Akihiro Matsufuji
Papers
8
Total Citations
34
H-Index
4
About
Akihiro Matsufuji is a researcher specializing in human-robot interaction, multimodal signal processing, and socially adaptive robotic systems. His work sits at the intersection of affective computing and conversational AI, with a particular focus on enabling robots to perceive and respond to nuanced human cues in real-world environments. Matsufuji's most influential contribution, cited 11 times, examines how speech information and head motion can be combined to estimate a speaker's confidence during conversation — a meaningful step beyond purely language-based approaches. This multimodal philosophy extends throughout his portfolio: he has developed adaptive machine learning architectures for estimating emotional states (5 citations), explored nonverbal behavior analysis to detect communicative awkwardness (4 citations), and refined gaze- and head-movement-based methods for inferring mental states in dialogue (3 citations). A distinctive thread in his recent work addresses how robots should modulate their voice in response to ambient and social contexts — from noisy airports to quiet classrooms — with studies published in 2021 and 2023 demonstrating tangible improvements in perceived robot intelligence and appropriateness. Collectively, Matsufuji's research advances a vision of robots that are not merely linguistically competent, but genuinely context-aware and socially attuned partners in human communication.
Research Focus
Key Achievements
Top Papers
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- 5Read the Room: Adapting a Robot's Voice to Ambient and Social Contexts3 citations · 2023
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- 8I'm a Robot, Hear Me Speak!2 citations · 2023