Abstract��After searching and analyzing the error forms of spoken initials, a two-time-two-level objective evaluation algorithm of initials was advanced on the basis of the phonetic knowledge. Ninety-eight combinations of initial and final were summarized as the basic elements of the initial objective evaluation. The experiment has manifested that the accuracy of the two-time-two-level algorithm is 2.56% higher than that of the Hidden Markov Model (HMM) algorithm, and 3.65% higher than that of BP neural network algorithm, and also 1.42% higher than that of single-time-two-level algorithm. The results prove that the calculation amount of decreases, and the accuracy increases.
2010, Vol. 30 
