Analysis of Matching of Corpus Input and English Proficiency Based on the Big Data Neural Network Model

Abstract

In the era of “Internet +” big data, the theory and technology of English corpus are becoming more and more mature. Corpus is an important method to reflect some language characteristics and clarify some language phenomena. In terms of cultural exchanges, Chinese students majoring in English have obvious cultural differences at home and abroad and lack the atmosphere and context for cultural exchanges. In addition, students have problems such as insufficient cultural communication skills. The big data neural network model is adopted in this paper to compare and analyze the intermediary sentences in the corpus to explore the development trend of English proficiency. Through the analysis of typical cases, it explores the weak links in the corpus teaching process and summarizes a method focusing on the combination of use of corpus and English teaching.