1. A method comprising: providing a deep neural network acoustic model; receiving audio data including one or more utterances of a speaker; extracting a plurality of speech recognition features from the one or more utterances of the speaker; creating a speaker identity vector for the speaker based on the speech recognition features extracted from the one or more utterances of the speaker; performing, by a computer system, an automatic speech recognition using the speech recognition features extracted from the one or more utterances of the speaker and the speaker identity vector by executing the deep neural network acoustic model; and adapting the deep neural network acoustic model executing on the computer system performing the automatic speech recognition using the speech recognition features extracted from the one or more utterances of the speaker and the speaker identity vector, wherein adapting the deep neural network acoustic model further comprises concatenating the speaker identity vector to each of the speech recognition features extracted from the one or more utterances of the speakers to form an input to the deep neural network acoustic model.