| | |
| | | import torch.distributed as dist |
| | | import torchaudio |
| | | import numpy as np |
| | | import soundfile |
| | | # import librosa |
| | | import librosa |
| | | from kaldiio import ReadHelper |
| | | from torch.utils.data import IterableDataset |
| | | |
| | |
| | | try: |
| | | waveform, sampling_rate = torchaudio.load(path) |
| | | except: |
| | | waveform, sampling_rate = soundfile.read(path, dtype='float32') |
| | | # waveform, sampling_rate = librosa.load(path, dtype='float32') |
| | | waveform, sampling_rate = librosa.load(path, dtype='float32') |
| | | if waveform.ndim == 2: |
| | | waveform = waveform[:, 0] |
| | | waveform = np.expand_dims(waveform, axis=0) |