Can you pass that tool?: Implications of Indirect Speech in Physical Human-Robot Collaboration

要旨

Indirect speech acts (ISAs) are a natural pragmatic feature of human communication, allowing requests to be conveyed implicitly while maintaining subtlety and flexibility. Although advancements in speech recognition have enabled natural language interactions with robots through direct, explicit commands—providing clarity in communication—the rise of large language models presents the potential for robots to interpret ISAs. However, empirical evidence on the effects of ISAs on human-robot collaboration (HRC) remains limited. To address this, we conducted a Wizard-of-Oz study (N=36), engaging a participant and a robot in collaborative physical tasks. Our findings indicate that robots capable of understanding ISAs significantly improve human's perceived robot anthropomorphism, team performance, and trust. However, the effectiveness of ISAs is task- and context-dependent, thus requiring careful use. These results highlight the importance of appropriately integrating direct and indirect requests in HRC to enhance collaborative experiences and task performance.

著者
Yan Zhang
University of Melbourne, Melbourne, VIC, Australia
Tharaka Sachintha Ratnayake
University of Melbourne, Melbourne, Australia
Cherie Sew
University of Melbourne, Melbourne, Australia
Jarrod Knibbe
The University of Queensland, St Lucia, QLD, Australia
Jorge Goncalves
University of Melbourne, Melbourne, Australia
Wafa Johal
University of Melbourne, Melbourne, VIC, Australia
DOI

10.1145/3706598.3713780

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713780

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Non-Verbal Communications

G401
7 件の発表
2025-04-29 23:10:00
2025-04-30 00:40:00
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