Publication:
Multimodal data collection of human-robot humorous interactions in the JOKER project

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Devillers, Laurence
Rosset, Sophie
Duplessis, Guillaume Dubuisson
Sehili, Mohamed A.
Bechade, Lucile
Delaborde, Agnes
Gossart, Clement
Letard, Vincent
Yang, Fan
Yemez, Yucel

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Publication Date

2015

Language

English

Type

Conference proceeding

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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.

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Source:

2015 International Conference on Affective Computing and Intelligent Interaction (ACII)

Publisher:

Institute of Electrical and Electronics Engineers (IEEE)

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Subject

Computer Science, Artificial intelligence, Computer science, information systems, Electrical electronics engineering

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