Abstract
Phrase-based and hierarchical phrase-based (Hiero) translation models differ radically in the way reordering is modeled. Lexicalized reordering models play an important role in phrase-based MT and such models have been added to CKY-based decoders for Hiero. Watanabe et al. (2006) proposed a promising decoding algorithm for Hiero (LR-Hiero) that visits input spans in arbitrary order and produces the translation in left to right (LR) order which leads to far fewer language model calls and leads to a considerable speedup in decoding. We introduce a novel shift-reduce algorithm to LR-Hiero to decode with our lexicalized reordering model (LRM) and show that it improves translation quality for Czech-English, Chinese-English and German-English.- Anthology ID:
- E17-2097
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Mirella Lapata, Phil Blunsom, Alexander Koller
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 612–618
- Language:
- URL:
- https://aclanthology.org/E17-2097
- DOI:
- Cite (ACL):
- Maryam Siahbani and Anoop Sarkar. 2017. Lexicalized Reordering for Left-to-Right Hierarchical Phrase-based Translation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 612–618, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Lexicalized Reordering for Left-to-Right Hierarchical Phrase-based Translation (Siahbani & Sarkar, EACL 2017)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/E17-2097.pdf