主旨
介绍了一种名为LibriTTS-R的语音数据集，通过语音修复技术提高了语音样本的质量，为TTS研究提供了加速。
论文地址
摘要
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{this http URL}.
