Method development for multimodal data corpus analysis of expressive instrumental music performance

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Abstract

Musical performance is a multimodal experience, for performers and listeners alike. This paper reports on a pilot study which constitutes the first step toward a comprehensive approach to the experience of music as performed. We aim at bridging the gap between qualitative and quantitative approaches, by combining methods for data collection. The purpose is to build a data corpus containing multimodal measures linked to high-level subjective observations. This will allow for a systematic inclusion of the knowledge of music professionals in an analytic framework, which synthesizes methods across established research disciplines. We outline the methods we are currently developing for the creation of a multimodal data corpus dedicated to the analysis and exploration of instrumental music performance from the perspective of embodied music cognition. This will enable the study of the multiple facets of instrumental music performance in great detail, as well as lead to the development of music creation techniques that take advantage of the cross-modal relationships and higher-level qualities emerging from the analysis of this multi-layered, multimodal corpus. The results of the pilot project suggest that qualitative analysis through stimulated recall is an efficient method for generating higher-level understandings of musical performance. Furthermore, the results indicate several directions for further development, regarding observational movement analysis, and computational analysis of coarticulation, chunking, and movement qualities in musical performance. We argue that the development of methods for combining qualitative and quantitative data are required to fully understand expressive musical performance, especially in a broader scenario in which arts, humanities, and science are increasingly entangled. The future work in the project will therefore entail an increasingly multimodal analysis, aiming to become as holistic as is music in performance.

Detaljer

Författare
Externa organisationer
  • Luleå University of Technology
  • Gesture Embodiment and Machines in Music (GEMM)
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Musik

Nyckelord

Originalspråkengelska
Artikelnummer576751
TidskriftFrontiers in Psychology
Volym11
StatusPublished - 2020 dec 4
PublikationskategoriForskning
Peer review utfördJa
Externt publiceradJa