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Recognizing Music Styles – An Approach Based on the Zipf-Mandelbrot Law

  • Viriato M. Marques
  • Cecília Reis
Conference paper
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 61)

Abstract

What makes a musical theme a good one? As an art, music evaluation is essentially a matter of aesthetical criterions and cultural inheritance. In fact, classifying melodies or complete musical pieces as good or bad is a particularly challenging task, although central for the production of artificial music by means of Evolutionary Computation, as the fitness function exactly consists of evaluating the quality of the generated melodies or complete scores. This paper presents a possible approach for the recognition of musical pieces style and, ultimately, their author. Certainly not enough from the point of view of fitness function implementation, this work is a step towards this goal, susceptible of further development and complementation by other techniques. The approach is based on the Zipf-Mandelbrot law, a probability distribution from the family of power laws that also describes word frequency in a given language or cities population all over the world.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Engineering InstituteCoimbra Polytechnic Institute (ISEC/IPC)CoimbraPortugal
  2. 2.Engineering InstitutePorto Polytechnic Institute (ISEP/IPP)PortoPortugal

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