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  • 51. Webber, Bonnie
    et al.
    Popescu-Belis, AndreiMarkert, KatjaTiedemann, JörgUppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Proceedings of the Workshop on Discourse in Machine Translation2013Conference proceedings (editor) (Other academic)
  • 52.
    Weijnitz, Per
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Forsbom, Eva
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Gustavii, Ebba
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Pettersson, Eva
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Tiedemann, Jörg
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    MT goes farming: comparing two machine translation approaches on a new domain2004In: Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC'04): Lisbon, Portugal, Paris, France: ELRA - European Language Resources Association , 2004, p. 2043-2046Conference paper (Refereed)
    Abstract [en]

    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 evaluation 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.

  • 53. Zampieri, Marcos
    et al.
    Ljubešić, Nikola
    Tiedemann, Jörg
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Merging Comparable Data Sources for the Discrimination of Similar Languages: The DSL Corpus Collection2014In: Proceedings of the 7th Workshop on Building and Using Comparable Corpora Building Resources for Machine Translation Research, 2014, p. 6-10Conference paper (Refereed)
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