Discovering Musical Patterns by Interpreting Artificial Neural Networks
Overview & Synopsis
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.
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Document Information
| Document Title | Discovering Musical Patterns by Interpreting Artificial Neural Networks |
|---|---|
| Author / Organization | Michael R. W. Dawson |
| Subject & Discipline | Neural Networks and Deep Learning, Computer, Digital, and Mathematical Music, Digital Signal Processing (DSP), Sound and Imaging Processing |
| Categories | Neural Networks and Deep Learning |
| Publication Year | 2018 |
| ISBN | 978-1771992206 |
| License / Rights | CC BY-NC-ND 4.0 |
| Resource Verification | Verification pending |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
|
| File Format | application/pdf (Portable Document Format) |
| Language | ENGLISH |
| Catalog ID | DOC-78966 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |
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