Active speaker detection (ASD) relies on audiovisual correspondence between speech and visible faces, yet this correspondence becomes unreliable in crowded scenes, or when visual evidence is unavailable. We introduce ROAM-ASD-C and ROAM-ASD-CR to extend ROAM-ASD with contextual and identity-aware reasoning. ROAM-ASD-C jointly reasons across simultaneously visible candidates, allowing other faces to provide complementary evidence when the target observation is ambiguous or incomplete. ROAM-ASD-CR incorporates registered-speaker representations derived from enrollment speech, allowing detection of whether a speaker is active even when that speaker is not visually observed. ROAM-ASD-C achieves state-of-the-art performance across five ASD benchmarks: 96.8% mAP on AVA, 98.9% on WASD, 88.8% on UniTalk, 98.7% on Talkies, and 99.5% on ASW. It also improves ROAM-ASD by up to 13.3 mAP under 75% target-track visual removal.

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