1. A method for language processing, comprising: training one or more automatic speech recognition models using an automatic speech recognition dictionary; 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 list of relevant words according to an error rate of relevant words in each hypothesis; and performing natural language processing on the best hypothesis.