Medix-AI/coqui-tts
Medix-AI
/
coqui-tts
mirror of https://github.com/coqui-ai/TTS.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

refactor(audio.processor): remove duplicate amp_to_db

This commit is contained in:
Enno Hermann 2023-11-13 21:54:02 +01:00
parent 794f41c611
commit 4fd5c46937
1 changed files with 4 additions and 29 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
TTS/utils/audio/processor.py
View File

@ -8,7 +8,7 @@ import scipy.signal
import soundfile as sf import soundfile as sf
from TTS.tts.utils.helpers import StandardScaler from TTS.tts.utils.helpers import StandardScaler
from TTS.utils.audio.numpy_transforms import compute_f0, db_to_amp, stft, griffin_lim from TTS.utils.audio.numpy_transforms import amp_to_db, compute_f0, db_to_amp, stft, griffin_lim
# pylint: disable=too-many-public-methods # pylint: disable=too-many-public-methods
@ -386,19 +386,6 @@ class AudioProcessor(object):
self.linear_scaler = StandardScaler() self.linear_scaler = StandardScaler()
self.linear_scaler.set_stats(linear_mean, linear_std) self.linear_scaler.set_stats(linear_mean, linear_std)
### DB and AMP conversion ###
# pylint: disable=no-self-use
def _amp_to_db(self, x: np.ndarray) -> np.ndarray:
"""Convert amplitude values to decibels.
Args:
x (np.ndarray): Amplitude spectrogram.
Returns:
np.ndarray: Decibels spectrogram.
"""
return self.spec_gain * _log(np.maximum(1e-5, x), self.base)
### Preemphasis ### ### Preemphasis ###
def apply_preemphasis(self, x: np.ndarray) -> np.ndarray: def apply_preemphasis(self, x: np.ndarray) -> np.ndarray:
"""Apply pre-emphasis to the audio signal. Useful to reduce the correlation between neighbouring signal values. """Apply pre-emphasis to the audio signal. Useful to reduce the correlation between neighbouring signal values.
@ -457,7 +444,7 @@ class AudioProcessor(object):
pad_mode=self.stft_pad_mode, pad_mode=self.stft_pad_mode,
) )
if self.do_amp_to_db_linear: if self.do_amp_to_db_linear:
S = self._amp_to_db(np.abs(D)) S = amp_to_db(x=np.abs(D), gain=self.spec_gain, base=self.base)
else: else:
S = np.abs(D) S = np.abs(D)
return self.normalize(S).astype(np.float32) return self.normalize(S).astype(np.float32)
@ -474,7 +461,7 @@ class AudioProcessor(object):
pad_mode=self.stft_pad_mode, pad_mode=self.stft_pad_mode,
) )
if self.do_amp_to_db_mel: if self.do_amp_to_db_mel:
S = self._amp_to_db(self._linear_to_mel(np.abs(D))) S = amp_to_db(x=self._linear_to_mel(np.abs(D)), gain=self.spec_gain, base=self.base)
else: else:
S = self._linear_to_mel(np.abs(D)) S = self._linear_to_mel(np.abs(D))
return self.normalize(S).astype(np.float32) return self.normalize(S).astype(np.float32)
@ -507,7 +494,7 @@ class AudioProcessor(object):
S = self.denormalize(linear_spec) S = self.denormalize(linear_spec)
S = db_to_amp(x=S, gain=self.spec_gain, base=self.base) S = db_to_amp(x=S, gain=self.spec_gain, base=self.base)
S = self._linear_to_mel(np.abs(S)) S = self._linear_to_mel(np.abs(S))
S = self._amp_to_db(S) S = amp_to_db(x=S, gain=self.spec_gain, base=self.base)
mel = self.normalize(S) mel = self.normalize(S)
return mel return mel
@ -721,15 +708,3 @@ class AudioProcessor(object):
def dequantize(x, bits): def dequantize(x, bits):
"""Dequantize a waveform from the given number of bits.""" """Dequantize a waveform from the given number of bits."""
return 2 * x / (2**bits - 1) - 1 return 2 * x / (2**bits - 1) - 1
def _log(x, base):
if base == 10:
return np.log10(x)
return np.log(x)
def _exp(x, base):
if base == 10:
return np.power(10, x)
return np.exp(x)