789~uno dos tres cuatro cinco seis siete ocho nueve -1234-5678~uno dos tres cuatro cinco seis siete ocho \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_time.txt deleted file mode 100644 index 62d5c3485dc3..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,26 +0,0 @@ -1.00~una -1:00~una -01:00~una -01 h~una -3 h~tres horas -1 h~una hora -1.05 h~una y cinco -01.05 h~una y cinco -1.00 h~una -1.00 a.m.~una de la mañana -1.00 a.m~una de la mañana -1.00 p.m.~una de la tarde -1.00 p.m est~una de la tarde e s t -1.00 est~una e s t -5:02 est~cinco y dos e s t -5:02 p.m pst~cinco y dos de la noche p s t -5:02 p.m.~cinco y dos de la noche -12.15~doce y cuarto -12.15 a.m.~doce y cuarto de la noche -12.15 p.m.~doce y cuarto del mediodía -13.30~trece y media -14.05~catorce y cinco -24:50~veinticuatro y cincuenta -3:02:32 pst~tres horas dos minutos y treinta y dos segundos p s t -00:52~cero y cincuenta y dos -0:52~cero y cincuenta y dos diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 1699392fc454..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,3 +0,0 @@ -el dr.~el doctor -sr. rodriguez~señor rodriguez -182 esq. toledo~ciento ochenta y dos esquina toledo \ No newline at end of file diff --git a/tests/nemo_text_processing/es/data_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/es/data_text_normalization/test_cases_word.txt deleted file mode 100644 index 0d3e97450c17..000000000000 --- a/tests/nemo_text_processing/es/data_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,48 +0,0 @@ -~ -yahoo!~yahoo! -veinte!~veinte! -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/es/test_cardinal.py b/tests/nemo_text_processing/es/test_cardinal.py deleted file mode 100644 index ddb302661d78..000000000000 --- a/tests/nemo_text_processing/es/test_cardinal.py +++ /dev/null @@ -1,76 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestCardinal: - - inverse_normalizer = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_date.py b/tests/nemo_text_processing/es/test_date.py deleted file mode 100644 index f14b3338ee7a..000000000000 --- a/tests/nemo_text_processing/es/test_date.py +++ /dev/null @@ -1,75 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDate: - inverse_normalizer = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_decimal.py b/tests/nemo_text_processing/es/test_decimal.py deleted file mode 100644 index 8ffab62e0bdd..000000000000 --- a/tests/nemo_text_processing/es/test_decimal.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDecimal: - inverse_normalizer = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_electronic.py b/tests/nemo_text_processing/es/test_electronic.py deleted file mode 100644 index a8eb62af3399..000000000000 --- a/tests/nemo_text_processing/es/test_electronic.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestElectronic: - inverse_normalizer_es = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_es(self, test_input, expected): - pred = self.inverse_normalizer_es.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_fraction.py b/tests/nemo_text_processing/es/test_fraction.py deleted file mode 100644 index 746a9857a7e3..000000000000 --- a/tests/nemo_text_processing/es/test_fraction.py +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestFraction: - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_fraction.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_measure.py b/tests/nemo_text_processing/es/test_measure.py deleted file mode 100644 index 8b7e673a3634..000000000000 --- a/tests/nemo_text_processing/es/test_measure.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMeasure: - inverse_normalizer_es = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_es(self, test_input, expected): - pred = self.inverse_normalizer_es.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_money.py b/tests/nemo_text_processing/es/test_money.py deleted file mode 100644 index 090aafe6ef07..000000000000 --- a/tests/nemo_text_processing/es/test_money.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMoney: - inverse_normalizer = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_normalization_with_audio.py b/tests/nemo_text_processing/es/test_normalization_with_audio.py deleted file mode 100644 index 67c495e9de2b..000000000000 --- a/tests/nemo_text_processing/es/test_normalization_with_audio.py +++ /dev/null @@ -1,50 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, get_test_cases_multiple - -try: - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestNormalizeWithAudio: - - normalizer_es = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(get_test_cases_multiple('es/data_text_normalization/test_cases_normalize_with_audio.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_es.normalize(test_input, n_tagged=50, punct_post_process=False) - print(expected) - print("pred") - print(pred) - assert len(set(pred).intersection(set(expected))) == len( - expected - ), f'missing: {set(expected).difference(set(pred))}' diff --git a/tests/nemo_text_processing/es/test_ordinal.py b/tests/nemo_text_processing/es/test_ordinal.py deleted file mode 100644 index ef49e4167669..000000000000 --- a/tests/nemo_text_processing/es/test_ordinal.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestOrdinal: - inverse_normalizer = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False, - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_sparrowhawk_inverse_text_normalization.sh b/tests/nemo_text_processing/es/test_sparrowhawk_inverse_text_normalization.sh deleted file mode 100644 index f6a71c2cb005..000000000000 --- a/tests/nemo_text_processing/es/test_sparrowhawk_inverse_text_normalization.sh +++ /dev/null @@ -1,64 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1) - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$spoken" "$written" "$denorm_pred" - done < "$input" -} - -testITNCardinal() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testITNDate() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_date.txt - runtest $input -} - -testITNDecimal() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_decimal.txt - runtest $input -} - -testITNOrdinal() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testITNTime() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_time.txt - runtest $input -} - -testITNMeasure() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_measure.txt - runtest $input -} - -testITNMoney() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_money.txt - runtest $input -} - -testITNWhitelist() { - input=$PROJECT_DIR/es/data_inverse_text_normalization/test_cases_whitelist.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/es/test_sparrowhawk_normalization.sh b/tests/nemo_text_processing/es/test_sparrowhawk_normalization.sh deleted file mode 100644 index a74399e26712..000000000000 --- a/tests/nemo_text_processing/es/test_sparrowhawk_normalization.sh +++ /dev/null @@ -1,84 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read written spoken <<< $testcase - denorm_pred=$(echo $written | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1) - - # trim white space - spoken="$(echo -e "${spoken}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$written" "$spoken" "$denorm_pred" - done < "$input" -} - -testTNCardinal() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testTNDate() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_date.txt - runtest $input -} - -testTNDecimal() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_decimal.txt - runtest $input -} - -testTNElectronic() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_electronic.txt - runtest $input -} - -testTNFraction() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_fraction.txt - runtest $input -} - -testTNMoney() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_money.txt - runtest $input -} - -testTNOrdinal() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testTNTelephone() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testTNTime() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_time.txt - runtest $input -} - -testTNMeasure() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_measure.txt - runtest $input -} - -testTNWhitelist() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testTNWord() { - input=$PROJECT_DIR/es/data_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/es/test_telephone.py b/tests/nemo_text_processing/es/test_telephone.py deleted file mode 100644 index edf020cf34e7..000000000000 --- a/tests/nemo_text_processing/es/test_telephone.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTelephone: - inverse_normalizer_es = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_es(self, test_input, expected): - pred = self.inverse_normalizer_es.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=30, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_time.py b/tests/nemo_text_processing/es/test_time.py deleted file mode 100644 index 0f19bad9b4ae..000000000000 --- a/tests/nemo_text_processing/es/test_time.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTime: - inverse_normalizer_es = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_es(self, test_input, expected): - pred = self.inverse_normalizer_es.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=500, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_whitelist.py b/tests/nemo_text_processing/es/test_whitelist.py deleted file mode 100644 index d8d36a5fd183..000000000000 --- a/tests/nemo_text_processing/es/test_whitelist.py +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWhitelist: - inverse_normalizer_es = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_es(self, test_input, expected): - pred = self.inverse_normalizer_es.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and PYNINI_AVAILABLE and RUN_AUDIO_BASED_TESTS - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer.normalize(test_input, verbose=False) - assert pred == expected - - if self.normalizer_with_audio: - pred_non_deterministic = self.normalizer_with_audio.normalize( - test_input, n_tagged=10, punct_post_process=False - ) - assert expected in pred_non_deterministic diff --git a/tests/nemo_text_processing/es/test_word.py b/tests/nemo_text_processing/es/test_word.py deleted file mode 100644 index 54b6307a30fe..000000000000 --- a/tests/nemo_text_processing/es/test_word.py +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, RUN_AUDIO_BASED_TESTS, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - from nemo_text_processing.text_normalization.normalize import Normalizer - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWord: - inverse_normalizer_es = ( - InverseNormalizer(lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('es/data_inverse_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_es(self, test_input, expected): - pred = self.inverse_normalizer_es.inverse_normalize(test_input, verbose=False) - assert pred == expected - - normalizer_es = ( - Normalizer(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if PYNINI_AVAILABLE - else None - ) - normalizer_with_audio_es = ( - NormalizerWithAudio(input_case='cased', lang='es', cache_dir=CACHE_DIR, overwrite_cache=False) - if CACHE_DIR and RUN_AUDIO_BASED_TESTS and PYNINI_AVAILABLE - else None - ) - - @parameterized.expand(parse_test_case_file('es/data_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm(self, test_input, expected): - pred = self.normalizer_es.normalize(test_input, verbose=False) - assert pred == expected, f"input: {test_input}" - - if self.normalizer_with_audio_es: - pred_non_deterministic = self.normalizer_with_audio_es.normalize( - test_input, n_tagged=150, punct_post_process=False - ) - assert expected in pred_non_deterministic, f"input: {test_input}" diff --git a/tests/nemo_text_processing/fr/__init__.py b/tests/nemo_text_processing/fr/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/tests/nemo_text_processing/fr/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index 9cebe04a5ffc..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,106 +0,0 @@ -cent~100 -dix-huit~18 -vingt et un~21 -vingt-et-un~21 -trente et un~31 -trente-et-un~31 -quarante-trois~43 -quarante trois~40 trois -cinquante et un~51 -cinquante-et-un~51 -soixante et un~61 -soixante-et-un~61 -soixante-dix~70 -soixante-douze~72 -quatre-vingts~80 -quatre-vingt-dix-huit~98 -cent~100 -cent deux~102 -cent-deux~102 -cent vingt~120 -cent-vingt~120 -deux-cents~200 -deux cent neuf~209 -deux-cent-neuf~209 -cent onze~111 -cent-onze~111 -mille~1000 -cent vingt~120 -cent-vingt~120 -mille vingt~1020 -mille-vingt~1020 -neuf billion sept cent quatre-vingt-neuf milliard trois cent quatre-vingt-deux million cinq cent trente-six mille cent trente~9789382536130 -neuf-billion-sept-cent-quatre-vingt-neuf-milliard-trois-cent-quatre-vingt-deux-million-cinq-cent-trente-six-mille-cent-trente~9789382536130 -deux cent cinquante-quatre~254 -deux-cent-cinquante-quatre~254 -cent quarante-sept mille quatre cent cinquante et une~147451 -cent-quarante-sept-mille-quatre-cent-cinquante-et-une~147451 -un million cent cinquante-six mille cent soixante-treize~1156173 -un-million-cent-cinquante-six-mille-cent-soixante-treize~1156173 -un milliard cinq cent quatre-vingt-treize million soixante-douze mille neuf cent soixante et un~1593072961 -un-milliard-cinq-cent-quatre-vingt-treize-million-soixante-douze-mille-neuf-cent-soixante-et-un~1593072961 -un milliard cinq cent quatre-vingt-treize million septante-deux mille neuf cent soixante et un~1593072961 -un-milliard-cinq-cent-quatre-vingt-treize-million-septante-deux-mille-neuf-cent-soixante-et-un~1593072961 -quatre-vingt-dix-sept billiard huit cent huit billion deux cent soixante-quatre milliard sept cent soixante-douze million sept cent quatre-vingt-douze mille cinq~97808264772792005 -quatre-vingt-dix-sept-billiard-huit-cent-huit-billion-deux-cent-soixante-quatre-milliard-sept-cent-soixante-douze-million-sept-cent-quatre-vingt-douze-mille-cinq~97808264772792005 -dix billiard dix billion dix million cent mille dix~10010000010100010 -dix-billiard-dix-billion-dix-million-cent-mille-dix~10010000010100010 -moins vingt-cinq mille trente-sept~-25037 -moins vingt-cinq-mille-trente-sept~-25037 -moins dix-neuf cent trente-sept~-1937 -moins dix-neuf-cent-trente-sept~-1937 -un billiard deux cent soixante-quatre billion trois cent un milliard neuf cent trente-huit million cent quatre~1264301938000104 -un-billiard-deux-cent-soixante-quatre-billion-trois-cent-un-milliard-neuf-cent-trente-huit-million-cent-quatre~1264301938000104 -moins soixante~-60 -quarante-six mille six cent soixante-quatre~46664 -quarante-six-mille-six-cent-soixante-quatre~46664 -soixante~60 -zéro~zéro -un~un -une~une -deux~deux -neuf~neuf -dix~10 -onze~11 -douze~12 -treize~13 -quatorze~14 -quinze~15 -seize~16 -dix-sept~17 -dix-huit~18 -vingt~20 -trente~30 -quarante~40 -cinquante~50 -soixante~60 -soixante-dix~70 -septante~70 -quatre-vingts~80 -huitante~80 -quatre-vingt-dix~90 -deux million dix~2000010 -deux-million-dix~2000010 -mille treize~1013 -mille-treize~1013 -mille un~1001 -mille-un~1001 -mille cent~1100 -mille-cent~1100 -onze cents~1100 -onze-cents~1100 -dix-huit mille treize~18013 -dix-huit-mille-treize~18013 -mille vingt-six~1026 -mille-vingt-six~1026 -mille cent vingt-six~1126 -mille-cent-vingt-six~1126 -onze cent vingt-six~1126 -onze-cent-vingt-six~1126 -dix-huit million quatre cent cinquante mille neuf cent quatre-vingt-dix~18450990 -dix-huit-million-quatre-cent-cinquante-mille-neuf-cent-quatre-vingt-dix~18450990 -dix-huit-million-quatre-cent-cinquante-mille-neuf-cent-nonante~18450990 -dix-huit mille huit cent quatre-vingts~18880 -dix-huit-mille-huit-cent-quatre-vingts~18880 -dix-huit mille huit cent huitante~18880 -dix-huit-mille-huit-cent-huitante~18880 \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_date.txt deleted file mode 100644 index b31c11c19ab9..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,6 +0,0 @@ -vingt-quatre juillet deux-mille-treize~24 juillet 2013 -vingt-quatre juillet~24 juillet -quatorze janvier~14 janvier -premier janvier~1ᵉʳ janvier -trente juin~30 juin -dix-huit mai dix-neuf cent trente~18 mai 1930 \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 6e14ac07e58b..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,15 +0,0 @@ -zéro virgule deux million~0,2 million -dix-huit milliards~18 milliards -quatre cent soixante millions~460 millions -quatre-cent-soixante millions~460 millions -quatre-cent-soixante-millions~460 millions -cent vingt millions~120 millions -cent-vingt-millions~120 millions -cent vingt millions~120 millions -dix billions~10 billions -dix-billions~10 billions -moins soixante virgule deux quatre zéro zéro~-60,240 0 -huit cent dix-huit virgule trois zéro trois~818,303 -huit-cent-dix-huit virgule trois zéro trois~818,303 -huit-cent-dix-huit virgule trente trois~818,303 -mille-huit-cent-dix-huit virgule trois zéro trois trois quatre~1 818,303 34 \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_electronic.txt deleted file mode 100644 index f70075b1896f..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,10 +0,0 @@ -a point b c arobase g mail point com~a.bc@gmail.com -a point b c at g mail point com~a.bc@gmail.com -c d f at a b c point e d u~cdf@abc.edu -a b c at g mail point a b c~abc@gmail.abc -a b c arobase g mail point a b c~abc@gmail.abc -a b c at a b c point com~abc@abc.com -a s d f un deux trois at a b c point com~asdf123@abc.com -a un b deux arobase a b c point com~a1b2@abc.com -a b trois point s d d point trois at g mail point com~ab3.sdd.3@gmail.com -a b trois point s d d point trois arobase g mail point com~ab3.sdd.3@gmail.com \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_fraction.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_fraction.txt deleted file mode 100644 index fbaed97b3ce2..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_fraction.txt +++ /dev/null @@ -1,30 +0,0 @@ -demi~1/2 -un tiers~1/3 -un quart~1/4 -un cinquième~1/5 -un sixième~1/6 -un septième~1/7 -un huitième~1/8 -deux neuvième~2/9 -un et demi~1 1/2 -un dixième~1/10 -un onzième~1/11 -un douzième~1/12 -un treizième~1/13 -un quatrième~1/4 -un quatorzième~1/14 -un quinzième~1/15 -un seizième~1/16 -un dix-septième~1/17 -un dix-huitième~1/18 -un dix-neuvième~1/19 -un vingtième~1/20 -un trentième~1/30 -un quarantième~1/40 -un cinquantième~1/50 -un soixantième~1/60 -un soixante-dixième~1/70 -un quatre-vingtième~1/80 -un quatre-vingt-dixième~1/90 -un centième~1/100 -quatre et deux quatrièmes~4 2/4 \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_measure.txt deleted file mode 100644 index af99890be5be..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,15 +0,0 @@ -deux cents mètres~200 m -cinquante-six virgule trois par kilomètre carré~56,3 /km² -deux-cents kilomètres par heure~200 km/h -deux-cents kilomètres heure~200 km/h -quarante-deux-mille-deux-cent-cinquante-neuf par mètre carré~42 259 /m² -moins soixante-six kilogrammes~-66 kg -un virgule zéro zéro zéro zéro vingt-huit centimètre cube~1,000 028 cm³ -cinquante minutes~50 min -deux mètres cubes~2 m³ -quatre-vingt-dix grammes~90 g -quatre-cent-quarante millilitres~440 ml -trois cents micromètres~300 µm -soixante-cinq kilomètres carrés~65 km² -deux kilomètres par heure~2 km/h -soixante virgule vingt-quatre zéro zéro kilogrammes~60,240 0 kg \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_money.txt deleted file mode 100644 index 9d67e8f05d76..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,22 +0,0 @@ -deux dollars~2 $ -un centime~0,01 € -vingt centimes~0,20 € -vingt-deux centimes~0,22 € -deux dollars vingt~2,20 $ -deux euros et vingt centimes~2,20 € -vingt euros~20 € -un franc suisse~1 CHF -vingt euro cinq~20,05 € -un euro~1 € -deux euro~2 € -cinq euro et soixante~5,60 € -cinquante centimes~0,50 € -quatre-vingt mille won~80 000 ₩ -quatre-vingt-mille won~80 000 ₩ -quatre-vingt-millions de wons~80 millions de wons -trois livre~3 £ -trois pence~0,03 £ -zéro euro~0 € -zéro euro quatre-vingt~0,80 € -deux-millions de dollars~2 millions de dollars -quatre virgule quatre-vingt milliards d'euros~4,80 milliards d'euros \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index 5d5c8efc7987..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,23 +0,0 @@ -centième~100ᵉ -centièmes~100ᵉˢ -vingt-cinq-mille-cent-onzième~25111ᵉ -première~1ʳᵉ -premières~1ʳᵉˢ -premier~1ᵉʳ -premiers~1ᵉʳˢ -second~2ᵈ -seconds~2ᵈˢ -seconde~2ᵈᵉ -secondes~2ᵈᵉˢ -deuxième~2ᵉ -troisième~3ᵉ -quatrième~4ᵉ -onzièmes~11ᵉˢ -treizième~13ᵉ -vingt-et-unième~21ᵉ -vingt-troisièmes~23ᵉˢ -cent-onzième~111ᵉ -cent onzième~111ᵉ -millième~1000ᵉ -dix-neuvième siècle~XIXᵉ siècle -vingtième siècle~XXᵉ siècle \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_telephone.txt deleted file mode 100644 index 764bedda74ee..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,4 +0,0 @@ -zéro deux douze trente-deux trente trente~02 12 32 30 30 -zéro deux une deux trois deux trois zéro trois zéro~02 12 32 30 30 -deux douze trente-deux trente trente~02 12 32 30 30 -deux une deux trois deux trois zéro trois zéro~02 12 32 30 30 \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_time.txt deleted file mode 100644 index a8381312406e..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,18 +0,0 @@ -huit heures~8 h -huit heures du matin~8 h -huit heures du soir~20 h -minuit~0 h -deux heures de l'après-midi~14 h -quatorze heures~14 h -midi~12 h -dix-huit heures~18 h -huit heures sept~8 h 07 -minuit dix-sept~0 h 17 -douze heures~12 h -onze heures et demie~11 h 30 -midi moins le quart~11 h 45 -onze heures et trois quarts~11 h 45 -midi moins trois~11 h 57 -onze heures cinquante-sept~11 h 57 -onze heures trente-huit~11 h 38 -midi moins vingt-deux~11 h 38 \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 8535bfd461cb..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,8 +0,0 @@ -docteur~Dʳ -docteures~Dʳᵉˢ -monsieur~M. -messieurs~MM. -madame~Mᵐᵉ -mesdames~Mᵐᵉˢ -mademoiselle~Mˡˡᵉ -mademoiselles~Mˡˡᵉˢ \ No newline at end of file diff --git a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_word.txt deleted file mode 100644 index 66f3445a034d..000000000000 --- a/tests/nemo_text_processing/fr/data_inverse_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,49 +0,0 @@ -~ -yahoo!~yahoo! -vingt!~20 ! -x ~x -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/fr/test_cardinal.py b/tests/nemo_text_processing/fr/test_cardinal.py deleted file mode 100644 index 3da85485d5c0..000000000000 --- a/tests/nemo_text_processing/fr/test_cardinal.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestCardinal: - - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_date.py b/tests/nemo_text_processing/fr/test_date.py deleted file mode 100644 index 2cb1120c0656..000000000000 --- a/tests/nemo_text_processing/fr/test_date.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDate: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_decimal.py b/tests/nemo_text_processing/fr/test_decimal.py deleted file mode 100644 index 0adbbc078306..000000000000 --- a/tests/nemo_text_processing/fr/test_decimal.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDecimal: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_electronic.py b/tests/nemo_text_processing/fr/test_electronic.py deleted file mode 100644 index 8ccb76e1829f..000000000000 --- a/tests/nemo_text_processing/fr/test_electronic.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestElectronic: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_fraction.py b/tests/nemo_text_processing/fr/test_fraction.py deleted file mode 100644 index cf4d132945c0..000000000000 --- a/tests/nemo_text_processing/fr/test_fraction.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestFraction: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_fraction.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_measure.py b/tests/nemo_text_processing/fr/test_measure.py deleted file mode 100644 index 68ec945aee6d..000000000000 --- a/tests/nemo_text_processing/fr/test_measure.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMeasure: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_money.py b/tests/nemo_text_processing/fr/test_money.py deleted file mode 100644 index 0b4ee9385a35..000000000000 --- a/tests/nemo_text_processing/fr/test_money.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMoney: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_ordinal.py b/tests/nemo_text_processing/fr/test_ordinal.py deleted file mode 100644 index ffe49df17bde..000000000000 --- a/tests/nemo_text_processing/fr/test_ordinal.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestOrdinal: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_sparrowhawk_inverse_text_normalization.sh b/tests/nemo_text_processing/fr/test_sparrowhawk_inverse_text_normalization.sh deleted file mode 100644 index 4ca12af7f278..000000000000 --- a/tests/nemo_text_processing/fr/test_sparrowhawk_inverse_text_normalization.sh +++ /dev/null @@ -1,84 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1) - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$spoken" "$written" "$denorm_pred" - done < "$input" -} - -testITNCardinal() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testITNDate() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_date.txt - runtest $input -} - -testITNDecimal() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_decimal.txt - runtest $input -} - -testITNOrdinal() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testITNFraction() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_fraction.txt - runtest $input -} - -testITNTime() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_time.txt - runtest $input -} - -testITNMeasure() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_measure.txt - runtest $input -} - -testITNMoney() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_money.txt - runtest $input -} - -testITNWhitelist() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testITNTelephone() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_telephone.txt - runtest $input -} - -testITNElectronic() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_electronic.txt - runtest $input -} - -testITNWord() { - input=$PROJECT_DIR/fr/data_inverse_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/fr/test_telephone.py b/tests/nemo_text_processing/fr/test_telephone.py deleted file mode 100644 index 10bc6051d0c5..000000000000 --- a/tests/nemo_text_processing/fr/test_telephone.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTelephone: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_time.py b/tests/nemo_text_processing/fr/test_time.py deleted file mode 100644 index 2b2cc356a3f2..000000000000 --- a/tests/nemo_text_processing/fr/test_time.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTime: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_whitelist.py b/tests/nemo_text_processing/fr/test_whitelist.py deleted file mode 100644 index ec8e8d57b94d..000000000000 --- a/tests/nemo_text_processing/fr/test_whitelist.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWhitelist: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/fr/test_word.py b/tests/nemo_text_processing/fr/test_word.py deleted file mode 100644 index 19ada867b030..000000000000 --- a/tests/nemo_text_processing/fr/test_word.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWord: - inverse_normalizer = ( - InverseNormalizer(lang='fr', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('fr/data_inverse_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/__init__.py b/tests/nemo_text_processing/pt/__init__.py deleted file mode 100644 index 2db92b257416..000000000000 --- a/tests/nemo_text_processing/pt/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_cardinal.txt deleted file mode 100755 index 7219efacd9fb..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,70 +0,0 @@ -(non-ideal case) entre dezesseis mil e dezoito e mil~(non-ideal case) entre 16018 e 1000 -duzentos e cinquenta e um~251 -novecentos e noventa e nove milhões novecentos e noventa e nove mil novecentos e noventa e nove~999999999 -zero~zero -um~um -uma~uma -dois~dois -nove~nove -dez~10 -onze~11 -, um~, um -, uma~, uma -, dez~, 10 -, onze~, 11 -vinte três~23 -vinte e três~23 -trinta e três~33 -menos vinte e três~-23 -cem~100 -cento e um~101 -cento e uma~101 -cento e dez~110 -cento e onze~111 -cento e vinte três~123 -cento e vinte e três~123 -cento e cinquenta~150 -duzentos~200 -duzentos e um~201 -mil e um~1001 -mil e uma~1001 -dois mil e vinte e dois~2022 -nove trilhões setecentos e oitenta e nove bilhões trezentos e oitenta e dois milhões quinhentos e trinta e seis mil cento e trinta~9789382536130 -duzentos e cinquenta e quatro~254 -cento e quarenta e sete mil quatrocentos e cinquenta e um~147451 -cento e quarenta e sete mil quatrocentos e cinquenta e uma~147451 -um milhão cento e cinquenta e seis mil cento e setenta e três~1156173 -um bilhão quinhentos e noventa e três milhões e setenta e dois mil novecentos e sessenta e um~1593072961 -noventa e sete quatrilhões oitocentos e oito trilhões duzentos e sessenta e quatro bilhões setecentos e setenta e dois milhões setecentos e noventa e dois mil e cinco~97808264772792005 -dezessete sextilhões oitocentos e cinquenta e cinco quintilhões e trinta e seis quatrilhões seiscentos e cinquenta e sete trilhões e sete bilhões quinhentos e noventa e seis milhões cento e dez mil novecentos e quarenta e nove~17855036657007596110949 -dez quatrilhões e dez trilhões e dez milhões e cem mil e dez~10010000010100010 -menos vinte e cinco mil e trinta e sete~-25037 -um quatrilhão duzentos e sessenta e quatro trilhões trezentos e um bilhões novecentos e trinta e oito milhões cento e quatro~1264301938000104 -menos sessenta~-60 -quarenta e seis mil seiscentos e sessenta e quatro~46664 -sessenta~60 -dois milhões e três~2000003 -mil e treze~1013 -mil e cem~1100 -mil e vinte e seis~1026 -mil cento e vinte e seis~1126 -dezoito milhões quatrocentos e cinquenta mil novecentos e noventa~18450990 -dezoito milhões novecentos e quarenta mil setecentos e vinte e dois~18940722 -dezoito milhões seiscentos e noventa mil novecentos e dezesseis~18690916 -dezoito mil oitocentos e oitenta~18880 -um bilhão e um~1000000001 -um bilhão e uma~1000000001 -um bilhão cento e um~1000000101 -um bilhão cento e uma~1000000101 -um bilhão e mil cento e um~1000001101 -um bilhão e mil cento e uma~1000001101 -um bilhão e dez mil cento e um~1000010101 -um bilhão e dez mil cento e uma~1000010101 -um bilhão e um milhão e dez mil cento e um~1001010101 -um bilhão e um milhão e dez mil cento e uma~1001010101 -dois bilhões e cinquenta e dois~2000000052 -muitos milhões~muitos milhões -um quatrilhão e um~1000000000000001 -um quatrilhão e uma~1000000000000001 -um sextilhão e um~1000000000000000000001 -um sextilhão e uma~1000000000000000000001 \ No newline at end of file diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_date.txt deleted file mode 100644 index 6aa2c03127e6..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,15 +0,0 @@ -primeiro de janeiro~01 de janeiro -um de janeiro~01 de janeiro -cinco de março~05 de março -em primeiro de dezembro~em 01 de dezembro -domingo vinte e seis de outubro~domingo 26 de outubro -trinta e um de dezembro de mil novecentos e oitenta e oito~31 de dezembro de 1988 -vinte e sete de agosto de dois mil e quinze~27 de agosto de 2015 -primeiro de setembro de dois mil e vinte e dois~01 de setembro de 2022 -um do um~01/01 -dois do dois~02/02 -trinta e um do doze~31/12 -um do um de mil novecentos e oitenta e sete~01/01/1987 -dez do oito de dois mil~10/08/2000 -doze do três de dois mil e dois~12/03/2002 -trinta e um do doze de dois mil e trinta e sete~31/12/2037 \ No newline at end of file diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_decimal.txt deleted file mode 100755 index bdafdc642442..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,26 +0,0 @@ -um vírgula dois seis~1,26 -menos um vírgula dois seis~-1,26 -um vírgula vinte e seis~1,26 -zero vírgula vinte e seis~0,26 -zero vírgula vinte seis~0,26 -três vírgula cento e quarenta e um~3,141 -três vírgula zero cento e quarenta e um~3,0141 -três vírgula cento e quarenta e um cinquenta e nove~3,14159 -três vírgula quatorze cento e cinquenta e nove~3,14159 -três vírgula quatorze quinze noventa e dois sessenta e cinco trinta e cinco~3,1415926535 -três vírgula quatorze quinze zero noventa e dois sessenta e cinco trinta e cinco~3,14150926535 -três vírgula quatorze quinze zero novecentos e vinte e seis zero quinhentos e trinta e cinco~3,141509260535 -quatrocentos milhões~400 milhões -um ponto trinta e três~1.33 -um ponto trinta e três milhões~1.33 milhões -zero vírgula seis milhões~0,6 milhões -mil oitocentos e vinte e quatro milhões~1824 milhões -ponto dois seis~.26 -um milhão~1 milhão -dois milhões~2 milhões -um bilhão~1 bilhão -dois bilhões~2 bilhões -um trilhão~1 trilhão -dois trilhões~2 trilhões -um quatrilhão~1 quatrilhão -dois quatrilhões~2 quatrilhões diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_electronic.txt deleted file mode 100644 index 70a5319756c0..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,13 +0,0 @@ -a ponto b c arroba g mail ponto com~a.bc@gmail.com -c d f arroba a b c ponto e d u~cdf@abc.edu -a b c arroba g mail ponto a b c~abc@gmail.abc -a b c arroba a b c ponto com~abc@abc.com -a s d f um dois três arroba a b c ponto com~asdf123@abc.com -a um b dois arroba a b c ponto com~a1b2@abc.com -a b três ponto s d d ponto três arroba g mail ponto com~ab3.sdd.3@gmail.com -agá tê tê pê ésse dois pontos barra barra dáblio dáblio dáblio ponto n vidia ponto com~https://www.nvidia.com -dáblio dáblio dáblio ponto n vidia ponto com~www.nvidia.com -dáblio dáblio dáblio ponto nvidia ponto com~www.nvidia.com -w w w ponto nvidia ponto com~www.nvidia.com -dáblio dáblio dáblio ponto a b c ponto es barra e f g~www.abc.es/efg -dáblio dáblio dáblio ponto a b c ponto br~www.abc.br \ No newline at end of file diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_measure.txt deleted file mode 100755 index 7e3c8ca8b90c..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,12 +0,0 @@ -duzentos metros~200 m -duzentos e quarenta e cinco milhas por hora~245 mph -duzentos e quarenta e cinco quilômetros por hora~245 kph -duzentos e quarenta e cinco metros por segundo~245 m/s -dois quilos~2 kg -sessenta vírgula dois quatro zero zero quilogramas~60,2400 kg -menos sessenta vírgula dois quatro zero zero quilogramas~-60,2400 kg -oito vírgula cinco dois por cento~8,52 % -menos oito vírgula cinco dois por cento~-8,52 % -um por cento~1 % -três centímetros~3 cm -cinco litros~5 l \ No newline at end of file diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_money.txt deleted file mode 100755 index 88d7e0e7db07..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,25 +0,0 @@ -doze dólares e cinco centavos~$ 12,05 -doze dólares~$ 12 -setenta e cinco dólares e sessenta e três~$ 75,63 -setenta e cinco dólares e sessenta e três centavos~$ 75,63 -setenta e cinco dólares com sessenta e três centavos~$ 75,63 -setenta e cinco dólares com sessenta e três~$ 75,63 -vinte e nove dólares e cinquenta centavos~$ 29,50 -um dólar~$ 1 -um real~R$ 1 -cem reais~R$ 100 -duzentos reais~R$ 200 -cento e noventa e nove reais e noventa e nove centavos~R$ 199,99 -um real e um centavo~R$ 1,01 -vinte centavos~R$ 0,20 -vinte e cinco centavos~R$ 0,25 -doze euros e cinco centavos~€ 12,05 -doze dólares americanos e cinco centavos~US$ 12,05 -duas libras esterlinas~£ 2 -doze dólares e cinco centavos~$ 12,05 -pagamos cento e quinze reais por uma bala~pagamos R$ 115 por uma bala -quinze mil reais~R$ 15000 -dois bilhões de reais~R$ 2 bilhões -dois milhões de reais~R$ 2 milhões -três vírgula sete milhões de reais~R$ 3,7 milhões -quatro ponto oito milhões de dólares~$ 4.8 milhões diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_ordinal.txt deleted file mode 100755 index 0ae43e978c8b..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,19 +0,0 @@ -primeiro~primeiro -terceira~terceira -nono~nono -nona~nona -décimo~10º -décima~10ª -décimo primeiro~11º -décima primeira~11ª -(technically ungrammatical) décima primeira~(technically ungrammatical) 11ª -(technically ungrammatical) décima primeira casa~(technically ungrammatical) 11ª casa -décimo terceiro~13º -vigésimo primeiro~21º -vigésima primeira~21ª -(technically ungrammatical) vigésimo primeira~(technically ungrammatical) 21ª -vigésimo segundo~22º -vigésima segunda~22ª -vigésimo terceiro~23º -centésimo décimo primeiro~111º -centésimo trigésimo quarto~134º diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_telephone.txt deleted file mode 100755 index 04e2875b5290..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,27 +0,0 @@ -um dois três quatro cinco seis sete oito~1234-5678 -um dois três quatro cinco seis sete oito telefone~1234-5678 telefone -um dois três quatro cinco meia sete oito~1234-5678 -um dois três quatro cinco meia sete oito telefone~1234-5678 telefone -um dois três quatro cinco seis sete oito nove~12345-6789 -um dois três quatro cinco seis sete oito nove telefone~12345-6789 telefone -quatro cinco um dois três quatro cinco seis sete oito~(45) 1234-5678 -quatro cinco um dois três quatro cinco seis sete oito telefone~(45) 1234-5678 telefone -quatro cinco um dois três quatro cinco seis sete oito nove~(45) 12345-6789 -quatro cinco um dois três quatro cinco seis sete oito nove telefone~(45) 12345-6789 telefone -vinte e sete vinte e oito trinta e sete trinta e oito~2728-3738 -vinte e sete vinte e oito trinta e sete trinta e oito telefone~2728-3738 telefone -um vinte e sete vinte e oito trinta e sete trinta e oito~12728-3738 -um vinte e sete vinte e oito trinta e sete trinta e oito telefone~12728-3738 telefone -nove oito sete seis cinquenta e quatro zero zero~9876-5400 -nove oito sete seis cinquenta e quatro zero um~9876-5401 -noventa e oito setenta e seis zero zero trinta e cinco~9876-0035 -noventa e oito setenta e seis zero zero trinta~9876-0030 -nove noventa e oito setenta e seis zero zero trinta e um~99876-0031 -nove noventa e oito setenta e seis zero zero trinta~99876-0030 -dois três nove noventa e oito setenta e seis zero zero trinta e um~(23) 99876-0031 -dois três nove noventa e oito setenta e seis zero zero trinta~(23) 99876-0030 -vinte e três nove noventa e oito setenta e seis zero zero trinta e um~(23) 99876-0031 -vinte e três nove noventa e oito setenta e seis zero zero trinta~(23) 99876-0030 -vinte e três nove noventa e oito setenta e seis zero meia trinta e um~(23) 99876-0631 -vinte e três nove noventa e oito setenta e seis zero meia trinta~(23) 99876-0630 -vinte três nove noventa e oito setenta e seis zero meia trinta~(23) 99876-0630 \ No newline at end of file diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_time.txt deleted file mode 100755 index 7aef50d2d489..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,19 +0,0 @@ -às quinze pro meio dia~às 11:45 -às quinze pra meia noite~às 23:45 -às quinze para a meia noite~às 23:45 -às quinze pras duas da tarde~às 1:45 da tarde -às dez pras duas da madrugada~às 1:50 da madrugada -às quinze pras duas da tarde~às 1:45 da tarde -chegaram às quinze pras duas da tarde~chegaram às 1:45 da tarde -ao meio dia~ao meio dia -ao meio dia e meia hora~ao 12:30 -ao meio dia e meia~ao 12:30 -ao meio dia e meio~ao 12:30 -meia noite~meia noite -à meia noite~à meia noite -à meia noite e quinze~à 0:15 -meia noite e meia~0:30 -à uma e trinta~à 1:30 -às onze e trinta~às 11:30 -às três horas e trinta minutos~às 3:30 -às quinze horas e quarenta minutos~às 15:40 diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_whitelist.txt deleted file mode 100755 index 798df8b9bdfd..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,6 +0,0 @@ -primeira segunda feira~primeira segunda-feira -primeira segunda-feira~primeira segunda-feira -terça feira~terça-feira -quarta feira~quarta-feira -quinta feira~quinta-feira -sexta feira~sexta-feira \ No newline at end of file diff --git a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_word.txt deleted file mode 100755 index fdd32f2ea4f2..000000000000 --- a/tests/nemo_text_processing/pt/data_inverse_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,49 +0,0 @@ -~ -yahoo!~yahoo! -vinte!~20 ! -x ~x -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/pt/test_cardinal.py b/tests/nemo_text_processing/pt/test_cardinal.py deleted file mode 100644 index 9a16a6b3477d..000000000000 --- a/tests/nemo_text_processing/pt/test_cardinal.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestCardinal: - - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_date.py b/tests/nemo_text_processing/pt/test_date.py deleted file mode 100644 index e7783819585c..000000000000 --- a/tests/nemo_text_processing/pt/test_date.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDate: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_decimal.py b/tests/nemo_text_processing/pt/test_decimal.py deleted file mode 100644 index 48daab819a38..000000000000 --- a/tests/nemo_text_processing/pt/test_decimal.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDecimal: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_electronic.py b/tests/nemo_text_processing/pt/test_electronic.py deleted file mode 100644 index cce372cffded..000000000000 --- a/tests/nemo_text_processing/pt/test_electronic.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestElectronic: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_measure.py b/tests/nemo_text_processing/pt/test_measure.py deleted file mode 100644 index b56fca76de6a..000000000000 --- a/tests/nemo_text_processing/pt/test_measure.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMeasure: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_money.py b/tests/nemo_text_processing/pt/test_money.py deleted file mode 100644 index 0d372f0f55e6..000000000000 --- a/tests/nemo_text_processing/pt/test_money.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMoney: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_ordinal.py b/tests/nemo_text_processing/pt/test_ordinal.py deleted file mode 100644 index 2ef6a89c87e3..000000000000 --- a/tests/nemo_text_processing/pt/test_ordinal.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestOrdinal: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_sparrowhawk_inverse_text_normalization.sh b/tests/nemo_text_processing/pt/test_sparrowhawk_inverse_text_normalization.sh deleted file mode 100755 index 74d8ddafdfc6..000000000000 --- a/tests/nemo_text_processing/pt/test_sparrowhawk_inverse_text_normalization.sh +++ /dev/null @@ -1,84 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1) - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$spoken" "$written" "$denorm_pred" - done < "$input" -} - -testITNCardinal() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testITNDate() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_date.txt - runtest $input -} - -testITNDecimal() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_decimal.txt - runtest $input -} - -testITNOrdinal() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_ordinal.txt - runtest $input -} - -#testITNFraction() { -# input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_fraction.txt -# runtest $input -#} - -testITNTime() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_time.txt - runtest $input -} - -testITNMeasure() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_measure.txt - runtest $input -} - -testITNMoney() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_money.txt - runtest $input -} - -testITNWhitelist() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testITNTelephone() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_telephone.txt - runtest $input -} - -testITNElectronic() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_electronic.txt - runtest $input -} - -testITNWord() { - input=$PROJECT_DIR/pt/data_inverse_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/pt/test_telephone.py b/tests/nemo_text_processing/pt/test_telephone.py deleted file mode 100644 index a2fecad525fe..000000000000 --- a/tests/nemo_text_processing/pt/test_telephone.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTelephone: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_time.py b/tests/nemo_text_processing/pt/test_time.py deleted file mode 100644 index 87f5bb2867a0..000000000000 --- a/tests/nemo_text_processing/pt/test_time.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTime: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_whitelist.py b/tests/nemo_text_processing/pt/test_whitelist.py deleted file mode 100644 index 978556c83a39..000000000000 --- a/tests/nemo_text_processing/pt/test_whitelist.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWhitelist: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/pt/test_word.py b/tests/nemo_text_processing/pt/test_word.py deleted file mode 100644 index b3ed35b32b52..000000000000 --- a/tests/nemo_text_processing/pt/test_word.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWord: - inverse_normalizer = ( - InverseNormalizer(lang='pt', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('pt/data_inverse_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/ru/__init__.py b/tests/nemo_text_processing/ru/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/tests/nemo_text_processing/ru/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index 015ece7d1dea..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,30 +0,0 @@ -двести пятьдесят четыре~254 -сто сорок семь тысяч четыреста пятьдесят один~147451 -один миллион сто пятьдесят шесть тысяч сто семьдесят три~1156173 -один миллиард пятьсот девяносто три миллиона семьдесят две тысячи девятьсот шестьдесят один~1593072961 -минус двадцать пять тысяч тридцать семь~-25037 -минус шестьдесят~-60 -сорок шесть тысяч шестьсот шестьдесят четыре~46664 -шестьдесят~60 -ноль~ноль -я одна~я одна -девять~девять -два миллиона три~2000003 -одна тысяча тринадцать~1013 -одна тысяча один~1001 -одна тысяча сто~1100 -одна тысяча двадцать шесть~1026 -одна тысяча сто двадцать шесть~1126 -тысяча тринадцать~1013 -тысяча один~1001 -тысяча сто~1100 -тысяча двадцать шесть~1026 -тысяча сто двадцать шесть~1126 -одна тысяча~1000 -тысяча~1000 -восемнадцать миллионов четыреста пятьдесят тысяч девятьсот девяносто~18450990 -восемнадцать миллионов девятьсот сорок тысяч семьсот двадцать два~18940722 -восемнадцать миллионов шестьсот девяносто тысяч девятьсот шестнадцать~18690916 -восемнадцать тысяч восемьсот восемьдесят~18880 -два миллиона~2000000 -одна тысяча~1000 diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_date.txt deleted file mode 100644 index 5bca2e0b6da1..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,15 +0,0 @@ -двенадцатое декабря две тысячи шестого~12.12.2006 -первого января восемьдесят шестого~01.01.86 -второе марта тысяча девятьсот шестого~02.03.1906 -шестое марта тысяча шестого года~06.03.1006г. -двадцать третьего октября две тысячи второго~23.10.2002 -восемнадцатое мая~18.05 -ноль второго мая две тысячи девятого~02.05.2009 -ноль второго пятого две тысячи девятого года~02.05.2009г. -ноль второго ноль первого~02.01 -тридцать первого января ноль шестого~31.01.06 -в двухтысячных годах~в 2000гг. -в две тысячи девятом~в 2009 -первый день марта~первый день марта -двадцатого июня~20.06 -первое февраля~01.02 \ No newline at end of file diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 29035aec84a5..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,16 +0,0 @@ -ноль целых и одна десятая~0,1 -ноль целых и семьсот двадцать девять тысячных~0,729 -одной целой и трех десятых~1,3 -одна целая и две десятых~1,2 -три целых и две сотых~3,02 -ноль целых и три тысячных~0,003 -одна целая и две десятитысячных~1,0002 -ноль целых и семьсот двадцать четыре тысячных~0,724 -триста целых и две сотых~300,02 -ноль целых и девять десятых~0,9 -две целых три десятых~2,3 -две целых три сотых~2,03 -две целых три тысячных~2,003 -две целых три десятитысячных~2,0003 -минус две целых пять десятых~-2,5 -одна целая двадцать три сотых миллиарда~1,23 млрд \ No newline at end of file diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_electronic.txt deleted file mode 100644 index 45c0c28e8cd1..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,4 +0,0 @@ -эй точка би си собака джи мейл точка ком~a.bc@gmail.com -эй собака хот мейл точка ди и~a@hotmail.de -эй один два три тире ви собака эй би си точка ком~a123-v@abc.com -адрес эй дефис один точка би три нижнее подчеркивание си амперсанд тире ди собака джи эм эй четыре ай тире эл точка ком тест~адрес a-1.b3_c&-d@gma4i-l.com тест diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_measure.txt deleted file mode 100644 index fb11e21b7330..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,16 +0,0 @@ -двенадцать килограм~12 кг -одного килограма~1 кг -три целых две десятых литра~3,2 л -три целых две десятых миллиона литров~3,2 млн л -три километра в час~3 км/ч -двадцати килограммовый мешок~20 килограммовый мешок -четыре целых пять десятых килограммовый мешок~4,5 килограммовый мешок -тест одна целая две сотых~тест 1,02 -тест восемнадцать~тест 18 -пятнадцать рублей за квадратный метр~15 pуб./м² -пятнадцать за килограм~15/кг -пять градусов~5 ° -пять градусов фаренгейта~5 °F -пять градусов цельсия~5 °C -пять градусов по цельсию~5 °C -пять градусов по фаренгейту~5 °F diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_money.txt deleted file mode 100644 index 913b437f9497..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,9 +0,0 @@ -один доллар~1 USD -один рубль~1 руб. -тридцать одного рубля~31 руб. -восемнадцать тысяч долларов сэ ш а~18000 долл. США -два рубля~2 руб. -две целых и пять десятых тысячи рублей~2,5 тыс руб. -две целых и три сотых рублей~2,03 руб. -шесть рублей тридцать пять копеек~6 руб. 35 коп. -одна целая двадцать три сотых миллиарда рублей~1,23 млрд руб. diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index e8e9b8892f80..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,15 +0,0 @@ -одна тысяча девятьсот девяносто шестого~1996 -тысяча девятьсот девяносто девятый~1999 -тысяча восемьсот шестьдесят третьего~1863 -тысяча девятьсот семьдесят четвертом~1974 -двадцать четвертого~24 -двадцать восьмой~28 -девятнадцатый~19 -десятый~10 -тысяча восемьсот пятьдесят третьего~1853 -две тысячи двенадцатый~2012 -тысяча пятьсот тридцать шестом~1536 -два миллиона пятитысячный~2005000 -двадцать первые~21 -двухтысячные~2000 -я в первый раз~я в первый раз \ No newline at end of file diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_ordinal_hard.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_ordinal_hard.txt deleted file mode 100644 index 6d62e345fdd5..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_ordinal_hard.txt +++ /dev/null @@ -1,57 +0,0 @@ -тысяча девятьсот пятидесятые~1950-е -восьмого~8-го -двадцатого~20-го -тысяча девятьсот девяностые~1990-е -третьих~3-х -тысяча девятьсот шестидесятых~1960-х -шестой~6-й -вторая~2-ая -пятьдесят шестого~56-го -тысяча девятьсот двадцатых~1920-х -второй~2-й -третье~3-е -двадцать вторая~22-я -тысяча восемьсот шестидесятых~1860-х -тысяча восемьсот семидесятых~1870-х -двести девяносто первый~291-й -пятый~5-й -шестой~6-й -первого~1-го -пятые~5-е -вторые~2-е -пятьдесят первая~51-я -одиннадцатый~11-й -первый~1-й -сорок шестая~46-я -второй~2-й -восемьдесят четвертом~84-м -тысяча девятьсот шестидесятые~1960-е -первые~1-е -пятьдесят шестой~56-й -тринадцатый~13-й -девятого~9-го -второго~2-го -первый~1-й -четвертом~4-м -втором~2-м -двадцатых~20-х -тысяча восемьсот сороковые~1840-е -пятая~5-я -тысяча девятьсот тридцатом~1930-м -тридцать восьмая~38-я -тридцатых~30-х -первого~1-го -второго~2-го -второго~2-го -семидесятая~70-я -тысяча девятьсот двадцатых~1920-х -шестнадцатый~16-й -двенадцатом~12 -четырнадцатом~14 -двух тысячных~2000-х -вторые~2-е -тысяча восемьсот девяностых~1890-х -вторые~2-е -двадцать седьмой~27-й -пятом~5-м -шестью семь это сорок два~6-ю 7 это 42 diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_telephone.txt deleted file mode 100644 index 676e8e260df5..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1 +0,0 @@ -восемь девятьсот тринадцать девятьсот восемьдесят три пятьдесят шесть ноль один~8-913-983-56-01 diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_time.txt deleted file mode 100644 index 2a9fd32f7d9e..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,9 +0,0 @@ -тринадцать часов пять минут~13:05 -тринадцать часов и пять минут~13:05 -два часа и три минуты~02:03 -один час ноль минут~01:00 -два часа~02:00 -без пятнадцати минут шесть~05:45 -без одной минуты десять~09:59 -двенадцать часов~12:00 -семь минут девятого~08:07 diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 9b2fc93c7cad..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,4 +0,0 @@ -двух комнатная квартира~двух комн. кв. -жилой комплекс Принцип~ЖК Принцип -Высокий градус нашей дискуссии.~Высокий градус нашей дискуссии. -мяч был в нескольких метрах от нас~мяч был в нескольких метрах от нас diff --git a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_word.txt deleted file mode 100644 index 3defc0486bbc..000000000000 --- a/tests/nemo_text_processing/ru/data_inverse_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,50 +0,0 @@ -~ -yahoo!~yahoo! -двадцать!~20 ! -два би тридцать пять~два би 35 -x ~x -—~— -aaa~aaa -aabach~aabach -aabenraa~aabenraa -aabye~aabye -aaccessed~aaccessed -aach~aach -aachen's~aachen's -aadri~aadri -aafia~aafia -aagaard~aagaard -aagadu~aagadu -aagard~aagard -aagathadi~aagathadi -aaghart's~aaghart's -aagnes~aagnes -aagomoni~aagomoni -aagon~aagon -aagoo~aagoo -aagot~aagot -aahar~aahar -aahh~aahh -aahperd~aahperd -aaibinterstate~aaibinterstate -aajab~aajab -aakasa~aakasa -aakervik~aakervik -aakirkeby~aakirkeby -aalam~aalam -aalbaek~aalbaek -aaldiu~aaldiu -aalem~aalem -a'ali~a'ali -aalilaassamthey~aalilaassamthey -aalin~aalin -aaliyan~aaliyan -aaliyan's~aaliyan's -aamadu~aamadu -aamara~aamara -aambala~aambala -aamera~aamera -aamer's~aamer's -aamina~aamina -aaminah~aaminah -aamjiwnaang~aamjiwnaang diff --git a/tests/nemo_text_processing/ru/data_text_normalization/__init__.py b/tests/nemo_text_processing/ru/data_text_normalization/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index 1850e07d3478..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,28 +0,0 @@ -три~03 -минус пятьдесят~-50 -минус пятьдесят~-050 -двести пятьдесят четыре~254 -две тысячи триста~2 300 -минус две тысячи триста~-2 300 -две тысячи триста~002300 -две тысячи триста~2.300 -шестьдесят~60 -ноль~0 -два миллиона три~2000003 -одна тысяча тринадцать~1013 -одна тысяча сто~1100 -тысяча сто~1100 -одна тысяча двадцать шесть~1026 -тысяча двадцать шесть~1026 -одна тысяча сто двадцать шесть~1126 -тысяча тринадцать~1013 -тысяча один~1001 -одна тысяча один~1001 -одна тысяча~1000 -тысяча~1000 -одна тысяча~1000 -две тысячи пять~2 005 -два б три четыре~2-б-34 -два би три~2-b-3 -тест два~тест2 -тридцать код~30код diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_cardinal_normalize_with_audio.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_cardinal_normalize_with_audio.txt deleted file mode 100644 index e2149b3fd101..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_cardinal_normalize_with_audio.txt +++ /dev/null @@ -1,51 +0,0 @@ -~03 -три -~-50 -минус пятьдесят -~-050 -минус пятьдесят -~254 -двести пятьдесят четыре -~147691 -сто сорок семь тысяч шестьсот девяносто один -~1156173 -один миллион сто пятьдесят шесть тысяч сто семьдесят три -~1593072961 -один миллиард пятьсот девяносто три миллиона семьдесят две тысячи девятьсот шестьдесят один -~46664 -сорое шесть тысяч шестьсот шестьдесят четыре -сорое шесть тысяч шестьсот шестьдесят четырый -~60 -шестьдесят -шестидесятый -~0 -ноль -~2000003 -два миллиона три -~1013 -одна тысяча тринадцать -~1001 -одна тысяча один -~1100 -одна тысяча сто -тысяча сто -~1026 -одна тысяча двадцать шесть -тысяча двадцать шесть -~1126 -одна тысяча сто двадцать шесть -~1013 -тысяча тринадцать -~1001 -тысяча один -~1000 -одна тысяча -тысяча -~18450990 -восемнадцать миллионов четыреста пятьдесят тысяч девятьсот девяносто -~18940722 -восемнадцать миллионов девятьсот сорок тысяч семьсот двадцать два -~18690916 -восемнадцать миллионов шестьсот девяносто тысяч девятьсот шестнадцать -~18880 -восемнадцать тысяч восемьсот восемьдесят \ No newline at end of file diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_date.txt deleted file mode 100644 index 40869e8bc4ab..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,6 +0,0 @@ -шестое марта две тысячи шестого~06.03.2006 -первого января восемьдесят шестого~01-01-86 -второе марта тысяча девятьсот шестого~2/3/1906 -шестое марта тысяча шестого года~6/3/1006г. -третьего февраля две тысячи второго~03-фев-2002 -тридцать первого января ноль шестого~31.01.06 diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 771475b0716e..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,17 +0,0 @@ -ноль целых одна десятая~0,1 -ноль целых семьсот двадцать девять тысячных~0,729 -одними целых три десятых~1,3 -одна целая две десятых~1,2 -три целых две сотых~3,02 -ноль целых три тысячных~0,003 -одна целая две десятитысячных~1,0002 -ноль целых семьсот двадцать четыре тысячных~0,724 -триста целых две сотых~300,02 -ноль целых девять десятых~0,9 -две целых три десятых~2,3 -две целых три сотых~2,03 -две целых три тысячных~2,003 -две целых три десятитысячных~2,0003 -минус две целых пять десятых~-2,5 -одна целая двадцать три сотых миллиарда~1,23млрд -одна целая двадцать три сотых миллиарда~1,23 млрд. diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_electronic.txt deleted file mode 100644 index 45c0c28e8cd1..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,4 +0,0 @@ -эй точка би си собака джи мейл точка ком~a.bc@gmail.com -эй собака хот мейл точка ди и~a@hotmail.de -эй один два три тире ви собака эй би си точка ком~a123-v@abc.com -адрес эй дефис один точка би три нижнее подчеркивание си амперсанд тире ди собака джи эм эй четыре ай тире эл точка ком тест~адрес a-1.b3_c&-d@gma4i-l.com тест diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_measure.txt deleted file mode 100644 index 7f646995924e..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,13 +0,0 @@ -двенадцать килограм~12 кг -двенадцать килограм~12кг -три целых две десятых литра~3,2 л -три целых две десятых миллиона литров~3,2 млн л -три километра в час~3 км/ч -четырех килограммовый мешок~4-х килограммовый мешок -девять мешок~9мешок -четыре целых два десятых килограммовый мешок~4,2-килограммовый мешок -тест одна целая две сотых~тест-1,02 -тест восемь~тест-8 -четыре килограма в килограме~4 кг/кг -один в килограме~1/кг -один квадратный метр~один м² diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_money.txt deleted file mode 100644 index 65fe14698829..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,9 +0,0 @@ -один доллар~1 USD -один рубль~1 руб. -тридцать одного рубля~31 руб. -восемнадцать тысяч долларов сэ ш а~18000 долл. США -два рубля~2 руб. -две целых пять десятых тысячи рублей~2,5 тыс руб. -две целых три сотых рублей~2,03 руб. -шесть рублей тридцать пять копеек~6 руб. 35 коп. -одна целая двадцать три сотых миллиарда рублей~1,23 млрд руб. diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index 1c4b9f2c409b..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,75 +0,0 @@ -тысяча девятьсот пятидесятые~1950-е -восьмого~8-го -двадцатого~20-го -тысяча девятьсот девяносто шестого~1996 -тысяча девятьсот девяносто девятый~1999 -тысяча девятьсот девяностые~1990-е -тысяча восемьсот шестьдесят третьего~1863 -третьих~3-х -тысяча девятьсот семьдесят четвертом~1974 -тысяча девятьсот шестидесятых~1960-х -шестой~6-й -вторая~2-ая -пятьдесят шестого~56-го -двадцать четвертого~24 -двадцать восьмой~28 -тысяча восемьсот пятьдесят третьего~1853 -две тысячи двенадцатый~2012 -тысяча восемьсот девяностом~1890 -тысяча девятьсот двадцатых~1920-х -тысяча девятьсот пятидесятом~1950 -второй~2-й -третье~3-е -двадцать вторая~22-я -тысяча восемьсот шестидесятых~1860-х -тысяча восемьсот семидесятых~1870-х -двести девяносто первый~291-й -пятый~5-й -шестой~6-й -первого~1-го -пятые~5-е -вторые~2-е -пятьдесят первая~51-я -одиннадцатый~11-й -первый~1-й -сорок шестая~46-я -второй~2-й -восемьдесят четвертом~84-м -второй~2-й -тысяча девятьсот шестидесятые~1960-е -тысяча семьсот восемьдесят первом~1781 -тысяча девятьсот сорок пятом~1945 -первые~1-е -тысяча девятьсот девятом~1909 -пятьдесят шестой~56-й -тринадцатый~13-й -тысяча девятьсот тридцать первого~1931 -тысяча девятьсот тридцать седьмой~1937 -девятого~9-го -второго~2-го -первый~1-й -четвертом~4-м -втором~2-м -тысяча пятьсот тридцать шестом~1536 -двадцатых~20-х -тысяча восемьсот сороковые~1840-е -пятая~5-я -тысяча девятьсот тридцатом~1930-м -две тысячи третьем~2003 -тридцать восьмая~38-я -тридцатых~30-х -семьсот сороковом~740 -первого~1-го -второго~2-го -второго~2-го -семидесятая~70-я -тысяча девятьсот двадцатых~1920-х -шестнадцатый~16-й -двенадцатом~12 -четырнадцатом~14 -двухтысячных~2000-х -вторые~2-е -тысяча восемьсот девяностых~1890-х -вторые~2-е -двадцать седьмой~27-й -пятом~5-м diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_telephone.txt deleted file mode 100644 index 676e8e260df5..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1 +0,0 @@ -восемь девятьсот тринадцать девятьсот восемьдесят три пятьдесят шесть ноль один~8-913-983-56-01 diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_time.txt deleted file mode 100644 index 2a9fd32f7d9e..