mirror of https://github.com/coqui-ai/TTS.git
bumpup librosa version to 0.8.0
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@ -6,13 +6,14 @@ from distutils.dir_util import copy_tree
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from multiprocessing import Pool
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import librosa
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import soundfile as sf
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from tqdm import tqdm
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def resample_file(func_args):
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filename, output_sr = func_args
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y, sr = librosa.load(filename, sr=output_sr)
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librosa.output.write_wav(filename, y, sr)
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sf.write(filename, y, sr)
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if __name__ == "__main__":
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@ -275,7 +275,7 @@ class AudioProcessor(object):
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else:
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D = self._stft(y)
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S = self._amp_to_db(np.abs(D))
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return self.normalize(S)
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return self.normalize(S).astype(np.float32)
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def melspectrogram(self, y):
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if self.preemphasis != 0:
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@ -283,7 +283,7 @@ class AudioProcessor(object):
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else:
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D = self._stft(y)
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S = self._amp_to_db(self._linear_to_mel(np.abs(D)))
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return self.normalize(S)
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return self.normalize(S).astype(np.float32)
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def inv_spectrogram(self, spectrogram):
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"""Converts spectrogram to waveform using librosa"""
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@ -1,2 +1 @@
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bokeh==1.4.0
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numba==0.48
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bokeh==1.4.0
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@ -3,7 +3,7 @@ flask
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gdown
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inflect
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jieba
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librosa==0.7.2
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librosa==0.8.0
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matplotlib
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numpy==1.18.5
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pandas
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