一句话：提出用蜕变测试评估机器翻译术语翻译，摆脱对参考译文和双语词典的依赖。
机器翻译已融入日常生活，术语翻译的准确性对翻译结果至关重要。然而，Google Translate 等现有系统仍会偶尔出现术语翻译错误；当前术语翻译评估指标依赖参考译文和双语词典，难以支持大规模自动化 MT 系统测试。该论文研究如何通过蜕变测试（metamorphic testing）评估机器翻译系统中的术语翻译。方法上，它利用蜕变关系来构造测试或判定译文应满足的变换，从而在缺少参考译文和双语词典时检测术语翻译错误。摘要未给出具体实验结果，但核心贡献在于提出面向术语翻译的不依赖参考的大规模自动化测试思路。
Machine translation has become an integral part of daily life, with terminology translation playing a crucial role in ensuring the accuracy of translation results. However, existing translation systems, such as Google Translate, have been shown to occasionally produce errors in terminology translation. Current metrics for assessing terminology translation rely on reference translations and bilingual dictionaries, limiting their effectiveness in large-scale automated MT system testing.
DOI 原文 ·
@inproceedings{paperbot8360,
title = {Evaluating Terminology Translation in Machine Translation Systems via Metamorphic Testing},
author = {Yihui Xu and Yanhui Li and Jun Wang and Xiaofang Zhang},
booktitle = {ASE},
year = {2024},
doi = {10.1145/3691620.3695069}
}