Design and Optimization of an Intelligent English Interaction System Based on Speech Recognition and Natural Language Processing Technology

With the rapid development of globalization, traditional learning methods have significant limitations in speaking practice and struggle to meet the personalized needs of learners. Innovative educational tools are needed to enhance students' speaking skills. This paper proposes a design and optimization plan for an intelligent English interactive system based on speech recognition and natural language processing technologies. It explores the adaptability of speech recognition technology under different accents, speech rates, and noise environments. By optimizing deep learning models, the accuracy of recognition is further improved. Meanwhile, by integrating natural language processing technology, the system understands user intentions and generates natural responses, enhancing the fluency of human-computer dialogue. In the system design, a modular architecture is adopted to facilitate later optimization, implementing core functional modules for speech recognition, natural language understanding, dialogue management, natural language generation, and speech synthesis. Experimental validation shows that the optimized system significantly improves recognition accuracy in multiple scenarios, performing particularly well in processing movie dialogues and everyday conversations. The research results indicate that the system designed in this paper not only enhances the English learning experience but also provides an effective technical path for the development of intelligent interactive systems.