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,9 +0,0 @@ -тринадцать часов пять минут~13:05 -тринадцать часов и пять минут~13:05 -два часа и три минуты~02:03 -один час ноль минут~01:00 -два часа~02:00 -без пятнадцати минут шесть~05:45 -без одной минуты десять~09:59 -двенадцать часов~12:00 -семь минут девятого~08:07 diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 18d573037863..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1,4 +0,0 @@ -квадратный метр~м² -градус~° -процент~% -эй би си~abc diff --git a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/ru/data_text_normalization/test_cases_word.txt deleted file mode 100644 index ec47add35a07..000000000000 --- a/tests/nemo_text_processing/ru/data_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,3 +0,0 @@ -~ -тест тест одна целая пять десятых в два часа~тест тест 1,5 в 2 часа -текст, и знаки препинания!~текст, и знаки препинания! diff --git a/tests/nemo_text_processing/ru/test_ru_inverse_normalization.py b/tests/nemo_text_processing/ru/test_ru_inverse_normalization.py deleted file mode 100644 index 779e236230f9..000000000000 --- a/tests/nemo_text_processing/ru/test_ru_inverse_normalization.py +++ /dev/null @@ -1,147 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestRuInverseNormalize: - - normalizer = InverseNormalizer(lang='ru', cache_dir=CACHE_DIR) if PYNINI_AVAILABLE else None - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_cardinal(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_ordinal(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - # @parameterized.expand(parse_test_case_file('ru_data_inverse_text_normalization/test_cases_ordinal_hard.txt')) - # @pytest.mark.run_only_on('CPU') - # @pytest.mark.unit - # def test_denorm_ordinal_hard(self, test_input, expected): - # pred = self.normalizer.inverse_normalize(test_input, verbose=False) - # assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_decimal(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_electronic(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_date(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_measure(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_money(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_time(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_whitelist(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred - - @parameterized.expand(parse_test_case_file('ru/data_inverse_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm_word(self, test_input, expected): - pred = self.normalizer.inverse_normalize(test_input, verbose=False) - assert expected == pred diff --git a/tests/nemo_text_processing/ru/test_ru_normalization.py b/tests/nemo_text_processing/ru/test_ru_normalization.py deleted file mode 100644 index 9ec3e78894c2..000000000000 --- a/tests/nemo_text_processing/ru/test_ru_normalization.py +++ /dev/null @@ -1,152 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestRuNormalizeWithAudio: - - normalizer = NormalizerWithAudio(input_case='cased', lang='ru', cache_dir=CACHE_DIR) if PYNINI_AVAILABLE else None - N_TAGGED = 100 - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_cardinal(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=50) - assert expected in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_ordinal(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_decimal(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_measure(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_date(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds, expected not in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_telephone(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds, expected not in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_money(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds, expected not in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_time(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds, expected not in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_electronic(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_whitelist(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds - - @parameterized.expand(parse_test_case_file('ru/data_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_word(self, expected, test_input): - preds = self.normalizer.normalize(test_input, n_tagged=self.N_TAGGED) - assert expected in preds diff --git a/tests/nemo_text_processing/ru/test_sparrowhawk_inverse_text_normalization.sh b/tests/nemo_text_processing/ru/test_sparrowhawk_inverse_text_normalization.sh deleted file mode 100644 index 1c975e07071e..000000000000 --- a/tests/nemo_text_processing/ru/test_sparrowhawk_inverse_text_normalization.sh +++ /dev/null @@ -1,79 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1) - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$spoken" "$written" "$denorm_pred" - done < "$input" -} - -testITNCardinal() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testITNOrdinal() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testITNDate() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_date.txt - runtest $input -} - -testITNDecimal() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_decimal.txt - runtest $input -} - -testITNElectronic() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_electronic.txt - runtest $input -} - -testITNTime() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_time.txt - runtest $input -} - -testITNMeasure() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_measure.txt - runtest $input -} - -testITNMoney() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_money.txt - runtest $input -} - -testITNWhitelist() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_whitelist.txt - runtest $input -} - -testITNTelephone() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_telephone.txt - runtest $input -} - -testITNWord() { - input=$PROJECT_DIR/ru/data_inverse_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/utils.py b/tests/nemo_text_processing/utils.py deleted file mode 100644 index df306c38200b..000000000000 --- a/tests/nemo_text_processing/utils.py +++ /dev/null @@ -1,66 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -CACHE_DIR = None -RUN_AUDIO_BASED_TESTS = False - - -def set_cache_dir(path: str = None): - """ - Sets cache directory for TN/ITN unittests. Default is None, e.g. no cache during tests. - """ - global CACHE_DIR - CACHE_DIR = path - - -def set_audio_based_tests(run_audio_based: bool = False): - """ - Sets audio-based test mode for TN/ITN unittests. Default is False, e.g. audio-based tests will be skipped. - """ - global RUN_AUDIO_BASED_TESTS - RUN_AUDIO_BASED_TESTS = run_audio_based - - -def parse_test_case_file(file_name: str): - """ - Prepares tests pairs for ITN and TN tests - """ - test_pairs = [] - with open(os.path.dirname(os.path.abspath(__file__)) + os.path.sep + file_name, 'r') as f: - for line in f: - spoken, written = line.split('~') - test_pairs.append((spoken, written.strip("\n"))) - return test_pairs - - -def get_test_cases_multiple(file_name: str = 'data_text_normalization/en/test_cases_normalize_with_audio.txt'): - """ - Prepares tests pairs for audio based TN tests - """ - test_pairs = [] - with open(os.path.dirname(os.path.abspath(__file__)) + os.path.sep + file_name, 'r') as f: - written = None - normalized_options = [] - for line in f: - if line.startswith('~'): - if written: - test_pairs.append((written, normalized_options)) - normalized_options = [] - written = line.strip().replace('~', '') - else: - normalized_options.append(line.strip()) - test_pairs.append((written, normalized_options)) - return test_pairs diff --git a/tests/nemo_text_processing/vi/__init__.py b/tests/nemo_text_processing/vi/__init__.py deleted file mode 100644 index bc443be41c4c..000000000000 --- a/tests/nemo_text_processing/vi/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_cardinal.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_cardinal.txt deleted file mode 100644 index 53853297c9b6..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_cardinal.txt +++ /dev/null @@ -1,93 +0,0 @@ -một trăm~100 -mười tám~18 -hai mốt~21 -hai mươi mốt~21 -ba mươi mốt~31 -ba mốt~31 -bốn ba~43 -bốn mươi tư~44 -năm lăm~55 -năm mươi bốn~54 -sáu bảy~67 -sáu mươi bẩy~67 -bẩy mươi~70 -bảy hai~72 -tám mươi~80 -chín mươi lăm~95 -một trăm linh hai~102 -một trăm lẻ tư~104 -một trăm hai mươi~120 -một trăm hai~120 -hai trăm~200 -hai trăm linh một~201 -một trăm mười một~111 -một trăm mốt~110 -một nghìn~1000 -một ngàn~1000 -năm trăm tư~540 -tám trăm rưỡi~850 -một nghìn hai mươi~1020 -một ngàn chín lăm~1095 -chín tỷ bảy trăm tám chín triệu ba trăm tám mươi hai ngàn năm trăm ba mươi lăm~9789382535 -tám tỉ chín trăm triệu~8900000000 -một trăm bốn bảy nghìn bốn trăm năm mốt~147451 -một trăm bốn mươi bảy nghìn bốn trăm năm mươi mốt~147451 -một triệu không trăm năm mươi sáu ngàn một trăm bảy mươi ba~1056173 -mười một triệu không trăm năm sáu nghìn một trăm bẩy ba~11056173 -một tỉ năm trăm chín ba triệu không trăm bảy mươi hai nghìn chín trăm sáu mốt~1593072961 -một trăm tỉ năm trăm chín ba triệu không trăm bảy mươi hai nghìn chín trăm sáu mốt~100593072961 -chín trăm năm mươi tỉ năm trăm chín ba triệu không trăm bảy mươi hai nghìn chín trăm sáu mốt~950593072961 -một trăm tỷ một trăm mười~100000000110 -một tỉ một triệu một trăm~1001000100 -âm hai mươi lăm nghìn ba bảy~-25037 -trừ hai lăm ngàn không trăm ba mươi bẩy~-25037 -trừ một nghìn chín trăm ba bảy~-1937 -âm một ngàn chín~-1900 -âm sáu mươi~-60 -trừ sáu mươi~-60 -âm một triệu không trăm linh một~-1000001 -không~không -một~một -hai~hai -lăm~lăm -mốt~mốt -tư~tư -mười~10 -mười một~11 -mười hai~12 -mười ba~13 -mười bốn~14 -mười lăm~15 -mười sáu~16 -mười bẩy~17 -mười bảy~17 -mười tám~18 -hai mươi~20 -ba mươi~30 -bốn mươi~40 -năm mươi~50 -sáu mươi~60 -bảy mươi~70 -bẩy mươi~70 -tám mươi~80 -chín mươi~90 -hai triệu mười~2000010 -một ngàn mười ba~1013 -một nghìn mười ba~1013 -một nghìn lẻ một~1001 -một ngàn linh một~1001 -một ngàn mốt~1100 -năm ngàn rưỡi~5500 -một nghìn hai sáu~1026 -một ngàn một trăm hai sáu~1126 -ba nghìn năm~3000 năm -bẩy ngàn năm~7000 năm -sáu triệu năm~6 triệu năm -năm năm~năm năm -ba năm~ba năm -tám nghìn mốt~8100 -một trăm một~100 một -một trăm linh một~101 -một trăm mốt~110 -một trăm mười~110 -hai triệu ba nghìn~2003000 \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_date.txt deleted file mode 100644 index 182c710e25b3..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,16 +0,0 @@ -hai tư tháng bảy năm hai nghìn mười ba~24 tháng 7 năm 2013 -ngày hai mươi tư tháng bẩy năm hai không mười ba~ngày 24 tháng 7 năm 2013 -mùng một tháng một năm một chín chín chín~mùng 1 tháng 1 năm 1999 -ngày ba mươi tháng tư~ngày 30 tháng 4 -hai mươi tư tháng bảy~24 tháng 7 -ngày ba mươi tháng sáu~ngày 30 tháng 6 -tháng mười hai~tháng 12 -tháng năm~tháng năm -tháng chín~tháng 9 -tháng mười năm hai ngàn linh chín~tháng 10 năm 2009 -năm một tám năm hai~năm 1852 -năm chín trăm ba tám~năm 938 -năm ba trăm lẻ tám~năm 308 -năm bẩy trăm bốn mươi tư~năm 744 -học kỳ này sẽ kết thúc vào tháng tư ngày mười tháng năm là tổng kết~học kỳ này sẽ kết thúc vào tháng 4 ngày 10 tháng 5 là tổng kết -học kỳ này sẽ kết thúc vào tháng năm ngày một tháng sáu là tổng kết~học kỳ này sẽ kết thúc vào tháng năm ngày 1 tháng 6 là tổng kết \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_decimal.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_decimal.txt deleted file mode 100644 index 9888ff64e4e0..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_decimal.txt +++ /dev/null @@ -1,25 +0,0 @@ -không phẩy hai triệu~0.2 triệu -một triệu hai~1.2 triệu -mười tám vạn~18 vạn -bốn trăm sáu mươi triệu~460 triệu -bốn trăm sáu triệu~460 triệu -bốn triệu sáu~4.6 triệu -một trăm hai mươi tỉ~120 tỉ -một trăm hai mươi tỷ~120 tỷ -mười vạn~10 vạn -sáu mươi phẩy hai bốn không~60.240 -sáu mươi chấm hai tư~60.24 -tám trăm mười tám chấm ba không ba~818.303 -tám trăm mười tám phẩy ba không ba~818.303 -không phẩy năm~0.5 -không chấm năm~0.5 -mười triệu rưỡi~10.5 triệu -mười triệu năm~10 triệu năm -mười triệu mốt~10.1 triệu -mười triệu tư~10.4 triệu -chín chín tỷ chín~99.9 tỷ -trừ chín chín tỷ chín~-99.9 tỷ -âm chín chín chấm chín lăm tỷ~-99.95 tỷ -hai mươi chấm tư~20.4 -mười hai chấm mốt~12 chấm mốt -chín trăm chín ba chấm lăm~993 chấm lăm \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_electronic.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_electronic.txt deleted file mode 100644 index 04168797eba0..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_electronic.txt +++ /dev/null @@ -1,10 +0,0 @@ -a chấm b c a còng g mail chấm com~a.bc@gmail.com -a chấm b c a móc g mail chấm com~a.bc@gmail.com -c d f a móc a b c chấm e d u~cdf@abc.edu -a b c a móc g mail chấm a b c~abc@gmail.abc -a b c a vòng g mail chấm a b c~abc@gmail.abc -a b c a móc a b c chấm com~abc@abc.com -a s d f một hai ba a móc a b c chấm com~asdf123@abc.com -a một b hai a vòng a b c chấm com~a1b2@abc.com -a b ba chấm s d d chấm ba a móc g mail chấm com~ab3.sdd.3@gmail.com -a b ba chấm s d d chấm ba a còng g mail chấm com~ab3.sdd.3@gmail.com \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_fraction.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_fraction.txt deleted file mode 100644 index 3249d734f497..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_fraction.txt +++ /dev/null @@ -1,14 +0,0 @@ -một trên hai~1/2 -hai trên mười lăm~2/15 -bốn lăm phần hai trăm mốt~45/210 -hai ba chia mười hai~23/12 -một chia bẩy~1/7 -một chia tám~1/8 -ba mươi phần một trăm~30/100 -hai phần ba~2/3 -chín phần chín~9/9 -một phần mười~1/10 -trừ năm phần mười hai~-5/12 -âm ba trên bốn~-3/4 -trừ ba mươi phần một trăm~-30/100 -âm tám phần ba~-8/3 \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_measure.txt deleted file mode 100644 index 8b8c97b96de5..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,22 +0,0 @@ -hai trăm mét~200 m -hai trăm lẻ tư mét~204 m -năm mươi sáu phẩy ba ki lô mét vuông~56.3 km² -hai trăm ki lô mét trên giờ~200 km/h -hai trăm kilomet trên giờ~200 km/h -năm xăng ti mét trên giây~5 cm/s -bốn mươi hai nghìn hai trăm năm chín mét vuông~42259 m² -trừ sáu sáu kí~-66 kg -một triệu không trăm hai tám xen ti mét khối~1000028 cm³ -năm mươi kí lô~50 kg -hai mét khối~2 m³ -chín mươi gram~90 g -bốn trăm bốn mươi mi li lít~440 ml -ba trăm muy crô mét~300 μm -sáu lăm inch~65 inch -hai vôn~2 v -ba mươi phần trăm~30 % -sáu mươi nghìn hai trăm bốn mươi mi li ampe~60240 mA -sáu mươi sáu phút~66 phút -hai phút~2 phút -năm giây~5 s -năm trăm sáu bảy giây~567 s \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_money.txt deleted file mode 100644 index 2d99fd4bba03..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,17 +0,0 @@ -hai đô~2$ -không phẩy không một euro~0.01€ -không chấm hai ơ rô~0.2€ -không phẩy hai hai euro~0.22€ -hai phẩy hai đô la mỹ~2.2$ -hai đô rưỡi~2.5$ -hai mươi euro~20€ -hai mươi chấm một euro~20.1€ -một đồng~1₫ -mười nghìn năm trăm đồng~10500₫ -năm phẩy sáu đồng~5.6₫ -hai mươi đồng rưỡi~20.5₫ -tám mươi nghìn một trăm won~80100₩ -tám mươi ngàn một trăm uôn~80100₩ -ba ringgit~3RM -không phẩy ba ringgit~0.3RM -không euro~0€ \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_ordinal.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_ordinal.txt deleted file mode 100644 index 740bc0bd2781..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_ordinal.txt +++ /dev/null @@ -1,12 +0,0 @@ -thứ nhất~thứ 1 -thứ nhì~thứ 2 -thứ hai~thứ 2 -thứ ba~thứ 3 -thứ bốn~thứ 4 -thứ tư~thứ 4 -thứ năm~thứ 5 -thứ sáu~thứ 6 -thứ bảy~thứ 7 -thứ bẩy~thứ 7 -thứ tám~thứ 8 -thứ chín~thứ 9 \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_telephone.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_telephone.txt deleted file mode 100644 index 0fa73bcaabb8..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_telephone.txt +++ /dev/null @@ -1,4 +0,0 @@ -không chín ba sáu năm năm năm bốn bốn chín~0936555449 -không một hai tám bốn hai hai năm~01284225 -một hai ba bốn năm sáu bảy tám chín~123456789 -chín tám bảy sáu năm bốn ba hai một không~9876543210 \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_time.txt deleted file mode 100644 index 4718c6d6c1b6..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,22 +0,0 @@ -tám giờ~8h -bảy giờ~7h -bẩy giờ~7h -hai mươi giờ~20h -mười tám giờ~18h -tám giờ bảy phút~8:07 -tám giờ hai mươi~8:20 -chín giờ rưỡi~9:30 -chín rưỡi~chín rưỡi -năm giờ hai mươi phút ba lăm giây~5:20:35 -sáu giờ mười phút năm giây~6:10:05 -mười sáu giờ kém mười lăm~15:45 -hai mươi giờ kém bốn phút~19:56 -năm giờ kém hai mươi phút~4:40 -năm giờ kém năm mươi sáu phút~4:04 -ba phút hai mươi giây~3p20s -bốn phút rưỡi~4p30s -mười hai phút ba giây~12p03s -năm chín phút năm mươi chín giây~59p59s -tám phút bốn lăm giây~8p45s -tám giờ hai ba phút gmt~8:23 gmt -mười lăm giờ cst~15h cst \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_whitelist.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_whitelist.txt deleted file mode 100644 index 4977bc62c0e5..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_whitelist.txt +++ /dev/null @@ -1 +0,0 @@ -~ \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_word.txt b/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_word.txt deleted file mode 100644 index b34357d4137a..000000000000 --- a/tests/nemo_text_processing/vi/data_inverse_text_normalization/test_cases_word.txt +++ /dev/null @@ -1,17 +0,0 @@ -~ -yahoo!~yahoo! -x~x -—~— -hôm~hôm -nay~nay -ăn~ăn -gì~gì -covid~covid -ngay~ngay -khi~khi -xảy~xảy -ra~ra -hiện~hiện -trường~trường -vụ~vụ -án~án \ No newline at end of file diff --git a/tests/nemo_text_processing/vi/test_cardinal.py b/tests/nemo_text_processing/vi/test_cardinal.py deleted file mode 100644 index 0a888f84bfd6..000000000000 --- a/tests/nemo_text_processing/vi/test_cardinal.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestCardinal: - - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_cardinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_date.py b/tests/nemo_text_processing/vi/test_date.py deleted file mode 100644 index 90885b6e4313..000000000000 --- a/tests/nemo_text_processing/vi/test_date.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDate: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_date.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_decimal.py b/tests/nemo_text_processing/vi/test_decimal.py deleted file mode 100644 index e1b246e1d7d2..000000000000 --- a/tests/nemo_text_processing/vi/test_decimal.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestDecimal: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_decimal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_electronic.py b/tests/nemo_text_processing/vi/test_electronic.py deleted file mode 100644 index 4df5810d9ff8..000000000000 --- a/tests/nemo_text_processing/vi/test_electronic.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestElectronic: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_electronic.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_fraction.py b/tests/nemo_text_processing/vi/test_fraction.py deleted file mode 100644 index acd465cfd9a5..000000000000 --- a/tests/nemo_text_processing/vi/test_fraction.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestFraction: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_fraction.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_measure.py b/tests/nemo_text_processing/vi/test_measure.py deleted file mode 100644 index 991cbc487612..000000000000 --- a/tests/nemo_text_processing/vi/test_measure.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMeasure: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_measure.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_money.py b/tests/nemo_text_processing/vi/test_money.py deleted file mode 100644 index c626eef41f27..000000000000 --- a/tests/nemo_text_processing/vi/test_money.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestMoney: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_money.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_ordinal.py b/tests/nemo_text_processing/vi/test_ordinal.py deleted file mode 100644 index 239234dda948..000000000000 --- a/tests/nemo_text_processing/vi/test_ordinal.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestOrdinal: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_ordinal.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_sparrowhawk_inverse_text_normalization.sh b/tests/nemo_text_processing/vi/test_sparrowhawk_inverse_text_normalization.sh deleted file mode 100644 index cc1defd4659f..000000000000 --- a/tests/nemo_text_processing/vi/test_sparrowhawk_inverse_text_normalization.sh +++ /dev/null @@ -1,79 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read spoken written <<< $testcase - denorm_pred=$(echo $spoken | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1) - - # trim white space - written="$(echo -e "${written}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$spoken" "$written" "$denorm_pred" - done < "$input" -} - -testITNCardinal() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_cardinal.txt - runtest $input -} - -testITNDate() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_date.txt - runtest $input -} - -testITNDecimal() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_decimal.txt - runtest $input -} - -testITNOrdinal() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_ordinal.txt - runtest $input -} - -testITNFraction() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_fraction.txt - runtest $input -} - -testITNTime() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_time.txt - runtest $input -} - -testITNMeasure() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_measure.txt - runtest $input -} - -testITNMoney() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_money.txt - runtest $input -} - -testITNTelephone() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_telephone.txt - runtest $input -} - -testITNElectronic() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_electronic.txt - runtest $input -} - -testITNWord() { - input=$PROJECT_DIR/vi/data_inverse_text_normalization/test_cases_word.txt - runtest $input -} - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/vi/test_telephone.py b/tests/nemo_text_processing/vi/test_telephone.py deleted file mode 100644 index f1fa16578abe..000000000000 --- a/tests/nemo_text_processing/vi/test_telephone.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTelephone: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_telephone.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_time.py b/tests/nemo_text_processing/vi/test_time.py deleted file mode 100644 index 9502cad5428e..000000000000 --- a/tests/nemo_text_processing/vi/test_time.py +++ /dev/null @@ -1,42 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestTime: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_time.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_whitelist.py b/tests/nemo_text_processing/vi/test_whitelist.py deleted file mode 100644 index 2ab06085f99e..000000000000 --- a/tests/nemo_text_processing/vi/test_whitelist.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWhitelist: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_whitelist.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/vi/test_word.py b/tests/nemo_text_processing/vi/test_word.py deleted file mode 100644 index e247dff796e6..000000000000 --- a/tests/nemo_text_processing/vi/test_word.py +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import pytest -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - -try: - from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer - - PYNINI_AVAILABLE = True -except (ImportError, ModuleNotFoundError): - PYNINI_AVAILABLE = False - - -class TestWord: - inverse_normalizer = ( - InverseNormalizer(lang='vi', cache_dir=CACHE_DIR, overwrite_cache=False) if PYNINI_AVAILABLE else None - ) - - @parameterized.expand(parse_test_case_file('vi/data_inverse_text_normalization/test_cases_word.txt')) - @pytest.mark.skipif( - not PYNINI_AVAILABLE, - reason="`pynini` not installed, please install via nemo_text_processing/pynini_install.sh", - ) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_denorm(self, test_input, expected): - pred = self.inverse_normalizer.inverse_normalize(test_input, verbose=False) - assert pred == expected diff --git a/tests/nemo_text_processing/zh/__init__.py b/tests/nemo_text_processing/zh/__init__.py deleted file mode 100644 index a1cf281f0908..000000000000 --- a/tests/nemo_text_processing/zh/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_char.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_char.txt deleted file mode 100644 index 4fedd2cd92fc..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_char.txt +++ /dev/null @@ -1,2 +0,0 @@ -你~你 -好~好 \ No newline at end of file diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_date.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_date.txt deleted file mode 100644 index ec0c76e8a8a2..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_date.txt +++ /dev/null @@ -1,5 +0,0 @@ -2002/01/28~二零零二年一月二十八日 -2002-01-28~二零零二年一月二十八日 -2002.01.28~二零零二年一月二十八日 -2001/11~二零零一年十一月 -03/12~零三年十二月 \ No newline at end of file diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_fraction.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_fraction.txt deleted file mode 100644 index ccfb5db1718d..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_fraction.txt +++ /dev/null @@ -1,3 +0,0 @@ -1/5~五分之一 -1/16~十六分之一 -3/2~二分之三 \ No newline at end of file diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_math.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_math.txt deleted file mode 100644 index 6b34a5c107c8..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_math.txt +++ /dev/null @@ -1,3 +0,0 @@ -78:96~七十八比九十六 --23℃~负二十三摄氏度 -±2~正负二 \ No newline at end of file diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_measure.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_measure.txt deleted file mode 100644 index f392d216fcd2..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_measure.txt +++ /dev/null @@ -1,6 +0,0 @@ -25kg~二十五千克 -38°C~三十八摄氏度 -120m²~一百二十平方米 -10ms~十毫秒 -6.3%~百分之六点三 -0.4%~百分之零点四 \ No newline at end of file diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_money.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_money.txt deleted file mode 100644 index c66297e52686..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_money.txt +++ /dev/null @@ -1,7 +0,0 @@ -￥1~一人民币 -USD1~一美元 -￡1~一英镑 -HKD20~二十港元 -J￥1.5~一点五日元 -€6~六欧元 -CAD3~三加元 \ No newline at end of file diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_preprocess.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_preprocess.txt deleted file mode 100644 index e1b592ebcda0..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_preprocess.txt +++ /dev/null @@ -1 +0,0 @@ -你啊好~你好 diff --git a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_time.txt b/tests/nemo_text_processing/zh/data_text_normalization/test_cases_time.txt deleted file mode 100644 index 2d6b788fff41..000000000000 --- a/tests/nemo_text_processing/zh/data_text_normalization/test_cases_time.txt +++ /dev/null @@ -1,4 +0,0 @@ -12:00~十二点 -5:02~五点零二分 -5:35:36~五点三十五分三十六秒 -8:00a.m.~上午八点 \ No newline at end of file diff --git a/tests/nemo_text_processing/zh/test_char.py b/tests/nemo_text_processing/zh/test_char.py deleted file mode 100644 index 1ca553eca3d0..000000000000 --- a/tests/nemo_text_processing/zh/test_char.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestChar: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_char.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_char(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tests/nemo_text_processing/zh/test_date.py b/tests/nemo_text_processing/zh/test_date.py deleted file mode 100644 index d8079e3a6b3a..000000000000 --- a/tests/nemo_text_processing/zh/test_date.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestDate: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_date.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_date(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tests/nemo_text_processing/zh/test_fraction.py b/tests/nemo_text_processing/zh/test_fraction.py deleted file mode 100644 index 03b508b2156e..000000000000 --- a/tests/nemo_text_processing/zh/test_fraction.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestFraction: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_fraction.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_fraction(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tests/nemo_text_processing/zh/test_math.py b/tests/nemo_text_processing/zh/test_math.py deleted file mode 100644 index e8740aa2dcbb..000000000000 --- a/tests/nemo_text_processing/zh/test_math.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestMath: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_math.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_math(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tests/nemo_text_processing/zh/test_measure.py b/tests/nemo_text_processing/zh/test_measure.py deleted file mode 100644 index 32df2885515c..000000000000 --- a/tests/nemo_text_processing/zh/test_measure.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestMeasure: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_measure.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_measure(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tests/nemo_text_processing/zh/test_money.py b/tests/nemo_text_processing/zh/test_money.py deleted file mode 100644 index d06a2b812942..000000000000 --- a/tests/nemo_text_processing/zh/test_money.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestMoney: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_money.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_money(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tests/nemo_text_processing/zh/test_preprocess.py b/tests/nemo_text_processing/zh/test_preprocess.py deleted file mode 100644 index f817517b56a5..000000000000 --- a/tests/nemo_text_processing/zh/test_preprocess.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestPreprocess: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_preprocess.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_preprocess(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tests/nemo_text_processing/zh/test_sparrowhawk_normalization.sh b/tests/nemo_text_processing/zh/test_sparrowhawk_normalization.sh deleted file mode 100644 index 6c3a6598f515..000000000000 --- a/tests/nemo_text_processing/zh/test_sparrowhawk_normalization.sh +++ /dev/null @@ -1,60 +0,0 @@ -#! /bin/sh - -PROJECT_DIR=/workspace/tests - -runtest () { - input=$1 - cd /workspace/sparrowhawk/documentation/grammars - - # read test file - while read testcase; do - IFS='~' read written spoken <<< $testcase - # replace non breaking space with breaking space - denorm_pred=$(echo $written | normalizer_main --config=sparrowhawk_configuration.ascii_proto 2>&1 | tail -n 1 | sed 's/\xC2\xA0/ /g') - - # # trim white space - spoken="$(echo -e "${spoken}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - denorm_pred="$(echo -e "${denorm_pred}" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')" - - # input expected actual - assertEquals "$written" "$spoken" "$denorm_pred" - done < "$input" -} - -testTNMoneyText() { - input=$PROJECT_DIR/zh/data_text_normalization/test_cases_money.txt - runtest $input -} -testTNCharText() { - input=$PROJECT_DIR/zh/data_text_normalization/test_cases_char.txt - runtest $input -} -testTNTimeText() { - input=$PROJECT_DIR/zh/data_text_normalization/test_cases_time.txt - runtest $input -} -testTNDateText() { - input=$PROJECT_DIR/zh/data_text_normalization/test_cases_date.txt - runtest $input -} -# testTNMathText() { -# input=$PROJECT_DIR/zh/data_text_normalization/test_cases_math.txt -# runtest $input -# } -testTNFractionText() { - input=$PROJECT_DIR/zh/data_text_normalization/test_cases_fraction.txt - runtest $input -} - -# testTNPreprocessText() { -# input=$PROJECT_DIR/zh/data_text_normalization/test_cases_preprocess.txt -# runtest $input -# } -testTNMeasureText() { - input=$PROJECT_DIR/zh/data_text_normalization/test_cases_measure.txt - runtest $input -} - - -# Load shUnit2 -. $PROJECT_DIR/../shunit2/shunit2 diff --git a/tests/nemo_text_processing/zh/test_time.py b/tests/nemo_text_processing/zh/test_time.py deleted file mode 100644 index d36737afb751..000000000000 --- a/tests/nemo_text_processing/zh/test_time.py +++ /dev/null @@ -1,30 +0,0 @@ -# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import pytest -from nemo_text_processing.text_normalization.normalize import Normalizer -from parameterized import parameterized - -from ..utils import CACHE_DIR, parse_test_case_file - - -class TestTime: - normalizer_zh = Normalizer(lang='zh', cache_dir=CACHE_DIR, overwrite_cache=False, input_case='cased') - - @parameterized.expand(parse_test_case_file('zh/data_text_normalization/test_cases_time.txt')) - @pytest.mark.run_only_on('CPU') - @pytest.mark.unit - def test_norm_time(self, test_input, expected): - preds = self.normalizer_zh.normalize(test_input) - assert expected == preds diff --git a/tools/ctc_segmentation/requirements.txt b/tools/ctc_segmentation/requirements.txt index cfcd12173eda..2c6cdaa1e755 100644 --- a/tools/ctc_segmentation/requirements.txt +++ b/tools/ctc_segmentation/requirements.txt @@ -1,2 +1,3 @@ ctc_segmentation==1.7.1 num2words +nemo_text_processing==0.1.6rc0 diff --git a/tools/text_processing_deployment/Dockerfile b/tools/text_processing_deployment/Dockerfile deleted file mode 100644 index 7d3ea46b2da2..000000000000 --- a/tools/text_processing_deployment/Dockerfile +++ /dev/null @@ -1,37 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Dockerfile for C++ (inverse) text normalization backend Sparrowhawk https://github.com/google/sparrowhawk - -# set base image (host OS) -FROM conda/miniconda3 - -# set the working directory in the container -WORKDIR /workspace - -# install dependencies -RUN conda install conda-build -y -RUN apt-get update && apt-get install -y --reinstall build-essential && apt-get upgrade -y && apt-get install -y git && apt-get install make -RUN git clone https://github.com/google/re2 -RUN cd re2 && make && make install -RUN apt-get install build-essential -y && apt-get install wget -y -RUN wget https://github.com/protocolbuffers/protobuf/releases/download/v2.5.0/protobuf-2.5.0.tar.gz -RUN tar xzvf protobuf-2.5.0.tar.gz -RUN cd protobuf-2.5.0 && ./configure && make && make install && ldconfig -RUN conda install -c conda-forge thrax=1.3.4 -y -RUN git clone https://github.com/yzhang123/sparrowhawk.git -RUN cd sparrowhawk && git checkout test && apt-get install -y autoconf && bash autoreconf && ./configure && make && make install && ldconfig -RUN git clone https://github.com/kward/shunit2.git -RUN echo "DONE" \ No newline at end of file diff --git a/tools/text_processing_deployment/README.rst b/tools/text_processing_deployment/README.rst deleted file mode 100644 index dfeadd12fda5..000000000000 --- a/tools/text_processing_deployment/README.rst +++ /dev/null @@ -1,10 +0,0 @@ -**Text Processing Deployment** -========================================= - -Introduction ------------- - -This folder provides scripts to deploy WFST-based grammars in `NeMo Text Processing `_ for -for production. - -See `documentation `_ for details. \ No newline at end of file diff --git a/tools/text_processing_deployment/docker/build.sh b/tools/text_processing_deployment/docker/build.sh deleted file mode 100644 index a179572bd77e..000000000000 --- a/tools/text_processing_deployment/docker/build.sh +++ /dev/null @@ -1,18 +0,0 @@ -#!/bin/bash - -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -FORCE_REBUILD=${1:-""} -docker build . --rm -t sparrowhawk $FORCE_REBUILD \ No newline at end of file diff --git a/tools/text_processing_deployment/docker/launch.sh b/tools/text_processing_deployment/docker/launch.sh deleted file mode 100644 index 227a27dccd2a..000000000000 --- a/tools/text_processing_deployment/docker/launch.sh +++ /dev/null @@ -1,45 +0,0 @@ -#!/bin/bash - -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -MODE=${1:-"export"} -LANGUAGE=${2:-"en"} -SCRIPT_DIR=$(cd $(dirname $0); pwd) -: ${CLASSIFY_DIR:="$SCRIPT_DIR/../$LANGUAGE/classify"} -: ${VERBALIZE_DIR:="$SCRIPT_DIR/../$LANGUAGE/verbalize"} -: ${CMD:=${3:-"/bin/bash"}} - -MOUNTS="" -MOUNTS+=" -v $CLASSIFY_DIR:/workspace/sparrowhawk/documentation/grammars/en_toy/classify" -MOUNTS+=" -v $VERBALIZE_DIR:/workspace/sparrowhawk/documentation/grammars/en_toy/verbalize" - -WORK_DIR="/workspace/sparrowhawk/documentation/grammars" -if [[ $MODE == "test_tn_grammars" ]]; then - CMD="bash test_sparrowhawk_normalization.sh" - WORK_DIR="/workspace/tests/${LANGUAGE}" -elif [[ $MODE == "test_itn_grammars" ]]; then - CMD="bash test_sparrowhawk_inverse_text_normalization.sh" - WORK_DIR="/workspace/tests/${LANGUAGE}" -fi - -echo $MOUNTS -docker run -it --rm \ - --shm-size=4g \ - --ulimit memlock=-1 \ - --ulimit stack=67108864 \ - $MOUNTS \ - -v $SCRIPT_DIR/../../../tests/nemo_text_processing/:/workspace/tests/ \ - -w $WORK_DIR \ - sparrowhawk:latest $CMD \ No newline at end of file diff --git a/tools/text_processing_deployment/export_grammars.sh b/tools/text_processing_deployment/export_grammars.sh deleted file mode 100644 index 981caadadab5..000000000000 --- a/tools/text_processing_deployment/export_grammars.sh +++ /dev/null @@ -1,80 +0,0 @@ -#!/bin/bash - -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# This script compiles and exports WFST-grammars from nemo_text_processing, builds C++ production backend Sparrowhawk (https://github.com/google/sparrowhawk) in docker, -# plugs grammars into Sparrowhawk and returns prompt inside docker. -# For inverse text normalization run: -# bash export_grammars.sh --GRAMMARS=itn_grammars --LANGUAGE=en -# echo "two dollars fifty" | ../../src/bin/normalizer_main --config=sparrowhawk_configuration.ascii_proto -# For text normalization run: -# bash export_grammars.sh --GRAMMARS=tn_grammars --LANGUAGE=en -# echo "\$2.5" | ../../src/bin/normalizer_main --config=sparrowhawk_configuration.ascii_proto -# -# To test TN grammars, run: -# bash export_grammars.sh --GRAMMARS=tn_grammars --LANGUAGE=en --MODE=test -# -# To test ITN grammars, run: -# bash export_grammars.sh --GRAMMARS=itn_grammars --LANGUAGE=en --MODE=test - -GRAMMARS="itn_grammars" # tn_grammars -INPUT_CASE="cased" # lower_cased, only for tn_grammars -LANGUAGE="en" # language, {'en', 'es', 'de','zh'} supports both TN and ITN, {'pt', 'ru', 'fr', 'vi'} supports ITN only -MODE="export" -OVERWRITE_CACHE="True" # Set to False to re-use .far files -FORCE_REBUILD="False" # Set to True to re-build docker file - -for ARG in "$@" -do - key=$(echo $ARG | cut -f1 -d=) - value=$(echo $ARG | cut -f2 -d=) - - if [[ $key == *"--"* ]]; then - v="${key/--/}" - declare $v="${value}" - fi -done - - -CACHE_DIR=${LANGUAGE} -echo "GRAMMARS = $GRAMMARS" -echo "MODE = $MODE" -echo "LANGUAGE = $LANGUAGE" -echo "INPUT_CASE = $INPUT_CASE" -echo "CACHE_DIR = $CACHE_DIR" -echo "OVERWRITE_CACHE = $OVERWRITE_CACHE" -echo "FORCE_REBUILD = $FORCE_REBUILD" - - -if [[ ${OVERWRITE_CACHE,,} == "true" ]]; then - OVERWRITE_CACHE="--overwrite_cache " - python3 pynini_export.py --output_dir=. --grammars=${GRAMMARS} --input_case=${INPUT_CASE} --language=${LANGUAGE} --cache_dir=${CACHE_DIR} ${OVERWRITE_CACHE}|| exit 1 - else OVERWRITE_CACHE="" -fi - -if [[ ${FORCE_REBUILD,,} == "true" ]]; then - FORCE_REBUILD="--no-cache" - else FORCE_REBUILD="" -fi - -find . -name "Makefile" -type f -delete -bash docker/build.sh $FORCE_REBUILD - -if [[ $MODE == "test" ]]; then - MODE=${MODE}_${GRAMMARS} -fi - -bash docker/launch.sh $MODE $LANGUAGE diff --git a/tools/text_processing_deployment/pynini_export.py b/tools/text_processing_deployment/pynini_export.py deleted file mode 100644 index e0f5935a3d0c..000000000000 --- a/tools/text_processing_deployment/pynini_export.py +++ /dev/null @@ -1,173 +0,0 @@ -# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. -# Copyright 2015 and onwards Google, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import os -import time -from argparse import ArgumentParser - -import pynini -from nemo_text_processing.text_normalization.en.graph_utils import generator_main - -# This script exports compiled grammars inside nemo_text_processing into OpenFst finite state archive files -# tokenize_and_classify.far and verbalize.far for production purposes - - -def itn_grammars(**kwargs): - d = {} - d['classify'] = { - 'TOKENIZE_AND_CLASSIFY': ITNClassifyFst( - cache_dir=kwargs["cache_dir"], overwrite_cache=kwargs["overwrite_cache"] - ).fst - } - d['verbalize'] = {'ALL': ITNVerbalizeFst().fst, 'REDUP': pynini.accep("REDUP")} - return d - - -def tn_grammars(**kwargs): - d = {} - d['classify'] = { - 'TOKENIZE_AND_CLASSIFY': TNClassifyFst( - input_case=kwargs["input_case"], - deterministic=True, - cache_dir=kwargs["cache_dir"], - overwrite_cache=kwargs["overwrite_cache"], - ).fst - } - d['verbalize'] = {'ALL': TNVerbalizeFst(deterministic=True).fst, 'REDUP': pynini.accep("REDUP")} - return d - - -def export_grammars(output_dir, grammars): - """ - Exports tokenizer_and_classify and verbalize Fsts as OpenFst finite state archive (FAR) files. - - Args: - output_dir: directory to export FAR files to. Subdirectories will be created for tagger and verbalizer respectively. - grammars: grammars to be exported - """ - - for category, graphs in grammars.items(): - out_dir = os.path.join(output_dir, category) - if not os.path.exists(out_dir): - os.makedirs(out_dir) - time.sleep(1) - if category == "classify": - category = "tokenize_and_classify" - generator_main(f"{out_dir}/{category}.far", graphs) - - -def parse_args(): - parser = ArgumentParser() - parser.add_argument("--output_dir", help="output directory for grammars", required=True, type=str) - parser.add_argument( - "--language", help="language", choices=["en", "de", "es", "pt", "ru", 'fr', 'vi', 'zh'], type=str, default='en' - ) - parser.add_argument( - "--grammars", help="grammars to be exported", choices=["tn_grammars", "itn_grammars"], type=str, required=True - ) - parser.add_argument( - "--input_case", help="input capitalization", choices=["lower_cased", "cased"], default="cased", type=str - ) - parser.add_argument("--overwrite_cache", help="set to True to re-create .far grammar files", action="store_true") - parser.add_argument( - "--cache_dir", - help="path to a dir with .far grammar file. Set to None to avoid using cache", - default=None, - type=str, - ) - return parser.parse_args() - - -if __name__ == '__main__': - args = parse_args() - - if args.language in ['pt', 'ru', 'fr', 'vi'] and args.grammars == 'tn_grammars': - raise ValueError('Only ITN grammars could be deployed in Sparrowhawk for the selected languages.') - - if args.language == 'en': - from nemo_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ( - ClassifyFst as ITNClassifyFst, - ) - from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize import ( - VerbalizeFst as ITNVerbalizeFst, - ) - from nemo_text_processing.text_normalization.en.taggers.tokenize_and_classify import ( - ClassifyFst as TNClassifyFst, - ) - from nemo_text_processing.text_normalization.en.verbalizers.verbalize import VerbalizeFst as TNVerbalizeFst - elif args.language == 'de': - from nemo_text_processing.inverse_text_normalization.de.taggers.tokenize_and_classify import ( - ClassifyFst as ITNClassifyFst, - ) - from nemo_text_processing.inverse_text_normalization.de.verbalizers.verbalize import ( - VerbalizeFst as ITNVerbalizeFst, - ) - from nemo_text_processing.text_normalization.de.taggers.tokenize_and_classify import ( - ClassifyFst as TNClassifyFst, - ) - from nemo_text_processing.text_normalization.de.verbalizers.verbalize import VerbalizeFst as TNVerbalizeFst - elif args.language == 'ru': - from nemo_text_processing.inverse_text_normalization.ru.taggers.tokenize_and_classify import ( - ClassifyFst as ITNClassifyFst, - ) - from nemo_text_processing.inverse_text_normalization.ru.verbalizers.verbalize import ( - VerbalizeFst as ITNVerbalizeFst, - ) - elif args.language == 'es': - from nemo_text_processing.inverse_text_normalization.es.taggers.tokenize_and_classify import ( - ClassifyFst as ITNClassifyFst, - ) - from nemo_text_processing.inverse_text_normalization.es.verbalizers.verbalize import ( - VerbalizeFst as ITNVerbalizeFst, - ) - from nemo_text_processing.text_normalization.es.taggers.tokenize_and_classify import ( - ClassifyFst as TNClassifyFst, - ) - from nemo_text_processing.text_normalization.es.verbalizers.verbalize import VerbalizeFst as TNVerbalizeFst - elif args.language == 'pt': - from nemo_text_processing.inverse_text_normalization.pt.taggers.tokenize_and_classify import ( - ClassifyFst as ITNClassifyFst, - ) - from nemo_text_processing.inverse_text_normalization.pt.verbalizers.verbalize import ( - VerbalizeFst as ITNVerbalizeFst, - ) - elif args.language == 'fr': - from nemo_text_processing.inverse_text_normalization.fr.taggers.tokenize_and_classify import ( - ClassifyFst as ITNClassifyFst, - ) - from nemo_text_processing.inverse_text_normalization.fr.verbalizers.verbalize import ( - VerbalizeFst as ITNVerbalizeFst, - ) - elif args.language == 'vi': - from nemo_text_processing.inverse_text_normalization.vi.taggers.tokenize_and_classify import ( - ClassifyFst as ITNClassifyFst, - ) - from nemo_text_processing.inverse_text_normalization.vi.verbalizers.verbalize import ( - VerbalizeFst as ITNVerbalizeFst, - ) - elif args.language == 'zh': - from nemo_text_processing.text_normalization.zh.taggers.tokenize_and_classify import ( - ClassifyFst as TNClassifyFst, - ) - from nemo_text_processing.text_normalization.zh.verbalizers.verbalize import VerbalizeFst as TNVerbalizeFst - - output_dir = os.path.join(args.output_dir, args.language) - export_grammars( - output_dir=output_dir, - grammars=locals()[args.grammars]( - input_case=args.input_case, cache_dir=args.cache_dir, overwrite_cache=args.overwrite_cache - ), - ) diff --git a/tutorials/text_processing/ITN_with_Thutmose_Tagger.ipynb b/tutorials/text_processing/ITN_with_Thutmose_Tagger.ipynb deleted file mode 100644 index b72cee51003b..000000000000 --- a/tutorials/text_processing/ITN_with_Thutmose_Tagger.ipynb +++ /dev/null @@ -1,1140 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "VFOY_ljrReXk" - }, - "outputs": [], - "source": [ - "\"\"\"\n", - "You can run either this notebook locally (if you have all the dependencies and a GPU) or on Google Colab.\n", - "\n", - "Instructions for setting up Colab are as follows:\n", - "1. Open a new Python 3 notebook.\n", - "2. Import this notebook from GitHub (File -> Upload Notebook -> \"GITHUB\" tab -> copy/paste GitHub URL)\n", - "3. Connect to an instance with a GPU (Runtime -> Change runtime type -> select \"GPU\" for hardware accelerator)\n", - "4. Run this cell to set up dependencies.\n", - "\"\"\"\n", - "\n", - "import os\n", - "\n", - "# install NeMo\n", - "BRANCH = 'main'\n", - "\n", - "GITHUB_ACCOUNT = 'NVIDIA' # change this if using a fork\n", - "\n", - "# either provide a path to local NeMo repository with NeMo already installed or git clone\n", - "\n", - "# option #1: local path to NeMo repo with NeMo already installed\n", - "NEMO_DIR_PATH = \"NeMo\"\n", - "\n", - "# option #2: download NeMo repo\n", - "if 'google.colab' in str(get_ipython()) or not os.path.exists(NEMO_DIR_PATH):\n", - " !git clone -b $BRANCH https://github.com/{GITHUB_ACCOUNT}/NeMo\n", - " %cd NeMo\n", - " !python -m pip install git+https://github.com/{GITHUB_ACCOUNT}/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - " %cd .." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "V8RfIztARxKH" - }, - "outputs": [], - "source": [ - "# If you're not using Colab, you might need to upgrade jupyter notebook to avoid the following error:\n", - "# 'ImportError: IProgress not found. Please update jupyter and ipywidgets.'\n", - "\n", - "!pip install ipywidgets\n", - "!jupyter nbextension enable --py widgetsnbextension\n", - "\n", - "# Please restart the kernel after running this cell" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oaTOPJHhTteF" - }, - "source": [ - "# Task Description\n", - "**Inverse text normalization (ITN)** is an important post-processing step within an automatic speech recognition (ASR) system. \n", - "ITN transforms spoken-domain text into its written form:\n", - "\n", - "> **Input:** \"on may third we paid one hundred and twenty three dollars\"\n", - "\n", - "> **Output:** \"on may 3 we paid \\$123\".\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sxo-kHP7frEX" - }, - "source": [ - "# Thutmose Tagger approach\n", - "We aim to do the following:\n", - "1. Align ITN expressions from the [Google Text normalization dataset](https://www.kaggle.com/richardwilliamsproat/text-normalization-for-english-russian-and-polish) on a granular level using [GIZA++](https://github.com/moses-smt/giza-pp), to get a monotonic one-to-one correspondence between each *spoken word* and corresponding *fragments* in written form. \n", - "2. Get a restricted vocabulary of target fragments (tags) that can cover most spoken-written pair conversions.\n", - "3. Build training dataset, where the input is the sentence in spoken form and the output is tags for all input words. \n", - "4. Train a token classifier neural model (see Figure below). \n", - "5. Apply a simple postprocessing procedure upon the tag sequence to get the final output" - ] - }, - { - "cell_type": "markdown", - "source": [ - "![Thutmose Tagger Architecture](images/thutmose_tagger_architecture.png)" - ], - "metadata": { - "id": "RG403l1gKyRy" - } - }, - { - "cell_type": "markdown", - "metadata": { - "id": "aMPeNtAracI9" - }, - "source": [ - "# Dataset\n", - "\n", - "The full English part of [Google Text normalization dataset](https://www.kaggle.com/richardwilliamsproat/text-normalization-for-english-russian-and-polish) consists of 1.1 billion words. For this tutorial we use only small subset of it.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "EqnuAgNNcVY-" - }, - "outputs": [], - "source": [ - "!rm -r en_data_small\n", - "!wget \"https://multilangaudiosamples.s3.us-east-2.amazonaws.com/en_data_small.zip\"\n", - "!unzip en_data_small" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "CkJ3LLaxRNFh" - }, - "outputs": [], - "source": [ - "## actually we do not need separate dev and test data in this tutorial, so just copy it \n", - "!cp -r en_data_small/test en_data_small/dev" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HLoXgnpMVACe" - }, - "source": [ - "\n", - "The dataset contains unnormalized (i.e. written form) and normalized (i.e. spoken form) sentence pairs that are aligned *on a phrase-level*. The normalized text is synthetic - obtained with the [Kestrel TTS text normalization system](https://www.cambridge.org/core/journals/natural-language-engineering/article/abs/kestrel-tts-text-normalization-system/F0C18A3F596B75D83B75C479E23795DA), so it’s not considered 100% correct.\n", - "\n", - "```\n", - "PLAIN Retrieved \n", - "DATE 18 April 2013 the eighteenth of april twenty thirteen\n", - "PUNCT . sil\n", - " \n", - "PLAIN Neuhorst \n", - "PUNCT ( sil\n", - "PLAIN Canada \n", - "DATE 2006 two thousand six\n", - "PLAIN Census \n", - "PLAIN population \n", - "CARDINAL 126 one hundred twenty six\n", - "PUNCT ) sil\n", - "PLAIN is \n", - "PLAIN a \n", - "PLAIN small \n", - "PLAIN hamlet \n", - "PLAIN in \n", - "PLAIN Saskatchewan \n", - "PUNCT , sil\n", - "PLAIN Canada \n", - "PLAIN about \n", - "CARDINAL 30 thirty\n", - "PLAIN minutes \n", - "PLAIN north \n", - "PLAIN of \n", - "PLAIN Saskatoon \n", - "PUNCT . sil\n", - " \n", - "```\n", - "\n", - "The following classes appear in the dataset:\n", - "* ADDRESS\n", - "* CARDINAL\n", - "* DATE\n", - "* DECIMAL\n", - "* DIGIT\n", - "* ELECTRONIC\n", - "* FRACTION\n", - "* LETTERS\n", - "* MEASURE\n", - "* MONEY\n", - "* ORDINAL\n", - "* PLAIN\n", - "* PUNCT\n", - "* TELEPHONE\n", - "* TIME\n", - "* VERBATIM\n", - "\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "source": [ - "# 1. Align ITN expressions on a granular-level" - ], - "metadata": { - "id": "rewQY1pbPeq8" - } - }, - { - "cell_type": "markdown", - "source": [ - "Let's download and compile GIZA++ as we will need it soon" - ], - "metadata": { - "id": "5cLXx7qdPpUK" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LNLjIDUJdY5f" - }, - "outputs": [], - "source": [ - "!git clone https://github.com/moses-smt/giza-pp.git giza-pp\n", - "%cd giza-pp\n", - "!ls\n", - "!make\n", - "%cd .." - ] - }, - { - "cell_type": "markdown", - "source": [ - "Do some imports" - ], - "metadata": { - "id": "2AfIeiu_P0Ik" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "mz8_O4kfS0fH" - }, - "outputs": [], - "source": [ - "from nemo.collections import nlp as nemo_nlp\n", - "from nemo.utils.exp_manager import exp_manager\n", - "import nemo\n", - "\n", - "import wget \n", - "import torch\n", - "import pytorch_lightning as pl\n", - "from omegaconf import OmegaConf\n", - "import pandas as pd" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uYW_qsDgkhCw" - }, - "source": [ - "First we need to prepare the input data for the aligner (GIZA++).\n", - "\n", - "We regard the corpus of ITN phrase-pairs as a parallel corpus. Parallel means that each pair has an equivalent meaning, though they may consist of any number of tokens and the task of an aligner is to find which source tokens corresponds to which target tokens.\n", - "The spoken phrase is tokenized by word boundary, while the written phrase is tokenized as follows: \n", - "1. All alphabetic sequences are separate tokens\n", - "2. In numeric sequences each character is a separate token.\n", - "3. All non-alphanumeric characters are separate tokens.\n", - "4. We add an underscore symbol to mark the beginning and end of a\n", - "sequence for future detokenization. \n", - "\n", - "Example\n", - "> **Spoken:** `january thirtieth two thousand five`\n", - "\n", - "> **Written initial:** `jan 30, 2005`\n", - "\n", - "> **Written tokenized**: `_jan_ _3 0 , 2 0 0 5_`" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "miXYxOv_mNVo" - }, - "source": [ - "The script [prepare_corpora_for_alignment.py](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/text_normalization_as_tagging/dataset_preparation/prepare_corpora_for_alignment.py) prepares the described parallel corpora. It extracts all unique ITN phrase-pairs from the Google TN dataset, tokenizes them as described above and stores in separate folders for each semiotic class. It also generates a bash script for running the alignment. At the end it prints how many examples it has found:\n", - "```\n", - "content/alignment/punct has 920953 instances\n", - "content/alignment/date has 150499 instances\n", - "content/alignment/letters has 68340 instances\n", - "content/alignment/cardinal has 61029 instances\n", - "...\n", - "``` " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_A12y5zNn4O0" - }, - "outputs": [], - "source": [ - "WORK_DIR=!pwd # returns array containing a single path, \n", - "WORK_DIR=WORK_DIR[0]\n", - "\n", - "CORPUS_LANG=\"en\"\n", - "if 'google.colab' in str(get_ipython()) or not os.path.exists(NEMO_DIR_PATH):\n", - " NEMO_PATH=WORK_DIR + \"/NeMo\"\n", - "else:\n", - " NEMO_PATH=NEMO_DIR_PATH\n", - "GIZA_BIN_DIR=WORK_DIR + \"/giza-pp/GIZA++-v2\"\n", - "MCKLS_BINARY=WORK_DIR + \"/giza-pp/mkcls-v2/mkcls\"\n", - "CORPUS_DIR=WORK_DIR + \"/en_data_small\"\n", - "ALIGNMENT_DIR=WORK_DIR + \"/alignment\"\n", - "\n", - "!mkdir {ALIGNMENT_DIR}" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "BguRSoIXesFx" - }, - "outputs": [], - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/prepare_corpora_for_alignment.py \\\n", - " --data_dir={CORPUS_DIR} \\\n", - " --out_dir={ALIGNMENT_DIR} \\\n", - " --giza_dir={GIZA_BIN_DIR} \\\n", - " --mckls_binary={MCKLS_BINARY} \\\n", - " --lang={CORPUS_LANG}" - ] - }, - { - "cell_type": "markdown", - "source": [ - "Let's exclude punct class, as our itn task doesn't require to restore punctuation marks" - ], - "metadata": { - "id": "v8LscfJrLUeg" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "VNOQ4nW2yF6I" - }, - "outputs": [], - "source": [ - "!rm -r {ALIGNMENT_DIR}/punct\n" - ] - }, - { - "cell_type": "markdown", - "source": [ - "Let's run GIZA++ alignment. \n", - "In this tutorial we only work with three semiotic classes: date, letters and cardinal (in real setting all classes are used, excluding punct).\n", - "\n", - "**Attention**: the environment variable USER should be defined with any value, otherwise GIZA++ ends with segmentation fault. " - ], - "metadata": { - "id": "uUQMhEKGT7gv" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "UPxcPu0_Xh2Y" - }, - "outputs": [], - "source": [ - "!chmod +x {ALIGNMENT_DIR}/date/run.sh\n", - "!chmod +x {ALIGNMENT_DIR}/letters/run.sh\n", - "!chmod +x {ALIGNMENT_DIR}/cardinal/run.sh" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gOCv-ctbU3Rv" - }, - "outputs": [], - "source": [ - "## It is necessary to specify environment variable USER=, otherwise GIZA++ terminates with a segfault \n", - "\n", - "%cd {ALIGNMENT_DIR}/date\n", - "!export USER=\"user\"; ./run.sh\n", - "%cd ../..\n", - "\n", - "%cd {ALIGNMENT_DIR}/letters\n", - "!export USER=\"user\"; ./run.sh\n", - "%cd ../..\n", - "\n", - "%cd {ALIGNMENT_DIR}/cardinal\n", - "!export USER=\"user\"; ./run.sh\n", - "%cd ../.." - ] - }, - { - "cell_type": "markdown", - "source": [ - "GIZA++ will generate many files in our class folders, but we need only two files with final alignments, those with suffixes `A3.final`. The two files correspond to the alignments produced by two GIZA++ runs - direct and reverse (switching source and target corpus). This is a common practice, it allows us to find safer alignment points - tokens that were aligned to one another in both runs. The script [extract_giza_alignments.py](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/text_normalization_as_tagging/dataset_preparation/extract_giza_alignments.py) heuristically combines these two GIZA++ alignments. It also applies a bunch of regular expressions to correct some alignment mistakes." - ], - "metadata": { - "id": "ueJYVF0cU3ic" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "j5WpPkzHNICP" - }, - "outputs": [], - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/extract_giza_alignments.py \\\n", - " --mode=itn \\\n", - " --giza_dir={ALIGNMENT_DIR}/date \\\n", - " --giza_suffix=\"A3.final\" \\\n", - " --out_filename=itn.out \\\n", - " --lang={CORPUS_LANG}\n", - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/extract_giza_alignments.py \\\n", - " --mode=itn \\\n", - " --giza_dir={ALIGNMENT_DIR}/letters \\\n", - " --giza_suffix=\"A3.final\" \\\n", - " --out_filename=itn.out \\\n", - " --lang={CORPUS_LANG}\n", - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/extract_giza_alignments.py \\\n", - " --mode=itn \\\n", - " --giza_dir={ALIGNMENT_DIR}/cardinal \\\n", - " --giza_suffix=\"A3.final\" \\\n", - " --out_filename=itn.out \\\n", - " --lang={CORPUS_LANG}" - ] - }, - { - "cell_type": "markdown", - "source": [ - "When we prepared the input corpus of ITN pairs for GIZA++, we made them unique and stored the frequencies in a separate file `freq`. Now let's append the frequencies to the resulting alignments." - ], - "metadata": { - "id": "vpqiKrS6XBlP" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "fxZ5jjUPlOFv" - }, - "outputs": [], - "source": [ - "!paste -d\"\\t\" {ALIGNMENT_DIR}/date/freq {ALIGNMENT_DIR}/date/itn.out > {ALIGNMENT_DIR}/date/itn.out2\n", - "!paste -d\"\\t\" {ALIGNMENT_DIR}/letters/freq {ALIGNMENT_DIR}/letters/itn.out > {ALIGNMENT_DIR}/letters/itn.out2\n", - "!paste -d\"\\t\" {ALIGNMENT_DIR}/cardinal/freq {ALIGNMENT_DIR}/cardinal/itn.out > {ALIGNMENT_DIR}/cardinal/itn.out2" - ] - }, - { - "cell_type": "markdown", - "source": [ - "Let's look at what we get. The output should look like\n", - "![Top of file with aligned expressions](images/thutmose_tagger_alignment_top.png)\n", - "...