用声音反馈让机器人表达内心状态，提升人机互信
Hearing the Robot's Mind: Sonification for Explicit Feedback in Human-Robot Interaction
- 将机器人感知与意图转为可听声音，实现主动沟通
- 26人视频调研+10人现场实验，证实声音能提升表达力
- 适合关注人机交互体验、声音设计的研究者
社交机器人不仅需理解人类意图，还应有效传达自身状态。本研究探索通过声学化（sonification）提供明确的听觉反馈，以增强人机交互中的相互理解。提出一种新型声学化方法，将机器人对附近个体及其互动意图的感知转化为声音信号。通过两阶段用户研究评估：26名参与者参与线上视频问卷调查，10名参与者参与现场实验。结果表明，声学化虽提升了机器人的表达能力与沟通效率，但声音设计仍需优化以改善用户体验。参与者认为听觉提示有用，但普遍感觉声音单调且不悦耳。研究强调，在构建高效、吸引人的交互系统中，精心设计的听觉反馈至关重要。
原文摘要 · Abstract (English)
Social robots are required not only to understand human intentions but also to effectively communicate their intentions or own internal states to users. This study explores the use of sonification to provide explicit auditory feedback, enhancing mutual understanding in HRI. We introduce a novel sonification approach that conveys the robot's internal state, linked to its perception of nearby individuals and their interaction intentions. The approach is evaluated through a two-fold user study: an online video-based survey with $26$ participants and live experiments with $10$ participants. Results indicate that while sonification improves the robot's expressivity and communication effectiveness, the design of the auditory feedback needs refinement to enhance user experience. Participants found the auditory cues useful but described the sounds as uninteresting and unpleasant. These findings underscore the importance of carefully designed auditory feedback in developing more effective and engaging HRI systems.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。