Feature Recognition Method based on Computer-Aided Technology and its Application in Music Teaching

Abstract

Due to the influence of factors such as strong music specialty, complex music theory knowledge and various changes, it is difficult to identify music features in the process of music teaching. Therefore, a music feature recognition system based on computer aided technology is proposed. The physical sensing layer of the system is equipped with sound sensors in different locations to collect the original music signals, and the digital signal processor is used to analyze and process the music signals. The network transmission layer will process the music signal and transmit it to the music signal database in the system application layer. The music feature analysis module in the application layer adopts dynamic time warping algorithm to obtain the maximum similarity between the test template and the reference template, realize the feature recognition of music signal, and identify music form and music emotion corresponding music feature content according to the recognition results. The experimental results show that the computer-aided music teaching system for music theory knowledge learning, works of music appreciation, music composition activity provides many functions, such as for teachers and students to provide a lot of learning resources, through the network technology to help music learners learn effectively and quickly, rich music knowledge, expand horizons, meet different users' personalized requirements.