\n", - "![Bottom of file with aligned expressions](images/thutmose_tagger_alignment_bottom.png)\n" - ], - "metadata": { - "id": "yzt87qeEX5o0" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "tJNFvVhG4SMo" - }, - "outputs": [], - "source": [ - "df = pd.read_csv(ALIGNMENT_DIR + \"/cardinal/itn.out2\", sep=\"\\t\", header=None)\n", - "df.columns = [\"freq\", \"verdict\", \"spoken\", \"written initial tokens\", \"left-side alignment\", \"right-side alignment\"]\n", - "is_spoken_multiword = df[\"spoken\"].apply(lambda x: \" \" in x)\n", - "df2 = df[is_spoken_multiword].sort_values(\"freq\", ascending=False).reset_index(drop=True)\n", - "df2.head(20)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cEcXh1MzDWFy" - }, - "outputs": [], - "source": [ - "df2.tail(10)" - ] - }, - { - "cell_type": "markdown", - "source": [ - "# 2. Get a restricted vocabulary of target fragments (tags)\n", - "\n", - "There can be some inconsistencies in the automatic alignments, but nevertheless we now have **one-to-one correspondence** between input words and output fragments. Let's collect all fragments in a vocabulary! The output should look like this\n", - "![Tag vocabulary](images/thutmose_tagger_tag_vocabulary.png)\n", - "\n" - ], - "metadata": { - "id": "OdEuRQKXYG3D" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "89zwtEQmQJZ1" - }, - "outputs": [], - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/prepare_corpora_after_alignment.py \\\n", - " --mode=get_replacement_vocab \\\n", - " --giza_dir={ALIGNMENT_DIR} \\\n", - " --alignment_filename=itn.out2 \\\n", - " --data_dir=\"\" \\\n", - " --vocab_filename={WORK_DIR}/replacement_vocab_full.txt \\\n", - " --out_filename=\"\" \\\n", - " --lang={CORPUS_LANG}\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "tx4gXO7CGzyQ" - }, - "outputs": [], - "source": [ - "df = pd.read_csv(\"replacement_vocab_full.txt.cardinal\", sep=\"\\t\", header=None)\n", - "df.columns = [\"replacement tag\", \"freq\"]\n", - "df" - ] - }, - { - "cell_type": "markdown", - "source": [ - "Tags with low frequencies are likely to be derived from sporadic alignment mistakes, so let's truncate them, and put together the tags from all our semiotic classes." - ], - "metadata": { - "id": "Ts_G3TnLEQn4" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "2TKbJELTFFXG" - }, - "outputs": [], - "source": [ - "!head -n 150 replacement_vocab_full.txt.cardinal > replacement_vocab_cardinal.txt\n", - "!head -n 150 replacement_vocab_full.txt.date > replacement_vocab_date.txt\n", - "!head -n 150 replacement_vocab_full.txt.letters > replacement_vocab_letters.txt\n", - "!cat replacement_vocab_cardinal.txt \\\n", - " replacement_vocab_date.txt \\\n", - " replacement_vocab_letters.txt > replacement_vocab.select.txt\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "x6eEYkVlJDK-" - }, - "source": [ - "After concatenation the vocabulary file can contain duplicates of the same tags coming from different semiotic classes, but this is not important at this moment. The final vocabulary will be created later." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "DoDHW-p1FUso" - }, - "outputs": [], - "source": [ - "!wc -l replacement_vocab.select.txt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xcQK5cHQH_NH" - }, - "outputs": [], - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/prepare_corpora_after_alignment.py \\\n", - " --mode=filter_by_vocab \\\n", - " --giza_dir={ALIGNMENT_DIR} \\\n", - " --alignment_filename=itn.out2 \\\n", - " --data_dir=\"\" \\\n", - " --vocab_filename={WORK_DIR}/replacement_vocab.select.txt \\\n", - " --out_filename=itn.select.out \\\n", - " --lang={CORPUS_LANG}\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yWhCQJ5DLgoZ" - }, - "source": [ - "The script `prepare_corpora_after_alignment.py --mode=filter_by_vocab` discards examples that are not fully covered with our selected replacement vocabulary. We can see that number of lines slightly decreases.\n", - "```\n", - "4997 content/alignment/cardinal/itn.out2\n", - "4681 content/alignment/cardinal/itn.select.out\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_nqeRRjmKoWg" - }, - "outputs": [], - "source": [ - "!wc -l {ALIGNMENT_DIR}/cardinal/itn.out2\n", - "!wc -l {ALIGNMENT_DIR}/cardinal/itn.select.out\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kUQwwCkLMKEX" - }, - "source": [ - "The format of lines also slightly changes: we add the name of semiotic class, choose only one alignment(left-side or right-side) based on class, and remove unnecessary columns.\n", - "\n", - "![Final alignment](images/thutmose_tagger_final_alignment.png)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "83Voerh_K8gR" - }, - "outputs": [], - "source": [ - "df = pd.read_csv(ALIGNMENT_DIR + \"/cardinal/itn.select.out\", sep=\"\\t\", header=None)\n", - "df.columns = [\"semiotic class\", \"spoken\", \"written initial fragments\", \"alignment\"]\n", - "df.head(10)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "C6cAEYNHOKex" - }, - "source": [ - "# 3. Build training dataset \n", - "\n", - "Now it's time to create a tag-labeled dataset, containing _full sentences_. After previous step we got a large dictionary of ITN phrase conversions *that we know how to tag*. Once again we loop through the Google TN dataset and process each sentence in the following way:\n", - "\n", - "* If a sentence contains at least one ITN conversion, that is missing from our dictionary, this sentence is discarded.\n", - "* Otherwise we assign tags to the input words\n", - " 1. All words outside ITN conversion spans are tagged as ``.\n", - " 2. Tags for words inside ITN spans are taken from the dictionary\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "DQVCzljrMyHu" - }, - "outputs": [], - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/prepare_corpora_after_alignment.py \\\n", - " --mode=get_labeled_corpus \\\n", - " --giza_dir={ALIGNMENT_DIR} \\\n", - " --alignment_filename=itn.select.out \\\n", - " --data_dir={CORPUS_DIR}/dev \\\n", - " --vocab_filename=\"\" \\\n", - " --out_filename={CORPUS_DIR}/dev.labeled \\\n", - " --lang={CORPUS_LANG}\n", - "\n", - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/prepare_corpora_after_alignment.py \\\n", - " --mode=get_labeled_corpus \\\n", - " --giza_dir={ALIGNMENT_DIR} \\\n", - " --alignment_filename=itn.select.out \\\n", - " --data_dir={CORPUS_DIR}/train \\\n", - " --vocab_filename=\"\" \\\n", - " --out_filename={CORPUS_DIR}/train.labeled \\\n", - " --lang=${CORPUS_LANG}\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bBfuML8TQrwz" - }, - "source": [ - "The resulting file consists of three columns:\n", - "* input words\n", - "* target tags\n", - "* semiotic spans (if any)\n", - "\n", - "The semiotic spans are separated by semicolon, each span consists of class, begin and end in terms of input word positions e.g. \"DATE 6 9\".\n", - "\n", - "```\n", - "it can be summarized as an error driven transformation based tagger\t \t\n", - "this plan was first enacted in nineteen eighty four and continued to be followed for nineteen years\t _19 8 4_ _19_ \tDATE 6 9;CARDINAL 15 16\n", - "```\n", - "The semiotic spans are used for two purposes:\n", - " \n", - "1. During validation step we calculate accuracy w.r.t. semiotic spans. For example, a DATE span is correct if **all** tag predictions inside this span match the ground truth labels.\n", - "2. The model has additional classification head that predicts a semiotic class label for each of the input words. These predictions are used in the post-processing step for better handling of swaps.\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "-TjToCTDN8t8" - }, - "outputs": [], - "source": [ - "!head {CORPUS_DIR}/dev.labeled" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Bf9Evpn8RWp4" - }, - "source": [ - "Get the final label vocabulary, based on our labeled corpora. The output file should look like this\n", - "```\n", - "KEEP\n", - "DELETE\n", - "DELETE|_20\n", - "DELETE|_19\n", - "DELETE|_2\n", - "DELETE|_200\n", - "DELETE|,20\n", - "DELETE|9_\n", - "DELETE|9\n", - "DELETE|8_\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "2RY2pZwEPdlZ" - }, - "outputs": [], - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/dataset_preparation/get_label_vocab.py \\\n", - " --train_filename={CORPUS_DIR}/train.labeled \\\n", - " --dev_filename={CORPUS_DIR}/dev.labeled \\\n", - " --out_filename={CORPUS_DIR}/label_map.txt\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9cGtBQSwRj-p" - }, - "outputs": [], - "source": [ - "!head {CORPUS_DIR}/label_map.txt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "KL4DINweSgUQ" - }, - "outputs": [], - "source": [ - "!echo \"ADDRESS\" > {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"CARDINAL\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"DATE\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"DECIMAL\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"DIGIT\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"ELECTRONIC\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"FRACTION\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"LETTERS\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"MEASURE\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"MONEY\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"ORDINAL\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"PLAIN\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"PUNCT\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"TELEPHONE\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"TIME\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "!echo \"VERBATIM\" >> {CORPUS_DIR}/semiotic_classes.txt\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "b7JrZxs-WTS8" - }, - "outputs": [], - "source": [ - "!mkdir {WORK_DIR}/datasets\n", - "\n", - "!cp {CORPUS_DIR}/label_map.txt {WORK_DIR}/datasets/label_map.txt\n", - "!cp {CORPUS_DIR}/semiotic_classes.txt {WORK_DIR}/datasets/semiotic_classes.txt\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "E-fXGmAb63z0" - }, - "source": [ - "Now the file `train.labeled` contains all sentences from initial Google TN data, that we have been able to cover with out tag dictionary. \n", - "From it we can create different datasets for our neural model, trying different sizes and sampling strategies.\n", - "\n", - "Let's create a toy dataset of 5'000 sentences for train set and 5'000 sentences for dev set. Test set is not used - see Evaluation section below." - ] - }, - { - "cell_type": "code", - "source": [ - "DATASET = WORK_DIR + \"/datasets/itn_sample10k\"\n", - "!mkdir {DATASET}\n", - "!head -n 5000 {CORPUS_DIR}/train.labeled > {DATASET}/train.tsv\n", - "!head -n 5000 {CORPUS_DIR}/dev.labeled > {DATASET}/valid.tsv\n", - "!cp {DATASET}/valid.tsv {DATASET}/test.tsv\n" - ], - "metadata": { - "id": "KFwzGmuJlC0N" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "# 4. Train a token classifier neural model\n", - "Now let's run training" - ], - "metadata": { - "id": "X1vWojxlmffT" - } - }, - { - "cell_type": "code", - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/normalization_as_tagging_train.py \\\n", - " lang=en \\\n", - " data.validation_ds.data_path={DATASET}/valid.tsv \\\n", - " data.train_ds.data_path={DATASET}/train.tsv \\\n", - " model.language_model.pretrained_model_name=bert-base-uncased \\\n", - " model.label_map={WORK_DIR}/datasets/label_map.txt \\\n", - " model.semiotic_classes={WORK_DIR}/datasets/semiotic_classes.txt \\\n", - " trainer.accelerator=gpu \\\n", - " trainer.max_epochs=1\n" - ], - "metadata": { - "id": "APBdPcihmFBa" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Each validation step generates three classification reports where rows correspond to different semiotic classes, `support` column is how many examples of this class occurred in the target of validation set, and `recall` column is the classifier **accuracy** on this class, i.e. percentage of _whole examples_ whose predicted tags match the target.\n", - "\n", - "1. Tag classification report. `PLAIN` class includes words that are tagged as ``.\n", - "2. Tag classification report for **multiword** examples only. They are less trivial and it is harder to achieve high accuracy on them.\n", - "3. Classification report for semiotic classes." - ], - "metadata": { - "id": "kjZU6fkvS0V5" - } - }, - { - "cell_type": "code", - "source": [ - "# the log can be found in nemo_experiments folder\n", - "!cat nemo_experiments/training/*/nemo_log_globalrank-0_localrank-0.txt" - ], - "metadata": { - "id": "gO1nez6AWJeW" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "# Inference" - ], - "metadata": { - "id": "hX-9t7XBqJbo" - } - }, - { - "cell_type": "markdown", - "source": [ - "Let's run the inference of our toy model.\n", - "First, copy the model, that we've just trained." - ], - "metadata": { - "id": "9x80qIKCsBQ7" - } - }, - { - "cell_type": "code", - "source": [ - "!cp nemo_experiments/training/*/checkpoints/training.nemo ." - ], - "metadata": { - "id": "dYfyklDTXuUM" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Generate some input sentences." - ], - "metadata": { - "id": "pVCV2Hchs-gG" - } - }, - { - "cell_type": "code", - "source": [ - "!echo \"on the ninth of may four days after her arrival at new orleans west carnifax was decommissioned and returned to the u s s b\" > test_sent.txt\n", - "!echo \"retrieved the fourth of october twenty fifteen\" >> test_sent.txt" - ], - "metadata": { - "id": "30KlsQ6uY6vu" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Run the inference." - ], - "metadata": { - "id": "uqyBEKn-tDXe" - } - }, - { - "cell_type": "code", - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/normalization_as_tagging_infer.py \\\n", - " pretrained_model=./training.nemo \\\n", - " inference.from_file=./test_sent.txt \\\n", - " inference.out_file=./test_sent.output" - ], - "metadata": { - "id": "SDSm6lg6ZOM_" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "!cat test_sent.output" - ], - "metadata": { - "id": "jrGJb9DcZ83E" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "The inference output consists of 5 columns:\n", - "\n", - "1. Final output text.\n", - "2. Input text.\n", - "3. Sequence of predicted tags.\n", - "4. Sequence of tags after post-processing (some swaps may be applied).\n", - "5. Sequence of predicted semiotic classes - one class for each input word.\n", - "\n", - "```\n", - "on ninth may four days after her arrival at new orleans west carnifax was decommissioned and returned to the u s s b\ton the ninth of may four days after her arrival at new orleans west carnifax was decommissioned and returned to the u s s b\t \t \tPLAIN DATE DATE DATE DATE DATE PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN PLAIN LETTERS LETTERS LETTERS LETTERS\n", - "retrieved 20 october 20 20\tretrieved the fourth of october twenty fifteen\t _20 _20 _20\t _20 _20 _20\tPLAIN DATE DATE DATE DATE DATE DATE```\n" - ], - "metadata": { - "id": "eYqtL7waaiZS" - } - }, - { - "cell_type": "markdown", - "source": [ - "We see that our toy model works and even manages to replace some numbers.\n", - "\n", - "To train a full-fledged model, you need more data.\n", - "\n", - "See also the scripts for the whole pipeline:\n", - "\n", - "> [prepare_dataset_en.sh](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/text_normalization_as_tagging/prepare_dataset_en.sh)\n", - "\n", - "> [normalization_as_tagging_train.py](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/text_normalization_as_tagging/normalization_as_tagging_train.py)\n", - "\n", - "> [run_infer.sh](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/text_normalization_as_tagging/run_infer.sh)\n", - "\n" - ], - "metadata": { - "id": "AY9sQCIcUEGO" - } - }, - { - "cell_type": "markdown", - "source": [ - "# Inference with a pretrained model\n", - "\n", - "We can also run inference with a pretrained model [itn_en_thutmose_bert](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/itn_en_thutmose_bert).\n", - "This is how to use it directly from python." - ], - "metadata": { - "id": "cMYFQLbaY3m-" - } - }, - { - "cell_type": "code", - "source": [ - "thutmose = nemo_nlp.models.ThutmoseTaggerModel.from_pretrained('itn_en_thutmose_bert')\n", - "thutmose.summarize()" - ], - "metadata": { - "id": "8Uor5qqcYgGF" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "from nemo.collections.nlp.data.text_normalization_as_tagging.utils import spoken_preprocessing\n", - "\n", - "lines = [\"on the ninth of may four days after her arrival at new orleans west carnifax was decommissioned and returned to the u s s b\",\n", - " \"retrieved the fourth of october twenty fifteen\"]\n", - "\n", - "\n", - "batch, all_preds = [], []\n", - "for i, line in enumerate(lines):\n", - " s = spoken_preprocessing(line) # this is the same input transformation as in corpus preparation\n", - " batch.append(s.strip())\n", - " outputs = thutmose._infer(batch)\n", - "for x in outputs:\n", - " all_preds.append(x)\n", - "\n", - "if len(all_preds) != len(lines):\n", - " raise ValueError(\n", - " \"number of input lines and predictions is different: predictions=\"\n", - " + str(len(all_preds))\n", - " + \"; lines=\"\n", - " + str(len(lines))\n", - " )\n", - "\n", - "for i in range(len(all_preds)):\n", - " print (all_preds[i])" - ], - "metadata": { - "id": "FcOiYPJwZzS0" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Or we can use the inference script" - ], - "metadata": { - "id": "sJguLcWhaFdE" - } - }, - { - "cell_type": "code", - "source": [ - "!python {NEMO_PATH}/examples/nlp/text_normalization_as_tagging/normalization_as_tagging_infer.py \\\n", - " pretrained_model=itn_en_thutmose_bert \\\n", - " inference.from_file=./test_sent.txt \\\n", - " inference.out_file=./test_sent.output" - ], - "metadata": { - "id": "4R1hRpU-aMUs" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "!cat test_sent.output" - ], - "metadata": { - "id": "E0qVTUyvaQt1" - }, - "execution_count": null, - "outputs": [] - } - ], - "metadata": { - "colab": { - "collapsed_sections": [], - "name": "ITN_with_Thutmose_Tagger.ipynb", - "provenance": [] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - }, - "language_info": { - "name": "python" - }, - "accelerator": "GPU" - }, - "nbformat": 4, - "nbformat_minor": 0 -} \ No newline at end of file diff --git a/tutorials/text_processing/Text_(Inverse)_Normalization.ipynb b/tutorials/text_processing/Text_(Inverse)_Normalization.ipynb deleted file mode 100755 index f8123146f55f..000000000000 --- a/tutorials/text_processing/Text_(Inverse)_Normalization.ipynb +++ /dev/null @@ -1,468 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "a5fA5qAm5Afg" - }, - "outputs": [], - "source": [ - "\"\"\"\n", - "You can run either this notebook locally or on Google Colab.\n", - "\n", - "Instructions for setting up Colab are as follows:\n", - "1. Open a new Python 3 notebook.\n", - "2. Import this notebook from GitHub (File -> Upload Notebook -> \"GITHUB\" tab -> copy/paste GitHub URL)\n", - "3. Optional: Restart the runtime (Runtime -> Restart Runtime) for any upgraded packages to take effect\n", - "\"\"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> **_NOTE:_** Find the official NeMo documentation at \n", - "https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/intro.html " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Overview\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "F-IrnmXMTevr" - }, - "source": [ - "A sentence can be split up into semiotic tokens stemming from a variety of classes, where the spoken form differs from the written form. Examples are *dates*, *decimals*, *cardinals*, *measures* etc. The good TN or ITN system will be able to handle a variety of **semiotic classes**." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-IT1Xr9iW2Xr" - }, - "source": [ - "# How to use\n", - "## 1. Installation" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "## Install NeMo, which installs both nemo and nemo_text_processing package\n", - "BRANCH = 'main'\n", - "!python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[nlp]\n", - "\n", - "# install Pynini for text normalization\n", - "! wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "! bash install_pynini.sh" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# try to import of nemo_text_processing an other dependencies\n", - "import nemo_text_processing\n", - "import os" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Text Normalization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Bfs7fa9lXDDh" - }, - "outputs": [], - "source": [ - "# create text normalization instance that works on cased input\n", - "from nemo_text_processing.text_normalization.normalize import Normalizer\n", - "normalizer = Normalizer(input_case='cased', lang='en')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# the normalizer class offers the following parameterization. \n", - "print(normalizer.__doc__)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> **_NOTE:_** Standard Text Normalization uses `deterministic=True`, outputting a single output for a given input string\n", - "\n", - "\n", - "\n", - "### 2.1 Run TN on input string" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Normalizer.normalize() offers the following parameterization\n", - "print(normalizer.normalize.__doc__)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# run normalization on example string input\n", - "written = \"We paid $123 for this desk.\"\n", - "normalized = normalizer.normalize(written, verbose=True, punct_post_process=True)\n", - "print(normalized)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "intermediate semiotic class information is shown if verbose=True. \n", - "\n", - "Long input text could be split into sentences as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "written = \"Mr. Smith paid $111 in U.S.A. on Dec. 17th. We paid $123 for this desk.\"\n", - "\n", - "# split long text into sentences\n", - "sentences = normalizer.split_text_into_sentences(written)\n", - "\n", - "for sent in sentences:\n", - " print(sent)\n", - "\n", - "# normalize each sentence separately using normalize() or all sentences at once with normalize_list()\n", - "normalizer.normalize_list(sentences)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "### 2.2 Run TN on list of input strings" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "UD-OuFmEOX3T" - }, - "outputs": [], - "source": [ - "# create temporary data folder and example input file\n", - "DATA_DIR = 'tmp_data_dir'\n", - "os.makedirs(DATA_DIR, exist_ok=True)\n", - "INPUT_FILE = f'{DATA_DIR}/inference.txt'\n", - "! echo -e 'The alarm went off at 10:00a.m. \\nI received $123' > $INPUT_FILE" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d4T0gXHwY3JZ" - }, - "outputs": [], - "source": [ - "# check input file was properly created\n", - "! cat $INPUT_FILE" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# load input file into 'data' - a list of strings\n", - "data = []\n", - "with open(INPUT_FILE, 'r') as fp:\n", - " for line in fp:\n", - " data.append(line.strip())\n", - "data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "F5wSJTI8ZFRg" - }, - "outputs": [], - "source": [ - "# run normalization on 'data'\n", - "normalizer.normalize_list(data, punct_post_process=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RMT5lkPYzZHK" - }, - "source": [ - "### 2.3 Evaluate TN on written-normalized text pairs \n", - "\n", - "The evaluation data needs to have the following format:\n", - "\n", - "'on 22 july 2022 they worked until 12:00' and the normalization is represented as " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# example evaluation sentence\n", - "eval_text = \"\"\"PLAIN\\ton\\t\n", - "DATE\\t22 july 2012\\tthe twenty second of july twenty twelve\n", - "PLAIN\\tthey\\t\n", - "PLAIN\\tworked\\t\n", - "PLAIN\\tuntil\\t\n", - "TIME\\t12:00\\ttwelve o'clock\n", - "\\t\n", - "\"\"\"\n", - "EVAL_FILE = f'{DATA_DIR}/eval.txt'\n", - "with open(EVAL_FILE, 'w') as fp:\n", - " fp.write(eval_text)\n", - "! cat $EVAL_FILE" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RMT5lkPYzZHK" - }, - "source": [ - "That is, every sentence is broken into semiotic tokens line by line and concluded by end of sentence token ``. In case of a plain token it's `[SEMIOTIC CLASS] [TAB] [WRITTEN] [TAB] `, otherwise `[SEMIOTIC CLASS] [TAB] [WRITTEN] [TAB] [NORMALIZED]`.\n", - "This format was introduced in [Google Text normalization dataset](https://arxiv.org/abs/1611.00068). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Parse evaluation file into written and normalized sentence pairs\n", - "from nemo_text_processing.text_normalization.data_loader_utils import load_files, training_data_to_sentences\n", - "eval_data = load_files([EVAL_FILE])\n", - "sentences_un_normalized, sentences_normalized, sentences_class_types = training_data_to_sentences(eval_data)\n", - "print(list(zip(sentences_un_normalized, sentences_normalized)))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# run prediction\n", - "sentences_prediction = normalizer.normalize_list(sentences_un_normalized)\n", - "print(sentences_prediction)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# measure sentence accuracy\n", - "from nemo_text_processing.text_normalization.data_loader_utils import evaluate\n", - "sentences_accuracy = evaluate(\n", - " preds=sentences_prediction, labels=sentences_normalized, input=sentences_un_normalized\n", - " )\n", - "print(\"- Accuracy: \" + str(sentences_accuracy))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Inverse Text Normalization\n", - "ITN supports equivalent API as TN. Here we are only going to show inverse normalization on input string" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# create inverse text normalization instance\n", - "from nemo_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer\n", - "inverse_normalizer = InverseNormalizer(lang='en')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# run ITN on example string input\n", - "spoken = \"we paid one hundred twenty three dollars for this desk\"\n", - "un_normalized = inverse_normalizer.inverse_normalize(spoken, verbose=True)\n", - "print(un_normalized)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 4. Audio-based Text Normalization\n", - "Audio-based text normalization uses extended [WFST](https://en.wikipedia.org/wiki/Finite-state_machine) grammars to provide a range of possible normalization options.\n", - "The following example shows the workflow: (Disclaimer: exact values in graphic do not need to be real system's behavior)\n", - "1. text \"627\" is sent to extended TN WFST grammar\n", - "2. grammar output 5 different options of verbalization based on text input alone\n", - "3. in case an audio file is presented we compare the audio transcript with the verbalization options to find out which normalization is correct based on character error rate. The transcript is generated using a pretrained NeMo ASR model. \n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The following shows an example of how to generate multiple normalization options:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# import non-deterministic WFST-based TN module\n", - "from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# initialize normalizer, this may take some time to generate the extended grammars. \n", - "# Thus, we recommend to cache the grammars by specifying a cache directory\n", - "normalizer = NormalizerWithAudio(\n", - " lang=\"en\",\n", - " input_case=\"cased\",\n", - " overwrite_cache=False,\n", - " cache_dir=\"cache_dir\",\n", - " )\n", - "# create up to 10 normalization options\n", - "print(normalizer.normalize(\"123\", n_tagged=10, punct_post_process=True))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Parallel execution\n", - "\n", - "`Normalizer.normalize()` as well as `InverseNormalizer.inverse_normalize()` are functions without side effect.\n", - "Thus, if you need to normalize large amounts of input examples, these can be executed in parallel." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ENMDNl9C4TkF" - }, - "source": [ - "# Tutorial on how to customize grammars\n", - "\n", - "https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/WFST_Tutorial.ipynb\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lcvT3P2lQ_GS" - }, - "source": [ - "# References and Further Reading:\n", - "\n", - "\n", - "- [Zhang, Yang, Bakhturina, Evelina, Gorman, Kyle and Ginsburg, Boris. \"NeMo Inverse Text Normalization: From Development To Production.\" (2021)](https://arxiv.org/abs/2104.05055)\n", - "- [Ebden, Peter, and Richard Sproat. \"The Kestrel TTS text normalization system.\" Natural Language Engineering 21.3 (2015): 333.](https://www.cambridge.org/core/journals/natural-language-engineering/article/abs/kestrel-tts-text-normalization-system/F0C18A3F596B75D83B75C479E23795DA)\n", - "- [Gorman, Kyle. \"Pynini: A Python library for weighted finite-state grammar compilation.\" Proceedings of the SIGFSM Workshop on Statistical NLP and Weighted Automata. 2016.](https://www.aclweb.org/anthology/W16-2409.pdf)\n", - "- [Mohri, Mehryar, Fernando Pereira, and Michael Riley. \"Weighted finite-state transducers in speech recognition.\" Computer Speech & Language 16.1 (2002): 69-88.](https://cs.nyu.edu/~mohri/postscript/csl01.pdf)" - ] - } - ], - "metadata": { - "accelerator": "GPU", - "colab": { - "collapsed_sections": [ - "lcvT3P2lQ_GS" - ], - "name": "Text_Normalization_Tutorial.ipynb", - "private_outputs": true, - "provenance": [], - "toc_visible": true - }, - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.7" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} \ No newline at end of file diff --git a/tutorials/text_processing/WFST_Tutorial.ipynb b/tutorials/text_processing/WFST_Tutorial.ipynb deleted file mode 100644 index ed7127241dd5..000000000000 --- a/tutorials/text_processing/WFST_Tutorial.ipynb +++ /dev/null @@ -1,7054 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "Qq1Hz6CKWdwl", - "outputId": "3d8f5bd6-f10e-431d-9039-eb88164fbb95" - }, - "outputs": [], - "source": [ - "\"\"\"\n", - "You can run either this notebook locally or on Google Colab.\n", - "\n", - "Instructions for setting up Colab are as follows:\n", - "1. Open a new Python 3 notebook.\n", - "2. Import this notebook from GitHub (File -> Upload Notebook -> \"GITHUB\" tab -> copy/paste GitHub URL)\n", - "3. Optional: Restart the runtime (Runtime -> Restart Runtime) for any upgraded packages to take effect\n", - "\"\"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "## Prerequisites:\n", - "1. Please make sure to read the [Text Processing Documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/intro.html) and [Text Normalization Introduction Tutorial](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/Text_(Inverse)_Normalization.ipynb) **before** this notebook. This notebook is a in-depth tutorial on how to customize and develop your own text normalization or inverse text normalization grammars.\n", - "2. download NeMo source code" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "## Install NeMo, which installs both nemo and nemo_text_processing package\n", - "BRANCH = 'main'\n", - "!python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[nemo_text_processing]\n", - "\n", - "# install Pynini for text normalization\n", - "! wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "! bash install_pynini.sh" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import pynini\n", - "import nemo_text_processing\n", - "from pynini.lib import pynutil" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from nemo_text_processing.text_normalization.en.graph_utils import GraphFst, NEMO_DIGIT, delete_space, NEMO_SIGMA, NEMO_NOT_QUOTE, delete_extra_space, NEMO_NON_BREAKING_SPACE\n", - "from nemo_text_processing.text_normalization.normalize import Normalizer\n", - "\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.cardinal import CardinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.decimal import DecimalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.money import MoneyFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.ordinal import OrdinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.punctuation import PunctuationFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.time import TimeFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.whitelist import WhiteListFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.word import WordFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.cardinal import CardinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.decimal import DecimalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.money import MoneyFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.ordinal import OrdinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.time import TimeFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.whitelist import WhiteListFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.word import WordFst\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "T0JxcvuPHvn9" - }, - "source": [ - "NeMo's Text Processing module uses Weighted Finite State Transducers (WFST) to deploy grammars for both efficient text normalization (TN) and inverse text normalization (ITN). In this tutorial, you will learn to build a normalization grammar from the ground up to use in your own text processing tasks. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Table of Contents\n", - "- WFSTs\n", - "- NeMo Inverse Text Processing\n", - "- Getting Started\n", - "- Cardinal WFST\n", - "- Ordinal WFST\n", - "- Decimal WFST\n", - "- Money WFST\n", - "- Time WFST\n", - "- WhiteList WFST\n", - "- Word and Punctuation WFST\n", - "- Other Classes\n", - "- Tokenize and Classify\n", - "- Verbalize and Verbalize Final\n", - "- Deployment" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lMUovcMsfXyI" - }, - "source": [ - "# WFSTs " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Y1ejNMLbH1jM" - }, - "source": [ - "WFSTs are a form of [Finite State Machines](https://en.wikipedia.org/wiki/Finite-state_machine) used to graph relations between regular languages (or [regular expressions](https://en.wikipedia.org/wiki/Regular_expression)). For our purposes, they can be defined by two major properties:\n", - "\n", - "1. Mappings between accepted input and output expressions for text substitution\n", - "2. Path weighting to direct graph traversal" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nNg45ZuaP_A8" - }, - "source": [ - "For example, consider a simple normalization task of mapping the word \"cent\" (French for \"one hundred\") to the numerical representation `100`. We would begin with a Finite State representation of the regex `/cent/`:" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uxo7gUkW_XKT" - }, - "source": [ - "![cent.png](images/cent.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "fahsjMVFlbCa" - }, - "source": [ - "And then create a mapping to the text string `100`:" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IMJ-fNSk_jXC" - }, - "source": [ - "![cent_to_100.png](images/cent_to_100.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bPKW0I4yAGUb" - }, - "source": [ - "*Note: Null characters are expressed as `ε` by convention*" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_0NK3aW5nG9C" - }, - "source": [ - "This would give us a WFST with universal path weights. (By default, `pynini` uses [tropical semirings](https://en.wikipedia.org/wiki/Tropical_semiring) for arcs, giving each arc a default weight of `0`.)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CzBc9D3qTGJ-" - }, - "source": [ - "Now, let us consider expanding our model. To indicate values between `100` and `200`, French uses the number scheme of `cent + digit`. For example, `120` would be pronounced as \"cent-vingt\". To create the appropriate output string, we would now want to map \"cent\" to `1` and the remaining aspect of our string to the appropriate digit representation." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "GRrKNQRjFDoL" - }, - "source": [ - "![cent_vingt_to_120.png](images/cent_vingt_to_120.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jLpm4mufAfUz" - }, - "source": [ - "However this would make our graph [non-deterministic](https://en.wikipedia.org/wiki/Nondeterministic_algorithm) - it will have multiple possibilities for termination. Now an input of \"cent-vingt\" could have the outcome of `100` or `10020` when only one is correct. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "![cent_vingt_bad.png](images/cent_vingt_bad.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "c-GJTpgIAf7S" - }, - "source": [ - "To correct this, we may add a new end state and a weight to the path that accepts the input without `s`:" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6GJcsdttGg_S" - }, - "source": [ - "![cent_vingt_good.png](images/cent_vingt_good.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "mHft1gzsAipc" - }, - "source": [ - "Now, we can guarantee an ideal mapping by relying on a shortest-path (smallest-weight) heuristic: traversal of the graph will prioritize longer inputs, only converting \"cent\" to `100` when a larger input isn't available. As such, we've now removed the undesired output `10020` while preserving our desired coverage in string mapping. \n", - "\n", - "This use of weights to ensure predictable behavior allows WFSTs to exploit the efficiency of standard graph traversal algorithms while also maintaining versatility. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8Ik4PBXafSSB" - }, - "source": [ - "# NeMo Inverse Text Processing " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b2fcWKhqYVF5" - }, - "source": [ - "Following [Google's Kestrel](https://www.researchgate.net/publication/277932107_The_Kestrel_TTS_text_normalization_system) framework, NeMo deploys two composite WFSTs for text normalization. They are as follows:\n", - "1. A *classifier* (or tagger) to label potential tokens by 'semiotic class' (e.g. currency, ordinal number, street address)\n", - "2. A *verbalizer* to render a tagged token in conventional written form\n", - "\n", - "For example, consider the sentence: <>\n", - "\n", - "For an ITN task, a tokenizer would identify the following tokens:\n", - "\n", - "`[\"le\" ,\"premier\", \"juillet\", \"il\", \"a\", \"mangé\", \"trente-cinq\", \"pommes\"]`\n", - "\n", - "and provide each a class token: \n", - "\n", - "- `tokens { name: \"le\" }`\n", - "- `tokens { date { day: \"1\" month: \"juillet\" } } ` \n", - "- `tokens { name: \"il\" }` \n", - "- `tokens { name: \"a\" }` \n", - "- `tokens { name: \"mangé\" }`\n", - "- `tokens { cardinal { integer: \"35\" } }` \n", - "- `tokens { name: \"pommes\" }`\n", - "\n", - "These tokens are then passed to a 'verbalizer' WFST, which renders each token in a conventional written form:\n", - "\n", - "- `tokens { name: \"le\" }` -> `le` \n", - "- `tokens { date { day: \"1\" month: \"juillet\" } } ` -> `1ᵉʳ` \n", - "- `tokens { name: \"il\" }` -> `juillet`\n", - "- `tokens { name: \"il\" }` -> `il` \n", - "- `tokens { name: \"a\" }` -> `a`\n", - "- `tokens { name: \"mangé\" }` -> `mangé` \n", - "- `tokens { cardinal { integer: \"35\" } }` -> `35` \n", - "- `tokens { name: \"pommes\" }` -> `pommes`\n", - "\n", - "and merged into a normalized string:\n", - "\n", - "`le 1ᵉʳ juillet il a mangé 35 pommes`\n", - "\n", - "With the equivalent TN task being the reverse process. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_n-5JExAbvwr" - }, - "source": [ - ">**_Note:_**\n", - ">A few things to note specific to inverse text normalization: \n", - ">- Each class token has a unique set of field names that must be parsed by the classifier. The default field names for NeMo are chosen to mirror the syntax in [Sparrowhawk](https://github.com/google/sparrowhawk) to enable deployment. If these fields are not exact, you will not be able to use Sparrowhawk.\n", - ">- NeMo assumes no punctuation (unless explicitly provided in the grammar) and all lower casing to ease integration with upstream ASR.\n", - ">- The `name` class token is default for any token that does not require processing. It will be left 'as is.'\n", - ">- You may note how the tokenizer performed the conversion of `premier` to `1` while the verbalizer normalized `1` -> `1ᵉʳ`. Such decisions are implementation dependent and will vary depending on preference and language. (That is, normalization from `premier` -> `1ᵉʳ` could have been a tokenization step.)\n", - ">- By default, NeMo will create several permutations of key values in a token to ease normalization. That is, given the token `tokens { date { day: \"1\" month: \"juillet\" } }`, it will also produce paths for `tokens { date { month: \"juillet\" day: \"1\" } }`. To prevent this and avoid ambiguity in verbalizer input, tokens can be assigned a `preserve_order` attribute to prevent permutation. (e.g. `tokens { date { day: \"1\" month: \"juillet\" preserve_order: true } }`) (We will discuss this [later in the tutorial](#verbalizer).)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## WFST Classes" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "NeMo Text Processing's base languages supports a range of semiotic classes to permit integration with Sparrowhawk.\n", - "For this tutorial, we will be focusing on the following classes:\n", - "- CARDINAL\n", - "- ORDINAL\n", - "- DECIMAL\n", - "- MONEY\n", - "- TIME\n", - "- WHITELIST\n", - "- WORD\n", - "- PUNCTUATION\n", - "\n", - "While not comprehensive, these classes will provide enough foundation and exposure to edge cases that you will feel comfortable constructing for other cases.\n", - "\n", - "**NOTE**: *If you intend to only develop for personal use with NeMo, you may rename these classes as desired. However, Sparrowhawk integration\n", - "REQUIRES use of only these tags and their assigned attributes. For list of Sparrowhawk tokens and attributes, [consult the Sparrowhawk repository](https://github.com/yzhang123/sparrowhawk/blob/test/src/proto/semiotic_classes.proto)*" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Further Reading" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If you wish to learn more about NeMo Text Processing, you may wish to consult the following:\n", - "- [Y. Zhang, E. Bakhturina, K. Gorman, and B. Ginsburg, \"NeMo Inverse Text Normalization: From Development To Production\"](https://arxiv.org/pdf/2104.05055.pdf)\n", - "- [NeMo's Text Normalization Documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/intro.html) \n", - "- [NeMo's Text Normalization Deployment Documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/wfst_text_processing_deployment.html)\n", - "- NeMo's [Text Normalization Introduction Tutorial](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/Text_Normalization.ipynb)\n", - "- [Sparrowhawk Documentation](https://github.com/google/sparrowhawk)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For further information regarding WFSTs, please see:\n", - "- [D. Jufasky and J. Martin, *Natural Language Processing*, Ch. 2](https://web.stanford.edu/~jurafsky/slp3/2.pdf)\n", - "- [K. Gorman and R. Sproat, *Finite-State Text Processing*](http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?products_id=1636)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XFdXRcnUfI25" - }, - "source": [ - "# Getting Started \n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "K3Zl3VwqdYqL" - }, - "source": [ - "To begin tokenizer development, make sure you have [installed NeMo from source](https://github.com/NVIDIA/NeMo)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rGg7Bf13FXgc" - }, - "source": [ - "For this tutorial, we will focus on developing an Inverse Text Normalization system, such as one you may encounter in downstream ASR processing. As such, we will navigate to\n", - "`nemo_text_processing/inverse_text_normalization` and create a directory for our target language (French) and subdirectories\n", - "for `taggers` and `verbalizers`. You may also wish to create a `data` subdirectory to ease navigation.\n", - "\n", - "(Note, for text normalization, the suggested directory structure would be the same within the `nemo_text_processing/text_normalization` folder. In fact, many of NeMo's grammars actively share between.)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "T58E4pU4FN3A" - }, - "source": [ - "```bash\n", - "git clone https://github.com/NVIDIA/NeMo\n", - "cd NeMo && ./reinstall.sh\n", - "cd nemo_text_processing/inverse_text_normalization/\n", - "export LANGUAGE=fr # Change this to your desired language\n", - "mkdir $LANGUAGE\n", - "mkdir $LANGUAGE/taggers\n", - "mkdir $LANGUAGE/verbalizers\n", - "mkdir $LANGUAGE/data\"\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "O1vfz-bUFpwz" - }, - "source": [ - "All WFSTs deployed in NeMo inherit from the `GraphFst` class.\n", - "While in most cases you can simply import from a pre-existing `graph_utils.py`, you may occasionally find it helpful for deployment to keep a copy \n", - "in your working directory for language specific edits. (For our purposes, we will be utilizing `nemo_text_processing.text_normalization.en.graph_utils`, which serves as default for NeMo's grammars.)\n", - "\n", - "You may also wish to keep a copy of `utils.py` (found in each language system's directory)\n", - "in your working directory to assist with pathing. (Make sure to adjust the imports towards your language.)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "3OME84EmOQ4h", - "outputId": "6eea17f9-aae9-4176-ae35-3d1f0e94b4ea" - }, - "source": [ - "```bash\n", - "cp ../text_normalization/en/graph_utils.py $LANGUAGE/\n", - "cp ../text_normalization/en/utils.py $LANGUAGE/\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Dependencies" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For development, we utilize `nemo_text_processing` and `pynini` (a Python library for efficient WFST construction and traversal, installed with `nemo` by default). " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "While this tutorial will attempt to make use of `pynini` tools transparent, it does assume some familiarity with its syntax. For a more in-depth guide, the following will provide a function overview:\n", - "\n", - "- [K. Gorman, Pynini: A Python library for weighted finite-state grammar compilation](https://aclanthology.org/W16-2409.pdf)\n", - "- [Pynini Documentation](https://www.openfst.org/twiki/bin/view/GRM/PyniniDocs) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will also import the `pynutil` module for access to some extra functionality, along with writing a simple helper function for printing `pynini` graphs through the previously discussed 'shortest-path' heuristic." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "sz18Ui8-8Kf4" - }, - "outputs": [], - "source": [ - "from pynini.lib import pynutil\n", - "\n", - "def apply_fst(text, fst):\n", - " \"\"\" Given a string input, returns the output string\n", - " produced by traversing the path with lowest weight.\n", - " If no valid path accepts input string, returns an\n", - " error.\n", - " \"\"\"\n", - " try:\n", - " print(pynini.shortestpath(text @ fst).string())\n", - " except pynini.FstOpError:\n", - " print(f\"Error: No valid output with given input: '{text}'\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Cardinal WFST " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rOyLZb9DgLoh" - }, - "source": [ - "The vast majority of ITN tasks require the ability to recognize and denormalize numbers. As such, we will begin with developing a Classifier and Verbalizer for Cardinal (integer) numbers. (e.g. `-3,-2,-1,0,1,2,3,4,5....99,100,101...`)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9GZQkH1V89kh" - }, - "source": [ - "## Grammar" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will begin by first constructing a Cardinal WFST, using French as an example language. While your target language will obviously differ greatly from our example, you will likely find some several similarities, such as:\n", - "- Use of a (semi) regular decimal (base-10) counting system. (A common - but not universal - feature of natural languages.)\n", - "- Incorporation of several irregularities requiring contingencies in our WFST construction. (e.g. a pseudo vigesimal (base-20) series.)\n", - "- Use of gender and number agreement in enumeration." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Digits" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "NzJ2DIwc_TT3" - }, - "source": [ - "We shall begin with the first decimal place. As these numbers serve as the building blocks for the rest of our WFST, we shall begin by explicitly calling their WFST mappings with `pynini.string_map`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "u0H4qg4BjYfB" - }, - "outputs": [], - "source": [ - "zero = pynini.string_map([(\"zéro\",\"0\")]) # French only pronounces zeroes as stand alone\n", - "digits = pynini.string_map([ # pynini function that creates explicit input-output mappings for a WFST\n", - "\t\t\t\t(\"un\",\"1\"),\n", - "\t\t\t\t(\"une\",\"1\"),\n", - "\t\t\t\t(\"deux\",\"2\"),\n", - "\t\t\t\t(\"trois\",\"3\"),\n", - "\t\t\t\t(\"quatre\",\"4\"),\n", - "\t\t\t\t(\"cinq\",\"5\"),\n", - "\t\t\t\t(\"six\",\"6\"),\n", - "\t\t\t\t(\"sept\",\"7\"),\n", - "\t\t\t\t(\"huit\",\"8\"),\n", - "\t\t\t\t(\"neuf\",\"9\")\n", - "])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0nHjY-NNjdWQ" - }, - "source": [ - "We may also simply write a `tsv` file in a separate data folder " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- zéro\t0\n", - "- un\t1\n", - "- une\t1\n", - "- deux\t2\n", - "- trois\t3\n", - "- quatre\t4\n", - "- cinq\t5\n", - "- six\t6\n", - "- sept\t7\n", - "- huit\t8\n", - "- neuf\t9" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xicKcZLEzQTg" - }, - "source": [ - "and import with `string_file`" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`digits = pynini.string_file(\"data/digits.tsv\")`\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If utils.py is in working directory you may also use `get_abs_path`, which will always call paths relative to your {LANGUAGE} directory:\n", - "\n", - "`from nemo_text_processing.inverse_normalization.{LANGUAGE}.utils import get_abs_path`\n", - "\n", - "`digits = pynini.string_file(get_abs_path(\"data/digits.tsv\"))`" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yPccmicQkYAB" - }, - "source": [ - "While we will use `string_map` throughout this tutorial, please note that NeMo employs the later option for maintainability and recommends its use instead." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Teens" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FQJiJcVMrNmC" - }, - "source": [ - "Let us consider our next set of numbers:\n", - "- 10 - dix\n", - "- 11 - onze\n", - "- 12 - douze\n", - "- 13 - treize\n", - "- 14 - quatorze\n", - "- 15 - quinze\n", - "- 16 - seize\n", - "- 17 - dix-sept\n", - "- 18 - dix-huit\n", - "- 19 - dix-neuf\n", - "\n", - "Like before, we can simply use `string_map` to compose a WFST for them. But note how there is some redundancy in the number set: `17`, `18`, and `19` are all of the form `dix + digit`. It would be more efficient simply to reuse our prior WFST in these cases than simply creating new arcs, states, and weights. \n", - "\n", - "We can achieve this using pynini's string concatenation function to extend the accepted input strings. First we will create an WFST for `11-16`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "orSgBwyXsfY5" - }, - "outputs": [], - "source": [ - "teens = pynini.string_map([\n", - "\t\t\t\t(\"onze\",\"11\"),\n", - "\t\t\t\t(\"douze\",\"12\"),\n", - "\t\t\t\t(\"treize\",\"13\"),\n", - "\t\t\t\t(\"quatorze\",\"14\"),\n", - "\t\t\t\t(\"quinze\",\"15\"),\n", - "\t\t\t\t(\"seize\",\"16\"),\n", - "])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "s1yIgigdtriQ" - }, - "source": [ - "Now, we will create a `tens` WFST that is responsible for mapping all instances of \"dix\" and concatenate (accomplished with the overloaded `+` operator) with the prior `digits` WFST. (Deleting any possible hyphens in-between with a build in `delete_hyphen`.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "CzwZrFCkt87W" - }, - "outputs": [], - "source": [ - "tens = pynini.string_map([(\"dix\", \"1\")])\n", - "delete_hyphen = pynini.closure(pynutil.delete(\"-\"), 0, 1) # Applies a closure from 0-1 of operation. Equivalent to regex /?/\n", - "\n", - "graph_tens = tens + delete_hyphen + digits" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2knCwybmuTDn" - }, - "source": [ - "We now can combine the `teens` and `graph_tens` WFST together through the union operation (done with the overloaded `|` operator), allowing our choice of either graph." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "WIRJ4PE7uRrl" - }, - "outputs": [], - "source": [ - "graph_tens_and_teens = graph_tens | teens" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TGkzKoeuxbeA" - }, - "source": [ - "Let's see if it works through the string function:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "v2iD0_HnxdUV", - "outputId": "1d8f434f-ff8a-4c85-b8d0-1127e4587ddf" - }, - "outputs": [], - "source": [ - "apply_fst(\"dix-huit\", graph_tens_and_teens)\n", - "apply_fst(\"seize\", graph_tens_and_teens)\n", - "apply_fst(\"dix\", graph_tens_and_teens)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Yh2f-3rux8_2" - }, - "source": [ - "The first two worked, but why did we get an error with \"dix\"? If you look back, you'll notice that while our graph has a mapping from \"dix\" to `1` - the concatenation with `digits` makes the assumption that some input from those strings will follow. That is, we left no opportunity for an *omission* of `digits`.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "OM_eJYlV1UVp" - }, - "source": [ - "![dix_to_digits.png](images/dix_to_digits.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "M4xCMKRA1Wzw" - }, - "source": [ - "You may also note that this issue would hold also if we wanted to normalize only digits - our graph would error out since it's expecting a `tens` or input first. \n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XJHnlJCm1dPv" - }, - "source": [ - "We can fix both of these problems by allowing an option to simply insert a zero without any extra input. (Much like our \"cent\" example.)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9_vvJ9Bl1dYQ" - }, - "source": [ - "![dix_to_digits_with_insert.png](images/dix_to_digits_with_insert.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "hJq3uoMN2OcC" - }, - "source": [ - "This may be accomplished through use of the `pynutil.insert` function:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "7h9xuNfA081P" - }, - "outputs": [], - "source": [ - "graph_digits = digits | pynutil.insert(\"0\") # inserts zero if no digit follows" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "fA_L_6Ky2SHm" - }, - "source": [ - "And for `graph_tens`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "jelVA81o2RXu" - }, - "outputs": [], - "source": [ - "tens = tens | pynutil.insert(\"0\") | tens + delete_hyphen\n", - "graph_tens = tens + graph_digits" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Gb5uhpGr3I4X" - }, - "source": [ - "Bringing everything together:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "bLkDddkA3Stu" - }, - "outputs": [], - "source": [ - "graph_teens_and_tens = graph_tens | teens\n", - "graph_all = graph_teens_and_tens | zero " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "DESDKScv3r3P" - }, - "source": [ - "Let us now check our tests:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "7wrDNXuD3oh9", - "outputId": "661d2526-5aa0-4640-9285-bca15cd56c75" - }, - "outputs": [], - "source": [ - "apply_fst(\"dix-huit\", graph_all) \n", - "apply_fst(\"seize\" , graph_all)\n", - "apply_fst(\"dix\" , graph_all) \n", - "apply_fst(\"une\" , graph_all) \n", - "apply_fst(\"trois\" , graph_all) \n", - "apply_fst(\"quatre\" , graph_all) \n", - "apply_fst(\"zéro\" , graph_all)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Tz_k3NoB66Bv" - }, - "source": [ - "Now we have no more error - albeit at the cost of leading zeroes. (We will take care of this later in the section.)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Tens" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2dJZAhE57an3" - }, - "source": [ - "Now that we've taken care of the teens, we can proceed with the rest of the tens. Like many languages, French employs a (fairly) regular schema of: `tens_digit + ones_digit` for 20-100. Indeed, we can summarize 20-69 in the following template:\n", - "\n", - "- 20 - vingt\n", - "- 21 - vingt-et-un\n", - "- 22 - vingt-deux\n", - "- 23 - vingt-trois\n", - "- 24 - vingt-quatre\n", - "- 25 - vingt-cinq\n", - "- 26 - vingt-six\n", - "- 27 - vingt-sept\n", - "- 28 - vingt-huit\n", - "- 29 - vingt-neuf\n", - "- 30 - trente\n", - "- 31 - trente-et-un\n", - "- 32 - trente-deux\n", - "- 33 - trente-trois\n", - "...\n", - "- 40 - quarante\n", - "...\n", - "- 50 - cinquante\n", - "...\n", - "- 60 - soixante\n", - "..." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "BuaxVG35UKcs" - }, - "source": [ - "Expanding `tens` is fairly easy to accommodate this template: we simply extend our earlier `string_map` for the new terms in the 'tens place.' From there, we once again concatenate the `digits` WFST (along with a simple WFST to delete the occurrence of the \"-et-\" term that occasionally occurs.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "qAnXlRkR32wt" - }, - "outputs": [], - "source": [ - "tens = pynini.string_map([\n", - "\t\t\t\t(\"dix\", \"1\"),\n", - "\t\t\t\t(\"vingt\",\"2\"),\n", - "\t\t\t\t(\"trente\",\"3\"),\n", - "\t\t\t\t(\"quarante\",\"4\"),\n", - "\t\t\t\t(\"cinquante\",\"5\"),\n", - "\t\t\t\t(\"soixante\",\"6\"),\n", - "\t\t])\n", - "\n", - "graph_et = pynutil.delete(\"-et-\")\n", - "\n", - "tens = tens | pynutil.insert(\"0\") | tens + pynutil.delete(\"-\") | tens + graph_et\n", - "\n", - "graph_tens = tens + graph_digits\n", - "graph_teens_and_tens = graph_tens | teens\n", - "graph_all = graph_teens_and_tens | zero " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-hJwqPDx8I2R" - }, - "source": [ - "#### Special Cases: 70-99" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zvBLvJdY9XPA" - }, - "source": [ - "However, things get tricky once we go beyond the 60s. Here, standard French possesses a notorious psuedo-vigecimal (base-20) system. For numbers 70-99:\n", - "\n", - "- 70 - soixante-dix <- Literally in English: \"sixty-ten\"\n", - "- 71 - soixante-et-onze <- Literally in English: \"sixty-and-eleven\"\n", - "- 72 - soixante-douze\n", - "- 73 - soixante-treize\n", - "- 74 - soixante-quatorze\n", - "- 75 - soixante-quinze\n", - "- 76 - soixante-seize\n", - "- 77 - soixante-dix-sept\n", - "- 78 - soixante-dix-huit\n", - "- 79 - soixante-dix-neuf\n", - "- 80 - quatre-vingts <- Literally in English: \"four-twenties\"\n", - "- 81 - quatre-vingt-un\n", - "- 82 - quatre-vingt-deux\n", - "- 83 - quatre-vingt-trois\n", - "- 84 - quatre-vingt-quatre\n", - "- 85 - quatre-vingt-cinq\n", - "- 86 - quatre-vingt-six\n", - "- 87 - quatre-vingt-sept\n", - "- 88 - quatre-vingt-huit\n", - "- 89 - quatre-vingt-nuef\n", - "- 90 - quatre-vingt-dix <- Literally in English: \"four-twenties-ten\"\n", - "- 91 - quatre-vingt-onze\n", - "- 92 - quatre-vingt-douze\n", - "- 93 - quatre-vingt-treize\n", - "- 94 - quatre-vingt-quatorze\n", - "- 95 - quatre-vingt-quinze\n", - "- 96 - quatre-vingt-seize\n", - "- 97 - quatre-vingt-dix-sept\n", - "- 98 - quatre-vingt-dix-huit\n", - "- 99 - quatre-vingt-dix-neuf" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HQNiwFDyVV_3" - }, - "source": [ - "As before, we want to take advantage of as much redundancy as we can without creating additional ambiguities that will impede graph traversal. \n", - "\n", - "We first note that - despite repeating prior words - \"quatre-vingt\" can be mapped to `8` without introducing ambiguity. This is because, despite \"quatre\" and \"vingt\" being present in our prior graphs, our WFST has no pathing for them in this exact order. As such, we can simply add it to `tens` and immediately improve our coverage for 81-89. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "AvJqaHhE9Wbd" - }, - "outputs": [], - "source": [ - "tens = pynini.string_map([\n", - "\t\t\t\t(\"dix\", \"1\"),\n", - "\t\t\t\t(\"vingt\",\"2\"),\n", - "\t\t\t\t(\"trente\",\"3\"),\n", - "\t\t\t\t(\"quarante\",\"4\"),\n", - "\t\t\t\t(\"cinquante\",\"5\"),\n", - "\t\t\t\t(\"soixante\",\"6\"),\n", - " (\"quatre-vingt\", \"8\")\n", - "\t\t])\n", - "tens = tens | pynutil.insert(\"0\") | tens + delete_hyphen | tens + graph_et\n", - "graph_tens = tens + graph_digits\n", - "graph_teens_and_tens = graph_tens | teens\n", - "graph_all = graph_teens_and_tens | zero " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0_DtcpZxZTzX" - }, - "source": [ - "Of course, now we permit the occurrence of:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "V2leANlDhCvj", - "outputId": "db8d5d02-c848-4e50-df23-d8499538281c" - }, - "outputs": [], - "source": [ - "apply_fst(\"quatre-vingt\", graph_all)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_X_ef3sihCHH" - }, - "source": [ - "which is invalid (French uses the plural \"quatre-vingt**s**\" here.) " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vgKT903Y6rIQ" - }, - "source": [ - "Should we alter the grammar because of this? Such a decision will largely be dependent on your intended implementation and design aims. If you see the question of 'legal' tokens as a responsibility of your upstream model, then there is no need for any alteration: \"quatre-vingt\" as a standalone token will simply not occur, so there is no input to be concerned with.\n", - "\n", - "However, if your ITN grammars are developed for an environment with low-fidelity ASR and/or where mistaken transcriptions incur heavy loss (e.g. ASR for driving directions, telephone-numbers, banking) then you may wish to err on the side of caution." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Hf_FghLT7jdY" - }, - "source": [ - "If we wanted to go for the latter, we would want to mark that \"quatre-vingts\" maps **only** to `80`. