mirror of https://github.com/coqui-ai/TTS.git
Optional silence trimming during inference and find_endpoint() fix (#898)
* Set find_endpoint db threshold in config.json * Optional silence trimming during inference * Make trim_db value negative
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@ -674,7 +674,7 @@ class AudioProcessor(object):
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return f0
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return f0
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### Audio Processing ###
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### Audio Processing ###
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def find_endpoint(self, wav: np.ndarray, threshold_db=-40, min_silence_sec=0.8) -> int:
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def find_endpoint(self, wav: np.ndarray, min_silence_sec=0.8) -> int:
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"""Find the last point without silence at the end of a audio signal.
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"""Find the last point without silence at the end of a audio signal.
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Args:
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Args:
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@ -687,7 +687,7 @@ class AudioProcessor(object):
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"""
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"""
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window_length = int(self.sample_rate * min_silence_sec)
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window_length = int(self.sample_rate * min_silence_sec)
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hop_length = int(window_length / 4)
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hop_length = int(window_length / 4)
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threshold = self._db_to_amp(threshold_db)
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threshold = self._db_to_amp(-self.trim_db)
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for x in range(hop_length, len(wav) - window_length, hop_length):
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for x in range(hop_length, len(wav) - window_length, hop_length):
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if np.max(wav[x : x + window_length]) < threshold:
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if np.max(wav[x : x + window_length]) < threshold:
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return x + hop_length
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return x + hop_length
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@ -265,7 +265,8 @@ class Synthesizer(object):
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waveform = waveform.squeeze()
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waveform = waveform.squeeze()
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# trim silence
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# trim silence
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waveform = trim_silence(waveform, self.ap)
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if self.tts_config.audio["do_trim_silence"] is True:
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waveform = trim_silence(waveform, self.ap)
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wavs += list(waveform)
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wavs += list(waveform)
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wavs += [0] * 10000
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wavs += [0] * 10000
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