$τ$-Voice: Benchmarking Full-Duplex Voice Agents on Real-World Domains
Full-duplex voice agents--systems that listen and speak simultaneously--are rapidly moving from research to production. However, existing evaluations address conversational dynamics and task completion in isolation. We introduce $τ$-voice, a benchmark for evaluating voice agents on grounded tasks with real-world complexity: agents must navigate complex multi-turn conversations, adhere to domain policies, and interact with the environment. The framework extends $τ^2$-bench into a novel voice agent benchmark combining verifiable completion of complex grounded tasks, full-duplex interaction, and realistic audio--enabling direct comparison between voice and text performance. A controllable an...
| Authors | Soham Ray, Keshav Dhandhania, Victor Barres et al. |
|---|---|
| Primary category | cs.SD |
| Published | 14 March 2026 |
| Last updated at source | 14 March 2026 |
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