Findings indicate that the proposed model translates English literary texts more accurately and aligns the translation more closely with Chinese literary style.
Abstract
This paper applied the Transformer model combined with the back-translation strategy module to the machine translation of English literary works. Simulation experiments compared the improved model traditional long short-term memory (LSTM) and Transformer models. The results showed that the improved model had a Bilingual Evaluation Understudy (BLEU) score of 49.9%, a Metric for Evaluation of Translation with Explicit ORdering (METEOR) score of 61.3%, a fluency score of 3.9, a translation accuracy score of 4.2, and a literary score of 4.6, respectively. These findings indicate that the proposed model translates English literary texts more accurately and aligns the translation more closely with Chinese literary style.
Recommendations for improving machine translation are provided, focusing on preserving semantic accuracy and cultural nuance in literary texts, showing that machine translation often fails to preserve semantic accuracy, especially with polysemous words or complex cultural contexts.
Nasiba Panjieva, Migena Arllati, A. Mambetniyazova et al.· Linguistic Frontiers· 0 citations
An English-to-target language translation model that integrates enhanced back-translation with translation memory is proposed, aiming to address the issues of low training efficiency, slow convergence, and weak domain adaptability in traditional machine translation models for English-to-multilingual tasks.
Yang Du· HighTech and Innovation Jour...· 0 citations
A statistical machine translation (SMT)-based phrase processing method that adds phrases in different suffix forms to the source-end sentences was proposed to improve translation quality and the results verify that the proposed method is reliable and can be applied in practice.
Danqiangyu Zhou· Journal of ICT Standardizati...· 0 citations
A Contrastive Learning-based Chinese-English Scientific Translation Quality Evaluation model (C-TQE), which provides an effective solution for large-scale scientific translation quality assessment and facilitates the accurate international communication of multidisciplinary engineering research, including electromagnet...
An English-to-target language translation model that integrates enhanced back-translation with translation memory is proposed, aiming to address the issues of low training efficiency, slow convergence, and weak domain adaptability in traditional machine translation models for English-to-multilingual tasks.
Yang Du· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
