Exploration on Classification of Vocal Music Theme Based on Intelligent Multi Image Feature Fusion

Music is a form of artistic expression, which can cultivate sentiment. Music can also be regarded as a language. Listening to music can give play to imagination through hearing, so as to resonate with the expression ideas of music creators. Music has no boundaries and is a cultural heritage. Therefore, when listening to music, music itself is not the purpose of listening, but the meaning behind music is the focus of feeling. People can communicate and express their feelings through music. The scope of music is very broad. Vocal music, as a kind of music, can be seen as an art combined with language. People’s understanding of the classification of the main melody of vocal music is very simple. The music culture is broad and profound. The clear classification of the main melody of vocal music is of great significance to deepen the understanding of music. Therefore, this paper proposed an intelligent multi image feature fusion classification of vocal music theme. Through the experiment on the classification of vocal music theme by the artificial intelligence multi image feature fusion model, the data obtained showed that the number of single part music included in the 60 music classification was 17; the number of polyphonic music was 22, and the number of theme music was 21. It was consistent with the judgment results of two professional music teachers and student B, which indicated that intelligent multi image feature fusion can improve the accuracy of music classification. This study provided a reference value for the role of intelligent multi image feature fusion in the classification of vocal theme, and provided a future direction for the development of vocal theme classification.