Representations of the MONK harmonisation systems

  • Daran Coates
Conference paper
Part of the Workshops in Computing book series (WORKSHOPS COMP.)


This paper describes the music representation approaches used in MONK, an implemented group of software modules from which harmonisation systems can be built. The basic design issues are outlined in relation to two preparatory studies, namely an examination of three recent harmonisation systems and an informal protocol analysis of practitioners performing harmonisations. The development of a symbolic model of the Longuet-Higgins map of harmony, LHSpace, is described and the manipulation of LHSpace by the MONK systems outlined. The representation of melody is outlined and compared with Conventional Music Notation. Approaches to representing other musical knowledge using traditional Artificial Intelligence techniques are discussed. The educational implications of the MONK representations are considered.


Strategy Module Intelligent Tutoring System Strategy Layer Harmonisation System Preparatory Study 
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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  1. [Coates ?]
    D. Coates. Description of the monk harmonisation systems. Technical report, Aberdeen University, ?.Google Scholar
  2. [Ebcioglu 86]
    K. Ebcioglu. An Expert System for Harmonization of Chorales in the Style of J.S. Bach. Unpublished PhD thesis, State University of New York at Buffalo, 1986.Google Scholar
  3. [Holland 89]
    S. Holland. Artificial Intelligence, Education and Music. Unpublished PhD thesis, published internally as OU IET CITE Report No. 88, July 1989, 1989.Google Scholar
  4. [Longuet-Higgins 62a]
    H.C. Longuet-Higgins. Letter to a musical friend. Music Review, pages 244–48, 1962.Google Scholar
  5. [Longuet-Higgins 62b]
    H.C. Longuet-Higgins. Second letter to a musical friend. Music Review, pages 271–80, 1962.Google Scholar
  6. [Piston 89]
    W. Piston. Harmony (4th impression). Gollancz Ltd, London, 1989.Google Scholar
  7. [Sirkin 87]
    D.W. Sirkin. Choralearn: A system that learns from examples to write simplified figured bass harmonizations of chorales using the pls1 clusterer. Unpublished M.Sc. thesis, University of Illinois at Urbana-Champaign, 1987.Google Scholar
  8. [Sloboda 85]
    Sloboda 85] J. Sloboda. The Musical Mind: The Cognitive Psychology of Music. Clarendon Press, Oxford, 1985.Google Scholar
  9. [Steedman 72]
    M. Steedman. The Formal Description of Musical Perception. Unpublished PhD thesis, University of Edinburgh, 1972.Google Scholar
  10. [Thomas 85]
    M.T. Thomas. Vivace: A rule based AI system for composition. In Proceedings of the International Computer Music Conference, 1985. 91Google Scholar
  11. [Wenger 87]
    E. Wenger. Artificial Intelligence and Tutoring Systems. Morgan Kaufman, Los Altos, California, 1987.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Daran Coates
    • 1
  1. 1.Department of Computing Faculty of Mathematics and ComputingOpen UniversityMilton KeynesEngland

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