We have shown how a three-component model that consists of a model of the phenomenon being studied and two distributional components, one from the source data and one from the target data, allows one to create data artificially for training a semantic parser.
analysis and minimal annotation of only a small subset of utterances from the target domain of spoken dialogue systems suffices to determine a model of NSUs as well as the necessary target distribution.