Generative Music from Fuzzy Logic and Probability: A Portfolio of Electroacoustic Compositions

Garrett, Richard (2017) Generative Music from Fuzzy Logic and Probability: A Portfolio of Electroacoustic Compositions. PhD thesis, Prifysgol Bangor University.

[img] Text
Richard Garrett Declaration.pdf
Restricted to Repository staff only

Download (81kB) | Request a copy
Text (Final version of thesis)
GarrettR Generative Music from Fuzzy Logic and Probability.pdf

Download (57MB) | Preview


This portfolio of thirteen recorded works was composed as an investigation into the application of generative processes to electroacoustic music, paying particular attention to the use of fuzzy logic and the rule-based constraint of chance events. These works were developed by a rolling process of program design and musical composition, focusing on two areas: the generation and transformation of large groups of sounds within a multi-dimensional parameter space for acousmatic composition (using the author’s software, Audio Spray Gun) and the real-time selection of sounds using audio descriptors, principally for live performance by instrument and electronics. Later stages of the project attempted to unite these processes in two ways: by the agent-based generation of large sound-groups for multichannel audio from live instruments or pre-recorded audio datasets and by the software generation of such groups for fixed-media composition using trajectories and transformations in ‘timbre space’. An accompanying document charts the development of these works with a programme note, technical discussion and performance records for each, along with spectrograms and scores as appropriate. It also describes the programming methods used and discusses the implications and limitations of these approaches, particularly for object-based spatial music and timbre selection.

Item Type: Thesis (PhD)
Subjects: Degree Thesis
Departments: College of Arts and Humanities > School of Music
Date Deposited: 13 Nov 2017 09:33
Last Modified: 13 Nov 2017 09:33
URI: http://e.bangor.ac.uk/id/eprint/10261
Administer Item Administer Item

eBangor is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.