Towards a simple and accurate statistical approach to learning translation relationships among words

Abstract

We report on a project to derive word translation relationships automatically from parallel corpora. Our effort is distinguished by the use of simpler, faster models than those used in previous high-accuracy approaches. Our methods achieve accuracy on single-word translations that seems comparable to any work previously reported, up to nearly 60% coverage of word types, and they perform particularly well on a class of multi-word compounds of special interest to our translation effort.