28 citations · 57 across the 30 of their papers we have counts for
6 papers · 1 filter
Fewer-token Neural Speech Codec with Time-invariant Codes
Yong Ren, Tao Wang, Jiangyan Yi +4
Language model based text-to-speech (TTS) models, like VALL-E, have gained attention for their outstanding in-context learning capability in zero-shot scenarios. Neural speech code…
Residual Speaker Representation for One-Shot Voice Conversion
Le Xu, Jiangyan Yi, Tao Wang +4
Recently, there have been significant advancements in voice conversion, resulting in high-quality performance. However, there are still two critical challenges in this field. First…
Learning Speech Representation From Contrastive Token-Acoustic Pretraining
Chunyu Qiang, Hao Li, Yixin Tian +4
For fine-grained generation and recognition tasks such as minimally-supervised text-to-speech (TTS), voice conversion (VC), and automatic speech recognition (ASR), the intermediate…
Boosting Fast and High-Quality Speech Synthesis with Linear Diffusion
Haogeng Liu, Tao Wang, Jie Cao +2
Denoising Diffusion Probabilistic Models have shown extraordinary ability on various generative tasks. However, their slow inference speed renders them impractical in speech synthe…
ADD 2023: the Second Audio Deepfake Detection Challenge
Jiangyan Yi, Jianhua Tao, Ruibo Fu +15
Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the…
UnifySpeech: A Unified Framework for Zero-shot Text-to-Speech and Voice Conversion
Haogeng Liu, Tao Wang, Ruibo Fu +3
Text-to-speech (TTS) and voice conversion (VC) are two different tasks both aiming at generating high quality speaking voice according to different input modality. Due to their sim…