The GREYC/LLACAN Machine Translation Systems for the IWSLT 2010 Campaign

Julien Gosme, Wigdan Mekki, Fathi Debili, Yves Lepage, Nadine Lucas

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

In this paper we explore the contribution of the use of two Arabic morphological analyzers as preprocessing tools for statistical machine translation. Similar investigations have already been reported for morphologically rich languages like German, Turkish and Arabic. Here, we focus on the case of the Arabic language and mainly discuss the use of the G-LexAr analyzer. A preliminary experiment has been designed to choose the most promising translation system among the 3 G-LexAr-based systems, we concluded that the systems are equivalent. Nevertheless, we decided to use the lemmatized output of G-LexAr and use its translations as primary run for the BTEC AE track. The results showed that G-LexAr outputs degrades translation compared to the basic SMT system trained on the un-analyzed corpus.

Original languageEnglish
Pages59-65
Number of pages7
Publication statusPublished - 2010
Event7th International Workshop on Spoken Language Translation, IWSLT 2010 - Paris, France
Duration: 2010 Dec 22010 Dec 3

Conference

Conference7th International Workshop on Spoken Language Translation, IWSLT 2010
Country/TerritoryFrance
CityParis
Period10/12/210/12/3

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Linguistics and Language

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