Proceedings of the International Conference on Education, Economics and Information Management (ICEEIM 2019)

A Summary of the Application of Artificial Intelligence in Music Education

Authors
Jin Zhang, Jiawei Wan
Corresponding Author
Jin Zhang
Available Online 6 April 2020.
DOI
10.2991/assehr.k.200401.012How to use a DOI?
Keywords
artificial intelligence, musicology, education
Abstract

With the development of modern science and technology, the application of artificial intelligence in music education is more and more extensive, which is beneficial to the development of music education in China. The application of artificial intelligence in music education has broken the traditional music education model, especially the application of computer music system and high intelligent music software in music education, which has greatly improved the quality of music teaching and expanded the music teaching model. This paper is a summary of the research achievements of Cao Meng, Zou Mengyu, Deng Yue and Yuan Quan.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Conference on Education, Economics and Information Management (ICEEIM 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
6 April 2020
ISBN
978-94-6252-949-6
ISSN
2352-5398
DOI
10.2991/assehr.k.200401.012How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jin Zhang
AU  - Jiawei Wan
PY  - 2020
DA  - 2020/04/06
TI  - A Summary of the Application of Artificial Intelligence in Music Education
BT  - Proceedings of the International Conference on Education, Economics and Information Management (ICEEIM 2019)
PB  - Atlantis Press
SP  - 42
EP  - 44
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200401.012
DO  - 10.2991/assehr.k.200401.012
ID  - Zhang2020
ER  -