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. 10. The method according to claim 9 wherein: said spoken sequence of words is spoken according to a known script; and the path computing step comprises using said script in defining allowability of any path through the HMMs.