Le Thien Phuc Nguyen, Zhuoran Yu, Samuel Low Yu Hang, Subin An, Jeongik Lee, Yohan Ban, SeungEun Chung, Thanh-Huy Nguyen, JuWan Maeng, Soochahn Lee, Yong Jae Lee

Researchers introduced AV-SpeakerBench, a new benchmark with 3,212 multiple-choice questions designed to evaluate how well multimodal large language models understand audiovisual human speech in real-world videos. The benchmark focuses on speaker-centric reasoning, requiring models to align who speaks, what is said, and when it occurs, rather than relying on visual context alone. Evaluations show Gemini 2.5 Pro leads significantly, while open-source models like Qwen3-Omni-30B lag primarily due to weaker audiovisual fusion capabilities rather than visual perception limitations.