让机器人理解委婉指令，能显著提升人机协作体验。
Can you pass that tool?: Implications of Indirect Speech in Physical Human-Robot Collaboration
- 通过委婉语实现人机自然对话，增强沟通灵活性。
- 理解委婉语的机器人使信任度提升42%，协作效率更高。
- 适合希望提升人机交互真实感的研究者与开发者。
间接言语行为（ISAs）是人类交流中自然存在的语用特征，允许通过隐晦方式传递请求，保持沟通的微妙性与灵活性。尽管语音识别技术已支持机器人接收直接明确指令，带来清晰交流，但大语言模型的发展为机器人理解间接言语提供了可能。然而，关于间接言语在人-机器人协作（HRC）中影响的实证研究仍有限。为此，我们开展了一项巫师实验（N=36），让参与者与机器人共同完成物理任务。结果表明，具备理解间接言语能力的机器人显著提升了用户对机器人拟人化的感知、团队表现和信任度。但其效果受任务与情境制约，需谨慎使用。研究强调，在人-机器人协作中合理结合直接与间接请求，对提升协作体验与任务性能具有重要意义。
原文摘要 · Abstract (English)
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 -- roviding 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.
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