刘婉婉,苏依拉,乌尼尔,仁庆道尔吉. 基于门控循环神经网络词性标注的蒙汉机器翻译研究[J]. 中文信息学报, 2018, 32(8): 68-74.
LIU Wanwan, SU Yila, Wunier, Renqingdaoerji. Mongolian-Chinese Machine Translation Research Based on Part of Speech Tagging with Gated Unit Neural Network. , 2018, 32(8): 68-74.
基于门控循环神经网络词性标注的蒙汉机器翻译研究
刘婉婉,苏依拉,乌尼尔,仁庆道尔吉
内蒙古工业大学 信息工程学院, 内蒙古 呼和浩特 010080
Mongolian-Chinese Machine Translation Research Based on Part of Speech Tagging with Gated Unit Neural Network
LIU Wanwan, SU Yila, Wunier, Renqingdaoerji
Inner Mongolia University of Technology, College of Information Engineering, Hohhot, Inner Mongolia 010080, China
Abstract：Statistics machine translation may be able to predict a relatively accurate target word with statistical analysis method, but it cannot get a much better translation as it couldn’t fully understand the original semantic relations. To address this problem, the model of Mongolian-Chinese machine translation system is constructed using gated unit recurrent neural network structure, and introduce the global attention mechanism to obtain bilingual alignment information. In the process of constructing a dictionary, the bilingual words are annotated to strengthen the semantics, alleviating the problem caused by erroneous training. The research result shows that the BLEU value is certainly promoted and improved compared with previous benchmark research and traditional statistical machine translation method.
2018, Vol. 32 
