Deep learning techniques for music generation / Jean-Pierre Briot, Gaëtan Hadjeres, François-David Pachet.
Av: Briot, Jean-Pierre [aut]
Medverkande: Hadjeres, Gaëtan [aut] | Pachet, François [aut]
Language: English Serie: Computational synthesis and creative systems: Publisher: Cham, Switzerland : Springer, 2020Copyright date: ©2020Beskrivning: xxviii, 284 pages illustrations (some color), music 25 cmInnehållstyp: text Mediatyp: unmediated Bärartyp: volumeISBN: 3319701622; 9783319701622Ämne(n): Datormusik | Maskininlärning | Computer music | Machine learningDDK-klassifikation: 781.34631 LOC-klassifikation: ML1380 | .B76 2020| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
| Book | Musik- och teaterbiblioteket Elektronmusikstudion EMS | EMS : A4 | Available (Längre framtagningstid) | 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)