Hidemasa Muta
Papers
1
Total Citations
15
H-Index
1
About
Hidemasa Muta is a robotics researcher whose work centers on human-robot interaction, conversational AI, and the practical deployment of service robots in real-world settings. His major contribution lies in advancing the concept of "conversational bootstrapping"—a technique that enables robots to improve their dialogue capabilities through continuous, online learning from live interactions. This approach was most notably demonstrated in his highly cited 2017 paper, "Conversational Bootstrapping and Other Tricks of a Concierge Robot" (15 citations), which details the development of a concierge robot designed to engage naturally with visitors over a two-year period. By integrating speech recognition with adaptive natural language processing, Muta’s work addresses the critical challenge of making robots not only functional but genuinely conversational in dynamic, unscripted environments. His research has practical implications for service robotics, particularly in hospitality and public information roles. Muta’s achievements highlight a pragmatic, iterative approach to robot learning, offering valuable insights for students and researchers interested in bridging the gap between laboratory prototypes and robust, real-world robotic assistants.
Research Focus
Key Achievements
Top Papers
- 1Conversational Bootstrapping and Other Tricks of a Concierge Robot15 citations · 2017