1. A method, comprising: receiving an input signal that is one of a wideband signal or a narrowband signal; extracting features from the one of the wideband signal or the narrowband signal for inclusion in a feature set, a number of features extracted for the narrowband signal being less when compared to a number of features extracted for the wideband signal; inputting the feature set to a deep neural network (DNN) in a recognition system regardless of whether the input signal is the wideband signal or the narrowband signal, the DNN being trained using both wideband signals and narrowband signals, wherein the DNN generates an output responsive to the inputting of the feature set to the DNN; and assigning a classification to the input signal based upon the output of the DNN.