README.md

---
license: cc-by-4.0
task_categories:
- text-to-speech
language:
- en
source_datasets:
- mythicinfinity/libritts_r
tags:
- voice-cloning
- tts
- reference-voices
- libritts
size_categories:
- 1K<n<10K
pretty_name: radiotalk-voices-2k
configs:
- config_name: default
  data_files:
  - split: train
    path: data/shard-*.parquet
---

# radiotalk-voices-2k

2,000 English reference voices — one 12–30s clip per speaker, selected as the longest qualifying utterance per speaker from [LibriTTS-R](https://huggingface.co/datasets/mythicinfinity/libritts_r). Built for zero-shot TTS voice cloning in the [radiotalk](https://github.com/twangodev/radiotalk) pipeline.

## Stats

- 2,000 voices · 12.03 hours total
- Duration: min 12.0s · median 21.8s · mean 21.7s · max 30.0s
- 24 kHz, mono, FLAC-encoded

## Schema

| Column | Type | Description |
|---|---|---|
| `voice_id` | string | Stable 12-hex-char id, derived from `(source, source_speaker_id)` |
| `audio` | Audio | FLAC bytes at 24 kHz (Hub viewer plays inline) |
| `text` | string | Normalized transcript from LibriTTS-R (`text_normalized`) |
| `source_clip_id` | string | Utterance id in LibriTTS-R, format `{speaker}_{chapter}_{section}_{utterance}` |

## Loading

```python
from datasets import load_dataset

ds = load_dataset("twangodev/radiotalk-voices-2k", split="train")
row = ds[0]
print(row["voice_id"], row["text"][:60])
audio = row["audio"]  # {"array": np.ndarray, "sampling_rate": 24000, "path": ...}
```

## Citation

If you use this dataset, please cite both this repository and the upstream LibriTTS-R corpus.

```bibtex
@misc{ding2026radiotalk,
  author       = {Ding, James},
  title        = {{radiotalk}: Data pipeline and reference voice pool for TTS},
  year         = {2026},
  howpublished = {\url{https://github.com/twangodev/radiotalk}},
}

@inproceedings{koizumi2023libritts,
  title     = {{LibriTTS-R}: A Restored Multi-Speaker Text-to-Speech Corpus},
  author    = {Koizumi, Yuma and Zen, Heiga and Karita, Shigeki and Ding, Yifan and Yatabe, Kohei and Morioka, Nobuyuki and Bacchiani, Michiel and Zhang, Yu and Han, Wei and Bapna, Ankur},
  booktitle = {Proc. Interspeech},
  year      = {2023},
}
```

## License

All clips are derived from LibriTTS-R, licensed **CC BY 4.0**. This dataset inherits that license. See `NOTICE.md` for the full source attribution.