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Unintended Consonances: Methods to Understand Robot Motor Sound Perception

Abstract

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.

Category

Academic chapter

Language

English

Author(s)

  • Dylan Moore
  • Tobias Dahl
  • Paula Varela
  • Wendy Ju
  • Tormod Næs
  • Ingunn Berget

Affiliation

  • SINTEF Digital / Smart Sensors and Microsystems
  • USA
  • Stanford University
  • Nofima, Norwegian Institute of Food, Fisheries and Aquaculture Research

Year

2019

Publisher

Association for Computing Machinery (ACM)

Book

ACM CHI Conference on Human Factors in Computing Systems

ISBN

9781450359702

Page(s)

1 - 12

View this publication at Norwegian Research Information Repository