ng to each phoneme of the phoneme model sequence in the training word, the parameters including a mean vector and weighting factor for each transition and a covariance matrix for each model; c) computing a set of observation probabilities for each phoneme of the phoneme model sequence the training word and the first set of model parameters; d) aligning the frame sequence of acoustic parameter vect