Outline

Ingegneria Sismica

Ingegneria Sismica

The Transformative Impact of Artificial Intelligence on Musical Aesthetics and Aesthetic Perception in the Age of the Intersection of Art and Technology

Author(s): Xiaohan Yu1, Lingling Fang2
1Music School of Liaoning Normal University, Dalian, Liaoning, 116000, China
2Computer Science and Artificial Intelligence School of Liaoning Normal University, Dalian 116081, Liaoning, China
Yu, Xiaohan. and Fang, Lingling. “The Transformative Impact of Artificial Intelligence on Musical Aesthetics and Aesthetic Perception in the Age of the Intersection of Art and Technology.” Ingegneria Sismica Volume 43 Issue 2: 1-21, doi:10.65102/is2026560.

Abstract

In the context of the era of the convergence of art and technology, traditional music education methods can not meet the current user needs, how to use artificial intelligence technology to accelerate the change of music aesthetics and aesthetic perception is an inevitable trend. This paper determines the source of this data, and uses crawler technology to obtain the data needed for the design of the artificial intelligence system, in order to complete the design of the data collection module. Randomly combining the post-deep learning neural network theory, music labeling features, to establish a music recommendation module based on LSTM-AM, in addition, the first use of the N-gram for coarse matching of music songs, in the use of DTW algorithm to further fine matching, so that the music retrieval is more accurate, and ultimately to complete the music retrieval module design. Finally, the user interaction module is designed from the aspect of music navigation and message pushing, and these four modules together constitute an artificial intelligence system for music aesthetics and aesthetic perception, and the system is discussed and analyzed in depth. The mean values of students’ tests on the artificial intelligence system oriented to music aesthetics and aesthetic perception are 87.25, 89.26 and 91.15, which are higher than the mean values of the music system based on multilayer neural networks by 35.55, 39.15 and 40.95, and higher than those of the music system based on the intelligent cloud service platform by 36.2, 40.45 and 42.8, which indicates that students’ tests on the artificial intelligence system oriented to music aesthetics and aesthetic perception are higher than those of the music system based on intelligent cloud service platform by 36.2, 40.45 and 42.8. Artificial Intelligence system evaluation in music aesthetics, aesthetic perception, and satisfaction performance satisfaction, to verify the practical application efficacy of the system, and to provide theoretical references for the change of music aesthetics and aesthetic perception empowered by Artificial Intelligence technology.

 

Keywords
lstm-am; n-gram-dtw; artificial intelligence system; music aesthetics; aesthetic perception

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