MT Goes Farming: Comparing Two Machine Translation Approaches on a New Domain

نویسندگان

  • Per Weijnitz
  • Eva Forsbom
  • Ebba Gustavii
  • Eva Pettersson
  • Jörg Tiedemann
چکیده

In the paper we present detailed analyses of two machine translation systems when applied to documents of a previously unseen domain: agricultural texts from the European Union. The two systems compared are a statistical machine translation (SMT) system using the freely available ISI ReWrite Decoder (Germann, 2003a), and the rule-based machine translation system MATS (Sågvall Hein et al., 2002). For the purpose of comparison we use a sentence-aligned Swedish-English corpus of approximately 75,000 words per language, where 90% are used for training and 10% are used for evaluation. In the paper we discuss the outcome of automatic evaluation and the results of our manual quality assessment.

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تاریخ انتشار 2004