Patent ID: 7853451

Claim:
A method for generating labeled utterances from human-human utterances for use in training a semantic classification model for a spoken dialog system, the method comprising: identifying via a processor call-type gaps in human-human utterances to yield identified call-type gaps, wherein the identified call-type gaps include one of a missing call-type and an infrequent call-type; augmenting the human-human utterances with data that relates to the identified call-type gaps in the human-human utterances; augmenting the human-human utterances, to yield augmented human-human utterances by placing at least one word within the text of the human-human utterances that improves a training ability of the human-human utterances according to conversation patterns of the spoken dialog system; clausifying the augmented human-human utterances to yield clausified, augmented human-human utterances; labeling the clausified, augmented human-human utterances to yield labeled utterances; and building a semantic classification model for the spoken dialog system using the labeled utterances.