An Emotional Gesture-based Dialogue Management System using Behavior Network

Abstract

Since robots have been used widely recently, research about human-robot communication is in process actively. Typically, natural language processing or gesture generation have been applied to human-robot interaction. However, existing methods for communication among robot and human have their limits in performing only static communication, thus the method for more natural and realistic interaction is required. In this paper, an emotional gesture based dialogue management system is proposed for sophisticated human-robot communication. The proposed system performs communication by using the Bayesian networks and pattern matching, and generates emotional gestures of robots in real-time while the user communicates with the robot. Through emotional gestures robot can communicate the user more efficiently also realistically. We used behavior networks as the gesture generation method to deal with dialogue situations which change dynamically. Finally, we designed a usability test to confirm the usefulness of the proposed system by comparing with the existing dialogue system.