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Audible Convergence for Optimal Base Melody Extension with Statistical Genre-Specific Interval Distance Evaluation

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Applications of Evolutionary Computing (EvoWorkshops 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3907))

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Abstract

In this paper, an evolutionary algorithm is used to calculate optimal extensions of a base melody line by statistical interval-distance minimization. Applying an evolutionary algorithm for solving such an optimization problem reveals the effect of audible convergence, when iterations of the optimization process, which represent sub-optimal melody lines, are combined to a musical piece. An example is provided to evaluate the algorithm, and to point out differences, when different musical genres, represented by different interval distance classification schemes, are applied.

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Author information

Authors and Affiliations

  1. Department of Statistics and Decision Support Systems, University of Vienna, Universitätsstraße 5/9, Vienna, 1010, Austria

    Ronald Hochreiter

Authors
  1. Ronald Hochreiter
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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. Centre of Informatics and Systems of the University of Coimbra,  

    Ernesto Costa

  5. Dept. LCC, Universidad de Málaga, Spain

    Carlos Cotta

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

    Rolf Drechsler

  7. INRIA Saclay - Ile-de-France, Parc Orsay Université, 4, rue Jacques Monod, 91893, ORSAY Cedex, France

    Evelyne Lutton

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

    Penousal Machado

  9. Dartmouth College, Lebanon, NH, USA

    Jason H. Moore

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

    Juan Romero

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

    George D. Smith

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

    Giovanni Squillero

  13. Kyushu University, Japan

    Hideyuki Takagi

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© 2006 Springer-Verlag Berlin Heidelberg

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Hochreiter, R. (2006). Audible Convergence for Optimal Base Melody Extension with Statistical Genre-Specific Interval Distance Evaluation. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_68

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  • DOI: https://doi.org/10.1007/11732242_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33237-4

  • Online ISBN: 978-3-540-33238-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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