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Explicit length modelling for statistical machine translation

descriptionPublicationkeyboard_double_arrow_right Article , Part of book or chapter of book 01 Jan 2011 Spain Publisher:Elsevier BVJournal:Pattern Recognition, volume 45, pages 3,183-3,192 (issn: 0031-3203,

Authors: Silvestre Cerdà, Joan Albert; Andrés Ferrer, Jesús; Civera Saiz, Jorge;

doi: 10.1016/j.patcog.2012.01.006 , 10.1007/978-3-642-21257-4_34

handle: 10251/34996 , 10251/35749

Explicit length modelling for statistical machine translation

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Abstract

[EN] Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods and two alternative parametrisations for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit bilingual length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, a systematic evaluation on reference SMT tasks considering different language pairs proves the benefits of explicit length modelling.

Work supported by the EC (FEDER/FSE) under the transLectures project (FP7-ICT-2011-7-287755) and the Spanish MEC/MICINN under the MIPRCV "Consolider Ingenio 2010" program (CSD2007-00018) and iTrans2 (TIN2009-14511) projects and FPU grant (AP2010-4349). Also supported by the Spanish MITyC under the erudito.com (TSI-020110-2009-439) project and by the Generalitat Valenciana under grants Prometeo/2009/014 and GV/2010/067, and by the UPV under the AdInTAO (20091027) project. The authors wish to thank the anonymous reviewers for their criticisms and suggestions.

Country

Spain

Related Organizations

Universitat Politècnica de València
Spain

Keywords

Statistical machine translation, Pattern recognition, Phrase-based models, ESTADISTICA E INVESTIGACION OPERATIVA, Log-linear models, LENGUAJES Y SISTEMAS INFORMATICOS, Length modelling

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