mirror of https://github.com/coqui-ai/TTS.git
Audio.py check and remove redundant code
parent
ecd31af125
commit
f1271b4ce8
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@ -21,7 +21,7 @@
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"eval_batch_size":-1,
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"r": 5,
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"griffin_lim_iters": 50,
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"griffin_lim_iters": 60,
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"power": 1.5,
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"num_loader_workers": 8,
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@ -66,8 +66,6 @@ class AudioProcessor(object):
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n_fft = (self.num_freq - 1) * 2
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hop_length = int(self.frame_shift_ms / 1000.0 * self.sample_rate)
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win_length = int(self.frame_length_ms / 1000.0 * self.sample_rate)
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hop_length = 256
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win_length = 1024
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print(" | > fft size: {}, hop length: {}, win length: {}".format(
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n_fft, hop_length, win_length))
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return n_fft, hop_length, win_length
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@ -107,17 +105,26 @@ class AudioProcessor(object):
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else:
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return self._griffin_lim(S**self.power)
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# def _griffin_lim(self, S):
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# '''Applies Griffin-Lim's raw.
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# '''
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# S_best = copy.deepcopy(S)
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# for i in range(self.griffin_lim_iters):
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# S_t = self._istft(S_best)
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# est = self._stft(S_t)
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# phase = est / np.maximum(1e-8, np.abs(est))
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# S_best = S * phase
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# S_t = self._istft(S_best)
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# y = np.real(S_t)
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# return y
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def _griffin_lim(self, S):
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'''Applies Griffin-Lim's raw.
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'''
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S_best = copy.deepcopy(S)
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angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
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S_complex = np.abs(S).astype(np.complex)
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y = self._istft(S_complex * angles)
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for i in range(self.griffin_lim_iters):
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S_t = self._istft(S_best)
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est = self._stft(S_t)
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phase = est / np.maximum(1e-8, np.abs(est))
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S_best = S * phase
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S_t = self._istft(S_best)
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y = np.real(S_t)
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angles = np.exp(1j * np.angle(self._stft(y)))
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y = self._istft(S_complex * angles)
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return y
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def melspectrogram(self, y):
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