A unified framework for phrase-based, hierarchical, and syntax-based statistical machine translation
Abstract
Despite many differences between phrase-based, hierarchical, and syntax-based translation models, their training and testing pipelines are strikingly similar. Drawing on this fact, we extend the Moses toolkit to implement hierarchical and syntactic models, making it the first open source toolkit with end-to-end support for all three of these popular models in a single package. This extension substantially lowers the barrier to entry for machine translation research across multiple models.- Anthology ID:
- 2009.iwslt-papers.4
- Volume:
- Proceedings of the 6th International Workshop on Spoken Language Translation: Papers
- Month:
- December 1-2
- Year:
- 2009
- Address:
- Tokyo, Japan
- Venue:
- IWSLT
- SIG:
- SIGSLT
- Publisher:
- Note:
- Pages:
- 152–159
- Language:
- URL:
- https://aclanthology.org/2009.iwslt-papers.4
- DOI:
- Cite (ACL):
- Hieu Hoang, Philipp Koehn, and Adam Lopez. 2009. A unified framework for phrase-based, hierarchical, and syntax-based statistical machine translation. In Proceedings of the 6th International Workshop on Spoken Language Translation: Papers, pages 152–159, Tokyo, Japan.
- Cite (Informal):
- A unified framework for phrase-based, hierarchical, and syntax-based statistical machine translation (Hoang et al., IWSLT 2009)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2009.iwslt-papers.4.pdf