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self.power = 1.5 | |
self.max_norm = 1.0 | |
self.preemphasis = 0.97 | |
self.ref_level_db = 20 | |
self.min_level_db = -100 | |
""" | |
Need to implement: | |
>>> np.clip | |
>>> np.power | |
>>> signal.lfilter | |
""" | |
def inv_spectrogram(self, spectrogram): | |
"""Converts spectrogram to waveform using librosa""" | |
S = self._denormalize(spectrogram) | |
S = self._db_to_amp(S + self.ref_level_db) # Convert back to linear | |
# Reconstruct phase | |
return self.apply_inv_preemphasis(self._griffin_lim(S**self.power)) | |
def _denormalize(self, S): | |
"""denormalize values""" | |
S_denorm = S | |
S_denorm = np.clip(S_denorm, 0, self.max_norm) | |
S_denorm = (S_denorm * -self.min_level_db / self.max_norm) + self.min_level_db | |
return S_denorm | |
def _db_to_amp(self, x): | |
return np.power(10.0, x * 0.05) | |
# 对经过Griffin Lim合成出的audio wav, 使用preemphasis. | |
def apply_inv_preemphasis(self, x): | |
return signal.lfilter([1], [1, -self.preemphasis], x) | |
########### 这个C++里已有实现 ############ | |
def _griffin_lim(self, S): | |
angles = np.exp(2j * np.pi * np.random.rand(*S.shape)) | |
S_complex = np.abs(S).astype(np.complex) | |
y = self._istft(S_complex * angles) | |
for i in range(self.griffin_lim_iters): | |
angles = np.exp(1j * np.angle(self._stft(y))) | |
y = self._istft(S_complex * angles) | |
return y | |
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