@inproceedings{jalota2023translating,
title = {Translating away Translationese without Parallel Data},
author = {Rricha Jalota and Koel Dutta Chowdhury and Cristina Espa{\~n}a-Bonet and Josef van Genabith},
editor = {Houda Bouamor and Juan Pino and Kalika Bali},
url = {https://aclanthology.org/2023.emnlp-main.438/},
doi = {https://doi.org/10.18653/v1/2023.emnlp-main.438},
year = {2023},
date = {2023},
booktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
pages = {7086-7100},
publisher = {Association for Computational Linguistics},
address = {Singapore},
abstract = {Translated texts exhibit systematic linguistic differences compared to original texts in the same language, and these differences are referred to as translationese. Translationese has effects on various cross-lingual natural language processing tasks, potentially leading to biased results. In this paper, we explore a novel approach to reduce translationese in translated texts: translation-based style transfer. As there are no parallel human-translated and original data in the same language, we use a self-supervised approach that can learn from comparable (rather than parallel) mono-lingual original and translated data. However, even this self-supervised approach requires some parallel data for validation. We show how we can eliminate the need for parallel validation data by combining the self-supervised loss with an unsupervised loss. This unsupervised loss leverages the original language model loss over the style-transferred output and a semantic similarity loss between the input and style-transferred output. We evaluate our approach in terms of original vs. translationese binary classification in addition to measuring content preservation and target-style fluency. The results show that our approach is able to reduce translationese classifier accuracy to a level of a random classifier after style transfer while adequately preserving the content and fluency in the target original style.},
pubstate = {published},
type = {inproceedings}
}