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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jean-Pierre Briot | - |
| dc.date.accessioned | 2022-04-27T04:32:49Z | - |
| dc.date.available | 2022-04-27T04:32:49Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.uri | https://thuvienso.thanglong.edu.vn/handle/TLU/2831 | - |
| dc.description.abstract | 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. | vi_VN |
| dc.language.iso | en | vi_VN |
| dc.publisher | Springer Fachmedien Wiesbaden | vi_VN |
| dc.subject | Music | Learning Techniques | Âm nhạc | vi_VN |
| dc.title | Deep Learning Techniques for Music Generation | vi_VN |
| dc.type | Recording, musical | vi_VN |
| Appears in Collections | Âm nhạc | |
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