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Music Education: An Artificial Intelligence Approach

Proceedings of a Workshop held as part of AI-ED 93, World Conference on Artificial Intelligence in Education, Edinburgh, Scotland, 25 August 1993

  • Matt Smith
  • Alan Smaill
  • Geraint A. Wiggins

Part of the Workshops in Computing book series (WORKSHOPS COMP.)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Music Education

  3. Representation of Musical Knowledge

    1. Front Matter
      Pages 75-75
    2. Alan Smaill, Geraint A. Wiggins, Eduardo Miranda
      Pages 108-119
  4. Music Theory and Computational Models

    1. Front Matter
      Pages 121-121
    2. Kenny R. Coventry, Tim Blackwell
      Pages 123-142
    3. Martin D. Westhead, Alan Smaill
      Pages 157-170
  5. Back Matter
    Pages 171-173

About these proceedings

Introduction

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".

Keywords

artificial intelligence behavior computer education intelligence knowledge learning memory music performance

Editors and affiliations

  • Matt Smith
    • 1
  • Alan Smaill
    • 2
  • Geraint A. Wiggins
    • 2
  1. 1.Department of ComputingKing Alfred’s College of Higher EducationWinchesterUK
  2. 2.Department of Artificial IntelligenceUniversity of EdinburghEdinburghScotland, UK

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-3571-5
  • Copyright Information Springer-Verlag London 1994
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-19873-4
  • Online ISBN 978-1-4471-3571-5
  • Series Print ISSN 1431-1682
  • Buy this book on publisher's site