Abstract
System architecture, experimental settings and experimental results of the EHR team for the WAT2017 tasks are described. We participate in three tasks: JPCen-ja, JPCzh-ja and JPCko-ja. Although the basic architecture of our system is NMT, reranking technique is conducted using SMT results. One of the major drawback of NMT is under-translation and over-translation. On the other hand, SMT infrequently makes such translations. So, using reranking of n-best NMT outputs by the SMT output, discarding such translations can be expected. We can improve BLEU score from 46.03 to 47.08 by this technique in JPCzh-ja task.- Anthology ID:
- W17-5710
- Volume:
- Proceedings of the 4th Workshop on Asian Translation (WAT2017)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Toshiaki Nakazawa, Isao Goto
- Venue:
- WAT
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 119–126
- Language:
- URL:
- https://aclanthology.org/W17-5710
- DOI:
- Cite (ACL):
- Terumasa Ehara. 2017. SMT reranked NMT. In Proceedings of the 4th Workshop on Asian Translation (WAT2017), pages 119–126, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- SMT reranked NMT (Ehara, WAT 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-5710.pdf