机器翻译译文质量估计综述

机器翻译译文质量估计(Quality Estimation,QE)是指在不需要人工参考译文的条件下,估计机器翻译系统产生的译文的质量,对机器翻译研究和应用具有很重要的价值。机器翻译译文质量估计经过最近几年的发展,取得了丰富的研究成果。该文首先介绍了机器翻译译文质量估计的背景与意义;然后详细介绍了句子级QE、单词级QE、文档级QE的具体任务目标、评价指标等内容,进一步概括了QE方法发展的三个阶段: 基于特征工程和机器学习的QE方法阶段,基于深度学习的QE方法阶段,融入预训练模型的QE方法阶段,并介绍了每一阶段中的代表性研究工作;最后分析了目前的研究现状及不足,并对未来QE方法的研究及发展方向进行了展望。

A Survey on Machine Translation Quality Estimation

Machine translation quality estimation refers to the estimation of the quality of the outputs by machine translation system without the human reference translations. It is of great value to the research and application of machine translation. In this survey, we firstly introduce the background and significance of machine translation quality estimation. Then we introduce in detail the specific task objectives and evaluation indicators of word-level QE, sentence-level QE, and document-level QE. We further summarize the development of QE methods to three main stage: methods based on feature engineering and machine learning, methods based on deep learning, and methods integrated with pre-training model. Representative research works in each stage are introduced, and the current research status and shortcomings are analyzed. Finally, we outline the outlook for the future research and development of QE.