A unified framework for phrase-based, hierarchical, and syntax-based statistical machine translation

Hieu Hoang, Philipp Koehn, Adam Lopez


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:
Bibkey:
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)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2009.iwslt-papers.4.pdf
Presentation:
 2009.iwslt-papers.4.Presentation.pdf