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20232026
most citedLarge Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition

10 citations · 24 across the 24 of their papers we have counts for

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11 papers · 1 filter

cs.CL2026

Full-duplex Spoken Language Modeling with Discrete Diffusion

Chen Chen, Pin-Jui Ku, Ankita Pasad +3

We introduce Diffuplex, a full-duplex spoken language model based on discrete diffusion that achieves an unprecedented balance between linguistic intelligence and response efficien…

eess.AS2026

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…

eess.AS2026

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…

cs.CL2026

NemotronLabs VoiceChat: An Open Full-duplex Speech-to-Speech Model with Tool Calling Capabilities

Jagadeesh Balam, Travis Bartley, Edresson Casanova +52

We introduce NemotronLabs VoiceChat, an open full-duplex speech-to-speech model with native tool-calling capabilities. NemotronLabs VoiceChat combines a streaming speech encoder an…

cs.CL2026

A frontend-backend architecture for tool calls in full-duplex speech models

Ke Hu, Slyne Deng, Chen Chen +10

Full-duplex speech-to-speech (S2S) models provide natural, low-latency conversational interaction and would benefit from the ability to use external tools and complete voice-agent…

cs.AI2026

JarvisBench: Always-on Intelligence Between Humans and Agents

Chen Chen, Zhehuai Chen

Long-horizon agents can execute continuously, but human attention remains intermittent and scarce. This creates a bidirectional coordination problem: users may need immediate acces…

eess.AS2026

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…

cs.AI2026

Just A Rather Very Intelligent Spoken Agent

Chen Chen, Zhehuai Chen

Long-horizon AI agents are becoming increasingly capable, yet their interaction with users remains surprisingly thin. In most workflows, users give an initial instruction, receive…

eess.AS2026

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…

eess.AS2026

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…

eess.AS2026

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…