  We consider phrase based Language Models (LM), which generalize the commonly
used word level models. Similar concept on phrase based LMs appears in speech
recognition, which is rather specialized and thus less suitable for machine
translation (MT). In contrast to the dependency LM, we first introduce the
exhaustive phrase-based LMs tailored for MT use. Preliminary experimental
results show that our approach outperform word based LMs with the respect to
perplexity and translation quality.
