1. A speech recognition system, comprising: a receiver component that receives a distorted speech utterance, the distorted speech utterance comprising additive distortions and convolutive distortions; and an updater component that is in communication with a first model and a second model, the first model being a nonlinear phase-sensitive model of additive and convolutive distortions in distorted speech utterances, the first model jointly outputting estimates of the additive distortions and the convolutive distortions in the distorted speech utterance received by the receiver component, wherein the updater component automatically updates parameters of the second model based at least in part upon the estimates of the additive distortions and the convolutive distortions output by the first model, wherein the second model is a Hidden Markov Model, wherein subsequent to the updater component updating the parameters of the second model, the second model outputs data that is indicative of a word in the distorted speech utterance, and wherein at least one computing task is performed based at least in part upon the data that is indicative of the word in the distorted speech utterance.
1. A speech recognition system, comprising: a receiver component that receives a distorted speech utterance, the distorted speech utterance comprising additive distortions and convolutive distortions; and an updater component that is in communication with a first model and a second model, the first model being a nonlinear phase-sensitive model of additive and convolutive distortions in distorted speech utterances, the first model jointly outputting estimates of the additive distortions and the convolutive distortions in the distorted speech utterance received by the receiver component, wherein the updater component automatically updates parameters of the second model based at least in part upon the estimates of the additive distortions and the convolutive distortions output by the first model, wherein the second model is a Hidden Markov Model, wherein subsequent to the updater component updating the parameters of the second model, the second model outputs data that is indicative of a word in the distorted speech utterance, and wherein at least one computing task is performed based at least in part upon the data that is indicative of the word in the distorted speech utterance. 3. The speech recognition system of claim 1 , wherein the first model outputs values for vector-valued distorted speech, clean speech, additive distortion, and convolutive distortion, and further comprising a linearizer component that outputs first-order vector Taylor Series approximations for the vector-valued distorted speech, the clean speech, the additive distortion, and the convolutive distortion, and wherein the updater component updates the parameters of the second model based at least in part upon the output approximations.