Digital Empirical Research of Influencing Factors of Musical Emotion Classification Based on Pleasure-Arousal Musical Emotion Fuzzy Model
Jing-Xian He*1,*2, Li Zhou*1,, Zhen-Tao Liu*3,*4, and Xin-Yue Hu*1
*1School of Arts and Communication, China University of Geosciences
388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China
*2School of Danyang Normal, Zhenjiang College
No.518 Changxiang West Avenue, College Park, Zhenjiang City, Jiangsu 212000, China
*3School of Automation, China University of Geosciences
388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China
*4Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
Wuhan, Hubei 430074, China
In recent years, with the further breakthrough of artificial intelligence theory and technology, as well as the further expansion of the Internet scale, the recognition of human emotions and the necessity for satisfying human psychological needs in future artificial intelligence technology development tendencies have been highlighted, in addition to physical task accomplishment. Musical emotion classification is an important research topic in artificial intelligence. The key premise of realizing music emotion classification is to construct a musical emotion model that conforms to the characteristics of music emotion recognition. Currently, three types of music emotion classification models are available: discrete category, continuous dimensional, and music emotion-specific models. The pleasure-arousal music emotion fuzzy model, which includes a wide range of emotions compared with other models, is selected as the emotional classification system in this study to investigate the influencing factor for musical emotion classification. Two representative emotional attributes, i.e., speed and strength, are used as variables. Based on test experiments involving music and non-music majors combined with questionnaire results, the relationship between music properties and emotional changes under the pleasure-arousal model is revealed quantitatively.
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