AI RESEARCH
VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents
arXiv CS.CV
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ArXi:2605.30256v1 Announce Type: new Natural human conversation is full-duplex and audio-visual: people simultaneously speak and listen while continuously interpreting and producing nonverbal cues, such as nods, smiles, and gestures. To successful human-agent interaction, agents must model full-duplex audiovisual conversation; however, existing full-duplex benchmarks evaluate only speech. In this work, we present VideoFDB, the first benchmark to evaluate full-duplex audio-visual-to-audio-visual (AV2AV) conversational agents.