@inproceedings{eriguchi2019combining,
author = {Eriguchi, Akiko and Rarrick, Spencer and Matsushita, Hitokazu},
title = {Combining Translation Memory with Neural Machine Translation},
booktitle = {WAT 2019 (The 6th Workshop on Asian Translation)},
year = {2019},
month = {November},
abstract = {In this paper, we report our submission systems (geoduck) to the Timely Disclosure task on the 6th Workshop on Asian Translation (WAT) (Nakazawa et al., 2019). Our system employs a combined approach of translation memory and Neural Machine Translation (NMT) models, where we can select final translation outputs from either a translation memory or an NMT system, when the similarity score of a test source sentence exceeds the predefined threshold. We observed that this combination approach significantly improves the translation performance on the Timely Disclosure corpus, as compared to a standalone NMT system. We also conducted source-based direct assessment on the final output, and we discuss the comparison between human references and each system’s output.},
publisher = {Association for Computational Linguistics},
url = {http://approjects.co.za/?big=en-us/research/publication/combining-translation-memory-with-neural-machine-translation/},
pages = {123-130},
}