Hearing movement: How taiko can inform automatic recognition of expressive movement qualities

Shannon Cuykendall, Michael Junokas, Mohammad Amanzadeh, David Kim Tcheng, Yawen Wang, Thecla Schiphorst, Guy E Garnett, Philippe Pasquier

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

Abstract

We describe the first stages of exploratory research undertaken to analyze expressive movement qualities of taiko performance, a Japaense artistic practice that combines stylized movement with drumming technique. The eventual goals of this research are to answer 1) Can expressive visual qualities of taiko be heard in the sound and 2) Can expressive sonic qualities of taiko be seen in the movement? We achieved high accuracy across multiple machine-learning algorithms in recognizing key sonic and visual qualities of taiko performance. In contrast to many current methods of studying expressive qualities of movement, we inform our data collection process and annotations with taiko technique. We seek to understand how the fundamentals of taiko create expression. More broadly, we suggest that codified artistic practices, like taiko, can inform automatic recognition and generation of expressive movement qualities that have been challenging to reliably classify, parse, and detect. In future work we propose ways to generalize expressive features of taiko so they can be recognized in other movement contexts.

Original languageEnglish (US)
Title of host publicationMOCO 2015 - Proceedings of the 2nd International Workshop on Movement and Computing
Subtitle of host publicationIntersecting Art, Meaning, Cognition, Technology
PublisherAssociation for Computing Machinery
Pages140-147
Number of pages8
ISBN (Electronic)9781450334570
DOIs
StatePublished - Aug 14 2015
Event2nd International Workshop on Movement and Computing, MOCO 2015 - Vancouver, Canada
Duration: Aug 14 2015Aug 15 2015

Publication series

NameACM International Conference Proceeding Series
Volume14-15-August-2015

Other

Other2nd International Workshop on Movement and Computing, MOCO 2015
CountryCanada
CityVancouver
Period8/14/158/15/15

Keywords

  • Expressive movement
  • Machine learning
  • Movement classification
  • Musical gesture
  • Sound-producing gesture
  • Taiko

ASJC Scopus subject areas

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

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  • Cite this

    Cuykendall, S., Junokas, M., Amanzadeh, M., Tcheng, D. K., Wang, Y., Schiphorst, T., Garnett, G. E., & Pasquier, P. (2015). Hearing movement: How taiko can inform automatic recognition of expressive movement qualities. In MOCO 2015 - Proceedings of the 2nd International Workshop on Movement and Computing: Intersecting Art, Meaning, Cognition, Technology (pp. 140-147). (ACM International Conference Proceeding Series; Vol. 14-15-August-2015). Association for Computing Machinery. https://doi.org/10.1145/2790994.2791004