MorphTagger: HMM-based Arabic segmentation for statistical machine translation

Saab Mansour


Abstract
In this paper, we investigate different methodologies of Arabic segmentation for statistical machine translation by comparing a rule-based segmenter to different statistically-based segmenters. We also present a new method for segmentation that serves the need for a real-time translation system without impairing the translation accuracy.
Anthology ID:
2010.iwslt-papers.15
Volume:
Proceedings of the 7th International Workshop on Spoken Language Translation: Papers
Month:
December 2-3
Year:
2010
Address:
Paris, France
Venue:
IWSLT
SIG:
Publisher:
Note:
Pages:
321–327
Language:
URL:
https://aclanthology.org/2010.iwslt-papers.15
DOI:
Bibkey:
Cite (ACL):
Saab Mansour. 2010. MorphTagger: HMM-based Arabic segmentation for statistical machine translation. In Proceedings of the 7th International Workshop on Spoken Language Translation: Papers, pages 321–327, Paris, France.
Cite (Informal):
MorphTagger: HMM-based Arabic segmentation for statistical machine translation (Mansour, IWSLT 2010)
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PDF:
https://preview.aclanthology.org/update-css-js/2010.iwslt-papers.15.pdf