Simulation of Piano Teaching System Based on Virtual Data Space System and Neural Network

Abstract

Cloud computing takes the analysis and digital processing technology based on virtual data space as the foundation and core of cloud computing technology development and research, and the significance and importance of data is self-evident. This paper designs a piano teaching system based on the virtual data space system and neural network, which can help users to master and use piano teaching information through the extensive application of this system. The functional test results show that the system fully realizes the automatic allocation of all virtual data spaces in the cloud computing environment and has the function of real-time synchronization with user terminals and applications in the virtual data space. Teachers can directly give lectures to students or give students detailed answers through live webcasting and other methods. Only by using this simple operation mode can they be able to solve the problems of piano teaching very conveniently. For the on-demand video, this paper manages the piano teaching videos by classification, that is, displays this type of video in an interface or table. The improved network recognition performance based on the loss function also achieves better improvement and improvement than the original network. The model has also achieved good performance in training and recognition on datasets in a strong noise environment.