Modélisation de comportements non-verbaux et d'attitudes sociales dans la simulation de groupes conversationnels

Abstract : Embodied Conversational Agents are virtual characters which main purpose is to interact with a human user. They are used in various domains such as personal assistance, social training or video games for instance. In order to improve their capabilities, it is possible to give them the ability to produce human-like behaviors. The users, even if they are aware that they interact with a machine, are still capable of analyzing and identifying social behaviors through the signals produced by these virtual characters. The research in Embodied Conversational Agents has focused for a long time on the reproduction and recognition of emotions by virtual characters and now the focus is on the ability to express different social attitudes. These attitudes show a behavioral style and are expressed through different modalities of the body, like the facial expressions, the gestures or the gazes for instance. We proposed a model that allows an agent to produce different nonverbal behaviors expressing different social attitudes in a conversation. The whole set of behaviors produced by our model allows a goup of agents animated by it to simulate a conversation, without any verbal content. Two evaluations of the model were conducted, one on the Internet and one in a Virtual Reality environment, to verify that the attitudes produced are well recognized
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Brian Ravenet. Modélisation de comportements non-verbaux et d'attitudes sociales dans la simulation de groupes conversationnels. Interface homme-machine [cs.HC]. Télécom ParisTech, 2015. Français. ⟨NNT : 2015ENST0075⟩. ⟨tel-01570050⟩

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