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "JliFTF3mZSsJ" - }, - "outputs": [], - "source": [ - "quatre_vingt_plural = pynini.string_map([\n", - " (\"quatre-vingts\", \"80\")\n", - "\t\t])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "81_b3XPbicT1" - }, - "source": [ - "And that \"quatre vingt\" can only accompany non-zero digits:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "E4_dmg6uin2j" - }, - "outputs": [], - "source": [ - "quatre_vingt_singular = pynini.string_map([\n", - " (\"quatre-vingt-\", \"8\") # Note that the hyphen can be assumed now\n", - "\t\t])\n", - "graph_digits_without_zero = pynini.string_map([\n", - "\t\t\t\t(\"un\",\"1\"),\n", - "\t\t\t\t(\"une\",\"1\"),\n", - "\t\t\t\t(\"deux\",\"2\"),\n", - "\t\t\t\t(\"trois\",\"3\"),\n", - "\t\t\t\t(\"quatre\",\"4\"),\n", - "\t\t\t\t(\"cinq\",\"5\"),\n", - "\t\t\t\t(\"six\",\"6\"),\n", - "\t\t\t\t(\"sept\",\"7\"),\n", - "\t\t\t\t(\"huit\",\"8\"),\n", - "\t\t\t\t(\"neuf\",\"9\")\n", - "])\n", - "graph_eighties = (quatre_vingt_singular + graph_digits_without_zero) | quatre_vingt_plural" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "mL7jpekV8VgP" - }, - "source": [ - "For the `70`'s and `90`'s, we would likewise need to form exclusive configurations for their number series, rewriting digits to recognize \"onze\", \"douze\", \"treize\"... as `1,2,3....` (Note, we'll have to separate `71` and `91` to manage \"soixante-**et**-onze\" vs. \"quatre-vingt-onze\".)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "y3dYkwK29zCX" - }, - "outputs": [], - "source": [ - "seventy_and_ninety = pynini.string_map([\n", - " (\"soixante-dix\", \"70\"),\n", - " (\"quatre-vingt-dix\", \"90\"),\n", - "\t\t])\n", - "\n", - "seventy_and_ninety_tens = pynini.string_map([\n", - " (\"soixante-\", \"7\"),\n", - " (\"quatre-vingt-\", \"9\"),\n", - "\t\t])\n", - "\n", - "seventy_and_ninety_one = pynini.string_map([\n", - " (\"soixante-et-onze\", \"71\"),\n", - " (\"quatre-vingt-onze\", \"91\"),\n", - "\t\t])\n", - "\n", - "seventy_and_ninety_digits = digits = pynini.string_map([ \n", - "\t\t\t\t(\"douze\",\"2\"),\n", - "\t\t\t\t(\"treize\",\"3\"),\n", - "\t\t\t\t(\"quatorze\",\"4\"),\n", - "\t\t\t\t(\"quinze\",\"5\"),\n", - "\t\t\t\t(\"seize\",\"6\"),\n", - "\t\t\t\t(\"dix-sept\",\"7\"), # For 97-99, digits are used as normal.\n", - "\t\t\t\t(\"dix-huit\",\"8\"),\n", - "\t\t\t\t(\"dix-neuf\",\"9\")\n", - "])\n", - "\n", - "graph_seventies_and_nineties = (seventy_and_ninety_tens + seventy_and_ninety_digits) | seventy_and_ninety | seventy_and_ninety_one " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4NCrCwEH9HVg" - }, - "source": [ - "Now we union them with our original `tens` series:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "psGCgxaH-btn" - }, - "outputs": [], - "source": [ - "tens = pynini.string_map([\n", - "\t\t\t\t(\"dix\", \"1\"),\n", - "\t\t\t\t(\"vingt\",\"2\"),\n", - "\t\t\t\t(\"trente\",\"3\"),\n", - "\t\t\t\t(\"quarante\",\"4\"),\n", - "\t\t\t\t(\"cinquante\",\"5\"),\n", - "\t\t\t\t(\"soixante\",\"6\"),\n", - "\t\t])\n", - "tens = tens | pynutil.insert(\"0\") | tens + delete_hyphen | tens + graph_et\n", - "\n", - "graph_tens = tens + graph_digits\n", - "graph_tens_with_special_cases = graph_tens | graph_seventies_and_nineties | graph_eighties\n", - "graph_teens_and_tens = graph_tens_with_special_cases | teens\n", - "graph_all = graph_teens_and_tens | zero " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xWjSAGRX_s0H" - }, - "source": [ - "Making sure test cases work:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "kapWmgos-xcn", - "outputId": "5e9c6f5c-1450-495f-cadf-2945355b651c" - }, - "outputs": [], - "source": [ - "apply_fst(\"quatre-vingt-treize\" , graph_all)\n", - "apply_fst(\"quatre-vingts\", graph_all)\n", - "apply_fst(\"quatre-vingt-deux\", graph_all)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "hNUepfKZ_vS_" - }, - "source": [ - "And the other cases fail as expected:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "wo2pCOXGAgYn", - "outputId": "0bbe2792-8bc9-40f7-dd28-4745bd1390e3" - }, - "outputs": [], - "source": [ - "apply_fst(\"quatre-vingt\", graph_all)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4VPuCTTtigh-" - }, - "source": [ - "Of course, there are other ways we could have reconfigured the grammar: we could simply make specific graphs for multiples of ten (`10,20,30..`) and all cases where \"-et-\" occurs (`21,31,41,51...91`). \n", - "\n", - "But this ignores a more important question: was any of this necessary in the first place? All these extra grammars did was simply expand coverage for thirty additional cardinals. And they still didn't exclude all faulty inputs! Note the following cases:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "KICvpeewCFyH", - "outputId": "174dd910-7329-4a5f-a5b0-5e796a174217" - }, - "outputs": [], - "source": [ - "apply_fst(\"dix-une\", graph_all) # supposed to be \"onze\"\n", - "apply_fst(\"dix-deux\", graph_all) # supposed to be \"douze\"\n", - "apply_fst(\"vingt-un\", graph_all) # supposed to be \"vingt-et-un\"\n", - "apply_fst(\"trente-un\", graph_all) # supposed to be \"trente-et-un\"" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0D130jIVCLp2" - }, - "source": [ - "We *still* need to address possible edge cases!\n", - "\n", - "All of this is to say that knowing your input domain before construction is imperative, as small decisions can easily determine your output range later down the line.\n", - "\n", - "Indeed, if you're particularly concerned with limiting input possibilities, it may be valid simply to write all unique options within a `string_map`. While a tad inelegant, it certainly assists in controlling your outputs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "RSp9w5ayA9ii" - }, - "outputs": [], - "source": [ - "graph_tens_special = pynini.string_map([\n", - "\t\t\t\t(\"soixante-dix\", \"70\"),\n", - "\t\t\t\t(\"soixante-et-onze\",\"71\"),\n", - " (\"soixante-douze\",\"72\"),\n", - "\t\t\t\t(\"soixante-treize\",\"73\"),\n", - "\t\t\t\t(\"soizante-quatorze\",\"74\"),\n", - "\t\t\t\t(\"soixante-quinze\",\"75\"),\n", - "\t\t\t\t(\"soixante-seize\",\"76\"),\n", - " (\"soixante-dix-sept\",\"77\"),\n", - " (\"soixante-dix-huit\",\"78\"),\n", - "\t\t\t\t(\"soixante-dix-neuf\",\"79\"),\n", - " (\"quatre-vingts\", \"80\"),\n", - " (\"quatre-vingt-un\", \"81\"),\n", - " (\"quatre-vingt-une\", \"81\"),\n", - "\t\t\t\t(\"quatre-vingt-deux\",\"82\"),\n", - " (\"quatre-vingt-trois\",\"83\"),\n", - " (\"quatre-vingt-quatre\",\"84\"),\n", - " (\"quatre-vingt-cinq\",\"85\"),\n", - " (\"quatre-vingt-six\",\"86\"),\n", - " (\"quatre-vingt-sept\",\"87\"),\n", - " (\"quatre-vingt-huit\",\"88\"),\n", - " (\"quatre-vingt-neuf\",\"89\"),\n", - " (\"quatre-vingt-dix\",\"90\"),\n", - " (\"quatre-vingt-onze\",\"91\"),\n", - " (\"quatre-vingt-douze\",\"92\"),\n", - " (\"quatre-vingt-treize\",\"93\"),\n", - " (\"quatre-vingt-quatorze\",\"94\"),\n", - " (\"quatre-vingt-quinze\",\"95\"),\n", - " (\"quatre-vingt-sieze\",\"96\"),\n", - " (\"quatre-vingt-dix-sept\",\"97\"),\n", - " (\"quatre-vingt-dix-huit\",\"98\"),\n", - " (\"quatre-vingt-dix-neuf\",\"99\"),])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "NUPs1qOUg-hE" - }, - "source": [ - "Which is more efficient? Once again, it is dependent on your language and implementation. If we simply visualize each graph and their number of states:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "sQ9GsIkNzxsU", - "outputId": "d70ca927-9c43-4f49-846c-c181e725e011" - }, - "outputs": [], - "source": [ - "constructed_version = (graph_seventies_and_nineties | graph_eighties)\n", - "constructed_version.num_states()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "Xsgdu5TYx09_", - "outputId": "5812912f-883b-42e8-afbf-3ec4a0170345" - }, - "outputs": [], - "source": [ - "string_map_version = graph_tens_special\n", - "string_map_version.num_states()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9jzn_U7s0Sit" - }, - "source": [ - "We see that their number of states (graph vertexes) are almost equal. Yet, if we use `pynini.optimize` - a method that calls a suite of WFST minimization algorithms: " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "7YtqhOY90iF0", - "outputId": "26f0f51b-b00d-4f5a-9b2f-330c9812666a" - }, - "outputs": [], - "source": [ - "constructed_version.optimize()\n", - "constructed_version.num_states()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "y93SqnOf0qa8", - "outputId": "74efcbfa-a272-4fc6-e36e-f1e31c6df221" - }, - "outputs": [], - "source": [ - "string_map_version.optimize()\n", - "string_map_version.num_states()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2cTdQj9L0xhl" - }, - "source": [ - "We see the latter possessing a significantly larger amount of graph vertices. \n", - "\n", - "So the decision will be dependent on your ITN needs, language, concern with efficiency, and design philosophy. Further, even decisions of language dialect will have an influence. \n", - "(e.g. Belgian, Canadian, and Swiss dialects of French will dispense with elements of the vigecimal system for the decimal schema.)\n", - "\n", - ">**_Note:_** \n", - ">while `nemo_text_processing` grammars aim to minimize invalid productions, they assume input tokens are valid strings for a target language. (e.g. The mapping of \"quatre-vingt\" to `80` is permitted since it is not likely to occur in a valid French string.)* " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "V1djCnvY3CjW" - }, - "source": [ - "For more information on optimization algorithms for WFSTs, please see:\n", - "\n", - "- [M. Mohri,\"Generic epsilon-removal and input epsilon-normalization algorithms for weighted transducers\"](https://cs.nyu.edu/~mohri/pub/ijfcs.pdf)\n", - "- [M. Mohri, \"Weighted automata algorithms\"](https://cs.nyu.edu/~mohri/pub/hwa.pdf)\n", - "- [K. Thompson, \"Programming techniques: regular expression search algorithm\"](http://www.oilshell.org/archive/Thompson-1968.pdf)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Hundreds\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dqPUdVBbi6gU" - }, - "source": [ - "\n", - "Moving on to the case of three digit cardinals (\"hundreds\"), it is likely that your chosen language becomes more regular in its schema. For instance, practically all French numbers `>100` obey the following:\n", - "\n", - "- `digit_from_1_to_9 + word_for_hundred + digit_from_1_to_99`\n", - "\n", - "For example:\n", - "- `203` - \"deux-cent-trois\"\n", - "- `530` - \"cinq-cent-trente\"\n", - "- `880` - \"huit-cent-quatre-vingt\"\n", - "\n", - "As such, we can write a simple `hundreds` WFST as:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "lOt-gc-FiF-X" - }, - "outputs": [], - "source": [ - "hundreds = graph_digits + delete_hyphen + pynutil.delete(\"cent\") + delete_hyphen + graph_all" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "Fyn1uL_NoEiz", - "outputId": "d491680b-1b3e-4762-8470-497833b82b0e" - }, - "outputs": [], - "source": [ - "apply_fst(\"deux-cent-trois\", hundreds)\n", - "apply_fst(\"huit-cent-quatre-vingts\", hundreds)\n", - "apply_fst(\"cinq-cent-trente\" , hundreds) " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qDjq_KfnoD5C" - }, - "source": [ - "Indeed, the use of French only presents two complications:\n", - "- French uses *only* the word \"cent\" for `100`. (Instead of \"un cent\".)\n", - "- 'Pure' multiples of a hundred (`200,300,400....`) use the plural \"cents\".\n", - "\n", - "The second one is the easier of the two so let's start there. There are actually two options open to us. First, we could treat \"cents\" the same way as we did \"cent\" in the base case and simply delete it. From there, the lack of any following inputs will allow the WFST to insert the trailing zeroes as appropriate." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "m2F-sumbxqLE" - }, - "outputs": [], - "source": [ - "cents = pynini.accep(\"cent\") | pynini.accep(\"cents\") # Creates a Finite State (Accep)tor, mapping inputs back to themselves\n", - "hundreds = graph_digits + delete_hyphen + pynutil.delete(cents) + delete_hyphen + graph_all" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "VisQu_Etx-QB" - }, - "source": [ - "Or we can use it as a cue to 'shortcut' the WFST to immediately insert zeroes." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "VspiTN5Vxxjl" - }, - "outputs": [], - "source": [ - "graph_cents = pynini.cross(\"cents\", \"00\") # Creates a single input-output mapping\n", - "hundreds = graph_digits + delete_hyphen + ((pynutil.delete(\"cent\") + delete_hyphen + graph_all) | graph_cents)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "meVn5BiyyX5v" - }, - "source": [ - "For the case of solitary \"cent\", we need to make sure our output is `1` only in the case that no digit precedes the occurrence. Here we need to be confident in the structure of our WFST and that any possible ambiguity has been dealt with by this point. (Something to keep in mind as we move to the thousands.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "277Z-zLWyWAf" - }, - "outputs": [], - "source": [ - "graph_cent = pynini.cross(\"cent\", \"1\")\n", - "graph_hundreds_first_digit = (graph_digits + delete_hyphen + pynutil.delete(cents)) | graph_cent\n", - "graph_hundreds = graph_hundreds_first_digit + delete_hyphen + graph_all" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "FNZlJsvS_Yvt", - "outputId": "e85ae561-e7a1-4b6a-e394-f0194fdb89e7" - }, - "outputs": [], - "source": [ - "apply_fst(\"trois-cents\", graph_hundreds) \n", - "apply_fst(\"cent\", graph_hundreds)\n", - "apply_fst(\"cent-trois\", graph_hundreds) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Thousands" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e7Dy5slLzp-K" - }, - "source": [ - "For quite a few languages, managing the WFST for the thousands place is the last aspect to figure out, as the higher powers of ten reuse the same schema. (For those working with counting systems that reserve special terms for \"ten-thousand\" (e.g. Chinese derived counting systems), you may need to extend unique coverage to the next power of ten.)\n", - "\n", - "For French, the question of thousands is rather simple: `digits_from_1_to_999 + mille + digits_from_1_to_999`\n", - "\n", - "With only the exception that any expression of one thousand drops a leading digit. \n", - "- `1,000` -> \"mille\"\n", - "- `1,001` -> \"mille-un\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "AvsnAAiPzlu_" - }, - "outputs": [], - "source": [ - "graph_one_thousand = pynini.cross(\"mille\", \"1\")\n", - "graph_many_thousand = graph_hundreds + delete_hyphen + pynutil.delete(\"mille\")\n", - "\n", - "graph_thousands = (graph_one_thousand | graph_many_thousand) + delete_hyphen + graph_hundreds" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "i3m9TG7Y4tkl", - "outputId": "d3f1f81d-c463-4934-9df7-3b8f2b67798f" - }, - "outputs": [], - "source": [ - "apply_fst(\"cent-mille-deux-cents\", graph_thousands)\n", - "apply_fst(\"deux-cent-mille-deux-cents\", graph_thousands)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "NoevSTZGGT17" - }, - "source": [ - "### Weighting" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "A2gcVIZM0-iv" - }, - "source": [ - "Question: will this cover all our grammar so far? (Hint: what assumptions were made about \"cent\"/\"cents\"?)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "cCFtPhr1BjAc", - "outputId": "048e0d93-a4a8-4f4e-d461-bfd70e911aff" - }, - "outputs": [], - "source": [ - "apply_fst(\"deux-mille-un\", graph_thousands)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Ne-7L9Cd4t-8" - }, - "source": [ - "Once again, we need to introduce the possibility of the prior power of ten not occurring in the string. There must be an option for simply inserting a string of `0` in place of the omitted \"cent\"." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iockqXdn-aG4" - }, - "source": [ - "Further, we want to be careful with how cavalier we have been with insertions. Consider the following:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "bxJlSnj2-Xw3", - "outputId": "6722e5ef-8a7f-43e1-84fe-b3f5f18307e1" - }, - "outputs": [], - "source": [ - "apply_fst(\"mille-cent-un\", graph_thousands) # Should be 1101\n", - "apply_fst(\"mille-cent\", graph_thousands) # 1100" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "fq5zEayA-kOx" - }, - "source": [ - "It appears that our WFST has developed a tendency to simply 'ignore' some of these higher powers. Let us return to our code for `graph_hundreds` and `graph_thousands`. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "S2aV1KQ4-1iP" - }, - "outputs": [], - "source": [ - "graph_cents = pynini.cross(\"cents\", \"00\")\n", - "graph_cent = pynini.cross(\"cent\", \"1\")\n", - "graph_hundreds_first_digit = (graph_digits + delete_hyphen + pynutil.delete(cents)) | graph_cent\n", - "graph_hundreds = (graph_hundreds_first_digit + delete_hyphen | pynutil.insert(\"0\")) + graph_all \n", - "\n", - "graph_one_thousand = pynini.cross(\"mille\", \"1\")\n", - "graph_many_thousand = graph_hundreds + delete_hyphen + pynutil.delete(\"mille\")\n", - "graph_thousands = (graph_one_thousand | graph_many_thousand) + delete_hyphen + graph_hundreds" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9avwOIkk-9qt" - }, - "source": [ - "Recall that throughout we have provided options for simply inserting zeroes in the case of omitted numbers? That tendency has finally caught up with us. The use of our previous `graph_hundreds` in `graph_many_thousands` now allows our graph to insert a string of `0`'s without penalty. \n", - "\n", - "You may note that this is very similar to the \"cents\" example brought up at the beginning, presenting a similar solution. We can control this output by making it too costly to traverse unless absolutely necessary for the graph. This can be accomplished simply by appending a weight to the insertion for hundreds:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "MQG3j0U8CUAQ" - }, - "outputs": [], - "source": [ - "graph_hundreds = (graph_hundreds_first_digit + delete_hyphen | pynutil.insert(\"0\", weight=.1)) + graph_all \n", - "\n", - "graph_one_thousand = pynini.cross(\"mille\", \"1\")\n", - "graph_many_thousand = graph_hundreds + delete_hyphen + pynutil.delete(\"mille\")\n", - "graph_thousands = (graph_one_thousand | graph_many_thousand) + delete_hyphen + graph_hundreds" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "KNHhrYZ7Ca58", - "outputId": "a7d07372-733d-4837-c1e9-1dc58ba2b87c" - }, - "outputs": [], - "source": [ - "apply_fst(\"mille-cent-un\", graph_thousands)\n", - "apply_fst(\"mille-cent\", graph_thousands)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "51yPEaf2EkbD" - }, - "source": [ - "Why choose a weight of `.1`? Quite simply: it's arbitrary. As mentioned earlier, the default graph in `pynini` is a tropical semiring, which uses the `min` function to select among two arcs for path traversal. Since all our paths so far are weight `0`, any positive value will ensure that it is a last option among path traversal. (Note, this conversely entails any negative weight path will be prioritized.)\n", - "\n", - "That we chose this number as a small value comes from a place of caution: the tropical semiring uses an additive function to calculate the total weight of an entire path to traverse a WFST. As our grammars can easily become massive, this means that small weights can have major impact down the line. Further, by constraining path weights to small values, we can have general certainty towards the maximum weight of any individual graph, allowing us to add constraints regarding maximum token length and token hierarchy. (As explained in [later sections](#classifyweights).) As such, when using weights in a localized setting, it is best to use small values to avoid unforeseen escalation. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iScKgvRxGt-B" - }, - "source": [ - "### Higher Powers\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rtHEd6OE2WSg" - }, - "source": [ - "At this point, we can propose a general heuristic with escalating to higher powers of ten: they always need a way for their absence to be accommodated in the WFST. Further, they require some weighting to prevent this absence from developing into a string of omitted values. To avoid further bumps, we'll take care of this now with `graph_thousands`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "iZMN7wcE2lH5" - }, - "outputs": [], - "source": [ - "graph_one_thousand = pynini.cross(\"mille\", \"1\")\n", - "graph_many_thousand = graph_hundreds + delete_hyphen + pynutil.delete(\"mille\")\n", - "graph_thousands = (graph_one_thousand | graph_many_thousand | pynutil.insert(\"000\", weight=.001)) + delete_hyphen + graph_hundreds" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Fkc3LIH824P7" - }, - "source": [ - "\n", - "For the rest of French (and many other languages), the rest of the work is simply repeating the prior pattern for the thousands element: \n", - "`hundreds + word_for_higher_power + hundreds.....` Of course there will be some variation in this schema, but the recursion should be regular. (It is rather rare that languages appropriate unique forms for these higher counts.) " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qGnK4ARX4Nay" - }, - "source": [ - "To finish French, we can list off the following equivalent for higher powers of ten:\n", - "- `million` - \"million/millions\" \n", - "- `billion` - \"milliard/milliards\"\n", - "- `trillion` - \"billion/billions\"\n", - "\n", - "Like the \"cent/cents\" rule, these values alternate with a plural form in the case of multiples of the value. Writing them out:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "sBu7-dub4vxz" - }, - "outputs": [], - "source": [ - "millions = pynini.accep(\"million\") | pynini.accep(\"millions\")\n", - "graph_millions = ((graph_hundreds + delete_hyphen + pynutil.delete(millions) + delete_hyphen) | pynutil.insert(\"000\", weight=.1) # We need three zeroes now\n", - " ) + graph_thousands" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LmMeCHXr5Bb5" - }, - "outputs": [], - "source": [ - "billions = pynini.accep(\"milliards\") | pynini.accep(\"milliard\")\n", - "graph_billions = ((graph_hundreds + delete_hyphen + pynutil.delete(billions) + delete_hyphen)| pynutil.insert(\"000\",weight=.1) # We need three zeroes now\n", - " ) + graph_millions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "CIRIeQEg5B0J" - }, - "outputs": [], - "source": [ - "trillions = pynini.accep(\"billion\") | pynini.accep(\"billions\")\n", - "graph_trillions = ((graph_hundreds + delete_hyphen + pynutil.delete(trillions) + delete_hyphen) | pynutil.insert(\"000\",weight=.1) # We need three zeroes now\n", - " ) + graph_billions" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sRNUPx-15J1v" - }, - "source": [ - "Bringing all together:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0dLOWm_B5SwQ" - }, - "outputs": [], - "source": [ - "graph = graph_trillions | zero" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nBFE3BrN6IPR" - }, - "source": [ - "Let's try it out:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "6lWwtR1S6LI4", - "outputId": "3a6740ee-9e92-4500-c2c8-965131167e58" - }, - "outputs": [], - "source": [ - "example = \"deux-cent-milliard-quatre-million-deux-cent-quatre-vingt-onze\"\n", - "apply_fst(example, graph) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Finishing Touches" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-w3KgX6C6mff" - }, - "source": [ - "Now that we have our cardinal in place, we can take care of that stylistic issue of the leading zeroes. For this, we want to develop a 'filter' that deletes all zeroes preceding the first non-zero in the string, and leave the rest 'as is.'\n", - "\n", - "First let us create the filter by calling on `NEMO_DIGIT`- a `graph_util` WFST that only permits digits as input. With it, we'll create a WFST that will delete all leading zeroes in a sting. We then compose this (using `@`) onto our original graph, creating a new graph that accepts inputs from our original but produces only the outputs of `clean_cardinal`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 290 - }, - "id": "EA4VnRe6FO-2", - "outputId": "59e412b3-a445-4172-ee64-b0f80281a167" - }, - "outputs": [], - "source": [ - "delete_leading_zeroes = pynutil.delete(pynini.closure(\"0\")) # will delete all zeroes under closure. Equivalent to regex * operator\n", - "stop_at_non_zero = pynini.difference(NEMO_DIGIT, \"0\") # creates a graph that accepts all input-outputs from NEMO_DIGIT except 0\n", - "rest_of_cardinal = pynini.closure(NEMO_DIGIT) # accepts all digits that may follow\n", - "\n", - "clean_cardinal = delete_leading_zeroes + stop_at_non_zero + rest_of_cardinal\n", - "clean_cardinal = clean_cardinal | \"0\" # We don't want to ignore the occurrence of zero\n", - "\n", - "graph = graph @ clean_cardinal " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "piP9nqQkHpo3" - }, - "source": [ - "Now our WFST will output our numbers as normal:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "dnQ9odSpIAB7" - }, - "outputs": [], - "source": [ - "apply_fst(example, graph)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Final Notes\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "p7zt8lVsK2rY" - }, - "source": [ - "We have finally formulated a grammar that will process French cardinals into numeric representation. Of course, not every grammar you write will be for French. But several of the principles we've worked through will be invaluable in your own development. Before moving on, here's a quick summary of (almost) universal points to take away for WFST construction.\n", - "- Decide at the beginning of construction the level of constraint you wish for your grammar. Is it necessary to have a specific domain or can you rely on upstream models to narrow your input possibilities for you? \n", - "- Work iteratively upwards from the smallest place value of your numeric system. This will assist you in forming building blocks for larger values. \n", - "- Always allow for the possibility of omission of previous place values. (Not every number in the thousands will contain mention of the hundreds place.)\n", - "- For each place value, consider how the sub-grammar will affect the preceding and following place values. Are there exceptions that you've built into the grammar that may become problematic later on?\n", - "- Utilize weights for default insertions to limit path traversal to only final options. When doing so, use small values to avoid escalating problems in your larger grammar." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nvyHg1bQIIHD" - }, - "source": [ - "With that handled, we can move on to converting this grammar into a Classifier." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gJ1YJUvhIZwm" - }, - "source": [ - "## Classifier" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "q2L2x0crIeXQ" - }, - "source": [ - "Now that we have a grammar that will convert individual tokens into number strings, we now want to focus on building it into a classifier to properly tag candidate tokens. This requires a couple of properties:\n", - "- It recognizes any valid token and permits traversal through the WFST graph\n", - "- Conversely, it does not allow invalid tokens to traverse the WFST graph\n", - "- It properly disambiguates overlap among ambiguous cases\n", - "- It attributes the proper attributes to a classified token\n", - "\n", - "While this seems like a lot, in practice this just means that your grammar will need a few more tweaks to improve exclusivity." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ArEYn7RWKcYI" - }, - "source": [ - "NeMo ITN performs token classification through a series of `GraphFst` classes and assumes deployment of your grammars through an object that inherits from this class. As such, you will need to instantiate your grammar as a `CardinalFST` " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 368 - }, - "id": "GWgMSybqLqiS", - "outputId": "597c00ae-0f62-417f-888c-88c81c24a3fc" - }, - "outputs": [], - "source": [ - "class CardinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"cardinal\", kind=\"classify\")\n", - " # Rest of the grammar here\n", - " # ....... \n", - " #........." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "SIE8dNQlL52G" - }, - "source": [ - "While the naming convention may vary, the `name` and `kind` properties must be set accordingly to permit Sparrowhawk integration.\n", - "\n", - "Further, the resulting graph must produce the classified token within the following format:\n", - "`token { cardinal { integer: \"DIGIT_STRING\" } }`\n", - "\n", - "This is accomplished by a series of string insertions:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "aC_c64KSNTCg" - }, - "outputs": [], - "source": [ - "class CardinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"cardinal\", kind=\"classify\")\n", - " # Rest of the grammar here\n", - " # ....... \n", - " #.........\n", - " self.fst = pynutil.insert(\"integer: \\\"\") + graph + pynutil.insert(\"\\\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "AGLQxOSzOK1F" - }, - "source": [ - "Followed by a call of the parent `GraphFst.add_tokens()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Jz-UXFipORps" - }, - "outputs": [], - "source": [ - "class CardinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"cardinal\", kind=\"classify\")\n", - " # Rest of the grammar here\n", - " # ....... \n", - " #.........\n", - " self.fst = pynutil.insert(\"integer: \\\"\") + graph + pynutil.insert(\"\\\"\")\n", - " final_graph = self.add_tokens(graph)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gh23S7BHOY0r" - }, - "source": [ - "Which will insert the appropriate formatting. Note that this formatting must be exact: a single space must follow each field name and each value must be within escaped double quotes.\n", - "\n", - "In the event that you also wish for `CardinalFst` to indicate negative values, the optional `negative: ` property may be used.\n", - "\n", - "For instance, French indicates negative values by prefacing the quantity with \"moins.\" As such:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "3JbTn35cOx0k" - }, - "outputs": [], - "source": [ - "optional_minus_graph = pynini.closure(\n", - " pynutil.insert(\"negative: \") + pynini.cross(\"moins\", \"\\\"-\\\"\") + \" \", 0, 1 # Note the extra space to separate the value from the integer field\n", - ")\n", - "\n", - "final_graph = optional_minus_graph + pynutil.insert(\"integer: \\\"\") + graph + pynutil.insert(\"\\\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "DCs1048v6N0K" - }, - "source": [ - "All together, your `CardinalFst` ultimately serves as a wrapper for your grammar, save with the addition of a few insertions to assist processing:\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "eo6uEz1s5TJY" - }, - "outputs": [], - "source": [ - "class CardinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"cardinal\", kind=\"classify\")\n", - " \n", - " ### Cardinal Grammar....\n", - " ### .....\n", - " graph = graph_trillions | zero \n", - "\n", - " ### Formatting grammar....\n", - " ### .....\n", - " graph = graph @ clean_cardinal\n", - "\n", - " ### Token insertion\n", - " optional_minus_graph = pynini.closure(\n", - " pynutil.insert(\"negative: \") + pynini.cross(\"moins\", \"\\\"-\\\"\") + \" \", 0, 1\n", - " )\n", - "\n", - " final_graph = optional_minus_graph + pynutil.insert(\"integer: \\\"\") + graph + pynutil.insert(\"\\\"\")\n", - "\n", - " final_graph = self.add_tokens(final_graph) # inserts the cardinal tag\n", - "\n", - " self.fst = final_graph" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "MFIMdLCoZzLK" - }, - "source": [ - "Let's see a demonstration. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "4CF6Iz9NZ7R_" - }, - "outputs": [], - "source": [ - "cardinal = CardinalFst().fst\n", - "\n", - "example = \"moins deux-cent-quatre\"\n", - "\n", - "apply_fst(example, cardinal)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Verbalizer" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uvUqpC_Q8FSt" - }, - "source": [ - "The verbalizer can be both the most crucial and simplest part of building each grammar. On one hand, it is the component that finalizes all of your previous work. If it is unable to properly normalize your text, everything has been for naught.\n", - "\n", - "On the other hand, your previous work has vastly limited the unpredictability of your input. Recall from our initial demonstration of the classifier-verbalizer system that and input like <> becomes:\n", - "\n", - "- `tokens { name: \"le\" }`\n", - "- `tokens { date { day: \"1\" month: \"juillet\" }` \n", - "- `tokens { name: \"il\" }` \n", - "- `tokens { name: \"a\" }` \n", - "- `tokens { name: \"mangé\" }`\n", - "- `tokens { cardinal { integer: \"35\" } }` \n", - "- `tokens { name: \"pommes\" }`\n", - "\n", - "Part of the purpose of the two stage set-up is that the input space for each verbalizer is obvious: it's simply the name of its semiotic class. As such, we only need to write our grammar to recognize its class, remove tokens accordingly, and then manage the attributes of each semiotic token." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "et1GgmBuAWzY" - }, - "source": [ - "We will begin as we did with our classifier and create a class to inherit from the `GraphFST` utility class:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "NNKpgWtkAgEW" - }, - "outputs": [], - "source": [ - "class CardinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"cardinal\", kind=\"verbalize\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "OyAV39NsAqSN" - }, - "source": [ - "One of the useful aspects of the `GraphFst` utility is that it already possesses a built in graph that will recognize and remove semiotic tokens: `delete_tokens`. As such we need only concern ourselves with managing the properties of the Cardinal class:\n", - "- `integers`\n", - "- `negative`\n", - "\n", - "Here, the desired written format of your chosen language will dictate how you proceed. For French, we have the following rules for Cardinal numbers:\n", - "- A negative sign is written before the numeral.\n", - "- Cardinal numbers representing quantities (e.g. \"mille euros\"/ \"one thousand dollars\") are written with spaces in-between every three digits. (e.g. `1 000`)\n", - "- Cardinal numbers representing place in a sequence or addresses (\"page mille\"/\"page one thousand\") are written without spacing. (`1000`)\n", - "\n", - "The first property seems easy enough to handle: write a grammar that simply removes the `negative` formatting, leaving only `-`. (Recall that our Classifier only inserted the string if it was present.) \n", - "\n", - "For the final two, we may note that our intention to develop WFSTs for the Decimal, Measure, and Money classes already will cover most desired quantities. As such, we can leave the issue of spacing to those instances and let the Cardinal WFST default to the non-spacing case. (Note that this will be helpful with Time, Date, Telephone, Electronic, and Ordinal classes as they will not use the spacing format either. It is usually better to reserve specific formatting rules to other classes and let the Cardinal serve as a default.)\n", - "\n", - "As such, we just need our WFST to remove the `integer` property and `negative` property (if it occurs). These can be managed through the `pynutil.delete` function, as seen in the following:\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 368 - }, - "id": "6MF2I6SLU7nf", - "outputId": "0437c4af-5c96-4122-8af0-ca37723c7228" - }, - "outputs": [], - "source": [ - "class CardinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"cardinal\", kind=\"verbalize\")\n", - " \n", - " # Removes the negative attribute and leaves the sign if occurs\n", - " optional_sign = pynini.closure(\n", - " pynutil.delete(\"negative:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.accep(\"-\")\n", - " + pynutil.delete(\"\\\"\")\n", - " + delete_space,\n", - " 0,\n", - " 1,\n", - " )\n", - " \n", - " # removes integer aspect\n", - " graph = (\n", - " pynutil.delete(\"integer:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1) # Accepts at least one digit\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - " \n", - " graph = optional_sign + graph # concatenates two properties\n", - "\n", - " delete_tokens = self.delete_tokens(graph) # removes semiotic class tag\n", - "\n", - " self.fst = delete_tokens.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "QSX2KlZJbRAA" - }, - "source": [ - "Let's see if it will properly render a given token:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "JxaLm2k0bYIJ" - }, - "outputs": [], - "source": [ - "cardinal = CardinalFst().fst\n", - "example = 'cardinal { negative: \"-\" integer: \"204\" }'\n", - "\n", - "apply_fst(example, cardinal)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Bc0-QCBHWg-8" - }, - "source": [ - "That's it! We've now completed all aspects of our `CardinalFst` from grammar writing to Verbalization. While we still have quite a few semiotic classes left, you will find that they build off the `CardinalFst` quite easily, making progression much simpler and straightforward.\n", - "\n", - ">**_Note:_**\n", - ">- `delete_tokens` is called on the completed graph, despite the token class occurring first in the tokenized string. This is because the function intersects with an initial WFST that deletes the tags. As such, the function must be passed a completed graph.\n", - ">- In our initial example, all tokens were enclosed within a `token` category. Insertion and deletion of this category is managed by the main [Classifier](#tokenize-and-classify) and [Verbalizer](#verbalize-and-verbalize-final) respectively and is not a concern during individual class grammar development.\n", - ">- Earlier in the tutorial we noted that NeMo ITN permutates all WFSTs unless the `preserve_order` tag is passed as part of the Classifier. This allows you to ignore possible variation in designing the verbalizer and focus on whatever form of processing is easiest for the grammar. That is, the decision to process the `negative` property before the `integer` property is not chosen because of a consequence of the French language but instead because it is easier to write out with `pynini`. \n", - ">- Conversely, if your language is completely invariant in this regard, it may be more efficient to pass `preserve_order` through the Classifier and manage the property here in the Verbalizer. This allows NeMo ITN to avoid building states and arcs for each permutation, reducing graph size and compiling time." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "aFUrbSdJ8Wk7" - }, - "source": [ - "# Ordinal WFST " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "w1b0Z7f5Z9Ar" - }, - "source": [ - "Ordinals is the class of numbers used for enumerating order or placement of entities in a series. In some languages, they are simply derivations of cardinal numbers. For instance, English enumerates order as `first, second, third, fourth, fifth....` After the third ordinal, they become a regular pattern of `cardinal + 'th'`.\n", - "\n", - "Meanwhile, other languages may reserve specific counting systems for ordinals. For example, while Korean uses a Chinese derived counting system for several Cardinal related tasks, it uses derivations from a native counting system for ordering:\n", - "\n", - "**Cardinal**/**Ordinal** = **English**\n", - "- il/cheot-jae = \"First\"\n", - "- i/dul-jae = \"Second\"\n", - "- sam/set-jae = \"Third\"\n", - "- sa/net-jae = \"Fourth\"\n", - "- o/daseot-jae = \"Fifth\"\n", - "\n", - "If your language is of the latter variety, you will likely need to begin development of Ordinal WFST by repeating Cardinal WFST development before proceeding. (Or make it part of your previous Cardinal WFST and combining with a `union` operation.) While you can extend coverage to the level of Cardinal WFST, you will find most Ordinals to be sufficiently covered by only enumerating to a few hundreds. (e.g. Is it common in your language to speak of the \"one millionth\" in an order and/or write out `1,000,000th`?)\n", - "\n", - "For this portion of the tutorial, we will focus on the first type of ordinals - those that primarily derived by altering Cardinals." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oq_xA8NPiANw" - }, - "source": [ - "## Grammar" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lhjcQS6oiD_w" - }, - "source": [ - "Continuing with our example language, we first begin by laying out our expected inputs and pinpointing a regular pattern to guide our WFSTs. We note the following examples:\n", - "\n", - " **English = French**\n", - " - \"first\" = \"premier/première\"\n", - " - \"second\" = \"second/seconde/deuxième\"\n", - " - \"third\" = \"troisième\"\n", - " - \"fourth\" = \"quatrième\"\n", - " - \"fifth\" = \"cinquième\"\n", - " - \"sixth\" = \"sixième\"\n", - " - \"seventh\" = \"septième\"\n", - "\n", - "From our examples inputs, it appears that spelling of French Ordinals follows a general format of: `cardinal + ième`. The only exceptions appear to be in the case of the first and second Ordinals - for which completely different roots appear - and the fourth and the fifth Ordinals - where the former drops the \"e\" at the end of the root (`quatre -> quatr`) and the latter appends a \"u\" (`cinq -> cinqu`). \n", - "\n", - "For the expected outputs, we observe the following examples:\n", - " - \"premier/première\" -> `1ᵉʳ/1ʳᵉ`\n", - " - \"second/seconde\" -> `2ᵈ/2ᵈᵉ`\n", - " - \"deuxième\" -> `2ᵉ`\n", - " - \"troisième\" -> `3ᵉ`\n", - " - \"quatrième\" -> `4ᵉ`\n", - " - \"cinquième\" -> `5ᵉ`\n", - " - \"sixième\" -> `6ᵉ`\n", - " - \"septième\" -> `7ᵉ`\n", - "\n", - "It appears that the output is simply the cardinal number of the root with an associated superscript. Since we have already constructed the Cardinal WFST, this means that the job of constructing an Ordinal WFST is simply a case of recognizing the cardinal root for the input and then utilizing a preconstructed Cardinal grammar to render the proper form alongside an associated superscript. That is, our tasks are to:\n", - "- Identify the proper superscript for the ordinal\n", - "- Change the ordinal back into a cardinal\n", - "- Use the Cardinal WFST to transform the cardinal into normalized form\n", - "- Properly render the ordinal using the normalized cardinal and proper superscript\n", - "\n", - "As information regarding the superscript will need to be conveyed through development of the Classifier, we will begin with creating the grammar necessary for rendering the ordinal as its cardinal root. \n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "AOUVZhiwT7hE" - }, - "source": [ - "### Stripping Suffixes" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "5nw0_lOTsEik" - }, - "source": [ - "Since French forms Ordinals by appending a suffix to Cardinals, we should start by creating a WFST to remove the suffix. Assuming that our grammar processes one token at a time, this means that we just need an WFST that will accept all tokens that end with \"ième\" and then delete the suffix from that token:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Rk89LhsxsHTO" - }, - "outputs": [], - "source": [ - "strip_morpheme = pynutil.delete(\"ième\") # deletes suffix\n", - "graph_strip_morpheme = NEMO_SIGMA + strip_morpheme # accepts all strings until passed suffix, then deletes suffix" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "pLg-PzdntV4N" - }, - "source": [ - "Now we can create a graph that permits all characters in a word token and deletes the ordinal suffix. (Note that this also means that the graph won't accept tokens without the suffix, helping us avoid false inputs.) \n", - "\n", - "We can now intersect this graph with our Cardinal WFST to now strip the suffixes from ordinals and treat them as cardinals. However, recall that our `CardinalFst` also inserted its own class tag. Obviously, we do not want to do this here as it will disrupt the formatting of the token. Instead, we should create a new subgraph *within* the `CardinalFst` class that will only produce the cardinals without tokens." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "class CardinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"cardinal\", kind=\"classify\")\n", - " \n", - " ### Cardinal Grammar....\n", - " ### .....\n", - " graph = graph_trillions | zero \n", - "\n", - " ### Formatting grammar....\n", - " ### .....\n", - " graph = graph @ clean_cardinal\n", - " \n", - " ### NEW GRAPH\n", - " self.just_cardinals = graph # will produce cardinals without formatting\n", - "\n", - " ### Token insertion\n", - " optional_minus_graph = pynini.closure(\n", - " pynutil.insert(\"negative: \") + pynini.cross(\"moins\", \"\\\"-\\\"\") + \" \", 0, 1\n", - " )\n", - "\n", - " final_graph = optional_minus_graph + pynutil.insert(\"integer: \\\"\") + graph + pynutil.insert(\"\\\"\")\n", - "\n", - " final_graph = self.add_tokens(final_graph)\n", - "\n", - " self.fst = final_graph" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now we call it for our graph:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vxDgBa4_t1nD" - }, - "outputs": [], - "source": [ - "graph_cardinal = CardinalFst().just_cardinals \n", - "graph_ordinal_regular_suffix = graph_strip_morpheme @ graph_cardinal" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "hSpk5M7BuXRz" - }, - "source": [ - "Let's see if it works and gives us the desired cardinal:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "7cJ7fieouY2r" - }, - "outputs": [], - "source": [ - "example = \"sixième\" # dervied from six/6\n", - "apply_fst(example, graph_ordinal_regular_suffix)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "GtEuV7sOuxek" - }, - "source": [ - "Now we can consider the edge cases. Beyond the first and second ordinals, French exhibits irregular behavior in the following cases:\n", - "- If the cardinal root ends with an \"e\", the \"e\" is dropped before adding the suffix (e.g. \"quatrième\"). \n", - "- Cardinals ending with \"cinq\", \"neuf\", and \"dix\" change their endings to \"cinqu\", \"neuv\" , and \"diz\" before appending the suffix, respectively. \n", - "\n", - "We could start by proposing a WFST that replaces the suffix \"ième\" with \"e\" and then compose this onto the Cardinal WFST. If it is a legitimate cardinal, then there will be a path through CardinalFST and the integer will be rendered as normal. \n", - "\n", - "Meanwhile, the case of \"dix\", \"cinq\", and \"neuf\" would each require a distinct WFST as they are each a consequence of different rules of orthography and phonology. Like the case with \"e\", we could change each back to its root and then see if the CardinalWFST will permit a path with the new input. \n", - "\n", - "It is at this point that we can do a cost-benefit analysis and realize that all these cases can be managed by an explicit `string_map/string_file`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_9KTNQeIw4sq" - }, - "outputs": [], - "source": [ - "graph_root_change = pynini.string_map([(\"quatrième\", \"quatre\"),\n", - " (\"cinquième\",\t\"cinq\"),\n", - " (\"neuvième\",\t\"neuf\"),\n", - " (\"onzième\",\t\"onze\"),\n", - " (\"douzième\",\t\"douze\"),\n", - " (\"treizième\",\t\"treize\"),\n", - " (\"quatorzième\",\t\"quatorze\"),\n", - " (\"quinzième\",\t\"quinze\"),\n", - " (\"seizième\",\t\"seize\"),\n", - " (\"trentième\",\t\"trente\"),\n", - " (\"quarantième\",\t\"quarante\"),\n", - " (\"cinquantième\",\t\"cinquante\"),\n", - " (\"soixantième\",\t\"soixante\"),\n", - " (\"millième\",\t\"mille\"),\n", - "])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "eo2_keFVqaY4" - }, - "source": [ - "We could then concatenate these with a WFST that accepts all tokens with these endings and then change the endings as desired. These will provide the cardinal roots just as effectively. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "O7I29ezmxylx" - }, - "source": [ - "The same can be said for \"premier/première\" and \"second/seconde\":" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "3JZoz51VyGS6" - }, - "outputs": [], - "source": [ - "graph_firsts = pynini.string_map([(\"premier\", \"un\"),(\"première\", \"un\")])\n", - "graph_seconds = pynini.string_map([(\"second\", \"deux\"),(\"seconde\", \"deux\")])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "NJ9BGGAwyTQ5" - }, - "source": [ - "*Note: We graph separately to manage their different superscripts later on.*\n", - "\n", - "Depending on your language of focus, the choice of implicitly reversing the root token or explicitly mapping back to root will be the most efficient, but it is worth considering both options if only to check your understanding of the language." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8PgVwDRRq9gr" - }, - "source": [ - "Putting our grammar together, we have:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ko2kAeKwrRSH" - }, - "outputs": [], - "source": [ - "strip_morpheme = pynutil.delete(\"ième\") # deletes suffix\n", - "\n", - "graph_root_change = pynini.string_map([(\"quatrième\", \"quatre\"),\n", - " (\"cinquième\",\t\"cinq\"),\n", - " (\"neuvième\",\t\"neuf\"),\n", - " (\"onzième\",\t\"onze\"),\n", - " (\"douzième\",\t\"douze\"),\n", - " (\"treizième\",\t\"treize\"),\n", - " (\"quatorzième\",\t\"quatorze\"),\n", - " (\"quinzième\",\t\"quinze\"),\n", - " (\"seizième\",\t\"seize\"),\n", - " (\"trentième\",\t\"trente\"),\n", - " (\"quarantième\",\t\"quarante\"),\n", - " (\"cinquantième\",\t\"cinquante\"),\n", - " (\"soixantième\",\t\"soixante\"),\n", - " (\"millième\",\t\"mille\"),\n", - "])\n", - "\n", - "# Component will accept all tokens that end with desired strings\n", - "graph_get_cardinal = NEMO_SIGMA + (strip_morpheme | graph_root_change) \n", - "\n", - "graph_firsts = pynini.string_map([(\"premier\", \"un\"),(\"première\", \"un\")])\n", - "graph_seconds = pynini.string_map([(\"second\", \"deux\"),(\"seconde\", \"deux\")])\n", - "\n", - "graph_get_cardinal = pynini.union(graph_firsts, graph_seconds, graph_get_cardinal) \n", - "\n", - "graph_cardinal = CardinalFst().just_cardinals\n", - "\n", - "graph_ordinal = graph_get_cardinal @ graph_cardinal" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ESxY3LsCdE8q" - }, - "outputs": [], - "source": [ - "apply_fst(\"sixième\", graph_ordinal)\n", - "apply_fst(\"première\", graph_ordinal)\n", - "apply_fst(\"seconde\", graph_ordinal)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qo_g8UdoUFJB" - }, - "source": [ - "## Classifier" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kemhdKAjzEIa" - }, - "source": [ - "Now that we've found a way to pass the work of the Ordinal grammar back onto the Cardinal grammar, we can move onto the Classifier. Like before, we need to inherit from `GraphFst` to properly insert token formatting and required attributes. As well, we will again use the `integer` property to tag our digit string.\n", - "\n", - "Indeed, the only major difference between the Ordinal Classifier and the Cardinal Classifier is the replacement of optional `negative` attribute with the `morphosyntactic_feature` attribute to indicate the superscript function." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "EHM4Y3TW2nXT" - }, - "source": [ - "Since we are relying on the `CardinalFst` class in our grammar, we want to consider how to instantiate an instance of it. Since our ultimate goal is to build a Classifier that unites all semiotic classes, it makes sense to simply use the `CardinalFst` that we will need to call for our ITN and pass it as an argument to our new class." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 273 - }, - "id": "KsmPhWSa3LF_", - "outputId": "9e881ca9-a926-4249-dda8-9c52175569b5" - }, - "outputs": [], - "source": [ - "def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"ordinal\", kind=\"classify\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CtBQ-udB3S5Q" - }, - "source": [ - "To clear up the namespace, we will now be importing from the NeMo implementation of `CardinalFst` for French." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "L-JAcidf4QQg" - }, - "outputs": [], - "source": [ - "from nemo_text_processing.inverse_text_normalization.fr.taggers.cardinal import CardinalFst\n", - "\n", - "class OrdinalFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"ordinal\", kind=\"classify\")\n", - " graph_cardinal = cardinal.graph_no_exception # NeMo equivalent to self.just_cardinals" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FQfkAqZavCAB" - }, - "source": [ - "We now add in our grammar:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "uUQ4BLuivGut" - }, - "outputs": [], - "source": [ - "class OrdinalFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"ordinal\", kind=\"classify\")\n", - " graph_cardinal = cardinal.graph_no_exception # may replace\n", - "\n", - " strip_morpheme = pynutil.delete(\"ième\") # deletes suffix\n", - "\n", - " graph_root_change = pynini.string_map([(\"quatrième\", \"quatre\"),\n", - " (\"cinquième\",\t\"cinq\"),\n", - " (\"neuvième\",\t\"neuf\"),\n", - " (\"onzième\",\t\"onze\"),\n", - " (\"douzième\",\t\"douze\"),\n", - " (\"treizième\",\t\"treize\"),\n", - " (\"quatorzième\",\t\"quatorze\"),\n", - " (\"quinzième\",\t\"quinze\"),\n", - " (\"seizième\",\t\"seize\"),\n", - " (\"trentième\",\t\"trente\"),\n", - " (\"quarantième\",\t\"quarante\"),\n", - " (\"cinquantième\",\t\"cinquante\"),\n", - " (\"soixantième\",\t\"soixante\"),\n", - " (\"millième\",\t\"mille\"),\n", - " ])\n", - " \n", - " # Component will accept all tokens that end with desired strings\n", - " graph_get_cardinal = NEMO_SIGMA + (strip_morpheme | graph_root_change) \n", - "\n", - " graph_firsts = pynini.string_map([(\"premier\", \"un\"),(\"première\", \"un\")])\n", - " graph_seconds = pynini.string_map([(\"second\", \"deux\"),(\"seconde\", \"deux\")])\n", - "\n", - " graph_get_cardinal = pynini.union(graph_firsts, graph_seconds, graph_get_cardinal) \n", - "\n", - " graph_ordinal = graph_get_cardinal @ graph_cardinal\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "F_6EXPRMvnp2" - }, - "source": [ - "Now we come to the `morphosyntactic_features` property - a linguistic term for aspects of a word related to grammar. If intending to deploy your WFST through Sparrowhawk, this is the only ordinal property that is permitted (outside of the universal properties like `preserve_order`) and thus must carry all information regarding how to properly normalize the ordinal. (If Sparrowhawk deployment is not necessary, you may add additional properties to the tag.)\n", - "\n", - "How should we convey this information? Since the Verbalizer will be the main interface for our tags, it really does not matter - so long as we can reliably process the features. For the purposes of French, we just need `morphosyntactic_features` to decide the following:\n", - "- Insert the specific superscripts for \"premier/première\" or \"second/seconde\"\n", - "- Insert \"ᵉ\" otherwise\n", - "\n", - "We will also introduce another aspect of French Ordinals: they can be either plural or singular, identified by the suffix \"s\" on input and superscript \"ˢ\" on output. As such, our `morphosyntactic_features` should also decide the additional property:\n", - "- Insert the plural superscript " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "atctz6p-2GtV" - }, - "source": [ - "Since the default superscript is near universal, we will just specify this in our WFST and focus on the second and first ordinals as specific cases. We will create a `graph_morpheme` component that inserts the default superscript - indicated with a standard \"e\" to avoid possible encoding issues. We will then append a WFST that will graph any possible plural marker - \"s\" - as part the `morphosyntactic_features`. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ui99osyP2UuQ" - }, - "outputs": [], - "source": [ - "graph_morpheme = pynutil.insert(\"e\") # Insert e superscript\n", - "graph_plural = pynini.closure(pynini.accep(\"s\"), 0, 1) # We create an acceptor since we must process the possible \"s\"\n", - "\n", - "graph_morpheme_component = graph_morpheme + graph_plural\n", - "\n", - "graph_morphosyntactic_features = (pynutil.insert(\" morphosyntactic_features: \\\"\") \n", - " + graph_morpheme_component\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "QAlqubA25gq0" - }, - "source": [ - "Introducing the `integer` feature:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "rs2TyIBc5la6" - }, - "outputs": [], - "source": [ - "graph_reg_ordinals = graph_get_cardinal @ graph_cardinal # Rewriting ordinals to remove the first and second ordinal.\n", - "\n", - "graph_ordinal = pynutil.insert(\"integer: \\\"\") + graph_reg_ordinals + pynutil.insert(\"\\\"\")\n", - "graph_ordinal += graph_morphosyntactic_features" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xoqk20Pi2gT8" - }, - "source": [ - "For the first and second ordinals, we can explicitly state their mappings, as these occurrences are invariable. (First and second ordinals do not need to accommodate being the endings of other terms.) As such, we can just have mappings from the token to the superscripts." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "54aqdH_P63Ea" - }, - "outputs": [], - "source": [ - "firsts = pynini.string_map([(\"premier\", \"er\"), (\"première\",\"re\")])\n", - "firsts += graph_plural # Still accepts plural marker in superscript\n", - "seconds = pynini.string_map([(\"second\", \"d\"),(\"seconde\", \"de\")])\n", - "seconds += graph_plural \n", - "\n", - "graph_firsts = pynutil.insert(\"integer: \\\"1\\\" morphosyntactic_features: \\\"\") + firsts\n", - "graph_seconds = pynutil.insert(\"integer: \\\"2\\\" morphosyntactic_features: \\\"\") + seconds" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "D2vQ4m7o7p84" - }, - "source": [ - "Placing them in our class:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "w_JKT8JMf-Mz" - }, - "outputs": [], - "source": [ - "class OrdinalFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"ordinal\", kind=\"classify\")\n", - " graph_cardinal = cardinal.graph_no_exception # may replace\n", - "\n", - " strip_morpheme = pynutil.delete(\"ième\") # deletes suffix\n", - "\n", - " graph_root_change = pynini.string_map([(\"quatrième\", \"quatre\"),\n", - " (\"cinquième\",\t\"cinq\"),\n", - " (\"neuvième\",\t\"neuf\"),\n", - " (\"onzième\",\t\"onze\"),\n", - " (\"douzième\",\t\"douze\"),\n", - " (\"treizième\",\t\"treize\"),\n", - " (\"quatorzième\",\t\"quatorze\"),\n", - " (\"quinzième\",\t\"quinze\"),\n", - " (\"seizième\",\t\"seize\"),\n", - " (\"trentième\",\t\"trente\"),\n", - " (\"quarantième\",\t\"quarante\"),\n", - " (\"cinquantième\",\t\"cinquante\"),\n", - " (\"soixantième\",\t\"soixante\"),\n", - " (\"millième\",\t\"mille\"),\n", - " ])\n", - " \n", - " # Component will accept all tokens that end with desired strings\n", - " graph_get_cardinal = NEMO_SIGMA + (strip_morpheme | graph_root_change) \n", - "\n", - " # Graph will map ordinals beyond second ordinal to their cardinals\n", - " graph_reg_ordinals = graph_get_cardinal @ graph_cardinal\n", - "\n", - " # Graphing morphosyntactic_features\n", - " graph_morpheme = pynutil.insert(\"e\") # Insert e superscript\n", - " graph_plural = pynini.accep(\"s\").ques # ques is equivalent to pynini.closure(, 0, 1)\n", - "\n", - " graph_morpheme_component = graph_morpheme + graph_plural\n", - "\n", - " graph_morphosyntactic_features = (pynutil.insert(\" morphosyntactic_features: \\\"\") \n", - " + graph_morpheme_component\n", - " )\n", - "\n", - " # Adding in the `integer` property:\n", - " graph_ordinal = pynutil.insert(\"integer: \\\"\") + graph_reg_ordinals + pynutil.insert(\"\\\"\")\n", - " graph_ordinal += graph_morphosyntactic_features \n", - "\n", - " # Case of first and second ordinals\n", - " firsts = pynini.string_map([(\"premier\", \"er\"), (\"première\",\"re\")])\n", - " firsts += graph_plural # Still accepts plural marker in superscript\n", - " seconds = pynini.string_map([(\"second\", \"d\"),(\"seconde\", \"de\")])\n", - " seconds += graph_plural \n", - "\n", - " graph_firsts = pynutil.insert(\"integer: \\\"1\\\" morphosyntactic_features: \\\"\") + firsts\n", - " graph_seconds = pynutil.insert(\"integer: \\\"2\\\" morphosyntactic_features: \\\"\") + seconds\n", - "\n", - " # All together\n", - " graph_ordinal = pynini.union(graph_ordinal, graph_firsts, graph_seconds)\n", - " self.fst = graph_ordinal.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CpGHVg6chmA0" - }, - "source": [ - "Trying out on some examples:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "b5DL3PZRhpc8" - }, - "outputs": [], - "source": [ - "cardinal = CardinalFst()\n", - "ordinal = OrdinalFst(cardinal).fst\n", - "\n", - "apply_fst(\"premier\", ordinal)\n", - "apply_fst(\"premiers\", ordinal)\n", - "apply_fst(\"seconde\", ordinal)\n", - "apply_fst(\"douzièmes\", ordinal)\n", - "apply_fst(\"cent-cinquièmes\", ordinal)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "MNQVgiv-UK29" - }, - "source": [ - "### Special Tokens" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UdiNAHGh71O9" - }, - "source": [ - "If you are particularly astute, you may have noticed that we have not closed the quotations around the `morphosyntactic_features` throughout, despite doing so for `integer`. This is not a typo, as there is one more aspect of the Classifier that must be addressed: special cases.