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
- Editors:
- Bonnie Webber, Andrei Popescu-Belis, Jörg Tiedemann
- Venue:
- DiscoMT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 82–92
- Language:
- URL:
- https://aclanthology.org/W17-4811
- DOI:
- 10.18653/v1/W17-4811
- Cite (ACL):
- Jörg Tiedemann and Yves Scherrer. 2017. Neural Machine Translation with Extended Context. In Proceedings of the Third Workshop on Discourse in Machine Translation, pages 82–92, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Neural Machine Translation with Extended Context (Tiedemann & Scherrer, DiscoMT 2017)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/W17-4811.pdf