Learning Gaze Behaviors for Balancing Participation in Group Human-Robot Interactions
Author:
Affiliation:
1. KTH Royal Institute of Technology
2. Yale University
Funder
Swedish Research Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9889327/9889305/09889416.pdf?arnumber=9889416
Reference51 articles.
1. Multidimensional binary search trees used for associative searching
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3. Maintaining awareness of the focus of attention of a conversation: A robot-centric reinforcement learning approach
4. Speech Driven Backchannel Generation Using Deep Q-Network for Enhancing Engagement in Human-Robot Interaction
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1. Interaction-Shaping Robotics: Robots That Influence Interactions between Other Agents;ACM Transactions on Human-Robot Interaction;2024-03-11
2. Identifying the Focus of Attention in Human-Robot Conversational Groups;International Conference on Human-Agent Interaction;2023-12-04
3. Affective Computing for Human-Robot Interaction Research: Four Critical Lessons for the Hitchhiker;2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN);2023-08-28
4. Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research;International Journal of Social Robotics;2023-03-08
5. Design Implications for Effective Robot Gaze Behaviors in Multiparty Interactions;2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI);2022-03-07
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