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Update doc to add two onnx pre-trained models. (#515)
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csukuangfj authored Dec 12, 2023
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20 changes: 20 additions & 0 deletions ...ls/offline-transducer/code-zipformer/sherpa-onnx-zipformer-gigaspeech-2023-12-12-int8.txt
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/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt --encoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.int8.onnx --decoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx --joiner=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.int8.onnx ./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1089-134686-0001.wav ./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0001.wav ./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0002.wav

OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.int8.onnx", decoder_filename="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx", joiner_filename="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.int8.onnx"), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), tokens="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt", num_threads=2, debug=False, provider="cpu", model_type=""), lm_config=OfflineLMConfig(model="", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5)
Creating recognizer ...
Started
Done!

./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1089-134686-0001.wav
{"text": " AFTER EARLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROTHELS", "timestamps": [0.00, 0.36, 0.52, 0.68, 0.96, 1.00, 1.08, 1.28, 1.40, 1.48, 1.60, 1.76, 1.80, 1.88, 1.92, 2.00, 2.20, 2.32, 2.36, 2.48, 2.60, 2.80, 2.84, 2.92, 3.12, 3.32, 3.56, 3.76, 4.04, 4.24, 4.32, 4.40, 4.56, 4.80, 4.92, 5.08, 5.36, 5.48, 5.64, 5.72, 5.88, 6.04, 6.24], "tokens":[" AFTER", " E", "AR", "LY", " ", "N", "IGHT", "F", "AL", "L", " THE", " ", "Y", "E", "LL", "OW", " LA", "M", "P", "S", " WOULD", " ", "L", "IGHT", " UP", " HERE", " AND", " THERE", " THE", " S", "QU", "AL", "ID", " QU", "AR", "TER", " OF", " THE", " B", "RO", "TH", "EL", "S"]}
----
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0001.wav
{"text": " GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENT FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN", "timestamps": [0.00, 0.16, 0.40, 0.68, 0.84, 0.96, 1.08, 1.12, 1.32, 1.52, 1.68, 1.76, 2.00, 2.12, 2.28, 2.40, 2.64, 2.92, 3.20, 3.32, 3.52, 3.64, 3.76, 3.96, 4.12, 4.36, 4.52, 4.72, 4.92, 5.16, 5.40, 5.64, 5.76, 5.88, 6.12, 6.28, 6.52, 6.84, 7.08, 7.32, 7.60, 7.92, 8.12, 8.24, 8.36, 8.48, 8.64, 8.76, 8.88, 9.12, 9.32, 9.48, 9.56, 9.60, 9.76, 10.00, 10.12, 10.20, 10.44, 10.68, 10.80, 11.00, 11.20, 11.36, 11.52, 11.76, 12.00, 12.12, 12.24, 12.28, 12.52, 12.72, 12.84, 12.96, 13.04, 13.24, 13.44, 13.64, 13.76, 14.00, 14.08, 14.24, 14.52, 14.68, 14.80, 15.00, 15.04, 15.28, 15.48, 15.76, 16.00, 16.12, 16.16, 16.32], "tokens":[" GO", "D", " AS", " A", " DI", "RE", "C", "T", " CON", "SE", "QU", "ENCE", " OF", " THE", " S", "IN", " WHICH", " MAN", " TH", "US", " P", "UN", "ISH", "ED", " HAD", " GIVE", "N", " HER", " A", " LOVE", "LY", " CHI", "L", "D", " WHO", "SE", " PLACE", " WAS", " ON", " THAT", " SAME", " DIS", "HO", "N", "OR", "ED", " BO", "S", "OM", " TO", " CON", "NE", "C", "T", " HER", " PA", "R", "ENT", " FOR", " E", "VER", " WITH", " THE", " RA", "CE", " AND", " DE", "S", "C", "ENT", " OF", " MO", "R", "T", "AL", "S", " AND", " TO", " BE", " F", "IN", "ALLY", " A", " B", "LES", "S", "ED", " SO", "UL", " IN", " HE", "A", "VE", "N"]}
----
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0002.wav
{"text": " YET THESE THOUGHTS AFFECTED HESTER PRYNNE LESS WITH HOPE THAN APPREHENSION", "timestamps": [0.00, 0.04, 0.12, 0.40, 0.68, 0.88, 0.96, 1.12, 1.24, 1.32, 1.44, 1.48, 1.64, 1.76, 1.88, 2.04, 2.16, 2.28, 2.32, 2.52, 2.68, 2.72, 2.88, 3.12, 3.32, 3.52, 3.80, 4.00, 4.16, 4.24, 4.40, 4.48], "tokens":[" ", "Y", "ET", " THESE", " THOUGH", "T", "S", " A", "FF", "E", "C", "TED", " HE", "S", "TER", " P", "RY", "N", "NE", " LE", "S", "S", " WITH", " HO", "PE", " THAN", " APP", "RE", "HE", "N", "S", "ION"]}
----
num threads: 2
decoding method: greedy_search
Elapsed seconds: 1.101 s
Real time factor (RTF): 1.101 / 28.165 = 0.039
20 changes: 20 additions & 0 deletions ..._models/offline-transducer/code-zipformer/sherpa-onnx-zipformer-gigaspeech-2023-12-12.txt
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/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt --encoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.onnx --decoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx --joiner=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.onnx ./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1089-134686-0001.wav ./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0001.wav ./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0002.wav

OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.onnx", decoder_filename="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx", joiner_filename="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.onnx"), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), tokens="./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt", num_threads=2, debug=False, provider="cpu", model_type=""), lm_config=OfflineLMConfig(model="", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5)
Creating recognizer ...
Started
Done!

./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1089-134686-0001.wav
{"text": " AFTER EARLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROTHELS", "timestamps": [0.00, 0.36, 0.52, 0.68, 0.96, 1.00, 1.08, 1.28, 1.40, 1.48, 1.60, 1.76, 1.80, 1.88, 1.92, 2.00, 2.20, 2.32, 2.36, 2.48, 2.60, 2.80, 2.84, 2.92, 3.12, 3.32, 3.56, 3.76, 4.04, 4.20, 4.32, 4.40, 4.56, 4.80, 4.92, 5.08, 5.36, 5.48, 5.64, 5.72, 5.88, 6.04, 6.24], "tokens":[" AFTER", " E", "AR", "LY", " ", "N", "IGHT", "F", "AL", "L", " THE", " ", "Y", "E", "LL", "OW", " LA", "M", "P", "S", " WOULD", " ", "L", "IGHT", " UP", " HERE", " AND", " THERE", " THE", " S", "QU", "AL", "ID", " QU", "AR", "TER", " OF", " THE", " B", "RO", "TH", "EL", "S"]}
----
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0001.wav
{"text": " GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENT FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN", "timestamps": [0.00, 0.16, 0.40, 0.68, 0.84, 0.96, 1.04, 1.12, 1.32, 1.52, 1.68, 1.76, 2.00, 2.12, 2.28, 2.40, 2.64, 2.92, 3.20, 3.32, 3.52, 3.64, 3.76, 3.96, 4.12, 4.36, 4.52, 4.72, 4.92, 5.16, 5.40, 5.64, 5.76, 5.88, 6.12, 6.28, 6.48, 6.84, 7.08, 7.32, 7.60, 7.92, 8.12, 8.24, 8.36, 8.48, 8.64, 8.76, 8.88, 9.12, 9.32, 9.48, 9.56, 9.60, 9.76, 10.00, 10.12, 10.20, 10.44, 10.68, 10.80, 11.00, 11.20, 11.36, 11.52, 11.76, 12.00, 12.12, 12.24, 12.28, 12.52, 12.72, 12.84, 12.96, 13.04, 13.24, 13.40, 13.64, 13.76, 14.00, 14.08, 14.24, 14.52, 14.68, 14.80, 15.00, 15.04, 15.28, 15.52, 15.76, 16.00, 16.12, 16.20, 16.32], "tokens":[" GO", "D", " AS", " A", " DI", "RE", "C", "T", " CON", "SE", "QU", "ENCE", " OF", " THE", " S", "IN", " WHICH", " MAN", " TH", "US", " P", "UN", "ISH", "ED", " HAD", " GIVE", "N", " HER", " A", " LOVE", "LY", " CHI", "L", "D", " WHO", "SE", " PLACE", " WAS", " ON", " THAT", " SAME", " DIS", "HO", "N", "OR", "ED", " BO", "S", "OM", " TO", " CON", "NE", "C", "T", " HER", " PA", "R", "ENT", " FOR", " E", "VER", " WITH", " THE", " RA", "CE", " AND", " DE", "S", "C", "ENT", " OF", " MO", "R", "T", "AL", "S", " AND", " TO", " BE", " F", "IN", "ALLY", " A", " B", "LES", "S", "ED", " SO", "UL", " IN", " HE", "A", "VE", "N"]}
