Parser Accuracy in Quality Estimation of Machine Translation: A Tree Kernel Approach
Rasoul Kaljahi, Jennifer Foster, Raphaël Rubino, Johann Roturier, Fred Hollowood · International Joint Conference on Natural Language Processing · 2013
We report on experiments designed to investigate the role of syntactic features in the task of quality estimation for machine translation, focusing on the effect of parser accuracy. Tree kernels are used to predict the segment-level BLEU score of EnglishFrench translations. In order to examine the effect of the accuracy of the parse tree on the accuracy of the quality estimation system, we experiment with various parsing systems which differ substantially with respect to their Parseval f-scores. We find that it makes very little difference which system we choose to use in the quality estimation task ‐ this effect is particularly apparent for source-side English parse trees.