Artificial intelligence, education and music : the use of artificial intelligence to encourage and facilitate music composition by novices

The goal of the research described in this thesis is to find ways of using artificial intelligence to encourage and facilitate music composition by musical novices, particularly those without traditional musical skills. Two complementary approaches are presented. We show how two recent cognitive theories of harmony can be used to design a new kind of direct manipulation tool for music, known as "Harmony Space", with the expressivity to allow novices to sketch, analyse, modify and compose harmonic sequences simply and clearly by moving two-dimensional patterns on a computer screen linker to a synthesizer. Harmony Space provides novices with a way of describing and controlling harmonic structures and relationships using a single, principled, uniform spatial metaphor at various musical levels; note level, interval level, chord level, harmonic succession level and key level. A prototype interface has been implemented to demonstrate the coherence and feasibility of the design. An investigation with a small number of subjects demonstrates that Harmony Space considerably reduces the prerequisites required for novices to learn about, sketch, analyse and experiment with harmony - activities that would normally be very difficult for them without considerable theoretical knowledge or instrumental skill. The second part of the thesis presents work towards a knowledge-based tutoring system to help novices using the interface to compose chord sequences. It is argued that traditional, remedial intelligent tutoring systems approaches are inadequate for tutoring in domains that require open-ended thinking. The foundation of a new approach is developed based on the exploration and transformation of case studies described in terms of chunks, styles and plans. This approach draws on a characterisation of creativity due to Johnson-Laird (1988). Programs have been implemented to illustrate the feasibility of key parts of the new approach