Cross-cultural Interaction Research Based on Transdisciplinarity in the Era of AI Converged Media

In the era of AI converged media, various digital media platforms have become the primary means for them to effectively engage in cross-cultural integration. Based on the concept of transdisciplinarity, this research studies the cross-cultural interaction competence of international students from the “Belt and Road” countries participating in the China Calling cross-cultural interaction AI digital media platform project of Shandong Youth University of Political Science, where a sentence semantic knowledge base is constructed as the reference standard for retrieval. The speech audio signals and keyword signals to be retrieved are fed into the model in the same way, and the preprocessing steps include pre-filtering noise reduction and signal enhancement. A convolutional network is built and integrated according to the principles of deep learning algorithms. In this network, feature vectors are extracted from the acoustic model and the language model, and the similarity among the vectors is calculated. Based on the similarity computation results, the retrieval outcomes of the speech content are obtained as well conducted empirical analysis on the constraints of various technical variables in the project using STATA. The results show that the development of digital media in the era of AI converged media as well as the integration of transdisciplinarity concepts are conducive to the innovation and sublimation of cross-cultural interaction, which can help to enhance the cross-cultural integration abilities of international students studying in China and further consolidate the consensus of building a community where humanity shares the future.