Sentence Level Machine Translation Evaluation as a Ranking
Yang Ye, Ming Zhou, Chin-Yew Lin · 2007
The paper proposes formulating MT evalu-ation as a ranking problem, as is often done in the practice of assessment by human. Un-der the ranking scenario, the study also in-vestigates the relative utility of several fea-tures. The results show greater correlation with human assessment at the sentence level, even when using an n-gram match score as a baseline feature. The feature contributing the most to the rank order correlation be-tween automatic ranking and human assess-ment was the dependency structure relation rather than BLEU score and reference lan-guage model feature. 1