Metaphorical Expression of Emotions in Modern Music Composition Based on Emotional Calculations

Abstract

In this paper, audio and lyrics features of music are fused from the audio and lyrics attributes of modern music tracks to obtain a joint representation of music. The features such as tempo, directionality, average value of intensity, beat, and change of rhythm of each musical segment are extracted from the main audio track to form the music feature vector. Subsequently, the music was separated into multiple segments with distinct emotions, and the emotional expression of modern music was evaluated using the Hevner emotion model. Finally, the note extraction performance of this paper’s model is analyzed, and the spectral contrast features of different music pieces and the emotional expression of music pieces under different features are explored. The results show that the pitch patterns of sad emotions are mostly distributed in the range of 0.5-0.55, and the values of the pitch patterns of angry music are basically larger than 0.55. The mean values of the spectral entropy of joy and calmness are mostly distributed in the range of 0.5-0.7, and the sad emotions are mostly in the vicinity of 0.7, while the mean values of the spectral entropy of angry emotions are larger than 0.8.

Keywords

• affective computing
• joint representation
• hevner affective model
• spectral contrast
• music composition emotion
• 00a65