Improving Machine Translation Systems via Isotopic Replacement

Zeyu Sun, Jie M. Zhang, Yingfei Xiong, Mark Harman, Mike Papadakis, Lu Zhang

Abstract

Machine translation plays an essential role in people's daily international communication. However, machine translation systems are far from perfect. To tackle this problem, researchers have proposed several approaches to testing machine translation. A promising trend among these approaches is to use word replacement, where only one word in the original sentence is replaced with another word to form a sentence pair. However, precise control of the impact of word replacement remains an outstanding issue in these approaches.

BibTeX

@inproceedings{Sun-al:ICSE22,
  author    = {Zeyu Sun and
               Jie M. Zhang and
               Yingfei Xiong and
               Mark Harman and
               Mike Papadakis and
               Lu Zhang},
  title     = {Improving Machine Translation Systems via Isotopic Replacement},
  booktitle = {ICSE},
  pages     = {1181--1192},
  publisher = {{ACM}},
  year      = {2022},
}

Improving Machine Translation Systems via Isotopic Replacement

Abstract

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