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Constraint-Based Patterns : An examination of an algorithmic composition method

This thesis examines the composition of three different musical works through the use of my constraint-based patterns. I have explored the patterns through spreadsheets and also SuperCollider: a software for algorithmic composition and audio synthesis. The aim is to find how the patterns can be used to reach clear contrasts while maintaining coherence in the music, as well as finding challenges and possibilities within the patterns, while exploring how evaluation of the artistic results can contribute to improved methods. While I see the main method as autoethnographical, with the core focus on composing, I have also used feedback from other composers, and through focus groups, as a way to collect data. Throughout this thesis I describe my process of constructing patterns and composing music, accompanied by my reasoning and relevant feedback. My results from analyzing feedback, score and patterns are that while some ways of using the patterns are well suited for achieving contrast and coherence, problems arose related to (among other things) musical form and predictability. Evaluation through feedback and interviews resulted in a better understanding of the patterns, and different workflows allowed for different viability in the evaluation. The most valuable insight is that the greater the amount of composition parameters which are controlled through constraint-based patterns, the simpler each individual composition parameter has to be in order to reach contrasting results that I find satisfying. My conclusion is that I can therefore design each individual composition parameter with high coherence to reach contrasting results when the composition parameters are applied on the same musical structure.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-85001
Date January 2021
CreatorsLilja, Robin
PublisherLuleå tekniska universitet, Institutionen för ekonomi, teknik, konst och samhälle
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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