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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2009: Applications of Evolutionary Computing pp 573–578Cite as

Generation of Pop-Rock Chord Sequences Using Genetic Algorithms and Variable Neighborhood Search

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5484))

Abstract

This work proposes a utility function that measures: 1) the vertical relation between notes in a melody and chords in a sequence, and 2) the horizontal relation among chords. This utility function is embedded in a procedure that combines a Genetic Algorithm (GA) with a Variable Neighborhood Search (VNS) to automatically generate style-based chord sequences. The two-step algorithm is tested in ten popular songs, achieving accompaniments that match closely those of the original versions.

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References

  1. Chuan, C., Chew, E.: A Hybrid System for Automatic Generation of Style-Specific Accompaniment. In: Proceedings of the Fourth International Joint Workshop on Computational Creativity, University of London (2007)

    Google Scholar 

  2. Hansen, P., Mladenoic, N.: Variable Neighborhood Search: Principles and Applications. European Journal of Operational Research 130, 449–467 (1999)

    Article  MathSciNet  Google Scholar 

  3. Harrison, M.: Contemporary Music Theory Level Two. Hal Leonard, Milwaukee (2004)

    Google Scholar 

  4. Kotska, S., Payne, D.: Tonal Harmony with an Introduction to Twentieth-Century Music. McGraw-Hill, New York (2003)

    Google Scholar 

  5. Manaris, B., Machado, P., McCauley, C., Romero, J., Krehbiel, D.: Developing Fitness Functions for Pleasant Music: Zipf’s Law and Interactive Evolution Systems. In: EvoMUSART 2005, 3rd European Workshop on Evolutionary Music and Art, Lausanne, Switzerland (2005)

    Google Scholar 

  6. Medaglia, A.L., Gutiérrez, E.: JGA: An Object-Oriented Framework for Rapid Development of Genetic Algorithms. In: Rennard, J.-P. (ed.) Handbook of Research on Nature Inspired Computing for Economics and Management. Grenoble (2006)

    Google Scholar 

  7. Michalewicz, Z.: Genetic Algorithms Plus Data Structures Equals Evolution Programs. Springer, New York (1996)

    Book  MATH  Google Scholar 

  8. Morris, D., Basu, S., Simon, I.: MySong: Automatic Accompaniment Generation for Vocal Melodies (2008)

    Google Scholar 

  9. Piston, W., DeVoto, M.: Harmony. Editorial Labor, Barcelona (1992)

    Google Scholar 

  10. Schell, D.: Optimality in Musical Melodies and Harmonic Progressions: The Traveling Musician. European Journal of Operational Research 140(2), 354–372 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  11. Sorensen, A., Brown, A.: jMusic: Musical Composition with Java (website). (last accessed on: November 9, 2008), http://jmusic.ci.qut.edu.au/index.html

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Author information

Authors and Affiliations

  1. Departamento de Ingeniería Industrial Centro de Optimización y Probabilidad Aplicada, Universidad de los Andes, USA

    Leonardo Lozano, Andrés L. Medaglia & Nubia Velasco

Authors
  1. Leonardo Lozano
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  2. Andrés L. Medaglia
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  3. Nubia Velasco
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Editor information

Editors and Affiliations

  1. Department of Animal Production Epidemiology and Ecology, University of Torino, Via Leonardo da Vinci 44, 10095, Grugliasco, Italy

    Mario Giacobini

  2. Quinn School of Business, Belfield, University College Dublin, Dublin 4, Ireland

    Anthony Brabazon

  3. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  4. Dalla Molle Institute for Artificial Intelligence (IDSIA), Gallelria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  5. School of Engineering and Applied Science,Aston Triangle, Aston University, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Complex Adaptive Systems Group, Instituto Tecnológico de Informática, Ciudad PolitŽcnica de la Innovacin, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna Isabel Esparcia-Alcázar

  7. Next Generation Itelligent Networks Research Center (nexGIN RC), National University of Computer and Emerging Sciences (NUCES), Islamabad, Pakistan

    Muddassar Farooq

  8. Faculty of Economics and Social Sciences, Helmut-Schmidt-University, Holstenhofweg 85, 22043, Hamburg, Germany

    Andreas Fink

  9. Department of Informatics Engineering, Polo II - Pinhal de Marrocos, University of Coimbra, 3030 - 290, Coimbra, Portugal

    Penousal Machado

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Lozano, L., Medaglia, A.L., Velasco, N. (2009). Generation of Pop-Rock Chord Sequences Using Genetic Algorithms and Variable Neighborhood Search. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_64

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  • DOI: https://doi.org/10.1007/978-3-642-01129-0_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01128-3

  • Online ISBN: 978-3-642-01129-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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