1 citations · 3 across the 6 of their papers we have counts for
6 papers
Vec-Tok-VC+: Residual-enhanced Robust Zero-shot Voice Conversion with Progressive Constraints in a Dual-mode Training Strategy
Linhan Ma, Xinfa Zhu, Yuanjun Lv +5
Zero-shot voice conversion (VC) aims to transform source speech into arbitrary unseen target voice while keeping the linguistic content unchanged. Recent VC methods have made signi…
Vec-Tok Speech: speech vectorization and tokenization for neural speech generation
Xinfa Zhu, Yuanjun Lv, Yi Lei +5
Language models (LMs) have recently flourished in natural language processing and computer vision, generating high-fidelity texts or images in various tasks. In contrast, the curre…
SALT: Distinguishable Speaker Anonymization Through Latent Space Transformation
Yuanjun Lv, Jixun Yao, Peikun Chen +3
Speaker anonymization aims to conceal a speaker's identity without degrading speech quality and intelligibility. Most speaker anonymization systems disentangle the speaker represen…
PromptVC: Flexible Stylistic Voice Conversion in Latent Space Driven by Natural Language Prompts
Jixun Yao, Yuguang Yang, Yi Lei +7
Style voice conversion aims to transform the style of source speech to a desired style according to real-world application demands. However, the current style voice conversion appr…
METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer
Xinfa Zhu, Yi Lei, Tao Li +4
Previous multilingual text-to-speech (TTS) approaches have considered leveraging monolingual speaker data to enable cross-lingual speech synthesis. However, such data-efficient app…
Improving Cross-lingual Speech Synthesis with Triplet Training Scheme
Jianhao Ye, Hongbin Zhou, Zhiba Su +4
Recent advances in cross-lingual text-to-speech (TTS) made it possible to synthesize speech in a language foreign to a monolingual speaker. However, there is still a large gap betw…