LibriTTS-R est une version améliorée de la qualité audio du corpus LibriTTS. Les résultats associés à cette ressource sont publiés dans l'article scientifique suivant : LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus, avec pour objectif de fournir des données vocales anglaises de haute qualité aux chercheurs en synthèse et traitement de la parole.

Ce jeu de données contient environ 585 heures d'enregistrements vocaux anglais multi-locuteurs lus à voix haute, échantillonnés à 24 kHz, et répartis en sept partitions (splits).

Référence bibliographique

@ARTICLE{Koizumi2023-hs,
  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",
  abstract      = "This paper introduces a new speech dataset called
                   ``LibriTTS-R'' designed for text-to-speech (TTS) use. It is
                   derived by applying speech restoration to the LibriTTS
                   corpus, which consists of 585 hours of speech data at 24 kHz
                   sampling rate from 2,456 speakers and the corresponding
                   texts. The constituent samples of LibriTTS-R are identical
                   to those of LibriTTS, with only the sound quality improved.
                   Experimental results show that the LibriTTS-R ground-truth
                   samples showed significantly improved sound quality compared
                   to those in LibriTTS. In addition, neural end-to-end TTS
                   trained with LibriTTS-R achieved speech naturalness on par
                   with that of the ground-truth samples. The corpus is freely
                   available for download from
                   \url{http://www.openslr.org/141/}.",
  month         = may,
  year          = 2023,
  copyright     = "http://creativecommons.org/licenses/by-nc-nd/4.0/",
  archivePrefix = "arXiv",
  primaryClass  = "eess.AS",
  eprint        = "2305.18802"
}