1. A computer-implemented method for providing a statistical initial topic classification model for use in a natural language call routing application to map a natural language user statement to at least one of a plurality of topics in the natural language call routing application, the computer-implemented method comprising acts of: accessing a voice user interface (VUI) specification that specifies a VUI for allowing users to interact with the natural language call routing application, the VUI specification comprising a plurality of expressions of possible user intentions composed by at least one VUI designer, the VUI specification further comprising, for each one of the plurality of expressions of possible user intentions, at least one system response or action defined by the at least one VUI designer as corresponding to the one of the plurality of expressions of possible user intentions; analyzing the VUI specification to determine a plurality of topic descriptions, each one of the plurality of topic descriptions describing a meaning of a corresponding one of the plurality of topics; and using, as training data, the plurality of topic descriptions determined by analyzing the VUI specification to build the statistical initial topic classification model, comprising; identifying keywords in the plurality of topic descriptions used as training data to build the statistical initial topic classification model; providing an optimal feature set comprising at least one combination of at least some of the keywords; and using at least one computer to build the statistical initial topic classification model based at least partially on the optimal feature set.
5. The method of claim 1 , wherein accessing the VUI specification comprises accessing at least one call flow document defining how a call from a user is to be handled, and wherein analyzing the VUI specification comprises parsing the call flow document to extract the plurality of topic descriptions.