Soft Computing

, Volume 16, Issue 12, pp 2057–2070 | Cite as

Automated evolutionary synthesis matching

Advanced evolutionary algorithms for difficult sound matching problems
  • Thomas Mitchell
Original Paper


This paper discusses the subject of automatic evolutionary sound matching: systems in which evolutionary algorithms are used to automatically derive the parameters of a synthesiser to produce a sound that matches a specified target sound. The paper describes prior work and identifies the principal causes of match inaccuracy, which are often due to optimiser limitations as a result of search space problem difficulty. The components of evolutionary matching systems contributing to problem difficulty are discussed and suggestions as to how improvements can be made through problem simplification or optimiser sophistication are considered. Subsequently, a novel clustering evolution strategy is presented which enables the concurrent optimisation of multiple distinct search space solutions, intended for the purposes of sound matching with standard frequency modulation (FM) synthesisers. The algorithm is shown to outperform standard multi-membered and multi-start (1 + 1) evolution strategies in application to different FM synthesis models for static and dynamic sounds. The comparative study makes use of a contrived matching method, which ensures that results are not affected by the limitations of the matching synthesiser.


Evolutionary computation Evolutionary sound matching Frequency modulation synthesis Clustering evolutionary algorithms Evolution strategy 



The author would like to thank Professor Larry Bull, Dr David Creasey and Professor Tony Pipe at the University of the West of England for their support and encouragement in the preparation of this work.


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Computer Science and Creative TechnologiesUniversity of the West of EnglandBristolUK

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