1. A method of generating a spoken language understanding module, the method comprising: a. selecting, via a processor, at least one predicate/argument pair as an intent from a set of a most frequent predicate/argument pairs for a domain associated with a spoken dialog system in a first language; b. labeling training data using mapping rules for the first language associated with the selected at least one predicate/argument pair and that specify rules for selecting a call-type label for an utterance; c. training a call-type classification model using the labeled training data; d. re-labeling the training data using the call-type classification model; and e. iteratively processing steps (c) and (d) until training set labels converge.
1. A method of generating a spoken language understanding module, the method comprising: a. selecting, via a processor, at least one predicate/argument pair as an intent from a set of a most frequent predicate/argument pairs for a domain associated with a spoken dialog system in a first language; b. labeling training data using mapping rules for the first language associated with the selected at least one predicate/argument pair and that specify rules for selecting a call-type label for an utterance; c. training a call-type classification model using the labeled training data; d. re-labeling the training data using the call-type classification model; and e. iteratively processing steps (c) and (d) until training set labels converge. 6. The method of claim 1 , wherein selecting at least one predicate/argument pair further comprises generating mapping rules and for labeling the training data.