Abstract: Techniques for performing command processing are described. A system receives, from a device, input data corresponding to a command. The input data may originate as audio data, as text data, or as other data. The system determines NLU processing results corresponding to the input data. The NLU processing results may be associated with multiple speechlets. The system also determines NLU confidences for the NLU processing results for each speechlet. The system sends NLU processing results and an indication to provide potential results to a portion of the multiple speechlets, and receives potential results from the portion of the speechlets. The system also receives indications whether the speechlets need to be re-called if the speechlets are selected to execute with respect to the command. The system ranks the portion of the speechlets based at least in part on the NLU processing results as well as the potential results provided by the portion of the speechlets.

Abstract: Various embodiments relating to partitioning a data set for training machine-learning classifiers based on an output of a globally trained machine-learning classifier are disclosed. In one embodiment, a first machine-learning classifier may be trained on a set of training data to produce a corresponding set of output data. The set of training data may be partitioned into a plurality of subsets based on the set of output data. Each subset may correspond to a different class. A second machine-learning classifier may be trained on the set of training data using a plurality of classes corresponding to the plurality of subsets to produce, for each data object of the set of training data, a probability distribution having for each class a probability that the data object is a member of the class.