Expression of Personality by Gaze Movements of an Android Robot in Multi-Party Dialogues

Abstract

In this study, we describe an improved version of our proposed model to generate gaze movements (eye and head movements) of a dialogue robot in multi-party dialogue situations, and investigated how the impressions change for models created by data of speakers with different personalities. For that purpose, we used a multimodal three-party dialogue data, and first analyzed the distributions of (1) the gaze target (towards dialogue partners or gaze aversion), (2) the gaze duration, and (3) the eyeball direction during gaze aversion. We then generated gaze behaviors in an android robot (Nikola) with the data of two people who were found to have distinctive personalities, and conducted subjective evaluation experiments. Results showed that a significant difference was found in the perceived personalities between the motions generated by the two models.