1. A computer-implemented method of estimating noise and channel distortions and updating distorted speech parameters for an utterance, within an unscented transformation framework, during automatic speech recognition, comprising: receiving, by the computer, the utterance, wherein the utterance comprises speech generated from a transmission source for delivery to a receiver; applying, by the computer, the unscented transformation framework to speech feature vectors representative of the speech, to determine static distorted speech parameters and dynamic distorted speech parameters with initial noise and channel distortions, the initial noise distortions comprising speech parameters which are initialized by averaging a predetermined number of frames at the beginning and ending of the utterance, wherein the unscented transformation framework utilizes non-linear mapping; and estimating, by the computer, noise and channel distortions in the utterance from the static distorted speech parameters and the dynamic distorted speech parameters.
5. The method of claim 1 , wherein applying, by the computer, the unscented transformation framework to the speech feature vectors to determine static distorted speech parameters and dynamic distorted speech parameters comprises: determining a static transformed mean utilizing a non-linear function corresponding to the speech in the utterance, the static transformed mean comprising a static transformed speech feature mean vector; and determining a static transformed variance, the static transformed variance comprising a static transformed speech feature variance, the static transformed speech feature variance comprising elements of a diagonal covariance matrix, utilizing the non-linear function corresponding to the speech in the utterance.