\n", - "\n", - "For your language, you may notice that there are occasional exceptions to writing rules that are signaled by a specific vocabulary token in a string. As this must be communicated to our Verbalizer, it is important that we signal this vocabulary through our Classifier. \n", - "\n", - "For French, this can occur in the normalization of centuries. When using Ordinals to indicate centuries, French commonly writes with Roman numerals. For example:\n", - "- \"Fifth century\" -> \"cinquième siècle\" -> `Vᵉ siècle` \n", - "- \"Twentieth century\" -> \"vintième siècle\" -> `XXᵉ siècle` \n", - "\n", - "As such, we must allow our Classifier to pass on the information that \"siècle\" follows an ordinal to our Verbalizer, so it may normalize with Roman numerals. We accomplish this by appending a WFST that accepts special tokens that follow our Ordinals, adding them to our `morphosyntactic_features` attribute with a forward slash to delineate." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "MsWnT4BfQKcC" - }, - "outputs": [], - "source": [ - "special_tokens = pynini.accep(\"siècle\")\n", - "\n", - "graph_special_tokens = delete_space + pynutil.insert(\"/\") + special_tokens # We need to delete the space in between this token and the following one.\n", - "graph_special_tokens = pynini.closure(graph_special_tokens, 0, 1)\n", - "\n", - "graph_ordinal += graph_special_tokens + pynutil.insert(\"\\\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "698_n5SFQ_jP" - }, - "source": [ - "*Once again, it is advised to retain a tsv file in `data` to quickly append these key-words.*\n", - "\n", - "Having taken care of the special case, we may now call `add_tokens` and complete the graph (fully written out below)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "nZ1dkft0Riou" - }, - "outputs": [], - "source": [ - "class OrdinalFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"ordinal\", kind=\"classify\")\n", - " graph_cardinal = cardinal.graph_no_exception # may replace\n", - "\n", - " strip_morpheme = pynutil.delete(\"ième\") # deletes suffix\n", - "\n", - " graph_root_change = pynini.string_map([(\"quatrième\", \"quatre\"),\n", - " (\"cinquième\",\t\"cinq\"),\n", - " (\"neuvième\",\t\"neuf\"),\n", - " (\"onzième\",\t\"onze\"),\n", - " (\"douzième\",\t\"douze\"),\n", - " (\"treizième\",\t\"treize\"),\n", - " (\"quatorzième\",\t\"quatorze\"),\n", - " (\"quinzième\",\t\"quinze\"),\n", - " (\"seizième\",\t\"seize\"),\n", - " (\"trentième\",\t\"trente\"),\n", - " (\"quarantième\",\t\"quarante\"),\n", - " (\"cinquantième\",\t\"cinquante\"),\n", - " (\"soixantième\",\t\"soixante\"),\n", - " (\"millième\",\t\"mille\"),\n", - " ])\n", - " \n", - " # Component will accept all tokens that end with desired strings\n", - " graph_get_cardinal = NEMO_SIGMA + (strip_morpheme | graph_root_change) \n", - "\n", - " # Graph will map ordinals beyond second ordinal to their cardinals\n", - " graph_reg_ordinals = graph_get_cardinal @ graph_cardinal\n", - "\n", - " # Graphing morphosyntactic_features\n", - " graph_morpheme = pynutil.insert(\"e\") # Insert e superscript\n", - " graph_plural = pynini.accep(\"s\").ques # We create an acceptor since we must process the possible \"s\"\n", - "\n", - " graph_morpheme_component = graph_morpheme + graph_plural\n", - "\n", - " graph_morphosyntactic_features = (pynutil.insert(\" morphosyntactic_features: \\\"\") \n", - " + graph_morpheme_component\n", - " )\n", - "\n", - " # Adding in the `integer` property:\n", - " graph_ordinal = pynutil.insert(\"integer: \\\"\") + graph_reg_ordinals + pynutil.insert(\"\\\"\")\n", - " graph_ordinal += graph_morphosyntactic_features \n", - "\n", - " # Case of first and second ordinals\n", - " firsts = pynini.string_map([(\"premier\", \"er\"), (\"première\",\"re\")])\n", - " firsts += graph_plural # Still accepts plural marker in superscript\n", - " seconds = pynini.string_map([(\"second\", \"d\"),(\"seconde\", \"de\")])\n", - " seconds += graph_plural \n", - "\n", - " graph_firsts = pynutil.insert(\"integer: \\\"1\\\" morphosyntactic_features: \\\"\") + firsts\n", - " graph_seconds = pynutil.insert(\"integer: \\\"2\\\" morphosyntactic_features: \\\"\") + seconds\n", - "\n", - "\n", - " # Special tokens\n", - " special_tokens = pynini.accep(\"siècle\")\n", - "\n", - " graph_special_tokens = delete_space + pynutil.insert(\"/\") + special_tokens # We need to delete the space in between this token and the following one.\n", - " graph_special_tokens = pynini.closure(graph_special_tokens, 0, 1)\n", - "\n", - " graph_ordinal += graph_special_tokens + pynutil.insert(\"\\\"\")\n", - "\n", - " # Finishing\n", - " graph_ordinal = self.add_tokens(graph_ordinal)\n", - " self.fst = graph_ordinal.optimize()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7a4zBo-YS1QD" - }, - "source": [ - "## Verbalizer" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zYbrcGyGS2rW" - }, - "source": [ - "The initial part of the Ordinal Verbalizer is similar to the Cardinal WFST: we simply need to build a Verbalizer that inherits from `GraphFST` and removes the `integer` property tag. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "KUv99A_rYjb9" - }, - "outputs": [], - "source": [ - "class OrdinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"ordinal\", kind=\"verbalize\")\n", - " graph_integer = (\n", - " pynutil.delete(\"integer:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zKCt_EapZXGW" - }, - "source": [ - "Now we need to manage the `morphosyntactic_features` component. The first steps seem simple enough: delete the property tag and replace the superscript indicators with the actual superscripts. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "yoa_mXMLabrU" - }, - "outputs": [], - "source": [ - " # Create mappings for all superscripts\n", - " superscript = pynini.union(\n", - " pynini.cross(\"e\", \"ᵉ\"), # only delete first quote since there may be more features\n", - " pynini.cross(\"d\", \"ᵈ\"),\n", - " pynini.cross(\"r\", \"ʳ\"),\n", - " pynini.cross(\"s\", \"ˢ\"),\n", - " )\n", - "\n", - " # Append to deletion of feature property. Note that we use plus closure for multiple superscripts.\n", - " graph_morphosyntactic_features = pynutil.delete(\" morphosyntactic_features: \\\"\") + superscript.plus" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xOA7_MsUrSJS" - }, - "source": [ - "### Romanization" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "K_SaG0DUa2t7" - }, - "source": [ - "Now we come to the possible Romanization component. Since we need to graph the superscript components as following the number, we want to design our graph so that `morphosyntactic_features` is the last component of the graph. However, we do not know that we need Romanization until we see the `morphosyntactic_features` component. As such, we need to design our graph such that two options are available initially for an input, but only one allows full traversal." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7dalc-tablG-" - }, - "source": [ - "![romanization.png](images/romanization.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "mPTNCddNcEEE" - }, - "source": [ - "In cases where your WFST decisions are dependent on latter parts of an input string, permitting the union of two separate paths when only one is valid usually assists, as a standard pathing heuristic will only choose the valid path. \n", - "\n", - "In the case of French, this would require us to separate our Verbalizer into two parts: one for Arabic numerals and one for Roman numerals. For the Arabic WFST, we simply conclude the graph. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0YSy1PYOcuyD" - }, - "outputs": [], - "source": [ - "graph_integer = (\n", - " pynutil.delete(\"integer:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - "graph_Arabic = graph_integer + graph_morphosyntactic_features + pynutil.delete(\"\\\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nnXjUU5Pf7Sh" - }, - "source": [ - "For the Roman graph, things get a bit trickier. Ideally, we would want to build a WFST that maps each digit of `graph_Arabic` to a Roman equivalent. However, consider the following examples:\n", - "- 1 -> I\n", - "- 10 -> X\n", - "- 11 -> XI\n", - "- 100 -> C\n", - "- 101 -> CI\n", - "- 110 -> CX\n", - "- 111 -> CXI\n", - "\n", - "Since Roman numerals do not preserve powers of ten through digit placement, we will need to design separate FSTs for each digit position and apply them accordingly. As this can quickly become intensive, we will only work to enumerate the Ordinals from 1 to 100. (Note: We are doing this to accommodate centuries; there is little likelihood that any century beyond the 99th will be used in regular strings.)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3-fQHMc2iQrz" - }, - "source": [ - "First we design our graphs for converting from Arabic to Roman numerals:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d6PDySykiXTh" - }, - "outputs": [], - "source": [ - "digits = pynini.string_map([(\"1\", \"I\"),\n", - " (\"2\",\t\"II\"),\n", - " (\"3\",\t\"III\"),\n", - " (\"4\",\t\"IV\"),\n", - " (\"5\",\t\"V\"),\n", - " (\"6\",\t\"VI\"),\n", - " (\"7\",\t\"VII\"),\n", - " (\"8\",\t\"VIII\"),\n", - " (\"9\",\t\"IX\"),\n", - " ])\n", - "tens = pynini.string_map([(\"1\", \"X\"),\n", - " (\"2\",\t\"XX\"),\n", - " (\"3\",\t\"XXX\"),\n", - " (\"4\",\t\"XL\"),\n", - " (\"5\",\t\"L\"),\n", - " (\"6\",\t\"LX\"),\n", - " (\"7\",\t\"LXX\"),\n", - " (\"8\",\t\"LXXX\"),\n", - " (\"9\",\t\"XC\"),\n", - " ])\n", - "zero = pynutil.delete(\"0\") # No Roman representation for zero." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wb-LmwJdk59m" - }, - "source": [ - "Now we build two separate filters: one will accept only single digit Arabic numerals and the other will accept two digit Arabic numerals. For this we can use `NEMO_DIGIT`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "DW3oD7Hbli2X" - }, - "outputs": [], - "source": [ - "map_one_digit = NEMO_DIGIT\n", - "map_two_digits = NEMO_DIGIT ** 2 # pynini overloads the exponent function to allow self-concatenation." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xtYKLy9AmJZS" - }, - "source": [ - "We now build mappings between two digit Arabic numerals and Roman numerals, composing them onto the filters:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "dUy7uEUXmT_g" - }, - "outputs": [], - "source": [ - "graph_one_digit_romans = NEMO_DIGIT @ digits\n", - "\n", - "graph_two_digit_romans = tens + (digits | zero)\n", - "graph_two_digit_romans = map_two_digits @ graph_two_digit_romans\n", - "\n", - "graph_romans = graph_one_digit_romans | graph_two_digit_romans" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JEinyAMdm7RJ" - }, - "source": [ - "We now take care of the occurrence of \"siècle\" before composing onto `graph_integer`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ERO19BbynPNX" - }, - "outputs": [], - "source": [ - "graph_romans = (graph_integer @ graph_romans) + graph_morphosyntactic_features\n", - "graph_romans += pynini.cross(\"/\", \" \") + \"siècle\" + pynutil.delete(\"\\\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zN-fwrCGoToQ" - }, - "source": [ - "We finalize with a union and calling `delete_tokens`, the complete Verbalizer now being::" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "kr2wcToAofWB" - }, - "outputs": [], - "source": [ - "class OrdinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"ordinal\", kind=\"verbalize\")\n", - "\n", - " # Maps integer and removes attribute\n", - " graph_integer = (\n", - " pynutil.delete(\"integer:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - "\n", - " # Create mappings for all superscripts\n", - " superscript = pynini.union(\n", - " pynini.cross(\"e\", \"ᵉ\"), # only delete first quote since there may be more features\n", - " pynini.cross(\"d\", \"ᵈ\"),\n", - " pynini.cross(\"r\", \"ʳ\"),\n", - " pynini.cross(\"s\", \"ˢ\"),\n", - " )\n", - "\n", - " # Append to deletion of feature property. Note that we use plus closure for multiple superscripts.\n", - " graph_morphosyntactic_features = pynutil.delete(\" morphosyntactic_features: \\\"\") + superscript.plus\n", - "\n", - " # Writing WFST for Arabic\n", - " graph_Arabic = graph_integer + graph_morphosyntactic_features + pynutil.delete(\"\\\"\")\n", - "\n", - " # Mapping Roman numerals\n", - " digits = pynini.string_map([(\"1\", \"I\"),\n", - " (\"2\",\t\"II\"),\n", - " (\"3\",\t\"III\"),\n", - " (\"4\",\t\"IV\"),\n", - " (\"5\",\t\"V\"),\n", - " (\"6\",\t\"VI\"),\n", - " (\"7\",\t\"VII\"),\n", - " (\"8\",\t\"VIII\"),\n", - " (\"9\",\t\"IX\"),\n", - " ])\n", - " tens = pynini.string_map([(\"1\", \"X\"),\n", - " (\"2\",\t\"XX\"),\n", - " (\"3\",\t\"XXX\"),\n", - " (\"4\",\t\"XL\"),\n", - " (\"5\",\t\"L\"),\n", - " (\"6\",\t\"LX\"),\n", - " (\"7\",\t\"LXX\"),\n", - " (\"8\",\t\"LXXX\"),\n", - " (\"9\",\t\"XC\"),\n", - " ])\n", - " zero = pynutil.delete(\"0\") # No Roman representation for zero.\n", - "\n", - " # filters for Roman digits\n", - " map_one_digit = NEMO_DIGIT\n", - " map_two_digits = NEMO_DIGIT ** 2 # pynini overloads the exponent function to allow self-concatenation.\n", - "\n", - " # Composing onto roman digits\n", - " graph_one_digit_romans = NEMO_DIGIT @ digits\n", - "\n", - " graph_two_digit_romans = tens + (digits | zero)\n", - " graph_two_digit_romans = map_two_digits @ graph_two_digit_romans\n", - "\n", - " graph_romans = graph_one_digit_romans | graph_two_digit_romans\n", - "\n", - " # Writing WFST for Roman\n", - " graph_romans = (graph_integer @ graph_romans) + graph_morphosyntactic_features\n", - " graph_romans += pynini.cross(\"/\", \" \") + \"siècle\" + pynutil.delete(\"\\\"\")\n", - "\n", - " # Final composition\n", - " graph = (graph_romans | graph_Arabic)\n", - "\n", - " delete_tokens = self.delete_tokens(graph)\n", - " self.fst = delete_tokens.optimize()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Trying out our examples:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "example_regular = 'ordinal { integer: \"12\" morphosyntactic_features: \"es\" }'\n", - "example_roman = 'ordinal { integer: \"12\" morphosyntactic_features: \"es/siècle\" }'\n", - "\n", - "fst = OrdinalFst().fst\n", - "\n", - "apply_fst(example_regular, fst)\n", - "apply_fst(example_roman, fst)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yBgLhTq9pWZe" - }, - "source": [ - "We have now completed an Ordinal WFST from the ground up, allowing a separate numbering system for special cases." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-W1-BMVJUXXk" - }, - "source": [ - "## Final notes" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kR7E64P4pPU_" - }, - "source": [ - "Before moving on, there are some key takeaways that you may find useful for most (if not all) languages:\n", - "- Many ordinal systems rely on alteration of Cardinals. Even in the example of Korean, it is using a pre-existing counting system and adding a suffix to indicate ordering. As such, your Ordinal WFST will likely follow this tutorial's structure of changing the Ordinal to its original root and then relying on your Cardinal WFST for the majority of processing.\n", - "- The `morphosyntactic_features` property will carry the vast majority of information necessary for normalization through your Verbalizer.\n", - "- While not all writing systems have the same quirk as using Roman numerals in reference to centuries, you will likely find cases in your language when a specific token indicates unique rules for a semiotic class. Carrying this information to the Verbalizer is usually the simplest means of preserving the token while also facilitating normalization. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Rx8-LuJOUaa5" - }, - "source": [ - "# Decimal WFST " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "D2MRXYxz8TGA" - }, - "source": [ - "\n", - "If the Cardinal WFST is the most crucial element of a normalization grammar, the construction of the Decimal WFST is a close second. Much like in the case of constructing Ordinals from Cardinal grammars, many aspects of the Decimal WFST will be reused throughout your other semiotic classes.\n", - "\n", - "To get started, you should study the numerical conventions in your language. In particular, you should take note of the following:\n", - "- How is the decimal component of a number pronounced in your language of focus. (e.g. The English number `1.33` can be verbalized as \"one point three three\" or \"one and thirty three hundredths.\")\n", - "- What is the punctuation mark used for decimal demarcation? (In North America, several writing systems use `.` while European nations will use `,`.)\n", - "- Are there general rules regarding pronunciation/formatting of numbers past the decimal demarcation? (e.g. Does your language pronounce each digit or pronounce as a series of three digit numbers?)\n", - "\n", - "Such questions will likely require some deep familiarity with the language, and it may benefit to ask a native speaker for some input. Of course, the level of depth is dependent on your needs, but researching these questions will help your normalization system appear more organic." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UsK78ib4N-gb" - }, - "source": [ - "## Grammar" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "p4CLOOA9OAwZ" - }, - "source": [ - "In the case of French, we have the following guidelines:\n", - "- French uses the comma ( `,` ) for decimal delineation. It is articulated as \"virgule\".\n", - "- Decimals can be read as a series of digits or grouped as Cardinal numbers arbitrarily. (e.g. \"`.333` can be \"virgule trois trois trois\" or \"virgule trois-cent-trente-trois\".) \n", - "\n", - "As such, our grammar needs to accommodate the following pattern: \n", - "\n", - "`cardinal + \"virgule\" + string_of_cardinals`\n", - "\n", - "Given our experience with our previous WFSTs, this seems simple enough. We assume we have an instance of CardinalFST available and create a subcomponent to map the integer portion of a decimal:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "XSp9FTzhf0XZ" - }, - "outputs": [], - "source": [ - "cardinal = CardinalFst().graph_no_exception # NeMo equivalent of just_cardinals\n", - "\n", - "# place cardinal under closure to permit values <=1\n", - "graph_integer = pynini.closure(cardinal, 0, 1)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bk3_3iawgAZE" - }, - "source": [ - "Compose it on a subcomponent that detects the delineator \"virgule\":" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "UMzfAKkngH6z" - }, - "outputs": [], - "source": [ - "delete_virgule = pynutil.delete(\"virgule\")\n", - "graph_decimal = graph_integer + delete_space + delete_virgule" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "GXjbtbLYgn17" - }, - "source": [ - "And permit the occurrence of several strings of cardinals to follow:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LMMNBJz8gtTA" - }, - "outputs": [], - "source": [ - "graph_string_of_cardinals = delete_space + graph_cardinal\n", - "graph_string_of_cardinals = pynini.closure(graph_string_of_cardinals, 1)\n", - "\n", - "graph_decimal += graph_string_of_cardinals" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jTgnRLddhGdE" - }, - "source": [ - "Let us try an example:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "D4rjDh0ShJAp" - }, - "outputs": [], - "source": [ - "example = \"trois virgule trois cinquante-cinq\" \n", - "apply_fst(example, graph_decimal) # Should output only the cardinals in the string" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RfD1d9JOioyl" - }, - "source": [ - "### Ambiguity?" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3IaI1mCIe_6i" - }, - "source": [ - "Note that our decision to include multiple strings of cardinals after the decimal marker has introduced some ambiguity into our WFST. Consider if a decimal number was followed by an integer series (e.g. `2.5, 5, 6`). Now what should be an application of one DecimalFST and two applications of a CardinalFST can be interpreted as a single DecimalFST application (e.g. `2.556`). What can be done?\n", - "\n", - "While we will address this in greater depth later (see [Tokenize and Classify](#tokenize-and-classify)), the short answer is that cases such as these must be calibrated according to use and linguistic intuition. As this is an inherent ambiguity in the language and its writing system, we can never truly remove this possibility without restricting our ability to model the language. However, we can rely on a few logical assumptions to guide our decision making:\n", - "- Unless the grammar is deployed in a restrictive setting (e.g. a Financial or environment where strings of numbers are often read in series) it's not likely for a valid string to exhibit this level of ambiguity. Speakers typically try to reduce possible ambiguity in their language production and would likely rephrase to avoid issues such as these. [See Grice's maxims](https://en.wikipedia.org/wiki/Cooperative_principle).\n", - "- While a language may allow a specific string by *rule*, speakers may typically avoid them *in practice* due to conventions or difficulty. In our case, while it may be possible to read `2,100 05` as \"deux virgule dix-mille-cinq\" (\"two point ten-thousand and five\"), it's dubious that a speaker would find such easier to read than \"deux virgule une zéro zéro zéro cinq\". (The place value of large strings tend to take longer to recognize.)\n", - "\n", - "While hardly satisfying, these two points will allow us to dismiss *some* worry. With the former observation being outside our grammar's ability to manage, we accommodate the latter point by using an alternate WFST from our CardinalFST: `numbers_up_to_million`. (To utilize in your own language, create a WFST in the Cardinal class right before building up to `graph_millions`. Again, calling `optimize` is advised.)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "piNe1AWspa4J" - }, - "outputs": [], - "source": [ - "cardinal = CardinalFst().numbers_up_to_million\n", - "\n", - "# place cardinal under closure to permit values <=1\n", - "graph_integer = pynini.closure(cardinal, 0, 1)\n", - "\n", - "delete_virgule = pynutil.delete(\"virgule\")\n", - "graph_decimal = graph_integer + delete_space + delete_virgule\n", - "\n", - "graph_string_of_cardinals = delete_space + cardinal\n", - "graph_string_of_cardinals = pynini.closure(graph_string_of_cardinals, 1)\n", - "\n", - "graph_decimal += graph_string_of_cardinals" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "B1gglt0tfM5V" - }, - "source": [ - "## Classifier" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "fVkOWkncgOZc" - }, - "source": [ - "Like with our previous WFSTs, the main duty for the classifier is inserting the necessary properties for the semiotic token. For the `decimal` tag, the following properties are used:\n", - "- `integer_part` - indicates value before decimal marker\n", - "- `fractional_part` - indicates values after the decimal marker\n", - "- `negative` - indicates if value is positive or negative (Optional)\n", - "- `quantity` - designates if decimal is in regards to a specific quantity. (See Quantities.)\n", - "\n", - "We can begin by inserting the `integer_part` around our `cardinal` subcomponent and the `fractional_part` around our `graph_string_of_cardinals`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "_zw_cDszh-fB" - }, - "outputs": [], - "source": [ - "graph_integer = pynutil.insert(\"integer_part: \\\"\") + cardinal + pynutil.insert(\"\\\" \")\n", - "graph_fractional = pynutil.insert(\"fractional_part: \\\"\") + graph_string_of_cardinals + pynutil.insert(\"\\\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bxlnn_7tiQMn" - }, - "source": [ - "We then concatenate them together with a component that recognizes and removes the decimal separator." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "BxNS9_AwiWHf" - }, - "outputs": [], - "source": [ - "graph_integer_or_none = graph_integer | pynutil.insert(\"integer_part: \\\"0\\\" \", weight=.1) # In cases we don't always have an integer preceding\n", - "graph_decimal_no_sign = graph_integer_or_none + delete_space + pynutil.delete(\"virgule\") + graph_fractional" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "b7uGfsi4i5UI" - }, - "source": [ - "*Note that we allow insertion of 0 if there is no integer to accommodate reading of only decimal values*\n", - "\n", - "Now we allow the possibility of negative values. (Recall French uses \"moins\" to indicate the negative.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "VsP79naojQZR" - }, - "outputs": [], - "source": [ - "graph_negative = pynini.cross(\"moins\", \"negative: \\\"-\\\" \") + delete_space\n", - "graph_decimal = graph_negative + graph_decimal_no_sign" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "QTcvq5HqllqW" - }, - "outputs": [], - "source": [ - "example = \"moins deux virgule cent-quatre\"\n", - "apply_fst(example, graph_decimal)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FVKuGj_9mZ75" - }, - "source": [ - "Placing within a `DecimalFst` class, we have:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "tXwr32ermesp" - }, - "outputs": [], - "source": [ - "class DecimalFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"decimal\", kind=\"classify\")\n", - " cardinal = cardinal.numbers_up_to_million\n", - " delete_virgule = pynutil.delete(\"virgule\")\n", - "\n", - " graph_integer = pynutil.insert(\"integer_part: \\\"\") + cardinal + pynutil.insert(\"\\\" \") + delete_space\n", - " graph_integer_or_none = graph_integer | pynutil.insert(\"integer_part: \\\"0\\\" \", weight=.001) # In cases we don't always have an integer preceding\n", - "\n", - " graph_string_of_cardinals = delete_space + cardinal\n", - " graph_string_of_cardinals = pynini.closure(graph_string_of_cardinals, 1)\n", - " graph_fractional = pynutil.insert(\"fractional_part: \\\"\") + graph_string_of_cardinals + pynutil.insert(\"\\\"\")\n", - "\n", - " graph_decimal_no_sign = graph_integer_or_none + pynutil.delete(\"virgule\") + graph_fractional \n", - "\n", - " graph_negative = pynini.cross(\"moins\", \"negative: \\\"-\\\" \") + delete_space\n", - " graph_negative = pynini.closure(graph_negative, 0, 1)\n", - "\n", - " graph_decimal = graph_negative + graph_decimal_no_sign\n", - "\n", - " graph = self.add_tokens(graph_decimal)\n", - " self.fst = graph.optimize()\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gjxI5mEKfHLo" - }, - "source": [ - "### Quantities" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3WuwWPf3py7G" - }, - "source": [ - "Recalling our earlier remarks regarding convention in language use, you may find a need to adjust the DecimalFst when processing specific values. For instance, consider the following equivalencies from English:\n", - "- `1,500,000` = \"one million five hundred thousand\" = \"one point five million\" = `1.5 million`\n", - "- `2,750,000` = \"two million seven hundred and fifty thousand\" = \"two point seven five million\" = `2.75 million`\n", - "\n", - "For large numbers, there is a tendency to use the decimal system as though one is describing a quantity. Notably, there is a minimum value for which this is comfortable. (A speaker of English may say \"three point five trillion\" but \"three point five hundred\" comes off as odd.)\n", - "\n", - "This behavior can occur in other languages. For example, the amount of `$1,500,000` may be read in French as \"une virgule cinq million de dollars\" (\"one point five million dollars\"). " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RgMBIKlYdsGz" - }, - "source": [ - "Our Classifier can be made to accommodate this behavior: we simply need to repeat what we did for `OrdinalFst` and set aside several key terms to trigger our model. For French, we will choose all terms added for values greater than a million. (Chosen empirically.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vEcsUXw5fUEe" - }, - "outputs": [], - "source": [ - "suffix = pynini.union(\n", - " \"million\",\n", - " \"millions\",\n", - " \"milliard\",\n", - " \"milliards\",\n", - " \"billion\",\n", - " \"billions\",\n", - " \"billiard\",\n", - " \"billiards\",\n", - " \"trillion\",\n", - " \"trillions\",\n", - " \"trilliard\",\n", - " \"trilliards\",\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wIIUAsR-fgQA" - }, - "source": [ - "We will then need to use a WFST to graph any numbers the precede these amounts. Note, unlike for our `DecimalFst`, we need to permit cardinals as well as decimals. This is because we want to be able to normalize a phrase like \"three million\" to `3 million` as this will be less obtrusive than `3,000,000`.\n", - "\n", - "As such, we will call a `CardinalFst` and a `DecimalFst` in for `graph_quantities`. Since these are both utilized for our `DecimalFst`, it would be more efficient to just pass them along as function/class variables." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "yern-idtycWg" - }, - "outputs": [], - "source": [ - "def get_quantity(decimal, cardinal_up_to_thousand):\n", - " key_values = pynini.union(\n", - " \"million\",\n", - " \"millions\",\n", - " \"milliard\",\n", - " \"milliards\",\n", - " \"billion\",\n", - " \"billions\",\n", - " \"billiard\",\n", - " \"billiards\",\n", - " \"trillion\",\n", - " \"trillions\",\n", - " \"trilliard\",\n", - " \"trilliards\",\n", - " )\n", - " # The French WFST that this borrows from has not removed leading zeroes yet.\n", - " numbers = cardinal_up_to_thousand @ (\n", - " pynutil.delete(pynini.closure(\"0\")) + pynini.difference(NEMO_DIGIT, \"0\") + pynini.closure(NEMO_DIGIT)\n", - " )\n", - " res = (\n", - " pynutil.insert(\"integer_part: \\\"\")\n", - " + numbers\n", - " + pynutil.insert(\"\\\"\")\n", - " + (\n", - " pynini.union(delete_hyphen, delete_extra_space)\n", - " ) # Can be written either as 'deux-millions' or 'deux millions' depending on whether it registers as a noun or part of cardinal.\n", - " + pynutil.insert(\" quantity: \\\"\")\n", - " + suffix\n", - " + pynutil.insert(\"\\\"\")\n", - " )\n", - " # Union with decimal to permit either a cardinal or decimal representation.\n", - " res |= decimal + delete_extra_space + pynutil.insert(\" quantity: \\\"\") + suffix + pynutil.insert(\"\\\"\")\n", - " return res" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uT4LMo8ADBAq" - }, - "source": [ - "We can now insert this into our Classifier, producing the following:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d2KrCuyGDLwh" - }, - "outputs": [], - "source": [ - "class DecimalFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"decimal\", kind=\"classify\")\n", - " quantities_cardinal = cardinal.graph_hundreds_component_at_least_one_none_zero_digit\n", - " cardinal = cardinal.graph_no_exception\n", - " delete_virgule = pynutil.delete(\"virgule\")\n", - "\n", - " graph_integer = pynutil.insert(\"integer_part: \\\"\") + cardinal + pynutil.insert(\"\\\" \") + delete_space\n", - " graph_integer_or_none = graph_integer | pynutil.insert(\"integer_part: \\\"0\\\" \", weight=.001) # In cases we don't always have an integer preceding\n", - "\n", - " graph_string_of_cardinals = delete_space + cardinal\n", - " graph_string_of_cardinals = pynini.closure(graph_string_of_cardinals, 1)\n", - " graph_fractional = pynutil.insert(\"fractional_part: \\\"\") + graph_string_of_cardinals + pynutil.insert(\"\\\"\")\n", - "\n", - " graph_decimal_no_sign = graph_integer_or_none + delete_virgule + graph_fractional \n", - "\n", - " graph_negative = pynini.cross(\"moins\", \"negative: \\\"-\\\" \") + delete_space\n", - " graph_negative = pynini.closure(graph_negative, 0, 1)\n", - " graph_decimal = graph_negative + graph_decimal_no_sign\n", - "\n", - " # Union default decimal with version that accepts quantities\n", - " graph_decimal |= graph_negative + get_quantity(\n", - " graph_decimal_no_sign, quantities_cardinal\n", - " )\n", - " final_graph = self.add_tokens(graph_decimal)\n", - " self.fst = final_graph.optimize()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "cD-eKqO6qTyh" - }, - "outputs": [], - "source": [ - "cardinal = CardinalFst()\n", - "decimal = DecimalFst(cardinal).fst\n", - "example = \"trois virgule cent-quatre billion\"\n", - "apply_fst(example, decimal)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HiSLKF3RfRZA" - }, - "source": [ - "## Verbalizer" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "QnkOV5FlteQA" - }, - "source": [ - "As before, the Verbalizer is responsible for removing the formatting and rendering a given token in conventional form. As the process remains similar to Ordinals and Cardinals (deleting strings in a regular matter) we will instead focus on a unique concern for `DecimalFst`: numeral spacing.\n", - "\n", - "For some writing systems, decimal numbers and other strings are typically not written as a single string, instead using punctuation to group numbers for clarity. For example, in the United States, integer digits greater than a thousand are separated by commas for every three digits:\n", - "- `12345.678` -> `12,345.678`\n", - "\n", - "A similar rule occurs in French, save it employs spaces on each side of the decimal marker:\n", - "- `12345,6789` -> `12 345,678 9`" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2h4WQZ1a4Cpc" - }, - "source": [ - "While simple enough, this rule poses a slight complication: it works from the left and right of the decimal separator, whereas WFSTs process linearly from the beginning (or end) of strings. As such we will need to break the formatting rule into two components: one for the integer component and one for the decimal component." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ViOFNdZw4-qu" - }, - "source": [ - "Starting with the integer component, we need our subcomponent to recognize every three digits and insert a space before. We can achieve this with some `graph_utils` helper objects - `NEMO_DIGIT` and `NEMO_NON_BREAKING_SPACE`, which accept all digits and non-breaking spaces, respectively. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Z36be2Vo5VbR" - }, - "outputs": [], - "source": [ - "every_three_digits = NEMO_DIGIT ** 3 # accepts a string of three digits\n", - "space_every_three_integer = pynini.closure(NEMO_NON_BREAKING_SPACE + every_three_digits) # inserts space before every three digits." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RSB2gGH-5vwi" - }, - "source": [ - "However, we cannot let the component insert spaces when there are *only* three digits (e.g. `100`.) As such, we need to make sure the insertion only begins starting from the beginning of a string (e.g. when there is a string between one and three digits.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "wfWp3ghH6mDQ" - }, - "outputs": [], - "source": [ - "space_every_three_integer = pynini.closure(NEMO_DIGIT, 1, 3) + space_every_three_integer" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "NJrQYSfA6vyu" - }, - "source": [ - "For the case of the decimal spacing, we simply reverse the logic:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vBP6ncTp6yXX" - }, - "outputs": [], - "source": [ - "space_every_three_decimal = pynini.closure(NEMO_NON_BREAKING_SPACE + every_three_digits)\n", - "space_every_three_decimal = space_every_three_decimal + pynini.closure(NEMO_DIGIT, 1, 3)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WRXPN_gk69VV" - }, - "source": [ - "Placed into our Verbalizer, we would see the following:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "h49eztvs7BXH" - }, - "outputs": [], - "source": [ - "class DecimalFst(GraphFst):\n", - " \"\"\"\n", - " Finite state transducer for verbalizing decimal, e.g.\n", - " decimal { negative: \"true\" integer_part: \"12\" fractional_part: \"5006\" quantity: \"billion\" } -> -12.5006 billion\n", - " \"\"\"\n", - "\n", - " def __init__(self):\n", - " super().__init__(name=\"decimal\", kind=\"verbalize\")\n", - "\n", - " # Need parser to group digits by threes\n", - " exactly_three_digits = NEMO_DIGIT ** 3\n", - " at_most_three_digits = pynini.closure(NEMO_DIGIT, 1, 3)\n", - "\n", - " space_every_three_integer = (\n", - " at_most_three_digits + (pynutil.insert(NEMO_NON_BREAKING_SPACE) + exactly_three_digits).closure()\n", - " )\n", - " space_every_three_decimal = (\n", - " pynini.accep(\",\")\n", - " + (exactly_three_digits + pynutil.insert(NEMO_NON_BREAKING_SPACE)).closure()\n", - " + at_most_three_digits\n", - " )\n", - " group_by_threes = space_every_three_integer | space_every_three_decimal\n", - " self.group_by_threes = group_by_threes\n", - "\n", - " optional_sign = pynini.closure(pynini.cross(\"negative: \\\"true\\\"\", \"-\") + delete_space, 0, 1)\n", - " integer = (\n", - " pynutil.delete(\"integer_part:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_NOT_QUOTE, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - " integer = integer @ group_by_threes\n", - " optional_integer = pynini.closure(integer + delete_space, 0, 1)\n", - " fractional = (\n", - " pynutil.insert(\",\")\n", - " + pynutil.delete(\"fractional_part:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_NOT_QUOTE, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - " fractional = fractional @ group_by_threes\n", - " optional_fractional = pynini.closure(fractional + delete_space, 0, 1)\n", - " quantity = (\n", - " pynutil.delete(\"quantity:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_NOT_QUOTE, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - " optional_quantity = pynini.closure(pynutil.insert(\" \") + quantity + delete_space, 0, 1)\n", - " graph = (optional_integer + optional_fractional + optional_quantity).optimize()\n", - " self.numbers = graph # Saving just the part of the graph used for numbers\n", - " graph = optional_sign + graph\n", - " delete_tokens = self.delete_tokens(graph)\n", - " self.fst = delete_tokens.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Trying out some examples:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "fst = DecimalFst().fst\n", - "\n", - "example1 = 'decimal { integer_part: \"3\" fractional_part: \"10453\" quantity: \"billion\" }'\n", - "example2 = 'decimal { integer_part: \"22323\" fractional_part: \"104553\" }'\n", - "\n", - "apply_fst(example1, fst)\n", - "apply_fst(example2, fst)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CZbshZCW8clI" - }, - "source": [ - "# Money WFST " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xuiv8HMz7yjm" - }, - "source": [ - "Now that we've handled some of the foundational classes, it's time to see how they build up to permit more concrete ones. Let's see how the previous WFSTs assist in building a WFST for normalizing currency: the `MoneyFst`. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wTU2c7MtUpqF" - }, - "source": [ - "## Grammar" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qqyRm8Ru8TDf" - }, - "source": [ - "While the exact phrasing will vary, a valid string for currency will possess the following qualities:\n", - "- A major and/or minor denomination of currency\n", - "- A numeric quantity of the denomination \n", - "\n", - "As our `CardinalFst` and `OrdinalFst` already allow us to normalize the quantity, the only issue for `MoneyFst` is to graph the amounts and build a vocabulary to recognize the denominations.\n", - "\n", - "For French, we will use the following examples to build upon:\n", - "- \"une euros\" -> `1 €`\n", - "- \"deux euros\" -> `2 €` \n", - "- \"deux euros cinq\" -> `2,5 €` \n", - "- \"cinq centimes\" -> `0,5 €`\n", - "- \"deux billions de euros\" -> `2 billions de euros`" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FMqUir9n9_cA" - }, - "source": [ - "These suggest the following requirements of our grammar:\n", - "- There must be a mapping between \"euro\" and \"centime\" and `€` in our vocabulary\n", - "- This mapping must allow both singular and plural forms\n", - "- The currency denomination is phrased between major and minor denominations (\"une euro cinq\" and not \"une cinq euro\")\n", - "- Large quantities of currency are left 'as is' instead of normalized\n", - "\n", - "We may deal with the vocabulary in the typical fashion:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "XN9nbNhB-vEV" - }, - "outputs": [], - "source": [ - "major_currency = pynini.string_map([(\"euro\", \"€\")])\n", - "minor_currency = pynini.string_map([(\"centime\", \"€\")])\n", - "\n", - "graph_plural = pynutil.delete(\"s\").ques\n", - "\n", - "major_currency += graph_plural\n", - "minor_currency += graph_plural" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3aHrm1qPAc-f" - }, - "source": [ - "Moving to the numbers, note that we need to append a leading zero to the value of fractional currency amounts (\"five cents\" -> `$0.05`). We bring back the subgraph from `CardinalFst` that maps tokens to numbers without tokenization to assist with this:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "jwi-yQW1AjvG" - }, - "outputs": [], - "source": [ - "from nemo_text_processing.inverse_text_normalization.fr.taggers import cardinal\n", - "\n", - "cardinal_graph = cardinal.CardinalFst()\n", - "graph_cardinal = cardinal_graph.graph_no_exception # graphs cardinals w/o tokenization\n", - "\n", - "add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert(\"0\") + NEMO_DIGIT)\n", - "graph_fractional_values = graph_cardinal @ add_leading_zero_to_double_digit" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now, let us consider how to manage arge quantities of currency. In our example (\"deux billions de euros\" -> `2 billions de euros`) we see that its behavior mirrors that of our `get_quantity` portion of `DecimalFst`. As such, it would be useful if there was a subcomponent of that graph that we could use in here. Like in the case of `CardinalFst`, let us go back and create a subgraph for later use. Since all our quantities are positive, this would be best accomplished right before incorporating the `negative` property, creating a `self.final_graph_wo_negative`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "class DecimalFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst):\n", - " super().__init__(name=\"decimal\", kind=\"classify\")\n", - " quantities_cardinal = cardinal.graph_hundreds_component_at_least_one_none_zero_digit\n", - " cardinal = cardinal.graph_no_exception\n", - " delete_virgule = pynutil.delete(\"virgule\")\n", - "\n", - " graph_integer = pynutil.insert(\"integer_part: \\\"\") + cardinal + pynutil.insert(\"\\\" \") + delete_space\n", - " graph_integer_or_none = graph_integer | pynutil.insert(\"integer_part: \\\"0\\\" \", weight=.001) # In cases we don't always have an integer preceding\n", - "\n", - " graph_string_of_cardinals = delete_space + cardinal\n", - " graph_string_of_cardinals = pynini.closure(graph_string_of_cardinals, 1)\n", - " graph_fractional = pynutil.insert(\"fractional_part: \\\"\") + graph_string_of_cardinals + pynutil.insert(\"\\\"\")\n", - "\n", - " graph_decimal_no_sign = graph_integer_or_none + delete_virgule + graph_fractional \n", - "\n", - " ### NEW GRAPH HERE\n", - " self.final_graph_wo_negative = graph_decimal_no_sign | get_quantity(\n", - " final_graph_wo_sign, cardinal.graph_hundreds_component_at_least_one_none_zero_digit\n", - " )\n", - " \n", - " graph_negative = pynini.cross(\"moins\", \"negative: \\\"-\\\" \") + delete_space\n", - " graph_negative = pynini.closure(graph_negative, 0, 1)\n", - " graph_decimal = graph_negative + graph_decimal_no_sign\n", - "\n", - " # Union default decimal with version that accepts quantities\n", - " graph_decimal |= graph_negative + get_quantity(\n", - " graph_decimal_no_sign, quantities_cardinal\n", - " )\n", - " final_graph = self.add_tokens(graph_decimal)\n", - " self.fst = final_graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Allowing us to change our grammar to:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from nemo_text_processing.inverse_text_normalization.fr.taggers import cardinal, decimal\n", - "\n", - "cardinal_graph = cardinal.CardinalFst()\n", - "decimal_graph = decimal.DecimalFst(cardinal_graph)\n", - "\n", - "graph_cardinal = cardinal_graph.graph_no_exception # graphs cardinals w/o tokenization\n", - "graph_decimal = decimal_graph.final_graph_wo_negative # graphs positive decimals w/o tokenization\n", - "\n", - "add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert(\"0\") + NEMO_DIGIT)\n", - "graph_fractional_values = graph_cardinal @ add_leading_zero_to_double_digit" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "L1RHoW-TLzIz" - }, - "source": [ - "Note that by doing this, we're also incorporating the formatting from the `decimal` class up to this point. Since these overlap with the `money` class (see next section), we have saved ourselves some work. \n", - "\n", - "Since we already made `graph_quantity` part of our `DecimalFst`, we can avoid dealing with large quantities now. However, this does mean we still need a way to leave currencies 'as is' without normalization. We can do this by using the `project` method, which will create a WFST that excepts either all valid inputs or all valid outputs of another WFST (depending on argument)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "7l_TLtJkMluU" - }, - "outputs": [], - "source": [ - "major_currency_no_normalize = major_currency.project(\"input\")\n", - "apply_fst(\"euro\", major_currency_no_normalize)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "raBdHc_WXEpG" - }, - "source": [ - "We then append this WFST with a WFST that recognizes prepositions commonly used before large values of currency (\"d'\", \"des\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "CEuxiVgDXRBf" - }, - "outputs": [], - "source": [ - "graph_preposition = pynini.union(\"des \", \"d'\") # Used for large amounts (billions de euros)\n", - "major_currency_no_normalize = pynini.closure(graph_preposition, 0, 1) + major_currency.project(\"input\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FlXmf8Fq_Rm1" - }, - "source": [ - "## Classifier" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "T5BBuQRzLuXS" - }, - "source": [ - "For the Money semiotic class, we have available the following properties for tokenization:\n", - "- `integer_part`\n", - "- `fractional_part` \n", - "- `currency`\n", - "\n", - "Laying the initial groundwork seems simple enough. We first instantiate our `MoneyFst` classifier with our initial grammars:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "EZaCeHcFWVP3" - }, - "outputs": [], - "source": [ - "class MoneyFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst, decimal: GraphFst):\n", - " super().__init__(name=\"money\", kind=\"classify\")\n", - " major_currency = pynini.string_map([(\"euro\", \"€\")])\n", - " minor_currency = pynini.string_map([(\"centime\", \"€\")])\n", - "\n", - " graph_plural = pynutil.delete(\"s\").ques\n", - "\n", - " major_currency += graph_plural\n", - " minor_currency += graph_plural\n", - "\n", - " major_currency_no_normalize = major_currency.project(\"input\")\n", - " graph_preposition = pynini.union(\"des \", \"d'\") # Used for large amounts (billions de euros)\n", - " major_currency_no_normalize = graph_preposition + major_currency.project(\"input\")\n", - "\n", - " graph_cardinal = cardinal.graph_no_exception\n", - " graph_decimal = decimal.final_graph_wo_negative\n", - "\n", - " add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert(\"0\") + NEMO_DIGIT)\n", - " graph_fractional_values = graph_cardinal @ add_leading_zero_to_double_digit" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_bpkXroLWaBo" - }, - "source": [ - "Let us now manage the `currency` property. We have the following scenarios to consider:\n", - "- Major denomination only\n", - "- Minor denomination only\n", - "- Major denomination and implicit minor denomination (\"cinq euro trois\")\n", - "- Major denomination and explicit minor denomination (\"cinq euros et trois centimes\")\n", - "- Large quantities of euros (\"cinq billion des euros\")\n", - "\n", - "Note how across cases the use of `graph_cardinal` and `graph_decimal` will be applied differently. Further, we may have varying orders in which tags are assigned proper values. For instance, if we have only minor denomination we would assign `fractional_part` before `currency`. Meanwhile, major denomination and implicit minor denomination would be the order of `integer_part`, `currency`, `fractional_part`. While we could try and figure out a way to preserve order, recall that the use of permutations in NeMo ITN makes that unnecessary: we can assume the desired order of tags reach our Verbalizer without make overt efforts in our Classifier! \n", - "\n", - "For example, let's say we need to process \"five dollars\" as `$5.00`. Processed linearly, we could get a token sequence along the lines of: `{ integer_part: \"5\" currency: \"$\" }`. If we passed this token array straight to a Verbalizer, we would need to configure a graph that effectively reverses the order so we could parse the `currency` field prior to the `integer_part` field, perhaps something along the lines of: \n", - "\n", - "`pynutil.insert(\"$\") + delete_space + pynutil.delete('integer_part: \\\"') +.... + pynutil.delete('currency: \"$\"')`\n", - "\n", - "But since NeMo creates permutations of our Classifier outputs, this is unnecessary. We can simply assume whatever would be the most convenient order for us (e.g. `{ currency: \"$\" integer_part: \"5\" }`) and build our Verbalizer around that:\n", - "\n", - "`pynutil.delete('currency: \\\"') + NEMO_SIGMA + pynutil.delete('\\\" integer_part: \\\"') + NEMO_DIGIT +...`\n", - "\n", - "Along with helping to keep our script simpler (we can focus simply on tokenization and not worry about what input order our Verbalizers will accept), this also allows us to overcome structural constraints of WFSTs, namely that they are [limited in reordering text strings](https://en.wikipedia.org/wiki/Pushdown_automaton)." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "fMZ13D2Dh9ZF" - }, - "source": [ - "Keeping this in mind, let's begin mapping the proper tags. Since they're relatively simple, we can start with only major and minor denominations:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "EtwWLp7VbbjM" - }, - "outputs": [], - "source": [ - "graph_integer_component = pynutil.insert(\"integer_part: \\\"\") + graph_cardinal + pynutil.insert(\"\\\"\")\n", - "graph_fractional_component = pynutil.insert(\"fractional_part: \\\"\") + graph_fractional_values + pynutil.insert(\"\\\"\")\n", - "\n", - "graph_major_currency = pynutil.insert(\" currency: \\\"\") + major_currency + pynutil.insert(\"\\\"\")\n", - "graph_minor_currency = pynutil.insert(\" currency: \\\"\") + minor_currency + pynutil.insert(\"\\\"\")\n", - "\n", - "graph_only_major_money = graph_integer_component + delete_space + graph_major_currency\n", - "graph_only_minor_money = graph_fractional_component + delete_space + graph_minor_currency " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XTmxrK4DmS39" - }, - "source": [ - "Now we may append the case of an implicit `fractional_part` to `graph_only_major_money`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Zvzn3pQinkT0" - }, - "outputs": [], - "source": [ - "implicit_fractional_part = delete_space + pynutil.insert(\"fractional_part: \\\"\") + graph_fractional_values + pynutil.insert(\"\\\"\") \n", - "implicit_fractional_part = pynini.closure(implicit_fractional_part, 0, 1) " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tKFZkCVmn1OX" - }, - "source": [ - "And the explicit fractional portion:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d_h0pTlMn3jz" - }, - "outputs": [], - "source": [ - "delete_et = pynutil.delete(\"et \") # Sometimes prefaces the minor currency\n", - "delete_et = pynini.closure(delete_et, 0 , 1)\n", - "\n", - "delete_minor = pynutil.delete(minor_currency.project(\"input\")) # to remove the minor currency\n", - "\n", - "explicit_fractional_part = pynutil.insert(\"fractional_part: \\\"\") + graph_fractional_values + pynutil.insert(\"\\\"\") \n", - "explicit_fractional_part = delete_space + delete_et + explicit_fractional_part + delete_space + delete_minor\n", - "explicit_fractional_part = pynini.closure(explicit_fractional_part, 0, 1)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rvnpAudgo-o3" - }, - "source": [ - "We join them together:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "qYzlIRWTpD8e" - }, - "outputs": [], - "source": [ - "graph_major_money = graph_only_major_money + (implicit_fractional_part | explicit_fractional_part)\n", - "graph_standard_money = graph_major_money | graph_only_minor_money" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TzeaKXVzpYs8" - }, - "source": [ - "Finishing with the case the large quantities of money, we need to use `graph_decimal` so we can exploit its ability to map quantities. Note that since we are using a pre-existing WFST, we can ignore inserting the tags ourselves, since this is already done by the Decimal WFST. As long as we remember to process this aspect with our Verbalizer, we can spare ourselves the extra step." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LnqX9mGFpmJm" - }, - "outputs": [], - "source": [ - "graph_large_money = pynutil.insert(\" currency: \\\"\") + major_currency_no_normalize + pynutil.insert(\"\\\"\")\n", - "graph_large_money = graph_decimal + delete_space + graph_large_money" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "24TUZnJKqgPA" - }, - "source": [ - "Alltogether, this would give the following Classifier:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "B7-muCO2qizg" - }, - "outputs": [], - "source": [ - "class MoneyFst(GraphFst):\n", - " def __init__(self, cardinal: GraphFst, decimal: GraphFst):\n", - " super().__init__(name=\"money\", kind=\"classify\")\n", - " major_currency = pynini.string_map([(\"euro\", \"€\")])\n", - " minor_currency = pynini.string_map([(\"centime\", \"€\")])\n", - "\n", - " graph_plural = pynutil.delete(\"s\").ques\n", - "\n", - " major_currency += graph_plural\n", - " minor_currency += graph_plural\n", - "\n", - " major_currency_no_normalize = major_currency.project(\"input\")\n", - " graph_preposition = pynini.union(\"des \", \"d'\") # Used for large amounts (billions de euros)\n", - " major_currency_no_normalize = graph_preposition + major_currency.project(\"input\")\n", - "\n", - " graph_cardinal = cardinal.graph_no_exception\n", - " graph_decimal = decimal.final_graph_wo_negative\n", - "\n", - " add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert(\"0\") + NEMO_DIGIT)\n", - " graph_fractional_values = graph_cardinal @ add_leading_zero_to_double_digit\n", - "\n", - " graph_integer_component = pynutil.insert(\"integer_part: \\\"\") + graph_cardinal + pynutil.insert(\"\\\"\")\n", - " graph_fractional_component = pynutil.insert(\"fractional_part: \\\"\") + graph_fractional_values + pynutil.insert(\"\\\"\")\n", - "\n", - " graph_major_currency = pynutil.insert(\" currency: \\\"\") + major_currency + pynutil.insert(\"\\\"\")\n", - " graph_minor_currency = pynutil.insert(\" currency: \\\"\") + minor_currency + pynutil.insert(\"\\\"\")\n", - "\n", - " graph_only_major_money = graph_integer_component + delete_space + graph_major_currency\n", - " graph_only_minor_money = graph_fractional_component + delete_space + graph_minor_currency \n", - "\n", - " implicit_fractional_part = delete_space + pynutil.insert(\"fractional_part: \\\"\") + graph_fractional_values + pynutil.insert(\"\\\"\") \n", - " implicit_fractional_part = pynini.closure(implicit_fractional_part, 0, 1) \n", - "\n", - "\n", - " delete_et = pynutil.delete(\"et \") # Sometimes prefaces the minor currency\n", - " delete_et = pynini.closure(delete_et, 0 , 1)\n", - "\n", - " delete_minor = pynutil.delete(minor_currency.project(\"input\")) # to remove the minor currency\n", - "\n", - " explicit_fractional_part = pynutil.insert(\"fractional_part: \\\"\") + graph_fractional_values + pynutil.insert(\"\\\"\") \n", - " explicit_fractional_part = delete_space + delete_et + explicit_fractional_part + delete_space + delete_minor\n", - " explicit_fractional_part = pynini.closure(explicit_fractional_part, 0, 1)\n", - "\n", - " graph_major_money = graph_only_major_money + (implicit_fractional_part | explicit_fractional_part)\n", - "\n", - " graph_large_money = pynutil.insert(\" currency: \\\"\") + major_currency_no_normalize + pynutil.insert(\"\\\"\")\n", - " graph_large_money = graph_decimal + delete_space + graph_large_money\n", - "\n", - " final_graph = graph_large_money | graph_major_money | graph_only_minor_money\n", - "\n", - " final_graph = self.add_tokens(final_graph)\n", - " self.fst = final_graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's see the results:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from nemo_text_processing.inverse_text_normalization.fr.taggers import decimal, cardinal\n", - "\n", - "cardFst = cardinal.CardinalFst()\n", - "decFst = decimal.DecimalFst(cardFst)\n", - "\n", - "moneyFst = MoneyFst(cardFst, decFst).fst\n", - "\n", - "example = \"douze virgule cinq billions d'euros\"\n", - "\n", - "apply_fst(example, moneyFst)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gxdcyuLmAZZa" - }, - "source": [ - "## Verbalizer" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZZFDWNwY6sOG" - }, - "source": [ - "By this point, the creation of the Verbalizer should be rather straight-forward - delete the expected tokens and perform any specific formatting that was not caught by the Classifier. \n", - "\n", - "In fact, it is so straight-forward that much of the work does not even need to be explicitly managed by the Verbalizer. As mentioned previously, two of the properties we inserted in our Classifier where already referenced in our `DecimalFst` - `integer_part` and `fractional_part`. We even went so far to directly call a component of `DecimalFst` in our Classifier. As such, outside of the `currency` property - there is little in our Money token that is different from a standard Decimal token. Indeed, even the normalized forms are similar (`200,5` vs. `200,5 €`.) " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "T7sgH0t79tmU" - }, - "source": [ - "Given these similarities, it seems that we can save ourselves some work and simply use the Decimal Verbalizer to manage much of the normalization. Let's look at the basic format of our `MoneyFst` verbalizer, writing it so it accepts a `DecimalFst` as input:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "BEu8nITP9mSG" - }, - "outputs": [], - "source": [ - "class MoneyFst(GraphFst):\n", - " def __init__(self, decimal: GraphFst):\n", - " super().__init__(name=\"money\", kind=\"verbalize\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "JYVLou5N-Dk8" - }, - "source": [ - "We manage the issue of deleting the `currency` property:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LO35tJ7G-H6N" - }, - "outputs": [], - "source": [ - "class MoneyFst(GraphFst):\n", - " def __init__(self, decimal: GraphFst):\n", - " super().__init__(name=\"money\", kind=\"verbalize\")\n", - " unit = (\n", - " pynutil.delete(\"currency:\")\n", - " + delete_extra_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_NOT_QUOTE, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bDS8XSII-Dpd" - }, - "source": [ - "Now consider, we need to normalize an integer component, a fractional component, and a decimal to separate them. Since NeMo will automatically permutate all tags, we can assume whatever order we want. As such, we can assume we get the exact order that is accepted by our `DecimalFst`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "VtGfpjVA-r3u" - }, - "outputs": [], - "source": [ - " def __init__(self, decimal: GraphFst):\n", - " super().__init__(name=\"money\", kind=\"verbalize\")\n", - " unit = (\n", - " pynutil.delete(\"currency:\")\n", - " + delete_extra_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_NOT_QUOTE, 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - " graph = decimal.numbers + delete_space + unit\n", - " delete_tokens = self.delete_tokens(graph)\n", - " self.fst = delete_tokens.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZefxZLIU-uRU" - }, - "source": [ - "It is as simple and compact as appending the `unit` component to the preexisting `decimal.numbers`. \n", - "\n", - "This feature is worth keeping in mind as you build up to more concrete classes: the combination of guaranteed tag permutations and prebuilt Verbalizers make the addition of semiotic classes progressively simpler despite the building complexity of your entire grammar." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WydC7Cn28l5Y" - }, - "source": [ - "# Time WFST " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "VelunbumCJJe" - }, - "source": [ - "Our next composite graph will be for the Time WFST. Here, you may see more variation between your language and our example than with our previous classes. This is for a number of reasons, among them being that while there may be some standard cross linguistic patterns regarding time (e.g. `quantity_of_hours + quantity_of_minutes`), the use of various equivalent phrases can make an exhaustive grammar incredibly specific (e.g. consider managing \"twelve fifteen\", \"twelve and a quarter\", \"quarter past twelve\", \"quarter after twelve\", and \"forty five until one\" all together). You may find yourself drawing upon WFSTs that accommodate Cardinals, Fractions, and some basic subtraction.