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Add C++ runtime for non-streaming faster conformer transducer from Ne…
…Mo. (k2-fsa#854)
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#!/usr/bin/env python3 | ||
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""" | ||
This file shows how to use a non-streaming CTC model from NeMo | ||
to decode files. | ||
Please download model files from | ||
https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models | ||
The example model supports 10 languages and it is converted from | ||
https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_multilingual_fastconformer_hybrid_large_pc | ||
""" | ||
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from pathlib import Path | ||
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import sherpa_onnx | ||
import soundfile as sf | ||
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def create_recognizer(): | ||
model = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/model.onnx" | ||
tokens = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/tokens.txt" | ||
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test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/de-german.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/en-english.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/es-spanish.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/fr-french.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/hr-croatian.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/it-italian.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/po-polish.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/ru-russian.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/uk-ukrainian.wav" | ||
|
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if not Path(model).is_file() or not Path(test_wav).is_file(): | ||
raise ValueError( | ||
"""Please download model files from | ||
https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models | ||
""" | ||
) | ||
return ( | ||
sherpa_onnx.OfflineRecognizer.from_nemo_ctc( | ||
model=model, | ||
tokens=tokens, | ||
debug=True, | ||
), | ||
test_wav, | ||
) | ||
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||
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def main(): | ||
recognizer, wave_filename = create_recognizer() | ||
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audio, sample_rate = sf.read(wave_filename, dtype="float32", always_2d=True) | ||
audio = audio[:, 0] # only use the first channel | ||
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# audio is a 1-D float32 numpy array normalized to the range [-1, 1] | ||
# sample_rate does not need to be 16000 Hz | ||
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stream = recognizer.create_stream() | ||
stream.accept_waveform(sample_rate, audio) | ||
recognizer.decode_stream(stream) | ||
print(wave_filename) | ||
print(stream.result) | ||
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if __name__ == "__main__": | ||
main() |
73 changes: 73 additions & 0 deletions
73
python-api-examples/offline-nemo-transducer-decode-files.py
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,73 @@ | ||
#!/usr/bin/env python3 | ||
|
||
""" | ||
This file shows how to use a non-streaming transducer model from NeMo | ||
to decode files. | ||
Please download model files from | ||
https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models | ||
The example model supports 10 languages and it is converted from | ||
https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_multilingual_fastconformer_hybrid_large_pc | ||
""" | ||
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from pathlib import Path | ||
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import sherpa_onnx | ||
import soundfile as sf | ||
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def create_recognizer(): | ||
encoder = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/encoder.onnx" | ||
decoder = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/decoder.onnx" | ||
joiner = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/joiner.onnx" | ||
tokens = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/tokens.txt" | ||
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test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/de-german.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/en-english.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/es-spanish.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/fr-french.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/hr-croatian.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/it-italian.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/po-polish.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/ru-russian.wav" | ||
# test_wav = "./sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/test_wavs/uk-ukrainian.wav" | ||
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if not Path(encoder).is_file() or not Path(test_wav).is_file(): | ||
raise ValueError( | ||
"""Please download model files from | ||
https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models | ||
""" | ||
) | ||
return ( | ||
sherpa_onnx.OfflineRecognizer.from_transducer( | ||
encoder=encoder, | ||
decoder=decoder, | ||
joiner=joiner, | ||
tokens=tokens, | ||
model_type="nemo_transducer", | ||
debug=True, | ||
), | ||
test_wav, | ||
) | ||
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def main(): | ||
recognizer, wave_filename = create_recognizer() | ||
|
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audio, sample_rate = sf.read(wave_filename, dtype="float32", always_2d=True) | ||
audio = audio[:, 0] # only use the first channel | ||
|
||
# audio is a 1-D float32 numpy array normalized to the range [-1, 1] | ||
# sample_rate does not need to be 16000 Hz | ||
|
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stream = recognizer.create_stream() | ||
stream.accept_waveform(sample_rate, audio) | ||
recognizer.decode_stream(stream) | ||
print(wave_filename) | ||
print(stream.result) | ||
|
||
|
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if __name__ == "__main__": | ||
main() |
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