@inproceedings{d7e86c5695974768becb98bbd13be1a8,
title = "Sentence level dialect identification for machine translation system selection",
abstract = "In this paper we study the use of sentence-level dialect identification in optimizing machine translation system selection when translating mixed dialect input. We test our approach on Arabic, a prototypical diglossic language; and we optimize the combination of four different machine translation systems. Our best result improves over the best single MT system baseline by 1.0% BLEU and over a strong system selection baseline by 0.6% BLEU on a blind test set.",
author = "Wael Salloum and Heba Elfardy and Linda Alamir-Salloum and Nizar Habash and Mona Diab",
year = "2014",
doi = "10.3115/v1/p14-2125",
language = "English (US)",
isbn = "9781937284732",
series = "52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "772--778",
booktitle = "Long Papers",
note = "52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 ; Conference date: 22-06-2014 Through 27-06-2014",
}