Page 20: 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.

Machine learning & AI

Multimodal AI learns to weigh text and images more evenly

Just as human eyes tend to focus on pictures before reading accompanying text, multimodal artificial intelligence (AI)—which processes multiple types of sensory data at once—also tends to depend more heavily on certain types ...

Consumer & Gadgets

Humanoid robots in the home? Not so fast, says expert

It's been a goal for as long as humanoids have been a subject of popular imagination—a general-purpose robot that can do rote tasks like fold laundry or sort recycling simply by being asked.

Machine learning & AI

Dialogue systems learn new words with fewer questions

Researchers at the University of Osaka have developed a mechanism that allows spoken dialog systems to learn new words through conversation without overwhelming users with repetitive questions. By optimizing when to ask a ...

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