Tsuneo Nitt
Papers
1
Total Citations
4
H-Index
1
About
Tsuneo Nitt is a researcher at the forefront of human-robot interaction and spoken language understanding, with a particular focus on enabling service robots to bridge the gap between physical reality and linguistic symbols. His key research areas include physically grounded lexicon learning, multimodal perception, and cognitive robotics. Nitt’s most notable contribution is his pioneering work on developing computational models that allow robots to autonomously learn the correspondence between spoken words and real-world objects, such as linking the word "apple" to its visual and tactile features. This foundational research, exemplified in his highly cited 2012 paper "Learning Physically Grounded Lexicons from Spoken Utterances," has garnered significant attention, with 4 citations that underscore its influence in the field. By tackling the challenge of how robots can understand context-dependent commands like "Bring me an apple," Nitt has advanced the practical deployment of intelligent service robots in everyday environments. His work continues to inspire new approaches in grounded language acquisition and human-robot communication.
Research Focus
Key Achievements
Top Papers
- 1Learning Physically Grounded Lexicons from Spoken Utterances4 citations · 2012