Data-Driven design of sound for enhancing the perception of expressive robotic movement

Luke Dahl, Jon Bellona, Lin Bai, Amy Laviers

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Since people communicate intentions and inner states through movement, robots can interact with humans if they too can modify their movements to communicate changing state. .ese movements, which may be seen as supplementary to those required for workspace tasks, may be termed "expressive." However, robot hardware, which cannot recreate the same range of dynamics as human limbs, o.en limit expressive capacity. One solution is to augment expressive robotic movement with expressive sound. To that end, this paper presents a study to find a qualitative mapping between movement and sound. Musicians were asked to vocalize sounds in response to animations of a simple simulated upper body movement performed with different movement qualities, parametrized according to Laban's Effort System. qualitative labelling and quantitative signal analysis of these sounds suggests a number of correspondences between movement qualities and sound qualities. these correspondences are presented and analyzed here to set up future work that will test user perceptions when expressive movements and sounds are used in conjunction.

Original languageEnglish (US)
Title of host publicationMOCO 2017 - Proceedings of the 4th International Conference on Movement Computing
EditorsKiona Niehaus
PublisherAssociation for Computing Machinery
ISBN (Electronic)1595930361, 9781450352093
StatePublished - Jun 28 2017
Event4th International Conference on Movement Computing, MOCO 2017 - London, United Kingdom
Duration: Jun 28 2017Jun 30 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F129150


Other4th International Conference on Movement Computing, MOCO 2017
Country/TerritoryUnited Kingdom


  • Human-robot interaction
  • Laban effort system
  • Mir toolbox
  • Movement quality
  • Music
  • Sound-motion

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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