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Published on 7 February 2024
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Wang,G. (2024). The investigation of artificial intelligence-based applications in music education . Applied and Computational Engineering,36,210-214.
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The investigation of artificial intelligence-based applications in music education

Ge Wang *,1,
  • 1 Dalian Maritime University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/36/20230448

Abstract

The field of music education has garnered significant attention due to the burgeoning advancements in artificial intelligence technology. Currently, there are many works on applying Artificial Intelligence (AI) technology to the field of music education, and this review aims to comprehensively summarize the application of AI methods in multiple subfields of music education. In this paper, according to the focus of AI technology, the areas of music education to which it has been applied are divided into four modules, namely personalized learning, automatic assessment, composition assistance and interactive teaching. Firstly, representative AI methods applied to each of these four subfields are introduced, including but not limited to: the principle of the AI method, the improvement brought by the application. The text then describes the current status of the application of these methods in their domains, discusses the limitations of the application, and makes brief conjectures on how to break through these limitations. The research in this review paper is important for the development of AI technology applied to the field of music education. At the same time, this review also provides directions and suggestions for future research to promote the further development of AI in the field of music education.

Keywords

music education, artificial intelligence, machine learning, deep learning

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Cite this article

Wang,G. (2024). The investigation of artificial intelligence-based applications in music education . Applied and Computational Engineering,36,210-214.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

Conference website: https://2023.confmla.org/
ISBN:978-1-83558-297-8(Print) / 978-1-83558-298-5(Online)
Conference date: 18 October 2023
Editor:Mustafa İSTANBULLU
Series: Applied and Computational Engineering
Volume number: Vol.36
ISSN:2755-2721(Print) / 2755-273X(Online)

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