Instructions to use espnet/CI_mini_an4_training_asr_transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/CI_mini_an4_training_asr_transformer with ESPnet:
unknown model type (must be text-to-speech or automatic-speech-recognition)
- Notebooks
- Google Colab
- Kaggle
| from __future__ import annotations | |
| from pathlib import Path | |
| from typing import List | |
| def gather_training_text(manifest_path: Path) -> List[str]: | |
| """Collect transcript texts from a TSV manifest file.""" | |
| manifest_path = Path(manifest_path) | |
| if not manifest_path.is_file(): | |
| raise FileNotFoundError(f"Manifest not found: {manifest_path}") | |
| texts: list[str] = [] | |
| with manifest_path.open("r", encoding="utf-8") as f: | |
| for line in f: | |
| line = line.strip() | |
| if not line: | |
| continue | |
| parts = line.split("\t", maxsplit=2) | |
| if len(parts) != 3: | |
| raise ValueError(f"Invalid manifest line: {line}") | |
| texts.append(parts[2]) | |
| if not texts: | |
| raise RuntimeError(f"No text found in manifest: {manifest_path}") | |
| return texts | |