AI-based intelligent recommendation and dynamic optimization of English speaking teaching resources in higher education

With the rapid development of artificial intelligence technology, the traditional mode of teaching spoken English in universities faces the challenges of personalization and efficiency improvement. Artificial intelligence technology provides opportunities for the development of spoken English teaching, and teachers should seize the favorable opportunity to actively carry out teaching reform and effectively solve the problem of weak foundation of spoken English of college students. Based on artificial intelligence algorithms, this paper studies the intelligent recommendation and dynamic optimization method of university oral English teaching resources. By combining students' learning needs, learning progress and interest characteristics, a personalized teaching resource recommendation algorithm is proposed, and a dynamic optimization mechanism is designed on this basis to achieve real-time adjustment and accurate push of teaching resources. This paper also explores a data-driven evaluation system to continuously optimize the recommendation effect based on learner feedback and learning performance. Through specific case studies, the effectiveness of this intelligent recommendation and optimization system in improving students' interest in oral learning and teaching effectiveness is verified. The research results show that the application of artificial intelligence algorithms in university oral English teaching not only improves the utilization efficiency of teaching resources, but also provides students with more targeted learning support, which has important practical significance and promotion value.