A Study of Artistic Expression and Spectral Data Analysis in Yangqin Performance Techniques

Abstract The yangqin was mainly used as an accompaniment instrument in the early days, and after years of development, it has become one of the most important members of Chinese folk musical instruments, and plays an important role in ensembles, repertoire and orchestra. In this paper, a model for analyzing the spectral data of yangqin performance is constructed. The feature selection based on recursive feature elimination and random forest is used to characterize the spectral features of the yangqin more accurately. Following the nearest neighbor principle and the center of mass principle, the codebook and iterative training parameters are set based on the LGB algorithm to realize the quantization of spectral data. This paper takes the yangqin concerto work “Smoke Gesture” by young composer Liu Chang as the research object, and analyzes the spectral data and artistic expression in its performance. In percussive playing, from the bass to the treble area, the peaks decrease from about 20 to about 10, and the distribution of peaks is more concentrated. The energy in the scraping method was concentrated at 394~2442 Hz, while the pitch frequency in the anti-bamboo method was generally higher than the reference frequency value, and the energy was mainly concentrated at 440~740 Hz. The average ratings of all dimensions of the total dimension of the evaluation in terms of artistic expression were all greater than 70, and the performance skills were better.