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タイトル: Autonomous Speech Volume Control for Social Robots in a Noisy Environment Using Deep Reinforcement Learning
著者: Bui, Ha-Duong
Chong, Nak Young
キーワード: Social Human-Robot Interaction
Speech Volume Control
Reinforcement Learning
発行日: 2019-12
出版者: Institute of Electrical and Electronics Engineers (IEEE)
誌名: Proceeding of the IEEE International Conference on Robotics and Biomimetics (ROBIO)
開始ページ: 1263
終了ページ: 1268
DOI: 10.1109/ROBIO49542.2019.8961810
抄録: This paper presents a novel approach to automatically adjusting the speech volume of a socially assistive humanoid robot to enhance the quality of human-robot interactions. We apply the Deep Q-learning algorithm to enable the robot to adapt to the preferences of a user in the volume of the robot’s voice in social contexts. Subjective experiments were conducted to verify the validity of the proposed system. Twenty-three human subjects had social conversations with humanoid robots across various noisy environments. Participants rated their perception of the robots’ voices in terms of clearness and comfortability through a questionnaire. The results show that the robot equipped with our framework outperforms other experimental robots in trials. This study confirmed the effectiveness of the proposed autonomous speech volume control system for social robots communicating with people in noisy environments.
Rights: This is the author's version of the work. Copyright (C) 2019 IEEE. Proceeding of the IEEE International Conference on Robotics and Biomimetics (ROBIO), 2019, pp.1263-1268. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/10119/16211
資料タイプ: author
出現コレクション:b11-1. 会議発表論文・発表資料 (Conference Papers)

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