Incorporating position information into a Maximum Entropy/Minimum Divergence translation model
George Foster · 2000
I describe two methods for incorporating information about the relative positions of bilingual word pairs into a Maximum Entropy/Minimum Divergence translation model. The better of the two achieves over 40% lower test corpus perplexity than an equivalent combination of a trigram language model and the classical IBM translation model 2.