9. The method according to claim 1 wherein the step of operating said acoustic segmentation system comprises the steps of: computing a path through trained hidden Markov models (HMMs) from among said speech acoustic models, said path being an allowable path through the HMMs that has maximum likelihood of generating an observed acoustic features sequence from said student speech sample; and determining from said path at least one boundary or duration of one acoustic unit.
9. The method according to claim 1 wherein the step of operating said acoustic segmentation system comprises the steps of: computing a path through trained hidden Markov models (HMMs) from among said speech acoustic models, said path being an allowable path through the HMMs that has maximum likelihood of generating an observed acoustic features sequence from said student speech sample; and determining from said path at least one boundary or duration of one acoustic unit. 11. The method according to claim 9 wherein said spoken sequence of words is unknown, and the path computing step comprises operating a computerized speech recognition system that determines said spoken sequence of words.