What makes rhythms hard to perform? An investigation using Steve Reich's Clapping Music

PLoS One. 2018 Oct 18;13(10):e0205847. doi: 10.1371/journal.pone.0205847. eCollection 2018.


Clapping Music is a minimalist work by Steve Reich based on twelve phased variations of a rhythmic pattern. It has been reimagined as a game-based mobile application, designed with a dual purpose. First, to introduce new audiences to the Minimalist genre through interaction with the piece presented as an engaging game. Second, to use large-scale data collection within the app to address research questions about the factors determining rhythm production performance. The twelve patterns can be differentiated using existing theories of rhythmic complexity. Using performance indicators from the game such as tap accuracy we can determine which patterns players found most challenging and so assess hypotheses from theoretical models with empirical evidence. The app has been downloaded over 140,000 times since the launch in July 2015, and over 46 million rows of gameplay data have been collected, requiring a big data approach to analysis. The results shed light on the rhythmic factors contributing to performance difficulty and show that the effect of making a transition from one pattern to the next is as significant, in terms of pattern difficulty, as the inherent complexity of the pattern itself. Challenges that arose in applying this novel approach are discussed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Auditory Perception / physiology*
  • Big Data
  • Data Mining / statistics & numerical data*
  • Datasets as Topic
  • Games, Experimental*
  • Humans
  • Mobile Applications / statistics & numerical data
  • Music / psychology*
  • Periodicity*

Grant support

This research was supported by The Digital R&D Fund for the Arts (https://www.nesta.org.uk/archive-pages/steve-reichs-clapping-music/), a partnership between Nesta, the Arts Council England and the Arts and Humanities Research Council (AHRC) awarded to MP in partnership with The London Sinfonietta and Touchpress. Further data collection, outreach work in schools and analysis was funded by an award from the Engineering and Physical Sciences Research Council (EPSRC) Platform Grant EP/K009559/1 (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/K009559/1; PI: Mark Sandler; MP is a co-investigator), held at Queen Mary University of London (QMUL). This research utilised QMUL’s MidPlus computational facilities, supported by QMUL Research-IT and funded by EPSRC grant EP/K000128/1 (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/K000128/1).