diff --git a/utils/audio.py b/utils/audio.py index 663fbd0a..1fcf7752 100644 --- a/utils/audio.py +++ b/utils/audio.py @@ -37,8 +37,8 @@ class AudioProcessor(object): def _build_mel_basis(self, ): n_fft = (self.num_freq - 1) * 2 - return librosa.filters.mel(self.sample_rate, n_fft, n_mels=self.num_mels, - fmin=self.min_mel_freq, fmax=self.max_mel_freq) + return librosa.filters.mel(self.sample_rate, n_fft, n_mels=self.num_mels) + # fmin=self.min_mel_freq, fmax=self.max_mel_freq) def _normalize(self, S): return np.clip((S - self.min_level_db) / -self.min_level_db, 0, 1) @@ -54,20 +54,20 @@ class AudioProcessor(object): def _amp_to_db(self, x): min_level = np.exp(self.min_level_db / 20 * np.log(10)) - return 20 * np.log10(np.maximum(1e-5, x)) + return 20 * np.log10(np.maximum(min_level, x)) def _db_to_amp(self, x): return np.power(10.0, x * 0.05) - # def apply_preemphasis(self, x): - # return signal.lfilter([1, -self.preemphasis], [1], x) - # - # def apply_inv_preemphasis(self, x): - # return signal.lfilter([1], [1, -self.preemphasis], x) + def apply_preemphasis(self, x): + return signal.lfilter([1, -0.97], [1], x) + + def apply_inv_preemphasis(self, x): + return signal.lfilter([1], [1, -0.97], x) def spectrogram(self, y): - # D = self._stft(self.apply_preemphasis(y)) - D = self._stft(y) + D = self._stft(self.apply_preemphasis(y)) + # D = self._stft(apply_preemphasis(y)) S = self._amp_to_db(np.abs(D)) - self.ref_level_db return self._normalize(S) @@ -76,8 +76,8 @@ class AudioProcessor(object): 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)) - return self._griffin_lim(S ** self.power) + return self.apply_inv_preemphasis(self._griffin_lim(S ** self.power)) + # return self._griffin_lim(S ** self.power) # def _griffin_lim(self, S): # '''librosa implementation of Griffin-Lim @@ -105,7 +105,7 @@ class AudioProcessor(object): return y def melspectrogram(self, y): - D = self._stft(y) + D = self._stft(self.apply_preemphasis(y)) S = self._amp_to_db(self._linear_to_mel(np.abs(D))) - self.ref_level_db return self._normalize(S)