<p>With the development of artificial intelligence technology, intelligent language teaching system has gradually become an important tool to improve language learning effect. This paper proposes an intelligent language teaching system framework based on speech recognition technology, combining natural language processing, deep learning algorithm and big data analysis to build a comprehensive teaching platform. The system mainly consists of three levels: data acquisition layer, core algorithm layer and application service layer. Among them, speech recognition technology is the core, supporting functions such as pronunciation evaluation, listening training, oral interaction and personalized learning recommendation. Through deep learning algorithm and noise suppression technology, the system can improve the accuracy and robustness of speech recognition and improve the learning effect in different environments. This paper elaborates on the core module design of the system and explores the application of speech recognition in pronunciation evaluation, automatic speech translation, oral training and other aspects. The experimental evaluation results show that the system is significantly superior to traditional learning tools in pronunciation accuracy, oral expression fluency and listening comprehension ability, providing new ideas and technical support for intelligent language learning.</p>