Intelligent Navigation Dialect Detection and Recognition Based on Multimodal Large Language Model

This paper discusses the research methods of dialect detection and recognition in intelligent navigation systems based on multimodal large language models, points out the development trend of today's intelligent navigation systems and the important application of speech recognition technology in them. It focuses on the progress, basic principles and practical applications of current research, and summarizes the key technologies of dialect detection, including data collection, model design and system integration, by reviewing a large number of literatures. Specifically, this paper covers the acquisition and fusion of voice data and image data, feature extraction and recognition algorithms based on large language models, multimodal fusion strategies, and optimization methods for the system in terms of real-time performance and user experience. Through these technical means, it aims to improve the adaptability and user experience of intelligent navigation systems in multilingual environments, and provide more accurate and personalized navigation services.