collaborators

7 papers

cs.SD2026

Speech Meets ELF: Audio Conditional Continuous-Target Diffusion for Speech Recognition and Translation

Xuanchen Li, Tianrui Wang, Yuheng Lu +11

Speech-to-text (S2T) systems for recognition (ASR) and translation (S2TT) typically generate discrete text tokens. In contrast, continuous-target language modelling performs genera…

cs.AI2026

Separate First, Fuse Later: Mitigating Cross-Modal Interference in Audio-Visual LLMs Reasoning with Modality-Specific Chain-of-Thought

Xuanchen Li, Yuheng Lu, Chenrui Cui +6

Audio and vision provide complementary evidence for audio-visual question answering, yet current audio-visual large language models may suffer from cross-modal interference: inform…

eess.AS2026

Evaluating the Expressive Appropriateness of Speech in Rich Contexts

Tianrui Wang, Ziyang Ma, Yizhou Peng +26

Evaluating expressive speech remains challenging, as existing methods mainly assess emotional intensity and overlook whether a speech sample is expressively appropriate for its con…

cs.SD2026

Expressive Prompting: Improving Emotion Intensity and Speaker Consistency in Zero-Shot TTS

Haoyu Wang, Chunyu Qiang, Tianrui Wang +6

Recent advancements in speech synthesis have enabled large language model (LLM)-based systems to perform zero-shot generation with controllable content, timbre, speaker identity, a…

eess.AS2026

Efficient Emotion and Speaker Adaptation in LLM-Based TTS via Characteristic-Specific Partial Fine-Tuning

Tianrui Wang, Meng Ge, Cheng Gong +11

While LLM-based TTS models exhibit zero-shot emotion and speaker cloning, their cloning fidelity and pronunciation clarity degrade on unseen domains. Fine-tuning is essential for a…

eess.AS2025

Rare Word Recognition and Translation Without Fine-Tuning via Task Vector in Speech Models

Ruihao Jing, Cheng Gong, Yu Jiang +5

Rare words remain a critical bottleneck for speech-to-text systems. While direct fine-tuning improves recognition of target words, it often incurs high cost, catastrophic forgettin…