Translation quality evaluation of MWE from French into English using an SMT system
Nowadays, Statistical Machine Translation (SMT) is widely available. Nevertheless, using Machine Translation at its best is not an easy task. Structures appearing sporadically trigger most of the regular mistakes of SMT systems. We work on one of those structures: the MultiWord Expressions (MWE) Our study aims at evaluating the quality of MWE translation obtained using SMT. Firstly, we present the process of our quality evaluation of the English translation got via an SMT system created using Moses Toolkit (Koehn et al. 2007) of one French technical document. On the French document, MWE have been semi automatically annotated according to their type (Tutin et al. 2015) Secondly, we describe the linguistic criteria of Vilar's classification of translation errors (Vilar et al. 2006) as well as the adaptation we had to perform to use Blast (Stymne, 2011) Thirdly, we analyse the global results of our quality evaluation before going into details, in our fourth part, on one particular type of MWE, which is the Full Phraseme one. We finally show that most of the French MWE are translated into English MWE, and that we need to implement in further work a collaborative error annotation tool.
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