Word2Vec vs DBnary: Augmenting METEOR using Vector Representations or Lexical Resources?

View Researcher's Other Codes

Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).

Please contact us in case of a broken link from here

Authors Alexandre Berard, Hervé Blanchon, Laurent Besacier, Christophe Servan, Zied Elloumi
Journal/Conference Name COLING 2016 12
Paper Category
Paper Abstract This paper presents an approach combining lexico-semantic resources and distributed representations of words applied to the evaluation in machine translation (MT). This study is made through the enrichment of a well-known MT evaluation metric: METEOR. This metric enables an approximate match (synonymy or morphological similarity) between an automatic and a reference translation. Our experiments are made in the framework of the Metrics task of WMT 2014. We show that distributed representations are a good alternative to lexico-semantic resources for MT evaluation and they can even bring interesting additional information. The augmented versions of METEOR, using vector representations, are made available on our Github page.
Date of publication 2016
Code Programming Language Java
Comment

Copyright Researcher 2022