Machine Translation Evaluation and Optimization
msra(2011)
摘要
The evaluation of machine translation (MT) systems is a vital field of research, both for determining the effectiveness of
existing MT systems and for optimizing the performance of MT systems. This part describes a range of different evaluation
approaches used in the GALE community and introduces evaluation protocols and methodologies used in the program. We discuss
the development and use of automatic, human, task-based and semi-automatic (human-in-the-loop) methods of evaluating machine
translation, focusing on the use of a human-mediated translation error rate HTER as the evaluation standard used in GALE.
We discuss the workflow associated with the use of this measure, including post editing, quality control, and scoring. We
document the evaluation tasks, data, protocols, and results of recent GALE MT Evaluations. In addition, we present a range
of different approaches for optimizing MT systems on the basis of different measures. We outline the requirements and specific
problems when using different optimization approaches and describe how the characteristics of different MT metrics affect
the optimization. Finally, we describe novel recent and ongoing work on the development of fully automatic MT evaluation metrics
that have the potential to substantially improve the effectiveness of evaluation and optimization of MT systems.
更多查看译文
关键词
error rate,machine translation,quality control
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要