Taras Kucherenko, Rajmund Nagy, Patrik Jonell, Michael Neff, Hedvig Kjellstrom, G. Henter
{"title":"Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech","authors":"Taras Kucherenko, Rajmund Nagy, Patrik Jonell, Michael Neff, Hedvig Kjellstrom, G. Henter","doi":"10.1145/3472306.3478333","DOIUrl":null,"url":null,"abstract":"We propose a new framework for gesture generation, aiming to allow data-driven approaches to produce more semantically rich gestures. Our approach first predicts whether to gesture, followed by a prediction of the gesture properties. Those properties are then used as conditioning for a modern probabilistic gesture-generation model capable of high-quality output. This empowers the approach to generate gestures that are both diverse and representational. Follow-ups and more information can be found on the project page: https://svito-zar.github.io/speech2properties2gestures/","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3472306.3478333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
We propose a new framework for gesture generation, aiming to allow data-driven approaches to produce more semantically rich gestures. Our approach first predicts whether to gesture, followed by a prediction of the gesture properties. Those properties are then used as conditioning for a modern probabilistic gesture-generation model capable of high-quality output. This empowers the approach to generate gestures that are both diverse and representational. Follow-ups and more information can be found on the project page: https://svito-zar.github.io/speech2properties2gestures/