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| | | import soundfile |
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| | | from funasr_onnx import Fsmn_vad |
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| | | model_dir = "/Users/zhifu/Downloads/speech_fsmn_vad_zh-cn-16k-common-pytorch" |
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| | | wav_path = "/Users/zhifu/Downloads/speech_fsmn_vad_zh-cn-16k-common-pytorch/example/vad_example.wav" |
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| | | model = Fsmn_vad(model_dir) |
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| | | wav_path = "/Users/zhifu/Downloads/speech_fsmn_vad_zh-cn-16k-common-pytorch/example/vad_example.wav" |
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| | | #offline vad |
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| | | # result = model(wav_path) |
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| | | # print(result) |
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| | | result = model(wav_path) |
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| | | print(result) |
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| | | #online vad |
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| | | speech, sample_rate = soundfile.read(wav_path) |
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| | | speech_length = speech.shape[0] |
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| | | sample_offset = 0 |
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| | | step = 160 * 10 |
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| | | param_dict = {'in_cache': []} |
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| | | for sample_offset in range(0, speech_length, min(step, speech_length - sample_offset)): |
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| | | if sample_offset + step >= speech_length - 1: |
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| | | step = speech_length - sample_offset |
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| | | is_final = True |
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| | | else: |
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| | | is_final = False |
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| | | param_dict['is_final'] = is_final |
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| | | segments_result = model(audio_in=speech[sample_offset: sample_offset + step], |
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| | | param_dict=param_dict) |
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| | | print(segments_result) |
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