arXiv — NLP / Computation & Language · · 3 min read

Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction

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Electrical Engineering and Systems Science > Audio and Speech Processing

arXiv:2609.25176 (eess)
[Submitted on 21 Sep 2026]

Title:Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction

View a PDF of the paper titled Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction, by Lujia Bao and 16 other authors
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Abstract:Real-time voice assistants must reason over evolving requests, execute actions, and follow conversational rules. Qwen-Audio-3.1-Realtime brings these requirements together through Think, Act, and Speak and Coordinate. Think combines Core-Cocktail supervised fine-tuning with Multimodality and Multi-Teacher On-Policy Distillation (M$^{2}$-OPD) to transfer language capabilities and develop native audio skills. Act uses self-evolving executable environments and multi-granularity rollouts for Group Relative Policy Optimization (GRPO), teaching the model to use tools, interpret feedback, and complete tasks. Speak and Coordinate aligns how, when, and whether the assistant speaks or acts. We evaluate audio reasoning, multilingual understanding, tool use, conversational behavior, full-duplex interaction, and safety. Compared with Qwen-Audio-3.0-Realtime, 3.1 raises overall task success from 78.4% to 82.0% on our half-duplex speech-to-text adaptation of $\tau$-Voice. On speech-to-speech Full-Duplex-Bench v1.5, the response rate to background speech falls from 73.0% to 13.0%. We also present a separate Voice Harness prototype, using Qwen-Audio-3.0-Realtime as its foreground, that extends spoken interaction to persistent tasks through foreground--background coordination and memory.
Comments: 20 pages, technical report
Subjects: Audio and Speech Processing (eess.AS); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Sound (cs.SD)
Cite as: arXiv:2609.25176 [eess.AS]
  (or arXiv:2609.25176v1 [eess.AS] for this version)
  https://doi.org/10.48550/arXiv.2609.25176
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Qian Chen [view email]
[v1] Mon, 21 Sep 2026 14:20:47 UTC (2,493 KB)
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