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Probabilistic and Logic-Based Modelling of Harmony

  • Simon Dixon
  • Matthias Mauch
  • Amélie Anglade
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6684)

Abstract

Many computational models of music fail to capture essential aspects of the high-level musical structure and context, and this limits their usefulness, particularly for musically informed users. We describe two recent approaches to modelling musical harmony, using a probabilistic and a logic-based framework respectively, which attempt to reduce the gap between computational models and human understanding of music. The first is a chord transcription system which uses a high-level model of musical context in which chord, key, metrical position, bass note, chroma features and repetition structure are integrated in a Bayesian framework, achieving state-of-the-art performance. The second approach uses inductive logic programming to learn logical descriptions of harmonic sequences which characterise particular styles or genres. Each approach brings us one step closer to modelling music in the way it is conceptualised by musicians.

Keywords

Chord transcription inductive logic programming musical harmony 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Simon Dixon
    • 1
  • Matthias Mauch
    • 1
  • Amélie Anglade
    • 1
  1. 1.Centre for Digital MusicQueen Mary University of LondonLondonUK

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