Play it Again: Evolved Audio Effects and Synthesizer Programming

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10198)

Abstract

Automatic programming of sound synthesizers and audio devices to match a given, desired sound is examined and a Genetic Algorithm (GA) that functions independent of specific synthesis techniques is proposed. Most work in this area has focused on one synthesis model or synthesizer, designing the GA and tuning the operator parameters to obtain optimal results. The scope of such inquiries has been limited by available computing power, however current software (Ableton Live, herein) and commercially available hardware is shown to quickly find accurate solutions, promising a practical application for music creators. Both software synthesizers and audio effects processors are examined, showing a wide range of performance times (from seconds to hours) and solution accuracy, based on particularities of the target devices. Random oscillators, phase synchronizing, and filters over empty frequency ranges are identified as primary challenges for GA based optimization.

Keywords

Sound synthesis Machine learning Adaptive genetic algorithms Audio effects 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Indiana University-Purdue University-IndianapolisIndianapolisUSA

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