Semantic Accuracy and Cultural Adaptability in the English-Chinese Translation of Jane Eyre Based on Computational Linguistics and Natural Language Processing Techniques

Abstract

Abstract This paper takes Jane Eyre as an example to study the role of computational linguistics and natural language processing technology on the semantic accuracy and cultural adaptability of English-Chinese translation. We construct an interactive translation system of Jane Eyre, based on the interactive translation model design of computational linguistics and natural language processing technology, to support the application of these technologies in the English-Chinese translation of Jane Eyre. Context-association mapping, semantic retrieval, and semantic ontology structural feature construction methods are employed to evaluate semantic accuracy and cultural adaptability. We empirically analyze the semantic accuracy and cultural adaptability of the English-Chinese translation of Jane Eyre using text data from a Python web crawler. The results show that the semantic accuracy of the English-Chinese translation of Jane Eyre in this paper’s model is the highest compared to SAN (self-attention network) and RNN (recurrent neural network) translation models. Among the 200 students sampled, the translation result achieved a satisfaction rate of 71.5%. The work’s translation of literary sentences is more in line with the effect of Chinese expression, indicating excellent cultural adaptability.