Unsupervised topic models can be used effectively in language modeling and information retrieval to tailor performance on broad corpora by determining clusters of related data. We combine such a topic model based on Latent Dirichlet Allocation with our recent work on corpus sub-selection to improve machine translation system results on a variety of TED talks.