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