Design of English Diagnostic Practice Sentence Repetition Recognition System Based on Matching Tree and Edge Computing

Abstract

English reading ability is an important indicator to measure learners’ English ability. However, because reading ability cannot be directly observed, people usually take tests to judge the reading ability of learners. Therefore, it is very necessary to design a reasonable diagnostic practice sentence repetition recognition system to analyze and test, inform learners of the advantages and disadvantages in reading, and give corresponding countermeasures. In order to properly solve the problem of repeated recognition of English diagnostic sentences, we have developed a new recognition system combined with matching tree and edge computing technology. First, the matching tree algorithm is used for the repetitive diagnosis of English sentences. The algorithm has achieved good results in the repetitive diagnosis and matching. Secondly, an English diagnostic practice sentence repetition recognition system architecture is built through edge computing algorithms, which improves the efficiency of the English diagnostic system. Finally, through the simulation test of the English diagnostic practice system, the applicability of the established repeated recognition model is verified.