1. A computer-implemented method for automatic speech recognition using a non-intrusive acoustic parameter estimation of a room without an estimate of a clean speech signal comprising: receiving, at a computing device, a first degraded speech signal associated with a user; extracting one or more short-term features from the first degraded speech signal, wherein the one or more short term features includes a line spectral frequency feature and at least one of a mel-frequency cepstral coefficient feature, a velocity feature and an acceleration feature; extracting one or more long-term features from the first degraded speech signal wherein the one or more long-term features includes a feature based upon, at least in part, a Hilbert phase calculation; determining one or more statistics of each of the one or more short-term features from the first degraded speech signal; classifying the one or more statistics as belonging to one or more acoustic parameter classes; selecting one or more automatic speech recognition (ASR) models based upon the one or more acoustic parameter classes; and performing automatic speech recognition based upon, at least in part, the selected one or more ASR models.