Robotics: Science and Systems XXI

Interruption Handling for Conversational Robots

Shiye Cao, Jiwon Moon, Amama Mahmood, Victor Nikhil Antony, Ziang Xiao, Anqi Liu, Chien-Ming Huang

Abstract:

Interruptions, a fundamental component of human communication, can enhance the dynamics and effectiveness of conversations, but only when effectively managed by all parties involved. Despite advancements in robotic systems, state-of-the-art systems still have limited capabilities in handling user-initiated interruptions in real-time. Prior research has primarily focused on post hoc analysis of interruptions. To address this gap, we present a system that detects user-initiated interruptions and manages them in real-time based on the interrupter's intent (i.e., cooperative agreement, cooperative assistance, cooperative clarification, or disruptive interruption). The system was designed based on interaction patterns identified from human-human interaction data. We integrated our system into an LLM-powered social robot and validated its effectiveness through a timed decision-making task and a contentious discussion task with 21 participants. Our system successfully handled 93.69% (n=104/111) of user-initiated interruptions. We discuss our learnings and their implications for designing interruption-handling behaviors in conversational robots.

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Bibtex:

  
@INPROCEEDINGS{CaoS-RSS-25, 
    AUTHOR    = {Shiye Cao AND Jiwon Moon AND Amama Mahmood AND Victor Nikhil Antony AND Ziang Xiao AND Anqi Liu AND Chien-Ming Huang}, 
    TITLE     = {{Interruption Handling for Conversational Robots}}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2025}, 
    ADDRESS   = {LosAngeles, CA, USA}, 
    MONTH     = {June}, 
    DOI       = {10.15607/RSS.2025.XXI.089} 
}