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    <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.</abstract>
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%0 Conference Proceedings
%T MorphTagger: HMM-based Arabic segmentation for statistical machine translation
%A Mansour, Saab
%S Proceedings of the 7th International Workshop on Spoken Language Translation: Papers
%D 2010
%8 dec 2 3
%C Paris, France
%F mansour-2010-morphtagger
%X 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.
%U https://aclanthology.org/2010.iwslt-papers.15
%P 321-327

Markdown (Informal)

[MorphTagger: HMM-based Arabic segmentation for statistical machine translation](https://aclanthology.org/2010.iwslt-papers.15) (Mansour, IWSLT 2010)

• MorphTagger: HMM-based Arabic segmentation for statistical machine translation (Mansour, IWSLT 2010)

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.