CAJ | 학술논문

通过罗列分析声母读音错误的主要表现形式,提出了利用语音知识引导的两层两级声母客观评测算法.根据普通话声母的特点,总结出98种普通话声韵组合作为声母的评测基元.实验结果表明,所提出的算法比单独用隐马尔可夫模型(HMM)算法评测的主客观符合率高2.56%,比单独用BP神经网络算法评测的主客观符合率高3.65%,比只用单层算法评测的主客观符合率高1.42%,证明该算法不但能减少计算量,还能提高评测的精度.
통과라렬분석성모독음착오적주요표현형식,제출료이용어음지식인도적량층량급성모객관평측산법.근거보통화성모적특점,총결출98충보통화성운조합작위성모적평측기원.실험결과표명,소제출적산법비단독용은마이가부모형(HMM)산법평측적주객관부합솔고2.56%,비단독용BP신경망락산법평측적주객관부합솔고3.65%,비지용단층산법평측적주객관부합솔고1.42%,증명해산법불단능감소계산량,환능제고평측적정도.
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.