Intelligent Error Detection Model for English Specialized Vocabulary Translation Based on GLR Algorithm
English has a huge vocabulary with constantly emerging specialized vocabulary including professional terminology,industry terminology,and innovative vocabulary.It's quite difficult to translate and detecting the error of these vocabulary items.To this end,it's necessary to construct an intelligent error detection model for English specialized vocabulary translation based on the generalized maximum likelihood ratio detection(GLR)algorithm.In this study,the GLR algorithm is used to calculate the separability of various errors in English specialized vocabulary translation,and text items with high separability are selected as feature text items for various translation error detection.The experimental results show that the model constructed by the research institute has an error detection accuracy of over 95％for three types of English specialized vocabulary translations:general domain translation texts,specific domain translation texts,and colloquial translation texts,which is significantly better than traditional methods.The above test results indicate this model has higher application reliability.
GLR algorithmEnglish specialized vocabularyseparabilityintelligent translation error detectionmodel construction
万方数据
维普