\n", - "\n", - "As such, we are going to focus on those aspects of the Time WFST that are necessary for a functional normalization of time related phrases, saving a more exhaustive grammar for your own specific languages and use cases." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8wqb28wzATOR" - }, - "source": [ - "## Grammar" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "AVntDM3AEz0v" - }, - "source": [ - "For our Time WFST, we will focus on the following aspects:\n", - "- Use of 24 or 12 hour base\n", - "- Use of fraction terminology (e.g. \"quarter\" = `15`)\n", - "- Accommodation of key-words (\"noon\", \"midnight\")\n", - "- Counting backwards from the hour (\"ten to five\", \"five to three\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "seU9hTbgFgu7" - }, - "source": [ - "We'll start with the basic system.\n", - "\n", - "For French, time operates on a twenty-four hour system, with the zeroth hour being midnight. Time is given in the following format:\n", - "\n", - "`cardinal + heure(s) + (cardinal)` \n", - "\n", - "This is normalized as:\n", - "\n", - "`cardinal h (cardinal)`\n", - "\n", - "For instance, for `3:03`, we would have:\n", - "- input: \"trois heures trois\"\n", - "- output: `3 h 03`\n", - "\n", - "As such, our grammar needs to utilize a Cardinal WFST and have a means to accept \"heures\" from the input. Taking care of the latter case is simple enough:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "HTSVxf4fI_ND" - }, - "outputs": [], - "source": [ - "graph_heures = pynini.accep(\"heure\") + pynini.accep(\"s\").ques\n", - "graph_heures = pynutil.delete(graph_heures)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6LW7pXaXJSZa" - }, - "source": [ - "For the cardinals, we could pass an instance of `CardinalFST` to our graph. But do we really need that level of coverage? We only really need to cover the numbers 0 - 60, which we could simply write a new WFST for. Further, it may be beneficial to allow our graph to separate possible ambiguity. While we will not cover it in our tutorial, you may in the future find it necessary to build a WFST for Measurements, of which quantities of time may play a part. Would it not be helpful for you WFST to know that \"thirty hours\" could only ever be a measurement instead of a possible time of day?\n", - "\n", - "Given the little amount of effort necessary and the quick benefit, we choose to make our hours and minutes explicit in the Time WFST." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "R4aa06ZPLKIR" - }, - "outputs": [], - "source": [ - "hours = pynini.string_map([\n", - " (\"zéro\",\"0\"),\n", - " (\"une\",\"1\"),\n", - " (\"deux\",\"2\"),\n", - " (\"trois\",\"3\"),\n", - " (\"quatre\",\"4\"),\n", - " (\"cinq\",\"5\"),\n", - " (\"six\",\"6\"),\n", - " (\"sept\",\"7\"),\n", - " (\"huit\",\"8\"),\n", - " (\"neuf\",\"9\"),\n", - " (\"dix\",\"10\"),\n", - " (\"onze\",\"11\"),\n", - " (\"douze\",\"12\"),\n", - " (\"treize\",\"13\"),\n", - " (\"quatorze\",\"14\"),\n", - " (\"quinze\",\"15\"),\n", - " (\"seize\",\"16\"),\n", - " (\"dix-sept\",\"17\"),\n", - " (\"dix-huit\",\"18\"),\n", - " (\"dix-neuf\",\"19\"),\n", - " (\"vingt\",\"20\"),\n", - " (\"vingt-et-une\",\"21\"),\n", - " (\"vingt et une\",\"21\"),\n", - " (\"vingt-deux\",\"22\"),\n", - " (\"vingt-trois\",\"23\"),\n", - " (\"vingt-quatre\",\"24\"),\n", - "])\n", - "minutes = pynini.string_map([\n", - " (\"une\", \"01\"),\n", - " (\"deux\", \"02\"),\n", - " (\"trois\", \"03\"),\n", - " (\"quatre\", \"04\"),\n", - " (\"cinq\", \"05\"),\n", - " (\"six\", \"06\"),\n", - " (\"sept\", \"07\"),\n", - " (\"huit\", \"08\"),\n", - " (\"neuf\", \"09\"),\n", - " (\"dix\", \"10\"),\n", - " (\"onze\", \"11\"),\n", - " (\"douze\", \"12\"),\n", - " (\"treize\", \"13\"),\n", - " (\"quatorze\", \"14\"),\n", - " (\"quinze\", \"15\"),\n", - " (\"seize\", \"16\"),\n", - " (\"dix-sept\", \"17\"),\n", - " (\"dix-huit\", \"18\"),\n", - " (\"dix-neuf\", \"19\"),\n", - " (\"vingt\", \"20\"),\n", - " (\"vingt-et-une\", \"21\"),\n", - " (\"vingt et une\", \"21\"),\n", - " (\"vingt-deux\", \"22\"),\n", - " (\"vingt-trois\", \"23\"),\n", - " (\"vingt-quatre\", \"27\"),\n", - " (\"vingt-cinq\", \"25\"),\n", - " (\"vingt-six\", \"26\"),\n", - " (\"vingt-sept\", \"27\"),\n", - " (\"vingt-huit\", \"28\"),\n", - " (\"vingt-neuf\", \"29\"),\n", - " (\"trente\", \"30\"),\n", - " (\"trente-et-une\", \"31\"),\n", - " (\"trente et une\", \"31\"),\n", - " (\"trente-deux\", \"32\"),\n", - " (\"trente-trois\", \"33\"),\n", - " (\"trente-quatre\", \"34\"),\n", - " (\"trente-cinq\", \"35\"),\n", - " (\"trente-six\", \"36\"),\n", - " (\"trente-sept\", \"37\"),\n", - " (\"trente-huit\", \"38\"),\n", - " (\"trente-neuf\", \"39\"),\n", - " (\"quarante\", \"40\"),\n", - " (\"quarante-et-une\", \"41\"),\n", - " (\"quarante et une\", \"41\"),\n", - " (\"quarante-deux\", \"42\"),\n", - " (\"quarante-trois\", \"43\"),\n", - " (\"quarante-quatre\", \"44\"),\n", - " (\"quarante-cinq\", \"45\"),\n", - " (\"quarante-six\", \"46\"),\n", - " (\"quarante-sept\", \"47\"),\n", - " (\"quarante-huit\", \"48\"),\n", - " (\"quarante-neuf\", \"49\"),\n", - " (\"cinquante\", \"50\"),\n", - " (\"cinquante-et-une\", \"51\"),\n", - " (\"cinquante et une\", \"51\"),\n", - " (\"cinquante-deux\", \"52\"),\n", - " (\"cinquante-trois\", \"53\"),\n", - " (\"cinquante-quatre\", \"54\"),\n", - " (\"cinquante-cinq\", \"55\"),\n", - " (\"cinquante-six\", \"56\"),\n", - " (\"cinquante-sept\", \"57\"),\n", - " (\"cinquante-huit\", \"58\"),\n", - " (\"cinquante-neuf\", \"59\"),\n", - "])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4SmNsNKLM9cC" - }, - "source": [ - "Now that we've managed the basic graph, we can address some of the more niche rules of French timekeeping.\n", - "\n", - "To start, French employs some colloquialisms that will be familiar to English speakers: minutes that are multiples of fifteen are referred to as fractions of a clock. In particular:\n", - "- `5 h 15` -> \"cinq heures **et quart**\"\n", - "- `5 h 30` -> \"cinq heures **et demie**\"\n", - "- `5 h 45` -> \"cinq eures **et trois quarts**\"\n", - "\n", - "We thus need a means of rendering these as their numerical equivalents:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "xHe3nfrpSlrE" - }, - "outputs": [], - "source": [ - "# Mapping 'et demi' and 'et qart'\n", - "graph_et = pynutil.delete(\"et\") + delete_space\n", - "\n", - "graph_demi = pynini.accep(\"demi\")\n", - "graph_demi += pynini.accep(\"e\").ques # people vary on feminine or masculine form\n", - "graph_demi = pynini.cross(graph_demi, \"30\")\n", - "\n", - "graph_quart = pynini.accep('quart')\n", - "graph_quart = pynini.cross(graph_quart, '15')\n", - "graph_trois_quart = pynini.cross(\"trois quarts\", \"45\")\n", - "\n", - "graph_fractions = graph_demi | graph_quart | graph_trois_quart\n", - "graph_fractions = graph_et + graph_fractions" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "HD2wobIQS3fX" - }, - "source": [ - "Also like English, French will use key words to designate a specific timeslot. Noon and midnight are \"midi\" and \"minuit\" respectively." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ahbkiZFuTN2t" - }, - "outputs": [], - "source": [ - "# Midi and minuit\n", - "graph_midi = pynini.cross(\"midi\", \"12\")\n", - "graph_minuit = pynini.cross(\"minuit\", \"0\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6OyMoqfZTX1U" - }, - "source": [ - "Now it's time to throw a wrench into things: counting backwards from the hour. How are we to get what is essentially a graph to do the subtraction necessarily for \"ten to twelve\" to become `11:50`?\n", - "\n", - "Easy: we build the subtraction into the graph itself. That is, we map the hours and minutes produced by our graph onto another graph that produces their amount shifted back a value.\n", - "\n", - "Let's take our \"ten to twelve\" example. Normally \"ten\" would map to `10` and \"twelve\" to `12`. But with these new graphs, the detection of the pattern `minute + to + hour` would signal that `10` should now become `50` and `12` become `11`." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "uMWifbm1VQjP" - }, - "source": [ - "Let us do this for our French example. Luckily enough, the indication that a French string is regular: counting backwards from the hour is by use of the pattern `cardinal + heures + moins + minutes`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "c4bV3T1pViCH" - }, - "outputs": [], - "source": [ - "hours_to = pynini.string_map([\n", - " (\"1\",\"0\"),\n", - " (\"2\",\"1\"),\n", - " (\"3\",\"2\"),\n", - " (\"4\",\"3\"),\n", - " (\"5\",\"4\"),\n", - " (\"6\",\"5\"),\n", - " (\"7\",\"6\"),\n", - " (\"8\",\"7\"),\n", - " (\"9\",\"8\"),\n", - " (\"10\",\"9\"),\n", - " (\"11\",\"10\"),\n", - " (\"12\",\"11\"),\n", - " (\"13\",\"12\"),\n", - " (\"14\",\"13\"),\n", - " (\"15\",\"14\"),\n", - " (\"16\",\"15\"),\n", - " (\"17\",\"16\"),\n", - " (\"18\",\"17\"),\n", - " (\"19\",\"18\"),\n", - " (\"20\",\"19\"),\n", - " (\"21\",\"20\"),\n", - " (\"22\",\"21\"),\n", - " (\"23\",\"22\"),\n", - " (\"24\",\"23\"),\n", - " (\"0\",\"23\"),\n", - "])\n", - "minutes_to = pynini.string_map([\n", - " (\"59\", \"01\"),\n", - " (\"58\", \"02\"),\n", - " (\"57\", \"03\"),\n", - " (\"56\", \"04\"),\n", - " (\"55\", \"05\"),\n", - " (\"54\", \"06\"),\n", - " (\"53\", \"07\"),\n", - " (\"52\", \"08\"),\n", - " (\"51\", \"09\"),\n", - " (\"50\", \"10\"),\n", - " (\"49\", \"11\"),\n", - " (\"48\", \"12\"),\n", - " (\"47\", \"13\"),\n", - " (\"46\", \"14\"),\n", - " (\"45\", \"15\"),\n", - " (\"44\", \"16\"),\n", - " (\"43\", \"17\"),\n", - " (\"42\", \"18\"),\n", - " (\"41\", \"19\"),\n", - " (\"40\", \"20\"),\n", - " (\"39\", \"21\"),\n", - " (\"38\", \"22\"),\n", - " (\"37\", \"23\"),\n", - " (\"36\", \"24\"),\n", - " (\"35\", \"25\"),\n", - " (\"34\", \"26\"),\n", - " (\"33\", \"27\"),\n", - " (\"32\", \"28\"),\n", - " (\"31\", \"29\"),\n", - " (\"30\", \"30\"),\n", - " (\"29\", \"31\"),\n", - " (\"28\", \"32\"),\n", - " (\"27\", \"33\"),\n", - " (\"26\", \"34\"),\n", - " (\"25\", \"35\"),\n", - " (\"24\", \"36\"),\n", - " (\"23\", \"37\"),\n", - " (\"22\", \"38\"),\n", - " (\"21\", \"39\"),\n", - " (\"20\", \"40\"),\n", - " (\"19\", \"41\"),\n", - " (\"18\", \"42\"),\n", - " (\"17\", \"43\"),\n", - " (\"16\", \"44\"),\n", - " (\"15\", \"45\"),\n", - " (\"14\", \"46\"),\n", - " (\"13\", \"47\"),\n", - " (\"12\", \"48\"),\n", - " (\"11\", \"49\"),\n", - " (\"10\", \"50\"),\n", - " (\"09\", \"51\"),\n", - " (\"08\", \"52\"),\n", - " (\"07\", \"53\"),\n", - " (\"06\", \"54\"),\n", - " (\"05\", \"55\"),\n", - " (\"04\", \"56\"),\n", - " (\"03\", \"57\"),\n", - " (\"02\", \"58\"),\n", - " (\"01\", \"59\"),\n", - "])\n", - "graph_moins = pynutil.delete(\"moins\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "XOKETkIYZy5M" - }, - "source": [ - "Why graph the digits instead of the tokens themselves? Along with avoiding some minor repetition and making editing more apparent, it allows this subgraph to be ported to other languages - if so desired.\n", - "\n", - "Further, it helps us illustrate a helpful idea within this tutorial: as long as a pattern is regular and/or finite, it is no major issue to accommodate it in our graph, regardless of mathematic or logic system it employs." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "DJbFiD2fAUc5" - }, - "source": [ - "## Classifier" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cK0SGXntaDkI" - }, - "source": [ - "Once again we place the grammar within the proper child class of `GraphFst`. We also insert the proper tags for the `Time` class, which are:\n", - "- `hours`\n", - "- `minutes`\n", - "- `suffix` (explained within this section)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9Eq5r-_VbBIg" - }, - "outputs": [], - "source": [ - "graph_hours_component = pynini.union(hours, graph_midi, graph_minuit)\n", - "graph_hours_component = pynutil.insert(\"hours: \\\"\") + graph_hours_component + pynutil.insert(\"\\\"\")\n", - "\n", - "graph_minutes_component = (\n", - " pynutil.insert(\" minutes: \\\"\") + pynini.union(minutes, graph_fractions) + pynutil.insert(\"\\\"\")\n", - ") \n", - "graph_minutes_component = delete_space + graph_minutes_component\n", - "\n", - "graph_time_standard = (graph_hours_component + delete_space + graph_heures \n", - " + pynini.closure(graph_minutes_component, 0, 1))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2avfS3IacSiC" - }, - "source": [ - "We now setup the alternate graph that allows backwards counting. Note, this is triggered by the occurrence of \"moins\" between the hour and minute component." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "TmpwisOVcn0T" - }, - "outputs": [], - "source": [ - "graph_hours_to_component = hours | graph_midi | graph_minuit\n", - "graph_hours_to_component @= hours_to\n", - "graph_hours_to_component = pynutil.insert(\"hours: \\\"\") + graph_hours_to_component + pynutil.insert(\"\\\"\")\n", - "graph_hours_to_component = graph_hours_to_component + delete_space + graph_heures\n", - "\n", - "graph_minutes_to_component = (minutes | graph_demi | # No 'et' in fractions\n", - " (pynutil.delete(\"le \") + graph_quart) | graph_trois_quart)\n", - "graph_minutes_to_component @= minutes_to\n", - "graph_minutes_to_component = pynutil.insert(\" minutes: \\\"\") + graph_minutes_to_component + pynutil.insert(\"\\\"\")\n", - "\n", - "graph_time_to = graph_hours_to_component + delete_space + graph_moins + delete_space + graph_minutes_to_component" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FkO4tRRfdQT4" - }, - "source": [ - "We now join it with our main component, allowing us to graph all times:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0O0vUVizdU8c" - }, - "outputs": [], - "source": [ - "graph_time = graph_time_standard | graph_time_to" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jbX4JV-LdY3Y" - }, - "source": [ - "Once again we throw a wrench into things with the `suffix` feature. As in the case of Ordinals and Decimals, key-words can play into our Time WFST. For French, this occurs with the words \"du matin\", \"de l'après-midi\", and \"du soir\". (Respectively: \"in the morning\", \"in the afternoon\", and \"in the evening\".) Much like in English, these phrases alter how we write down the time. But instead of indicating `a.m.` or `p.m.`, these indicate *what hour system is used*. For example:\n", - "- \"deux heures du matin\" -> `2 h` = `2:00 a.m.`\n", - "- \"deux heures de l'après-midi\" -> `14 h` = `2:00 p.m.`\n", - "\n", - "Only a twelve hour system is used when these suffixes accompany the time. As such, our Classifier will need to either adjust the times like in the case of counting backwards or must pass the information to the Verbalizer so it can adjust. \n", - "\n", - "Since our Classifier is long enough as is, we will simply store this information in the `suffix` property and allow the Verbalizer to manage." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OqVa78zRgJw9" - }, - "outputs": [], - "source": [ - "graph_suffix_am = pynini.cross(\"du matin\", \"am\")\n", - "graph_suffix_pm = pynini.string_map([(\"de l'après-midi\", \"pm\"),(\"du soir\", \"pm\")])\n", - "\n", - "graph_suffix = pynini.cross(graph_suffix_am, \"am\") | pynini.cross(graph_suffix_pm, \"pm\")\n", - "\n", - "graph_suffix_component = pynutil.insert(\" suffix: \\\"\") + graph_suffix + pynutil.insert(\"\\\"\")\n", - "graph_suffix_component = delete_space + graph_suffix_component\n", - "graph_suffix_component = pynini.closure(graph_suffix_component, 0, 1)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-LaJMIjUf1XR" - }, - "source": [ - "And we append to our graph:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "76myCFiggX3E" - }, - "outputs": [], - "source": [ - "class TimeFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"time\", kind=\"classify\")\n", - " \"\"\"grammar omitted for length\n", - " ....\n", - " ....\n", - " ....\n", - " \"\"\"\n", - " graph_hours_component = pynini.union(hours, graph_midi, graph_minuit)\n", - " graph_hours_component = pynutil.insert(\"hours: \\\"\") + graph_hours_component + pynutil.insert(\"\\\"\")\n", - "\n", - " graph_minutes_component = (\n", - " pynutil.insert(\" minutes: \\\"\") + pynini.union(minutes, graph_fractions) + pynutil.insert(\"\\\"\")\n", - " ) \n", - " graph_minutes_component = delete_space + graph_minutes_component\n", - "\n", - " graph_time_standard = (graph_hours_component + delete_space + graph_heures \n", - " + pynini.closure(graph_minutes_component, 0, 1))\n", - "\n", - " graph_hours_to_component = hours | graph_midi | graph_minuit\n", - " graph_hours_to_component @= hours_to\n", - " graph_hours_to_component = pynutil.insert(\"hours: \\\"\") + graph_hours_to_component + pynutil.insert(\"\\\"\")\n", - " graph_hours_to_component = graph_hours_to_component + delete_space + graph_heures\n", - "\n", - " graph_minutes_to_component = (minutes | graph_demi | # No 'et' in fractions\n", - " (pynutil.delete(\"le \") + graph_quart) | graph_trois_quart)\n", - " graph_minutes_to_component @= minutes_to\n", - " graph_minutes_to_component = pynutil.insert(\" minutes: \\\"\") + graph_minutes_to_component + pynutil.insert(\"\\\"\")\n", - "\n", - " graph_time_to = graph_hours_to_component + delete_space + graph_moins + delete_space + graph_minutes_to_component\n", - "\n", - " graph_time_no_suffix = graph_time_standard | graph_time_to\n", - "\n", - " graph_suffix_am = pynini.cross(\"du matin\", \"am\")\n", - " graph_suffix_pm = pynini.string_map([(\"de l'après-midi\", \"pm\"),(\"du soir\", \"pm\")])\n", - "\n", - " graph_suffix = pynini.cross(graph_suffix_am, \"am\") | pynini.cross(graph_suffix_pm, \"pm\")\n", - "\n", - " graph_suffix_component = pynutil.insert(\" suffix: \\\"\") + graph_suffix + pynutil.insert(\"\\\"\")\n", - " graph_suffix_component = delete_space + graph_suffix_component\n", - " graph_suffix_component = pynini.closure(graph_suffix_component, 0, 1)\n", - " \n", - " final_graph = graph_time_no_suffix + graph_suffix_component\n", - "\n", - " final_graph = self.add_tokens(final_graph)\n", - "\n", - " self.fst = final_graph.optimize()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's see how we did:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "time = TimeFst().fst\n", - "example = \"quatre heures moins cinq\"\n", - "apply_fst(example, time)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lPlJ1qyeAWOL" - }, - "source": [ - "## Verbalizer" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "CrO-xtJ87PEl" - }, - "source": [ - "The initial part of the Verbalizer should appear familiar. We delete the property tags `hours` and `minutes`, making sure they preserve the actual values for formatting." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "fCzZKR7ek0Mz" - }, - "outputs": [], - "source": [ - "hour = (\n", - " pynutil.delete(\"hours:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1, 2)\n", - " + pynutil.delete(\"\\\"\")\n", - ")\n", - "minute = (\n", - " pynutil.delete(\"minutes:\")\n", - " + delete_extra_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1, 2)\n", - " + pynutil.delete(\"\\\"\")\n", - ")\n", - "graph = hour + delete_extra_space + pynutil.insert(\"h\") + minute.ques" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WnVV9GUKk-b7" - }, - "source": [ - "We then deal with the case of `suffix`. We first note that if the suffix is for a morning time (before noon), then there is no further conversion that is needed. We may simply delete the property and its value." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "haOEiSbglc6s" - }, - "outputs": [], - "source": [ - "day_suffixes = pynutil.delete(\"suffix: \\\"am\\\"\")\n", - "\n", - "graph = hours + delete_extra_space + pynutil.insert(\"h\") + minute.ques + delete_space + day_suffixes.ques" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wL0FNg6Xlhb-" - }, - "source": [ - "Meanwhile, the post-noon suffixes would require us shifting the hours value by twelve. Much like in the case of counting backwards from the hour, we can simply create a WFST to do this addition work for us." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "YLrabUNplwG7" - }, - "outputs": [], - "source": [ - "hour_to_night = pynini.string_map([\n", - " (\"1\", \"13\"),\n", - " (\"2\", \"14\"),\n", - " (\"3\", \"15\"),\n", - " (\"4\", \"16\"),\n", - " (\"5\", \"17\"),\n", - " (\"6\", \"18\"),\n", - " (\"7\", \"19\"),\n", - " (\"8\", \"20\"),\n", - " (\"9\", \"21\"),\n", - " (\"10\", \"22\"),\n", - " (\"11\", \"23\"), # Note that 12 and 24 would be phrased \"midi\" and \"minuit\" respectively\n", - "])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "X0-z-qJAmIiI" - }, - "source": [ - "We then create an alternate graph where this conversion is mapped onto the hours function - given a post-noon suffix - and create a union with our earlier graph:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "8CdEmo9NmN7u" - }, - "outputs": [], - "source": [ - "night_suffixes = pynutil.delete(\"suffix: \\\"pm\\\"\")\n", - "graph |= (\n", - " hour @ hour_to_night\n", - " + delete_extra_space\n", - " + pynutil.insert(\"h\")\n", - " + minute.ques\n", - " + delete_space\n", - " + night_suffixes\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YnoIkZBqmaTo" - }, - "source": [ - "Giving us a final Verbalizer of:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "ZfXimvFBmdDD" - }, - "outputs": [], - "source": [ - "class TimeFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"time\", kind=\"verbalize\")\n", - "\n", - " hour_to_night = pynini.string_map([\n", - " (\"1\", \"13\"),\n", - " (\"2\", \"14\"),\n", - " (\"3\", \"15\"),\n", - " (\"4\", \"16\"),\n", - " (\"5\", \"17\"),\n", - " (\"6\", \"18\"),\n", - " (\"7\", \"19\"),\n", - " (\"8\", \"20\"),\n", - " (\"9\", \"21\"),\n", - " (\"10\", \"22\"),\n", - " (\"11\", \"23\"),\n", - "])\n", - "\n", - " day_suffixes = pynutil.delete(\"suffix: \\\"am\\\"\")\n", - " night_suffixes = pynutil.delete(\"suffix: \\\"pm\\\"\")\n", - "\n", - " hour = (\n", - " pynutil.delete(\"hours:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1, 2)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - " minute = (\n", - " pynutil.delete(\"minutes:\")\n", - " + delete_extra_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_DIGIT, 1, 2)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - "\n", - " graph = hour + delete_extra_space + pynutil.insert(\"h\") + minute.ques + delete_space + day_suffixes.ques\n", - "\n", - " graph |= (\n", - " hour @ hour_to_night\n", - " + delete_extra_space\n", - " + pynutil.insert(\"h\")\n", - " + minute.ques\n", - " + delete_space\n", - " + night_suffixes\n", - " )\n", - " delete_tokens = self.delete_tokens(graph)\n", - " self.fst = delete_tokens.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e5tPcCaSYuhY" - }, - "source": [ - "If you've noticed, the Verbalizer process has become simpler as we've progressed through our WFSTs. Commonly, you will seldom need to even provide the amount of overhead we've seen in `TimeFst`, `MoneyFst`, and `OrdinalFst`, and the majority of this component is simply removing tokens as an intermediary step, as we'll see for our Name class." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iHmRe3UIhyIH" - }, - "source": [ - "# WhiteList WFST " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "8kMn2qB9bVFy" - }, - "source": [ - "\n", - "While developing your grammars, you may encounter tokens that refuse standard categorization and yet still require normalization. For example, you may need to render \"Mister Brown\" as `Mr. Brown` or \"H M S Nelson\" as `H.M.S. Nelson`. As these cases are rather specific, they lack a regular pattern for a specific classifier. (What about \"mister\" as a token requires tokenization as opposed to \"Brown\".) Instead, we need to explicitly list their input-output mappings (i.e. a whitelist).\n", - "\n", - "For NeMo, this is performed through the `WhiteListFst`:\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6B4oPXYcccWs" - }, - "source": [ - "## Grammar" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RThTLUCRceOO" - }, - "source": [ - "`WhitelistFst` is essentially just a wrapper for a `string_map` or `string_file` mapping with the appropriate formatting for deployment. Per our example, we can make a graph with the following:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "eIOOb_wJdMMx" - }, - "outputs": [], - "source": [ - "graph = pynini.string_map([\n", - " (\"mister\", \"mr.\"),\n", - " (\"h m s\", \"h.m.s\"),\n", - " (\"doctor\", \"dr.\")\n", - "])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "O5kTXwmPZ9Tt" - }, - "source": [ - "As previously mentioned, here is where the use of `string_file` will make maintenance much easier. Discovering whitelist mappings is an iterative process and you will more than likely need to return to your list throughout development. For instance, it may be obvious that tokens such as \"madame\", \"miss\", \"esquire\", but would you think of providing abbreviations for \"the right honorable\" or \"tennessee valley authority\"? Keeping a tsv file available for quick insertions greatly assists here." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "RC5Cf-Z8dYVk" - }, - "source": [ - "## Classifier" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "144nvAHEdfBJ" - }, - "source": [ - "Unlike for our other WFSTs, There is no specific semiotic class for `WhiteListFst`. It instead falls under the default Name class to designate there is no need for further processing beyond obligatory tokenization. Indeed, we can simply insert the token ourselves instead of calling `add_tokens`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "oPkrmg2gdznd" - }, - "outputs": [], - "source": [ - "class WhiteListFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"whitelist\", kind=\"classify\")\n", - "\n", - " whitelist = pynini.string_map([\n", - " (\"mister\", \"mr.\"),\n", - " (\"h m s\", \"h.m.s\"),\n", - " (\"doctor\", \"dr.\")])\n", - " graph = pynutil.insert(\"name: \\\"\") + convert_space(whitelist) + pynutil.insert(\"\\\"\")\n", - " self.fst = graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "B05kdSIdd2dv" - }, - "source": [ - "## Verbalizer" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Since the whitelisted token has already been rendered in the desired normalized form, all that is necessary is to strip the `name` token and render the string 'as is'. This can be done by through the following:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gaq3voIYiUCA" - }, - "outputs": [], - "source": [ - "class WhiteListFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"whitelist\", kind=\"verbalize\")\n", - " graph = (\n", - " pynutil.delete(\"name:\")\n", - " + delete_space\n", - " + pynutil.delete(\"\\\"\")\n", - " + pynini.closure(NEMO_CHAR - \" \", 1)\n", - " + pynutil.delete(\"\\\"\")\n", - " )\n", - " graph = graph @ pynini.cdrewrite(pynini.cross(u\"\\u00A0\", \" \"), \"\", \"\", NEMO_SIGMA) # Removes possible null token\n", - " self.fst = graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cUE7Gg35bWKb" - }, - "source": [ - "While the graph is largely self-explanatory, take note that the default implementation assumes a character string without spacing. If you intend to include additional formatting in your normalization (e.g. `H. M. S.` instead of `H.M.S.`), you may need to adjust the graph to expand coverage." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_o_a15Fg7niv" - }, - "source": [ - "# Word and Punctuation WFST " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Zi6lP7mTmnUV" - }, - "source": [ - "Continuing with the Name class, we will conclude with the Word and Punctuation WFSTs. These are among the simplest and most crucial classes of the entire ITN system, as they classify all tokens that are not caught by other semiotic classes. Since these other tokens make up the majority of all strings your normalization system will encounter, they are essential for general functionality.\n", - "\n", - "However, they escape discussion as their function is self-evident: since they function as default classes, tokens only reach Word WFST and Punctuation WFST if they have not been accepted by the other WFSTs. As such, we can simply accept the tokens as they are, providing them a `name` tag." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9zCqczLqp5NW" - }, - "source": [ - "## Classifier" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "eUWum5U0p99c" - }, - "source": [ - "For instance, consider the entire `WordFst` Classifier in its entirety:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "CCZSTeDHofDl" - }, - "outputs": [], - "source": [ - "class WordFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"word\", kind=\"classify\")\n", - " word = pynutil.insert(\"name: \\\"\") + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert(\"\\\"\")\n", - " self.fst = word.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9ys2VpjjoiEC" - }, - "source": [ - "It just processes the entire token string with the `NEMO_NOT_SPACE` utility WFST (which accepts any string that is not a space). For your language, you may simply use one of the preexisting `WordFst`.\n", - "\n", - "Depending on language, the `PunctuationFst` may require some (minimal) adjustment. Note the following:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Mnnd3PVMpF4t" - }, - "outputs": [], - "source": [ - "class PunctuationFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"punctuation\", kind=\"classify\")\n", - "\n", - " s = \"!#$%&\\'()*+,-./:;<=>?@^_`{|}~\"\n", - " punct = pynini.union(*s)\n", - "\n", - " graph = pynutil.insert(\"name: \\\"\") + punct + pynutil.insert(\"\\\"\")\n", - "\n", - " self.fst = graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_afW02LXpLtz" - }, - "source": [ - "If your language uses other punctuation than that in the `s` string (or reserves some of the punctuation as characters), you may simply edit `s` to accommodate. \n", - "\n", - "For instance, French has a unique quotation style that utilizes guillemets \"« »\". We may add their Unicode codepoints (to avoid encoding issues) to `s`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "mgfZIKzVplVm" - }, - "outputs": [], - "source": [ - "class PunctuationFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"punctuation\", kind=\"classify\")\n", - "\n", - " s = \"!#$%&\\'()*+,-./:;<=>?@^_`{|}~\"\n", - " guillemets = \"\\u00AB\" + \"\\u00BB\" # quotation marks in French.\n", - " s += guillemets\n", - " punct = pynini.union(*s)\n", - "\n", - " graph = pynutil.insert(\"name: \\\"\") + punct + pynutil.insert(\"\\\"\")\n", - "\n", - " self.fst = graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6Upb5-wcp_7H" - }, - "source": [ - "## Verbalizer" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ufWT1T6GqCCT" - }, - "source": [ - "Note that both `PunctuationFst` and `WordFst` both encode with the `name` property. This leaves no differentiation between the two for a Verbalizer. This makes sense as there are no particular formatting rules for them, they simply need a placeholder tag to avoid alteration between the Classifier and Verbalizer step. Once passed to the verbalizer, they are rendered as normal by simply removing the tag (this is practically identical to the WhiteListFST):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "LqyhqQKZqcph" - }, - "outputs": [], - "source": [ - "class WordFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"word\", kind=\"verbalize\")\n", - " chars = pynini.closure(NEMO_CHAR - \" \", 1)\n", - " char = pynutil.delete(\"name:\") + delete_space + pynutil.delete(\"\\\"\") + chars + pynutil.delete(\"\\\"\")\n", - " graph = char @ pynini.cdrewrite(pynini.cross(u\"\\u00A0\", \" \"), \"\", \"\", NEMO_SIGMA) # Cleans up possible null character\n", - "\n", - " self.fst = graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lGbrUkcpapyi" - }, - "source": [ - "For many languages, the writing of your `WordFst` and `PunctuationFst` (both Classifiers and Verbalizers) will require no more than duplicating the preexisting grammars found in NeMo Text Processing." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "5y9jhkhQ7p4W" - }, - "source": [ - "# Other Classes " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "j1mgnISmiu-g" - }, - "source": [ - "While the preceding discussion should be suitable for development of the remaining classes, some helpful notes may be of use before continuing:\n", - "- Fraction WFST: This is the last of the 'fundamental' classes and should take priority after completion of the Decimal WFST. It operates very similarly to the Ordinal WFST in that you wish to recover the Cardinal roots for the numerator and denominator prior to tagging. Its properties are: `negative`, `integer_part`, `numerator`, and `denominator`.\n", - "- Measure WFST: Like the Money WFST, this will require management of several 'parent' WFSTS (Fraction, Cardinal, Decimal) to be suitably comprehensive. As well, you may find it more productive to find ways to compose new measurement units instead of simply listing all (e.g. micrometers, petameters, miles per hour, feet per second). Its properties are: `negative`, `units` and it allows subgraphs of the `cardinal`, `decimal`, and `fraction` classes. (This is, it allows tokenization within the tokenization.)\n", - "- Date WFST: Depending on writing conventions, this may vary in complexity. For instance, English speakers may write dates as `01/01/2021/` or `Jan. 1 2021`. Are there specific use cases where one is preferred or should you simply decide on a format? Further, you may wish to take advantage of the `preserve order` property to avoid possible unwanted verbalizations (some implementations will permit both `Jan. 1` and `1 Jan.` if not careful.) Its properties are: `month`, `day`, and `year`. \n", - "- Telephone WFST: These will be heavily dependent not only on writing conventions but even regional preference. For instance, the U.S. commonly uses a ten digit system broken into the following sequence: `###-###-####`. Meanwhile, mainland France breaks a ten digit sequence into groups of two: `##-##-##-##-##`. Take careful note of how your language's target region verbalizes these figures and leave room for some variation in development. The `telephone` class has only one property: `number_part`. \n", - "- Electronic WFST: For normalizing email addresses or urls, you will need to develop for the `electronic` class. The main concerns will be managing alphanumeric strings and parsing the reserved symbols used for protocols and domains. (How does your target language pronounce \"https://\"? www? '.' or '@'?\") Depending on whether you are normalizing a url or email, the following properties will be needed:\n", - " - email: `username`, `domain`\n", - " - url: `protocol` (Sparrowhawk allows further detail here but NeMo passes the entire url through the `protocol` property)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-i25X8mK90n3" - }, - "source": [ - "# Tokenize and Classify " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "v4bcigU6b9ss" - }, - "source": [ - "We are now ready to build a general Classifier for our entire language. Upon completion of your grammars, the next step is to unite them together in a general Classifier WFST - located within a `tokenize_and_classify.py` file, preferably. This WFST will be responsible for determining the appropriate semiotic class for each token in your string and processing the necessary properties for normalization.\n", - "\n", - "For this section, we will focus on the following: grammar composition, assignment of weights, and importing/exporting as a FAR file. Since we will need to work with some instantiated graphs, let's preload them before proceeding. (Note the compilingtime.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from nemo_text_processing.inverse_text_normalization.fr.taggers.cardinal import CardinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.decimal import DecimalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.money import MoneyFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.ordinal import OrdinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.punctuation import PunctuationFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.time import TimeFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.whitelist import WhiteListFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.taggers.word import WordFst\n", - "\n", - "cardinal = CardinalFst()\n", - "cardinal_graph = cardinal.fst\n", - "\n", - "ordinal = OrdinalFst(cardinal)\n", - "ordinal_graph = ordinal.fst\n", - "\n", - "decimal = DecimalFst(cardinal)\n", - "decimal_graph = decimal.fst\n", - "\n", - "whitelist_graph = WhiteListFst().fst\n", - "word_graph = WordFst().fst\n", - "time_graph = TimeFst().fst\n", - "money_graph = MoneyFst(cardinal, decimal).fst\n", - "punct_graph = PunctuationFst().fst" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "MIv58eSocOV1" - }, - "source": [ - "## Grammar" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "k_RPlnfVdG5E" - }, - "source": [ - "As for all previous grammars, the `tokenize_and_classify` grammar inherits from a `GraphFst` as an individual class: `ClassifyFst`. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "WHKG4c2WdW0G" - }, - "outputs": [], - "source": [ - "class ClassifyFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "j9_I6DJmdcOG" - }, - "source": [ - "This class is responsible for instantiating all subgraphs and passing necessary dependencies:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "4YtmcxLOdlas" - }, - "outputs": [], - "source": [ - "class ClassifyFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")\n", - "\n", - " cardinal = CardinalFst()\n", - " cardinal_graph = cardinal.fst\n", - "\n", - " ordinal = OrdinalFst(cardinal)\n", - " ordinal_graph = ordinal.fst\n", - "\n", - " decimal = DecimalFst(cardinal)\n", - " decimal_graph = decimal.fst\n", - "\n", - " whitelist_graph = WhiteList().fst\n", - " word_graph = WordFst().fst\n", - " time_graph = TimeFst().fst\n", - " money_graph = MoneyFst(cardinal, decimal).fst\n", - " punct_graph = PunctuationFst().fst" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "y5vGvv3HeAY9" - }, - "source": [ - "We then join all the grammars together so `ClassifyFst` can apply them. Rather unceremoniously, this is accomplished by performing a union across all grammars (excluding `PunctuationFst`, to assist tokenization). We then follow this union by inserting the `tokens` class around the resulting formatting (required for processing):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "oocgPQ5geZJO" - }, - "outputs": [], - "source": [ - "class ClassifyFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")\n", - "\n", - " cardinal = CardinalFst()\n", - " cardinal_graph = cardinal.fst\n", - "\n", - " ordinal = OrdinalFst(cardinal)\n", - " ordinal_graph = ordinal.fst\n", - "\n", - " decimal = DecimalFst(cardinal)\n", - " decimal_graph = decimal.fst\n", - "\n", - " whitelist_graph = WhiteListFst().fst\n", - " word_graph = WordFst().fst\n", - " time_graph = TimeFst().fst\n", - " money_graph = MoneyFst(cardinal, decimal).fst\n", - " punct_graph = PunctuationFst().fst\n", - "\n", - " classify = (\n", - " time_graph\n", - " | whitelist_graph\n", - " | decimal_graph\n", - " | cardinal_graph\n", - " | ordinal_graph\n", - " | money_graph\n", - " | word_graph\n", - " )\n", - " token = pynutil.insert(\"tokens { \") + classify + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ASWDXWQjfLEU" - }, - "source": [ - "Our graph is now able to process an individual token. But what about a string? Here you will need to be mindful of the tokenization behavior for your language and decide on your desired treatment of punctuation (hence exclusion from the main graph). \n", - "\n", - "For our purposes, we will assume the convention of space and punctuation serving as token separators. We graph punctuation as individual tokens" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "r6WztK2jwhFt" - }, - "outputs": [], - "source": [ - "punct_graph = PunctuationFst().fst\n", - "punct = pynutil.insert(\"tokens { \") + punct_graph + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9T2rT89jw3T1" - }, - "source": [ - "and join the `punct` graph with our `tokens` graph (inserting spaces between tokens for formatting)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "rGtVOK-txKOP" - }, - "outputs": [], - "source": [ - "token = \"PLACEHOLDER\"\n", - "token_plus_punct = (\n", - " pynini.closure(punct + pynutil.insert(\" \")) + token + pynini.closure(pynutil.insert(\" \") + punct)\n", - " ) # Note the use of closure incase there are multiple punctuations\n", - "graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_gixfQ69xWPe" - }, - "source": [ - "then address space between tokens: \n", - "\n", - "`graph = delete_space + graph + delete_space`" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "DWnmazWecyUG" - }, - "source": [ - "## Weighting " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "egHbwIbMx-hT" - }, - "source": [ - "Were we to leave our `ClassifyFst` like this, we would undoubtedly encounter a mountain of errors. What will stop our graph from treating punctuation that is part of a previous grammar as a token separator (e.g. \"vingt-et-un\")? How do we ensure that a currency string isn't treated as solely a decimal string with a `name` token following?\n", - "\n", - "As in previous cases, the solution lies in our choice of weights for the grammar." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "y3U7_M8CyxZ1" - }, - "source": [ - "Let us return to the main graph:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "9VXe1dfsy3Be" - }, - "outputs": [], - "source": [ - "classify = (\n", - " time_graph\n", - " | whitelist_graph\n", - " | decimal_graph\n", - " | cardinal_graph\n", - " | ordinal_graph\n", - " | money_graph\n", - " | word_graph\n", - " )\n", - "punct = pynutil.insert(\"tokens { \") + punct_graph + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "aY4vOFqxy5ua" - }, - "source": [ - "Beyond the path weights that we explicitly added, these graphs are currently weightless. Since we want the graphs themselves to be the general determiners of a path, let us use some default weights an order of magnitude beyond our path weights (we use `pynutil.add_weight`):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "bthyt_Le2rsA" - }, - "outputs": [], - "source": [ - "classify = (\n", - " pynutil.add_weight(time_graph, 1)\n", - " | pynutil.add_weight(whitelist_graph, 1)\n", - " | pynutil.add_weight(decimal_graph, 1)\n", - " | pynutil.add_weight(cardinal_graph, 1)\n", - " | pynutil.add_weight(ordinal_graph, 1)\n", - " | pynutil.add_weight(money_graph, 1)\n", - " | pynutil.add_weight(word_graph, 1)\n", - " )\n", - "punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, 1) + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xMNIJbzj3MMP" - }, - "source": [ - "Let's see what logical adjustments should be made. First off, we know that we want each class token to span the largest string possible. (e.g. We don't want \"quatre-vingt\" to be rendered as two `cardinal` classes with a hyphen in between.) As such, we want to penalize our graph for using more than one tokens. We can do so by establishing the following constraint: the sum of two or more tokens cannot be less than the weight of a single token. Or, for any pair of tokens `w_1` and `w_2`, their sum must always be greater than any other individual token (including themselves):\n", - "\n", - "`w_1 + w_2 > k >= w`\n", - "\n", - "To keep things simple, let us make the upper limit `2`. This means we should increase all the weights to keep our constraint:\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "classify = (\n", - " pynutil.add_weight(time_graph, 1.1)\n", - " | pynutil.add_weight(whitelist_graph, 1.1)\n", - " | pynutil.add_weight(decimal_graph, 1.1)\n", - " | pynutil.add_weight(cardinal_graph, 1.1)\n", - " | pynutil.add_weight(ordinal_graph, 1.1)\n", - " | pynutil.add_weight(money_graph, 1.1)\n", - " | pynutil.add_weight(word_graph, 1.1)\n", - " )\n", - "punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, 1.1) + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Do we want this constraint to include all tokens? Imagine if we had a string of multiple semiotic tokens in a row. Since this string's combined weight would be larger than any single class token, a grammar that served as a universal acceptor (i.e. `word_graph`) would be preferred over these individual classes. This would be obviously incorrect. As such, we want to make sure that `word_graph` would only be traversed when there is truly no other option:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "qc_CU2ro63eg" - }, - "outputs": [], - "source": [ - "classify = (\n", - " pynutil.add_weight(time_graph, 1.1)\n", - " | pynutil.add_weight(whitelist_graph, 1.1)\n", - " | pynutil.add_weight(decimal_graph, 1.1)\n", - " | pynutil.add_weight(cardinal_graph, 1.1)\n", - " | pynutil.add_weight(ordinal_graph, 1.1)\n", - " | pynutil.add_weight(money_graph, 1.1)\n", - " | pynutil.add_weight(word_graph, 100)\n", - " )\n", - "punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, 1.1) + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now, even with a string of fifty different class tokens, `word_graph` would still not be considered as a path to traverse." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "fW8C3vD-7Dbl" - }, - "source": [ - "Next, let us consider our foundational graph: `cardinal_graph`. As Cardinals occur in practically all our WFSTs, it's possible for `cardinal_graph` to apply in almost all cases. Yet, we've specifically invoked `CardinalFST` when it was required in any of the other classes, so it will never be needed in any of those cases. This means that we want all those graphs to have *priority* over `cardinal_graph`. As such, we will increase its weight so it takes second lowest precedence (while still paying attention to the combined weight constraint). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "97UwGaEn8pj7" - }, - "outputs": [], - "source": [ - "classify = (\n", - " pynutil.add_weight(time_graph, 1.1)\n", - " | pynutil.add_weight(whitelist_graph, 1.1)\n", - " | pynutil.add_weight(decimal_graph, 1.1)\n", - " | pynutil.add_weight(cardinal_graph, 1.2)\n", - " | pynutil.add_weight(ordinal_graph, 1.1)\n", - " | pynutil.add_weight(money_graph, 1.1)\n", - " | pynutil.add_weight(word_graph, 100)\n", - " )\n", - "punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, 1.1) + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0d9Lw4Ot88_B" - }, - "source": [ - "This form of thinking can be applied to all the 'foundational' graphs you may develop: the dependent graphs should take higher precedence than the graphs they borrow from. For instance, since `money_graph` utilizes `decimal_graph`, we know it should take precedence. However, since `decimal_graph` borrows from `cardinal_graph`, its weight must still be less than `1.2`. As such: " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "-wF8cgLK9tpU" - }, - "outputs": [], - "source": [ - "classify = (\n", - " pynutil.add_weight(time_graph, 1)\n", - " | pynutil.add_weight(whitelist_graph, 1)\n", - " | pynutil.add_weight(decimal_graph, 1.1)\n", - " | pynutil.add_weight(cardinal_graph, 1.2)\n", - " | pynutil.add_weight(ordinal_graph, 1)\n", - " | pynutil.add_weight(money_graph, 1.09)\n", - " | pynutil.add_weight(word_graph, 100)\n", - " )\n", - "punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, 1) + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "huMzDoZ2-FD2" - }, - "source": [ - "For those classes that don't seem affected, we can set their weights as the same as those below their 'foundation' graphs, simply to prevent prioritization when not required\n", - "\n", - "Meanwhile, `whitelist_graph` should take precedence over all others, as it may contain unique normalizations that may get accidentally caught by the other graphs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gWG6ttyd-bbD" - }, - "outputs": [], - "source": [ - "classify = (\n", - " pynutil.add_weight(time_graph, 1.1)\n", - " | pynutil.add_weight(whitelist_graph, 1.07)\n", - " | pynutil.add_weight(decimal_graph, 1.1)\n", - " | pynutil.add_weight(cardinal_graph, 1.2)\n", - " | pynutil.add_weight(ordinal_graph, 1.1)\n", - " | pynutil.add_weight(money_graph, 1.08)\n", - " | pynutil.add_weight(word_graph, 100)\n", - " )\n", - "punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, 1.1) + pynutil.insert(\" }\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "1TH08f8O-fWx" - }, - "source": [ - "Keep in mind that building weights in this manner is hardly a rule for grammar development and is instead intended as a means to initialize weights for empirical development. You will find that actual strings will cause unexpected behavior that require fine tuning. \n", - "\n", - "For instance, the Classifier for French in NeMo ITN benefits from having varying precedence for some weights, as seen in the following excerpt:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "gKdkyDK3_r46" - }, - "outputs": [], - "source": [ - "class ClassifyFst(GraphFst):\n", - " \"\"\"\n", - " Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased.\n", - " For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File. \n", - " More details to deployment at NeMo/tools/text_processing_deployment.\n", - "\n", - " Args:\n", - " cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache.\n", - " overwrite_cache: set to True to overwrite .far files\n", - " \"\"\"\n", - "\n", - " def __init__(self, cache_dir: str = None, overwrite_cache: bool = False):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")\n", - "\n", - " far_file = None\n", - " if cache_dir is not None and cache_dir != \"None\":\n", - " os.makedirs(cache_dir, exist_ok=True)\n", - " far_file = os.path.join(cache_dir, \"_fr_itn.far\")\n", - " if not overwrite_cache and far_file and os.path.exists(far_file):\n", - " self.fst = pynini.Far(far_file, mode=\"r\")[\"tokenize_and_classify\"]\n", - " logging.info(f\"ClassifyFst.fst was restored from {far_file}.\")\n", - " else:\n", - " logging.info(f\"Creating ClassifyFst grammars.\")\n", - "\n", - " cardinal = CardinalFst()\n", - " cardinal_graph = cardinal.fst\n", - "\n", - " fraction = FractionFst(cardinal)\n", - " fraction_graph = fraction.fst\n", - "\n", - " ordinal = OrdinalFst(cardinal)\n", - " ordinal_graph = ordinal.fst\n", - "\n", - " decimal = DecimalFst(cardinal)\n", - " decimal_graph = decimal.fst\n", - "\n", - " measure_graph = MeasureFst(cardinal=cardinal, decimal=decimal, fraction=fraction).fst\n", - " date_graph = DateFst(cardinal).fst\n", - " word_graph = WordFst().fst\n", - " time_graph = TimeFst().fst\n", - " money_graph = MoneyFst(cardinal, decimal).fst\n", - " whitelist_graph = WhiteListFst().fst\n", - " punct_graph = PunctuationFst().fst\n", - " electronic_graph = ElectronicFst().fst\n", - " telephone_graph = TelephoneFst().fst\n", - "\n", - " classify = (\n", - " pynutil.add_weight(whitelist_graph, 1.01)\n", - " | pynutil.add_weight(time_graph, 1.05)\n", - " | pynutil.add_weight(date_graph, 1.09)\n", - " | pynutil.add_weight(decimal_graph, 1.08)\n", - " | pynutil.add_weight(measure_graph, 1.1)\n", - " | pynutil.add_weight(cardinal_graph, 1.1)\n", - " | pynutil.add_weight(ordinal_graph, 1.1)\n", - " | pynutil.add_weight(fraction_graph, 1.09)\n", - " | pynutil.add_weight(money_graph, 1.07)\n", - " | pynutil.add_weight(telephone_graph, 1.1)\n", - " | pynutil.add_weight(electronic_graph, 1.1)\n", - " | pynutil.add_weight(word_graph, 100)\n", - " )\n", - "\n", - " punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(\" }\")\n", - " token = pynutil.insert(\"tokens { \") + classify + pynutil.insert(\" }\")\n", - " token_plus_punct = (\n", - " pynini.closure(punct + pynutil.insert(\" \")) + token + pynini.closure(pynutil.insert(\" \") + punct)\n", - " )\n", - "\n", - " graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct)\n", - " graph = delete_space + graph + delete_space\n", - "\n", - " self.fst = graph.optimize()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qc4B_0rNcQZu" - }, - "source": [ - "## FAR import/export" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0nRRPvy-AYsA" - }, - "source": [ - "While working through these code excerpts, you may have noticed some latency with each instantiation of our WFSTs (notably wherever `CardinalFst` was involved). This is because the `pynini.optimize` that we call with each graph's instantiation is computationally expensive. For our ultimate purpose of deployment, it seems a waste of resources to recreate stable graphs for each use.\n", - "\n", - "To address this, NeMo ITN supports WFST caching through use of `pynini.Far`, storing and recovering Classify grammars as FAR (Fst ARchives).\n", - "\n", - "Let us update our `ClassifyFst` to permit passing a cache and allowing overwriting (for development):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "5XgWevUzD1AE" - }, - "outputs": [], - "source": [ - "class ClassifyFst(GraphFst):\n", - " def __init__(self, cache_dir: str = None, overwrite_cache: bool = False):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "l28GMR70ESz0" - }, - "source": [ - "For storing our graphs as FARs, we can use `graph_utils.generator_main`, which saves our WFSTs by type for easier management. For arguments it takes a string name and a dict mapping of WFST type to graph:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "AzTkcmAWFLYm" - }, - "outputs": [], - "source": [ - "import os\n", - "\n", - "class ClassifyFst(GraphFst):\n", - " def __init__(self, cache_dir: str = None, overwrite_cache: bool = False):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")\n", - " # Grammar here\n", - " # ....\n", - " if cache_dir is not None and cache_dir != \"None\":\n", - " os.makedirs(cache_dir, exist_ok=True)\n", - " far_file = os.path.join(cache_dir, \"_fr_itn.far\")\n", - " generator_main(far_file, {\"tokenize_and_classify\": self.fst})" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Wz8wjCQSD6eJ" - }, - "source": [ - "We pair this with the ability to load from cache (note the `\"tokenize_and_classify\"` key being passed):" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "FRFYgMmuD_53" - }, - "outputs": [], - "source": [ - "import os\n", - "\n", - "class ClassifyFst(GraphFst):\n", - " def __init__(self, cache_dir: str = None, overwrite_cache: bool = False):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")\n", - " if not overwrite_cache and far_file and os.path.exists(far_file):\n", - " self.fst = pynini.Far(far_file, mode=\"r\")[\"tokenize_and_classify\"]\n", - " else:\n", - " # Grammar here\n", - " # ....\n", - " if cache_dir is not None and cache_dir != \"None\":\n", - " os.makedirs(cache_dir, exist_ok=True)\n", - " far_file = os.path.join(cache_dir, \"_fr_itn.far\")\n", - " generator_main(far_file, {\"tokenize_and_classify\": self.fst})\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ib9nggZxF38s" - }, - "source": [ - "Producing our `ClassifyFst` as:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "d2BZyx6sGGg2" - }, - "outputs": [], - "source": [ - "class ClassifyFst(GraphFst):\n", - " def __init__(self, cache_dir: str = None, overwrite_cache: bool = False):\n", - " super().__init__(name=\"tokenize_and_classify\", kind=\"classify\")\n", - "\n", - " far_file = None\n", - " if cache_dir is not None and cache_dir != \"None\":\n", - " os.makedirs(cache_dir, exist_ok=True)\n", - " far_file = os.path.join(cache_dir, \"_fr_itn.far\")\n", - " if not overwrite_cache and far_file and os.path.exists(far_file):\n", - " self.fst = pynini.Far(far_file, mode=\"r\")[\"tokenize_and_classify\"]\n", - " else:\n", - " cardinal = CardinalFst()\n", - " cardinal_graph = cardinal.fst\n", - "\n", - " ordinal = OrdinalFst(cardinal)\n", - " ordinal_graph = ordinal.fst\n", - "\n", - " decimal = DecimalFst(cardinal)\n", - " decimal_graph = decimal.fst\n", - "\n", - " whitelist_graph = WhiteList().fst\n", - " word_graph = WordFst().fst\n", - " time_graph = TimeFst().fst\n", - " money_graph = MoneyFst(cardinal, decimal).fst\n", - " whitelist_graph = WhiteListFst().fst\n", - " punct_graph = PunctuationFst().fst\n", - "\n", - " classify = (\n", - " pynutil.add_weight(time_graph, 1.1)\n", - " | pynutil.add_weight(whitelist_graph, 1.01)\n", - " | pynutil.add_weight(decimal_graph, 1.09)\n", - " | pynutil.add_weight(cardinal_graph, 1.1)\n", - " | pynutil.add_weight(ordinal_graph, 1.09)\n", - " | pynutil.add_weight(money_graph, 1.08)\n", - " | pynutil.add_weight(word_graph, 100)\n", - " )\n", - "\n", - " punct = pynutil.insert(\"tokens { \") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(\" }\")\n", - " token = pynutil.insert(\"tokens { \") + classify + pynutil.insert(\" }\")\n", - " token_plus_punct = (\n", - " pynini.closure(punct + pynutil.insert(\" \")) + token + pynini.closure(pynutil.insert(\" \") + punct)\n", - " )\n", - "\n", - " graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct)\n", - " graph = delete_space + graph + delete_space\n", - "\n", - " self.fst = graph.optimize()\n", - "\n", - " if far_file:\n", - " generator_main(far_file, {\"tokenize_and_classify\": self.fst})" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nEhY6wKKtfhn" - }, - "source": [ - "You should find the caching to vastly speed up compilingtime." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rTtCnC5w95CI" - }, - "source": [ - "# Verbalize and Verbalize Final " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "H9y5yuk1HaGj" - }, - "source": [ - "Our last step is to create a universal Verbalizer for all classes. This is very similar to development of `ClassifierFst`, except that the Verbalizer breaks its normalization task into two components:\n", - "- `VerbalizeFst`, which removes formatting for each token\n", - "- `VerbalizeFinalFst`, which extends `VerbalizeFst` across all tokens in a string\n", - "Why two components when `tokenize_and_classify` was one? Because Sparrowhawk performs all the functionality of `VerbalizeFinalFst`, so its inclusion would break deployment. However, without it, your NeMo grammar would be unable to function at base. So we separate the two to allow the best of both world." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vUawTJVuH8iR" - }, - "source": [ - "## VerbalizeFst" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xghiBV06IIWU" - }, - "source": [ - "Much like `ClassifyFst`, `VerbalizeFst` instantiates all its subgraphs and then joins them together under a union operation. However, it does not need to employ weighting. Why? Because `ClassifyFst` has assigned each token a specific class. As each class is unique, there is no possibility that a subgraph will be employed for the wrong token.\n", - "\n", - "As such, our `VerbalizeFst` is formed by a simple union operation across all previous Verbalizer graphs:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "uMVCqCvsIt2v" - }, - "outputs": [], - "source": [ - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.cardinal import CardinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.decimal import DecimalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.money import MoneyFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.ordinal import OrdinalFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.time import TimeFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.whitelist import WhiteListFst\n", - "from nemo_text_processing.inverse_text_normalization.fr.verbalizers.word import WordFst\n", - "\n", - "class VerbalizeFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"verbalize\", kind=\"verbalize\")\n", - " cardinal = CardinalFst()\n", - " cardinal_graph = cardinal.fst\n", - " ordinal_graph = OrdinalFst().fst\n", - " decimal = DecimalFst()\n", - " decimal_graph = decimal.fst\n", - " whitelist_graph = WhiteListFst().fst\n", - " money_graph = MoneyFst(decimal=decimal).fst\n", - " time_graph = TimeFst().fst\n", - " graph = (\n", - " time_graph\n", - " | whitelist_graph\n", - " | money_graph\n", - " | ordinal_graph\n", - " | decimal_graph\n", - " | cardinal_graph\n", - " )\n", - " self.fst = graph" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Wap-LU6EI2Iu" - }, - "source": [ - "## Verbalize Final" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TYaEt_0tI47t" - }, - "source": [ - "With `VerbalizeFst` complete, we now extend our graph to cover any series of tokens. All this requires is deletion of the `tokens` formatting (note the absence of such in our previous graph) and use of closure for any series of one or more tokens.\n", - "\n", - "This provides the following graph:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "L-9lJNE6JPCW" - }, - "outputs": [], - "source": [ - "\n", - "class VerbalizeFinalFst(GraphFst):\n", - " def __init__(self):\n", - " super().