Search Results - "cada, Mikel L"

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  1. 1

    Fuzzy-Match Repair Guided by Quality Estimation by Ortega, John E., Forcada, Mikel L., Sanchez-Martinez, Felipe

    “…Computer-aided translation tools based on translation memories are widely used to assist professional translators. A translation memory (TM) consists of a set…”
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    Journal Article
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    Apertium: a free/open-source platform for rule-based machine translation by Forcada, Mikel L., Ginestí-Rosell, Mireia, Nordfalk, Jacob, O'Regan, Jim, Ortiz-Rojas, Sergio, Pérez-Ortiz, Juan Antonio, Sánchez-Martínez, Felipe, Ramírez-Sánchez, Gema, Tyers, Francis M.

    Published in Machine translation (01-06-2011)
    “…Apertium is a free/open-source platform for rule-based machine translation. It is being widely used to build machine translation systems for a variety of…”
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    Journal Article
  4. 4

    Using Machine Translation to Provide Target-Language Edit Hints in Computer Aided Translation Based on Translation Memories by Esplà-Gomis, Miquel, Sánchez-Martínez, Felipe, Forcada, Mikel L.

    “…This paper explores the use of general-purpose machine translation (MT) in assisting the users of computer-aided translation (CAT) systems based on translation…”
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    CONSTRUIR SISTEMES DE TRADUCCIÓ AUTOMÀTICA PER A LLENGÜES MENORS: REPTES I EFECTES by cada, Mikel L

    Published in Revista de llengua i dret (01-06-2020)
    “…La creació de sistemes de traducció automàtica per a llengües desfavorides, que anomenaré llengües menors, presenta diversos reptes alhora que obri la porta a…”
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    Journal Article
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    Apertium: Automatic Translation with Open-Source Software for Romance Languages by cada, Mikel L

    Published in Linguamática (Braga, Portugal) (01-01-2009)
    “…After defining automatic translation & explaining its chief advantages, the concept of open-source software & its application in automatic translation programs…”
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    Journal Article
  9. 9

    Stand-off Annotation of Web Content as a Legally Safer Alternative to Crawling for Distribution by cada, Mikel L, Esplà-Gomis, Miquel, Pérez-Ortiz, Juan Antonio

    Published in Baltic Journal of Modern Computing (01-01-2016)
    “…Sentence-aligned web-crawled parallel text or bitext is frequently used to train statistical machine translation systems. To that end, web-crawled…”
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    Journal Article
  10. 10

    Free/open-source machine translation: preface by Sánchez-Martínez, Felipe, Forcada, Mikel L.

    Published in Machine translation (01-06-2011)
    “…This issue of Machine Translation, which focuses on on the use of free/open-source software in machine translation, is introduced. Adapted from the source…”
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    Journal Article
  11. 11

    Using Target-Language Information to Train Part-of-Speech Taggers for Machine Translation by Sánchez-Martínez, Felipe, Pérez-Ortiz, Juan Antonio, Forcada, Mikel L.

    Published in Machine translation (01-03-2008)
    “…Although corpus-based approaches to machine translation (MT) are growing in interest, they are not applicable when the translation involves lessresourced…”
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    Journal Article
  12. 12

    Automatic Induction of Bilingual Resources from Aligned Parallel Corpora: Application to Shallow-Transfer Machine Translation by Caseli, Helena M., Nunes, Maria das Graças V., Forcada, Mikel L.

    Published in Machine translation (01-03-2006)
    “…The availability of machine-readable bilingual linguistic resources is crucial not only for rule-based machine translation but also for other applications such…”
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    Journal Article
  13. 13

    Inferring Shallow-Transfer Machine Translation Rules from Small Parallel Corpora by Sánchez-Martínez, Felipe, Forcada, Mikel L

    Published 15-01-2014
    “…Journal Of Artificial Intelligence Research, Volume 34, pages 605-635, 2009 This paper describes a method for the automatic inference of structural transfer…”
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    Journal Article
  14. 14

    Online text prediction with recurrent neural networks by PEREZ-ORTIZ, Juan Antonio, CALERA-RUBIO, Jorge, FORCADA, Mikel L

    Published in Neural processing letters (01-10-2001)
    “…Arithmetic coding is one of the most outstanding techniques for lossless data compression. It attains its good performance with the help of a probability model…”
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    Journal Article