L. Devillers, S. Rosset, G. D. Duplessis, M. A. Sehili, Lucile Bechade, Agnès Delaborde, Clément Gossart, Vincent Letard, Fan Yang, Y. Yemez, Bekir Berker Turker, T. M. Sezgin, Kevin El Haddad, S. Dupont, Daniel Luzzati, Y. Estève, E. Gilmartin, N. Campbell
{"title":"Multimodal data collection of human-robot humorous interactions in the Joker project","authors":"L. Devillers, S. Rosset, G. D. Duplessis, M. A. Sehili, Lucile Bechade, Agnès Delaborde, Clément Gossart, Vincent Letard, Fan Yang, Y. Yemez, Bekir Berker Turker, T. M. Sezgin, Kevin El Haddad, S. Dupont, Daniel Luzzati, Y. Estève, E. Gilmartin, N. Campbell","doi":"10.1109/ACII.2015.7344594","DOIUrl":null,"url":null,"abstract":"Thanks to a remarkably great ability to show amusement and engagement, laughter is one of the most important social markers in human interactions. Laughing together can actually help to set up a positive atmosphere and favors the creation of new relationships. This paper presents a data collection of social interaction dialogs involving humor between a human participant and a robot. In this work, interaction scenarios have been designed in order to study social markers such as laughter. They have been implemented within two automatic systems developed in the Joker project: a social dialog system using paralinguistic cues and a task-based dialog system using linguistic content. One of the major contributions of this work is to provide a context to study human laughter produced during a human-robot interaction. The collected data will be used to build a generic intelligent user interface which provides a multimodal dialog system with social communication skills including humor and other informal socially oriented behaviors. This system will emphasize the fusion of verbal and non-verbal channels for emotional and social behavior perception, interaction and generation capabilities.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"122 1","pages":"348-354"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACII.2015.7344594","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
Thanks to a remarkably great ability to show amusement and engagement, laughter is one of the most important social markers in human interactions. Laughing together can actually help to set up a positive atmosphere and favors the creation of new relationships. This paper presents a data collection of social interaction dialogs involving humor between a human participant and a robot. In this work, interaction scenarios have been designed in order to study social markers such as laughter. They have been implemented within two automatic systems developed in the Joker project: a social dialog system using paralinguistic cues and a task-based dialog system using linguistic content. One of the major contributions of this work is to provide a context to study human laughter produced during a human-robot interaction. The collected data will be used to build a generic intelligent user interface which provides a multimodal dialog system with social communication skills including humor and other informal socially oriented behaviors. This system will emphasize the fusion of verbal and non-verbal channels for emotional and social behavior perception, interaction and generation capabilities.