The Auxiliary Role of College Music in Teaching in View of Artificial Intelligence

Music is a common art and it is a jewel of human civilisation. In the course of music’s development, the evaluation of music teaching is an inevitable step in the development of quality music. Universities are important places that abound with musical souls and their contribution to the development...

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Bibliographic Details
Published inMobile information systems Vol. 2022; pp. 1 - 11
Main Author Liu, Jie
Format Journal Article
LanguageEnglish
Published Amsterdam Hindawi 22.06.2022
John Wiley & Sons, Inc
Subjects
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ISSN1574-017X
1875-905X
DOI10.1155/2022/2693199

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Summary:Music is a common art and it is a jewel of human civilisation. In the course of music’s development, the evaluation of music teaching is an inevitable step in the development of quality music. Universities are important places that abound with musical souls and their contribution to the development of music has been outstanding. But with the development of the times, university music has been hampered in the field of teaching and learning. As an important branch in the field of computer science and information technology, artificial intelligence technology contains many intersecting and comprehensive subject connotations, bringing brand-new elements to music education. It has also had an important impact on the development of music teaching. The article focuses in depth on the traditional process of music development in terms of the characteristics and ways of teaching music. Based on this, the article further explores the integration of artificial intelligence and music and analyses the role of emerging technologies as an aid to music from the perspective of the times. And this article uses emotion recognition as an evaluation index to explore the evaluation role of artificial intelligence technology in college music teaching, and improve the quality and efficiency of music teaching. The experimental results show that the teacher’s positive emotion rate based on image data is 57.8%, and the student’s positive emotion rate is 44.5%; the teacher’s positive emotion rate based on voice data is 53.3%, and the student’s positive emotion rate is 51.1%. The classroom emotion is negative at 7–13 minutes, the classroom emotion continues to be low at 28–40 minutes, and the teacher and student emotions are more positive at 13–28 minutes.
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ISSN:1574-017X
1875-905X
DOI:10.1155/2022/2693199