English Vocabulary Memory Intelligent Review System Supported by Deep Learning

In the context of globalization, English learning is becoming increasingly important, but traditional vocabulary memorization methods have many limitations. This paper constructs an intelligent review system for English vocabulary memorization based on deep learning, integrating big data analysis and personalized learning theory. Through word vector generation and reinforcement learning algorithms, the system realizes vocabulary representation learning, memory updating, and personalized review strategy generation. The experiment selected 50 English learners and divided them into an experimental group and a control group for comparison. The results showed that the experimental group had an average score of 75.36 in the later immediate recall test and an average score of 62.48 in the delayed memory test, which were significantly higher than those of the control group, and the learning time was reduced by 19.05% and the learning pressure was reduced by 21.43%. The system effectively improves the efficiency and persistence of vocabulary memory, provides an efficient and personalized tool for English learning, and promotes the development of language learning theory.