----
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0002.wav
{"text": " YET THESE THOUGHTS AFFECTED HESTER PRYNE LESS WITH HOPE THAN APPREHENSION", "timestamps": [0.00, 0.04, 0.12, 0.40, 0.68, 0.88, 0.96, 1.12, 1.20, 1.32, 1.44, 1.48, 1.64, 1.76, 1.88, 2.04, 2.16, 2.28, 2.52, 2.68, 2.72, 2.88, 3.12, 3.28, 3.52, 3.80, 4.00, 4.16, 4.24, 4.40, 4.48], "tokens":[" ", "Y", "ET", " THESE", " THOUGH", "T", "S", " A", "FF", "E", "C", "TED", " HE", "S", "TER", " P", "RY", "NE", " LE", "S", "S", " WITH", " HO", "PE", " THAN", " APP", "RE", "HE", "N", "S", "ION"]}
----
num threads: 2
decoding method: greedy_search
Elapsed seconds: 1.407 s
Real time factor (RTF): 1.407 / 28.165 = 0.050
125 changes: 125 additions & 0 deletions ...ource/onnx/pretrained_models/offline-transducer/zipformer-transducer-models.rst
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Expand Up @@ -8,6 +8,131 @@ Zipformer-transducer-based Models
Please refer to :ref:`install_sherpa_onnx` to install `sherpa-onnx`
before you read this section.


sherpa-onnx-zipformer-gigaspeech-2023-12-12 (English)
-----------------------------------------------------

Training code for this model is `<https://github.com/k2-fsa/icefall/pull/1254>`_.
It supports only English since it is trained on the `GigaSpeech`_ dataset.

In the following, we describe how to download it and use it with `sherpa-onnx`_.

Download the model
~~~~~~~~~~~~~~~~~~

Please use the following commands to download it.

.. code-block:: bash
wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-zipformer-gigaspeech-2023-12-12.tar.bz2
tar xf sherpa-onnx-zipformer-gigaspeech-2023-12-12.tar.bz2
ls -lh sherpa-onnx-zipformer-gigaspeech-2023-12-12
You should see the following output:

.. code-block:: bash
$ ls -lh sherpa-onnx-zipformer-gigaspeech-2023-12-12
total 656184
-rw-r--r-- 1 fangjun staff 28B Dec 12 19:00 README.md
-rw-r--r-- 1 fangjun staff 239K Dec 12 19:00 bpe.model
-rw-r--r-- 1 fangjun staff 528K Dec 12 19:00 decoder-epoch-30-avg-1.int8.onnx
-rw-r--r-- 1 fangjun staff 2.0M Dec 12 19:00 decoder-epoch-30-avg-1.onnx
-rw-r--r-- 1 fangjun staff 68M Dec 12 19:00 encoder-epoch-30-avg-1.int8.onnx
-rw-r--r-- 1 fangjun staff 249M Dec 12 19:00 encoder-epoch-30-avg-1.onnx
-rw-r--r-- 1 fangjun staff 253K Dec 12 19:00 joiner-epoch-30-avg-1.int8.onnx
-rw-r--r-- 1 fangjun staff 1.0M Dec 12 19:00 joiner-epoch-30-avg-1.onnx
drwxr-xr-x 5 fangjun staff 160B Dec 12 19:00 test_wavs
-rw-r--r-- 1 fangjun staff 4.9K Dec 12 19:00 tokens.txt
Decode wave files
~~~~~~~~~~~~~~~~~

