Recording artist career comparison through audio content analysis

Audio content analysis can be deployed to examine relationships within and between collected works of different music artists, allowing a new approach to comparative analysis of recorded music within the domain of computational musicology. Although current-generation automatic transcription retains some flaws with respect to expert human analysis, there is a consistency to applying the same algorithms on disparate works, and the benefit of tireless calculation with explicit open bias. In the present study, three successful alternative rock groups, and three 'control' artists, all from either the United States or the UK, are compared with respect to their musical careers through their main recorded releases (spanning the years 1983-2021 for the main three and 1957-2000 for the controls). Statistical measures of variation over time, and the diversity of their recorded output, are used to answer research questions on their studio career and the originality of their work. The techniques explored here are immediately pertinent to study other artists outside of this starting point, and we discuss the potential and challenges of such approaches for the musicology of recorded music.

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Publication Details

Journal
Royal Society Open Science
Published
2025-07-01
DOI
https://doi.org/10.1098/rsos.241647
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
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article

Recording artist career comparison through audio content analysis

Nuala Collins
Royal Society Open Science
Music and Audio Processing
article

Recording artist career comparison through audio content analysis

Nuala Collins
article en

Abstract

Audio content analysis can be deployed to examine relationships within and between collected works of different music artists, allowing a new approach to comparative analysis of recorded music within the domain of computational musicology. Although current-generation automatic transcription retains some flaws with respect to expert human analysis, there is a consistency to applying the same algorithms on disparate works, and the benefit of tireless calculation with explicit open bias. In the present study, three successful alternative rock groups, and three 'control' artists, all from either the United States or the UK, are compared with respect to their musical careers through their main recorded releases (spanning the years 1983-2021 for the main three and 1957-2000 for the controls). Statistical measures of variation over time, and the diversity of their recorded output, are used to answer research questions on their studio career and the originality of their work. The techniques explored here are immediately pertinent to study other artists outside of this starting point, and we discuss the potential and challenges of such approaches for the musicology of recorded music.

Royal Society Open ScienceVol. 12(7)
Durham University (GB)
Openalex Percentile: Top 81%
Music and Audio Processing
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