15 citations · 15 across the 6 of their papers we have counts for
4 papers · 1 filter
Learning Expressive Disentangled Speech Representations with Soft Speech Units and Adversarial Style Augmentation
Yimin Deng, Jianzong Wang, Xulong Zhang +2
Voice conversion is the task to transform voice characteristics of source speech while preserving content information. Nowadays, self-supervised representation learning models are…
Learning Disentangled Speech Representations with Contrastive Learning and Time-Invariant Retrieval
Yimin Deng, Huaizhen Tang, Xulong Zhang +3
Voice conversion refers to transferring speaker identity with well-preserved content. Better disentanglement of speech representations leads to better voice conversion. Recent stud…
CLN-VC: Text-Free Voice Conversion Based on Fine-Grained Style Control and Contrastive Learning with Negative Samples Augmentation
Yimin Deng, Xulong Zhang, Jianzong Wang +2
Better disentanglement of speech representation is essential to improve the quality of voice conversion. Recently contrastive learning is applied to voice conversion successfully b…
PMVC: Data Augmentation-Based Prosody Modeling for Expressive Voice Conversion
Yimin Deng, Huaizhen Tang, Xulong Zhang +3
Voice conversion as the style transfer task applied to speech, refers to converting one person's speech into a new speech that sounds like another person's. Up to now, there has be…