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Using Note-Level Music Encodings to Facilitate Interdisciplinary Research on Human Engagement with Music
Author(s) -
Johanna Devaney
Publication year - 2020
Publication title -
transactions of the international society for music information retrieval
Language(s) - English
Resource type - Journals
ISSN - 2514-3298
DOI - 10.5334/tismir.56
Subject(s) - musical , encoding (memory) , computer science , relation (database) , pop music automation , simplicity , cognitive science , musical composition , psychology , artificial intelligence , visual arts , epistemology , art , data mining , philosophy
Music encoding can link disparate types of musical data for the purposes of archiving and search. The encoding of human response data explicitly in relation to musical notes facilitates the study of the ways humans engage with music as performers and listeners. This paper reflects on the developments and trends in formal music encoding systems as well as the types of data representations used in corpora released by researchers working on expert music analyses, musical performances, and listener responses. It argues that while the specificity (and often simplicity) afforded by project-specific encoding formats may be useful for individual research projects, larger-scale interdisciplinary research would be better served by explicit, formalized linking of data to specific musical elements. The paper concludes by offering some concrete suggestions for how to achieve this goal.

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