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Cookie akzeptieren![Briot, Jean-Pierre / Pachet, François-David et al. Deep Learning Techniques for Music Generation. Springer International Publishing, 2019.](https://eichendorff21.de/cdata/KoAurY6u8CT6v_GRctbJmdoyHnQ=/300x0/9783319701622.png)
Jean-Pierre Briot / François-David Pachet / Gaëtan Hadjeres
Deep Learning Techniques for Music Generation
- Springer International Publishing
- 2019
- Gebunden
- 312 Seiten
- ISBN 9783319701622
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. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the
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