Application of Diagrammatics in Computational Music Analysis

Peer-Reviewed

Anna Maria Matuszewska


Institute of Literary Research, Polish Academy of Sciences (Poland)
https://orcid.org/0000-0002-3832-855X

Abstract

Musical repositories recorded in various digital formats are being created and developed with ever increasing intensity. This situation opens up wide research possibilities, but also places demands on musicologists, who need to learn how to work with large databases using digital tools. These tools facilitate searching large musical collections and prove more and more effective in musical analysis. Though many solutions have already been proposed in this field, there is still room for greater coordination of research perspectives derived from musicology and computer science, which can make the results of computational analyses more clear, comprehensible, and flexibly processable. Musicologists’ needs should also be addressed by creating interfaces specially designed for music analysis.

The paper aims to present new methods of processing, presenting, and analysing musicological data. Selected musical information from Johann Sebastian Bach’s fugues BWV 846–869, generated by means of Humdrum Tools, music21 and Music Processing Suite (MPS) software, has been transformed into a relational database and visualised by means of so-called dashboards (sets of graphic data representations) using the Tableau Public software. Interactive solutions applied in this process have been designed so as to make computational analyses possibly intuitive and easily adaptable. The proposed analytic dashboards do not impose rigid working methods on researchers. The presented data can be reconfigured. Analysis of the selected piece of music can be restricted to any combination of parts, motifs, or set of measures, making both general and detailed exploration of the material possible. The project has been designed on the principles of diagrammatic reasoning proposed by Charles Sanders Peirce. The multiplicity of additional user-adaptable options creates conditions for the generation of abductive hypotheses.


Keywords:

computational musicology, interactive music analysis, diagrammatics

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Published
2023-07-17

Cited by

Matuszewska, A. M. (2023). Application of Diagrammatics in Computational Music Analysis. Muzyka, 68(2), 94–117. https://doi.org/10.36744/m.1773

Authors

Anna Maria Matuszewska 

Institute of Literary Research, Polish Academy of Sciences Poland
https://orcid.org/0000-0002-3832-855X

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