A method for English paragraph grammar correction based on differential fusion of syntactic features.

ABSTRACT: The new progress of deep learning and natural language processing technology has strongly promoted the development of English grammar error correction. However, the existing methods mostly rely on large-scale corpus, and often ignore the fine syntactic correlation in paragraphs, which limits the efficiency in complex grammar error correction scenarios. In order to break through this bottleneck, this study proposes an innovative method to effectively use syntactic features to improve the quality and accuracy of paragraph-level grammar correction. Firstly, the sentence vector representation is constructed by BERT, and then the syntactic structure is extracted by dependency parsing. Then carry out difference fusion analysis, measure the syntactic differences of adjacent sentences by cosine si

SUBMITTER: Liu W 

PROVIDER: S-EPMC12266432 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature