Research on Intelligent Construction of Bilingual Translation Corpus Based on Differential Evolution Algorithm

In the construction stage of bilingual translation corpus, due to the lack of analysis of the relationship between the basic corpora, the translation quality is low. Therefore, a research on intelligent construction of bilingual translation corpus based on differential evolution algorithm is proposed. The differential evolution algorithm is used to optimize the reverse learning of bilingual translation corpus, improve the quality of natural language corpus, and expand the search area of corpus to complement the global exploration ability of bilingual translation corpus. The method of random neighborhood variation is used to extract bilingual sentence pairs. From the perspective of diversity to ensure the quality of natural language corpus, the method of adaptive updating is used to establish the relationship between the basic corpus through differentiated neighborhood size and scaling factors, and to extract bilingual sentence pairs.In this test, the translation quality of the designed bilingual translation corpus pair and the sentence level and text level test data is at a high level.