A Statistical English Syntax Analysis Model Based on Linguistic Evaluation Information

Abstract

Language evaluation research currently focuses on the analysis of scholars from various native language backgrounds, whereas the local grammatical characteristics of other groups, particularly English language learners, are discussed less frequently. Local grammar offers a new perspective for analyzing the meaning characteristics of evaluation languages from the point of view of the people who employ them. In order to provide context for this paper, past research on local syntax is reviewed. The language model generates text that can be analyzed to determine the model’s aggressiveness when perturbed. To evaluate the method’s precision and efficacy, we compared the aggressiveness of pretrained models under various conditions using an English database. The results demonstrate that the method is capable of automatically and effectively evaluating the aggressiveness of language models. We then examine the scales of model parameters and the relationships between words in the training corpus.