the invention provides a hidden markov model based automated speech recognition system that dynamically adapts to changing background noise by detecting long pauses in speech , and for each pause processing background noise during the pause to extract a feature vector that characterizes the background noise , identifying a gaussian mixture component of noise states that most closely matches the extracted feature vector , and updating the mean of the identified gaussian mixture component so that it more closely matches the extracted feature vector , and consequently more closely matches the current noise environment . alternatively , the process is also applied to refine the gaussian mixtures associated with other emitting states of the hidden markov model .