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Merged
patrickvonplaten merged 3 commits into from
Apr 6, 2022
Merged

[Speech2Text Doc] Fix docs #16611

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95dec59
[Speech2Text Doc] Fix docs
patrickvonplaten Apr 5, 2022
e175213
Merge branch 'main' of https://github.com/huggingface/transformers in…
patrickvonplaten Apr 6, 2022
42f6394
apply ydshiehs suggestions
patrickvonplaten Apr 6, 2022
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33 changes: 10 additions & 23 deletions docs/source/en/model_doc/speech_to_text.mdx
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Expand Up @@ -47,25 +47,19 @@ be installed as follows: `apt install libsndfile1-dev`
>>> import torch
>>> from transformers import Speech2TextProcessor, Speech2TextForConditionalGeneration
>>> from datasets import load_dataset
>>> import soundfile as sf

>>> model = Speech2TextForConditionalGeneration.from_pretrained("facebook/s2t-small-librispeech-asr")
>>> processor = Speech2TextProcessor.from_pretrained("facebook/s2t-small-librispeech-asr")


>>> def map_to_array(batch):
... speech, _ = sf.read(batch["file"])
... batch["speech"] = speech
... return batch
>>> ds = load_dataset("hf-internal-testing/librispeech_asr_demo", "clean", split="validation")


>>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
>>> ds = ds.map(map_to_array)

>>> inputs = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="pt")
>>> generated_ids = model.generate(input_ids=inputs["input_features"], attention_mask=inputs["attention_mask"])
>>> inputs = processor(ds[0]["audio"]["array"], sampling_rate=ds[0]["audio"]["sampling_rate"], return_tensors="pt")
>>> generated_ids = model.generate(inputs["input_features"], attention_mask=inputs["attention_mask"])

>>> transcription = processor.batch_decode(generated_ids)
>>> transcription
['mister quilter is the apostle of the middle classes and we are glad to welcome his gospel']
```

- Multilingual speech translation
Expand All @@ -80,29 +74,22 @@ be installed as follows: `apt install libsndfile1-dev`
>>> import torch
>>> from transformers import Speech2TextProcessor, Speech2TextForConditionalGeneration
>>> from datasets import load_dataset
>>> import soundfile as sf

>>> model = Speech2TextForConditionalGeneration.from_pretrained("facebook/s2t-medium-mustc-multilingual-st")
>>> processor = Speech2TextProcessor.from_pretrained("facebook/s2t-medium-mustc-multilingual-st")

>>> ds = load_dataset("hf-internal-testing/librispeech_asr_demo", "clean", split="validation")

>>> def map_to_array(batch):
... speech, _ = sf.read(batch["file"])
... batch["speech"] = speech
... return batch


>>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
>>> ds = ds.map(map_to_array)

>>> inputs = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="pt")
>>> inputs = processor(ds[0]["audio"]["array"], sampling_rate=ds[0]["audio"]["sampling_rate"], return_tensors="pt")
>>> generated_ids = model.generate(
... input_ids=inputs["input_features"],
... inputs["input_features"],
... attention_mask=inputs["attention_mask"],
... forced_bos_token_id=processor.tokenizer.lang_code_to_id["fr"],
... )

>>> translation = processor.batch_decode(generated_ids)
>>> translation
["<lang:fr> (Vidéo) Si M. Kilder est l'apossible des classes moyennes, et nous sommes heureux d'être accueillis dans son évangile."]
```

See the [model hub](https://huggingface.co/models?filter=speech_to_text) to look for Speech2Text checkpoints.
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1 change: 1 addition & 0 deletions utils/documentation_tests.txt
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@@ -1,5 +1,6 @@
docs/source/en/quicktour.mdx
docs/source/en/task_summary.mdx
docs/source/en/model_doc/speech_to_text.mdx
src/transformers/generation_utils.py
src/transformers/models/bart/modeling_bart.py
src/transformers/models/beit/modeling_beit.py
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