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Evolutionary Computation Applied to Melody Generation
Intelligent Engineering Systems through Artificial Neural Networks
  • Matt D. Johnson
  • Daniel R. Tauritz, Missouri University of Science and Technology
  • Ralph W. Wilkerson, Missouri University of Science and Technology
Abstract

One of the major goals in the field of computer generated music is capturing the intangible human perception which determines whether or not a melody is "good." Human perception of music is extremely difficult to encode in a computer because doing so requires modeling human experiences which combine to form an individual's perception. Modeling perception is even more difficult when one considers that every person on earth has a unique vantage point. A solution employed by many researchers in the field is selecting one genre of music and building models from "good" selections in that style of music. The principal goal of this research is to determine whether a tree based music model can be used in an evolutionary algorithm fitness function to rate computer generated melodies. Well-known examples of church hymnody were employed in the construction of our music model. The results presented show that tree based music models are effective music critics when combined with application specific genetic operators.

Department(s)
Computer Science
Keywords and Phrases
  • Computer Generated Sound,
  • Music Generation
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2004 American Society of Mechanical Engineers (ASME), All rights reserved.
Publication Date
1-1-2004
Disciplines
Citation Information
Matt D. Johnson, Daniel R. Tauritz and Ralph W. Wilkerson. "Evolutionary Computation Applied to Melody Generation" Intelligent Engineering Systems through Artificial Neural Networks (2004)
Available at: http://works.bepress.com/daniel-tauritz/32/