Design of Computer Intelligent Proofreading Algorithm for English Translation Based on Markov Model
Xiaofeng Li · 2023
The passage discusses a proposed method for proofreading English translations of long sentences, particularly in the context of machine translation (MT). The traditional manual proofreading process is deemed inefficient, and existing intelligent proofreading systems are considered inadequate when dealing with a large volume of English long sentence translations. The proposed method involves a part-of-speech tagging approach based on an improved Markov model and an antagonistic learning framework. It utilizes a distribution model of text feature concept sets to identify and correct English translation errors. The results indicate that this method outperforms the traditional ID3 algorithm, with a reduction in Mean Absolute Error (MAE) by about 15% and an increase in recall rate by approximately 10%. These improvements demonstrate the effectiveness of the proposed intelligent proofreading algorithm for enhancing the quality of translations, particularly for complex English long sentences. Overall, the system described in the paper is shown to have a high level of accuracy in detecting grammatical errors in English sentences, automating the detection of translation errors, and delivering superior performance.