Natsuki Oka
Papers
17
Total Citations
119
H-Index
6
About
Natsuki Oka is a leading researcher in human-robot interaction, with a focus on designing robots that can adapt to and communicate naturally with humans, especially children. Her work centers on key areas such as mutual adaptive speech interfaces, robot-directed speech detection, and the social dynamics of mimicry in human-agent interactions. Oka’s major contributions include developing the Multimodal Semantic Confidence (MSC) measure, a novel method for robots to detect when speech is directed at them versus others, enhancing situational understanding in physical tasks. She also pioneered strategies for robotic playmates to engage shy children, demonstrating that an optimal mimicry rate of about 83% can increase likability and motivation for helping. Her research on robot-mediated handholding combined with video calls has shown promise in enhancing feelings of closeness in remote communication. With her most-cited paper, “Toward playmate robots that can play with children considering personality,” garnering 33 citations, Oka’s work has significant impact, influencing the design of more empathetic and effective interactive agents. Her achievements include advancing top-down visual attention control and robust child behavior tracking, making her a notable figure in creating socially intelligent robots.
Research Focus
Key Achievements
Top Papers
- 1Toward playmate robots that can play with children considering personality33 citations · 2014
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- 9The Optimum Rate of Mimicry in Human-Agent Interaction6 citations · 2016
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