Connectionist Representations of Tonal Music

Discovering Musical Patterns by Interpreting Artificial Neural Networks

by Michael R. W. Dawson

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Book Description

Previously, artificial neural networks have been used to capture only the informal properties of music. However, cognitive scientist Michael Dawson found that by training artificial neural networks to make basic judgments concerning tonal music, such as identifying the tonic of a scale or the quality of a musical chord, the networks revealed formal musical properties that differ dramatically from those typically presented in music theory. For example, where Western music theory identifies twelve distinct notes or pitch-classes, trained artificial neural networks treat notes as if they belong to only three or four pitch-classes, a wildly different interpretation of the components of tonal music.

Intended to introduce readers to the use of artificial neural networks in the study of music, this volume contains numerous case studies and research findings that address problems related to identifying scales, keys, classifying musical chords, and learning jazz chord progressions. A detailed analysis of the internal structure of trained networks could yield important contributions to the field of music cognition.

This open book is licensed under a Creative Commons License (CC BY-NC-ND). You can download Connectionist Representations of Tonal Music ebook for free in PDF format (13.3 MB).

Table of Contents

Chapter 1
Science, Music, and Cognitivism
Chapter 2
Artificial Neural Networks and Music
Chapter 3
The Scale Tonic Perceptron
Chapter 4
The Scale Mode Network
Chapter 5
Networks for Key-Finding
Chapter 6
Classifying Chords with Strange Circles
Chapter 7
Classifying Extended Tetrachords
Chapter 8
Jazz Progression Networks
Chapter 9
Connectionist Reflections

Book Details

Publisher
AU Press
Published
2018
Pages
311
Edition
1
Language
English
ISBN13
9781771992206
ISBN10
1771992204
ISBN13 Digital
9781771992213
ISBN10 Digital
1771992212
PDF Size
13.3 MB
License
CC BY-NC-ND

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