1. A system for determining audio and acoustic characteristics of an Application Target Domain (ATD), comprising: a processor; and a memory with computer code instructions stored thereon, the memory operatively coupled to the processor such that the computer code instructions cause the processor to: determine a distribution of at least one audio characteristic and acoustic characteristic associated with one or more speech data samples from the target ATD by analyzing each of the one or more speech samples from the target ATD using only observed speech data samples without using a reference signal, the at least one audio characteristic and acoustic characteristic comprising: (a) CODEC type; (b) bit-rate associated with the one or more speech data samples; (c) sampling frequency associated with the speech data samples; (d) active bandwidth associated with the speech data samples; (e) noise level associated with the speech data samples; (f) reverberation level associated with the speech data samples; (g) clipping level associated with the speech data samples; (f) speaking rate associated with the speech data samples; and store in the memory, as a target data profile, the one or more target audio and acoustic characteristics; extract a feature set from the one or more speech data samples; one or both of: reduce the feature dimension of the feature set with a Classification and Regression Tree (CART) based feature extraction analysis to produce a final feature set; or train a Deep Neural Network (DNN) classifier with the final feature set or a previously-determined feature set; and one or both of: apply the trained DNN to perform a CODEC type classification of one or more of the one or more speech data samples to produce a CODEC type associated with the one or more speech data samples; or apply the trained DNN to perform a bit-rate classification of one or more of the one or more speech data samples and bit-rate associated with the one or more speech data samples.