A Study on the Linguistic Adaptation of Language Modeling Techniques in Translating British Victorian Literature

This paper discusses the application of the neural machine translation model based on language modeling technology in British Victorian literature and its linguistic adaptation.Firstly, the linguistic features of Victorian literary works are analyzed, including thematic content and social background.Then the neural machine translation model based on language modeling technology is designed, and the text style migration method based on style representation is proposed to reproduce the linguistic features of the literary works.The performance of the translation models under the three fusion style methods is compared with five baseline systems, and the BLEU value, style migration accuracy, and style migration fluency of the machine translation model using the text migration decoding module are 37.49, 0.978, and 3.59, respectively, which are all higher than those of other models.Taking the translation of Wuthering Heights as an example, there is not much difference between this model and the human translation in terms of language adaptation evaluation.It shows that the machine translation model designed based on language modeling technology in this paper has better language adaptability for translating Victorian literature.