Towards melodic extension using genetic algorithms
Genetic Algorithms (GA's) are considered promising for music composition because they combine ‘creativity’ (ability to explore a large search space) with constraints (creative 'excess' is 'pruned' using a fitness function). A major difficulty with the use of GA's for this task is to define fitness functions which capture the aesthetic qualities of the wide range of successful melodies. In this paper we report on research that addresses this problem in the context of a modest compositional task, melodic extension. We describe 21 melodic features used as the basis for a GA fitness function and for mutation procedures. We discuss how the features were chosen, measured for significance, and might be incorporated into a fitness function.
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|Item Type:||Journal Article|
|Keywords:||Genetic algorithms, Music composition, Creativity, Fitness functions, Melodic extensions, Melodic features|
|Subjects:||Australian and New Zealand Standard Research Classification > STUDIES IN CREATIVE ARTS AND WRITING (190000) > PERFORMING ARTS AND CREATIVE WRITING (190400) > Musicology and Ethnomusicology (190409)|
|Divisions:||Current > QUT Faculties and Divisions > Creative Industries Faculty|
|Copyright Owner:||Copyright 2001 International Forum of Educational Technology & Society / (please consult author)|
|Copyright Statement:||Reproduced in accordance with the copyright policy of the publisher: This journal is available online.|
|Deposited On:||31 Aug 2005 00:00|
|Last Modified:||10 Aug 2011 13:51|
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