10. A computer-implemented method for automatic speech recognition that extracts words from user speech, the system comprising: classifying, via a processor, a set of labeled candidate utterances based on a previously trained classifier; generating, via a processor, classification types for each candidate utterance; receiving confidence scores for the classification types from the trained classifier; sorting the classified utterances based on an analysis of the confidence score of each candidate utterance compared to a respective label of the candidate utterance, wherein the analysis is based at least in part on a Kullback-Liebler divergence; and rechecking candidate utterances when the Kullback-Liebler divergence is greater than a threshold.
10. A computer-implemented method for automatic speech recognition that extracts words from user speech, the system comprising: classifying, via a processor, a set of labeled candidate utterances based on a previously trained classifier; generating, via a processor, classification types for each candidate utterance; receiving confidence scores for the classification types from the trained classifier; sorting the classified utterances based on an analysis of the confidence score of each candidate utterance compared to a respective label of the candidate utterance, wherein the analysis is based at least in part on a Kullback-Liebler divergence; and rechecking candidate utterances when the Kullback-Liebler divergence is greater than a threshold. 14. The computer-implemented method of claim 10 , wherein the trained classifier comprises an iterative classifier.