论文标题

重新思考机器翻译评估的往返翻译

Rethinking Round-Trip Translation for Machine Translation Evaluation

论文作者

Zhuo, Terry Yue, Xu, Qiongkai, He, Xuanli, Cohn, Trevor

论文摘要

对低资源语言翻译的自动评估患有平行语料库的缺陷。往返翻译可以用作一种巧妙而直接的技术,以减轻并行评估语料库的要求。但是,在统计机器翻译时代(SMT)时,通过向前和往返翻译进行评估得分之间的晦涩的相关性。在本文中,我们报告了令人惊讶的发现,即无需参考即可将往返翻译用于自动评估。首先,我们对SMT评估中的往返翻译进行了重新访问,即其长期存在的误解本质上是由复制机制引起的。删除SMT中的复制机制后,往返翻译分数可以适当反映前向翻译性能。然后,我们证明了纠正的逾期,因为往返翻译可以使多个机器翻译评估任务受益。更具体的是,可以使用往返翻译i)预测相应的正向翻译得分; ii)提高最近高级质量估计模型的性能; iii)通过跨系统验证在共享任务中确定对抗性竞争对手。

Automatic evaluation on low-resource language translation suffers from a deficiency of parallel corpora. Round-trip translation could be served as a clever and straightforward technique to alleviate the requirement of the parallel evaluation corpus. However, there was an observation of obscure correlations between the evaluation scores by forward and round-trip translations in the era of statistical machine translation (SMT). In this paper, we report the surprising finding that round-trip translation can be used for automatic evaluation without the references. Firstly, our revisit on the round-trip translation in SMT evaluation unveils that its long-standing misunderstanding is essentially caused by copying mechanism. After removing copying mechanism in SMT, round-trip translation scores can appropriately reflect the forward translation performance. Then, we demonstrate the rectification is overdue as round-trip translation could benefit multiple machine translation evaluation tasks. To be more specific, round-trip translation could be used i) to predict corresponding forward translation scores; ii) to improve the performance of the recently advanced quality estimation model; and iii) to identify adversarial competitors in shared tasks via cross-system verification.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源