Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
De Prisco, R., Zaccagnino, G., Zaccagnino, R.: EvoBassComposer: a multi-objective genetic algorithm for 4-voice compositions. In: Proceedings of the 12th ACM Annual Conference on Genetic and Evolutionary Computation, GECCO 2010, pp. 817–818 (2010)
De Prisco, R., Zaccagnino, G., Zaccagnino, R.: A multi-objective differential evolution algorithm for 4-voice compositions. In: Proceedings of IEEE Symposium on Differential Evolution, SDE 2011, pp. 817–818 (2011)
Emura, N., Miura, M., Hama, N., Yanagida, M.: A system giving the optimal chordform sequence for playing a guitar. Acoustical Science and Technology (January 2006)
Kandel, A.: Fuzzy expert systems. CRC Press, Boca Raton (1992)
Jang, J.R.: ANFIS: An Adaptive-Nework-Based Fuzzy Inference System. IEEE Transactions on Systems, Man, and Cybernetics 23(3) (May/June 1993)
Miura, M., Yanagida, M.: Finger-position determination and tablature generation for novice guitar players. In: Proceedings of the 7th International Conference on Music Perception and Cognition (2002)
Neri, F., Tirronen, V.: Scale factor local search in differential evolution. Memetic Comp. 1, 153–171 (2009)
Neri, F., Tirronen, V.: Recent Advances in Differential Evolution: A Review and Experimental Analysis. Artificial Intelligence Review 33(1), 61–106
Radisavljevic, A., Driessen, P.: Path difference learning for guitar fingering problem. In: Proceedings of the International Computer Music Conference (2004)
Sayegh, S.: Fingering for string instruments with the optimum path paradigm. Computer Music Journal 6(13), 76–84 (1989)
Storn, R., Price, K.: Differential evolution: a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical Report TR-95-012, International Computer Science Institute, Berkeley
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. Proceedings of IEEE Transactions on Systems, Man, and Cybernetics 15, 116–132 (1985)
Tuohy, D., Potter, W.: A genetic algorithm for the automatic generation of playable guitar tablature. In: Proceedings of the International Computer Music Conference (2004)
Tuohy, D., Potter, W.: GA-based music arranging for guitar. In: Procedings of IEEE Congress on Evolutionary Computation, CEC 2006 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
De Prisco, R., Zaccagnino, G., Zaccagnino, R. (2012). A Differential Evolution Algorithm Assisted by ANFIS for Music Fingering. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Swarm and Evolutionary Computation. EC SIDE 2012 2012. Lecture Notes in Computer Science, vol 7269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29353-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-29353-5_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29352-8
Online ISBN: 978-3-642-29353-5
eBook Packages: Computer ScienceComputer Science (R0)