Optimizing the Design of a Vocal Teaching Platform Based on Big Data Feature Analysis of the Audio Spectrum

Abstract

With the development of electronics and communication technology, digital audio processing technologies such as digital audio broadcasting and multimedia communication have been widely used in society, and their influence on people’s lives has become increasingly profound. At present, the real-time and accuracy of musical instrument tuners on the market need to be improved, which hinders the design of vocal music teaching system. Based on the BP neural network algorithm and fast Fourier transform algorithm in FPGA, this paper designs a real-time and efficient audio spectrum analysis system, which realizes the spectrum analysis function of music signal. The methods to calculate fast discrete Fourier transform are the FFT algorithm based on time extraction and the FFT algorithm based on frequency extraction. The characteristic of BP neural network algorithm is that it can not only obtain the corresponding estimation results by forward propagation of the input data but also carry out back propagation from the output layer according to the error between the estimation results and the actual results, so as to optimize the connection weight between each layer. This paper proposes to add Nios II system to FPGA processor and adopt cyclone IV in the hardware design of the system, which can be better compatible with the system designed in this paper. In the software part, WM8731 is used to process the audio data. WM8731 consumes very little power to the system, which will effectively improve the processing efficiency of the system. Compared with the original system, the data model obtained after screening and processing of the system model designed in this paper has an algorithm accuracy of more than 90%, among which the audio spectrum clarity of vocal music can reach 95%. Based on the above, the circuit of each module is tested, and in the specific experimental process, the audio frequency spectrum under different conditions is analyzed and data processed. The system can complete the collection and analysis of various music signals in real time, overcome the limitation of single function of traditional tuner, improve the utilization rate of tuner and the clarity of timbre, and also tune a variety of musical instruments and greatly improve the intonation of musical instruments and the utilization rate of tuner, which has a certain practical value.