Papers
1
Total Citations
6
H-Index
1
About
Yuya Asano is a researcher at the intersection of human-robot interaction, educational technology, and natural language processing. His work centers on how dialogue systems—particularly teachable robots—can foster learning and engagement through lexical alignment and adaptive interaction. In his most-cited paper, "Comparison of Lexical Alignment with a Teachable Robot in Human-Robot and Human-Human-Robot Interactions" (2022, 6 citations), Asano and collaborators explored how students align their language with a robot tutor during collaborative problem-solving, revealing key differences in alignment patterns between human-robot and human-human-robot dynamics. This research contributes to designing more effective, socially aware educational robots that can personalize instruction. Asano’s work has been presented at venues like the SIGDIAL conference, and his findings inform the development of intelligent tutoring systems that leverage conversational alignment to improve learning outcomes. With a growing citation footprint, his contributions are shaping how robots can serve as adaptive, interactive partners in education.
Research Focus
Key Achievements
Top Papers
- 1