This work explores the use of speech knowledge for robust speech recognition by first describing the speech signal through a set of broad speech units, and then conducting a more detailed analysis from these broad units. These units are formed by grouping together parts of the acoustic signal that have similar temporal and spectral characteristics. This work first introduces a novel instantaneous adaptation technique to robustly detect broad classes (BCs) from the input signal using the Extended Baum-Welch (EBW) transformations. Recognition experiments indicate that the EBW method offers a...