Contextualized Automatic Translation System for English Translation Based on Improved GLR Algorithm

In order to solve the problem that the traditional English translation calibration computer system only pays attention to the accuracy of words and grammar, and ignores the context, it is easy to cause the overall incomprehension of the translation. This paper presents an automatic translation calibration system based on improved GLR algorithm. In order to accurately identify phrases, an intelligent phrase recognition algorithm based on improved GLR algorithm is designed. This algorithm constructs a phrase corpus with 740000 English and Chinese words, which enables the phrase to have a searchable function. The phrase structure can be constructed through the phrase center point, and the part of speech recognition results can be obtained. The English and Chinese structural ambiguity in the part of speech recognition results can be corrected according to the syntactic function of the parsing Linear List, and the final recognition content can be obtained. This article identifies the problems of inconsistencies in English translation results and develops a smart model for recognizing English translations that can provide complex and concise meanings again translation results. The result finding that improved GLR algorithm has a score of 92.3, which is higher than other similar algorithms and has the best performance of other algorithms. The statistical method of dynamic memory algorithm based on the improved GLR algorithm is more accurate and ensures the accuracy above 95%, The improved GLR-based algorithm is very effective in translation.