Application and Optimization of Multilingual Intelligent Interaction in International Cultural Communication

Yang Ziwei^1,2

1.Institute of Kede College of Capital Normal University, The University of Edinburgh, Edinburgh, UK; 2.Taiyuan Normal University

Abstract：

In an era defined by globalization, digital transformation, and the ascendancy of artificial intelligence, multilingual intelligent interaction has emerged as a pivotal force reshaping international cultural communication. This paper examines the theoretical foundations, practical applications, and optimization strategies of multilingual intelligent interaction systems within cross-cultural contexts. Drawing upon recent advances in natural language processing (NLP), cloud-based deep learning architectures, and cultural intelligence frameworks, this study argues that intelligent multilingual systems—when properly optimized—can bridge communication gaps, enhance cultural awareness, and foster genuine intercultural understanding. The paper further explores challenges including contextual nuance loss, privacy concerns, and the need for culturally adaptive algorithms, proposing a multi-layered optimization framework that integrates real-time NLP, federated learning, and cultural frame-switching mechanisms. Empirical evidence from interactive multilingual learning systems (IMLS), diabetes risk prediction platforms, and AI-driven voice interaction models demonstrates the transformative potential of these technologies. The findings suggest that the synergy between optimization theory, artificial intelligence, and intercultural communication scholarship represents the frontier of inclusive global dialogue.

Key Words：

multilingual intelligent interaction; cross-cultural communication; natural language processing; optimization; cultural intelligence; AI-based translation