| import logging | |
| from pathlib import Path | |
| import torchaudio | |
| from hw_asr.base.base_dataset import BaseDataset | |
| logger = logging.getLogger(__name__) | |
| class CustomAudioDataset(BaseDataset): | |
| def __init__(self, data, *args, **kwargs): | |
| index = data | |
| for entry in data: | |
| assert "path" in entry | |
| assert Path(entry["path"]).exists(), f"Path {entry['path']} doesn't exist" | |
| entry["path"] = str(Path(entry["path"]).absolute().resolve()) | |
| entry["text"] = entry.get("text", "") | |
| t_info = torchaudio.info(entry["path"]) | |
| entry["audio_len"] = t_info.num_frames / t_info.sample_rate | |
| super().__init__(index, *args, **kwargs) | |