Exploration of Personalized English Learning Applications and Practices on Mobile Terminals Under Voice Interaction Technology

Abstract

The proliferation of mobile internet and the advancement of artificial intelligence have made voice interaction a significant breakthrough in the field of English language learning. This paper focuses on voice interaction technology and examines its application pathways and practical outcomes in personalized English learning on mobile terminals. Research indicates that the coordinated use of technologies such as automatic speech recognition and natural language processing can effectively support personalized learning needs across multiple dimensions, including vocabulary, grammar, and oral expression, while adaptive systems further enable dynamic matching of learning content and progress. On this basis, the paper constructs a multi-dimensional evaluation index system and proposes optimization recommendations addressing the technical limitations and application bottlenecks present in current practice.