Throughout history, art has continued to defy the attempts of scholars and analysts to understand it and reduce it to a set of logical principles. As one of many art forms, music has probably attracted the most attention from formal methods of study and analysis. Analysis leads to models and theories of aspects of musical behaviour, and algorithmic composition is the practice of composing according to a set of rules, processes or principles. The goal of this thesis is to elucidate some fundamental aspects of simple intra-musical meanings. If they can be formulated, then it might be possible to construct an algorithm which can compose music that can be described as 'meaningful' according to certain criteria. This thesis proposes that such intra-musical meanings are closely related to the role of repetition and variation in music, as well as Gestalt grouping principles, and are often what makes music interesting to listen to. The main contribution of this thesis is the development and evaluation of three algorithmic composition systems that attempt to impart a degree of 'meaning' in their output.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:571612 |
| Date | January 1999 |
| Creators | Leach, Jeremy L. |
| Publisher | University of Bath |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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