• DocumentCode
    3703337
  • Title

    Multimodal data collection of human-robot humorous interactions in the Joker project

  • Author

    Laurence Devillers;Sophie Rosset;Guillaume Dubuisson Duplessis;Mohamed A. Sehili;Lucile B?chade;Agn?s Delaborde;Clement Gossart;Vincent Letard;Fan Yang;Y?cel Yemez;Bekir B. T?rker;Metin Sezgin;Kevin El Haddad;St?phane Dupont;Daniel Luzzati;Yannick Esteve;

  • Author_Institution
    LIMSI-CNRS, Paris, France
  • fYear
    2015
  • Firstpage
    348
  • Lastpage
    354
  • 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.
  • Keywords
    "Robots","Data collection","Context","Pragmatics","Databases","Speech","Adaptation models"
  • Publisher
    ieee
  • Conference_Titel
    Affective Computing and Intelligent Interaction (ACII), 2015 International Conference on
  • Electronic_ISBN
    2156-8111
  • Type

    conf

  • DOI
    10.1109/ACII.2015.7344594
  • Filename
    7344594