- author = "Matthieu Macret and Philippe Pasquier",
- title = "Automatic design of sound synthesizers as pure data patches using coevolutionary mixed-typed cartesian genetic programming",
- booktitle = "GECCO '14: Proceedings of the 2014 conference on Genetic and evolutionary computation",
- year = "2014",
- editor = "Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. {Montes de Oca} and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges",
- isbn13 = "978-1-4503-2662-9",
- pages = "309--316",
- keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Vancouver, BC, Canada",
-
URL = "
http://doi.acm.org/10.1145/2576768.2598303",
-
DOI = "
10.1145/2576768.2598303",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- abstract = "A sound synthesizer can be defined as a program that takes a few input parameters and returns a sound. The general sound synthesis problem could then be formulated as: given a sound (or a set of sounds) what program and set of input parameters can generate that sound (set of sounds)? We propose a novel approach to tackle this problem in which we represent sound synthesisers using Pure Data (Pd), a graphic programming language for digital signal processing. We search the space of possible sound synthesisers using Coevolutionary Mixed-typed Cartesian Genetic Programming (MT-CGP), and the set of input parameters using a standard Genetic Algorithm (GA). The proposed algorithm co-evolves a population of MT-CGP graphs, representing the functional forms of synthesisers, and a population of GA chromosomes, representing their inputs parameters. A fitness function based on the Mel-frequency Cepstral Coefficients (MFCC) evaluates the distance between the target and produced sounds. Our approach is capable of suggesting novel functional forms and input parameters, suitable to approximate a given target sound (and we hope in future iterations a set of sounds). Since the resulting synthesizers are presented as Pd patches, the user can experiment, interact with, and reuse them.",
-
notes = "http://metacreation.net/automatic-puredata-patch-generation/
Music
Also known as \cite{2598303} GECCO-2014 A joint meeting of the twenty third international conference on genetic algorithms (ICGA-2014) and the nineteenth annual genetic programming conference (GP-2014)",
