Deep learning techniques for music generation / Jean-Pierre Briot, Gaëtan Hadjeres, François-David Pachet.
Språk: Engelska Serie: Computational synthesis and creative systemsUtgivning: Cham, Switzerland : Springer, 2020Utgivningstid: ©2020Beskrivning: xxviii, 284 pages illustrations (some color), music 25 cmInnehållstyp:- text
- unmediated
- volume
- 3319701622
- 9783319701622
- 781.34631 23/swe
- ML1380
| Cover image | Item type | Current library | Home library | Collection | Shelving location | Call number | Materials specified | Vol info | URL | Copy number | Status | Notes | Date due | Barcode | Item holds | Item hold queue priority | Course reserves | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Book | Musik- och teaterbiblioteket Elektronmusikstudion EMS | EMS : A4.2 | Available (Längre framtagningstid / Longer processing time) | 26201850223 |
Includes bibliographical references (pages 251-261) and index
Introduction -- Method -- Objective -- Representation -- Architecture -- Challenge and Strategy -- Analysis -- Discussion and Conclusion
"This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation."--Page 4 of cover
Imported from: zcat.oclc.org:210/OLUCWorldCat (Do not remove)