Using POS information for statistical machine translation into morphologically rich languages

DOIResolve DOI: http://doi.org/10.3115/1067807.1067853
AuthorSearch for: ; Search for:
TypeArticle
Proceedings titleProceedings of the Tenth Conference on European Chapter of the Association for Computational Linguistics
Conference10th Conference on European Chapter of the Association for Computational Linguistics, April 12-17, 2003, Budapest, Hungary
ISBN1-333-56789-0
Pages347354; # of pages: 8
AbstractWhen translating from languages with hardly any inflectional morphology like English into morphologically rich languages, the English word forms often do not contain enough information for producing the correct fullform in the target language. We investigate methods for improving the quality of such translations by making use of part-of-speech information and maximum entropy modeling. Results for translations from English into Spanish and Catalan are presented on the LC-STAR corpus which consists of spontaneously spoken dialogues in the domain of appointment scheduling and travel planning.
LanguageEnglish
Peer reviewedYes
NPARC number21275290
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Record identifierc4fa6a53-71e3-447a-b143-6a36c380eeeb
Record created2015-06-01
Record modified2016-05-09
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