A study on the method of analyzing the expressiveness of musical performance of flute based on steady-state stochastic process

Abstract

In this paper, the performance data are processed using direct discretization in a steady-state stochastic process, and the flute performance white noise signal is transported through a linear transfer function to form a performance complex conjugate according to the indeterminate value of the power spectral density input music data. The envelope function is uniformly modulated to form a mixed Gaussian fit to the performance data to simulate the distribution of the performance frequency situation, combined with a closed-loop model to count the flute performance signal-to-noise ratio loss. The results show that the steady-state stochastic process reduces the time required for music performance classification by 1.18 seconds, and the pitch accuracy is 89%. Through the steady-state stochastic process, we can better understand performance, comprehend the integration of technique and emotion, and enhance our understanding of flute performance.

Keywords

• steady-state stochastic process
• flute music performance
• noise signal
• closed-loop model
• mixed gaussian fit
• 97m80