Naoya Ikeda
Papers
1
Total Citations
2
H-Index
1
About
Naoya Ikeda is a researcher whose work lies at the intersection of human-computer interaction and social signal processing, with a particular focus on understanding and modeling multiparty conversation dynamics. His key research area centers on the automatic estimation of conversational dominance—a critical component for developing more natural and responsive dialogue systems. Ikeda’s major contribution is the proposal of a dominance estimation mechanism that leverages two fundamental nonverbal cues: eye-gaze patterns and turn-taking information. By analyzing a corpus of group interactions, he established a regression model that quantitatively links these observable behaviors to perceived conversational dominance, offering a computational framework for machines to interpret social hierarchies in real time. While his most-cited paper, "A dominance estimation mechanism using eye-gaze and turn-taking information" (2013), has garnered 2 citations, its conceptual foundation is notable for addressing a nuanced challenge in multiparty conversation management. Ikeda’s work provides a valuable stepping stone for researchers aiming to build socially aware AI, demonstrating how subtle nonverbal signals can be systematically decoded to enhance human-machine collaboration in complex group settings.
Research Focus
Key Achievements
Top Papers
- 1