Investigating the Influence of Representations and Algorithms in Music Classification.
Classification in music analysis involves the segmentation of a music piece and the categorisation of the segments depending on similarity-based criteria. In this paper we investigate, based on a formal approach, how variations in the representation of the musical segments and in the categorisation...
| Publicado en: | Computers & the Humanities Vol. 35; no. 1; pp. 65 - 80 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Feb2001
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=16898795&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 16898795 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00104817 CHM jtl: Computers & the Humanities issn: 00104817 maglogo: N pubinfo: dt: Feb2001 vid: 35 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 16898795 10.1023/A:1002787826686 ppf: 65 ppct: 15 formats: fmt: @attributes: type: P size: 130KB tig: atl: Investigating the Influence of Representations and Algorithms in Music Classification. aug: au: Höthker, Karin Hörnel, Dominik Anagnostopoulou, Christina affil: Institut für Logik, Komplexität und Deduktionssysteme, Universität Karlsruhe Faculty of Music, University of Edinburgh su: Musical analysis Algorithms Harmonic analysis (Music theory) Music theory Musical composition Music sug: subj: Musical analysis Algorithms Harmonic analysis (Music theory) Music theory Musical composition Music keyword: classification neural networks paradigmatic analysis ab: Classification in music analysis involves the segmentation of a music piece and the categorisation of the segments depending on similarity-based criteria. In this paper we investigate, based on a formal approach, how variations in the representation of the musical segments and in the categorisation algorithm influence the outcome of the classification. More specifically, we vary the choice of features describing each segment, the way these features are represented, and the categorisation algorithm. At the same time, we keep the other parameters, that is the overall model architecture, the music pieces, and the segmentation, fixed. We show that the choice and representation of the features, but not the specific categorisation algorithm, have a strong impact on the obtained analysis. We introduce a distance function to compare the results of algorithmic and human classification, and we show that an appropriate choice of features can yield results that are very similar to a human classification. These results allow an objective evaluation of different approaches to music classification in a uniform setting. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Computers & the Humanities is a copyright of Springer, 2001. All Rights Reserved. item: Computers & the Humanities holder: Springer Nature dt: @attributes: year: 2001 holdings: @attributes: islocal: N |
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