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Amy K. Hoover and Kenneth O. Stanley (2009)
Exploiting Functional Relationships in Musical Composition
To appear in: Connection Science Special Issue on Music, Brain, & Cognition. Abington, UK: Taylor & Francis, 2009 (Manuscript 33 pages)

Note: This paper is accompanied with a set of musical samples at http://eplex.cs.ucf.edu/neatmusic

Note: This is a preprint of the article accepted in Connection Science © 2009 Taylor & Francis. The journal version of the article is available online at informaworld^TM at
http://www.informaworld.com/smpp/content~content=a911513244~db=all?jumptype=alert&alerttype=author,email

Abstract

The ability of gifted composers such as Mozart to create complex multipart musical compositions with relative ease suggests a highly efficient mechanism for generating multiple parts simultaneously. Computational models of human music composition can potentially shed light on how such rapid creativity is possible. This paper proposes such a model based on the idea that the multiple threads of a song are temporal patterns that are functionally related, which means that one instrument's sequence is a function of another's. This idea is implemented in a program called NEAT Drummer that interactively evolves a type of artificial neural network (ANN) called a Compositional Pattern Producing Network (CPPN), which represents the functional relationship between the instruments and drums. The main result is that richly textured drum tracks that tightly follow the structure of the original song are easily generated because of their functional relationship to it.