1. A method for generating a natural language understanding model, comprising: a. collecting a plurality of unlabeled utterances; b. generating via a processor a plurality of call types for a first natural language understanding model based on call types with high probabilities in an existing natural language understanding model for a different application, each generated call type being based on a first set of utterances selected from the plurality of unlabeled utterances; c. generating the first natural language understanding model using call type information contained within the first set of utterances; d. testing the first natural language understanding model; e. modifying the plurality of call types based on the testing; and f. generating a second natural language understanding model using the modified plurality of call types.