Research news on Human-centered AI interfaces

Human-centered AI interfaces encompass computational systems that use machine learning, generative models, and multimodal sensing to mediate, augment, or interpret human communication and behavior. Work in this area spans assistive communication for speech, hearing, and motor impairments, real-time sign language and speech technologies, and social robots that adapt behavior and express empathy. Vision-language models and video analytics support long-video reasoning, activity recognition, and error detection, while interactive agents, privacy-aware speech systems, and affect-sensitive tools enable more accessible, expressive, and context-aware human–AI interaction across physical and virtual environments.