Rhythmic, Melodic and Vertical N-Gram Features as a Means of Studying Symbolic Music Computationally
| Autor: | McKay, Cory, Cumming, Julie, Fujinaga, Ichiro |
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| Přispěvatelé: | Scholger, Walter, Vogeler, Georg, Tasovac, Toma, Baillot, Anne, Raunig, Elisabeth, Scholger, Martina, Steiner, Elisabeth, Centre for Information Modelling, Helling, Patrick |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
Paper
attribution studies and stylometric analysis Music theory representation Library & information science Musicology Statistics Automated analysis encoding N-grams Music classification jSymbolic Computer science manuscripts description Short Presentation Machine learning FOS: Mathematics and analysis artificial intelligence and machine learning Features music and sound digitization |
| DOI: | 10.5281/zenodo.8142648 |
| Popis: | This presentation explores how n-grams can be used to automatically classify and learn about music. An overall discussion is provided of various ways in which n-grams can be adapted for use with digital scores, and of how musically meaningful features can be extracted from them. The jSymbolic 3.0 alpha prototype feature extractor is then used in three sets of music classification experiments investigating how n-gram features perform relative to and combined with other types of features extracted from symbolic music files. Funded by the FRQSC and SSHRC. |
| Databáze: | OpenAIRE |
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