Exploring the Interactive Application of Artificial Intelligence in Oral English Teaching

Abstract

With the increasing development of digital education, the demand for interactivity and personalization in English oral teaching is becoming more urgent. The research focuses on the interactive application of artificial intelligence technology in oral teaching, aiming to explore how it can meet these needs. The application of various artificial intelligence technology models in oral teaching was studied and analyzed, including real-time feedback of speech recognition, personalized guidance of dialogue systems, simulation of virtual character scenarios, data-driven path optimization, and multimodal human-machine collaboration. Through the deconstruction and practical verification of technical functions, the effectiveness of these technologies in actual teaching has been evaluated. The study focuses on English oral learners, especially those who hope to receive more support in terms of interactivity and personalization. Research has found that artificial intelligence technology can significantly improve practice frequency, optimize feedback efficiency, and enhance situational realism in English oral teaching. These technologies break through the limitations of traditional interactive teaching and provide learners with high-frequency and precise interactive experiences. This study has important guiding significance for the innovation of smart language education and provides new directions for the future development of English oral teaching.