A Study of the Application of Bioacoustic Technology in the Integration of Music Teaching with Traditional Teaching Methods

Dan Wang
School of Basic Education, Putian University, Putian, Fujian, 351100, China
Chai Su
Conservatory of Music, Keimyung University, Korea’s Daegu, 42601, Korea

Abstract:

This study provides a more diverse and personalized teaching tool for music education by combining an improved Bayesian estimator and acoustic indices in bioacoustic technology. The article proposes an improved Bayesian estimator that is based on the magnitude spectrum of the Fourier coefficients of the music signal under the Chi distribution and takes into account factors such as the probability of music presence, the noise environment, and the a priori signal-to-noise ratio. This improved Bayesian estimator is able to achieve noise reduction for different music signals by introducing adaptive parameters. Then the difference between the music played by the students and the standard music is compared according to the beta acoustic index. Through experimental analysis, the improved Bayesian estimator in this paper increases the recognition accuracy of music signals by 0.312. Finally, through the use of teaching, the music skill level of the students in the experimental class is higher than that of the students in the traditional teaching class by an average of 2.4 points. Based on this technique teacher can evaluate and instruct students’ musical performance more accurately, analyze the differences between the music played by students and the standard music, and provide targeted teaching.