A Software Platform for Genetic Algorithms based Parameter Estimation on Digital Sound Synthesizers
Kamer Ali Yuksel, Batuhan Bozkurt, Hamed Ketabdar
In this research, we introduce a general-purpose sound synthesis architecture for parameter estimation system, which is employing genetic algorithms (GA), to search the parameter space for diﬀerent digital sound synthesizer topologies. Based on the architecture, we have implemented the software using the SuperCollider audio synthesis and programming environment and conducted several experiments. Primary consideration of the implementation was a modular and ﬂexible structure of the framework that may open widerange of opportunities for musicians and researchers in the ﬁeld.