8. An unsupervised learning method for training a speech classifier in a spoken language understanding system from a single kind of information, the method comprising: (1) receiving a collection of unlabeled utterance data that has been collected by a natural language dialog system; (2) generating confidence values for the received collection of unlabeled utterance data; (3) assembling a group of utterances from the received collection of unlabeled utterance data that has a confidence value indicative of usefulness in augmenting the speech classifier; and (4) augmenting the speech classifier with the assembled group of utterances, wherein the augmenting further comprises minimizing a loss function.
8. An unsupervised learning method for training a speech classifier in a spoken language understanding system from a single kind of information, the method comprising: (1) receiving a collection of unlabeled utterance data that has been collected by a natural language dialog system; (2) generating confidence values for the received collection of unlabeled utterance data; (3) assembling a group of utterances from the received collection of unlabeled utterance data that has a confidence value indicative of usefulness in augmenting the speech classifier; and (4) augmenting the speech classifier with the assembled group of utterances, wherein the augmenting further comprises minimizing a loss function. 11. The method of claim 8 , further comprising identifying a set of utterances that are candidates for manual labeling, wherein said assembling comprises assembling the remainder of the received collection of unlabeled utterance data that has not been identified for manual labeling.