Research on Intelligent Translation System Based on Deep Learning
Rui Feng Sun, Lihua Luo, Mengsha Kong, Yong Zhong · 2019
Based on the new generation of artificial intelligence theory, such as deep learning, this paper proposed an intelligent translation model based on bidirectional long short-term memory model and attention mechanism. By training deep recurrent neural network, the encoder-decoder framework significantly improves the translation accuracy and system stability, and significantly reduces the training time compared with the traditional statistical machine translation model. Meanwhile, it will also improve the robustness of the intelligent translation system and solve problems such as the lack of training corpus for small language.