Masafumi Nishida

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About

Masafumi Nishida is a leading researcher in multimodal communication and second-language acquisition, with a focus on how embodied agents and robots can enhance language learning through natural, multi-party interactions. His most-cited work, the "Multimodal Corpus of Multi-party Conversations in Second Language" (2012, 7 citations), lays the foundation for developing dialogue-based tutoring systems that teach English to Japanese students. Nishida’s core contributions lie in integrating speech, gesture, and gaze data to create realistic, interactive learning environments, aiming to transfer software tutoring agents into physical robots for richer, more natural small-group conversations. His research bridges computational linguistics, human-robot interaction, and educational technology, offering practical tools for analyzing second-language discourse. By emphasizing multimodal cues—such as turn-taking and nonverbal feedback—Nishida’s work informs the design of adaptive tutoring systems that respond to learners’ needs. Though his citation count reflects a niche but growing field, his pioneering corpus and vision for embodied AI tutors highlight his impact on making language education more immersive and socially engaging.