The research fields of "artificial intelligence and music" and "cognitive musicology" are relative newcomers to the many interdisciplinary groupings based around the centre of AI and cognitive science. They are concerned with the computational study and emulation of human behaviour with respect to music, in many aspects, and with varying degrees of emphasis on psychological plausibility. Recent publications have included work in such diverse areas as rhythm and pitch perception, performance, composition, and formal analysis. Music shares with language the property of giving access to human mental behaviour in a very direct way. As such, it has the potential to be a very useful domain for AI work. Furthermore, in the course of time, AI related work will surely throw light back onto some or all of the fields to which it is applied. Indeed, we are already beginning to feel the benefits of the application of AI techniques to music technology. It is not surprising, therefore, that one of the first areas interest for of musical AI study is that of music education. There are many ways in which an artificial intelligence or cognitive science approach to music education may be applied - for example, to automate tuition, to explain learning processes, to provide metaphors for human computer interaction, and so on. This collection of papers, which is intended to give an impression of both the breadth and depth of the field, originated from a workshop entitled "Music Education: An Artificial Intelligence Approach".

Klappentext

This volume is based on the proceedings of the Workshop on Music Education: An Artificial Intelligence Approach, which was held in Edinburgh, Scotland, on 25 August 1993, as part of AI-ED 93, the World Conference on Artificial Intelligence in Education. Music education is an area of particular interest within artificial intelligence/music research, which is concerned with the computational study and emulation of human behaviour with respect to music. The workshop concentrated on the themes of music education, representation of musical knowledge, and music theory and computational models. This volume covers a wide range of topics, and as such serves both as an introductory text to a relatively new field, and also as a report on (aspects of) the state of the art. It will be of particular interest to researchers, practitioners, and postgraduate students.

Inhalt
Section I: Music Education.- Agent Reflection in an Intelligent Learning Environment Architecture for Musical Composition.- Learning About Harmony with Harmony Space: An Overview.- MOTIVE: The Development of an AI Tool for Beginning Melody Composers.- Uncovering Cognitive Processes in Music Composition: Educational and Computational Approaches.- Section II: Representation of Musical Knowledge.- Representations of the MONK Harmonisation Systems.- Slappability: A New Metaphor for Human Computer Interaction.- Music Representation Between the Musician and the Computer.- Section III: Music Theory and Computational Models.- Pragmatics in Language and Music.- The Role of Musical Memory in Creativity and Learning: A Study of Jazz Performance.- Automatic Characterisation of Musical Style.- Author Index.