1. An automated task classification system that operates on a task objective of a user, through a natural language dialog with the user in which system prompts are not ordered in a menu, the system comprising: a recognizer that spots at least one of a plurality of meaningful phrases in substantially simultaneous user natural language verbal and non-verbal input, wherein the natural language verbal and non-verbal input each convey different information and are associated with a coordinated message that achieves an appropriate response, each of the plurality of meaningful phrases having an association with at least one of a predetermined set of task objectives, and the predetermined set of task objectives based, at least partly, on a salience measure of one of the plurality of meaningful phrases to a specified one of the predetermined task objectives, wherein the salience measure is represented as a conditional probability of the task objective being requested given an appearance of one of the plurality of meaningful phrases in the input communication, the conditional probability being a highest value in a distribution of conditional probabilities over the set of predetermined task objectives; and a task classifier that makes a classification decision based, at least partly, on the spotted at least one of the plurality of meaningful phrases.