1. A method of determining a predictive model for discourse functions comprising the steps of: determining a training corpus of speech utterances; determining discourse functions associated with speech utterances in the training corpus, the discourse functions being determined automatically based on a theory of discourse analysis; determining prosodic features associated with the speech utterances in the training corpus; and determining a predictive model of discourse functions by associating the prosodic features determined from the speech utterances in the training corpus with the discourse functions determined from the speech utterances in the training corpus, wherein the predictive model of discourse functions is used to predict from prosodic features of a specific recognized speech, a likelihood that speech utterances of the specific recognized speech reflect a specific discourse function, and wherein the predictive model of discourse functions is used to predict, based, at least in part, on the prosodic features, a likelihood of a first portion of a speech utterance being associated with a command directed at an application and a second portion of the speech utterance being associated with content being provided to the application.
3. The method of claim 1 , in which the predictive models are determined based on at least one of: machine learning, rules.