METEOR For Multiple Target Languages Using DBnary
| Autor: | Elloumi, Zied, Blanchon, Hervé, Serasset, Gilles, Besacier, Laurent |
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| Přispěvatelé: | Groupe d’Étude en Traduction Automatique/Traitement Automatisé des Langues et de la Parole (GETALP), Laboratoire d'Informatique de Grenoble (LIG), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), ANR-14-CE24-0016,KEHATH,Méthodes qualité avancées pour la post-édition de traduction automatique(2014) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | Proceedings of the Summit XV, vol 1 MT Summit 2015 MT Summit 2015, Nov 2015, Miami, United States |
| Popis: | International audience; This paper proposes an extension of METEOR, a well-known MT evaluation metric, for multiple target languages using an in-house lexical resource called DBnary (an extraction from Wiktionary provided to the community as a Multilingual Lexical Linked Open Data). Today, the use of the synonymy module of METEOR is only exploited when English is the target language (use of WordNet). A synonymy module using DBnary would allow its use for the 21 languages (covered up to now) as target languages. The code of this new instance of METEOR, adapted to several target languages, is provided to the community via a github repository. We also show that our DBnary augmented METEOR increases the correlation with human judgements on the WMT 2013 and 2014 metrics dataset for English-to-(French, Russian, German, Spanish) language pairs. |
| Databáze: | OpenAIRE |
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