Advances in Data Analysis and Classification

, Volume 1, Issue 3, pp 255–291 | Cite as

Classification in music research

  • Claus Weihs
  • Uwe Ligges
  • Fabian Mörchen
  • Daniel Müllensiefen
Regular Article

Abstract

Since a few years, classification in music research is a very broad and quickly growing field. Most important for adequate classification is the knowledge of adequate observable or deduced features on the basis of which meaningful groups or classes can be distinguished. Unsupervised classification additionally needs an adequate similarity or distance measure grouping is to be based upon. Evaluation of supervised learning is typically based on the error rates of the classification rules. In this paper we first discuss typical problems and possible influential features derived from signal analysis, mental mechanisms or concepts, and compositional structure. Then, we present typical solutions of such tasks related to music research, namely for organization of music collections, transcription of music signals, cognitive psychology of music, and compositional structure analysis.

Keywords

Classification in musicology Automatic transcription Music psychology Organization of music collections Compositional structure analysis 

Mathematics Subject Classification (2000)

62H30 

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Claus Weihs
    • 1
  • Uwe Ligges
    • 1
  • Fabian Mörchen
    • 2
  • Daniel Müllensiefen
    • 3
  1. 1.Fachbereich StatistikUniversität DortmundDortmundGermany
  2. 2.Siemens Corporate ResearchPrincetonUSA
  3. 3.Department of ComputingGoldsmiths College, University of LondonLondonUK

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