Topic Analysis of English Oral Competence Research Based on LDA Model

This study utilizes the Latent Dirichlet Allocation (LDA) topic modeling method to systematically analyze academic articles related to “English oral competence” published in core domestic journals between 1999 and 2024. By exploring a large corpus of literature, the research identifies three primary themes: English oral competence pedagogy, English oral competence testing and assessment, and English oral competence learning and language analysis. Through a detailed analysis of the evolution of these themes, the study reveals that the application of intelligent technologies, such as artificial intelligence and automated speech recognition, is gradually becoming a focal point in English oral competence research. At the same time, the modernization of oral testing and pedagogy remains a key area of concern for educators and researchers. Future research trends are likely to prioritize the integration of cutting-edge technologies, such as machine learning and AI, alongside interdisciplinary approaches, providing new directions and momentum for the further development of English oral competence research. This study contributes valuable insights into the ongoing transformation of the field.