10 citations · 24 across the 24 of their papers we have counts for
9 papers · 1 filter
CharDuplex: Building Character-Consistent Full-Duplex Spoken Dialogue Models
Donghang Wu, Yisi Liu, Chen Chen +2
Full-duplex speech models are moving voice interaction beyond conventional turn-taking, yet natural conversation is shaped not only by when an agent speaks, but also by how it beha…
Beyond Textual Chain-of-Thought: JEPA-Conditioned Latent Reasoning for Large Audio Language Models
Donghang Wu, Haoyang Zhang, Yizhou Peng +6
Explicit textual Chain-of-Thought (CoT) has improved the reasoning ability of large audio language models (LALMs). However, textual CoTs are often constructed from text captions of…
VoiceChat-TTS: A Low-Latency Continuous Speech Synthesis Model for Interactive Agents
Edresson Casanova, Jaehyeon Kim, Mariana Graterol Fuenmayor +17
Spoken dialogue is a natural form of human--computer interaction, yet most speech language models remain limited to turn-based operation and lack real-time adaptability, such as us…
Decoupling Conversational Dynamics in Full-Duplex Spoken Models through Reinforcement Learning
Yuxin Li, Donghang Wu, Guan-Ting Lin +4
Recent full-duplex spoken dialogue models have demonstrated compelling progress toward human-like interaction, enabling agents to respond with low latency, produce backchannels, an…
Full-Duplex-Bench-v3: Benchmarking Tool Use for Full-Duplex Voice Agents Under Real-World Disfluency
Guan-Ting Lin, Chen Chen, Zhehuai Chen +1
We introduce Full-Duplex-Bench-v3 (FDB-v3), a benchmark for evaluating spoken language models under naturalistic speech conditions and multi-step tool use. Unlike prior work, our d…
The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning
Donghang Wu, Tianyu Zhang, Yuxin Li +4
During conversational interactions, humans subconsciously engage in concurrent thinking while listening to a speaker. Although this internal cognitive processing may not always man…
GenSE: Generative Speech Enhancement via Language Models using Hierarchical Modeling
Jixun Yao, Hexin Liu, Chen Chen +3
Semantic information refers to the meaning conveyed through words, phrases, and contextual relationships within a given linguistic structure. Humans can leverage semantic informati…
From KAN to GR-KAN: Advancing Speech Enhancement with KAN-Based Methodology
Haoyang Li, Yuchen Hu, Chen Chen +3
Deep neural network (DNN)-based speech enhancement (SE) usually uses conventional activation functions, which lack the expressiveness to capture complex multiscale structures neede…
SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and Synthesis
Helin Wang, Meng Yu, Jiarui Hai +5
In this paper, we introduce SSR-Speech, a neural codec autoregressive model designed for stable, safe, and robust zero-shot textbased speech editing and text-to-speech synthesis. S…