Towards advanced collocation error correction in Spanish learner corpora.

Collocations in the sense of idiosyncratic binary lexical co-occurrences are one of the biggest challenges for any language learner. Even advanced learners make collocation mistakes in that they literally translate collocation elements from their native tongue, create new words as collocation elemen...

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Publicado en:Language Resources & Evaluation Vol. 48; no. 1; pp. 45 - 65
Autores principales: Ferraro, Gabriela, Nazar, Rogelio, Alonso Ramos, Margarita, Wanner, Leo
Formato: Artículo
Publicado: Springer Nature Mar2014
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1007/s10579-013-9242-3
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          Ferraro, Gabriela
          Nazar, Rogelio
          Alonso Ramos, Margarita
          Wanner, Leo
        affil:
          Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona Spain
          Institute for Applied Linguistics, Pompeu Fabra University, Barcelona Spain
          Faculty of Philology, University of La Coruña, La Coruña Spain
          Department of Information and Communication Technologies, Catalan Institute for Research and Advanced Studies (ICREA), Pompeu Fabra University, Barcelona Spain
      su:
        Collocation (Linguistics)
        Error correction (Information theory)
        Spanish language
        Corpora
        Accuracy of information
      sug:
        subj:
          Collocation (Linguistics)
          Error correction (Information theory)
          Spanish language
          Corpora
          Accuracy of information
      keyword:
        CALL
        Collocation
        Collocation error
        Collocation error correction
        Collocation error detection
        Miscollocation
      ab: Collocations in the sense of idiosyncratic binary lexical co-occurrences are one of the biggest challenges for any language learner. Even advanced learners make collocation mistakes in that they literally translate collocation elements from their native tongue, create new words as collocation elements, choose a wrong subcategorization for one of the elements, etc. Therefore, automatic collocation error detection and correction is increasingly in demand. However, while state-of-the-art models predict, with a reasonable accuracy, whether a given co-occurrence is a valid collocation or not, only few of them manage to suggest appropriate corrections with an acceptable hit rate. Most often, a ranked list of correction options is offered from which the learner has then to choose. This is clearly unsatisfactory. Our proposal focuses on this critical part of the problem in the context of the acquisition of Spanish as second language. For collocation error detection, we use a frequency-based technique. To improve on collocation error correction, we discuss three different metrics with respect to their capability to select the most appropriate correction of miscollocations found in our learner corpus.
      pubtype: Academic Journal
      doctype: Article
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    language: English
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      custom: Language Resources & Evaluation is a copyright of Springer, 2014. All Rights Reserved.
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