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Connectionist Representations of Tonal Music

Discovering Musical Patterns by Interpreting Artifical Neural Networks
Langbeschreibung
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.
Inhaltsverzeichnis
List of FiguresList of Tables
Acknowledgements
Overture: Alien Music

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

References / Index
Michael R. W. Dawson is a professor of psychology at the University of Alberta. He is the author of numerous scientific papers as well as the books Mind, Body, World: Foundations of Cognitive Science (2013) and From Bricks to Brains: The Embodied Cognitive Science of LEGO Robots (2010).
ISBN-13:
9781771992220
Veröffentl:
2018
Seiten:
312
Autor:
Michael R. W. Dawson
eBook Typ:
EPUB
eBook Format:
EPUB
Kopierschutz:
2 - DRM Adobe
Sprache:
Englisch

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