Publication: Multimodal data collection of human-robot humorous interactions in the JOKER project
Program
KU Authors
Co-Authors
Devillers, Laurence
Rosset, Sophie
Duplessis, Guillaume Dubuisson
Sehili, Mohamed A.
Bechade, Lucile
Delaborde, Agnes
Gossart, Clement
Letard, Vincent
Yang, Fan
Yemez, Yucel
Advisor
Publication Date
2015
Language
English
Type
Conference proceeding
Journal Title
Journal ISSN
Volume Title
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.
Description
Source:
2015 International Conference on Affective Computing and Intelligent Interaction (ACII)
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Keywords:
Subject
Computer Science, Artificial intelligence, Computer science, information systems, Electrical electronics engineering