Multi-Domain Adaptation and Optimization of English Translation Based on Cross-Language Transfer Learning

Adaptive research in many fields of English translation plays an important role in improving the quality of translation. In this paper, traditional English translation adaptation methods are compared with cross-language transfer learning (CLTL) algorithms, and their performance in terms of translation quality and translation stability is evaluated. It optimizes a multi-domain adaptation approach to English translation based on CLTL. The experimental results show that the method based on CLTL is superior to the traditional method in terms of TER, BLEU value and stability. The results of this study validate the superiority of the approach based on CLTL in the multi-domain adaptation of English translation. The study of this paper provided a useful reference and inspiration for the research and practice of English translation.