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ROAM-ASD: Robust Open-World Active Speaker Detection with Flexible Multimodal Fusion

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Active speaker detection (ASD) requires reliable association between visible faces and acoustic speech, yet existing systems often degrade under challenging domains or incomplete observations. We introduce ROAM-ASD, a robust audiovisual framework that jointly models audio, full-face, and fine-grained mouth representations. A unified joint self-attention mechanism processes all input streams together with modality-agnostic query tokens, enabling direct interaction among available modality inputs. Modality dropout further improves robustness when input streams are unavailable. ROAM-ASD achieves

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First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.