Browsing by Author "Fomicheva, Marina"

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  • Boosting the creation of a treebank
    Arias Badia, Blanca; Bel Rafecas, Núria; Fomicheva, Marina; Larrea Mendizabal, Imanol; Lorente, Mercè; Marimon, Montserrat; Milà-Garcia, Alba; Vivaldi, J. (Jorge), 1952-; Padró, Muntsa (ELRA (European Language Resources Association), 2014)
    We present the results of the experiment of bootstrapping a Treebank for Catalan by using a Dependency Parser trained with Spanish sentences. In order to save time and cost, our approach was to profit from the typological ...
  • CobaltF: a fluent metric for MT evaluation
    Fomicheva, Marina; Bel Rafecas, Núria; Specia, Lucia; da Cunha Fanego, Iria; Malinovskiy, Anton (ACL (Association for Computational Linguistics), 2016)
    The vast majority of Machine Translation (MT) evaluation approaches are based on the idea that the closer the MT output is to a human reference translation, the higher its quality. While translation quality has two ...
  • Neutralizing the effect of translation shifts on automatic machine translation evaluation
    Fomicheva, Marina; Bel Rafecas, Núria; da Cunha Fanego, Iria (Springer, 2015)
    State-of-the-art automatic Machine Translation [MT] evaluation is based on the idea that the closer MT output is to Human Translation [HT], the higher its quality. Thus, automatic evaluation is typically approached by ...
  • The Role of human reference translation in machine translation evaluation
    Fomicheva, Marina (Universitat Pompeu Fabra, 2017-07-18)
    Both manual and automatic methods for Machine Translation (MT) evaluation heavily rely on professional human translation. In manual evaluation, human translation is often used instead of the source text in order to avoid ...
  • UPF-cobalt submission to WMT15 metrics task
    Fomicheva, Marina; Bel Rafecas, Núria; da Cunha Fanego, Iria; Malinovskiy, Anton (ACL (Association for Computational Linguistics), 2015)
    An important limitation of automatic evaluation metrics is that, when comparing Machine Translation (MT) to a human reference, they are often unable to discriminate between acceptable variation and the differences that are ...