Research on Music Emotion Classification Based on CNN-LSTM Network

Abstract

Music art contains rich emotional information. The research on the classification of music emotion is of great significance for massive music organization and retrieval. In view of this, this study extracts the feature parameters in music information based on support vector machine (SVM), convolutional neural network (CNN) and cyclic neural network (RNN). While analyzing the impact of different feature parameters on music emotion classification, this paper constructs a CNN-LSTM combined network classification model. The results show that compared with the traditional classification algorithms, the combined model constructed in this study has higher classification accuracy and can improve the performance of music emotion classification thoroughly.