Evolutionary Music Composer integrating Formal Grammar

Khalifa, Y.M.A.; Begovic, Jasmin; Khan, Badar; Wisdom, Airrion; Almourad, Mohamed Basel

doi:10.1007/978-1-4020-6264-3_87

Cited by 2 publications

(3 citation statements)

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“…GenJam [10], likewise offers rich representation possibilities and diversity in music, but the system itself needs already composed musical data in the initial population. The motifs in [8] share some resemblance to the presented segments. However, the motif combination is only done by note transition resolutions of last and first notes and the possibility of composition with multiple instruments is not discussed.…”

Section: Comparison With An Objective Fitness Function Approachmentioning

confidence: 84%

“…The GA composition system is written in C++ and uses the GAlib 1 , a C++ library of genetic algorithm components. 1 http://lancet.mit.edu/ga/ E2 G2 G2 G (9,10), (11,10), (11,10), (11,8) F G2 A2 B2 (10,8), (11,10), (12,10), (12,10) …”

Section: Genotype/phenotypementioning

confidence: 99%

“…An objective fitness function is used in [8], using contextfree grammar as musical rules. One important point is that previously used heuristic search algorithms like GAs with an unrestricted space usually suffer from the fitness bottleneck [2][10], a gigantic and mostly unusable search space.…”

Section: Introductionmentioning

confidence: 99%

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Genetic algorithms and the abc music notation language for rock music composition

Oliwa

2008

Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation

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In this paper a music composition system based on genetic algorithms (GAs) will be presented. It can create multiinstrumental, guitar-orientated rock music using objective measures for its fitness functions. The output of this system is a song in the MIDI format. Along with this system, a unique conversion procedure from numerical values to the abc language (and vice versa), which allows the combination of numerical optimization with the rich expressiveness of a music description language, will be shown. The described music composition system will be further compared to other composition systems.

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Section: Comparison With An Objective Fitness Function Approachmentioning

confidence: 84%