Spaces:
Sleeping
Sleeping
| import os | |
| import torchaudio | |
| import torch | |
| from ttts.vocoder.feature_extractors import MelSpectrogramFeatures | |
| device = 'cuda' | |
| mel_extractor = MelSpectrogramFeatures().to(device) | |
| def process_mel(wav_file): | |
| # print(f"Processing {wav_file}..") | |
| outfile = f'{wav_file}.mel.pth' | |
| if os.path.exists(outfile): | |
| return | |
| try: | |
| wave, sample_rate = torchaudio.load(wav_file) | |
| wave = wave.to(device) | |
| if wave.size(0) > 1: # mix to mono | |
| wave = wave[0].unsqueeze(0) | |
| if sample_rate!=24000: | |
| resample = torchaudio.transforms.Resample(sample_rate,24000).to(device) | |
| wave = resample(wave) | |
| except Exception as e: | |
| print(e) | |
| print(f"Error with {wav_file}") | |
| return | |
| mel = mel_extractor(wave) | |
| torch.save(mel.cpu().detach(), outfile) |