From artificial neural networks to deep learning for music generation: history, concepts and trends

The current wave of deep learning (the hyper-vitamined return of artificial neural networks) applies not only to traditional statistical machine learning tasks: prediction and classification (e.g., for weather prediction and pattern recognition), but has already conquered other areas, such as transl...

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Vydáno v:	Neural computing & applications Ročník 33; číslo 1; s. 39 - 65
Hlavní autor:	Briot, Jean-Pierre
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.01.2021 Springer Nature B.V Springer Verlag
Témata:	Artificial Intelligence Artificial neural networks Cognitive tasks Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Deep learning Humanities and Social Sciences Image Processing and Computer Vision Machine learning Music Musicology and performing arts Neural and Evolutionary Computing Neural networks Pattern recognition Probability and Statistics in Computer Science S. I : Neural Networks in Art sound and Design Statistical methods Weather forecasting Deep learning Tutorial Concepts Generation Music Artificial neural networks Trends History deep learning music generation
ISSN:	0941-0643, 1433-3058
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Shrnutí:	The current wave of deep learning (the hyper-vitamined return of artificial neural networks) applies not only to traditional statistical machine learning tasks: prediction and classification (e.g., for weather prediction and pattern recognition), but has already conquered other areas, such as translation. A growing area of application is the generation of creative content, notably the case of music, the topic of this article. The motivation is in using the capacity of modern deep learning techniques to automatically learn musical styles from arbitrary musical corpora and then to generate musical samples from the estimated distribution, with some degree of control over the generation. This article provides a tutorial on music generation based on deep learning techniques. After a short introduction to the topic illustrated by a recent example, the article analyzes some early works from the late 1980s using artificial neural networks for music generation and how their pioneering contributions foreshadowed current techniques. Then, we introduce some conceptual framework to analyze various concepts and dimensions involved. Various examples of recent systems are introduced and analyzed to illustrate the variety of concerns and of techniques.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	0941-0643 1433-3058
DOI:	10.1007/s00521-020-05399-0