| | |
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| | | |
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| | | model = AutoModel(model="iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", |
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| | | model_revision="v2.0.4", |
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| | | vad_model="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch", |
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| | | vad_model_revision="v2.0.4", |
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| | | punc_model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", |
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| | | punc_model_revision="v2.0.4", |
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| | | # vad_model="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch", |
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| | | # vad_model_revision="v2.0.4", |
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| | | # punc_model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", |
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| | | # punc_model_revision="v2.0.4", |
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| | | # spk_model="damo/speech_campplus_sv_zh-cn_16k-common", |
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| | | # spk_model_revision="v2.0.2", |
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| | | ) |
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| | |
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| | | wav_file = os.path.join(model.model_path, "example/asr_example.wav") |
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| | | speech, sample_rate = soundfile.read(wav_file) |
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| | | res = model.generate(input=[speech], batch_size_s=300, is_final=True) |
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| | | ''' |
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| | | ''' |
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