Exploring Humor as a Repair Strategy During Communication Breakdowns with Voice Assistants
Open accessAbstract
Voice assistants are becoming increasingly useful and support realistic conversations, yet communication breakdowns occur. We investigate the use of humor as a repair strategy in an experiment where the voice assistant makes a mistake and then utilizes one of four humorous personalities to repair the breakdown in the conversation. We conducted a study with 30 participants, each of whom took the Humor Style Questionnaire (HSQ) to understand their predisposition to humor type, and then engaged in conversation with each of the four humorous personalities and one that was designed to give neutral repair responses (non-humorous). Aggressive personalities were rated as the funniest, yet there was no clear connection between the participant’s humor style and their preferred voice assistant personality. While humorous responses were successful in repairing communication breakdowns, participants overall preferred non-humorous responses. This research provides insight into the role of humor in communication breakdown repair with voice assistants.
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System-repair strategies research explores how SDSs can be designed to effectively manage conversations, including mechanisms for grounding, interruptions, and corrections, and assesses their impact on user experience and SDS efficiency.
“System-repair strategies research explores how SDSs can be designed to effectively manage conversations, including mechanisms for grounding, interruptions, and corrections, and assesses their impact on user experience and SDS efficiency [17, 60].”
From System and User Strategies to Repair Conversational Breakdowns of Spoken Dialogue Systems: A Scoping Review (2024) · cites this paper as [17]
Sections 3.1–3.3 describe clarification and repetition after voice-assistant misunderstandings and measures of user satisfaction and perceptions. The paper therefore supports the claim's general point about repair strategies and user experience, but the cited passages do not address interruptions, corrections, or SDS efficiency, and its focus is narrower than the range of mechanisms claimed. (LLM, conf=0.86)
Experimental — accuracy not yet measuredCertain domains are aligned with particular platform types, indicating specialised applications; for example, the smart home assistance domain was associated with Amazon Alexa [6, 17, 19, 33, 46, 60], the INSPIRE system [74], and devices not specified [38].
“Certain domains are aligned with particular platform types, indicating specialised applications e.g. the smart home assistance domain was associated with devices such as Amazon Alexa [6, 17, 19, 33, 46, 60], the INSPIRE system [74], and devices not specified [38].”
From System and User Strategies to Repair Conversational Breakdowns of Spoken Dialogue Systems: A Scoping Review (2024) · cites this paper as [17]
Approximately half of the SDSs employed in the reviewed studies (N=16) were mock-ups in which participants interacted with the SDSs through Wizard of Oz (WoZ) setups.
“Approximately half of the SDSs (N=16) employed in the reviewed studies were mock-ups in which participants interacted with the SDSs through Wizard of Oz (WoZ) setups(e.g. [17, 77]).”
From System and User Strategies to Repair Conversational Breakdowns of Spoken Dialogue Systems: A Scoping Review (2024) · cites this paper as [17]
Most study participants were drawn from the general population, but four studies specifically included participants with computer science backgrounds [17, 22, 53, 79].
“Although most study participants were drawn from the general population, four studies specifically included participants with computer science backgrounds [17, 22, 53, 79].”
From System and User Strategies to Repair Conversational Breakdowns of Spoken Dialogue Systems: A Scoping Review (2024) · cites this paper as [17]
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Cited by
Sorted by citations
Alghamdi, E., Halvey, M., & Nicol, E. (2024) · ACM Conversational User Interfaces 2024 · doi:10.1145/3640794.3665558 · Cited by 36 · see citing works
- Authors
- Clausen, M., Kyhn, M. P., Papachristos, E., & Merritt, T.
- Affiliations
- Aalborg University (DK)
- Norwegian University of Science and Technology (NO)
- Venue
- Proceedings of the 5th International Conference on Conversational User Interfaces
- Publisher
- ACM
- Published
- 2023-07-19
- Pages
- 1-9
- OpenAlex
- W4384520753
- Cited by
- 12
- References
- 34
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 7 · 2023: 1
- FWCI
- 6.01
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Conference on Conversational User Interfaces (CUI) (publishedVersion)
- VBN Forskningsportal (Aalborg Universitet) (publishedVersion, other-oa)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- Topics
- Social Sciences › Psychology › Social Psychology › Humor Studies and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- humor, repair strategies, communication breakdown, voice assistants, chatbots, personality, humor styles, aggressive humor, user preferences, human-agent interaction
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