Bilingual Synchronization: Restoring Translational Relationships with Editing Operations
Jitao Xu, Josep Crego, François Yvon
Abstract
Machine Translation (MT) is usually viewed as a one-shot process that generates the target language equivalent of some source text from scratch. We consider here a more general setting which assumes an initial target sequence, that must be transformed into a valid translation of the source, thereby restoring parallelism between source and target. For this bilingual synchronization task, we consider several architectures (both autoregressive and non-autoregressive) and training regimes, and experiment with multiple practical settings such as simulated interactive MT, translating with Translation Memory (TM) and TM cleaning. Our results suggest that one single generic edit-based system, once fine-tuned, can compare with, or even outperform, dedicated systems specifically trained for these tasks.
BibTeX
@inproceedings{xu-etal-2022-bilingual,
title = "Bilingual Synchronization: Restoring Translational Relationships with Editing Operations",
author = "Xu, Jitao and
Crego, Josep and
Yvon, Fran{\c{c}}ois",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.548/",
doi = "10.18653/v1/2022.emnlp-main.548",
pages = "8016--8030"
}