Entrainment between speech and gestures in human-robot interaction

Social robots providing services in real environments have been developed recently. Such robots should appropriately recognize orders from users in the manner of communications like humans. However, their communication styles are too diverse to achieve this goal. If the robot could shape the styles, its recognition ability would increase. Entrainment has attracted attention as a phenomenon to synchronize human gestures and speech implicitly with robot gestures and speech. Previous studies have reported entrainment occurring within the same modality, but we need to clarify the cross-modality effects because human-robot interaction is inherently multi-modal. In this paper, we define “mutual entrainment” as entrainment across different modalities and investigate its effects through a laboratory experiment. We evaluate how the frequency of human pointing gestures varies with the amount of information in robot speech, and as a result, we find that the gesture frequency increases as the amount of information decreases. The results suggest that smoother human-robot communications can be achieved by shaping human behavior through mutual entrainment.