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Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance

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...

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Autores principales: Visi, Federico Ghelli, Östersjö, Stefan, Ek, Robert, Röijezon, Ulrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746541/
https://www.ncbi.nlm.nih.gov/pubmed/33343452
http://dx.doi.org/10.3389/fpsyg.2020.576751
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author Visi, Federico Ghelli
Östersjö, Stefan
Ek, Robert
Röijezon, Ulrik
author_facet Visi, Federico Ghelli
Östersjö, Stefan
Ek, Robert
Röijezon, Ulrik
author_sort Visi, Federico Ghelli
collection PubMed
description 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.
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spelling pubmed-77465412020-12-19 Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance Visi, Federico Ghelli Östersjö, Stefan Ek, Robert Röijezon, Ulrik Front Psychol Psychology 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. Frontiers Media S.A. 2020-12-04 /pmc/articles/PMC7746541/ /pubmed/33343452 http://dx.doi.org/10.3389/fpsyg.2020.576751 Text en Copyright © 2020 Visi, Östersjö, Ek and Röijezon. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Visi, Federico Ghelli
Östersjö, Stefan
Ek, Robert
Röijezon, Ulrik
Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance
title Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance
title_full Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance
title_fullStr Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance
title_full_unstemmed Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance
title_short Method Development for Multimodal Data Corpus Analysis of Expressive Instrumental Music Performance
title_sort method development for multimodal data corpus analysis of expressive instrumental music performance
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746541/
https://www.ncbi.nlm.nih.gov/pubmed/33343452
http://dx.doi.org/10.3389/fpsyg.2020.576751
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