Big Data Analysis of Music Education for Future Intelligent Learning Leveraging E-Learning Using Deep Learning Technology

被引:0
|
作者
Yu Y. [1 ]
Cao D. [2 ]
Rahman M. [3 ]
机构
[1] Weifang Engineering Vocational College, Phoenix College of Art, Shandong Province, Qingzhou
[2] College of Music, Changchun University, Changchun
[3] National University of Sciences and Technology, Islamabad
来源
Computer-Aided Design and Applications | 2024年 / 21卷 / S22期
关键词
Big Data; Deep Learning; Future Intelligent Learning; Leveraging E-Learning; Music Education;
D O I
10.14733/cadaps.2024.S22.103-114
中图分类号
学科分类号
摘要
In music education, using artificial intelligence and extensive data analysis to identify learners' abilities and provide them with personalized guidance will profoundly impact the entire learning process. The article describes how to use deep learning techniques to build a predictive music learning system through two of the most significant applications in music education: music education platform and music teaching software. The article first reviews the research on deep learning in music education and then introduces the data sources and methods that can be used to build deep neural networks. Based on this, a system is constructed that can predict a user's playing style from their playing data. By testing the performance data of hundreds of users, the article implements a music learning system based on deep learning technology, which can predict the user's performance style based on the user's previous learning experience and performance style. The experimental results show that using deep learning technology to optimize the music education extensive data analysis system can increase its accuracy to 93%. © 2024, CAD Solutions, LLC. All rights reserved.
引用
收藏
页码:103 / 114
页数:11
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