When do we smile? Analysis and modeling of the nonverbal context of listener smiles in conversation

Abstract

In this paper we will look into reactive models for embodied conversational agents for generating smiling behavior. One trigger for smiling behaviour is smiling of the human interlocutor which is used in reactive models based on mimicry. However, other features might be useful as well. In order to develop such models we look at the nonverbal context of smiles in human-human conversation. We make a distinction between three types of smiles - amused, polite and embarrassed - and highlighted differences in context where each type occurs in conversation. Using machine learning techniques we have build predictive models using the nonverbal contextual features analyzed. Results show that reactive models can offer an interesting contribution to the generation of smiling behaviors. © 2011 Springer-Verlag.