The UN Parallel Corpus Annotated for Translation Direction
Computation and Language
2018-05-22 v1
Abstract
This work distinguishes between translated and original text in the UN protocol corpus. By modeling the problem as classification problem, we can achieve up to 95% classification accuracy. We begin by deriving a parallel corpus for different language-pairs annotated for translation direction, and then classify the data by using various feature extraction methods. We compare the different methods as well as the ability to distinguish between translated and original texts in the different languages. The annotated corpus is publicly available.
Keywords
Cite
@article{arxiv.1805.07697,
title = {The UN Parallel Corpus Annotated for Translation Direction},
author = {Elad Tolochinsky and Ohad Mosafi and Ella Rabinovich and Shuly Wintner},
journal= {arXiv preprint arXiv:1805.07697},
year = {2018}
}