collaborators

11 papers

cs.CL2026

Cross-modal Consistency Guidance for Robust Emotion Control in Auto-Regressive TTS Models

Yizhou Peng, Yukun Ma, Chong Zhang +4

While Text-to-Speech (TTS) systems enable emotional control via natural-language instructions, expressiveness, naturalness, and speech quality degrade when the target emotion confl…

cs.LG2026

FGGM: Fisher-Guided Gradient Masking for Continual Learning

Chao-Hong Tan, Qian Chen, Wen Wang +6

Catastrophic forgetting impairs the continuous learning of large language models. We propose Fisher-Guided Gradient Masking (FGGM), a framework that mitigates this by strategically…

eess.AS2026

Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions

Kun Zhou, You Zhang, Dianwen Ng +3

Emotional text-to-speech (TTS) systems sturggle to capture the full spectrum of human emotions due to the inherent complexity of emotional expressions and the limited coverage of e…

cs.CL2025

DrVoice: Parallel Speech-Text Voice Conversation Model via Dual-Resolution Speech Representations

Chao-Hong Tan, Qian Chen, Wen Wang +14

Recent studies on end-to-end (E2E) speech generation with large language models (LLMs) have attracted significant community attention, with multiple works extending text-based LLMs…

eess.AS2025

Online Audio-Visual Autoregressive Speaker Extraction

Zexu Pan, Wupeng Wang, Shengkui Zhao +4

This paper proposes a novel online audio-visual speaker extraction model. In the streaming regime, most studies optimize the audio network only, leaving the visual frontend less ex…

eess.AS2025

Plug-and-Play Co-Occurring Face Attention for Robust Audio-Visual Speaker Extraction

Zexu Pan, Shengkui Zhao, Tingting Wang +4

Audio-visual speaker extraction isolates a target speaker's speech from a mixture speech signal conditioned on a visual cue, typically using the target speaker's face recording. Ho…