Starting from an SMT model trained initially on bilingual data, the problem is to minimize the human effort in translating new sentences which will be added to the training data to make the retrained SMT model achieves a certain level of performance.
given a bitext L := {(f i , e i )} and a monolingual source text U := {f j }, the goal is to select a subset of highly informative sentences from U to present to a human expert for translation.