{"title":"Detection of Musical Borrowing Using Data Science","authors":"Steven Walczak, Thomas E. Moore‐Pizon","doi":"10.1002/pra2.843","DOIUrl":null,"url":null,"abstract":"ABSTRACT Data science may be used to determine similarities between musical scores. Programs are written in C++ to capture note progressions from musical scores and to compare progressions from different songs to identify overlapping areas. These tools enable the study of musical borrowing across musical genres and may assist in copyright violation cases. Results indicate that within the Celtic music genre, borrowing occurs across greater than 10% of the songs.","PeriodicalId":37833,"journal":{"name":"Proceedings of the Association for Information Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Association for Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/pra2.843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT Data science may be used to determine similarities between musical scores. Programs are written in C++ to capture note progressions from musical scores and to compare progressions from different songs to identify overlapping areas. These tools enable the study of musical borrowing across musical genres and may assist in copyright violation cases. Results indicate that within the Celtic music genre, borrowing occurs across greater than 10% of the songs.
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