Word-Level Nonequivalence and Translation Strategies in English–Chinese Translation Based on Image Processing Technology

Abstract

The process of translation is the process of accurately understanding the original work. It uses other languages to express the meaning of the original work and reproduce the original text in other languages. However, translation equivalence is a relative term, and there is no complete equivalence. In translation practice, translators often face different inequalities. The inequality of lexical levels means that no words matching the original text can be found in the specified language. These equivalence relationships are different to some extent, which brings great difficulties to translation. This paper first made a relevant interpretation of the common phenomenon of word-level inequality in English–Chinese translation, and analyzed the differences of source language concepts in translation. It made a relevant study on the lexical inequality in English–Chinese translation, and described the cultural inequality. After that, this paper studied and planned the equivalence requirements and solutions in English–Chinese translation. It was proposed to strengthen the learning and understanding of Chinese and Western cultures, and to translate based on the cultural characteristics of different regions. It was also proposed that transliteration should be used to ensure the accuracy of English–Chinese translation and reduce the nonequivalence between word levels. Subsequently, this paper introduced image processing technology into translation and used image processing technology to strengthen translation strategies. It also focused on analyzing the main types of image processing technology and used image processing technology to fully understand the translation process. It was necessary to use image processing technology to correctly express the translation. Finally, image processing technology was used to strengthen translation strategies and research. According to experiments and surveys, the use of image processing technology to create new English–Chinese translation strategies could effectively improve the satisfaction of 18% of translators.