TY - CONF T1 - A maximum entropy approach to combining word alignments T2 - Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics Y1 - 2006 A1 - Ayan,Necip Fazil A1 - Dorr, Bonnie J AB - This paper presents a new approach to combining outputs of existing word alignment systems. Each alignment link is represented with a set of feature functions extracted from linguistic features and input alignments. These features are used as the basis of alignment decisions made by a maximum entropy approach. The learning method has been evaluated on three language pairs, yielding significant improvements over input alignments and three heuristic combination methods. The impact of word alignment on MT quality is investigated, using a phrase-based MT system. JA - Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics T3 - HLT-NAACL '06 PB - Association for Computational Linguistics CY - Stroudsburg, PA, USA UR - http://dx.doi.org/10.3115/1220835.1220848 M3 - 10.3115/1220835.1220848 ER -