LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus
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 http://www.openslr.org/141/.
6476e29583d4fdaedde073d8
Yuma Koizumi
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Heiga Zen
6476e29583d4fdaedde073da
Shigeki Karita
admin_assigned
2023-05-31T13:47:52.250Z
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Shigeki Karita
user
ShigekiKarita
6476e29583d4fdaedde073db
Yifan Ding
6476e29583d4fdaedde073dc
Kohei Yatabe
6476e29583d4fdaedde073dd
Nobuyuki Morioka
6476e29583d4fdaedde073de
Michiel Bacchiani
6476e29583d4fdaedde073df
Yu Zhang
6476e29583d4fdaedde073e0
Wei Han
claimed_verified
2023-06-23T14:28:00.962Z
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Wei Han
user
weihan3
6476e29583d4fdaedde073e1
Ankur Bapna
admin_assigned
2023-05-31T13:49:27.257Z
62cdba279403ec4719d384f8
/avatars/c62c7d16b5cf382cdeb7fbfb5e291917.svg
Ankur Bapna
user
ankurbpn
LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus
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 http://www.openslr.org/141/.
A new speech dataset called LibriTTS-R, derived by applying speech restoration to LibriTTS, improves sound quality and enhances neural end-to-end TTS performance.
speech restoration text-to-speech TTS LibriTTS neural end-to-end TTS speech naturalness