Research on Correcting the Accuracy of English Translation Based on Improved Particle Swarm Optimization Algorithm

With the development of cognitive technology, replacing manual English translation(ET) with machines has gradually come into people's sight, and the accuracy of translation is also constantly improving. When computers and other machines are used to translate English content, it often happens that a word is translated incorrectly or the context is not smooth due to the improper recognition of the word content and context, which is one of the shortcomings of traditional machine ET. In order to improve the intelligence level of machine ET, this paper proposes a method of correcting the accuracy of machine ET based on particle swarm optimization (PSO), constructs an information extraction model of machine ET, selects the optimal solution of fuzzy semantics, and draws a valid conclusion. The results show that the accuracy and correction ability of the model can significantly eliminate errors in ET, and can effectively improve the accuracy and rationality of ET.