21. In an automatic speech processing system, a method for grading the pronunciation of a student speech sample, the method comprising: accepting said student speech sample which comprises a sequence of words spoken by a student speaker; operating a set of trained speech models to compute at least one posterior probability from said speech sample, each of said posterior probabilities being a probability that a particular portion of said student speech sample corresponds to a particular known model given said particular portion of said speech sample; and computing an evaluation score, herein referred to as the posterior-based evaluation score, of pronunciation quality for said student speech sample from said posterior probabilities wherein each of said posterior probabilities is derived from a model likelihood by dividing the likelihood that said particular known model generated said particular portion of said student speech sample by the summation of the likelihoods that individual models generated said particular portion of said speech sample.
23. The method according to claim 21 wherein said particular portion of said speech sample is a phone.