A Differential Evolution Algorithm Assisted by ANFIS for Music Fingering

  • Roberto De Prisco
  • Gianluca Zaccagnino
  • Rocco Zaccagnino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7269)


Music fingering is a cognitive process whose goal is to map each note of a music score to a fingering on some instrument. A fingering specifies the fingers of the hands that the player should use to play the notes. This problem arises for many instruments and it can be quite different from instrument to instrument; guitar fingering, for example, is different from piano fingering. Previous work focuses on specific instruments, in particular the guitar, and evolutionary algorithms have been used.

In this paper, we propose a differential evolution (DE) algorithm designed for general music fingering (any kind of music instruments). The algorithm uses an Adaptive Neuro-Fuzzy Inference System (ANFIS) engine that learns the fingering from music already fingered.

The algorithm follows the basic DE strategy but exploits also some customizations specific to the fingering problem. We have implemented the DE algorithm in Java and we have used the ANFIS network in Matlab. The two systems communicate by using the MatlabControl library. Several tests have been performed to evaluate its efficacy.


Fuzzy Inference System ANFIS Model Trial Vector Music Score Memetic Comp 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Roberto De Prisco
    • 1
  • Gianluca Zaccagnino
    • 1
  • Rocco Zaccagnino
    • 1
  1. 1.Musimathics Laboratory Dipartimento di InformaticaUniversità di SalernoFiscianoItaly

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