Abstract
In the early stage of vocal music education, students generally do not understand the structure of the human body, and have doubts about how to pronounce their voices scientifically. However, with the continuous development of computers, computer technology has become more and more developed, and computer processing speed has been greatly increased, which provides favorable conditions for the development of the application of vocal spectrum analysis technology in vocal music teaching. In this paper, we first study the GMM-SVM and DBN, and combine them to extract the deep Gaussian super vector DGS, and further construct the feature DGCS on the basis of DGS; then we study the convolutional neural network (CNN), which has achieved great success in the image recognition task in recent years, and design a CNN model to extract the deep fusion features of vocal music. The experimental simulations show that the CNN fusion-based speaker recognition system achieves very good results in terms of recognition rate.
Highlights
The development of integrated technology has driven the development of semiconductor chips, each chip is able to store tens of thousands of transistors, allowing calculators and controllers to be concentrated on a single chip, which led to the emergence of the microprocessor, combined with large-scale, very large-scale integrated circuits to form the microcomputer, which is a notebook and desktop computer [1]
Spectral analysis technology is widely used in vocal music teaching through computers [3]
The computer displays the time, frequency, and intensity of sound occurring from the computer screen primarily through three-dimensional images; the y-axis represents the frequency spectrum, and the darker the grayscale, the stronger the intensity, and the lighter the grayscale, the weaker the intensity [4]
Summary
The development of integrated technology has driven the development of semiconductor chips, each chip is able to store tens of thousands of transistors, allowing calculators and controllers to be concentrated on a single chip, which led to the emergence of the microprocessor, combined with large-scale, very large-scale integrated circuits to form the microcomputer, which is a notebook and desktop computer [1]. Spectral analysis technology is widely used in vocal music teaching through computers [3]. The use of computer technology in the vocal music teaching process has significantly improved the teaching quality of vocal music education [5]. The use of advanced spectral analysis technology, the usual abstract concepts of sound into computer graphics, so that students can be more vivid and concrete understanding of their own voice, breaking through the traditional "one-to-one" teaching mode, to achieve the "mouth - ear - nose! As a result, advanced computerized spectral analysis techniques are widely used in vocal music classrooms, and they have achieved a very good result. Based on the superior performance of the fusion feature, this paper constructs a CNN fusion feature using a convolutional neural network. The experimental simulation shows that the CNN fusion-based speaker recognition system achieves a good recognition rate
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