1. A method for generating a natural language statistical model comprising: receiving, at at least one system comprising a combination of hardware and software, a set of training data comprising unigrams identified as being individually meaningless; assigning, via the at least one system, at least a portion of the unigrams identified as being meaningless to a first n-gram class selected from a plurality of n-gram classes; and processing the classified training data via the at least one system to generate the natural language statistical model.