Abstract
This paper describes a system for converting music to guitar tablature. At run time, the system employs a distributed genetic algorithm (DGA) to create tablature and an artificial neural network to assign fingers to each note. Three additional genetic algorithms are used to optimize the fitness function of the DGA, the operating parameters of the DGA, and the learning environment of the Neural Network. These steps are taken in the hope of maximizing the consistency of our algorithm with human experts. The results have been encouraging.
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References
Gordon, V.S., Whitley, D.: Serial and Parallel Genetic Algorithms as Function Optimizers. In: 5th International Conference on Genetic Algorithms, pp. 177–183 (1993)
Heijink, H., Meulenbroek, R.G.J.: On the complexity of classical guitar playing: functional adaptations to task constraints. Journal of Motor Behaviour 34(4), 339–351 (2002)
Miura, M., Hirota, I., Hama, N., Yanigida, M.: Constructing a System for Finger-Position Determination and Tablature Generation for Playing Melodies on Guitars. Systems and Computers in Japan 35(6), 755–763 (2004)
Radicioni, D., Lombardo, V.: Guitar Fingering for Music Performance. In: Proceedings of the Internation Computer Music Conference, Barcelona, Spain (2005)
Radicioni, D., Anselma, L., Lombardo, V.: A segmentation-based prototype to compute string instruments fingering. In: Proceedings of the Conference on Interdisciplinary Musicology, Graz, Austria (2004)
Radisavljevic, A., Driessen, P.: Path Difference Learning for Guitar Fingering Problem. In: Proceedings of the International Computer Music Conference, Miami, USA (2004)
Sayegh, S.: Fingering for String Instruments with the Optimum Path Paradigm. Computer Music Journal 13(6), 76–84 (1989)
Smith, B.: GAIL: Georgia Artificial Intelligence Library Neural Network Package, University of Georgia (2004)
Tuohy, D., Potter, W.D.: A Genetic Algorithm for the Automatic Generation of Playable Guitar Tablature. In: Proceedings of the International Computer Music Conference, Barcelona, Spain (2005)
Tuohy, D., Potter, W.D.: GA-based Music Arranging for Guitar. IEEE Congress on Evolutionary Computation (submitted, 2006)
Wang, J., Tsai-Yen, L.: Generating Guitar Scores from a MIDI Source. In: International Symposium on Multimedia Information Processing, Taipei, Taiwan (1997)
Whitley, D.: Genetic Algorithms and Neural Networks. In: Genetic Algorithms in Engineering and Computer Science, pp. 1–15 (1995)
Whitley, D., Kauth, J.: GENITOR: A Different Genetic Algorithm. In: Proceedings of the Rocky Mountain Conference on Artificial Intelligence
Whitley, D., Starkweather, T.: GENITOR II: a distributed genetic algorithm. J. Expt. Theor. Artif. Intel. 2, 189–213 (1990)
NeuroShell 2 Neural Network Kit by Ward Systems Group, http://www.wardsystems.com
Classical Guitar Tablature, http://www.classtab.org
A-Z Guitar Tabs, http://www.guitaretab.com
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© 2006 Springer-Verlag Berlin Heidelberg
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Tuohy, D.R., Potter, W.D. (2006). Generating Guitar Tablature with LHF Notation Via DGA and ANN. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_28
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DOI: https://doi.org/10.1007/11779568_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35453-6
Online ISBN: 978-3-540-35454-3
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