1. A computer-implemented selection system, comprising: linguistic data corpora that include an in-domain corpus and an out-domain corpus for domain adaptation for machine translation model training, the in-domain corpus and the out-domain corpus including multi-lingual data translated to the corpora in parallel; a relevance component that selects relevant multi-lingual data from the out-domain corpus based on a similarity measure, the similarity measure considering a difference of cross-entropy scores according to an in-domain language model and an out-domain language model, the relevant multi-lingual data utilized in combination with the in-domain corpus or in isolation without the in-domain corpus; and a processor that executes computer-executable instructions associated with at least the relevance component.
2. The system of claim 1 , wherein the relevant multi-lingual data is selected based on the similarity measure that considers the difference of cross-entropy scores according to the in-domain language model and the out-domain language model on a source side and a target side.