1. A method for language processing, comprising: training one or more automatic speech recognition models using an automatic speech recognition dictionary and speech recognition training data; determining a set of N automatic speech recognition hypotheses that characterize a spoken input, based on the one or more automatic speech recognition models, using a processor; selecting a hypothesis from the set of N automatic speech recognition hypotheses using a discriminative language model and a first natural language processing dictionary that excludes words having little discriminatory value according to an error rate of only words other than words having little likely effect on the natural language outcome in each hypothesis; and performing natural language processing on the selected hypothesis using a second natural language processing dictionary that is different from the automatic speech recognition dictionary and the first natural language processing dictionary.