15. A computer-implemented selection method, comprising acts of: receiving an in-domain corpus of bilingual sentences and an out-domain corpus of bilingual sentences; generating an in-domain machine translation system from the in-domain corpus; training an in-domain language model based on the in-domain corpus and training an out-domain language model based on the out-domain corpus; applying a similarity measure to a sentence of the out-domain corpus and the in-domain language model, and to the sentence and the out-domain language model, to obtain similarity scores; selecting relevant sentences from the out-domain corpus based on the scores to create a subselected out-domain translation system; combining the in-domain machine translation system and the subselected out-domain translation system to create a domain adapted machine translation system; and utilizing a processor that executes instructions stored in memory to perform at least one of the acts of generating, training, applying, selecting, or combining.
16. The method of claim 15 , further comprising ranking the sentences for selection according to similarity scores, the scores obtained as a combination of a difference of the similarity scores according to the in-domain language model and the out-domain language model on each of a source side and a target side.