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
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"
Conference_Titel :
Affective Computing and Intelligent Interaction (ACII), 2015 International Conference on
Electronic_ISBN :
2156-8111
DOI :
10.1109/ACII.2015.7344594