35 citations · 47 across the 5 of their papers we have counts for
5 papers
ContextSpeech: Expressive and Efficient Text-to-Speech for Paragraph Reading
Yujia Xiao, Shaofei Zhang, Xi Wang +5
While state-of-the-art Text-to-Speech systems can generate natural speech of very high quality at sentence level, they still meet great challenges in speech generation for paragrap…
Self-supervised Context-aware Style Representation for Expressive Speech Synthesis
Yihan Wu, Xi Wang, Shaofei Zhang +3
Expressive speech synthesis, like audiobook synthesis, is still challenging for style representation learning and prediction. Deriving from reference audio or predicting style tags…
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
Xu Tan, Jiawei Chen, Haohe Liu +11
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…
s-Transformer: Segment-Transformer for Robust Neural Speech Synthesis
Xi Wang, Huaiping Ming, Lei He +1
Neural end-to-end text-to-speech (TTS) , which adopts either a recurrent model, e.g. Tacotron, or an attention one, e.g. Transformer, to characterize a speech utterance, has achiev…
Forward-Backward Decoding for Regularizing End-to-End TTS
Yibin Zheng, Xi Wang, Lei He +4
Neural end-to-end TTS can generate very high-quality synthesized speech, and even close to human recording within similar domain text. However, it performs unsatisfactory when scal…