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About the Book

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.

About the Author

Michael R.W. Dawson is professor of psychology at the University of Alberta and the author of Understanding Cognitive Science (1998), Minds and Machines (2004), Connectionism: A Hands-on Approach (2005), From Bricks to Brains: The Embodied Cognitive Science of LEGO Robots (2010), and Mind, Body, World: Foundations of Cognitive Science (2013).

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Copyright: This work is licensed under a Creative Commons License (CC BY-NC-ND 2.5 CA). It may be reproduced for non-commercial purposes, provided that the original author is credited.

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DownloadFront Matter

DownloadTable of Contents

DownloadList of Figures

DownloadList of Tables

DownloadAcknowledgements

DownloadOverture: Alien Music

DownloadChapter 1: Science, Music, and Cognitivism

1.1 Mechanical Philosophy, Mathematics, and Music

1.2 Mechanical Philosophy and Tuning

1.3 Psychophysics of Music

1.4 From Rationalism to Classical Cognitive Science

1.5 Musical Cognitivism

1.6 Summary

DownloadChapter 2: Artificial Neural Networks and Music

2.1 Some Connectionist Basics

2.2 Romanticism and Connectionism

2.3 Against Connectionist Romanticism

2.4 The Value Unit Architecture

2.5 Summary and Implications

DownloadChapter 3: The Scale Tonic Perceptron

3.1 Pitch-Class Representations of Scales

3.2 Identifying the Tonics of Musical Scales

3.3 Interpreting the Scale Tonic Perceptron

3.4 Summary and Implications

DownloadChapter 4: The Scale Mode Network

4.1 The Multilayer Perceptron

4.2 Identifying Scale Mode

4.3 Interpreting the Scale Mode Network

4.4 Tritone Imbalance and Key Mode

4.5 Further Network Analysis

4.6 Summary and Implications

DownloadChapter 5: Networks for Key-Finding

5.1 Key-Finding

5.2 Key-Finding with Multilayered Perceptrons

5.3 Interpreting the Network

5.4 Coarse Codes for Key-Finding

5.5 Key-Finding with Perceptrons

5.6 Network Interpretation

5.7 Summary and Implications

DownloadChapter 6: Classifying Chords with Strange Circles

6.1 Four Types of Triads

6.2 Triad Classification Networks

6.3 Interval Cycles and Strange Circles

6.4 Added Note Tetrachords

6.5 Classifying Tetrachords

6.6 Interpreting the Tetrachord Network

6.7 Summary and Implications

โปรแกรมพรีเมียร์ลีกDownloadChapter 7: Classifying Extended Tetrachords

7.1 Extended Tetrachords

7.2 Classifying Extended Tetrachords

7.3 Interpreting the Extended Tetrachord Network

7.4 Bands and Coarse Coding

7.5 Summary and Implications

DownloadChapter 8: Jazz Progression Networks

8.1 The ii-V-I Progression

8.2 The Importance of Encodings

8.3 Four Encodings of the ii-V-I Problem

8.4 Complexity, Encoding, and Training Time

8.5 Interpreting a Pitch-class Perceptron

8.6 The Coltrane Changes

8.7 Learning the Coltrane Changes

8.8 Interpreting a Coltrane Perceptron

8.9 Strange Circles and Coltrane Changes

8.10 Summary and Implications

DownloadChapter 9: Connectionist Reflections

9.1 A Less Romantic Connectionism

9.2 Synthetic Psychology of Music

9.3 Musical Implications

9.4 Implications for Musical Cognition

9.5 Future Directions

DownloadReferences

DownloadIndex