Unintended Consonances: Methods to Understand Robot Motor Sound Perception
Unintended Consonances: Methods to Understand Robot Motor Sound Perception
复制标题
意想不到的协和：理解机器人电机声音感知的方法
DOI：
10.1145/3290605.3300730
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
I. Berget
中科院分区：
文献类型：
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作者：
D. Moore;T. Dahl;P. Varela;Wendy Ju;T. Næs;I. Berget
最近的研究表明，机器人的马达发出的声音可以影响用户对机器人特征的感知。为了更深入地了解用户与特定声音特征的联系，我们采用了感官科学的方法，包括检查所有适用（CATA）问题和极化感官定位（PSP），以在在线调查中梳理出运动声音的微小差异。这些方法对于未经训练的人来说是直接的，在在线环境中进行，数学上严格，并且可以探索各种微妙的听觉和感知刺激。我们描述了如何使用这些方法，用几种直观的视觉表示来解释结果，并表明结果与以前对同一数据集的研究一致。最后，我们讨论了应用这些方法研究人机交互社区中微妙现象的好处和局限性。
Recent research suggests that a robot's motors make sounds that can influence users' perception of the robot's characteristics. To more deeply understand users' associations with specific sonic characteristics, we adapted methods from sensory science including Check All That Apply (CATA) questions and Polarized Sensory Positioning (PSP) to tease out small differences in motor sounds in an online survey. These methods are straightforward for untrained people to do in an online setting, mathematically rigorous, and can explore a variety of subtle auditory and perceptual stimuli. We describe how to use these methods, interpret the results with several intuitive visual representations, and show that the results align with a previous study of the same dataset. We close by discussing benefits and limitations of applying these methods to study subtle phenomena in the HCI community.