Composing and Analyzing with the Performing Body

  • Guerino Mazzola
  • René Guitart
  • Jocelyn Ho
  • Alex Lubet
  • Maria Mannone
  • Matt Rahaim
  • Florian Thalmann
Chapter
Part of the Computational Music Science book series (CMS)

Summary

In this chapter, we tackle both analysis and composition as reciprocal processes to investigate the performer’s body. We argue that performers, more specifically, the performers’ bodily gestures, are key to the critical understanding and the creation of music. This chapter contains three parts: first, we will investigate the concept of embodied musical gestures through a range of inter-disciplinary scholars, ultimately defining a concept that is useful and fruitful in discussing performance. In the second part, we will use Toru Takemitsu’s Rain Tree Sketch II for Piano (1994) as a testing ground for analyzing with the performative body as the starting point. And lastly, we will discuss how composing with performative gestures in my composition Sheng (2016) for piano, audience’s smartphones, and fixed audio playback elicits the cross-modal, intersensory nature of embodied musical gestures. Indeed, the concept of embodied musical gesture has the potential to dissolve the artificial fractures between the activities of thinking, creating, and doing. Analyzing and composing with the performing body do away with this mind-body split, offering refreshing and generative insights that do justice to the physical nature of music making.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  • Guerino Mazzola
    • 1
  • René Guitart
    • 2
  • Jocelyn Ho
    • 3
  • Alex Lubet
    • 1
  • Maria Mannone
    • 1
  • Matt Rahaim
    • 1
  • Florian Thalmann
    • 4
  1. 1.School of MusicUniversity of MinnesotaMinneapolisUSA
  2. 2.Institut de Mathématiques de JussieuUniversité Diderot Paris 7ParisFrance
  3. 3.Department of MusicUCLA Herb Alpert School of MusicLos AngelesUSA
  4. 4.School of Electronic Engineering and Computer ScienceQueen Mary University of LondonLondonUK

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