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.

翻译：社交机器人不仅需要理解人类意图，还需有效向用户传达其自身意图或内部状态。本研究探索利用声化技术提供显式听觉反馈，以增强人机交互中的相互理解。我们提出一种新颖的声化方法，用于传达机器人的内部状态，该状态与其对附近个体的感知及交互意图相关联。通过双重用户研究对该方法进行评估：一项包含26名参与者的在线视频调查，以及一项包含10名参与者的现场实验。结果表明，虽然声化技术提升了机器人的表现力与沟通效能，但听觉反馈的设计仍需改进以优化用户体验。参与者认为听觉提示具有实用性，但普遍反馈音效单调乏味且令人不适。这些发现强调了在开发更高效、更具吸引力的人机交互系统时，精心设计听觉反馈的重要性。