Neural Machine Translation with Extended Context

Jörg Tiedemann, Yves Scherrer


Abstract
We investigate the use of extended context in attention-based neural machine translation. We base our experiments on translated movie subtitles and discuss the effect of increasing the segments beyond single translation units. We study the use of extended source language context as well as bilingual context extensions. The models learn to distinguish between information from different segments and are surprisingly robust with respect to translation quality. In this pilot study, we observe interesting cross-sentential attention patterns that improve textual coherence in translation at least in some selected cases.
Anthology ID:
W17-4811
Volume:
Proceedings of the Third Workshop on Discourse in Machine Translation
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Venues:
DiscoMT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
82–92
Language:
URL:
https://www.aclweb.org/anthology/W17-4811
DOI:
10.18653/v1/W17-4811
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-4811.pdf