Todd, P.M. (1989). A connectionist approach to algorithmic composition. Computer Music Journal, 13(4), 27-43.

Abstract

With the advent of von Neumann-style computers, widespread exploration of new methods of music composition became possible. The approach to algorithmic composition based on the wedding between von Neumann computing machinery and rule-based software systems has been prevalent for the past thirty years. The arrival of a new paradigm for computing--parallel distributed processing (PDP), or connectionism--has made a new approach to algorithmic composition possible. One of the major features of the PDP approach is that it replaces strict rule-following behavior with regularity-learning and generalization. This fundamental shift allows the development of new algorithmic composition methods which rely on learning the structure of existing musical examples and generalizing from these learned structures to compose new pieces. This paper presents a particular type of PDP network for music composition applications. Various issues are discussed in designing the network, choosing the music representation used, training the network, and using it for composition. Comparisons are made to previous methods of algorithmic composition, and examples of the network's output are presented.



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