Three generative, lexicalised models for statistical parsing
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Minimum error rate training in statistical machine translation
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Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Clause restructuring for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Arabic tokenization, part-of-speech tagging and morphological disambiguation in one fell swoop
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Improving a statistical MT system with automatically learned rewrite patterns
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Segmentation for English-to-Arabic statistical machine translation
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Morphological analysis for statistical machine translation
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Arabic preprocessing schemes for statistical machine translation
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Joint morphological-lexical language modeling for machine translation
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
A word reordering model for improved machine translation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Post-Ordering by Parsing with ITG for Japanese-English Statistical Machine Translation
ACM Transactions on Asian Language Information Processing (TALIP)
Statistical machine translation enhancements through linguistic levels: A survey
ACM Computing Surveys (CSUR)
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Syntactic Reordering of the source language to better match the phrase structure of the target language has been shown to improve the performance of phrase-based Statistical Machine Translation. This paper applies syntactic reordering to English-to-Arabic translation. It introduces reordering rules, and motivates them linguistically. It also studies the effect of combining reordering with Arabic morphological segmentation, a preprocessing technique that has been shown to improve Arabic-English and English-Arabic translation. We report on results in the news text domain, the UN text domain and in the spoken travel domain.