3 citations · 8 across the 6 of their papers we have counts for
6 papers
Audio-Thinker: Guiding Audio Language Model When and How to Think via Reinforcement Learning
Shu Wu, Chenxing Li, Wenfu Wang +4
Recent advancements in large language models, multimodal large language models, and large audio language models (LALMs) have significantly improved their reasoning capabilities thr…
LLM-Enhanced Dialogue Management for Full-Duplex Spoken Dialogue Systems
Hao Zhang, Weiwei Li, Rilin Chen +3
Achieving full-duplex communication in spoken dialogue systems (SDS) requires real-time coordination between listening, speaking, and thinking. This paper proposes a semantic voice…
Restorative Speech Enhancement: A Progressive Approach Using SE and Codec Modules
Hsin-Tien Chiang, Hao Zhang, Yong Xu +2
In challenging environments with significant noise and reverberation, traditional speech enhancement (SE) methods often lead to over-suppressed speech, creating artifacts during li…
Preference Alignment Improves Language Model-Based TTS
Jinchuan Tian, Chunlei Zhang, Jiatong Shi +4
Recent advancements in text-to-speech (TTS) have shown that language model (LM)-based systems offer competitive performance to their counterparts. Further optimization can be achie…
EzAudio: Enhancing Text-to-Audio Generation with Efficient Diffusion Transformer
Jiarui Hai, Yong Xu, Hao Zhang +4
We introduce EzAudio, a text-to-audio (T2A) generation framework designed to produce high-quality, natural-sounding sound effects. Core designs include: (1) We propose EzAudio-DiT,…
SMRU: Split-and-Merge Recurrent-based UNet for Acoustic Echo Cancellation and Noise Suppression
Zhihang Sun, Andong Li, Rilin Chen +4
The proliferation of deep neural networks has spawned the rapid development of acoustic echo cancellation and noise suppression, and plenty of prior arts have been proposed, which…