.. hint::

It supports decoding only wave files of a single channel with 16-bit
encoded samples, while the sampling rate does not need to be 16 kHz.

fp32
^^^^

The following code shows how to use ``fp32`` models to decode wave files:

.. code-block:: bash
cd /path/to/sherpa-onnx
./build/bin/sherpa-onnx-offline \
--tokens=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt \
--encoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.onnx \
--decoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx \
--joiner=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.onnx \
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1089-134686-0001.wav \
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0001.wav \
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0002.wav
.. note::

Please use ``./build/bin/Release/sherpa-onnx-offline.exe`` for Windows.

You should see the following output:

.. literalinclude:: ./code-zipformer/sherpa-onnx-zipformer-gigaspeech-2023-12-12.txt

int8
^^^^

The following code shows how to use ``int8`` models to decode wave files:

.. code-block:: bash
cd /path/to/sherpa-onnx
./build/bin/sherpa-onnx-offline \
--tokens=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt \
--encoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.int8.onnx \
--decoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx \
--joiner=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.int8.onnx \
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1089-134686-0001.wav \
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0001.wav \
./sherpa-onnx-zipformer-gigaspeech-2023-12-12/test_wavs/1221-135766-0002.wav
.. note::

Please use ``./build/bin/Release/sherpa-onnx-offline.exe`` for Windows.

You should see the following output:

.. literalinclude:: ./code-zipformer/sherpa-onnx-zipformer-gigaspeech-2023-12-12-int8.txt

Speech recognition from a microphone
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code-block:: bash
cd /path/to/sherpa-onnx
./build/bin/sherpa-onnx-microphone-offline \
--tokens=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt \
--encoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.int8.onnx \
--decoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx \
--joiner=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.int8.onnx
Speech recognition from a microphone with VAD
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code-block:: bash
cd /path/to/sherpa-onnx
wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
./build/bin/sherpa-onnx-vad-microphone-offline-asr \
--silero-vad-model=./silero_vad.onnx \
--tokens=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/tokens.txt \
--encoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.int8.onnx \
--decoder=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx \
--joiner=./sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.int8.onnx
zrjin/sherpa-onnx-zipformer-multi-zh-hans-2023-9-2 (Chinese)
------------------------------------------------------------

Expand Down
8 changes: 8 additions & 0 deletions ...ansducer/code-zipformer/sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12-int8.txt
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/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./build/bin/sherpa-onnx --tokens=./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/tokens.txt --encoder=./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx --decoder=./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/decoder-epoch-20-avg-1-chunk-16-left-128.onnx --joiner=./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx ./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/test_wavs/DEV_T0000000000.wav

OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder="./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx", decoder="./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/decoder-epoch-20-avg-1-chunk-16-left-128.onnx", joiner="./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx"), paraformer=OnlineParaformerModelConfig(encoder="", decoder=""), wenet_ctc=OnlineWenetCtcModelConfig(model="", chunk_size=16, num_left_chunks=4), tokens="./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type=""), lm_config=OnlineLMConfig(model="", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file="", decoding_method="greedy_search")
./sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12/test_wavs/DEV_T0000000000.wav
Elapsed seconds: 0.5, Real time factor (RTF): 0.088
对我做了介绍那么我想说的是大家如果对我的研究感兴趣
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