1. A method for speech recognition comprising the steps of: digitizing and framing a speech utterance token; transmitting said digitized and framed speech utterance token to Mel-filter banks; Mel-filtering the digitized and framed utterance token to produce log energy vectors for the number of classes C; transmitting a sequence of log energy vectors according to the frames to compute feature transformation operation; computing feature transformations for each class i of the utterance token and transmitting the result to next operation; computing static and dynamic features therefrom and transmitting the result to next operation; calculating a respective log likelihood for each of the utterance tokens Pi and transmitting the result to next operation; testing the token Pi to see if it is less than S and if it is, then the method branches to the next testing operation and if Pi is equal to S then setting index j equal to class index i and proceeding to the next testing operation; testing to see if index i is less than the number of classes C, if yes then iterating the index i by one and proceeding back to the computing feature transformations for each class i step and repeating this iteration and return until the expression i&lt;C is false, which means all classes i have been processed; if index i is not less than the number of classes C, then classification of this utterance token is finished and a j-th class is recognized for this given token; testing to see if this is the last utterance token to be processed and if it is the last then proceeding to done, otherwise returning to the digitizing and framing step to begin processing a subsequent utterance token.