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Non-projective parsing for statistical machine translation

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Jan 2009 Spain, United States Publisher:Association for Computational Linguistics (ACL)Journal:Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 1 - EMNLP '09, volume 1, page 200

Authors: Carreras Perez, Xavier; Collins, Michael;

doi: 10.3115/1699510.1699537

handle: 2117/9813 , 1721.1/59365

Non-projective parsing for statistical machine translation

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Abstract

We describe a novel approach for syntaxbased statistical MT, which builds on a variant of tree adjoining grammar (TAG). Inspired by work in discriminative dependency parsing, the key idea in our approach is to allow highly flexible reordering operations during parsing, in combination with a discriminative model that can condition on rich features of the sourcelanguage string. Experiments on translation from German to English show improvements over phrase-based systems, both in terms of BLEU scores and in human evaluations.

Peer Reviewed

Countries

Spain, United States

Related Organizations

Massachusetts Institute of Technology
United States
Universitat Polite`cnica de Catalunya
Spain

Keywords

Computational linguistics, Lingüística computacional, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural, :Informàtica::Intel·ligència artificial::Llenguatge natural [Àrees temàtiques de la UPC]

Impact byBIP!

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	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average