Large Model and Lip Feature Extraction: Key Fusion Points for Building an Efficient Lip Recognition System

This article delves into the application of the large model in lip reading recognition, focusing on the basic principles and architecture of large models, and elaborating on their crucial role in lip feature extraction. The article begins by reviewing the development history of deep learning models, highlighting the characteristics and advantages of large models, and providing an in-depth analysis of typical large model architectures. Subsequently, addressing the difficulties and challenges in lip feature extraction, the article discusses the advantages of large models in feature extraction and explores how they can enhance the accuracy of lip reading recognition. Furthermore, the article compares traditional lip feature extraction methods with those based on deep learning, further highlighting the application value of large models. Building on this, the article proposes a fusion strategy of large models and lip feature extraction, and validates its application effects through experiments. The experimental results show that this fusion strategy can effectively improve the performance of lip reading recognition. Finally, the article summarizes the research findings and looks forward to the future development trends of lip reading recognition technology.