Interruption Handling for Conversational Robots
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909594680295424 |
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| author | Cao, Shiye Moon, Jiwon Mahmood, Amama Antony, Victor Nikhil Xiao, Ziang Liu, Anqi Huang, Chien-Ming |
| author_facet | Cao, Shiye Moon, Jiwon Mahmood, Amama Antony, Victor Nikhil Xiao, Ziang Liu, Anqi Huang, Chien-Ming |
| contents | Interruptions, a fundamental component of human communication, can enhance the dynamism 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_01568 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Interruption Handling for Conversational Robots Cao, Shiye Moon, Jiwon Mahmood, Amama Antony, Victor Nikhil Xiao, Ziang Liu, Anqi Huang, Chien-Ming Human-Computer Interaction Robotics Interruptions, a fundamental component of human communication, can enhance the dynamism 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. |
| title | Interruption Handling for Conversational Robots |
| topic | Human-Computer Interaction Robotics |
| url | https://arxiv.org/abs/2501.01568 |