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@@ -7,6 +7,8 @@ pretty_name: 'LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus'
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  Official website: [https://www.openslr.org/141/](https://www.openslr.org/141/)
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  LibriTTS-R ([paper](https://arxiv.org/abs/2305.18802)) is a sound quality improved version of the [LibriTTS corpus](http://www.openslr.org/60/) 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](https://arxiv.org/abs/2303.01664), was used.
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  For more information, refer to the paper. If you use the LibriTTS-R corpus in your work, please cite the dataset paper where it was introduced.
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  Official website: [https://www.openslr.org/141/](https://www.openslr.org/141/)
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+ This repository contains LibriTTS-R converted to a [WebDataset](https://github.com/webdataset/webdataset). The original Wave files have been converted to 64kbps MP3 files for efficient streaming.
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  LibriTTS-R ([paper](https://arxiv.org/abs/2305.18802)) is a sound quality improved version of the [LibriTTS corpus](http://www.openslr.org/60/) 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](https://arxiv.org/abs/2303.01664), was used.
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  For more information, refer to the paper. If you use the LibriTTS-R corpus in your work, please cite the dataset paper where it was introduced.
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