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...
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| Language: | English |
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The Royal Society
2025-07-01
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| Series: | Royal Society Open Science |
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| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.241647 |
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| author | Nick Collins |
| author_facet | Nick Collins |
| author_sort | Nick Collins |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-00f0d88feb45417b858c711a78afc5d6 |
| institution | Matheson Library |
| issn | 2054-5703 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj-art-00f0d88feb45417b858c711a78afc5d62025-07-30T08:18:43ZengThe Royal SocietyRoyal Society Open Science2054-57032025-07-0112710.1098/rsos.241647Recording artist career comparison through audio content analysisNick Collins0Music Department, Durham University, Durham, UKAudio 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.https://royalsocietypublishing.org/doi/10.1098/rsos.241647music information retrievalaudio content analysisrecording artist careers |
| spellingShingle | Nick Collins Recording artist career comparison through audio content analysis Royal Society Open Science music information retrieval audio content analysis recording artist careers |
| title | Recording artist career comparison through audio content analysis |
| title_full | Recording artist career comparison through audio content analysis |
| title_fullStr | Recording artist career comparison through audio content analysis |
| title_full_unstemmed | Recording artist career comparison through audio content analysis |
| title_short | Recording artist career comparison through audio content analysis |
| title_sort | recording artist career comparison through audio content analysis |
| topic | music information retrieval audio content analysis recording artist careers |
| url | https://royalsocietypublishing.org/doi/10.1098/rsos.241647 |
| work_keys_str_mv | AT nickcollins recordingartistcareercomparisonthroughaudiocontentanalysis |