Towards a Model for Recognising the Social Attitude in Natural Interaction with Embodied Agents

Abstract

The problem of implementing socially intelligent agents has been widely investigated in the field of both Embodied Conversational Agents (ECAs) and Social Robots that have the advantage of offering to people the possibility to relate with computer media at a social level. We focus our study on the recognition of the social response of users to embodied agents in the context of ambient intelligence. In this paper we describe how we extended a model for recognizing the social attitude in natural conversation from text by adding two additional knowledge sources: speech and gestures.