__init__(name=\"verbalize_final\", kind=\"verbalize\")\n", - " verbalize = VerbalizeFst().fst\n", - " word = WordFst().fst\n", - " types = verbalize | word\n", - " graph = (\n", - " pynutil.delete(\"tokens\")\n", - " + delete_space\n", - " + pynutil.delete(\"{\")\n", - " + delete_space\n", - " + types\n", - " + delete_space\n", - " + pynutil.delete(\"}\")\n", - " )\n", - " graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space\n", - " self.fst = graph" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WwMKFw-QJVgm" - }, - "source": [ - "Unlike `ClassifyFst`, NeMo ITN does not cache `VerbalizeFst` or `VerbalizeFinalFst`. (While you are welcome to provide such functionality in your own development, keep in mind that the limited complexity of our Verbalizers makes compilingtimes less significant.)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "7U21AZearZMK" - }, - "source": [ - "# Deployment " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "VrSccoh9K6JK" - }, - "source": [ - "Now that we have done all the groundwork, we can finally move to deployment. This final section will just cover the minor code alterations required to call your language through NeMo ITN and deploy through Sparrowhawk. For further information on using NeMo ITN, please see [this tutorial](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/text_processing/Inverse_(Text)_Normalization.ipynb). " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0Le2aJvFIAKd" - }, - "source": [ - "## InverseNormalize" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "r2R3TUCDLi5-" - }, - "source": [ - "NeMo calls upon the `InverseNormalizer` class for all ITN tasks. Given a string and language, it will instantiate both the `ClassifierFst` and `VerbalizeFst` respective for the given language. (Note: we do not use `VerbalizeFinal` as its functions are managed by Sparrowhawk.) To make your language deployable in the general NeMo ITN system, you must designate the availability of these classes for instantiation. (For more information, see the [source code](https://github.com/NVIDIA/NeMo/blob/main/nemo_text_processing/inverse_text_normalization/inverse_normalize.py).)\n", - "\n", - "To do so requires only two changes. The first is providing a string to identify your language as an option for `parse_args` ([ISO codes are advised](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes)):" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "tfv4Ee3ML-Fg" - }, - "source": [ - "```Python\n", - "def parse_args():\n", - " parser = ArgumentParser()\n", - " ...\n", - " parser.add_argument(\"--language\", choices=[..., 'MY_LANGUAGE'], type=str)\n", - " ...\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "awVl5nAsMUTl" - }, - "source": [ - "The next is to call your `ClassifyFst` and `VerbalizeFst` from `__init__`:" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "```bash\n", - "class InverseNormalizer(Normalizer):\n", - " def __init__(self, lang: str = 'en', cache_dir: str = None, overwrite_cache: bool = False):\n", - "\n", - " if lang == 'en':\n", - " from nemo_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst\n", - " from nemo_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import (\n", - " VerbalizeFinalFst,\n", - " )\n", - " # Other languages\n", - " # ....\n", - " elif lang == 'MY_LANGUAGE':\n", - "\n", - " from nemo_text_processing.inverse_text_normalization.MY_LANGUAGE.taggers.tokenize_and_classify import ClassifyFst\n", - "\n", - " from nemo_text_processing.inverse_text_normalization.MY_LANGUAGE.verbalizers.verbalize_final import (\n", - "\n", - " VerbalizeFst,\n", - "\n", - " )\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TI1PuejLMxdI" - }, - "source": [ - "And you're done! NeMo will handle the rest. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "xrksINQoICfj" - }, - "source": [ - "## Grammar export and Deployment to C++" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rP9-dmMJSg3h" - }, - "source": [ - "Find information here:\n", - "https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/wfst_text_processing_deployment.html" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "TDoVUxCE-Dax" - }, - "source": [ - "# Final Notes" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Fw-9mU7ql8iY" - }, - "source": [ - "Congratulations, you have now constructed an entire ITN system from the ground up! While your experience will vary with each language, you will find several commonalities that will assist you in further development. \n", - "\n", - "If you are interested in working further with your language WFSTs, you may wish to construct a TN system. Broadly, this is accomplished by inverting your previous graphs (`pynini.invert` may assist here) and changing your outputs to avoid indeterminacy (i.e. decide on one canonical output for your grammar for each class). But outside of such grammar specific edits, you repeat many of the steps exhibited here, such as:\n", - "- Use of a two step classifier-verbalizer system\n", - "- Same semiotic classes for tagging\n", - "- Inheritance of `GraphFst`\n", - "\n", - "For Audio-based non-deterministic text normalization please extend your grammars with additional output options for ambiguous options. Every semiotic class has a input flag `deterministic` which is by default set to True. For non-deterministic text normalization add additional grammar for the case `deterministic=False` \n", - "\n", - "We also recommend to look at the source of some of the existing [languages](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/text_normalization/wfst/wfst_text_normalization.html#language-support), in particular English: https://github.com/NVIDIA/NeMo/tree/main/nemo_text_processing/inverse_text_normalization/en." - ] - } - ], - "metadata": { - "colab": { - "collapsed_sections": [], - "name": "WFST Tutorial.ipynb", - "provenance": [], - "toc_visible": true - }, - "interpreter": { - "hash": "fbc643a332f9d7801191710b24a8a955d342df4f32791f7fb65121dc4784751f" - }, - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": 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.../tokenizers/text_to_speech/tokenizer_wrapper.py | 3 +-- .../tokenizers/text_to_speech/tts_tokenizers.py | 11 +++++------ nemo/collections/tts/g2p/models/__init__.py | 2 +- nemo/collections/tts/g2p/models/ctc_g2p.py | 4 ++-- .../tts/g2p/models/heteronym_classification.py | 4 ++-- nemo/collections/tts/g2p/models/t5_g2p.py | 4 ++-- nemo/collections/tts/g2p/modules.py | 4 ++-- .../tokenizers/text_to_speech/test_tts_tokenizers.py | 2 +- tests/collections/tts/test_torch_tts.py | 2 +- tools/ctc_segmentation/requirements.txt | 2 +- 15 files changed, 23 insertions(+), 30 deletions(-) diff --git a/examples/tts/g2p/g2p_inference.py b/examples/tts/g2p/g2p_inference.py index ec32c29c4a95..a178e474c7f8 100644 --- a/examples/tts/g2p/g2p_inference.py +++ b/examples/tts/g2p/g2p_inference.py @@ -18,14 +18,13 @@ import pytorch_lightning as pl import torch -from nemo.collections.tts.g2p.models import G2PModel from omegaconf import OmegaConf from utils import get_metrics +from nemo.collections.tts.g2p.models import G2PModel from nemo.core.config import hydra_runner from nemo.utils import logging - """ python g2p_inference.py \ pretrained_model=" \ diff --git a/examples/tts/g2p/g2p_train_and_evaluate.py b/examples/tts/g2p/g2p_train_and_evaluate.py index 1770bd28f87d..3627681ffe15 100644 --- a/examples/tts/g2p/g2p_train_and_evaluate.py +++ b/examples/tts/g2p/g2p_train_and_evaluate.py @@ -16,15 +16,14 @@ import pytorch_lightning as pl import torch -from nemo.collections.tts.g2p.models import G2PModel from utils import get_model from nemo.collections.common.callbacks import LogEpochTimeCallback +from nemo.collections.tts.g2p.models import G2PModel from nemo.core.config import hydra_runner from nemo.utils import logging, model_utils from nemo.utils.exp_manager import exp_manager - """ This script supports training of G2PModels (for T5G2PModel use t5_g2p.yaml, for CTCG2PModel use either g2p_conformer.yaml or g2p_t5_ctc.yaml) diff --git a/examples/tts/g2p/heteronym_classification_inference.py b/examples/tts/g2p/heteronym_classification_inference.py index a4621422a8f4..931f01439d3d 100644 --- a/examples/tts/g2p/heteronym_classification_inference.py +++ b/examples/tts/g2p/heteronym_classification_inference.py @@ -20,13 +20,12 @@ import pytorch_lightning as pl import torch -from nemo.collections.tts.g2p.models.heteronym_classification import HeteronymClassificationModel from omegaconf import OmegaConf +from nemo.collections.tts.g2p.models.heteronym_classification import HeteronymClassificationModel from nemo.core.config import hydra_runner from nemo.utils import logging - """ This script runs inference with HeteronymClassificationModel If the input manifest contains target "word_id", evaluation will be also performed. diff --git a/examples/tts/g2p/heteronym_classification_train_and_evaluate.py b/examples/tts/g2p/heteronym_classification_train_and_evaluate.py index 012e7a894958..171760f1cd3d 100644 --- a/examples/tts/g2p/heteronym_classification_train_and_evaluate.py +++ b/examples/tts/g2p/heteronym_classification_train_and_evaluate.py @@ -16,14 +16,13 @@ import pytorch_lightning as pl import torch -from nemo.collections.tts.g2p.models.heteronym_classification import HeteronymClassificationModel from nemo.collections.common.callbacks import LogEpochTimeCallback +from nemo.collections.tts.g2p.models.heteronym_classification import HeteronymClassificationModel from nemo.core.config import hydra_runner from nemo.utils import logging from nemo.utils.exp_manager import exp_manager - """ This script runs training and evaluation of HeteronymClassificationModel diff --git a/examples/tts/g2p/utils.py b/examples/tts/g2p/utils.py index c91be04f2ae3..143259356ce6 100644 --- a/examples/tts/g2p/utils.py +++ b/examples/tts/g2p/utils.py @@ -14,10 +14,9 @@ import json +from nemo.collections.asr.metrics.wer import word_error_rate from nemo.collections.tts.g2p.models import CTCG2PModel from nemo.collections.tts.g2p.models.t5_g2p import T5G2PModel - -from nemo.collections.asr.metrics.wer import word_error_rate from nemo.utils import logging diff --git a/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py b/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py index 539c9d85a829..e043367a9feb 100644 --- a/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py +++ b/nemo/collections/common/tokenizers/text_to_speech/tokenizer_wrapper.py @@ -12,10 +12,9 @@ # See the License for the specific language governing permissions and # limitations under the License. -from nemo.collections.tts.g2p.modules import EnglishG2p - from nemo.collections.common.tokenizers import TokenizerSpec from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import EnglishPhonemesTokenizer +from nemo.collections.tts.g2p.modules import EnglishG2p __all__ = ['TextToSpeechTokenizer'] diff --git a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py index ac9cb45a2724..ef66913d22f0 100644 --- a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py +++ b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py @@ -19,18 +19,17 @@ from contextlib import contextmanager from typing import List, Optional +from nemo.collections.common.tokenizers.text_to_speech.ipa_lexicon import ( + get_grapheme_character_set, + get_ipa_punctuation_list, + validate_locale, +) from nemo.collections.tts.g2p.data.data_utils import ( any_locale_text_preprocessing, chinese_text_preprocessing, english_text_preprocessing, spanish_text_preprocessing, ) - -from nemo.collections.common.tokenizers.text_to_speech.ipa_lexicon import ( - get_grapheme_character_set, - get_ipa_punctuation_list, - validate_locale, -) from nemo.utils import logging from nemo.utils.decorators import experimental diff --git a/nemo/collections/tts/g2p/models/__init__.py b/nemo/collections/tts/g2p/models/__init__.py index 46c89fc49a6e..e1eeee3b2c33 100644 --- a/nemo/collections/tts/g2p/models/__init__.py +++ b/nemo/collections/tts/g2p/models/__init__.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -from nemo.collections.tts.g2p.models.t5_g2p import T5G2PModel from nemo.collections.tts.g2p.models.ctc_g2p import CTCG2PModel +from nemo.collections.tts.g2p.models.t5_g2p import T5G2PModel __all__ = ["T5G2PModel", "CTCG2PModel"] diff --git a/nemo/collections/tts/g2p/models/ctc_g2p.py b/nemo/collections/tts/g2p/models/ctc_g2p.py index 2a7ad7965c02..66475513ba59 100644 --- a/nemo/collections/tts/g2p/models/ctc_g2p.py +++ b/nemo/collections/tts/g2p/models/ctc_g2p.py @@ -19,13 +19,13 @@ import torch from hydra.utils import instantiate -from nemo.collections.tts.g2p.data.ctc_g2p import CTCG2PBPEDataset -from nemo.collections.tts.g2p.models.g2p_model import G2PModel from omegaconf import DictConfig, ListConfig, OmegaConf, open_dict from pytorch_lightning import Trainer from torch import nn from transformers import AutoConfig, AutoModel, AutoTokenizer +from nemo.collections.tts.g2p.data.ctc_g2p import CTCG2PBPEDataset +from nemo.collections.tts.g2p.models.g2p_model import G2PModel from nemo.core.classes.common import PretrainedModelInfo from nemo.utils import logging diff --git a/nemo/collections/tts/g2p/models/heteronym_classification.py b/nemo/collections/tts/g2p/models/heteronym_classification.py index ddfac56ef93a..f9727c7ad887 100644 --- a/nemo/collections/tts/g2p/models/heteronym_classification.py +++ b/nemo/collections/tts/g2p/models/heteronym_classification.py @@ -19,8 +19,6 @@ import torch from hydra.utils import instantiate -from nemo.collections.tts.g2p.data.data_utils import get_heteronym_spans, get_wordid_to_phonemes, read_wordids -from nemo.collections.tts.g2p.data.heteronym_classification_data import HeteronymClassificationDataset from omegaconf import DictConfig from pytorch_lightning import Trainer @@ -28,6 +26,8 @@ from nemo.collections.nlp.metrics.classification_report import ClassificationReport from nemo.collections.nlp.modules.common import TokenClassifier from nemo.collections.nlp.parts.utils_funcs import tensor2list +from nemo.collections.tts.g2p.data.data_utils import get_heteronym_spans, get_wordid_to_phonemes, read_wordids +from nemo.collections.tts.g2p.data.heteronym_classification_data import HeteronymClassificationDataset from nemo.core.classes.common import PretrainedModelInfo from nemo.utils import logging diff --git a/nemo/collections/tts/g2p/models/t5_g2p.py b/nemo/collections/tts/g2p/models/t5_g2p.py index bc1ba7e88ab9..a3d54caf3644 100644 --- a/nemo/collections/tts/g2p/models/t5_g2p.py +++ b/nemo/collections/tts/g2p/models/t5_g2p.py @@ -17,13 +17,13 @@ import torch from hydra.utils import instantiate -from nemo.collections.tts.g2p.data.t5_g2p import T5G2PDataset -from nemo.collections.tts.g2p.models.g2p_model import G2PModel from omegaconf import DictConfig, OmegaConf from pytorch_lightning import Trainer from transformers import AutoTokenizer, T5ForConditionalGeneration from nemo.collections.asr.metrics.wer import word_error_rate +from nemo.collections.tts.g2p.data.t5_g2p import T5G2PDataset +from nemo.collections.tts.g2p.models.g2p_model import G2PModel from nemo.core.classes.common import PretrainedModelInfo, typecheck from nemo.core.neural_types import LabelsType, LossType, MaskType, NeuralType, TokenIndex from nemo.utils import logging diff --git a/nemo/collections/tts/g2p/modules.py b/nemo/collections/tts/g2p/modules.py index 6108098cfa74..e1feb2981cb4 100644 --- a/nemo/collections/tts/g2p/modules.py +++ b/nemo/collections/tts/g2p/modules.py @@ -23,6 +23,8 @@ import nltk import torch + +from nemo.collections.common.tokenizers.text_to_speech.ipa_lexicon import validate_locale from nemo.collections.tts.g2p.data.data_utils import ( GRAPHEME_CASE_MIXED, GRAPHEME_CASE_UPPER, @@ -32,8 +34,6 @@ normalize_unicode_text, set_grapheme_case, ) - -from nemo.collections.common.tokenizers.text_to_speech.ipa_lexicon import validate_locale from nemo.utils import logging from nemo.utils.decorators import experimental from nemo.utils.get_rank import is_global_rank_zero diff --git a/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py b/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py index 54fc0f061ca8..4a8fe62e351b 100644 --- a/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py +++ b/tests/collections/common/tokenizers/text_to_speech/test_tts_tokenizers.py @@ -13,7 +13,6 @@ # limitations under the License. import pytest -from nemo.collections.tts.g2p.modules import IPAG2P from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import ( EnglishCharsTokenizer, @@ -21,6 +20,7 @@ IPATokenizer, SpanishCharsTokenizer, ) +from nemo.collections.tts.g2p.modules import IPAG2P class TestTTSTokenizers: diff --git a/tests/collections/tts/test_torch_tts.py b/tests/collections/tts/test_torch_tts.py index 4a1c2a4e0990..5d39c955fa88 100644 --- a/tests/collections/tts/test_torch_tts.py +++ b/tests/collections/tts/test_torch_tts.py @@ -18,9 +18,9 @@ import pytest import torch -from nemo.collections.tts.g2p.modules import EnglishG2p from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import EnglishPhonemesTokenizer +from nemo.collections.tts.g2p.modules import EnglishG2p from nemo.collections.tts.torch.data import TTSDataset from nemo.collections.tts.torch.helpers import get_base_dir diff --git a/tools/ctc_segmentation/requirements.txt b/tools/ctc_segmentation/requirements.txt index 2c6cdaa1e755..f010b225a66e 100644 --- a/tools/ctc_segmentation/requirements.txt +++ b/tools/ctc_segmentation/requirements.txt @@ -1,3 +1,3 @@ ctc_segmentation==1.7.1 -num2words nemo_text_processing==0.1.6rc0 +num2words From e7019b7f0a9bf5ceee52ad770bd74c1ea4b8016e Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 12:06:24 -0800 Subject: [PATCH 03/19] fix imports Signed-off-by: ekmb --- docs/source/tts/api.rst | 2 +- docs/source/tts/checkpoints.rst | 2 +- docs/source/tts/configs.rst | 6 +- docs/source/tts/datasets.rst | 2 +- examples/tts/conf/aligner.yaml | 4 +- .../conf/de/fastpitch_align_22050_mix.yaml | 2 +- .../conf/es/fastpitch_align_44100_ipa.yaml | 2 +- .../es/fastpitch_align_44100_ipa_multi.yaml | 2 +- examples/tts/conf/fastpitch_align_44100.yaml | 4 +- examples/tts/conf/fastpitch_align_ipa.yaml | 4 +- examples/tts/conf/fastpitch_align_v1.05.yaml | 4 +- examples/tts/conf/mixer-tts-x.yaml | 2 +- examples/tts/conf/mixer-tts.yaml | 4 +- examples/tts/conf/rad-tts_dec.yaml | 4 +- examples/tts/conf/rad-tts_feature_pred.yaml | 4 +- examples/tts/conf/tacotron2.yaml | 4 +- examples/tts/conf/vits.yaml | 4 +- examples/tts/conf/vits_44100.yaml | 4 +- .../tts/conf/zh/fastpitch_align_22050.yaml | 2 +- examples/tts/g2p/conf/g2p_conformer_ctc.yaml | 2 +- .../text_to_speech/tts_tokenizers.py | 2 +- nemo/collections/tts/g2p/modules.py | 2 +- nemo/collections/tts/torch/tts_dataset.yaml | 4 +- .../ds_conf/ds_for_fastpitch_align.yaml | 4 +- .../ljspeech/ds_conf/ds_for_mixer_tts.yaml | 4 +- .../ljspeech/ds_conf/ds_for_mixer_tts_x.yaml | 2 +- .../tts/ljspeech/get_data.py | 2 +- .../ds_conf/ds_for_fastpitch_align.yaml | 4 +- .../wordid_to_ipa-0.7b_nv22.10.tsv | 326 ++++++++++++++++++ .../asr/test_text_to_text_dataset.py | 2 +- .../tts/FastPitch_ChineseTTS_Training.ipynb | 2 +- .../tts/FastPitch_MixerTTS_Training.ipynb | 4 +- tutorials/tts/NeMo_TTS_Primer.ipynb | 2 +- .../tts/Pronunciation_customization.ipynb | 2 +- tutorials/tts/Tacotron2_Training.ipynb | 4 +- 35 files changed, 378 insertions(+), 52 deletions(-) create mode 100644 scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv diff --git a/docs/source/tts/api.rst b/docs/source/tts/api.rst index b68bb0458331..7e87687aa0a8 100644 --- a/docs/source/tts/api.rst +++ b/docs/source/tts/api.rst @@ -96,4 +96,4 @@ Dataset Processing Classes .. autoclass:: nemo.collections.tts.torch.data.VocoderDataset :show-inheritance: - :members: \ No newline at end of file + :members: diff --git a/docs/source/tts/checkpoints.rst b/docs/source/tts/checkpoints.rst index f78cf6a2805e..8d79c4a278f1 100644 --- a/docs/source/tts/checkpoints.rst +++ b/docs/source/tts/checkpoints.rst @@ -150,4 +150,4 @@ End2End models .. csv-table:: :file: data/ngc_models_e2e.csv :align: left - :header-rows: 1 \ No newline at end of file + :header-rows: 1 diff --git a/docs/source/tts/configs.rst b/docs/source/tts/configs.rst index c8f47c82c03f..cecaee29673a 100644 --- a/docs/source/tts/configs.rst +++ b/docs/source/tts/configs.rst @@ -96,7 +96,7 @@ Text normalization (TN) converts text from written form into its verbalized form _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" + whitelist: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" text_normalizer_call_kwargs: verbose: false @@ -118,7 +118,7 @@ Tokenization converts input text string to a list of integer tokens. It may pad apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 @@ -260,4 +260,4 @@ Fine-tuning via a Pytorch Lightning checkpoint trainer.devices=-1 \ trainer.accelerator='gpu' \ trainer.max_epochs=50 \ - +init_from_ptl_ckpt="" \ No newline at end of file + +init_from_ptl_ckpt="" diff --git a/docs/source/tts/datasets.rst b/docs/source/tts/datasets.rst index 083566bc7cb8..4b2e96baedb6 100644 --- a/docs/source/tts/datasets.rst +++ b/docs/source/tts/datasets.rst @@ -47,7 +47,7 @@ LJSpeech $ python scripts/dataset_processing/tts/ljspeech/get_data.py \ --data-root \ --whitelist-path \ - or default nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv + or default scripts/tts_dataset_files/en/whitelist_lj_speech.tsv $ python scripts/dataset_processing/tts/extract_sup_data.py \ --config-path ljspeech/ds_conf \ diff --git a/examples/tts/conf/aligner.yaml b/examples/tts/conf/aligner.yaml index 3ee77b70ead1..e0008e65fe4b 100644 --- a/examples/tts/conf/aligner.yaml +++ b/examples/tts/conf/aligner.yaml @@ -21,7 +21,7 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: symbols_embedding_dim: 384 @@ -56,7 +56,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} diff --git a/examples/tts/conf/de/fastpitch_align_22050_mix.yaml b/examples/tts/conf/de/fastpitch_align_22050_mix.yaml index 1ea036055e09..ddd25d07bb38 100644 --- a/examples/tts/conf/de/fastpitch_align_22050_mix.yaml +++ b/examples/tts/conf/de/fastpitch_align_22050_mix.yaml @@ -74,7 +74,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P locale: 'de-DE' phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} diff --git a/examples/tts/conf/es/fastpitch_align_44100_ipa.yaml b/examples/tts/conf/es/fastpitch_align_44100_ipa.yaml index 53b8f813e1dc..38159321a75a 100644 --- a/examples/tts/conf/es/fastpitch_align_44100_ipa.yaml +++ b/examples/tts/conf/es/fastpitch_align_44100_ipa.yaml @@ -60,7 +60,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P locale: es-ES phoneme_dict: ${phoneme_dict_path} phoneme_probability: 0.5 diff --git a/examples/tts/conf/es/fastpitch_align_44100_ipa_multi.yaml b/examples/tts/conf/es/fastpitch_align_44100_ipa_multi.yaml index 034de2396cb1..d31634f7b3b8 100644 --- a/examples/tts/conf/es/fastpitch_align_44100_ipa_multi.yaml +++ b/examples/tts/conf/es/fastpitch_align_44100_ipa_multi.yaml @@ -57,7 +57,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P locale: es-ES phoneme_dict: ${phoneme_dict_path} phoneme_probability: 0.5 diff --git a/examples/tts/conf/fastpitch_align_44100.yaml b/examples/tts/conf/fastpitch_align_44100.yaml index aa60093f2d3b..29ef03109ef6 100644 --- a/examples/tts/conf/fastpitch_align_44100.yaml +++ b/examples/tts/conf/fastpitch_align_44100.yaml @@ -29,7 +29,7 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: learn_alignment: true @@ -74,7 +74,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 diff --git a/examples/tts/conf/fastpitch_align_ipa.yaml b/examples/tts/conf/fastpitch_align_ipa.yaml index 5765b3e91797..d1a55d909e1e 100644 --- a/examples/tts/conf/fastpitch_align_ipa.yaml +++ b/examples/tts/conf/fastpitch_align_ipa.yaml @@ -30,7 +30,7 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: learn_alignment: true @@ -73,7 +73,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.8 diff --git a/examples/tts/conf/fastpitch_align_v1.05.yaml b/examples/tts/conf/fastpitch_align_v1.05.yaml index 368dd4e502fd..aa31b52fd5ec 100644 --- a/examples/tts/conf/fastpitch_align_v1.05.yaml +++ b/examples/tts/conf/fastpitch_align_v1.05.yaml @@ -30,7 +30,7 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: learn_alignment: true @@ -75,7 +75,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 diff --git a/examples/tts/conf/mixer-tts-x.yaml b/examples/tts/conf/mixer-tts-x.yaml index 9a0f552dc4bb..5f55dc02a095 100644 --- a/examples/tts/conf/mixer-tts-x.yaml +++ b/examples/tts/conf/mixer-tts-x.yaml @@ -30,7 +30,7 @@ window: hann lm_model: albert -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: bin_loss_start_ratio: 0.2 diff --git a/examples/tts/conf/mixer-tts.yaml b/examples/tts/conf/mixer-tts.yaml index 474e32a3e730..7668b9d5bf96 100644 --- a/examples/tts/conf/mixer-tts.yaml +++ b/examples/tts/conf/mixer-tts.yaml @@ -30,7 +30,7 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: bin_loss_start_ratio: 0.2 @@ -76,7 +76,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} diff --git a/examples/tts/conf/rad-tts_dec.yaml b/examples/tts/conf/rad-tts_dec.yaml index 7b5cd5bc3442..7e676e7985da 100644 --- a/examples/tts/conf/rad-tts_dec.yaml +++ b/examples/tts/conf/rad-tts_dec.yaml @@ -104,7 +104,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 @@ -148,7 +148,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 diff --git a/examples/tts/conf/rad-tts_feature_pred.yaml b/examples/tts/conf/rad-tts_feature_pred.yaml index cd7cce38f1a1..9aee2d4a6264 100644 --- a/examples/tts/conf/rad-tts_feature_pred.yaml +++ b/examples/tts/conf/rad-tts_feature_pred.yaml @@ -103,7 +103,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 @@ -147,7 +147,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 diff --git a/examples/tts/conf/tacotron2.yaml b/examples/tts/conf/tacotron2.yaml index 4137ef19b5ad..4d30f25e4ae3 100644 --- a/examples/tts/conf/tacotron2.yaml +++ b/examples/tts/conf/tacotron2.yaml @@ -11,7 +11,7 @@ sup_data_types: null phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: pitch_fmin: 65.40639132514966 @@ -46,7 +46,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} diff --git a/examples/tts/conf/vits.yaml b/examples/tts/conf/vits.yaml index 1002bdfe89f5..64b1cf6ff12d 100644 --- a/examples/tts/conf/vits.yaml +++ b/examples/tts/conf/vits.yaml @@ -13,7 +13,7 @@ sup_data_types: null phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" # Default values from librosa.pyin pitch_fmin: 65.40639132514966 @@ -66,7 +66,7 @@ model: apostrophe: true pad_with_space: false g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.8 diff --git a/examples/tts/conf/vits_44100.yaml b/examples/tts/conf/vits_44100.yaml index c9955e70abce..d666ae31f048 100644 --- a/examples/tts/conf/vits_44100.yaml +++ b/examples/tts/conf/vits_44100.yaml @@ -23,7 +23,7 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: n_speakers: 13000 @@ -61,7 +61,7 @@ model: apostrophe: true pad_with_space: false g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.8 diff --git a/examples/tts/conf/zh/fastpitch_align_22050.yaml b/examples/tts/conf/zh/fastpitch_align_22050.yaml index b09540a75aad..c5275ba44fb8 100644 --- a/examples/tts/conf/zh/fastpitch_align_22050.yaml +++ b/examples/tts/conf/zh/fastpitch_align_22050.yaml @@ -72,7 +72,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.ChineseG2p + _target_: nemo.collections.tts.g2p.modules.ChineseG2p phoneme_dict: ${phoneme_dict_path} word_segmenter: jieba # Only jieba is supported now. diff --git a/examples/tts/g2p/conf/g2p_conformer_ctc.yaml b/examples/tts/g2p/conf/g2p_conformer_ctc.yaml index aa94405747fb..d1c4b0b9ae9f 100644 --- a/examples/tts/g2p/conf/g2p_conformer_ctc.yaml +++ b/examples/tts/g2p/conf/g2p_conformer_ctc.yaml @@ -1,4 +1,4 @@ -name: G2P_paper-Conformer-CTC +name: G2P-Conformer-CTC # Dataset info train_manifest: ??? diff --git a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py index ac9cb45a2724..4e535589747e 100644 --- a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py +++ b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py @@ -605,7 +605,7 @@ def encode_from_g2p(self, g2p_text: List[str], raw_text: Optional[str] = None) - of graphemes, or a mixture of both. For example, `['ˈ', 's', 'i', ' ', '#O', '#O', '#V']`, which is the G2P_paper's output of the text "see OOV", where '#' is prepended to each grapheme in order to distinguish graphemes from phonemes if there are overlaps in between. The prefix '#' can be customized in - `nemo_text_processing.g2p.modules.IPAG2P.grapheme_prefix`. + `nemo.collections.tts.g2p.modules.IPAG2P.grapheme_prefix`. raw_text (str): the original text after calling `self.text_preprocessing_func`. It is optional. It is only used to deliver a warning message that some graphemes from the original text are skipped. diff --git a/nemo/collections/tts/g2p/modules.py b/nemo/collections/tts/g2p/modules.py index 6108098cfa74..636966395a3f 100644 --- a/nemo/collections/tts/g2p/modules.py +++ b/nemo/collections/tts/g2p/modules.py @@ -436,7 +436,7 @@ def _parse_phoneme_dict( continue # Note that latin character pattern should be consistent with - # nemo_text_processing.g2p.data.data_utils.LATIN_CHARS_ALL. It is advised to extend its character + # nemo.collections.tts.g2p.data.data_utils.LATIN_CHARS_ALL. It is advised to extend its character # coverage if adding the support of new languages. # TODO @xueyang: unify hardcoded range of characters with LATIN_CHARS_ALL to avoid duplicates. line = normalize_unicode_text(line) diff --git a/nemo/collections/tts/torch/tts_dataset.yaml b/nemo/collections/tts/torch/tts_dataset.yaml index fb7aef09b955..2ca29630910e 100644 --- a/nemo/collections/tts/torch/tts_dataset.yaml +++ b/nemo/collections/tts/torch/tts_dataset.yaml @@ -22,7 +22,7 @@ tts_dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" + whitelist: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" text_normalizer_call_kwargs: verbose: False @@ -41,6 +41,6 @@ tts_dataset: add_blank_at: null pad_with_space: True g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms: "scripts/tts_dataset_files/heteronyms-052722" diff --git a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml index cbb124fdef1f..8e66cb3497aa 100644 --- a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml +++ b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml @@ -3,7 +3,7 @@ name: "ds_for_fastpitch_align" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" @@ -46,6 +46,6 @@ dataset: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} diff --git a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml index 66222656d9b9..bfec225353d3 100644 --- a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml +++ b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml @@ -3,7 +3,7 @@ name: "ds_for_mixer_tts" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" @@ -46,6 +46,6 @@ dataset: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.EnglishG2p + _target_: nemo.collections.tts.g2p.modules.EnglishG2p phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} diff --git a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml index ec0aa391fa84..89cf74f6b7de 100644 --- a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml +++ b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml @@ -3,7 +3,7 @@ name: "ds_for_mixer_tts_x" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch", "lm_tokens" ] -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" dataset: _target_: nemo.collections.tts.torch.data.MixerTTSXDataset diff --git a/scripts/dataset_processing/tts/ljspeech/get_data.py b/scripts/dataset_processing/tts/ljspeech/get_data.py index d165fcce25e9..0d933f8a29ca 100644 --- a/scripts/dataset_processing/tts/ljspeech/get_data.py +++ b/scripts/dataset_processing/tts/ljspeech/get_data.py @@ -56,7 +56,7 @@ def __extract_file(filepath, data_dir): def __process_data(data_root, whitelist_path): if whitelist_path is None: wget.download( - "https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv", + "https://raw.githubusercontent.com/NVIDIA/NeMo/main/scripts/tts_dataset_files/en/whitelist_lj_speech.tsv", out=str(data_root), ) whitelist_path = data_root / "lj_speech.tsv" diff --git a/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml b/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml index 12ba58a93dc7..f675e49954f0 100755 --- a/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml +++ b/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml @@ -3,7 +3,7 @@ name: "ds_for_fastpitch_align" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: "nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv" +whitelist_path: null # default whitelist will be used from https://raw.githubusercontent.com/NVIDIA/NeMo-text-processing/main/nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv phoneme_dict_path: "scripts/tts_dataset_files/zh/pinyin_dict_nv_22.10.txt" dataset: @@ -46,6 +46,6 @@ dataset: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.ChineseG2p + _target_: nemo.collections.tts.g2p.modules.ChineseG2p phoneme_dict: ${phoneme_dict_path} word_segmenter: jieba # Only jieba is supported now. diff --git a/scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv b/scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv new file mode 100644 index 000000000000..d46ae401895a --- /dev/null +++ b/scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv @@ -0,0 +1,326 @@ +ABSTRACT_ADJ-NOU ˈæbˌstɹækt +ABSTRACT_VRB æbˈstɹækt +ABUSE_NOU əbˈjus +ABUSE_VRB əbˈjuz +ABUSES_NOU əbˈjusɪz +ABUSES_VRB əbˈjuzɪz +ADDICT_NOU ˈæˌdɪkt +ADDICT_VRB əˈdɪkt +ADVOCATE_NOU ˈædvəkət +ADVOCATE_VRB ˈædvəˌkeɪt +AFFECT_NOU-PSY ˈæˌfɛkt +AFFECT əˈfɛkt +AFFILIATE_NOU əˈfɪliət +AFFILIATE_VRB əˈfɪliˌeɪt +AGED_ADJ ˈeɪdʒɪd +AGED ˈeɪdʒd +AGGREGATE_ADJ-NOU ˈæɡɹəɡət +AGGREGATE_VRB ˈæɡɹəɡeɪt +ALTERNATE_ADJ-NOU ˈɔltɚnət +ALTERNATE_VRB ˈɔltɚˌneɪt +ANALYSES_NOU æˈnælɪˌsiz +ANALYSES_VRB ænəˈlaɪˌzɪz +ANIMATE_ADJ-NOU ˈænəmət +ANIMATE_VRB ˈænəˌmeɪt +APPROPRIATE_ADJ əˈpɹoʊpɹiət +APPROPRIATE_VRB əˈpɹoʊpɹiˌeɪt +APPROXIMATE_ADJ-NOU əˈpɹɑksəmət +APPROXIMATE_VRB əˈpɹɑksəˌmeɪt +ARTICULATE_ADJ ɑɹˈtɪkjələt +ARTICULATE_VRB ɑɹˈtɪkjəˌleɪt +ASSOCIATE_ADJ-NOU əˈsoʊsiət +ASSOCIATE_VRB əˈsoʊsiˌeɪt +ATTRIBUTE_NOU ˈætɹəbˌjut +ATTRIBUTE_VRB əˈtɹɪbˌjut +AUGUST_ADJ ˌɑˈɡəst +AUGUST ˈɑɡəst +AUGUST_NAM ˈaʊˌɡʊst +AXES_NOU ˈækˌsiz +AXES_NOU-VRB ˈækˌsɪz +BASS ˈbeɪs +BASS_CORP ˈbæs +BLESSED_ADJ ˈblɛsəd +BLESSED_VRB ˈblɛst +BOLOGNA_GEO bəˈloʊˌŋɑ +BOLOGNA bəˈloʊni +BOW_NOU-KNOT ˈboʊ +BOW_NOU-SHIP ˈbaʊ +BUFFET_NOU bəˈfeɪ +BUFFET_VRB ˈbʌfət +CELTIC_ADJ-NOU-SPORTS ˈsɛltɪk +CELTIC ˈkɛltɪk +CLOSE_ADJ-NOU ˈkloʊs +CLOSE_VRB ˈkloʊz +COMBINE_NOU ˈkɑmbaɪn +COMBINE_VRB kəmˈbaɪn +COMPACT_ADJ-NOU ˈkɑmpækt +COMPACT_VRB kəmˈpækt +COMPOUND_NOU ˈkɑmpaʊnd +COMPOUND_VRB kəmˈpaʊnd +COMPRESS_NOU ˈkɑmpɹɛs +COMPRESS kəmˈpɹɛs +CONDUCT_NOU ˈkɑndəkt +CONDUCT_VRB kɑnˈdʌkt +CONFINES_NOU ˈkɑnˌfaɪnz +CONFINES_VRB kənˈfaɪnz +CONFLICT_NOU ˈkɑnflɪkt +CONFLICT_VRB kənˈflɪkt +CONGLOMERATE_ADJ-NOU kənˈɡlɑmɚət +CONGLOMERATE_VRB kənˈɡlɑmɝˌeɪt +CONJUGATE_ADJ-NOU ˈkɑndʒəˌɡeɪt +CONJUGATE_VRB ˈkɑndʒəˌɡeɪt +CONSCRIPT_NOU ˈkɑnsˌkɹɪpt +CONSCRIPT_VRB kənsˈkɹɪpt +CONSOLE_NOU ˈkɑnsoʊl +CONSOLE_VRB kənˈsoʊl +CONSORT_NOU ˈkɑnˌsɔɹt +CONSORT_VRB kənˈsɔɹt +CONSTRUCT_NOU ˈkɑnstɹəkt +CONSTRUCT_VRB kənˈstɹʌkt +CONSUMMATE_ADJ ˈkɑnsəmət +CONSUMMATE_VRB ˈkɑnsəˌmeɪt +CONTENT_ADJ-NOU-VRB kənˈtɛnt +CONTENT_NOU ˈkɑntɛnt +CONTEST_NOU ˈkɑntɛst +CONTEST_VRB kənˈtɛst +CONTRACT_NOU ˈkɑnˌtɹækt +CONTRACT_VRB kənˈtɹækt +CONTRAST_NOU ˈkɑntɹæst +CONTRAST_VRB kənˈtɹæst +CONVERSE_ADJ-NOU ˈkɑnvɚs +CONVERSE_VRB kənˈvɝs +CONVERT_NOU ˈkɑnvɚt +CONVERT_VRB kənˈvɝt +CONVICT_NOU ˈkɑnvɪkt +CONVICT_VRB kənˈvɪkt +COORDINATE_ADJ-NOU koʊˈɔɹdənət +COORDINATE_VRB koʊˈɔɹdəˌneɪt +CORRELATE_NOU ˈkɔɹələt +CORRELATE_NOU-VRB ˈkɔɹəˌleɪt +DECREASE_NOU ˈdiˌkɹis +DECREASE_VRB dɪˈkɹis +DEFECT_NOU ˈdifɛkt +DEFECT_VRB dɪˈfɛkt +DEGENERATE_ADJ-NOU dɪˈdʒɛnɚət +DEGENERATE_VRB dɪˈdʒɛnɚˌeɪt +DELEGATE_NOU ˈdɛləɡət +DELEGATE_VRB ˈdɛləˌɡeɪt +DELIBERATE_ADJ dɪˈlɪbɚət +DELIBERATE_VRB dɪˈlɪbɚˌeɪt +DESERT_NOU ˈdɛzɚt +DESERT_VRB dɪˈzɝt +DEVIATE_NOU ˈdiˌviət +DEVIATE_VRB ˈdiviˌeɪt +DIAGNOSES_NOU ˌdaɪəɡˈnoʊsiz +DIAGNOSES_VRB ˌdaɪəɡˈnoʊsəz +DIFFUSE_ADJ dɪfˈjus +DIFFUSE_VRB dɪfˈjuz +DISCARD_NOU ˈdɪsˌkɑɹd +DISCARD_VRB dəsˈkɑɹd +DISCHARGE_NOU ˈdɪsˌtʃɑɹdʒ +DISCHARGE_VRB dɪsˈtʃɑɹdʒ +DISCOUNT_NOU ˈdɪskaʊnt +DISCOUNT_VRB dɪˈskaʊnt +DOCUMENT_NOU ˈdɑkjumɛnt +DOCUMENT_VRB ˈdɑkjəmɛnt +DOVE ˈdʌv +DOVE_VRB ˈdoʊv +DUPLICATE_ADJ-NOU ˈdupləkət +DUPLICATE_VRB ˈdupləˌkeɪt +ELABORATE_ADJ ɪˈlæbɹət +ELABORATE_VRB ɪˈlæbɚˌeɪt +ENTRANCE_NOU ˈɛntɹəns +ENTRANCE_VRB əˈntɹæns +ESCORT_NOU ˈɛskɔɹt +ESCORT_VRB ɛˈskɔɹt +ESTIMATE_NOU ˈɛstəmət +ESTIMATE_VRB ˈɛstəˌmeɪt +EXCUSE_NOU ɪkˈskjus +EXCUSE_VRB ɪkˈskjuz +EXPATRIATE_NOU ɛkˈspeɪtɹiət +EXPATRIATE_VRB ɛkˈspeɪtɹiˌeɪt +EXPLOIT_NOU ˈɛksˌplɔɪt +EXPLOIT_VRB ˌɛksˈplɔɪt +EXPORT_NOU ˈɛkspɔɹt +EXPORT_VRB əkˈspɔɹt +EXPOSE_NOU ˌɛkˌspoʊˈzeɪ +EXPOSE_VRB ɪkˈspoʊz +EXTRACT_NOU ˈɛkˌstɹækt +EXTRACT_VRB ɪkˈstɹækt +FRAGMENT_NOU ˈfɹæɡmənt +FRAGMENT_VRB ˌfɹæɡˈmɛnt +FREQUENT_ADJ ˈfɹikwənt +FREQUENT_VRB ˌfɹiˈkwɛnt +GRADUATE_ADJ-NOU ˈɡɹædʒuwət +GRADUATE_VRB ˈɡɹædʒuˌeɪt +HOUSE_NOU ˈhaʊs +HOUSE_VRB ˈhaʊz +IMPACT_NOU ˈɪmpækt +IMPACT_VRB ˌɪmˈpækt +IMPLANT_NOU ˈɪmˌplænt +IMPLANT_VRB ˌɪmˈplænt +IMPLEMENT_NOU ˈɪmpləmənt +IMPLEMENT_VRB ˈɪmpləˌmɛnt +IMPORT_NOU ˈɪmˌpɔɹt +IMPORT_VRB ˌɪmˈpɔɹt +INCENSE_NOU ˈɪnˌsɛns +INCENSE_VRB ˌɪnˈsɛns +INCLINE_NOU ˈɪnklaɪn +INCLINE_VRB ˌɪnˈklaɪn +INCREASE_NOU ˈɪnˌkɹis +INCREASE_VRB ˌɪnˈkɹis +INCREMENT_NOU ˈɪnkɹəmənt +INCREMENT_VRB ˈɪnkɹəˌmɛnt +INITIATE_NOU əˈnɪˌʃiət +INITIATE_VRB ˌɪˈnɪʃiˌeɪt +INSERT_NOU ˈɪnˌsɝt +INSERT_VRB ˌɪnˈsɝt +INSTRUMENT_NOU ˈɪnstɹəmənt +INSTRUMENT_VRB ˈɪnstɹəˌmɛnt +INSULT_NOU ˈɪnˌsʌlt +INSULT_VRB ˌɪnˈsʌlt +INTERCHANGE_NOU ˈɪntɚˌtʃeɪndʒ +INTERCHANGE_VRB ˌɪntɚˈtʃeɪndʒ +INTIMATE_ADJ ˈɪntəmət +INTIMATE_VRB ˈɪntɪˌmeɪt +INTRIGUE_NOU ˈɪntɹiɡ +INTRIGUE_NOU-VRB ˌɪnˈtɹiɡ +INVALID_ADJ ˌɪnˈvæləd +INVALID_NOU ˈɪnvələd +INVERT_ADJ-NOU ˈɪnvɝt +INVERT_VRB ˌɪnˈvɝt +INVITE_NOU ˈɪnˌvaɪt +INVITE_VRB ˌɪnˈvaɪt +ISOLATE_NOU ˈaɪsələt +ISOLATE ˈaɪsəˌleɪt +JESUS ˈdʒizəs +JESUS_ES ˌheɪˈsus +JOB_BIBLE ˈdʒoʊb +JOB ˈdʒɑb +LAMINATE_NOU ˈlæmənət +LAMINATE_VRB ˈlæməˌneɪt +LEAD_NOU ˈlɛd +LEAD_NOU-VRB ˈlid +LEARNED_ADJ ˈlɝnɪd +LEARNED_VRB ˈlɝnd +LIVE_ADJ ˈlaɪv +LIVE_VRB ˈlɪv +LIVES_NOU ˈlaɪvz +LIVES_VRB ˈlɪvz +MATE_NOU ˈmɑˌteɪ +MATE ˈmeɪt +MINUTE_ADJ maɪˈnut +MINUTE ˈmɪnət +MISUSE_NOU mɪsˈjus +MISUSE_VRB mɪsˈjuz +MOBILE ˈmoʊbəl +MOBILE_GEO ˌmoʊˈbil +MOBILE_NOU-ART ˈmoʊˌbil +MODERATE_ADJ-NOU ˈmɑdɚət +MODERATE_VRB ˈmɑdɚˌeɪt +MOPED_NOU ˈmoʊpɛd +MOPED_VRB ˈmoʊpt +MOUTH_NOU ˈmaʊθ +MOUTH_VRB ˈmaʊð +NESTLE_NAM ˈnɛsˈli +NESTLE_VRB ˈnɛsəl +OBJECT_NOU ˈɑbdʒɛkt +OBJECT_VRB əbˈdʒɛkt +ORNAMENT_NOU ˈɔɹnəmənt +ORNAMENT_VRB ˌɔɹnəˈmɛnt +OVERTHROW_NOU ˈoʊvɚˌθɹoʊ +OVERTHROW_VRB ˌoʊvɚˈθɹoʊ +PASTY_ADJ ˈpeɪˌsti +PASTY_NOU ˈpæsˌti +PERFECT_ADJ ˈpɝˌfɪkt +PERFECT_VRB pɚˈfɛkt +PERFUME_NOU ˈpɝˌfjum +PERFUME_VRB pɚˈfjum +PERMIT_NOU ˈpɝˌmɪt +PERMIT_VRB pɚˈmɪt +PERVERT_NOU ˈpɝvɚt +PERVERT_VRB pɚˈvɝt +PIGMENT_NOU ˈpɪɡmɛnt +PIGMENT_VRB pəɡˈmɛnt +POLISH_GEO ˈpoʊlɪʃ +POLISH ˈpɑlɪʃ +POSTULATE_NOU ˈpɑstʃələt +POSTULATE_VRB ˈpɑstʃəˌleɪt +PRECIPITATE_ADJ-NOU pɹəˈsɪpətət +PRECIPITATE_VRB pɹɪˈsɪpɪˌteɪt +PREDICATE_NOU ˈpɹɛdɪkət +PREDICATE_VRB ˈpɹɛdəˌkeɪt +PRESENT_ADJ-NOU ˈpɹɛzənt +PRESENT_VRB pɹiˈzɛnt +PRODUCE_NOU ˈpɹoʊdus +PRODUCE_VRB pɹəˈdus +PROGRESS_NOU ˈpɹɑˌɡɹɛs +PROGRESS_VRB pɹəˈɡɹɛs +PROJECT_NOU ˈpɹɑdʒɛkt +PROJECT_VRB pɹɑˈdʒɛkt +PROTEST_NOU ˈpɹoʊˌtɛst +PROTEST_VRB pɹəˈtɛst +RAVEL_NAM ɹəˈvɛl +RAVEL_NOU ˈɹævəl +READING_EN ˈɹidɪŋ +READING_GEO ˈɹɛdɪŋ +READ_PAST ˈɹɛd +READ_PRESENT ˈɹid +REBEL_NOU ˈɹɛbəl +REBEL_VRB ɹɪˈbɛl +RECORD_NOU ˈɹɛkɚd +RECORD_VRB ɹəˈkɔɹd +RECOUNT_NOU ˈɹiˌkaʊnt +RECOUNT_VRB ˌɹiˈkaʊnt +REFUND_NOU ˈɹiˌfʌnd +REFUND_VRB ɹɪˈfʌnd +REFUSE_NOU ˈɹɛfˌjuz +REFUSE_VRB ɹəfˈjuz +REJECT_NOU ˈɹidʒɛkt +REJECT_VRB ɹɪˈdʒɛkt +RERELEASE ˈɹiɹəˌlis +RERELEASE_VRB ˌɹiɹəˈlis +RESUME_NOU ˈɹɛzəˌmeɪ +RESUME_VRB ɹiˈzum +RETARD_NOU ˈɹitɑɹd +RETARD_VRB ɹɪˈtɑɹd +RODEO_GEO ˌɹoʊˈdeɪˌoʊ +RODEO ˈɹoʊdiˌoʊ +ROW_1 ˈɹoʊ +ROW_2 ˈɹaʊ +SAKE_JP ˈsɑˌkeɪ +SAKE ˈseɪk +SEPARATE_ADJ ˈsɛpɚɪt +SEPARATE_VRB ˈsɛpɚˌeɪt +SOW_NOU ˈsaʊ +SOW ˈsoʊ +SUBJECT_ADJ-NOU ˈsʌbdʒɪkt +SUBJECT_VRB səbˈdʒɛkt +SUBORDINATE_ADJ-NOU səˈbɔɹdənət +SUBORDINATE_VRB səˈbɔɹdəˌneɪt +SUPPLEMENT_NOU ˈsʌpləmənt +SUPPLEMENT_VRB ˈsʌpləmənt +SUSPECT_ADJ-NOU ˈsʌsˌpɛkt +SUSPECT_VRB səˈspɛkt +SYNDICATE_NOU ˈsɪndɪkət +SYNDICATE_VRB ˈsɪndəˌkeɪt +TEAR_NOU ˈtɪɹ +TEAR_VRB ˈtɛɹ +TRANSFORM_NOU ˈtɹænsfɔɹm +TRANSFORM tɹænsˈfɔɹm +TRANSPLANT_NOU ˈtɹænsˌplænt +TRANSPLANT_VRB tɹænsˈplænt +TRANSPORT_NOU ˈtɹænspɔɹt +TRANSPORT_VRB tɹænˈspɔɹt +UPSET_NOU ˈʌpˌsɛt +UPSET_VRB əpˈsɛt +USES_NOU ˈjusəz +USES_VRB ˈjuzəz +USE_NOU ˈjus +USE_VRB ˈjuz +WIND_NOU ˈwɪnd +WIND_VRB ˈwaɪnd +WINDS_NOU ˈwɪndz +WINDS_VRB ˈwaɪndz +WOUND_NOU-VRB ˈwund +WOUND_VRB ˈwaʊnd diff --git a/tests/collections/asr/test_text_to_text_dataset.py b/tests/collections/asr/test_text_to_text_dataset.py index 3c8951f0141f..a2f387e22c82 100644 --- a/tests/collections/asr/test_text_to_text_dataset.py +++ b/tests/collections/asr/test_text_to_text_dataset.py @@ -96,7 +96,7 @@ def asr_tokenizer(test_data_dir): def tts_tokenizer(): @dataclass class G2PConfig: - _target_: str = "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: str = "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: str = str(BASE_DIR / "scripts/tts_dataset_files/cmudict-0.7b_nv22.10") heteronyms: str = str(BASE_DIR / "scripts/tts_dataset_files/heteronyms-052722") phoneme_probability: float = 0.5 diff --git a/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb b/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb index e0c58fdf6ebd..0542a006ed91 100644 --- a/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb @@ -433,7 +433,7 @@ " apostrophe: true\n", " pad_with_space: true\n", " g2p:\n", - " _target_: nemo_text_processing.g2p.modules.ChineseG2p\n", + " _target_: nemo.collections.tts.g2p.modules.ChineseG2p\n", " phoneme_dict: ${phoneme_dict_path}\n", "```\n", "\n", diff --git a/tutorials/tts/FastPitch_MixerTTS_Training.ipynb b/tutorials/tts/FastPitch_MixerTTS_Training.ipynb index 1b2ebc66ea3b..52d555faa934 100644 --- a/tutorials/tts/FastPitch_MixerTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_MixerTTS_Training.ipynb @@ -198,7 +198,7 @@ "metadata": {}, "outputs": [], "source": [ - "from nemo_text_processing.g2p.modules import EnglishG2p\n", + "from nemo.collections.tts.g2p.modules import EnglishG2p\n", "from nemo.collections.tts.torch.data import TTSDataset\n", "from nemo_text_processing.text_normalization.normalize import Normalizer\n", "from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import EnglishPhonemesTokenizer, EnglishCharsTokenizer" @@ -230,7 +230,7 @@ "!mkdir -p tts_dataset_files && cd tts_dataset_files \\\n", "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/cmudict-0.7b_nv22.10 \\\n", "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/heteronyms-052722 \\\n", - "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv \\\n", + "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/en/whitelist_lj_speech.tsv \\\n", "&& cd .." ] }, diff --git a/tutorials/tts/NeMo_TTS_Primer.ipynb b/tutorials/tts/NeMo_TTS_Primer.ipynb index a0e0b3f7097a..e323536fa56b 100644 --- a/tutorials/tts/NeMo_TTS_Primer.ipynb +++ b/tutorials/tts/NeMo_TTS_Primer.ipynb @@ -2072,4 +2072,4 @@ }, "nbformat": 4, "nbformat_minor": 1 -} \ No newline at end of file +} diff --git a/tutorials/tts/Pronunciation_customization.ipynb b/tutorials/tts/Pronunciation_customization.ipynb index f6ae09f7aa8a..14269ce33455 100644 --- a/tutorials/tts/Pronunciation_customization.ipynb +++ b/tutorials/tts/Pronunciation_customization.ipynb @@ -85,7 +85,7 @@ "source": [ "import os\n", "import nemo.collections.tts as nemo_tts\n", - "from nemo_text_processing.g2p.modules import IPAG2P\n", + "from nemo.collections.tts.g2p.modules import IPAG2P\n", "import soundfile as sf\n", "import IPython.display as ipd\n", "import torch\n", diff --git a/tutorials/tts/Tacotron2_Training.ipynb b/tutorials/tts/Tacotron2_Training.ipynb index 3642a3e9e4dc..28ca250a8b58 100644 --- a/tutorials/tts/Tacotron2_Training.ipynb +++ b/tutorials/tts/Tacotron2_Training.ipynb @@ -171,7 +171,7 @@ " \n", "!(mkdir -p nemo_text_processing/text_normalization/en/data/whitelist/ \\\n", " && cd nemo_text_processing/text_normalization/en/data/whitelist/ \\\n", - " && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv \\\n", + " && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/en/whitelist_lj_speech.tsv \\\n", " && cd ..)" ] }, @@ -235,7 +235,7 @@ "\n", "phoneme_dict_path: \"scripts/tts_dataset_files/cmudict-0.7b_nv22.10\"\n", "heteronyms_path: \"scripts/tts_dataset_files/heteronyms-052722\"\n", - "whitelist_path: \"nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv\"\n", + "whitelist_path: \"scripts/tts_dataset_files/en/whitelist_lj_speech.tsv\"\n", "```\n", "\n", "The first part of the yaml defines dataset parameters used by Tacotron. Then in the head of 'model' section there are processing - related parameters. You can see\n", From dec4c0bc4b36f123d8aa889d5ff19eb4557ced90 Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 12:35:13 -0800 Subject: [PATCH 04/19] fix import Signed-off-by: ekmb --- nemo/collections/tts/__init__.py | 1 + 1 file changed, 1 insertion(+) diff --git a/nemo/collections/tts/__init__.py b/nemo/collections/tts/__init__.py index 2370d83948ce..75b3b35a8ad4 100644 --- a/nemo/collections/tts/__init__.py +++ b/nemo/collections/tts/__init__.py @@ -14,3 +14,4 @@ import nemo.collections.tts.helpers import nemo.collections.tts.models +import nemo.collections.tts.g2p From 48683abd6383531dbd3e3f675dc3b7eebff521f6 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 10 Feb 2023 20:36:50 +0000 Subject: [PATCH 05/19] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- nemo/collections/tts/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nemo/collections/tts/__init__.py b/nemo/collections/tts/__init__.py index 75b3b35a8ad4..d122a46d2a02 100644 --- a/nemo/collections/tts/__init__.py +++ b/nemo/collections/tts/__init__.py @@ -12,6 +12,6 @@ # See the License for the specific language governing permissions and # limitations under the License. +import nemo.collections.tts.g2p import nemo.collections.tts.helpers import nemo.collections.tts.models -import nemo.collections.tts.g2p From 09e881fed74709b31d78cd28e77023defdc431e3 Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 13:13:54 -0800 Subject: [PATCH 06/19] add missing init Signed-off-by: ekmb --- nemo/collections/tts/g2p/__init__.py | 13 +++++++++++++ 1 file changed, 13 insertions(+) create mode 100644 nemo/collections/tts/g2p/__init__.py diff --git a/nemo/collections/tts/g2p/__init__.py b/nemo/collections/tts/g2p/__init__.py new file mode 100644 index 000000000000..a1cf281f0908 --- /dev/null +++ b/nemo/collections/tts/g2p/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. From 71b061668c85b64db5e02ce6d4c29d886dc71f8a Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 13:15:55 -0800 Subject: [PATCH 07/19] fix import Signed-off-by: ekmb --- nemo/collections/tts/g2p/data/__init__.py | 1 + 1 file changed, 1 insertion(+) diff --git a/nemo/collections/tts/g2p/data/__init__.py b/nemo/collections/tts/g2p/data/__init__.py index 5857cda3f17b..1162dacc7031 100644 --- a/nemo/collections/tts/g2p/data/__init__.py +++ b/nemo/collections/tts/g2p/data/__init__.py @@ -13,5 +13,6 @@ # limitations under the License. from nemo.collections.tts.g2p.data.t5_g2p import T5G2PDataset +from nemo.collections.tts.g2p.data.ctc_g2p import CTCG2PBPEDataset __all__ = ["T5G2PDataset", "CTCG2PBPEDataset"] From 1fc2f822798a41cf686e80dfb649c4fa48bc9475 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 10 Feb 2023 21:17:02 +0000 Subject: [PATCH 08/19] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- nemo/collections/tts/g2p/data/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nemo/collections/tts/g2p/data/__init__.py b/nemo/collections/tts/g2p/data/__init__.py index 1162dacc7031..d74b1a7ebee6 100644 --- a/nemo/collections/tts/g2p/data/__init__.py +++ b/nemo/collections/tts/g2p/data/__init__.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -from nemo.collections.tts.g2p.data.t5_g2p import T5G2PDataset from nemo.collections.tts.g2p.data.ctc_g2p import CTCG2PBPEDataset +from nemo.collections.tts.g2p.data.t5_g2p import T5G2PDataset __all__ = ["T5G2PDataset", "CTCG2PBPEDataset"] From 0399299108dcf5c5b3a2ec3ade0a02893fea3af1 Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 15:15:09 -0800 Subject: [PATCH 09/19] rename unit test Signed-off-by: ekmb --- .../tts/g2p/data/{test_data_utils.py => test_g2p_data_utils.py} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename tests/collections/tts/g2p/data/{test_data_utils.py => test_g2p_data_utils.py} (100%) diff --git a/tests/collections/tts/g2p/data/test_data_utils.py b/tests/collections/tts/g2p/data/test_g2p_data_utils.py similarity index 100% rename from tests/collections/tts/g2p/data/test_data_utils.py rename to tests/collections/tts/g2p/data/test_g2p_data_utils.py From fcc8f08e24936c029222b24ca513aebc3e13fadd Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 22:10:22 -0800 Subject: [PATCH 10/19] fix import Signed-off-by: ekmb --- examples/tts/conf/rad-tts_dec.yaml | 2 +- examples/tts/conf/rad-tts_dec_ipa.yaml | 8 ++++---- examples/tts/conf/rad-tts_feature_pred.yaml | 2 +- examples/tts/conf/rad-tts_feature_pred_ipa.yaml | 8 ++++---- nemo/collections/tts/torch/g2ps.py | 1 + 5 files changed, 11 insertions(+), 10 deletions(-) diff --git a/examples/tts/conf/rad-tts_dec.yaml b/examples/tts/conf/rad-tts_dec.yaml index 7e676e7985da..6192d1538399 100644 --- a/examples/tts/conf/rad-tts_dec.yaml +++ b/examples/tts/conf/rad-tts_dec.yaml @@ -8,7 +8,7 @@ export_dir: ??? sup_data_path: ??? sup_data_types: ["log_mel", "align_prior_matrix", "pitch", "voiced_mask", "p_voiced", "energy"] -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv" +whitelist_path: null # https://github.com/NVIDIA/NeMo-text-processing/blob/main/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv default will be used # these frame-wise values depend on pitch_fmin and pitch_fmax, you can get values # by running `scripts/dataset_processing/tts/extract_sup_data.py` diff --git a/examples/tts/conf/rad-tts_dec_ipa.yaml b/examples/tts/conf/rad-tts_dec_ipa.yaml index b251537daad8..f135eb713b1c 100644 --- a/examples/tts/conf/rad-tts_dec_ipa.yaml +++ b/examples/tts/conf/rad-tts_dec_ipa.yaml @@ -31,7 +31,7 @@ window: "hann" phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" mapping_file_path: "" model: @@ -62,7 +62,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 @@ -106,7 +106,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 @@ -150,7 +150,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 diff --git a/examples/tts/conf/rad-tts_feature_pred.yaml b/examples/tts/conf/rad-tts_feature_pred.yaml index 9aee2d4a6264..58c7481f0674 100644 --- a/examples/tts/conf/rad-tts_feature_pred.yaml +++ b/examples/tts/conf/rad-tts_feature_pred.yaml @@ -8,7 +8,7 @@ export_dir: ??? sup_data_path: ??? sup_data_types: ["log_mel", "align_prior_matrix", "pitch", "voiced_mask", "p_voiced", "energy"] -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv" +whitelist_path: null # default https://github.com/NVIDIA/NeMo-text-processing/blob/main/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv will be used # these frame-wise values depend on pitch_fmin and pitch_fmax, you can get values # by running `scripts/dataset_processing/tts/extract_sup_data.py` diff --git a/examples/tts/conf/rad-tts_feature_pred_ipa.yaml b/examples/tts/conf/rad-tts_feature_pred_ipa.yaml index cf36d7ad9506..9e0615b1f81b 100644 --- a/examples/tts/conf/rad-tts_feature_pred_ipa.yaml +++ b/examples/tts/conf/rad-tts_feature_pred_ipa.yaml @@ -29,7 +29,7 @@ window: "hann" phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "nemo_text_processing/text_normalization/en/data/whitelist/lj_speech.tsv" +whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" mapping_file_path: "" model: @@ -60,7 +60,7 @@ model: apostrophe: true pad_with_space: true g2p: - _target_: nemo_text_processing.g2p.modules.IPAG2P + _target_: nemo.collections.tts.g2p.modules.IPAG2P phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 @@ -104,7 +104,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 @@ -148,7 +148,7 @@ model: add_blank_at: null pad_with_space: True g2p: - _target_: "nemo_text_processing.g2p.modules.EnglishG2p" + _target_: "nemo.collections.tts.g2p.modules.EnglishG2p" phoneme_dict: ${phoneme_dict_path} heteronyms: ${heteronyms_path} phoneme_probability: 0.5 diff --git a/nemo/collections/tts/torch/g2ps.py b/nemo/collections/tts/torch/g2ps.py index e6347a0657a9..4bdbde5e6380 100644 --- a/nemo/collections/tts/torch/g2ps.py +++ b/nemo/collections/tts/torch/g2ps.py @@ -14,3 +14,4 @@ # TODO @xueyang: deprecate this file since no other places import modules from here anymore. However, # all checkpoints uploaded in ngc used this path. So it requires to update all ngc checkpoints g2p path as well. +from nemo.collections.tts.g2p.modules import IPAG2P, BaseG2p, EnglishG2p From 6bcdbf1bc1d5c2071438e14ecb5eee4189d45f60 Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 22:47:43 -0800 Subject: [PATCH 11/19] fix modules test Signed-off-by: ekmb --- tests/collections/tts/g2p/test_modules.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/collections/tts/g2p/test_modules.py b/tests/collections/tts/g2p/test_modules.py index 196239c65f7f..dd2a1812fad2 100644 --- a/tests/collections/tts/g2p/test_modules.py +++ b/tests/collections/tts/g2p/test_modules.py @@ -325,7 +325,7 @@ def test_forward_call_en_us(self): expected_output_mixed = ( [char for char in "həˈɫoʊ ɛnˈvɪdiəz ˈɛɹˌpɔɹts ˈdʒoʊnzɪz ˈɛɹˌpɔɹts ˈwɝɫdz"] + [" "] - + [f"{self.GRAPHEME_PREFIX}{char}" for char in "Kitty"] + + [f"{self.GRAPHEME_PREFIX}{char}" for char in "kitty"] + ["!"] ) From bfead4bcad9848f38c6278a4080324baf71faaba Mon Sep 17 00:00:00 2001 From: ekmb Date: Fri, 10 Feb 2023 23:38:23 -0800 Subject: [PATCH 12/19] fix imports Signed-off-by: ekmb --- examples/tts/g2p/conf/g2p_conformer_ctc.yaml | 4 ++-- examples/tts/g2p/conf/heteronym_classification.yaml | 6 +++--- examples/tts/g2p/conf/t5_g2p.yaml | 6 +++--- examples/tts/g2p/g2p_inference.py | 2 +- examples/tts/g2p/g2p_train_and_evaluate.py | 2 +- 5 files changed, 10 insertions(+), 10 deletions(-) diff --git a/examples/tts/g2p/conf/g2p_conformer_ctc.yaml b/examples/tts/g2p/conf/g2p_conformer_ctc.yaml index d1c4b0b9ae9f..10e3ac3ec3d1 100644 --- a/examples/tts/g2p/conf/g2p_conformer_ctc.yaml +++ b/examples/tts/g2p/conf/g2p_conformer_ctc.yaml @@ -69,7 +69,7 @@ model: train_ds: manifest_filepath: ${train_manifest} dataset: - _target_: "nemo.tts.g2p.data.ctc_g2p.CTCG2PBPEDataset" + _target_: "nemo.collections.tts.g2p.data.ctc_g2p.CTCG2PBPEDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: @@ -81,7 +81,7 @@ model: validation_ds: manifest_filepath: ${validation_manifest} dataset: - _target_: "nemo.tts.g2p.data.ctc_g2p.CTCG2PBPEDataset" + _target_: "nemo.collections.tts.g2p.data.ctc_g2p.CTCG2PBPEDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: diff --git a/examples/tts/g2p/conf/heteronym_classification.yaml b/examples/tts/g2p/conf/heteronym_classification.yaml index 89c2899230de..aae427a36597 100644 --- a/examples/tts/g2p/conf/heteronym_classification.yaml +++ b/examples/tts/g2p/conf/heteronym_classification.yaml @@ -35,7 +35,7 @@ model: train_ds: dataset: - _target_: "nemo.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" + _target_: "nemo.collections.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" manifest: ${train_manifest} grapheme_field: "text_graphemes" # name of the field in manifest for input grapheme text dataloader_params: @@ -46,7 +46,7 @@ model: validation_ds: dataset: - _target_: "nemo.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" + _target_: "nemo.collections.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" manifest: ${validation_manifest} grapheme_field: "text_graphemes" # name of the field in manifest for input grapheme text dataloader_params: @@ -57,7 +57,7 @@ model: test_ds: dataset: - _target_: "nemo.