An exploration of evolutionary computation applied to frequency modulation audio synthesis parameter optimisation

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Mitchell, T. J. (2010) An exploration of evolutionary computation applied to frequency modulation audio synthesis parameter optimisation. EngD, University of the West of England. Available from:

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With the ever-increasing complexity of sound synthesisers, there is a growing demand for automated parameter estimation and sound space navigation techniques. This thesis explores the potential for evolutionary computation to automatically map known sound qualities onto the parameters of frequency modulation synthesis. Within this exploration are original contributions in the domain of synthesis parameter estimation and, within the developed system, evolutionary computation, in the form of the evolutionary algorithms that drive the underlying optimisation process. Based upon the requirement for the parameter estimation system to deliver multiple search space solutions, existing evolutionary algorithmic architectures are augmented to enable niching, while maintaining the strengths of the original algorithms. Two novel evolutionary algorithms are proposed in which cluster analysis is used to identify and maintain species within the evolving populations. A conventional evolution strategy and cooperative coevolution strategy are defined, with cluster-orientated operators that enable the simultaneous optimisation of multiple search space solutions at distinct optima. A test methodology is developed that enables components of the synthesis matching problem to be identified and isolated, enabling the performance of different optimisation techniques to be compared quantitatively. A system is consequently developed that evolves sound matches using conventional frequency modulation synthesis models, and the effectiveness of different evolutionary algorithms is assessed and compared in application to both static and timevarying sound matching problems. Performance of the system is then evaluated by interview with expert listeners. The thesis is closed with a reflection on the algorithms and systems which have been developed, discussing possibilities for the future of automated synthesis parameter estimation techniques, and how they might be employed.

Item Type: Thesis (EngD)
Uncontrolled Keywords: evolutionary synthesis matching, evolutionary computation, evolution strategies, FM synthesis
Faculty/Department: Faculty of Environment and Technology > Department of Computer Science and Creative Technologies
Depositing User: Dr T. Mitchell
Date Deposited: 09 Jan 2013 16:17
Last Modified: 19 Nov 2016 02:38


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