Research on Intelligent Human-Machine Interaction System Design and Data Visualization Based on Multimodal Data Fusion

This paper focuses on the research of intelligent human-machine interaction systems that integrate multimodal data. Firstly, the key aspects of system design are introduced, including system architecture, interaction modes, decision algorithms, and user models. Then, the role of data visualization technology in human-machine interaction is discussed, elucidating relevant methods such as information visualization design, interactive visualization, and visualization evaluation. Finally, the paper emphasizes the implementation of key technologies for multimodal data fusion, including feature extraction, modality alignment, and attention fusion strategies, along with the system testing and evaluation process. The system is capable of integrating multiple heterogeneous data sources such as speech, images, and text, achieving intelligent decision-making through modal fusion, and demonstrating outstanding performance and good user experience in a series of tests and evaluations, thereby providing strong support for natural and efficient human-machine interaction.