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" + _target_: "nemo.collections.tts.g2p.data.heteronym_classification_data.HeteronymClassificationDataset" manifest: ${test_manifest} grapheme_field: "text_graphemes" # name of the field in manifest for input grapheme text dataloader_params: diff --git a/examples/tts/g2p/conf/t5_g2p.yaml b/examples/tts/g2p/conf/t5_g2p.yaml index 24eca43ce12f..9b4929656666 100644 --- a/examples/tts/g2p/conf/t5_g2p.yaml +++ b/examples/tts/g2p/conf/t5_g2p.yaml @@ -17,7 +17,7 @@ model: train_ds: manifest_filepath: ${train_manifest} dataset: - _target_: "nemo.tts.g2p.data.t5_g2p.T5G2PDataset" + _target_: "nemo.collections.tts.g2p.data.t5_g2p.T5G2PDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: @@ -29,7 +29,7 @@ model: validation_ds: manifest_filepath: ${validation_manifest} dataset: - _target_: "nemo.tts.g2p.data.t5_g2p.T5G2PDataset" + _target_: "nemo.collections.tts.g2p.data.t5_g2p.T5G2PDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: @@ -41,7 +41,7 @@ model: test_ds: manifest_filepath: ${test_manifest} dataset: - _target_: "nemo.tts.g2p.data.t5_g2p.T5G2PDataset" + _target_: "nemo.collections.tts.g2p.data.t5_g2p.T5G2PDataset" phoneme_field: "text" # name of the field in manifest_filepath for ground truth phonemes grapheme_field: "text_graphemes" # name of the field in manifest_filepath for input grapheme text dataloader_params: diff --git a/examples/tts/g2p/g2p_inference.py b/examples/tts/g2p/g2p_inference.py index a178e474c7f8..4b8f48ef1319 100644 --- a/examples/tts/g2p/g2p_inference.py +++ b/examples/tts/g2p/g2p_inference.py @@ -21,7 +21,7 @@ from omegaconf import OmegaConf from utils import get_metrics -from nemo.collections.tts.g2p.models import G2PModel +from nemo.collections.tts.g2p.models.g2p_model import G2PModel from nemo.core.config import hydra_runner from nemo.utils import logging diff --git a/examples/tts/g2p/g2p_train_and_evaluate.py b/examples/tts/g2p/g2p_train_and_evaluate.py index 3627681ffe15..e2edef695180 100644 --- a/examples/tts/g2p/g2p_train_and_evaluate.py +++ b/examples/tts/g2p/g2p_train_and_evaluate.py @@ -19,7 +19,7 @@ from utils import get_model from nemo.collections.common.callbacks import LogEpochTimeCallback -from nemo.collections.tts.g2p.models import G2PModel +from nemo.collections.tts.g2p.models.g2p_model import G2PModel from nemo.core.config import hydra_runner from nemo.utils import logging, model_utils from nemo.utils.exp_manager import exp_manager From be645ed9be823919552e43821d2d4c827ae5c282 Mon Sep 17 00:00:00 2001 From: ekmb Date: Tue, 14 Feb 2023 17:35:26 -0800 Subject: [PATCH 13/19] remove whitelist from config Signed-off-by: ekmb --- docs/source/tts/configs.rst | 1 - docs/source/tts/datasets.rst | 4 +--- examples/tts/conf/aligner.yaml | 2 -- .../de/fastpitch_align_22050_grapheme.yaml | 3 --- .../conf/de/fastpitch_align_22050_mix.yaml | 2 -- .../de/fastpitch_align_44100_grapheme.yaml | 3 --- .../de/fastpitch_align_44100_phoneme.yaml | 3 --- examples/tts/conf/fastpitch_align_44100.yaml | 2 -- examples/tts/conf/fastpitch_align_ipa.yaml | 2 -- examples/tts/conf/fastpitch_align_v1.05.yaml | 2 -- examples/tts/conf/mixer-tts-x.yaml | 3 --- examples/tts/conf/mixer-tts.yaml | 2 -- examples/tts/conf/rad-tts_dec.yaml | 3 --- examples/tts/conf/rad-tts_dec_ipa.yaml | 2 -- examples/tts/conf/rad-tts_feature_pred.yaml | 3 --- .../tts/conf/rad-tts_feature_pred_ipa.yaml | 2 -- examples/tts/conf/tacotron2.yaml | 2 -- examples/tts/conf/vits.yaml | 2 -- examples/tts/conf/vits_44100.yaml | 2 -- .../tts/conf/zh/fastpitch_align_22050.yaml | 2 -- nemo/collections/tts/torch/tts_dataset.yaml | 1 - .../ds_conf/ds_for_fastpitch_align.yaml | 2 -- .../ds_conf/ds_for_fastpitch_align.yaml | 2 -- .../ljspeech/ds_conf/ds_for_mixer_tts.yaml | 2 -- .../ljspeech/ds_conf/ds_for_mixer_tts_x.yaml | 2 -- .../tts/ljspeech/get_data.py | 2 +- .../tts/ljspeech/lj_speech.tsv | 21 +++++++++++++++++++ .../ds_conf/ds_for_fastpitch_align.yaml | 2 -- .../ds_conf/ds_for_fastpitch_align.yaml | 2 -- .../tts/FastPitch_ChineseTTS_Training.ipynb | 8 +------ tutorials/tts/FastPitch_Finetuning.ipynb | 5 +---- .../tts/FastPitch_GermanTTS_Training.ipynb | 10 +-------- .../tts/FastPitch_MixerTTS_Training.ipynb | 5 ----- tutorials/tts/Tacotron2_Training.ipynb | 6 ------ 34 files changed, 26 insertions(+), 91 deletions(-) create mode 100644 scripts/dataset_processing/tts/ljspeech/lj_speech.tsv diff --git a/docs/source/tts/configs.rst b/docs/source/tts/configs.rst index cecaee29673a..38e1629c0a68 100644 --- a/docs/source/tts/configs.rst +++ b/docs/source/tts/configs.rst @@ -96,7 +96,6 @@ Text normalization (TN) converts text from written form into its verbalized form _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" text_normalizer_call_kwargs: verbose: false diff --git a/docs/source/tts/datasets.rst b/docs/source/tts/datasets.rst index 4b2e96baedb6..62d5c2f3ec17 100644 --- a/docs/source/tts/datasets.rst +++ b/docs/source/tts/datasets.rst @@ -45,9 +45,7 @@ LJSpeech .. code-block:: shell-session $ python scripts/dataset_processing/tts/ljspeech/get_data.py \ - --data-root \ - --whitelist-path \ - or default scripts/tts_dataset_files/en/whitelist_lj_speech.tsv + --data-root $ python scripts/dataset_processing/tts/extract_sup_data.py \ --config-path ljspeech/ds_conf \ diff --git a/examples/tts/conf/aligner.yaml b/examples/tts/conf/aligner.yaml index e0008e65fe4b..4fd64e823118 100644 --- a/examples/tts/conf/aligner.yaml +++ b/examples/tts/conf/aligner.yaml @@ -21,7 +21,6 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: symbols_embedding_dim: 384 @@ -41,7 +40,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/de/fastpitch_align_22050_grapheme.yaml b/examples/tts/conf/de/fastpitch_align_22050_grapheme.yaml index 3217f976347d..85ad6a1e5cc2 100644 --- a/examples/tts/conf/de/fastpitch_align_22050_grapheme.yaml +++ b/examples/tts/conf/de/fastpitch_align_22050_grapheme.yaml @@ -28,8 +28,6 @@ lowfreq: 0 highfreq: null window: hann -whitelist_path: "nemo_text_processing/text_normalization/de/data/whitelist.tsv" - model: learn_alignment: true bin_loss_warmup_epochs: 100 @@ -58,7 +56,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: de input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/de/fastpitch_align_22050_mix.yaml b/examples/tts/conf/de/fastpitch_align_22050_mix.yaml index ddd25d07bb38..d7fabcb4de5a 100644 --- a/examples/tts/conf/de/fastpitch_align_22050_mix.yaml +++ b/examples/tts/conf/de/fastpitch_align_22050_mix.yaml @@ -30,7 +30,6 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/de/de_nv230119.dict" heteronyms_path: "scripts/tts_dataset_files/de/de_nv230119.heteronyms" -whitelist_path: "nemo_text_processing/text_normalization/de/data/whitelist.tsv" model: learn_alignment: true @@ -60,7 +59,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: de input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/de/fastpitch_align_44100_grapheme.yaml b/examples/tts/conf/de/fastpitch_align_44100_grapheme.yaml index 5395ccb57080..57bc8ffedf4b 100644 --- a/examples/tts/conf/de/fastpitch_align_44100_grapheme.yaml +++ b/examples/tts/conf/de/fastpitch_align_44100_grapheme.yaml @@ -28,8 +28,6 @@ lowfreq: 0 highfreq: null window: hann -whitelist_path: "nemo_text_processing/text_normalization/de/data/whitelist.tsv" - model: learn_alignment: true bin_loss_warmup_epochs: 100 @@ -58,7 +56,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: de input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/de/fastpitch_align_44100_phoneme.yaml b/examples/tts/conf/de/fastpitch_align_44100_phoneme.yaml index 832a37505ca4..2dc66ce69231 100644 --- a/examples/tts/conf/de/fastpitch_align_44100_phoneme.yaml +++ b/examples/tts/conf/de/fastpitch_align_44100_phoneme.yaml @@ -28,8 +28,6 @@ lowfreq: 0 highfreq: null window: hann -whitelist_path: "nemo_text_processing/text_normalization/de/data/whitelist.tsv" - model: learn_alignment: true bin_loss_warmup_epochs: 100 @@ -58,7 +56,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: de input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/fastpitch_align_44100.yaml b/examples/tts/conf/fastpitch_align_44100.yaml index 29ef03109ef6..aa1845c5498d 100644 --- a/examples/tts/conf/fastpitch_align_44100.yaml +++ b/examples/tts/conf/fastpitch_align_44100.yaml @@ -29,7 +29,6 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: learn_alignment: true @@ -59,7 +58,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/fastpitch_align_ipa.yaml b/examples/tts/conf/fastpitch_align_ipa.yaml index d1a55d909e1e..639a332c2a41 100644 --- a/examples/tts/conf/fastpitch_align_ipa.yaml +++ b/examples/tts/conf/fastpitch_align_ipa.yaml @@ -30,7 +30,6 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: learn_alignment: true @@ -60,7 +59,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/fastpitch_align_v1.05.yaml b/examples/tts/conf/fastpitch_align_v1.05.yaml index aa31b52fd5ec..7e14bbf53ee9 100644 --- a/examples/tts/conf/fastpitch_align_v1.05.yaml +++ b/examples/tts/conf/fastpitch_align_v1.05.yaml @@ -30,7 +30,6 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: learn_alignment: true @@ -60,7 +59,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/mixer-tts-x.yaml b/examples/tts/conf/mixer-tts-x.yaml index 5f55dc02a095..be0f3449f28d 100644 --- a/examples/tts/conf/mixer-tts-x.yaml +++ b/examples/tts/conf/mixer-tts-x.yaml @@ -30,8 +30,6 @@ window: hann lm_model: albert -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" - model: bin_loss_start_ratio: 0.2 bin_loss_warmup_epochs: 100 @@ -63,7 +61,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/mixer-tts.yaml b/examples/tts/conf/mixer-tts.yaml index 7668b9d5bf96..510993cd1761 100644 --- a/examples/tts/conf/mixer-tts.yaml +++ b/examples/tts/conf/mixer-tts.yaml @@ -30,7 +30,6 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: bin_loss_start_ratio: 0.2 @@ -61,7 +60,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/rad-tts_dec.yaml b/examples/tts/conf/rad-tts_dec.yaml index 6192d1538399..f15d4209e938 100644 --- a/examples/tts/conf/rad-tts_dec.yaml +++ b/examples/tts/conf/rad-tts_dec.yaml @@ -8,8 +8,6 @@ export_dir: ??? sup_data_path: ??? sup_data_types: ["log_mel", "align_prior_matrix", "pitch", "voiced_mask", "p_voiced", "energy"] -whitelist_path: null # https://github.com/NVIDIA/NeMo-text-processing/blob/main/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv default will be used - # these frame-wise values depend on pitch_fmin and pitch_fmax, you can get values # by running `scripts/dataset_processing/tts/extract_sup_data.py` pitch_mean: ??? # e.g. 212.35873413085938 for LJSpeech @@ -48,7 +46,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/rad-tts_dec_ipa.yaml b/examples/tts/conf/rad-tts_dec_ipa.yaml index f135eb713b1c..83e2f3c41950 100644 --- a/examples/tts/conf/rad-tts_dec_ipa.yaml +++ b/examples/tts/conf/rad-tts_dec_ipa.yaml @@ -31,7 +31,6 @@ window: "hann" phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" mapping_file_path: "" model: @@ -49,7 +48,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/rad-tts_feature_pred.yaml b/examples/tts/conf/rad-tts_feature_pred.yaml index 58c7481f0674..2e5c9fa2b492 100644 --- a/examples/tts/conf/rad-tts_feature_pred.yaml +++ b/examples/tts/conf/rad-tts_feature_pred.yaml @@ -8,8 +8,6 @@ export_dir: ??? sup_data_path: ??? sup_data_types: ["log_mel", "align_prior_matrix", "pitch", "voiced_mask", "p_voiced", "energy"] -whitelist_path: null # default https://github.com/NVIDIA/NeMo-text-processing/blob/main/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv will be used - # these frame-wise values depend on pitch_fmin and pitch_fmax, you can get values # by running `scripts/dataset_processing/tts/extract_sup_data.py` pitch_mean: ??? # e.g. 212.35873413085938 for LJSpeech @@ -47,7 +45,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/rad-tts_feature_pred_ipa.yaml b/examples/tts/conf/rad-tts_feature_pred_ipa.yaml index 9e0615b1f81b..2e8e44b2e06e 100644 --- a/examples/tts/conf/rad-tts_feature_pred_ipa.yaml +++ b/examples/tts/conf/rad-tts_feature_pred_ipa.yaml @@ -29,7 +29,6 @@ window: "hann" phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" mapping_file_path: "" model: @@ -47,7 +46,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/tacotron2.yaml b/examples/tts/conf/tacotron2.yaml index 4d30f25e4ae3..cece80d54b25 100644 --- a/examples/tts/conf/tacotron2.yaml +++ b/examples/tts/conf/tacotron2.yaml @@ -11,7 +11,6 @@ sup_data_types: null phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: pitch_fmin: 65.40639132514966 @@ -31,7 +30,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/vits.yaml b/examples/tts/conf/vits.yaml index 64b1cf6ff12d..de0db6ef21cd 100644 --- a/examples/tts/conf/vits.yaml +++ b/examples/tts/conf/vits.yaml @@ -13,7 +13,6 @@ sup_data_types: null phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" # Default values from librosa.pyin pitch_fmin: 65.40639132514966 @@ -53,7 +52,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/vits_44100.yaml b/examples/tts/conf/vits_44100.yaml index d666ae31f048..b1d645a0c143 100644 --- a/examples/tts/conf/vits_44100.yaml +++ b/examples/tts/conf/vits_44100.yaml @@ -23,7 +23,6 @@ window: hann phoneme_dict_path: "scripts/tts_dataset_files/ipa_cmudict-0.7b_nv22.10.txt" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" model: n_speakers: 13000 @@ -48,7 +47,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/examples/tts/conf/zh/fastpitch_align_22050.yaml b/examples/tts/conf/zh/fastpitch_align_22050.yaml index c5275ba44fb8..f1c491a3a4c3 100644 --- a/examples/tts/conf/zh/fastpitch_align_22050.yaml +++ b/examples/tts/conf/zh/fastpitch_align_22050.yaml @@ -28,7 +28,6 @@ lowfreq: 0 highfreq: null window: hann -whitelist_path: "nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv" phoneme_dict_path: "scripts/tts_dataset_files/zh/pinyin_dict_nv_22.10.txt" model: @@ -59,7 +58,6 @@ model: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: zh input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/nemo/collections/tts/torch/tts_dataset.yaml b/nemo/collections/tts/torch/tts_dataset.yaml index 2ca29630910e..3fc2798efeea 100644 --- a/nemo/collections/tts/torch/tts_dataset.yaml +++ b/nemo/collections/tts/torch/tts_dataset.yaml @@ -22,7 +22,6 @@ tts_dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" text_normalizer_call_kwargs: verbose: False diff --git a/scripts/dataset_processing/tts/hui_acg/ds_conf/ds_for_fastpitch_align.yaml b/scripts/dataset_processing/tts/hui_acg/ds_conf/ds_for_fastpitch_align.yaml index ab3717edf926..25db823926d1 100644 --- a/scripts/dataset_processing/tts/hui_acg/ds_conf/ds_for_fastpitch_align.yaml +++ b/scripts/dataset_processing/tts/hui_acg/ds_conf/ds_for_fastpitch_align.yaml @@ -3,7 +3,6 @@ name: "ds_for_fastpitch_align" manifest_filepath: ??? sup_data_path: ??? sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: "nemo_text_processing/text_normalization/de/data/whitelist.tsv" dataset: _target_: nemo.collections.tts.torch.data.TTSDataset @@ -30,7 +29,6 @@ dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: de input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml index 8e66cb3497aa..28a2550c69a1 100644 --- a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml +++ b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_fastpitch_align.yaml @@ -3,7 +3,6 @@ name: "ds_for_fastpitch_align" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" @@ -31,7 +30,6 @@ dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml index bfec225353d3..f902937371ad 100644 --- a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml +++ b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts.yaml @@ -3,7 +3,6 @@ name: "ds_for_mixer_tts" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" phoneme_dict_path: "scripts/tts_dataset_files/cmudict-0.7b_nv22.10" heteronyms_path: "scripts/tts_dataset_files/heteronyms-052722" @@ -31,7 +30,6 @@ dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml index 89cf74f6b7de..242c8a61360a 100644 --- a/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml +++ b/scripts/dataset_processing/tts/ljspeech/ds_conf/ds_for_mixer_tts_x.yaml @@ -3,7 +3,6 @@ name: "ds_for_mixer_tts_x" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch", "lm_tokens" ] -whitelist_path: "scripts/tts_dataset_files/en/whitelist_lj_speech.tsv" dataset: _target_: nemo.collections.tts.torch.data.MixerTTSXDataset @@ -30,7 +29,6 @@ dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: en input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/scripts/dataset_processing/tts/ljspeech/get_data.py b/scripts/dataset_processing/tts/ljspeech/get_data.py index 0d933f8a29ca..733f9b76b354 100644 --- a/scripts/dataset_processing/tts/ljspeech/get_data.py +++ b/scripts/dataset_processing/tts/ljspeech/get_data.py @@ -27,7 +27,7 @@ def get_args(): parser = argparse.ArgumentParser(description='Download LJSpeech and create manifests with predefined split') parser.add_argument("--data-root", required=True, type=Path) - parser.add_argument('--whitelist-path', type=str, default=None) + parser.add_argument('--whitelist-path', type=str, default="lj_speech.tsv") args = parser.parse_args() return args diff --git a/scripts/dataset_processing/tts/ljspeech/lj_speech.tsv b/scripts/dataset_processing/tts/ljspeech/lj_speech.tsv new file mode 100644 index 000000000000..a55a04b9ab68 --- /dev/null +++ b/scripts/dataset_processing/tts/ljspeech/lj_speech.tsv @@ -0,0 +1,21 @@ +Mr. mister +Mrs. misses +Dr. doctor +Drs. doctors +Co. company +Lt. lieutenant +Sgt. sergeant +St. saint +Jr. junior +Maj. major +Hon. honorable +Gov. governor +Capt. captain +Esq. esquire +Gen. general +Ltd. limited +Rev. reverend +Col. colonel +Mt. mount +Ft. fort +etc. et cetera diff --git a/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml b/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml index f675e49954f0..46bb35b66c08 100755 --- a/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml +++ b/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml @@ -3,7 +3,6 @@ name: "ds_for_fastpitch_align" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: null # default whitelist will be used from https://raw.githubusercontent.com/NVIDIA/NeMo-text-processing/main/nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv phoneme_dict_path: "scripts/tts_dataset_files/zh/pinyin_dict_nv_22.10.txt" dataset: @@ -33,7 +32,6 @@ dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: zh input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/scripts/dataset_processing/tts/thorsten_neutral/ds_conf/ds_for_fastpitch_align.yaml b/scripts/dataset_processing/tts/thorsten_neutral/ds_conf/ds_for_fastpitch_align.yaml index 709a212395b9..48f4f6b2a530 100644 --- a/scripts/dataset_processing/tts/thorsten_neutral/ds_conf/ds_for_fastpitch_align.yaml +++ b/scripts/dataset_processing/tts/thorsten_neutral/ds_conf/ds_for_fastpitch_align.yaml @@ -3,7 +3,6 @@ name: "ds_for_fastpitch_align" manifest_filepath: "train_manifest.json" sup_data_path: "sup_data" sup_data_types: [ "align_prior_matrix", "pitch" ] -whitelist_path: "nemo_text_processing/text_normalization/de/data/whitelist.tsv" dataset: _target_: nemo.collections.tts.torch.data.TTSDataset @@ -32,7 +31,6 @@ dataset: _target_: nemo_text_processing.text_normalization.normalize.Normalizer lang: de input_case: cased - whitelist: ${whitelist_path} text_normalizer_call_kwargs: verbose: false diff --git a/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb b/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb index 0542a006ed91..5735017ea64d 100644 --- a/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb @@ -95,7 +95,6 @@ "!cd NeMoChineseTTS && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/scripts/dataset_processing/tts/sfbilingual/ds_conf/ds_for_fastpitch_align.yaml\n", "!cd NeMoChineseTTS && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/examples/tts/conf/zh/fastpitch_align_22050.yaml\n", "!cd NeMoChineseTTS && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/examples/tts/conf/hifigan/hifigan.yaml\n", - "!cd NeMoChineseTTS && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv\n", "!cd NeMoChineseTTS && mkdir -p model/train_ds && cd model/train_ds && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/examples/tts/conf/hifigan/model/train_ds/train_ds_finetune.yaml\n", "!cd NeMoChineseTTS && mkdir -p model/validation_ds && cd model/validation_ds && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/examples/tts/conf/hifigan/model/validation_ds/val_ds_finetune.yaml\n", "!cd NeMoChineseTTS && mkdir -p model/generator && cd model/generator && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/examples/tts/conf/hifigan/model/generator/v1.yaml" @@ -382,8 +381,6 @@ "\n", "2. The `text_normalizer.lang` is set to `zh`, in order to use the tokenizer defined in `nemo_text_processing/text_normalization/zh` (as discussed above).\n", "\n", - "3. Update the `whitelist_path` to point to Chinese whitelist: `nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv`\n", - "\n", "Final config looks like:\n", "\n", "```yaml\n", @@ -392,7 +389,6 @@ "manifest_filepath: \"train_manifest.json\"\n", "sup_data_path: \"sup_data\"\n", "sup_data_types: [ \"align_prior_matrix\", \"pitch\" ]\n", - "whitelist_path: \"nemo_text_processing/text_normalization/zh/data/whitelist/default.tsv\"\n", "\n", "phoneme_dict_path: \"scripts/tts_dataset_files/zh/pinyin_dict.txt\"\n", "\n", @@ -420,7 +416,6 @@ " _target_: nemo_text_processing.text_normalization.normalize.Normalizer\n", " lang: zh\n", " input_case: cased\n", - " whitelist: ${whitelist_path}\n", "\n", " text_normalizer_call_kwargs:\n", " verbose: false\n", @@ -491,7 +486,7 @@ "metadata": {}, "source": [ "Before we train our model, let's define model config. Most of the model config stays the same as defined here: `examples/tts/conf/fastpitch_align_44100.yaml`, except:\n", - "1. Make the same changes that we made in dataset config for `text_tokenizer`, `text_normalizer` and `whitelist_path`.\n", + "1. Make the same changes that we made in dataset config for `text_tokenizer` and `text_normalizer`.\n", "\n", "2. The `pitch_mean` and `pitch_std` are updated to the values reported by the `extract_sup_data.py` script.\n", "\n", @@ -553,7 +548,6 @@ " train_dataset=./train_manifest.json \\\n", " validation_datasets=./val_manifest.json \\\n", " sup_data_path=./sup-data-phonemes \\\n", - " whitelist_path=./default.tsv \\\n", " exp_manager.exp_dir=resultChineseTTS \\\n", " trainer.max_epochs=1 \\\n", " trainer.check_val_every_n_epoch=1 \\\n", diff --git a/tutorials/tts/FastPitch_Finetuning.ipynb b/tutorials/tts/FastPitch_Finetuning.ipynb index fe607944c1e8..208f31841505 100755 --- a/tutorials/tts/FastPitch_Finetuning.ipynb +++ b/tutorials/tts/FastPitch_Finetuning.ipynb @@ -248,7 +248,6 @@ "!mkdir -p tts_dataset_files && cd tts_dataset_files \\\n", "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/cmudict-0.7b_nv22.10 \\\n", "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/heteronyms-052722 \\\n", - "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/nemo_text_processing/text_normalization/en/data/whitelist/tts.tsv \\\n", "&& cd .." ] }, @@ -290,7 +289,6 @@ " sup_data_path=./fastpitch_sup_data \\\n", " phoneme_dict_path=tts_dataset_files/cmudict-0.7b_nv22.10 \\\n", " heteronyms_path=tts_dataset_files/heteronyms-052722 \\\n", - " whitelist_path=tts_dataset_files/tts.tsv \\\n", " exp_manager.exp_dir=./ljspeech_to_9017_no_mixing_5_mins \\\n", " +init_from_nemo_model=./tts_en_fastpitch_align.nemo \\\n", " +trainer.max_steps=1000 ~trainer.max_epochs \\\n", @@ -322,9 +320,8 @@ " \n", "* `phoneme_dict_path=tts_dataset_files/cmudict-0.7b_nv22.10 \n", "heteronyms_path=tts_dataset_files/heteronyms-052722\n", - "whitelist_path=tts_dataset_files/tts.tsv \n", "`\n", - " * We tell the script where `phoneme_dict_path`, `heteronyms-052722` and `whitelist_path` are located. These are the additional files we downloaded earlier, and are used in preprocessing the data.\n", + " * We tell the script where `phoneme_dict_path` and `heteronyms-052722` are located. These are the additional files we downloaded earlier, and are used in preprocessing the data.\n", " \n", "* `exp_manager.exp_dir=./ljspeech_to_9017_no_mixing_5_mins`\n", " * Where we want to save our log files, tensorboard file, checkpoints, and more.\n", diff --git a/tutorials/tts/FastPitch_GermanTTS_Training.ipynb b/tutorials/tts/FastPitch_GermanTTS_Training.ipynb index 0b2e4f3fe132..05e8555c9f0a 100644 --- a/tutorials/tts/FastPitch_GermanTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_GermanTTS_Training.ipynb @@ -93,7 +93,6 @@ "!cd NeMoGermanTTS && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/scripts/dataset_processing/tts/extract_sup_data.py\n", "!cd NeMoGermanTTS && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/examples/tts/conf/de/fastpitch_align_22050.yaml\n", "!cd NeMoGermanTTS && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/examples/tts/conf/hifigan/hifigan.yaml\n", - "!cd NeMoGermanTTS && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/nemo_text_processing/text_normalization/de/data/whitelist.tsv\n", "!cd NeMoGermanTTS && mkdir -p model/train_ds && cd model/train_ds && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/examples/tts/conf/hifigan/model/train_ds/train_ds_finetune.yaml\n", "!cd NeMoGermanTTS && mkdir -p model/validation_ds && cd model/validation_ds && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/examples/tts/conf/hifigan/model/validation_ds/val_ds_finetune.yaml\n", "!cd NeMoGermanTTS && mkdir -p model/generator && cd model/generator && wget https://raw.githubusercontent.com/nvidia/NeMo/$BRANCH/examples/tts/conf/hifigan/model/generator/v1.yaml" @@ -446,8 +445,6 @@ "\n", "2. The `text_normalizer.lang` is set to `de`, in order to use the tokenizer defined in `nemo_text_processing/text_normalization/de` (as discussed above).\n", "\n", - "3. Update the `whitelist_path` to point to German whitelist: `nemo_text_processing/text_normalization/de/data/whitelist.tsv`\n", - "\n", "Final config looks like:\n", "\n", "```yaml\n", @@ -456,7 +453,6 @@ "manifest_filepath: \"train_manifest.json\"\n", "sup_data_path: \"sup_data\"\n", "sup_data_types: [ \"align_prior_matrix\", \"pitch\" ]\n", - "whitelist_path: \"NeMoGermanTTS/whitelist.tsv\"\n", "\n", "dataset:\n", " _target_: nemo.collections.tts.torch.data.TTSDataset\n", @@ -482,7 +478,6 @@ " _target_: nemo_text_processing.text_normalization.normalize.Normalizer\n", " lang: de\n", " input_case: cased\n", - " whitelist: ${whitelist_path}\n", "\n", " text_normalizer_call_kwargs:\n", " verbose: false\n", @@ -511,7 +506,6 @@ "manifest_filepath: \"train_manifest.json\"\n", "sup_data_path: \"sup_data\"\n", "sup_data_types: [ \"align_prior_matrix\", \"pitch\" ]\n", - "whitelist_path: \"NeMoGermanTTS/whitelist.tsv\"\n", "\n", "dataset:\n", " _target_: nemo.collections.tts.torch.data.TTSDataset\n", @@ -537,7 +531,6 @@ " _target_: nemo_text_processing.text_normalization.normalize.Normalizer\n", " lang: de\n", " input_case: cased\n", - " whitelist: ${whitelist_path}\n", "\n", " text_normalizer_call_kwargs:\n", " verbose: false\n", @@ -608,7 +601,7 @@ "metadata": {}, "source": [ "Before we train our model, let's define model config. Most of the model config stays the same as defined here: `examples/tts/conf/fastpitch_align_44100.yaml`, except:\n", - "1. Make the same changes that we made in dataset config for `text_tokenizer`, `text_normalizer` and `whitelist_path`.\n", + "1. Make the same changes that we made in dataset config for `text_tokenizer` and `text_normalizer`.\n", "\n", "2. The `pitch_mean` and `pitch_std` are updated to the values reported by the `extract_sup_data.py` script.\n", "\n", @@ -666,7 +659,6 @@ " train_dataset=../DataGermanTTS/thorsten-de/train_manifest_phonemes.json \\\n", " validation_datasets=../DataGermanTTS/thorsten-de/val_manifest_phonemes.json \\\n", " sup_data_path=../DataGermanTTS/thorsten-de/phonemes/ \\\n", - " whitelist_path=./whitelist.tsv \\\n", " exp_manager.exp_dir=resultGermanTTS \\\n", " trainer.max_epochs=1 \\\n", " trainer.check_val_every_n_epoch=1 \\\n", diff --git a/tutorials/tts/FastPitch_MixerTTS_Training.ipynb b/tutorials/tts/FastPitch_MixerTTS_Training.ipynb index 52d555faa934..05434c03e6d0 100644 --- a/tutorials/tts/FastPitch_MixerTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_MixerTTS_Training.ipynb @@ -230,7 +230,6 @@ "!mkdir -p tts_dataset_files && cd tts_dataset_files \\\n", "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/cmudict-0.7b_nv22.10 \\\n", "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/heteronyms-052722 \\\n", - "&& wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/en/whitelist_lj_speech.tsv \\\n", "&& cd .." ] }, @@ -281,7 +280,6 @@ "text_normalizer = Normalizer(\n", " lang=\"en\", \n", " input_case=\"cased\", \n", - " whitelist=\"tts_dataset_files/lj_speech.tsv\"\n", ")\n", "\n", "text_normalizer_call_kwargs = {\n", @@ -420,7 +418,6 @@ "text_normalizer = Normalizer(\n", " lang=\"en\", \n", " input_case=\"cased\", \n", - " whitelist=\"tts_dataset_files/lj_speech.tsv\"\n", ")\n", "\n", "text_normalizer_call_kwargs = {\n", @@ -501,7 +498,6 @@ " validation_datasets=tests/data/asr/an4_val.json \\\n", " sup_data_types=\"['align_prior_matrix', 'pitch']\" \\\n", " sup_data_path={fastpitch_sup_data_path} \\\n", - " whitelist_path=tts_dataset_files/lj_speech.tsv \\\n", " pitch_mean={pitch_mean} \\\n", " pitch_std={pitch_std} \\\n", " pitch_fmin={pitch_min} \\\n", @@ -558,7 +554,6 @@ "sup_data_path={mixer_tts_sup_data_path} \\\n", "phoneme_dict_path=tts_dataset_files/cmudict-0.7b_nv22.10 \\\n", "heteronyms_path=tts_dataset_files/heteronyms-052722 \\\n", - "whitelist_path=tts_dataset_files/lj_speech.tsv \\\n", "pitch_mean={pitch_mean} \\\n", "pitch_std={pitch_std} \\\n", "model.train_ds.dataloader_params.batch_size=6 \\\n", diff --git a/tutorials/tts/Tacotron2_Training.ipynb b/tutorials/tts/Tacotron2_Training.ipynb index 28ca250a8b58..a12cb980dc0b 100644 --- a/tutorials/tts/Tacotron2_Training.ipynb +++ b/tutorials/tts/Tacotron2_Training.ipynb @@ -168,11 +168,6 @@ " && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/cmudict-0.7b_nv22.10 \\\n", " && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/heteronyms-052722 \\\n", " && cd ..)\n", - " \n", - "!(mkdir -p nemo_text_processing/text_normalization/en/data/whitelist/ \\\n", - " && cd nemo_text_processing/text_normalization/en/data/whitelist/ \\\n", - " && wget https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/tts_dataset_files/en/whitelist_lj_speech.tsv \\\n", - " && cd ..)" ] }, { @@ -235,7 +230,6 @@ "\n", "phoneme_dict_path: \"scripts/tts_dataset_files/cmudict-0.7b_nv22.10\"\n", "heteronyms_path: \"scripts/tts_dataset_files/heteronyms-052722\"\n", - "whitelist_path: \"scripts/tts_dataset_files/en/whitelist_lj_speech.tsv\"\n", "```\n", "\n", "The first part of the yaml defines dataset parameters used by Tacotron. Then in the head of 'model' section there are processing - related parameters. You can see\n", From 6cbc570aed616ced51a1cd45b853fe7a65d621c3 Mon Sep 17 00:00:00 2001 From: ekmb Date: Tue, 14 Feb 2023 18:38:18 -0800 Subject: [PATCH 14/19] delete wordid file Signed-off-by: ekmb --- .../wordid_to_ipa-0.7b_nv22.10.tsv | 326 ------------------ 1 file changed, 326 deletions(-) delete mode 100644 scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv diff --git a/scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv b/scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv deleted file mode 100644 index d46ae401895a..000000000000 --- a/scripts/tts_dataset_files/wordid_to_ipa-0.7b_nv22.10.tsv +++ /dev/null @@ -1,326 +0,0 @@ -ABSTRACT_ADJ-NOU ˈæbˌstɹækt -ABSTRACT_VRB æbˈstɹækt -ABUSE_NOU əbˈjus -ABUSE_VRB əbˈjuz -ABUSES_NOU əbˈjusɪz -ABUSES_VRB əbˈjuzɪz -ADDICT_NOU ˈæˌdɪkt -ADDICT_VRB əˈdɪkt -ADVOCATE_NOU ˈædvəkət -ADVOCATE_VRB ˈædvəˌkeɪt -AFFECT_NOU-PSY ˈæˌfɛkt -AFFECT əˈfɛkt -AFFILIATE_NOU əˈfɪliət -AFFILIATE_VRB əˈfɪliˌeɪt -AGED_ADJ ˈeɪdʒɪd -AGED ˈeɪdʒd -AGGREGATE_ADJ-NOU ˈæɡɹəɡət -AGGREGATE_VRB ˈæɡɹəɡeɪt -ALTERNATE_ADJ-NOU ˈɔltɚnət -ALTERNATE_VRB ˈɔltɚˌneɪt -ANALYSES_NOU æˈnælɪˌsiz -ANALYSES_VRB ænəˈlaɪˌzɪz -ANIMATE_ADJ-NOU ˈænəmət -ANIMATE_VRB ˈænəˌmeɪt -APPROPRIATE_ADJ əˈpɹoʊpɹiət -APPROPRIATE_VRB əˈpɹoʊpɹiˌeɪt -APPROXIMATE_ADJ-NOU əˈpɹɑksəmət -APPROXIMATE_VRB əˈpɹɑksəˌmeɪt -ARTICULATE_ADJ ɑɹˈtɪkjələt -ARTICULATE_VRB ɑɹˈtɪkjəˌleɪt -ASSOCIATE_ADJ-NOU əˈsoʊsiət -ASSOCIATE_VRB əˈsoʊsiˌeɪt -ATTRIBUTE_NOU ˈætɹəbˌjut -ATTRIBUTE_VRB əˈtɹɪbˌjut -AUGUST_ADJ ˌɑˈɡəst -AUGUST ˈɑɡəst -AUGUST_NAM ˈaʊˌɡʊst -AXES_NOU ˈækˌsiz -AXES_NOU-VRB ˈækˌsɪz -BASS ˈbeɪs -BASS_CORP ˈbæs -BLESSED_ADJ ˈblɛsəd -BLESSED_VRB ˈblɛst -BOLOGNA_GEO bəˈloʊˌŋɑ -BOLOGNA bəˈloʊni -BOW_NOU-KNOT ˈboʊ -BOW_NOU-SHIP ˈbaʊ -BUFFET_NOU bəˈfeɪ -BUFFET_VRB ˈbʌfət -CELTIC_ADJ-NOU-SPORTS ˈsɛltɪk -CELTIC ˈkɛltɪk -CLOSE_ADJ-NOU ˈkloʊs -CLOSE_VRB ˈkloʊz -COMBINE_NOU ˈkɑmbaɪn -COMBINE_VRB kəmˈbaɪn -COMPACT_ADJ-NOU ˈkɑmpækt -COMPACT_VRB kəmˈpækt -COMPOUND_NOU ˈkɑmpaʊnd -COMPOUND_VRB kəmˈpaʊnd -COMPRESS_NOU ˈkɑmpɹɛs -COMPRESS kəmˈpɹɛs -CONDUCT_NOU ˈkɑndəkt -CONDUCT_VRB kɑnˈdʌkt -CONFINES_NOU ˈkɑnˌfaɪnz -CONFINES_VRB kənˈfaɪnz -CONFLICT_NOU ˈkɑnflɪkt -CONFLICT_VRB kənˈflɪkt -CONGLOMERATE_ADJ-NOU kənˈɡlɑmɚət -CONGLOMERATE_VRB kənˈɡlɑmɝˌeɪt -CONJUGATE_ADJ-NOU ˈkɑndʒəˌɡeɪt -CONJUGATE_VRB ˈkɑndʒəˌɡeɪt -CONSCRIPT_NOU ˈkɑnsˌkɹɪpt -CONSCRIPT_VRB kənsˈkɹɪpt -CONSOLE_NOU ˈkɑnsoʊl -CONSOLE_VRB kənˈsoʊl -CONSORT_NOU ˈkɑnˌsɔɹt -CONSORT_VRB kənˈsɔɹt -CONSTRUCT_NOU ˈkɑnstɹəkt -CONSTRUCT_VRB kənˈstɹʌkt -CONSUMMATE_ADJ ˈkɑnsəmət -CONSUMMATE_VRB ˈkɑnsəˌmeɪt -CONTENT_ADJ-NOU-VRB kənˈtɛnt -CONTENT_NOU ˈkɑntɛnt -CONTEST_NOU ˈkɑntɛst -CONTEST_VRB kənˈtɛst -CONTRACT_NOU ˈkɑnˌtɹækt -CONTRACT_VRB kənˈtɹækt -CONTRAST_NOU ˈkɑntɹæst -CONTRAST_VRB kənˈtɹæst -CONVERSE_ADJ-NOU ˈkɑnvɚs -CONVERSE_VRB kənˈvɝs -CONVERT_NOU ˈkɑnvɚt -CONVERT_VRB kənˈvɝt -CONVICT_NOU ˈkɑnvɪkt -CONVICT_VRB kənˈvɪkt -COORDINATE_ADJ-NOU koʊˈɔɹdənət -COORDINATE_VRB koʊˈɔɹdəˌneɪt -CORRELATE_NOU ˈkɔɹələt -CORRELATE_NOU-VRB ˈkɔɹəˌleɪt -DECREASE_NOU ˈdiˌkɹis -DECREASE_VRB dɪˈkɹis -DEFECT_NOU ˈdifɛkt -DEFECT_VRB dɪˈfɛkt -DEGENERATE_ADJ-NOU dɪˈdʒɛnɚət -DEGENERATE_VRB dɪˈdʒɛnɚˌeɪt -DELEGATE_NOU ˈdɛləɡət -DELEGATE_VRB ˈdɛləˌɡeɪt -DELIBERATE_ADJ dɪˈlɪbɚət -DELIBERATE_VRB dɪˈlɪbɚˌeɪt -DESERT_NOU ˈdɛzɚt -DESERT_VRB dɪˈzɝt -DEVIATE_NOU ˈdiˌviət -DEVIATE_VRB ˈdiviˌeɪt -DIAGNOSES_NOU ˌdaɪəɡˈnoʊsiz -DIAGNOSES_VRB ˌdaɪəɡˈnoʊsəz -DIFFUSE_ADJ dɪfˈjus -DIFFUSE_VRB dɪfˈjuz -DISCARD_NOU ˈdɪsˌkɑɹd -DISCARD_VRB dəsˈkɑɹd -DISCHARGE_NOU ˈdɪsˌtʃɑɹdʒ -DISCHARGE_VRB dɪsˈtʃɑɹdʒ -DISCOUNT_NOU ˈdɪskaʊnt -DISCOUNT_VRB dɪˈskaʊnt -DOCUMENT_NOU ˈdɑkjumɛnt -DOCUMENT_VRB ˈdɑkjəmɛnt -DOVE ˈdʌv -DOVE_VRB ˈdoʊv -DUPLICATE_ADJ-NOU ˈdupləkət -DUPLICATE_VRB ˈdupləˌkeɪt -ELABORATE_ADJ ɪˈlæbɹət -ELABORATE_VRB ɪˈlæbɚˌeɪt -ENTRANCE_NOU ˈɛntɹəns -ENTRANCE_VRB əˈntɹæns -ESCORT_NOU ˈɛskɔɹt -ESCORT_VRB ɛˈskɔɹt -ESTIMATE_NOU ˈɛstəmət -ESTIMATE_VRB ˈɛstəˌmeɪt -EXCUSE_NOU ɪkˈskjus -EXCUSE_VRB ɪkˈskjuz -EXPATRIATE_NOU ɛkˈspeɪtɹiət -EXPATRIATE_VRB ɛkˈspeɪtɹiˌeɪt -EXPLOIT_NOU ˈɛksˌplɔɪt -EXPLOIT_VRB ˌɛksˈplɔɪt -EXPORT_NOU ˈɛkspɔɹt -EXPORT_VRB əkˈspɔɹt -EXPOSE_NOU ˌɛkˌspoʊˈzeɪ -EXPOSE_VRB ɪkˈspoʊz -EXTRACT_NOU ˈɛkˌstɹækt -EXTRACT_VRB ɪkˈstɹækt -FRAGMENT_NOU ˈfɹæɡmənt -FRAGMENT_VRB ˌfɹæɡˈmɛnt -FREQUENT_ADJ ˈfɹikwənt -FREQUENT_VRB ˌfɹiˈkwɛnt -GRADUATE_ADJ-NOU ˈɡɹædʒuwət -GRADUATE_VRB ˈɡɹædʒuˌeɪt -HOUSE_NOU ˈhaʊs -HOUSE_VRB ˈhaʊz -IMPACT_NOU ˈɪmpækt -IMPACT_VRB ˌɪmˈpækt -IMPLANT_NOU ˈɪmˌplænt -IMPLANT_VRB ˌɪmˈplænt -IMPLEMENT_NOU ˈɪmpləmənt -IMPLEMENT_VRB ˈɪmpləˌmɛnt -IMPORT_NOU ˈɪmˌpɔɹt -IMPORT_VRB ˌɪmˈpɔɹt -INCENSE_NOU ˈɪnˌsɛns -INCENSE_VRB ˌɪnˈsɛns -INCLINE_NOU ˈɪnklaɪn -INCLINE_VRB ˌɪnˈklaɪn -INCREASE_NOU ˈɪnˌkɹis -INCREASE_VRB ˌɪnˈkɹis -INCREMENT_NOU ˈɪnkɹəmənt -INCREMENT_VRB ˈɪnkɹəˌmɛnt -INITIATE_NOU əˈnɪˌʃiət -INITIATE_VRB ˌɪˈnɪʃiˌeɪt -INSERT_NOU ˈɪnˌsɝt -INSERT_VRB ˌɪnˈsɝt -INSTRUMENT_NOU ˈɪnstɹəmənt -INSTRUMENT_VRB ˈɪnstɹəˌmɛnt -INSULT_NOU ˈɪnˌsʌlt -INSULT_VRB ˌɪnˈsʌlt -INTERCHANGE_NOU ˈɪntɚˌtʃeɪndʒ -INTERCHANGE_VRB ˌɪntɚˈtʃeɪndʒ -INTIMATE_ADJ ˈɪntəmət -INTIMATE_VRB ˈɪntɪˌmeɪt -INTRIGUE_NOU ˈɪntɹiɡ -INTRIGUE_NOU-VRB ˌɪnˈtɹiɡ -INVALID_ADJ ˌɪnˈvæləd -INVALID_NOU ˈɪnvələd -INVERT_ADJ-NOU ˈɪnvɝt -INVERT_VRB ˌɪnˈvɝt -INVITE_NOU ˈɪnˌvaɪt -INVITE_VRB ˌɪnˈvaɪt -ISOLATE_NOU ˈaɪsələt -ISOLATE ˈaɪsəˌleɪt -JESUS ˈdʒizəs -JESUS_ES ˌheɪˈsus -JOB_BIBLE ˈdʒoʊb -JOB ˈdʒɑb -LAMINATE_NOU ˈlæmənət -LAMINATE_VRB ˈlæməˌneɪt -LEAD_NOU ˈlɛd -LEAD_NOU-VRB ˈlid -LEARNED_ADJ ˈlɝnɪd -LEARNED_VRB ˈlɝnd -LIVE_ADJ ˈlaɪv -LIVE_VRB ˈlɪv -LIVES_NOU ˈlaɪvz -LIVES_VRB ˈlɪvz -MATE_NOU ˈmɑˌteɪ -MATE ˈmeɪt -MINUTE_ADJ maɪˈnut -MINUTE ˈmɪnət -MISUSE_NOU mɪsˈjus -MISUSE_VRB mɪsˈjuz -MOBILE ˈmoʊbəl -MOBILE_GEO ˌmoʊˈbil -MOBILE_NOU-ART ˈmoʊˌbil -MODERATE_ADJ-NOU ˈmɑdɚət -MODERATE_VRB ˈmɑdɚˌeɪt -MOPED_NOU ˈmoʊpɛd -MOPED_VRB ˈmoʊpt -MOUTH_NOU ˈmaʊθ -MOUTH_VRB ˈmaʊð -NESTLE_NAM ˈnɛsˈli -NESTLE_VRB ˈnɛsəl -OBJECT_NOU ˈɑbdʒɛkt -OBJECT_VRB əbˈdʒɛkt -ORNAMENT_NOU ˈɔɹnəmənt -ORNAMENT_VRB ˌɔɹnəˈmɛnt -OVERTHROW_NOU ˈoʊvɚˌθɹoʊ -OVERTHROW_VRB ˌoʊvɚˈθɹoʊ -PASTY_ADJ ˈpeɪˌsti -PASTY_NOU ˈpæsˌti -PERFECT_ADJ ˈpɝˌfɪkt -PERFECT_VRB pɚˈfɛkt -PERFUME_NOU ˈpɝˌfjum -PERFUME_VRB pɚˈfjum -PERMIT_NOU ˈpɝˌmɪt -PERMIT_VRB pɚˈmɪt -PERVERT_NOU ˈpɝvɚt -PERVERT_VRB pɚˈvɝt -PIGMENT_NOU ˈpɪɡmɛnt -PIGMENT_VRB pəɡˈmɛnt -POLISH_GEO ˈpoʊlɪʃ -POLISH ˈpɑlɪʃ -POSTULATE_NOU ˈpɑstʃələt -POSTULATE_VRB ˈpɑstʃəˌleɪt -PRECIPITATE_ADJ-NOU pɹəˈsɪpətət -PRECIPITATE_VRB pɹɪˈsɪpɪˌteɪt -PREDICATE_NOU ˈpɹɛdɪkət -PREDICATE_VRB ˈpɹɛdəˌkeɪt -PRESENT_ADJ-NOU ˈpɹɛzənt -PRESENT_VRB pɹiˈzɛnt -PRODUCE_NOU ˈpɹoʊdus -PRODUCE_VRB pɹəˈdus -PROGRESS_NOU ˈpɹɑˌɡɹɛs -PROGRESS_VRB pɹəˈɡɹɛs -PROJECT_NOU ˈpɹɑdʒɛkt -PROJECT_VRB pɹɑˈdʒɛkt -PROTEST_NOU ˈpɹoʊˌtɛst -PROTEST_VRB pɹəˈtɛst -RAVEL_NAM ɹəˈvɛl -RAVEL_NOU ˈɹævəl -READING_EN ˈɹidɪŋ -READING_GEO ˈɹɛdɪŋ -READ_PAST ˈɹɛd -READ_PRESENT ˈɹid -REBEL_NOU ˈɹɛbəl -REBEL_VRB ɹɪˈbɛl -RECORD_NOU ˈɹɛkɚd -RECORD_VRB ɹəˈkɔɹd -RECOUNT_NOU ˈɹiˌkaʊnt -RECOUNT_VRB ˌɹiˈkaʊnt -REFUND_NOU ˈɹiˌfʌnd -REFUND_VRB ɹɪˈfʌnd -REFUSE_NOU ˈɹɛfˌjuz -REFUSE_VRB ɹəfˈjuz -REJECT_NOU ˈɹidʒɛkt -REJECT_VRB ɹɪˈdʒɛkt -RERELEASE ˈɹiɹəˌlis -RERELEASE_VRB ˌɹiɹəˈlis -RESUME_NOU ˈɹɛzəˌmeɪ -RESUME_VRB ɹiˈzum -RETARD_NOU ˈɹitɑɹd -RETARD_VRB ɹɪˈtɑɹd -RODEO_GEO ˌɹoʊˈdeɪˌoʊ -RODEO ˈɹoʊdiˌoʊ -ROW_1 ˈɹoʊ -ROW_2 ˈɹaʊ -SAKE_JP ˈsɑˌkeɪ -SAKE ˈseɪk -SEPARATE_ADJ ˈsɛpɚɪt -SEPARATE_VRB ˈsɛpɚˌeɪt -SOW_NOU ˈsaʊ -SOW ˈsoʊ -SUBJECT_ADJ-NOU ˈsʌbdʒɪkt -SUBJECT_VRB səbˈdʒɛkt -SUBORDINATE_ADJ-NOU səˈbɔɹdənət -SUBORDINATE_VRB səˈbɔɹdəˌneɪt -SUPPLEMENT_NOU ˈsʌpləmənt -SUPPLEMENT_VRB ˈsʌpləmənt -SUSPECT_ADJ-NOU ˈsʌsˌpɛkt -SUSPECT_VRB səˈspɛkt -SYNDICATE_NOU ˈsɪndɪkət -SYNDICATE_VRB ˈsɪndəˌkeɪt -TEAR_NOU ˈtɪɹ -TEAR_VRB ˈtɛɹ -TRANSFORM_NOU ˈtɹænsfɔɹm -TRANSFORM tɹænsˈfɔɹm -TRANSPLANT_NOU ˈtɹænsˌplænt -TRANSPLANT_VRB tɹænsˈplænt -TRANSPORT_NOU ˈtɹænspɔɹt -TRANSPORT_VRB tɹænˈspɔɹt -UPSET_NOU ˈʌpˌsɛt -UPSET_VRB əpˈsɛt -USES_NOU ˈjusəz -USES_VRB ˈjuzəz -USE_NOU ˈjus -USE_VRB ˈjuz -WIND_NOU ˈwɪnd -WIND_VRB ˈwaɪnd -WINDS_NOU ˈwɪndz -WINDS_VRB ˈwaɪndz -WOUND_NOU-VRB ˈwund -WOUND_VRB ˈwaʊnd From 2696d10b58a8eb641fe148e8271177a6716ef7de Mon Sep 17 00:00:00 2001 From: ekmb Date: Tue, 14 Feb 2023 19:56:16 -0800 Subject: [PATCH 15/19] remove pynini_install from tutorials Signed-off-by: ekmb --- .../duplex_text_normalization/duplex_decoder.py | 4 +++- nemo/collections/tts/torch/data.py | 4 +++- tutorials/AudioTranslationSample.ipynb | 6 +----- tutorials/VoiceSwapSample.ipynb | 4 ---- tutorials/tts/Aligner_Inference_Examples.ipynb | 4 +--- tutorials/tts/FastPitch_ChineseTTS_Training.ipynb | 4 +--- tutorials/tts/FastPitch_Finetuning.ipynb | 6 ++---- tutorials/tts/FastPitch_GermanTTS_Training.ipynb | 6 ++---- tutorials/tts/FastPitch_MixerTTS_Training.ipynb | 6 ++---- .../tts/Inference_DurationPitchControl.ipynb | 4 +--- tutorials/tts/Inference_ModelSelect.ipynb | 4 +--- tutorials/tts/NeMo_TTS_Primer.ipynb | 15 --------------- tutorials/tts/Pronunciation_customization.ipynb | 6 ++---- tutorials/tts/Tacotron2_Training.ipynb | 4 +--- 14 files changed, 20 insertions(+), 57 deletions(-) diff --git a/nemo/collections/nlp/models/duplex_text_normalization/duplex_decoder.py b/nemo/collections/nlp/models/duplex_text_normalization/duplex_decoder.py index 861676acf316..7d4cac46cc28 100644 --- a/nemo/collections/nlp/models/duplex_text_normalization/duplex_decoder.py +++ b/nemo/collections/nlp/models/duplex_text_normalization/duplex_decoder.py @@ -111,7 +111,9 @@ def setup_cgs(self, cfg: DictConfig): self.cg_normalizer = NormalizerWithAudio(input_case=input_case, lang=self.lang) else: self.cg_normalizer = None - logging.warning("`pynini` not installed, please install via nemo_text_processing/pynini_install.sh") + logging.warning( + "`nemo_text_processing` is not installed, see https://github.com/NVIDIA/NeMo-text-processing for details" + ) @typecheck() def forward(self, input_ids, decoder_input_ids, attention_mask, labels): diff --git a/nemo/collections/tts/torch/data.py b/nemo/collections/tts/torch/data.py index a5e0e01f3a41..36d5c4b3634c 100644 --- a/nemo/collections/tts/torch/data.py +++ b/nemo/collections/tts/torch/data.py @@ -203,7 +203,9 @@ def __init__( if self.text_normalizer is None: self.text_normalizer_call = None elif not PYNINI_AVAILABLE: - raise ImportError("pynini is not installed, please install via nemo_text_processing/install_pynini.sh") + raise ImportError( + "`nemo_text_processing` is not installed, see https://github.com/NVIDIA/NeMo-text-processing for details" + ) else: self.text_normalizer_call = ( self.text_normalizer.normalize diff --git a/tutorials/AudioTranslationSample.ipynb b/tutorials/AudioTranslationSample.ipynb index c4fec16c4181..12b354725982 100644 --- a/tutorials/AudioTranslationSample.ipynb +++ b/tutorials/AudioTranslationSample.ipynb @@ -39,11 +39,7 @@ "outputs": [], "source": [ "BRANCH = 'main'\n", - "!python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "\n", - "# install Pynini for text normalization\n", - "! wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "! bash install_pynini.sh" + "!python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/VoiceSwapSample.ipynb b/tutorials/VoiceSwapSample.ipynb index 016737f26a9f..4f22e2cb82a6 100644 --- a/tutorials/VoiceSwapSample.ipynb +++ b/tutorials/VoiceSwapSample.ipynb @@ -41,10 +41,6 @@ "source": [ "BRANCH = 'main'\n", "!python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "\n", - "# install Pynini for text normalization\n", - "! wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "! bash install_pynini.sh" ] }, { diff --git a/tutorials/tts/Aligner_Inference_Examples.ipynb b/tutorials/tts/Aligner_Inference_Examples.ipynb index f6acbfa2c0d4..7a94102b3dee 100644 --- a/tutorials/tts/Aligner_Inference_Examples.ipynb +++ b/tutorials/tts/Aligner_Inference_Examples.ipynb @@ -43,9 +43,7 @@ "# # If you're using Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", "# !pip install wget text-unidecode\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb b/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb index 5735017ea64d..57ea4f20bea2 100644 --- a/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_ChineseTTS_Training.ipynb @@ -54,10 +54,8 @@ "BRANCH = 'main'\n", "# # If you're using Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", - "# !pip install wget text-unidecode pynini==2.1.4 scipy==1.7.3\n", + "# !pip install wget text-unidecode scipy==1.7.3\n", "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh\n", "# !pip install pypinyin opencc-python-reimplemented" ] }, diff --git a/tutorials/tts/FastPitch_Finetuning.ipynb b/tutorials/tts/FastPitch_Finetuning.ipynb index 208f31841505..be4e99c3caab 100755 --- a/tutorials/tts/FastPitch_Finetuning.ipynb +++ b/tutorials/tts/FastPitch_Finetuning.ipynb @@ -60,10 +60,8 @@ "BRANCH = 'main'\n", "# # If you're using Google Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", - "# !pip install wget text-unidecode pynini==2.1.4\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !pip install wget text-unidecode \n", + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/tts/FastPitch_GermanTTS_Training.ipynb b/tutorials/tts/FastPitch_GermanTTS_Training.ipynb index 05e8555c9f0a..110720c9ce33 100644 --- a/tutorials/tts/FastPitch_GermanTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_GermanTTS_Training.ipynb @@ -54,10 +54,8 @@ "BRANCH = 'main'\n", "# # If you're using Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", - "# !pip install wget text-unidecode pynini==2.1.4 scipy==1.7.3\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !pip install wget text-unidecode scipy==1.7.3\n", + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/tts/FastPitch_MixerTTS_Training.ipynb b/tutorials/tts/FastPitch_MixerTTS_Training.ipynb index 05434c03e6d0..8916825f92df 100644 --- a/tutorials/tts/FastPitch_MixerTTS_Training.ipynb +++ b/tutorials/tts/FastPitch_MixerTTS_Training.ipynb @@ -53,10 +53,8 @@ "BRANCH = 'main'\n", "# # If you're using Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", - "# !pip install wget text-unidecode pynini==2.1.4 scipy==1.7.3\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !pip install wget text-unidecode scipy==1.7.3\n", + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/tts/Inference_DurationPitchControl.ipynb b/tutorials/tts/Inference_DurationPitchControl.ipynb index c4879f38274c..831f4b0b3c4d 100644 --- a/tutorials/tts/Inference_DurationPitchControl.ipynb +++ b/tutorials/tts/Inference_DurationPitchControl.ipynb @@ -50,9 +50,7 @@ "# # If you're using Google Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", "# !pip install wget text-unidecode\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/tts/Inference_ModelSelect.ipynb b/tutorials/tts/Inference_ModelSelect.ipynb index 8fe398edafa6..223c1f62a19a 100644 --- a/tutorials/tts/Inference_ModelSelect.ipynb +++ b/tutorials/tts/Inference_ModelSelect.ipynb @@ -50,9 +50,7 @@ "# # If you're using Google Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", "# !pip install wget text-unidecode\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/tts/NeMo_TTS_Primer.ipynb b/tutorials/tts/NeMo_TTS_Primer.ipynb index e323536fa56b..12e3984fbe03 100644 --- a/tutorials/tts/NeMo_TTS_Primer.ipynb +++ b/tutorials/tts/NeMo_TTS_Primer.ipynb @@ -46,21 +46,6 @@ "!git clone https://github.com/NVIDIA/NeMo.git $NEMO_DIR" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "goNEA8hOAmAP", - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "# Install pynini for text processing\n", - "!bash $NEMO_DIR/nemo_text_processing/install_pynini.sh" - ] - }, { "cell_type": "markdown", "metadata": { diff --git a/tutorials/tts/Pronunciation_customization.ipynb b/tutorials/tts/Pronunciation_customization.ipynb index 14269ce33455..44a376b596ac 100644 --- a/tutorials/tts/Pronunciation_customization.ipynb +++ b/tutorials/tts/Pronunciation_customization.ipynb @@ -29,10 +29,8 @@ "BRANCH = 'main'\n", "# # If you're using Google Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", - "# !pip install wget text-unidecode pynini==2.1.4\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !pip install wget text-unidecode \n", + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { diff --git a/tutorials/tts/Tacotron2_Training.ipynb b/tutorials/tts/Tacotron2_Training.ipynb index a12cb980dc0b..7f3c65a81249 100644 --- a/tutorials/tts/Tacotron2_Training.ipynb +++ b/tutorials/tts/Tacotron2_Training.ipynb @@ -58,9 +58,7 @@ "# # If you're using Colab and not running locally, uncomment and run this cell.\n", "# !apt-get install sox libsndfile1 ffmpeg\n", "# !pip install wget text-unidecode\n", - "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n", - "# !wget https://raw.githubusercontent.com/NVIDIA/NeMo/main/nemo_text_processing/install_pynini.sh\n", - "# !bash install_pynini.sh" + "# !python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]\n" ] }, { From b3c3ca64e3326fcbe533f1f706e10c064dee46f9 Mon Sep 17 00:00:00 2001 From: ekmb Date: Tue, 14 Feb 2023 20:07:24 -0800 Subject: [PATCH 16/19] update requirements Signed-off-by: ekmb --- .../requirements_nemo_text_processing.txt | 1 - requirements/requirements_tts.txt | 1 + setup.py | 36 ++----------------- 3 files changed, 4 insertions(+), 34 deletions(-) delete mode 100644 requirements/requirements_nemo_text_processing.txt diff --git a/requirements/requirements_nemo_text_processing.txt b/requirements/requirements_nemo_text_processing.txt deleted file mode 100644 index 989ce0ac03b0..000000000000 --- a/requirements/requirements_nemo_text_processing.txt +++ /dev/null @@ -1 +0,0 @@ -nemo_text_processing==0.1.6rc0 diff --git a/requirements/requirements_tts.txt b/requirements/requirements_tts.txt index d4604a044191..e4f246c210c3 100644 --- a/requirements/requirements_tts.txt +++ b/requirements/requirements_tts.txt @@ -9,3 +9,4 @@ nltk pandas pypinyin pypinyin-dict +nemo_text_processing==0.1.6rc0 diff --git a/setup.py b/setup.py index 328bbec60d44..315fed8b0caf 100644 --- a/setup.py +++ b/setup.py @@ -79,8 +79,6 @@ def req_file(filename, folder="requirements"): extras_require = { # User packages 'test': req_file("requirements_test.txt"), - # NeMo Tools - 'nemo_text_processing': req_file("requirements_nemo_text_processing.txt"), # Lightning Collections Packages 'core': req_file("requirements_lightning.txt"), 'common': req_file('requirements_common.txt'), @@ -95,39 +93,11 @@ def req_file(filename, folder="requirements"): extras_require['all'] = list(chain(extras_require.values())) # Add lightning requirements as needed -extras_require['nemo_text_processing'] = list(chain([extras_require['nemo_text_processing'], extras_require['core']])) extras_require['common'] = list(chain([extras_require['common'], extras_require['core']])) -extras_require['test'] = list( - chain( - [ - extras_require['tts'], - extras_require['core'], - extras_require['common'], - extras_require['nemo_text_processing'], - ] - ) -) +extras_require['test'] = list(chain([extras_require['tts'], extras_require['core'], extras_require['common'],])) extras_require['asr'] = list(chain([extras_require['asr'], extras_require['core'], extras_require['common']])) -extras_require['nlp'] = list( - chain( - [ - extras_require['nlp'], - extras_require['core'], - extras_require['common'], - extras_require['nemo_text_processing'], - ] - ) -) -extras_require['tts'] = list( - chain( - [ - extras_require['tts'], - extras_require['core'], - extras_require['common'], - extras_require['nemo_text_processing'], - ] - ) -) +extras_require['nlp'] = list(chain([extras_require['nlp'], extras_require['core'], extras_require['common'],])) +extras_require['tts'] = list(chain([extras_require['tts'], extras_require['core'], extras_require['common'],])) # TTS has extra dependencies extras_require['tts'] = list(chain([extras_require['tts'], extras_require['asr']])) From eb8adf21c73e890a523a118b21ae2e74100b480d Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 15 Feb 2023 04:08:35 +0000 Subject: [PATCH 17/19] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- requirements/requirements_tts.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements/requirements_tts.txt b/requirements/requirements_tts.txt index e4f246c210c3..f21fda57e6ff 100644 --- a/requirements/requirements_tts.txt +++ b/requirements/requirements_tts.txt @@ -5,8 +5,8 @@ jieba kornia librosa matplotlib +nemo_text_processing==0.1.6rc0 nltk pandas pypinyin pypinyin-dict -nemo_text_processing==0.1.6rc0 From 9e8e0dcb827cdd07a6928d97281e7ba2a5059665 Mon Sep 17 00:00:00 2001 From: ekmb Date: Tue, 14 Feb 2023 20:24:48 -0800 Subject: [PATCH 18/19] add support warning Signed-off-by: ekmb --- nemo/collections/tts/models/aligner.py | 1 + nemo/collections/tts/models/fastpitch.py | 1 + nemo/collections/tts/models/mixer_tts.py | 1 + nemo/collections/tts/models/radtts.py | 1 + nemo/collections/tts/models/tacotron2.py | 1 + nemo/collections/tts/models/vits.py | 1 + 6 files changed, 6 insertions(+) diff --git a/nemo/collections/tts/models/aligner.py b/nemo/collections/tts/models/aligner.py index ce1eeba309ef..4f0744776641 100644 --- a/nemo/collections/tts/models/aligner.py +++ b/nemo/collections/tts/models/aligner.py @@ -103,6 +103,7 @@ def _setup_tokenizer(self, cfg): cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( "nemo_text_processing.g2p", "nemo.collections.tts.g2p" ) + logging.warning("This checkpoint support will be dropped after r1.18.0.") g2p_kwargs = {} diff --git a/nemo/collections/tts/models/fastpitch.py b/nemo/collections/tts/models/fastpitch.py index 70c6cd6f14f5..d22c8d47038c 100644 --- a/nemo/collections/tts/models/fastpitch.py +++ b/nemo/collections/tts/models/fastpitch.py @@ -206,6 +206,7 @@ def _setup_tokenizer(self, cfg): cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( "nemo_text_processing.g2p", "nemo.collections.tts.g2p" ) + logging.warning("This checkpoint support will be dropped after r1.18.0.") g2p_kwargs = {} diff --git a/nemo/collections/tts/models/mixer_tts.py b/nemo/collections/tts/models/mixer_tts.py index 5f59e93554c5..225076b7b027 100644 --- a/nemo/collections/tts/models/mixer_tts.py +++ b/nemo/collections/tts/models/mixer_tts.py @@ -153,6 +153,7 @@ def _setup_tokenizer(self, cfg): cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( "nemo_text_processing.g2p", "nemo.collections.tts.g2p" ) + logging.warning("This checkpoint support will be dropped after r1.18.0.") g2p_kwargs = {} diff --git a/nemo/collections/tts/models/radtts.py b/nemo/collections/tts/models/radtts.py index ac2bf2dd19b1..f7f1344eaf37 100644 --- a/nemo/collections/tts/models/radtts.py +++ b/nemo/collections/tts/models/radtts.py @@ -342,6 +342,7 @@ def _setup_tokenizer(self, cfg): cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( "nemo_text_processing.g2p", "nemo.collections.tts.g2p" ) + logging.warning("This checkpoint support will be dropped after r1.18.0.") g2p_kwargs = {} diff --git a/nemo/collections/tts/models/tacotron2.py b/nemo/collections/tts/models/tacotron2.py index 20fee29a7c31..2ed69c8809a0 100644 --- a/nemo/collections/tts/models/tacotron2.py +++ b/nemo/collections/tts/models/tacotron2.py @@ -328,6 +328,7 @@ def _setup_tokenizer(self, cfg): cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( "nemo_text_processing.g2p", "nemo.collections.tts.g2p" ) + logging.warning("This checkpoint support will be dropped after r1.18.0.") g2p_kwargs = {} diff --git a/nemo/collections/tts/models/vits.py b/nemo/collections/tts/models/vits.py index 832197195742..7b2f20743184 100644 --- a/nemo/collections/tts/models/vits.py +++ b/nemo/collections/tts/models/vits.py @@ -118,6 +118,7 @@ def _setup_tokenizer(self, cfg): cfg.text_tokenizer.g2p['_target_'] = cfg.text_tokenizer.g2p['_target_'].replace( "nemo_text_processing.g2p", "nemo.collections.tts.g2p" ) + logging.warning("This checkpoint support will be dropped after r1.18.0.") g2p_kwargs = {} From e304858cd301f0ad038f0c5ac4549f58b63b2d47 Mon Sep 17 00:00:00 2001 From: ekmb Date: Wed, 15 Feb 2023 11:20:32 -0800 Subject: [PATCH 19/19] review Signed-off-by: ekmb --- README.rst | 6 +---- .../tts/aligner_heteronym_disambiguation.py | 12 +++++----- examples/tts/g2p/g2p_train_and_evaluate.py | 2 +- .../text_to_speech/tts_tokenizers.py | 22 +++++++++---------- nemo/collections/tts/g2p/data/ctc_g2p.py | 2 +- nemo/collections/tts/g2p/data/t5_g2p.py | 2 +- nemo/collections/tts/g2p/modules.py | 6 ++--- .../export_wikihomograph_data_to_manifest.py | 4 ++-- 8 files changed, 26 insertions(+), 30 deletions(-) diff --git a/README.rst b/README.rst index 7aa25ba88f21..7bbc1fe5037a 100644 --- a/README.rst +++ b/README.rst @@ -243,11 +243,7 @@ Transformer Engine enables FP8 training on NVIDIA Hopper GPUs. NeMo Text Processing ~~~~~~~~~~~~~~~~~~~~ -NeMo Text Processing, specifically (Inverse) Text Normalization, requires `Pynini `_ to be installed. - -.. code-block:: bash - - bash NeMo/nemo_text_processing/install_pynini.sh +NeMo Text Processing, specifically (Inverse) Text Normalization, is now a separate repository `https://github.com/NVIDIA/NeMo-text-processing `_. Docker containers: ~~~~~~~~~~~~~~~~~~ diff --git a/examples/tts/aligner_heteronym_disambiguation.py b/examples/tts/aligner_heteronym_disambiguation.py index ad6b1ac13eee..fe5d89747a2b 100644 --- a/examples/tts/aligner_heteronym_disambiguation.py +++ b/examples/tts/aligner_heteronym_disambiguation.py @@ -26,7 +26,7 @@ """ -G2P_paper disambiguation using an Aligner model's input embedding distances. +G2P disambiguation using an Aligner model's input embedding distances. Does not handle OOV and leaves them as graphemes. @@ -46,7 +46,7 @@ def get_args(): """Retrieve arguments for disambiguation. """ - parser = argparse.ArgumentParser("G2P_paper disambiguation using Aligner input embedding distances.") + parser = argparse.ArgumentParser("G2P disambiguation using Aligner input embedding distances.") # TODO(jocelynh): Make this required=False with default download from NGC once ckpt uploaded parser.add_argument('--model', required=True, type=str, help="Path to Aligner model checkpoint (.nemo file).") parser.add_argument( @@ -108,7 +108,7 @@ def disambiguate_candidates(aligner, text, spec, spec_len, confidence, device, h Note: This could be sped up if multiple words' candidates were batched, but this is conceptually easier. """ - # Grab original G2P_paper result + # Grab original G2P result aligner_g2p = aligner.tokenizer.g2p base_g2p = aligner_g2p(text) @@ -122,7 +122,7 @@ def disambiguate_candidates(aligner, text, spec, spec_len, confidence, device, h has_heteronym = False for word in words: - # Retrieve the length of the word in the default G2P_paper conversion + # Retrieve the length of the word in the default G2P conversion g2p_default_len = len(aligner_g2p(word)) # Check if word needs to be disambiguated @@ -134,7 +134,7 @@ def disambiguate_candidates(aligner, text, spec, spec_len, confidence, device, h candidate_prons_and_lengths = [] for pron in aligner_g2p.phoneme_dict[word]: - # Replace graphemes in the base G2P_paper result with the current variant + # Replace graphemes in the base G2P result with the current variant candidate = base_g2p[:word_start_idx] + pron + base_g2p[word_start_idx + g2p_default_len :] candidate_tokens = aligner.tokenizer.encode_from_g2p(candidate) @@ -247,7 +247,7 @@ def disambiguate_dataset( count = 0 for line in f_in: - # Retrieve entry and base G2P_paper conversion for full text + # Retrieve entry and base G2P conversion for full text entry = json.loads(line) # Set punct_post_process=True in order to preserve words with apostrophes text = aligner.normalizer.normalize(entry['text'], punct_post_process=True) diff --git a/examples/tts/g2p/g2p_train_and_evaluate.py b/examples/tts/g2p/g2p_train_and_evaluate.py index e2edef695180..d7a98a4d77ad 100644 --- a/examples/tts/g2p/g2p_train_and_evaluate.py +++ b/examples/tts/g2p/g2p_train_and_evaluate.py @@ -40,7 +40,7 @@ Example of the config file: NeMo/examples/text_processing/g2p/conf/t5_g2p.yaml -# Training Conformer-G2P_paper Model and evaluation at the end of training: +# Training Conformer-G2P Model and evaluation at the end of training: python examples/text_processing/g2p/g2p_train_and_evaluate.py \ # (Optional: --config-path= --config-name=) \ model.train_ds.manifest_filepath="" \ diff --git a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py index 2ee5ee489722..a708355622d4 100644 --- a/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py +++ b/nemo/collections/common/tokenizers/text_to_speech/tts_tokenizers.py @@ -446,11 +446,11 @@ def encode(self, text): def encode_from_g2p(self, g2p_text: List[str], raw_text: Optional[str] = None): """ - Encodes text that has already been run through G2P_paper. - Called for encoding to tokens after text preprocessing and G2P_paper. + Encodes text that has already been run through G2P. + Called for encoding to tokens after text preprocessing and G2P. Args: - g2p_text: G2P_paper's output, could be a mixture of phonemes and graphemes, + g2p_text: G2P's output, could be a mixture of phonemes and graphemes, e.g. "see OOV" -> ['S', 'IY1', ' ', 'O', 'O', 'V'] raw_text: original raw input """ @@ -533,11 +533,11 @@ def __init__( """ if not hasattr(g2p, "symbols"): logging.error( - f"Please make sure the G2P_paper module passed into the IPATokenizer has a `symbols` attribute. " + f"Please make sure the G2P module passed into the IPATokenizer has a `symbols` attribute. " f"This is required in order to build the tokenizer vocabulary.\n" f"Expected e.g. IPAG2P, found {type(g2p)}" ) - raise ValueError("G2P_paper modules passed into the IPATokenizer must have `symbols` defined.") + raise ValueError("G2P modules passed into the IPATokenizer must have `symbols` defined.") if locale is not None: validate_locale(locale) @@ -595,14 +595,14 @@ def encode(self, text: str) -> List[int]: def encode_from_g2p(self, g2p_text: List[str], raw_text: Optional[str] = None) -> List[int]: """ - Tokenize the `g2p_text` that has been already run through G2P_paper. Each item in the `g2p_text` would be encoded as + Tokenize the `g2p_text` that has been already run through G2P. Each item in the `g2p_text` would be encoded as one of the integer IDs predefined in `self._token2id`. Note that this function should be called after `self.text_preprocessing_func` and `self.g2p` functions Args: - g2p_text (List[str]): a sequence of tokens from G2P_paper's output. It could be a sequence of phonemes, a sequence + g2p_text (List[str]): a sequence of tokens from G2P's output. It could be a sequence of phonemes, a sequence of graphemes, or a mixture of both. For example, `['ˈ', 's', 'i', ' ', '#O', '#O', '#V']`, which is the - G2P_paper's output of the text "see OOV", where '#' is prepended to each grapheme in order to distinguish + G2P's output of the text "see OOV", where '#' is prepended to each grapheme in order to distinguish graphemes from phonemes if there are overlaps in between. The prefix '#' can be customized in `nemo.collections.tts.g2p.modules.IPAG2P.grapheme_prefix`. raw_text (str): the original text after calling `self.text_preprocessing_func`. It is optional. It is only @@ -731,11 +731,11 @@ def encode(self, text): def encode_from_g2p(self, g2p_text: List[str], raw_text: Optional[str] = None): """ - Encodes text that has already been run through G2P_paper. - Called for encoding to tokens after text preprocessing and G2P_paper. + Encodes text that has already been run through G2Pr. + Called for encoding to tokens after text preprocessing and G2P. Args: - g2p_text: G2P_paper's output, could be a mixture of Chinese phonemes and English letters. + g2p_text: G2P's output, could be a mixture of Chinese phonemes and English letters. raw_text: original raw input """ ps, space, tokens = [], self.tokens[self.space], set(self.tokens) diff --git a/nemo/collections/tts/g2p/data/ctc_g2p.py b/nemo/collections/tts/g2p/data/ctc_g2p.py index 6b0052db6996..792a92a10fa6 100644 --- a/nemo/collections/tts/g2p/data/ctc_g2p.py +++ b/nemo/collections/tts/g2p/data/ctc_g2p.py @@ -37,7 +37,7 @@ def __init__( with_labels: bool = True, ): """ - Creates a dataset to train a CTC-based G2P_paper models. + Creates a dataset to train a CTC-based G2P models. Args: manifest_filepath: path to a .json manifest that contains "phoneme_field" and "grapheme_field" diff --git a/nemo/collections/tts/g2p/data/t5_g2p.py b/nemo/collections/tts/g2p/data/t5_g2p.py index 200d057fb0ab..0e4c5f2697b6 100644 --- a/nemo/collections/tts/g2p/data/t5_g2p.py +++ b/nemo/collections/tts/g2p/data/t5_g2p.py @@ -40,7 +40,7 @@ def __init__( with_labels: bool = True, ): """ - Dataset to train T5-based G2P_paper generative model. + Dataset to train T5-based G2P generative model. Args: manifest_filepath: path to a .json manifest that contains "phoneme_field" and "grapheme_field" diff --git a/nemo/collections/tts/g2p/modules.py b/nemo/collections/tts/g2p/modules.py index 67b0f901cf0d..219d595ec05a 100644 --- a/nemo/collections/tts/g2p/modules.py +++ b/nemo/collections/tts/g2p/modules.py @@ -102,7 +102,7 @@ def __init__( phoneme_probability: Optional[float] = None, mapping_file: Optional[str] = None, ): - """English G2P_paper module. This module converts words from grapheme to phoneme representation using phoneme_dict in CMU dict format. + """English G2P module. This module converts words from grapheme to phoneme representation using phoneme_dict in CMU dict format. Optionally, it can ignore words which are heteronyms, ambiguous or marked as unchangeable by word_tokenize_func (see code for details). Ignored words are left unchanged or passed through apply_to_oov_word for handling. Args: @@ -310,7 +310,7 @@ def __init__( mapping_file: Optional[str] = None, ) -> None: """ - Generic IPA G2P_paper module. This module converts words from graphemes to International Phonetic Alphabet + Generic IPA G2P module. This module converts words from graphemes to International Phonetic Alphabet representations. Optionally, it can ignore heteronyms, ambiguous words, or words marked as unchangeable by `word_tokenize_func` (see code for details). Ignored words are left unchanged or passed through `apply_to_oov_word` for handling. @@ -683,7 +683,7 @@ def __init__( mapping_file: Optional[str] = None, word_segmenter: Optional[str] = None, ): - """Chinese G2P_paper module. This module first converts Chinese characters into pinyin sequences using pypinyin, then pinyin sequences would + """Chinese G2P module. This module first converts Chinese characters into pinyin sequences using pypinyin, then pinyin sequences would be further converted into phoneme sequences using pinyin_dict_nv_22.10.txt dict file. For Chinese and English bilingual sentences, the English words would be converted into letters. Args: diff --git a/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py b/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py index 28f9cdd4e499..0819dc8384ce 100644 --- a/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py +++ b/scripts/dataset_processing/g2p/export_wikihomograph_data_to_manifest.py @@ -125,8 +125,8 @@ def correct_wikihomograph_data(sentence: str, start: int = None, end: int = None if sentence in corrections: start, end = corrections[sentence] - sentence = sentence.replace("2014Coordinate", "2014 Coordinate") # for normalized data for G2P_paper OOV models - sentence = sentence.replace("AAA", "triple A") # for normalized data for G2P_paper OOV models + sentence = sentence.replace("2014Coordinate", "2014 Coordinate") # for normalized data for G2P OOV models + sentence = sentence.replace("AAA", "triple A") # for normalized data for G2P OOV models return sentence, start, end

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