One might attempt self-training (McClosky et al., 2006), where new instances are generated by applying a trained model to unannotated data, using high-confidence predictions as ground truth labels.
one way around this is to use beam search (BS), which checks the likelihood of every possible continuation of a sentence fragment, and maintains a list of the n best translations generated up to the current time-step.