Design of Computer Intelligent Scoring System for English Translation Based on Markov Model

The existing scoring methods have many shortcomings, such as long calculation time and significant differences from manual scoring results. A machine correction system based on Markov model is proposed to address the problems in English translation correction, in order to reduce manual correction work during the correction process and improve correction efficiency. A hierarchical structure system consisting of modules such as translation data collection, information feature extraction, analysis model construction, and evaluation result feedback has been established for the English translation evaluation system; A language model for evaluating English translations has been proposed, and this model is used to calculate the specific sentence order and word count that appear in the translation. Statistics were conducted on English translation data, and statistical analysis was conducted on the translation data. Intelligent scoring of English translations. Experiments have shown that the difference between the intelligent scoring system and manual scoring is only 0.1 points.