Abstract
We explore six challenges for neural machine translation: domain mismatch, amount of training data, rare words, long sentences, word alignment, and beam search. We show both deficiencies and improvements over the quality of phrase-based statistical machine translation.- Anthology ID:
- W17-3204
- Volume:
- Proceedings of the First Workshop on Neural Machine Translation
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver
- Editors:
- Thang Luong, Alexandra Birch, Graham Neubig, Andrew Finch
- Venue:
- NGT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 28–39
- Language:
- URL:
- https://aclanthology.org/W17-3204
- DOI:
- 10.18653/v1/W17-3204
- Cite (ACL):
- Philipp Koehn and Rebecca Knowles. 2017. Six Challenges for Neural Machine Translation. In Proceedings of the First Workshop on Neural Machine Translation, pages 28–39, Vancouver. Association for Computational Linguistics.
- Cite (Informal):
- Six Challenges for Neural Machine Translation (Koehn & Knowles, NGT 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/W17-3204.pdf