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| | | |
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| | | |
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| | | class E2EVadModel(nn.Module): |
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| | | def __init__(self, encoder: FSMN, vad_post_args: Dict[str, Any]): |
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| | | def __init__(self, encoder: FSMN, vad_post_args: Dict[str, Any], frontend=None): |
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| | | super(E2EVadModel, self).__init__() |
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| | | self.vad_opts = VADXOptions(**vad_post_args) |
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| | | self.windows_detector = WindowDetector(self.vad_opts.window_size_ms, |
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| | |
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| | | self.data_buf_all = None |
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| | | self.waveform = None |
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| | | self.ResetDetection() |
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| | | self.frontend = frontend |
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| | | |
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| | | def AllResetDetection(self): |
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| | | self.is_final = False |
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| | |
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| | | ) -> Tuple[List[List[List[int]]], Dict[str, torch.Tensor]]: |
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| | | self.max_end_sil_frame_cnt_thresh = max_end_sil - self.vad_opts.speech_to_sil_time_thres |
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| | | self.waveform = waveform # compute decibel for each frame |
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| | | self.ComputeDecibel() |
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| | | |
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| | | self.ComputeScores(feats, in_cache) |
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| | | self.ComputeDecibel() |
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| | | if not is_final: |
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| | | self.DetectCommonFrames() |
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| | | else: |
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