Learning labelled dependencies in machine translation evaluation
He, Yifan and Way, AndyORCID: 0000-0001-5736-5930
(2009)
Learning labelled dependencies in machine translation evaluation.
In: EAMT 2009 - 13th Annual Conference of the European Association for Machine Translation, 13-15 May 2009, Barcelona, Spain.
Recently novel MT evaluation metrics have been presented which go beyond pure string matching, and which correlate
better than other existing metrics with human judgements. Other research in this area has presented machine learning
methods which learn directly from human judgements. In this paper, we present a novel combination of dependency- and
machine learning-based approaches to automatic MT evaluation, and demonstrate greater correlations with human judgement than the existing state-of-the-art methods.
In addition, we examine the extent to which our novel method can be generalised across different tasks and domains.