With a belief that a language model that embraces a larger context provides better prediction ability, we learn additional information from training data to enhance conventional n-gram language models and extend their ability to capture richer contexts and long-distance dependencies.
we integrate backward n-grams and mutual information (MI) triggers into language models in SMT.