1. A method comprising: receiving, via a microphone, a speech signal corresponding to a particular speaker; selecting, via a processor, a cluster model to be stored in at least one memory device, the cluster model comprises both a speaker independent portion that defines a plurality of states and a plurality of state tyings and a speaker dependent portion, wherein the speaker independent portion is selected based at least in part on a recognition result of a recognition operation and wherein the speaker dependent portion is a subspace Hidden Markov Model, wherein the subspace Hidden Markov Model is selected based at least in part on a characteristic of speech of the particular speaker, the microphone, and on a rescoring of the recognition result; storing the speaker dependent portion of the selected cluster model locally and storing different speaker dependent portions remotely; and processing the speech signal, using the selected cluster model, to convert the speech signal into text.