Towards a listening agent: a system generating audiovisual laughs and smiles to show interest

In this work, we experiment with the use of smiling and laughter in order to help create more natural and efficient listening agents. We present preliminary results on a system which predicts smile and laughter sequences in one dialogue participant based on observations of the other participant's behavior. This system also predicts the level of intensity or arousal for these sequences. We also describe an audiovisual concatenative synthesis process used to generate laughter and smiling sequences, producing multilevel amusement expressions from a dataset of audiovisual laughs. We thus present two contributions: one in the generation of smiling and laughter responses, the other in the prediction of what laughter and smiles to use in response to an interlocutor's behaviour. Both the synthesis system and the prediction system have been evaluated via Mean Opinion Score tests and have proved to give satisfying and promising results which open the door to interesting perspectives.