Research on Machine Translation Method of English-Chinese Long Sentences Based on Fuzzy Semantic Optimization

Abstract

The machine translation of English-Chinese long sentences is out of order under the constraint of the mixed corpus. In order to improve the accuracy of machine translation of English-Chinese long sentences, a machine translation method based on fuzzy semantic optimization is proposed. By adopting the method of systematic semantic configuration structure fusion, the ontology mapping model of the English-Chinese long sentence subject list under the constraint of the mixed corpus is constructed. In the distribution structure space of English-Chinese long sentences under the constraint of the mixed corpus, the method of extracting the best semantic relevance and analyzing the concept tree of context semantic mapping is adopted to mine the dynamic features of the subject list of English-Chinese long sentence translation under the constraint of the mixed corpus. In the intrinsic distribution sequence of semantic mapping between concepts, the fuzzy semantic combination features of English-Chinese long sentences under the constraint of the mixed corpus are extracted. The distribution results of word knowledge priority selection sequence, the automatic translation of English-Chinese long sentences under the constraint of the mixed corpus is realized by scheduling a grammatical error correction task list. According to the simulation results, machine translation of long English-Chinese sentences under the restriction of mixed corpora is capable of good semantic configuration. The degree of linguistic structural similarity between English and Chinese is great, which enhances the automatic translation capacity of English-Chinese long sentences under the limitation of the mixed corpus.