In maximum-likelihood based speech recognition systems, it is important to accurately estimate the joint distribution of feature vectors given a particular acoustic model. In previous work, we showed we can boost accuracy in this task by modeling the joint distribution of time-localized feature vectors along with statistics relating those feature vectors to their surrounding context. In this wo...