Abstract
Aiming at the disadvantages of the traditional rule-based machine translation model that the English translation results are not accurate enough and it is difficult to accurately describe the relationship between words, the English machine translation model based on the semantic network is designed and improved. The algorithm analyses the English grammatical rules, then performs Gaussian marginalization on the semantics to obtain the rectangular window function, obtains the window feature vector, projects the semantic information entropy data, and adds the semantic correlation factors to the information entropy and information gain of the text., So as to obtain the semantic nonlinear spectral characteristics. Experimental results show that the designed English machine translation model has high translation accuracy and stability.
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