1. A method comprising: training, via a processor, an automatic speech recognition module, a spoken language understanding module and a dialog management module using task-independent call-types of a previous application; recognizing a received user utterance in response to a prompt to a user using the automatic speech recognition module to yield a recognized user utterance; classifying the recognized user utterance using the spoken language understanding module to yield a classification; if the recognized user utterance is classifiable by the spoken language understanding module with a confidence more than an acceptance threshold, then acting according to a call-type associated with the classification; and if the recognized user utterance is not classifiable by the spoken language understanding module to a predetermined rejection threshold and if a dialog-wide re-prompt counter is exceeded, then transferring the user to a human, wherein the received user utterance is transcribed, labeled and used for training the spoken dialog system, and wherein at least one of the acceptance threshold and the predetermined rejection threshold are related to an entity referenced in the recognized user utterance.
1. A method comprising: training, via a processor, an automatic speech recognition module, a spoken language understanding module and a dialog management module using task-independent call-types of a previous application; recognizing a received user utterance in response to a prompt to a user using the automatic speech recognition module to yield a recognized user utterance; classifying the recognized user utterance using the spoken language understanding module to yield a classification; if the recognized user utterance is classifiable by the spoken language understanding module with a confidence more than an acceptance threshold, then acting according to a call-type associated with the classification; and if the recognized user utterance is not classifiable by the spoken language understanding module to a predetermined rejection threshold and if a dialog-wide re-prompt counter is exceeded, then transferring the user to a human, wherein the received user utterance is transcribed, labeled and used for training the spoken dialog system, and wherein at least one of the acceptance threshold and the predetermined rejection threshold are related to an entity referenced in the recognized user utterance. 6. The method of claim 1 , wherein the spoken dialog system performs call-type classification.