UniTalk: towards universal active speaker detection in real world scenarios
Published in arXiv preprint arXiv:2505.21954, 2025
Authors: Le Thien Phuc Nguyen, Zhuoran Yu, Khoa Quang Nhat Cao, Yuwei Guo, Tu Ho Manh Pham, Tuan Tai Nguyen, Toan Ngo Duc Vo, Lucas Poon, Soochahn Lee, Yong Jae Lee
TL;DR: UniTalk proposes a universal active speaker detection framework that works robustly across diverse real-world scenarios, handling challenging conditions like occlusion, noise, and multiple speakers.
What this paper is about
Active speaker detection – figuring out who is currently talking in a video – sounds simple but breaks down in real-world conditions. Existing methods struggle with occlusions, noisy audio, multiple simultaneous speakers, and diverse recording setups.
Key idea
UniTalk introduces a unified framework designed to generalize across varied real-world scenarios for active speaker detection. It likely leverages multi-modal cues (audio and visual) with architectural choices that make the system robust to the messy conditions found outside of controlled datasets.
Why it matters
Reliable active speaker detection is a key building block for video conferencing, surveillance, and multimedia understanding systems that need to work in unconstrained environments.
