Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Synthesising timbres and timbre-changes from adjectives/adverbs
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The problem with evolutionary art is ...
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
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PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Experiments are described which use genetic algorithms operating on the parameter settings of an FM synthesizer, with the aim of mimicking known synthesized sounds. The work is considered as a precursor to the development of synthesis plug-ins using evolution directed by a user. Attention is focussed on the fitness functions used to drive the evolution: the main result is that a composite fitness function – based on a combination of perceptual measures, spectral analysis, and low-level sample-by-sample comparison – drives more successful evolution than fitness functions which use only one of these types of criterion.