Generation and Evaluation of Audio-Visual Anger Emotional Expression for Android Robot

Abstract

Recent studies in human-human interaction (HHI) have revealed the propensity of negative emotional expression to initiate affiliating functions that are beneficial to the expresser and also help to foster cordiality and closeness amongst interlocutors. However, efforts in human-robot interaction (HRI) have not attempted to investigate the consequences of expression of negative emotion by robots on HRI. Thus, the background of this study as a first step is to furnish humanoid robots with natural audio-visual anger expression for HRI. Based on the analysis results from a multimodal HHI corpus, we implemented different types of gestures related to anger expressions for humanoid robots and carried-out subjective evaluation of the generated anger expressions. Findings from this study revealed that the semantic context and functional content of anger-based utterances play a significant role in the choice of gesture to accompany such utterance. Our current result shows that "Pointing" gesture is adjudged more appropriate for utterances with "you" and anger-based "questioning" utterances; while "both arms spread" and "both arm swing" gestures were evaluated more appropriated for "declarative" and "disagreement" utterances respectively.