Exploring the Implementation Methods of AI-Driven Robots in Media Interaction Experience Design

The purpose of this study is to deeply explore the innovative implementation methods of artificial intelligence (AI)-driven robots in media interactive experience design. Firstly, this paper expounds how AI-driven robot technology can provide users with a more natural and intelligent interactive experience through natural language processing (NLP), speech recognition, computer vision and other technologies, thus enhancing users' sense of participation and immersion. In order to realize the efficient application of AI-driven robot in media interaction, this study proposes a series of implementation methods, including improving the accuracy and personalization of robot interaction by using NLP and deep learning algorithm; Identify user expressions and gestures through computer vision technology to enhance the naturalness of interaction; Multi-modal interactive technology is used to integrate multi-sensory channel information to provide comprehensive interactive experience; Use deep learning technology to train the robot's ability to perceive and understand users' needs, and introduce emotion analysis technology to realize more humanized service; By constructing user portraits, we design personalized interaction schemes that adapt to different scenarios and users. In the experimental part, three different scenes, library, shopping mall and museum, are selected to verify the effectiveness of the design scheme. The results show that the AI-driven robot significantly improves the user's satisfaction and emotional experience under the personalized interaction scheme.