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twangodev/radiotalk-voices-2k

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. Built for zero-shot TTS voice cloning in the 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… See the full description on the dataset page: https://huggingface.co/datasets/twangodev/radiotalk-voices-2k.

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Dataset Card

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. Built for zero-shot TTS voice cloning in the 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

ColumnTypeDescription
voice_idstringStable 12-hex-char id, derived from (source, source_speaker_id)
audioAudioFLAC bytes at 24 kHz (Hub viewer plays inline)
textstringNormalized transcript from LibriTTS-R (text_normalized)
source_clip_idstringUtterance 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.