Evolving Musical Harmonisation (original) (raw)

1999, Artificial neural nets and …

We describe a series of experiments in generating traditional musical harmony using Genetic Algorithms. We discuss some problems which are specific to the musical domain, and conclude that a GA with no notion of meta-level control of the reasoning process is unlikely to solve the harmonisation problem well. 1. the use of knowledge-rich structures and procedures within the algorithm itself, as opposed to the more traditional use of GA components which are not problem-specific; 2. the strict use of objective methods, in the sense that any reasoning encoded in the GA should be stated explicitly, rather than being implicit in the expressed opinion of a human user. These criteria are important because we are working in the wider context of simulating and understanding aspects of human behaviour, so we are not interested just in achieving a musical result: we wish to be able to examine the internal behaviour of our methods, and attempt to form some notion of why the answer we achieve is produced. In particular, we wish to compare the behaviour of our harmonisation system with human behaviour, and attempt to explain any discrepancies. This paper is structured as follows. We present a brief statement on the issues interaction vs. noninteraction in GAs from the point of view of this study. We then outline existing applications of GAs in computer music. We present a case study of a knowledge-rich musical GA, including a discussion of some significant problems, and then draw conclusions about the implications of the work for musical GAs in general.

Sign up for access to the world's latest research.

checkGet notified about relevant papers

checkSave papers to use in your research

checkJoin the discussion with peers

checkTrack your impact