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 approach to an original matrix in the DNN model; in response to applying the decomposition approach, converting the original matrix into a plurality of new matrices, each of the plurality of new matrices being smaller than the original matrix; adding, by the computing device, another matrix to the plurality of new matrices; and adapting, by the computing device, the DNN model by updating the added matrix, the adapted DNN model comprising a reduction in a number of parameters in the DNN model.