Izvorni znanstveni članak

https://doi.org/10.17559/TV-20221222092039

A Generative Adversarial Networks Based Approach for Literary Translation

Fangming Gong ; The College of Chinese Language and Literature, School of Foreign Languages, Hunan University, Lushan Gate, Lushan South Road, Yuelu District, Changsha City, Hunan Province, China, 410082

Sažetak

This study aims to solve the problem of mistranslation due to the fact that literary intelligent translation only stays at the stage of text description and elaboration and lacks relevant facts. Therefore, this paper puts forward an improvement method of literary intelligent translation text based on generation confrontation network. First, an adaptive literary intelligent translation mode is designed under the generation confrontation network, and then the data of literary intelligent translation text improvement is preprocessed, and the data mining of text improvement quality evaluation is carried out. According to the mining results, a literary intelligent translation text improvement quality evaluation model is constructed to evaluate the quality of literary intelligent translation text improvement. According to the quality results, this paper constructs the improvement model of literary intelligent translation text, designs the improvement process, and completes the research on the improvement method of literary intelligent translation text that generates confrontation network. The experimental results show that this method has better detection effect of mistranslation features, better stability of the improved method, accurate and reliable results, and can improve the literary literacy of students and teachers.

Ključne riječi

data mining; generate confrontation network; intelligent translation of literature; literary literacy; text improvement methods

Hrčak ID:

300703

URI

https://hrcak.srce.hr/300703

Datum izdavanja:

23.4.2023.

Posjeta: 856 *