| dataset_info: | |
| features: | |
| - name: audio | |
| dtype: | |
| audio: | |
| sampling_rate: 16000 | |
| - name: text | |
| dtype: string | |
| - name: ref_index | |
| dtype: int64 | |
| splits: | |
| - name: train | |
| num_bytes: 1000427885.04 | |
| num_examples: 4730 | |
| - name: validation | |
| num_bytes: 21703376.0 | |
| num_examples: 179 | |
| download_size: 1012364638 | |
| dataset_size: 1022131261.04 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: validation | |
| path: data/validation-* | |
| # Code-Quasar/Tn-TTS | |
| Tunisian Derja speech for VoxCPM2 fine-tuning. | |
| - `audio` — 16000 Hz mono, decoded by the `datasets` Audio feature | |
| - `text` — transcript, every row prefixed with `(Tunisian Dialect)` | |
| - `ref_index` — row index of a reference clip for in-context cloning, or -1 | |
| ## Use | |
| ```bash | |
| python data.py pull # materializes wavs + manifests | |
| ``` | |
| Derived from corpora with their own licence terms; the voices belong to real speakers. Check before redistributing. | |