Automatic tuning of the OP-1 synthesizer using a multi-objective genetic algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@MastersThesis{Macret2013aa,

• author = "Matthieu Michel Jean Macret",
• title = "Automatic tuning of the {OP-1} synthesizer using a multi-objective genetic algorithm",
• school = "Communication, Art \& Technology: School of Interactive Arts and Technology, Simon Fraser University",
• year = "2013",
• address = "Vancouver, Canada",
• month = jul # ", 16",
• keywords = "Genetic Algorithms, genetic programming, DEAP, Artificial Intelligence, Sound Synthesis, Multi-objective Optimization",
• date-added = "2018-07-31 16:52:16 +0900",
• date-modified = "2018-07-31 16:53:11 +0900",
• URL = "http://summit.sfu.ca/item/13452",
• size = "108 pages",
• abstract = "Calibrating a sound synthesizer to replicate or approximate a given target sound is a complex and time consuming task for musicians and sound designers. In the case of the OP1, a commercial synthesizer developed by Teenage Engineering, the difficulty is multiple. The OP-1 contains several synthesis engines, effects and low frequency oscillators, which make the parameters search space very large and discontinuous. Furthermore, interactions between parameters are common and the OP-1 is not fully deterministic. We address the problem of automatically calibrating the parameters of the OP-1 to approximate a given target sound. We propose and evaluate a solution to this problem using a multi-objective Non-dominated-Sorting-Genetic-Algorithm-II. We show that our approach makes it possible to handle the problem complexity, and returns a small set of presets that best approximate the target sound while covering the Pareto front of this multi-objective optimization problem.",
• notes = "Some comparison with GP",

}

Genetic Programming entries for Matthieu Macret

Citations