Identifying Computer-Translated Paragraphs using Coherence Features
Abstract
We have developed a method for extracting the coherence features from a paragraph by matching similar words in its sentences. We conducted an experiment with a parallel German corpus containing 2000 human-created and 2000 machine-translated paragraphs. The result showed that our method achieved the best performance (accuracy = 72.3%, equal error rate = 29.8%) when it is compared with previous methods on various computer-generated text including translation and paper generation (best accuracy = 67.9%, equal error rate = 32.0%). Experiments on Dutch, another rich resource language, and a low resource one (Japanese) attained similar performances. It demonstrated the efficiency of the coherence features at distinguishing computer-translated from human-created paragraphs on diverse languages.
Keywords
Cite
@article{arxiv.1812.10896,
title = {Identifying Computer-Translated Paragraphs using Coherence Features},
author = {Hoang-Quoc Nguyen-Son and Ngoc-Dung T. Tieu and Huy H. Nguyen and Junichi Yamagishi and Isao Echizen},
journal= {arXiv preprint arXiv:1812.10896},
year = {2018}
}
Comments
9 pages, PACLIC 2018