# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import librosa
import numpy as np
import soundfile as sf
__all__ = ["AudioProcessor"]
[docs]class AudioProcessor(object):
def __init__(self,
sample_rate: int,
n_fft: int,
win_length: int,
hop_length: int,
n_mels: int=80,
fmin: int=0,
fmax: int=None,
window="hann",
center=True,
pad_mode="reflect",
normalize=True):
# read & write
self.sample_rate = sample_rate
self.normalize = normalize
# stft
self.n_fft = n_fft
self.win_length = win_length
self.hop_length = hop_length
self.window = window
self.center = center
self.pad_mode = pad_mode
# mel
self.n_mels = n_mels
self.fmin = fmin
self.fmax = fmax
self.mel_filter = self._create_mel_filter()
self.inv_mel_filter = np.linalg.pinv(self.mel_filter)
def _create_mel_filter(self):
mel_filter = librosa.filters.mel(
sr=self.sample_rate,
n_fft=self.n_fft,
n_mels=self.n_mels,
fmin=self.fmin,
fmax=self.fmax)
return mel_filter
[docs] def read_wav(self, filename):
# resampling may occur
wav, _ = librosa.load(filename, sr=self.sample_rate)
# normalize the volume
if self.normalize:
wav = wav / np.max(np.abs(wav)) * 0.999
return wav
[docs] def write_wav(self, path, wav):
sf.write(path, wav, samplerate=self.sample_rate)
[docs] def stft(self, wav):
D = librosa.core.stft(
wav,
n_fft=self.n_fft,
hop_length=self.hop_length,
win_length=self.win_length,
window=self.window,
center=self.center,
pad_mode=self.pad_mode)
return D
[docs] def istft(self, D):
wav = librosa.core.istft(
D,
hop_length=self.hop_length,
win_length=self.win_length,
window=self.window,
center=self.center)
return wav
[docs] def spectrogram(self, wav):
D = self.stft(wav)
return np.abs(D)
[docs] def mel_spectrogram(self, wav):
S = self.spectrogram(wav)
mel = np.dot(self.mel_filter, S)
return mel