12. A non-transitory computer-readable medium storing a computer program having instructions for using alternate recognition hypotheses to improve whole-dialog understanding accuracy, the instructions comprising: receiving an utterance as part of a user dialog turn; generating an N-best list of recognition hypotheses for the user dialog turn to yield a generated N-best list; selecting an underlying user intention based on a belief distribution across the generated N-best list and at least one contextually similar N-best list that is based on an analysis of confidence scores calculated by summing over all possible hidden states and all possible hidden user actions associated with the recognition hypotheses in the generated N-best list and the at least one contextually similar N-best list; and responding to the user based on the selected underlying user intention.
12. A non-transitory computer-readable medium storing a computer program having instructions for using alternate recognition hypotheses to improve whole-dialog understanding accuracy, the instructions comprising: receiving an utterance as part of a user dialog turn; generating an N-best list of recognition hypotheses for the user dialog turn to yield a generated N-best list; selecting an underlying user intention based on a belief distribution across the generated N-best list and at least one contextually similar N-best list that is based on an analysis of confidence scores calculated by summing over all possible hidden states and all possible hidden user actions associated with the recognition hypotheses in the generated N-best list and the at least one contextually similar N-best list; and responding to the user based on the selected underlying user intention. 13. The non-transitory computer-readable medium of claim 12 , the instructions further comprising assigning an individual confidence score to each recognition hypothesis in the generated N-best list and in the at least one contextually similar N-best list.