Yee-King, Matthew John (2011) Automatic sound synthesizer programming: techniques and applications. Doctoral thesis (DPhil), University of Sussex.

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Abstract

The aim of this thesis is to investigate techniques for, and applications of automatic sound synthesizer programming. An automatic sound synthesizer programmer is a system which removes the requirement to explicitly specify parameter settings for a sound synthesis algorithm from the user. Two forms of these systems are discussed in this thesis:
tone matching programmers and synthesis space explorers. A tone matching programmer takes at its input a sound synthesis algorithm and a desired target sound. At its output it produces a configuration for the sound synthesis algorithm which causes it to emit a
similar sound to the target. The techniques for achieving this that are investigated are
genetic algorithms, neural networks, hill climbers and data driven approaches. A synthesis
space explorer provides a user with a representation of the space of possible sounds
that a synthesizer can produce and allows them to interactively explore this space. The
applications of automatic sound synthesizer programming that are investigated include
studio tools, an autonomous musical agent and a self-reprogramming drum machine. The
research employs several methodologies: the development of novel software frameworks
and tools, the examination of existing software at the source code and performance levels
and user trials of the tools and software. The main contributions made are: a method
for visualisation of sound synthesis space and low dimensional control of sound synthesizers; a general purpose framework for the deployment and testing of sound synthesis and optimisation algorithms in the SuperCollider language sclang; a comparison of a variety of optimisation techniques for sound synthesizer programming; an analysis of sound synthesizer error surfaces; a general purpose sound synthesizer programmer compatible with industry standard tools; an automatic improviser which passes a loose equivalent of the Turing test for Jazz musicians, i.e. being half of a man-machine duet which was rated as one of the best sessions of 2009 on the BBC's 'Jazz on 3' programme.

Item Type:	Thesis (Doctoral)
Schools and Departments:	School of Engineering and Informatics > Informatics
Subjects:	M Music. Literature on music. Musical instruction and study > M Music > M0005 Instrumental music > M1470 Aleatory music. Electronic music. Mixed media T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics
Depositing User:	Library Cataloguing
Date Deposited:	15 Dec 2011 13:13
Last Modified:	24 Aug 2015 14:48
URI:	http://srodev.sussex.ac.uk/id/eprint/7612

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