Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots

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dc.contributor.authorYoon, Youngwooko
dc.contributor.authorKo, Woo-Riko
dc.contributor.authorJang, Minsuko
dc.contributor.authorLee, Jaeyeonko
dc.contributor.authorKim, Jaehongko
dc.contributor.authorLee, Geehyukko
dc.date.accessioned2020-01-20T05:21:11Z-
dc.date.available2020-01-20T05:21:11Z-
dc.date.created2020-01-20-
dc.date.created2020-01-20-
dc.date.created2020-01-20-
dc.date.created2020-01-20-
dc.date.created2020-01-20-
dc.date.issued2019-05-22-
dc.identifier.citation2019 International Conference on Robotics and Automation (ICRA), pp.4303 - 4309-
dc.identifier.urihttp://hdl.handle.net/10203/271588-
dc.description.abstractCo-speech gestures enhance interaction experiences between humans as well as between humans and robots. Most existing robots use rule-based speech-gesture association, but this requires human labor and prior knowledge of experts to be implemented. We present a learning-based co-speech gesture generation that is learned from 52 h of TED talks. The proposed end-to-end neural network model consists of an encoder for speech text understanding and a decoder to generate a sequence of gestures. The model successfully produces various gestures including iconic, metaphoric, deictic, and beat gestures. In a subjective evaluation, participants reported that the gestures were human-like and matched the speech content. We also demonstrate a co-speech gesture with a NAO robot working in real time.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleRobots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots-
dc.typeConference-
dc.identifier.wosid000494942303022-
dc.identifier.scopusid2-s2.0-85069740325-
dc.type.rimsCONF-
dc.citation.beginningpage4303-
dc.citation.endingpage4309-
dc.citation.publicationname2019 International Conference on Robotics and Automation (ICRA)-
dc.identifier.conferencecountryCN-
dc.identifier.conferencelocationMontreal Convention Center, Montreal-
dc.identifier.doi10.1109/icra.2019.8793720-
dc.contributor.localauthorLee, Geehyuk-
dc.contributor.nonIdAuthorKo, Woo-Ri-
dc.contributor.nonIdAuthorJang, Minsu-
dc.contributor.nonIdAuthorLee, Jaeyeon-
dc.contributor.nonIdAuthorKim, Jaehong-
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CS-Conference Papers(학술회의논문)
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