Chinese English translation accuracy detection method based on machine learning

Abstract

In order to improve the accuracy and efficiency of Chinese English translation accuracy detection, this paper proposes a new Chinese English translation accuracy detection method based on machine learning. In order to test the accuracy of Chinese English translation, a bilingual statistical dictionary is constructed firstly, and the language words are counted according to the dictionary. According to the calculation results of translation length probability, the Chinese English semantic ontology mapping model is constructed to improve the detection accuracy of translation accuracy. In order to accurately detect the accuracy of Chinese English translation, machine learning method is used to detect the semantic similarity of Chinese English translation. Machine learning can detect the similarity of Chinese and English translation texts by constructing knowledge map. According to the calculation results of Chinese and English Translation Association similarity, using machine learning method combined with similarity function to detect semantic similarity, the accuracy of Chinese and English translation can be obtained. Experimental results show that, compared with the traditional detection methods, the detection accuracy and efficiency of the text method are significantly improved.