7. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain a Gaussian mixture model-based (“GMM-based”) acoustic model; obtain a neural network-based (“NN-based”) acoustic model; compute a first sequence of feature vectors from audio data; compute a first transform using the GMM-based acoustic model and the first sequence of feature vectors, wherein the first transform comprises a first linear portion and a first bias portion; compute a second linear portion of a NN-based transform by minimizing a first least squares difference function, wherein the first least squares difference function comprises a difference between the first linear portion and the second linear portion; compute a second bias portion of the NN-based transform by minimizing a second least squares difference function, wherein the second least squares difference function comprises a difference between the first bias portion and the second bias portion; compute a second sequence of feature vectors from an audio signal comprising user speech; compute a third sequence of feature vectors by applying the second linear portion and the second bias portion to the second sequence of feature vectors; perform speech recognition on the audio signal using the third sequence of feature vectors and the NN-based acoustic model; and determine using results of the speech recognition, an action to perform.
8. The system of claim 7 , wherein the audio data comprises the audio signal.