LibriTTS-R [1] is a sound quality improved version of the <a href="http://www.openslr.org/60">LibriTTS corpus (http://www.openslr.org/60/)</a> which is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz sampling rate, published in 2019. The constituent samples of LibriTTS-R are identical to those of LibriTTS, with only the sound quality improved. To improve sound quality, a speech restoration model, Miipher proposed by Yuma Koizumi [2], was used.

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For more information, refer to the paper [1]. If you use the LibriTTS-R corpus in your work, please cite the dataset paper [1] where it was introduced.

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Audio samples of the ground-truth and TTS generated samples are available at the demo page: <a href="https://google.github.io/df-conformer/librittsr/">https://google.github.io/df-conformer/librittsr/</a>

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[1] Yuma Koizumi, Heiga Zen, Shigeki Karita, Yifan Ding, Kohei Yatabe, Nobuyuki Morioka, Michiel Bacchiani, Yu Zhang, Wei Han, and Ankur Bapna, "LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus," arXiv, 2023.<br>
[2] Yuma Koizumi, Heiga Zen, Shigeki Karita, Yifan Ding, Kohei Yatabe, Nobuyuki Morioka, Yu Zhang, Wei Han, Ankur Bapna, and Michiel Bacchiani, "Miipher: A Robust Speech Restoration Model Integrating Self-Supervised Speech and Text Representations," arXiv, 2023.