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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/16711

Title: Learning from Humans to Generate Communicative Gestures for Social Robots
Authors: Tuyen, Nguyen Tan Viet
Elibol, Armagan
Chong, Nak Young
Issue Date: 2020-06
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: Proceedings of the 2020 17th International Conference on Ubiquitous Robots (UR)
Start page: 264
End page: 269
DOI: 10.1109/UR49135.2020.9144985
Abstract: Non-verbal behaviors play an essential role in human-human interaction, allowing people to convey their intention and attitudes, and affecting social outcomes. Of particular importance in the context of human-robot interaction is that the communicative gestures are expected to endow social robots with the capability of emphasizing its speech, describing something, or showing its intention. In this paper, we propose an approach to learn the relation between human behaviors and natural language based on a Conditional Generative Adversarial Network (CGAN). We demonstrated the validity of our model through a public dataset. The experimental results indicated that the generated human-like gestures correctly convey the meaning of input sentences. The generated gestures were transformed into the target robot’s motion, being the robot’s personalized communicative gestures, which showed significant improvements over the baselines and could be widely accepted and understood by the general public.
Rights: This is the author's version of the work. Copyright (C) 2020 IEEE. Proceedings of the 2020 17th International Conference on Ubiquitous Robots (UR), 2020, pp.264-269. 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/10119/16711
Material Type: author
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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