Development of music teaching software based on neural network algorithm and user analysis

Abstract

Abstract At this stage, music teaching is facing an increasingly serious shortage of teacher resources. Therefore, it is particularly important to develop a music teaching software by using computer assisted music teaching activities. First of all, the operation method program of this system is carefully designed according to the principles of computer network technology. Using the performance characteristics of Fourier transform and its enhanced functions to extract music, the priority key system modules are designed according to the system structure framework and data processing program, and the main design code is provided. With the development of artificial intelligence technology, neural network has gradually become an important research method in this field. And compared with the traditional mechanical learning methods, the neural network based method has the advantages of simple algorithm mode, good universality, strong robustness, organic and mobility. With the rapid change of in-depth learning technology, music teaching software has shown great overall advantages in the accuracy and speed of detection. In addition, this paper analyzes the specific user level of music teaching programs, focusing on their interest in and specific acceptance of these music teaching programs, as well as the use of user feedback to develop specific and effective music teaching programs. Neural network algorithm and user analysis provide a new strategy for developing music teaching software.