Research on Pattern Recognition Methods of Traditional Music Style Characteristics in Big Data Environment

Traditional music is a cultural treasure emerging from the long history of mankind, and the study of traditional music has important artistic and humanistic values. In this paper, the SVM algorithm under incremental learning is used to construct a traditional music style pattern recognition model using the extracted traditional music style feature parameters. The database is constructed by using traditional music compositions containing five music styles, and the data are pre-emphasized and pre-processed by adding windows and frames. After extracting the time-domain feature parameters and MFCC feature parameters of the database songs, the recognition model constructed in this paper is used for traditional music style pattern recognition. In traditional music style recognition, the accuracy of this paper’s model for five traditional music styles is around 90%, and the accuracy of traditional music recognition for opera style is as high as 95.11%. Overall, the model constructed in this paper is able to effectively recognize the styles of traditional music through the extracted traditional music style feature parameters.