Author(s)

Ranwei Huang

Corresponding Author

Ranwei Huang

Abstract

With the rapid development of Artificial Intelligence Generated Content (AIGC) technology, personalized interaction design has gradually become a key trend in improving user experience. AIGC can generate high-quality content in real-time through technologies such as Generative Adversarial Networks (GANs), Natural Language Processing (NLP), and multimodal fusion, meeting the diverse and personalized needs of users. This article focuses on AIGC and explores in depth the construction methods of personalized interaction design systems and their applications in user experience optimization, covering technical foundations, system architecture design, user experience models, and practical case analysis. Research has shown that interaction design systems based on AIGC can not only generate customized content through accurate user profiles, but also dynamically adapt to user needs, enhancing the immersion and participation of interactions. In addition, this article proposes strategies to optimize system performance and improve user satisfaction, including specific methods such as data privacy protection, content generation quality optimization, and multimodal interaction design. Through case studies in education, virtual navigation, and other fields, AIGC has demonstrated significant advantages in personalized interaction and user experience improvement. Finally, this article analyzes the current technological and ethical challenges faced and provides clear directions for future research and practice.

Keywords

AIGC; Personalized Interaction Design; User Experience Optimization; System Construction