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NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality. (arXiv:2205.04421v2 [eess.AS] UPDATED)
Web: http://arxiv.org/abs/2205.04421
May 11, 2022, 1:12 a.m. | Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, Yuanhao Yi, Lei He, Frank Soong, Tao Qin, Sheng Zhao, Tie-Y
cs.LG updates on arXiv.org arxiv.org
Text to speech (TTS) has made rapid progress in both academia and industry in
recent years. Some questions naturally arise that whether a TTS system can
achieve human-level quality, how to define/judge that quality and how to
achieve it. In this paper, we answer these questions by first defining the
human-level quality based on the statistical significance of subjective measure
and introducing appropriate guidelines to judge it, and then developing a TTS
system called NaturalSpeech that achieves human-level quality on …
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