北京大学学报（自然科学版）2018，Vol.54Issue(2)：279-285,7.DOI:10.13209/j.0479-8023.2017.158
基于伪数据的机器翻译质量估计模型的训练
Training Machine Translation Quality Estimation Model Based on Pseudo Data
摘要
Abstract
Aimed at providing efficient training data for neural translation quality estimation model, a pseudo data construction method for target dataset is proposed, the model is trained by two stage model training method: pre training based on pseudo data and fine tuning. The experimental design of different pseudo data scale is carried out. The experiment results show that the machine translation quality estimation model trained by the pseudo data has significantly improved in the correlation between the scores given by human and the artificial scores.关键词
机器翻译质量估计/深度学习/伪数据Key words
machine translation quality estimation/deep learning/pseudo data分类
信息技术与安全科学引用本文复制引用
吴焕钦,张红阳,李静梅,朱俊国,杨沐昀,李生..基于伪数据的机器翻译质量估计模型的训练[J].北京大学学报（自然科学版）,2018,54(2):279-285,7.基金项目
国家高技术研究发展计划(2015AA015405)和国家自然科学基金(61370170,61402134)资助 （2015AA015405）
