56 citations · 166 across the 19 of their papers we have counts for
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cs.SD2022
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech
Yang Li, Cheng Yu, Guangzhi Sun +6
Modelling prosody variation is critical for synthesizing natural and expressive speech in end-to-end text-to-speech (TTS) systems. In this paper, a cross-utterance conditional VAE…
cs.SD2022★ 1 cited
Perceptual Contrast Stretching on Target Feature for Speech Enhancement
Rong Chao, Cheng Yu, Szu-Wei Fu +2
Speech enhancement (SE) performance has improved considerably owing to the use of deep learning models as a base function. Herein, we propose a perceptual contrast stretching (PCS)…
eess.AS2022
Conditional Diffusion Probabilistic Model for Speech Enhancement
Yen-Ju Lu, Zhong-Qiu Wang, Shinji Watanabe +3
Speech enhancement is a critical component of many user-oriented audio applications, yet current systems still suffer from distorted and unnatural outputs. While generative models…