Do Audio LLMs Listen Before They Act? Diagnosing Acoustic-Context Gating in Voice Agents
Audio language models can recognize spoken commands and invoke tools, but an agent must first decide whether the acoustic and conversational context warrants action. We introduce VGBench, a 1,018-item diagnostic benchmark for action-level addressedness across side-talk, self-talk, and speaker-switch scenarios. Each item uses a shared action space comprising silence, a tool call, and a natural-language answer. Speaker-switch pairs hold the specified words fixed while source, distance rendering, and a temporal boundary define a controlled wearer-to-bystander shift. Six raw Audio LLMs and three training-free adaptations often identify the target tool yet rarely withhold action under this shi...
| Authors | Yanjie Zhang, Nanchen Hu, Yushi Sun |
|---|---|
| Primary category | cs.SD |
| Published | 26 September 2026 |
| Last updated at source | 26 September 2026 |
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