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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2005: Applications of Evolutionary Computing pp 498–507Cite as

Developing Fitness Functions for Pleasant Music: Zipf’s Law and Interactive Evolution Systems

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 3449)

Abstract

In domains such as music and visual art, where the quality of an individual often depends on subjective or hard to express concepts, the automating fitness assignment becomes a difficult problem. This paper discusses the application of Zipf’s Law in evaluation of music pleasantness. Preliminary results indicate that a set of Zipf-based metrics can be effectively used to classify music according to pleasantness as reported by human subjects. These studies suggest that metrics based on Zipf’s law may capture essential aspects of proportion in music as it relates to music aesthetics. We discuss the significance of these results for the automation of fitness assignment in evolutionary music systems.

Keywords

  • Average Success Rate
  • Style Identification
  • Interactive Evolution
  • Fitness Assignment
  • Music Excerpt

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-540-32003-6_50
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Author information

Authors and Affiliations

  1. Computer Science Department, College of Charleston, 66 George Street, Charleston, SC, 29424, USA

    Bill Manaris & Clayton McCauley

  2. Instituto Superior de Engenharia de Coimbra, Qta. da Nora, 3030, Coimbra, Portugal

    Penousal Machado

  3. Creative Computer Group – RNASA Lab – Faculty of Computer Science, University of A Coruña, Coruña, Spain

    Juan Romero

  4. Psychology Department, Bethel College, North Newton, KS, 67117, USA

    Dwight Krehbiel

Authors
  1. Bill Manaris
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  2. Penousal Machado
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  3. Clayton McCauley
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  4. Juan Romero
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  5. Dwight Krehbiel
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Editor information

Editors and Affiliations

  1. Johannes Gutenberg University, Mainz, Germany

    Franz Rothlauf

  2. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  3. Dipartimento di Ingegneria dell’Informazione, Università di Parma,  

    Stefano Cagnoni

  4. School of Mathematical and Computer Science, Heriot-Watt University, EH14 8AS, Edinburgh, UK

    David Wolfe Corne

  5. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  6. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

  7. CISUC, Department of Informatics Engineering, University of Coimbra, Polo II of the University of Coimbra, 3030, Coimbra, Portugal

    Penousal Machado

  8. ICIS, Radboud University Nijmegen, The Netherlands

    Elena Marchiori

  9. Universidade de A Coruña, CP 15071, A Coruña, Spain

    Juan Romero

  10. School of Computing Sciences, University of East Anglia, UEA Norwich, NR4 7TJ, Norwich, UK

    George D. Smith

  11. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

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© 2005 Springer-Verlag Berlin Heidelberg

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Manaris, B., Machado, P., McCauley, C., Romero, J., Krehbiel, D. (2005). Developing Fitness Functions for Pleasant Music: Zipf’s Law and Interactive Evolution Systems. In: , et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_50

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  • DOI: https://doi.org/10.1007/978-3-540-32003-6_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25396-9

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