Synthesizers are hardware or software instruments designed to generate sounds. Given a set of target sounds, the question is: what is a (or the best) synthesizer capable of producing it? This research explores a method for automated synthesizers’ design to producing a given target sound. The synthesizer’s architecture and its parameters are grown using Genetic Programming (GP), a population-based evolutionary algorithm. The resulting synthesizers are presented as interactive Pure Data Patches.
Kıvanç Tatar, Matthieu Macret, Denis Lebel, Philippe Pasquier, Noemie Perona.
Macret, M. & Pasquier, P. (2014). “Automatic Design of Sound Synthesizers as Pure Data Patches using Coevolutionary Mixed-typed Cartesian Genetic Programming” Proceedings of the 2014 conference on Genetic and evolutionary computation Automatic Design of Sound Synthesizers as Pure Data Patches using Coevolutionary Mixed-typed Cartesian Genetic Programming.
Results of experiments with one target sound:
Results of ongoing experiments with multiple target sounds: