Multidimensional Scale Analysis and Modeling of Emotional Space in Yao Music

Abstract

Abstract The research content of this paper gives a detailed analysis of the system structure of the music emotion recognition system. In the process of music feature extraction and recognition, the system first reads the note queue and tempo information queue of the format music and then analyzes and calculates the basic features of the music, tonal and melodic features, etc., respectively. The content of the text set is projected into a three-dimensional visual space using the multidimensional scale analysis method, and then the emotional theme is obtained by dividing the class groups. The samples from the Yao music database are selected as the data source for music emotion research, and performance analysis is performed. The results prove that the method of this paper can effectively perform feature extraction on Yao music files, with an average misdetection rate of only 0.09% and a recognition rate of more than 83% in all cases. The musical structure of Yao Village Impression can be broken down into five parts. The musical melodies mostly consist of major second and minor third intervals. The emotional labeling of structures 1 and 4 in the cluster analysis is distributed in four quadrants, with a preference for pleasurable emotions. Structure 2 was more concentrated in quadrants 1, 4. These emotion distribution results are consistent with the music depicting the beauty of Yao village and the emotional life of Yao people.