Abstract
This paper presents a multi-objective approach for making melody compositions in evolutionary music. There exist several methods to generate music based on computer algorithms, but they cannot deal with multi-dimensional aspects such as a trade-off relation effectively. Our approach generates a set of melodies that maximize two fitness functions, which represent a trade-off between stability and tension. It includes a pre-defined chord progression and rhythm to initialize and evaluate population. Multi-objective genetic algorithm is applied to the music composition, it is able to successfully compose melody lines based on the chord progression.
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Jeong, J.H., Ahn, C.W. (2015). Automatic Evolutionary Music Composition Based on Multi-objective Genetic Algorithm. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, KC. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-13356-0_9
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DOI: https://doi.org/10.1007/978-3-319-13356-0_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13355-3
Online ISBN: 978-3-319-13356-0
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