2. The method of claim 1 , further comprising: training the first classifier using a first plurality of first confidence score groups, wherein: each first confidence score group is associated with a training utterance, each first confidence score group includes a plurality of confidence scores, each confidence score of the first confidence score group is associated with a training ASR hypothesis corresponding to the respective training utterance, and each first confidence score group is labeled for either (a) selecting a highest scoring training ASR hypothesis associated with the associated training utterance or (b) selecting a plurality of training ASR hypotheses associated with the training utterance for disambiguation; and training a second classifier using the second plurality of second confidence score groups, wherein: each second confidence score group is associated with a candidate training ASR hypothesis, each second confidence score group includes a plurality of confidence scores corresponding to different training ASR hypotheses of a same training utterance, and each second confidence score group is labeled for either (a) selecting the respective training ASR hypothesis for disambiguation or (b) not selecting the respective training ASR hypothesis for disambiguation.
2. The method of claim 1 , further comprising: training the first classifier using a first plurality of first confidence score groups, wherein: each first confidence score group is associated with a training utterance, each first confidence score group includes a plurality of confidence scores, each confidence score of the first confidence score group is associated with a training ASR hypothesis corresponding to the respective training utterance, and each first confidence score group is labeled for either (a) selecting a highest scoring training ASR hypothesis associated with the associated training utterance or (b) selecting a plurality of training ASR hypotheses associated with the training utterance for disambiguation; and training a second classifier using the second plurality of second confidence score groups, wherein: each second confidence score group is associated with a candidate training ASR hypothesis, each second confidence score group includes a plurality of confidence scores corresponding to different training ASR hypotheses of a same training utterance, and each second confidence score group is labeled for either (a) selecting the respective training ASR hypothesis for disambiguation or (b) not selecting the respective training ASR hypothesis for disambiguation. 3. The method of claim 2 , further comprising determining the second plurality of second confidence score groups from among the first confidence score groups labeled for (b) selecting a plurality of training ASR hypotheses associated with the training utterance for disambiguation.