Multimodal technology for constructing Chinese-specific discourse terminology databases: A Computational framework with AI-Driven integration

Under the rapid development of Internet technology and national initiatives to enhance Chinese civilization’s global influence, constructing a multimodal Chinese-specific discourse terminology database is crucial for disseminating and developing China’s unique discourse culture. This research establishes five core principles governing its construction: Purposefulness, Scientificity, Scalability, Maintainability, and Security. Leveraging advanced computational techniques-including natural language processing (NLP), deep learning, and multimodal data fusion-we propose a systematic framework integrating data relationships and functional architecture. The implementation pathway comprises three phases: (1) systematic identification and extraction of Chinese-specific discourse terms using transformer-based models (e.g., BERT); (2) acquisition and processing of associated multimodal data (images, audio, video) via convolutional neural networks (CNNs) and recurrent neural networks (RNNs); and (3) database generation and deployment with cloud-native technologies (e.g., Kubernetes, Docker). By integrating multimodal Internet technologies, this study establishes an open-access platform that provides robust data infrastructure and technical foundations for innovating, preserving, and globally disseminating Chinese discourse paradigms.