18. A method comprising: receiving, by at least one processing device, a log file comprising data associated with one or more spoken utterances, system prompt information, and denied confirmations associated with a sub-set of the one or more spoken utterances; calculating pseudo-semantic labels for each spoken utterance in the sub-set of the one or more spoken utterances, the pseudo-semantic labels comprising a classification result that is consistent with both the data and the denied confirmations, is selected from a set of potential concepts germane to the data and the system prompt information, and represents an association between the denied confirmation and one or more rejected semantic labels; training a classifier using the calculated pseudo-semantic labels; and using the trained classifier to process input speech data.
18. A method comprising: receiving, by at least one processing device, a log file comprising data associated with one or more spoken utterances, system prompt information, and denied confirmations associated with a sub-set of the one or more spoken utterances; calculating pseudo-semantic labels for each spoken utterance in the sub-set of the one or more spoken utterances, the pseudo-semantic labels comprising a classification result that is consistent with both the data and the denied confirmations, is selected from a set of potential concepts germane to the data and the system prompt information, and represents an association between the denied confirmation and one or more rejected semantic labels; training a classifier using the calculated pseudo-semantic labels; and using the trained classifier to process input speech data. 19. The method of claim 18 further comprising: generating training data comprising spoken utterances having accepted confirmations and spoken utterances having settled denied confirmations; and training a classification model associated with the classifier with the training data.