Algorithm Design of Translation Accuracy Correction for English Translation Softwares

Abstract

With the development of economic globalization, English is needed in more and more different cases in people’s daily life, and so is English translation. Traditional English software translation mainly depends on machine, which on the one hand facilitates people’s life, while on the other hand it also has some disadvantages. For example, translation errors are characterized by iterative transmission, weak logic and low accuracy. Traditional machine translation has been unable to meet people’s demand for both speed and quality, so it can no longer meet people’s needs. Therefore, this paper puts forward the design of translation accuracy correction algorithm for English translation softwares. First of all, an in-depth research on the traditional English translation methods, such as lexical semantic translation and phrase translation, are conducted with the method of documentation. Then, a dependency tree to string model and log linear model are established. Finally, the BLEU value and NIST value of the three translation softwares as well as the translation accuracy before and after algorithm correction is compared and analyzed. The conclusion shows that the highest accuracy of English translation before correction is only 75.6%, while the lowest accuracy is as high as 98.7% after the algorithm is adopted in this paper. The difference of accuracy between the two shows that the effectiveness of the correction system in this paper makes an outstanding contribution.

An Intelligent Recognition of English Translation Based on Improved GLR Algorithm

“…Conflict phenomenon analysis in the analysis table is commonly used in machine translation principles. e GLR has three parts: the analysis state table, the grammar rules, and the list of graph structures [15].…”