One obvious choice is to use Maximum Likelihood (ML) criterion.
rapid adaptation for acoustic modeling, using such methods as Maximum Likelihood Linear Regression (MLLR) (Legetter & Woodland, 1995), is possible using very small amount of acoustic data, thanks to the inherent structure of acoustic models that allow large degrees of parameter tying across different words (several thousand context dependent states are shared by all the words in the dictionary).