1. A method of adapting and personalizing a deep neural network (DNN) model for automatic speech recognition (ASR), comprising: receiving, by a computing device, at least one utterance comprising a plurality of speech features for one or more speakers from one or more ASR tasks; applying, by the computing device, a decomposition process to two or more matrices in the DNN model; in response to applying the decomposition process, adapting the DNN model to include a decomposed matrix that is generated from decomposition processing of the two or more matrices; and exposing the adapted DNN model as a service.