Detection of Musical Borrowing Using Data Science

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.