A Study of the Function of Emotional Calculation in Expressing and Communicating in Music Performance in Multicultural Contexts

Abstract

Affective computing technology can recognize emotional expressions in multimodal information. In this paper, a music performance emotion optimization method is proposed, which uses MFCCG-PCA to extract music emotion information and optimize it and then constructs a music emotion expression optimization model according to KTH rules and genetic algorithm. The experiments show that the average accuracy of emotion recognition in the open MFCCG-PCA test is 92.73%, and the accuracy of emotion calculation in five cultural types of music performances is 82.93%. The emotion optimization results were close to the performance requirements, with an emotion optimization accuracy of 86.9%, and the overall subjective score of the optimization results for musical performances was 4.12, which was a better performance than the comparison methods. The results of this research can be used to optimize emotion in multicultural music performance.