論文

査読有り
2019年

On the Importance of Representations for Speech-Driven Gesture Generation

AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS
  • Taras Kucherenko
  • ,
  • Dai Hasegawa
  • ,
  • Naoshi Kaneko
  • ,
  • Gustav Eje Henter
  • ,
  • Hedvig Kjellstrom

開始ページ
2072
終了ページ
2074
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
出版者・発行元
ASSOC COMPUTING MACHINERY

This paper presents a novel framework for automatic speech-driven gesture generation applicable to human-agent interaction, including both virtual agents and robots. Specifically, we extend recent deep-learning-based, data-driven methods for speech-driven gesture generation by incorporating representation learning. Our model takes speech features as input and produces gestures in the form of sequences of 3D joint coordinates representing motion as output. The results of objective and subjective evaluations confirm the benefits of the representation learning.


リンク情報
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000474345000309&DestApp=WOS_CPL
URL
http://dl.acm.org/citation.cfm?id=3332014
Dblp Cross Ref
https://dblp.uni-trier.de/conf/atal/2019
Dblp Url
https://dblp.uni-trier.de/db/conf/atal/aamas2019.html#KucherenkoHKHK19

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