A Design of Interactive Online English Translation System Based on Deep Learning

Abstract

In order to overcome the low translation speed and accuracy of traditional online English translation system, this paper proposes a new interactive English translation system based on deep learning. Based on B/S architecture, a three-tier system architecture is designed. The hardware part of the system includes corpus preprocessing module, English morphology classification module and interactive online translation service module to improve the performance of the system. In the software part of the system, the two-way long-term and short-term memory network of deep learning technology is used to extract features of English translation data, so as to improve the accuracy of translation. The experimental results show that, compared with the existing translation system, the translation speed and accuracy of the designed system are effectively improved, so the practical application performance of the designed system is strong.