Modeling Multicultural Interaction in Silk Road Ethnomusicology Education Based on Deep Learning Framework

Abstract

The countries along the Silk Road are rich in music resources, and the unique multicultural interaction of ethnic music education is an important trend to carry out the living heritage and innovative development of ethnic music culture. In this paper, based on analyzing the dynamic interaction between technology and ethnic music culture, a Trans-GAN model is constructed by combining Transformer Network and GAN model to generate diversified ethnic music. Using the generated diversified ethnic music as teaching resources, we established an ethnic music teaching model by combining the concept of realm pulse. A teaching experiment was designed with the teaching model to verify the feasibility of the model to enhance the multicultural interaction level of ethnic music with the students majoring in ethnic music in G Nationality University as the research object. The results show that the deep learning model can generate more diversified ethnic music of the Silk Road, and the students' ethnic music performance and cultural interaction level can be significantly improved. The integration of deep learning technology into folk music education to realize the diversification of teaching resources provides technical support to help students enhance the level of multicultural interaction, and also provides a new path for the inheritance and innovation of Silk Road folk music.