研究机器人运行声音如何影响人类感知,提出优化建议。
Sound Judgment: Properties of Consequential Sounds Affecting Human-Perception of Robots

- 通过182人调研分析人类对机器人声音的偏好
- 响亮高频声令人不适,有节奏自然声更受欢迎
- 用可预测、拟自然声改善人机交互体验
机器人在共享环境中的持续使用依赖于积极的人类感知。本研究探讨了机器人运行时产生的后果性声音(consequential sounds)对人类感知的影响。通过对182名参与者观看不同机器人执行典型动作视频后的在线问卷调查,采用主题分析识别出人类对这类声音的偏好与厌恶特征。结果表明:除普遍反感高音调和大音量外,多数参与者更倾向能提供运动目的与轨迹可预测性的有声反馈,而非无声;偏好有节奏的声音,而非尖锐或持续的噪声;许多受访者希望以风声、猫呼噜声等自然声音替代机械噪音。研究揭示了引发负面感知的声音特征,并为优化机器人声音设计提供了方向,有助于提升人机交互质量。
原文摘要 · Abstract (English)
Positive human-perception of robots is critical to achieving sustained use of robots in shared environments. One key factor affecting human-perception of robots are their sounds, especially the consequential sounds which robots (as machines) must produce as they operate. This paper explores qualitative responses from 182 participants to gain insight into human-perception of robot consequential sounds. Participants viewed videos of different robots performing their typical movements, and responded to an online survey regarding their perceptions of robots and the sounds they produce. Topic analysis was used to identify common properties of robot consequential sounds that participants expressed liking, disliking, wanting or wanting to avoid being produced by robots. Alongside expected reports of disliking high pitched and loud sounds, many participants preferred informative and audible sounds (over no sound) to provide predictability of purpose and trajectory of the robot. Rhythmic sounds were preferred over acute or continuous sounds, and many participants wanted more natural sounds (such as wind or cat purrs) in-place of machine-like noise. The results presented in this paper support future research on methods to improve consequential sounds produced by robots by highlighting features of sounds that cause negative perceptions, and providing insights into sound profile changes for improvement of human-perception of robots, thus enhancing human robot interaction.
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。