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ylzz1997 2023-05-29 01:46:18 +08:00
parent e3dc2b2b94
commit 966cb48134
1 changed files with 7 additions and 9 deletions
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16
data_utils.py
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@ -7,7 +7,7 @@ import torch.utils.data
import modules.commons as commons
import utils
from modules.mel_processing import spectrogram_torch, spec_to_mel_torch, mel_spectrogram_torch
from modules.mel_processing import spectrogram_torch, spec_to_mel_torch, spectrogram_torch
from utils import load_wav_to_torch, load_filepaths_and_text
# import h5py
@ -101,14 +101,12 @@ class TextAudioSpeakerLoader(torch.utils.data.Dataset):
log10_vol_shift = random.uniform(-1, max_shift)
audio_norm = audio_norm * (10 ** log10_vol_shift)
volume = volume * (10 ** log10_vol_shift)
spec = mel_spectrogram_torch(audio_norm,
self.hparams.data.filter_length,
self.hparams.data.n_mel_channels,
self.hparams.data.sampling_rate,
self.hparams.data.hop_length,
self.hparams.data.win_length,
self.hparams.data.mel_fmin,
self.hparams.data.mel_fmax)
spec = spectrogram_torch(audio_norm,
self.hparams.data.filter_length,
self.hparams.data.sampling_rate,
self.hparams.data.hop_length,
self.hparams.data.win_length,
center=False)[0]
if spec.shape[1] > 800:
start = random.randint(0, spec.shape[1]-800)