MuVAP: Multimodal Multiparty Voice Activity Projection for Turn-taking Prediction in the Wild
Current multiparty turn-taking models often rely on complex microphone arrays or multi-camera setups, limiting their applicability in human-robot interaction scenarios. We introduce MuVAP, a causal multimodal framework that extends Voice Activity Projection by grounding acoustic predictions in face tracks, enabling speaker-aware turn-taking predictions from a monaural audio stream and a single camera view. To address the combinatorial complexity of modeling multiple speakers, we propose Role-Relative Projection, which maps any N-speaker interaction onto a fixed current versus next floor-holder state. Because existing audiovisual datasets contain disruptive editing cuts that break causal t...
| Authors | Haotian Qi, Gabriel Skantze |
|---|---|
| Primary category | cs.SD |
| Published | 15 June 2026 |
| Last updated at source | 18 June 2026 |
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