A Systematic Cross-Corpus Analysis of Human Reactions to Robot Conversational Failures

Abstract

In this paper, we analyze multimodal behavioral responses to robot failures across different tasks. Two multimodal datasets are examined in which humans interact with guided-task robots in task-oriented dialogues. In both datasets, the robots simulated failures of conversational breakdown and miscommunication typically observed in human-robot interactions. We closely examine human reactions to these failures looking at facial and acoustic features. Our analyses identify the significant behavioral features for automatic detection of such failures in interaction. We also examine human responses to different types of robot failures and if failures occurred early or late in the interaction cause variation in the responses. Our findings indicate that several nonverbal behaviors are consistently present in responses to robots’ failures, e.g., gaze and speech prosody, whereas, linguistic features appear to be task-dependent. We discuss how these findings may generalize to other tasks, and how autonomous robots may identify opportunities to detect and recover from failures in interactions with humans.