【摘要】 本文提出一种用隐马氏链模型识别汉语声调的新方案。由每一种声调的训练语音求出相应的概率模型参数作为识别模板。识别时,分别用每一种声调的模型参数计算出现输入语声周期序列的概率,概率最大者即为输入语声的声调模型。实验语音选用的是“小学汉语拼音教学录音磁带”,一个男声和一个女声,对于其中的24个韵母和21组拼音音节,正确识别率为98%。更多还原

【Abstract】 We Present a Probabilistic approach to Chinese four-tone recognition in which the well-known technique of a hidden Markov modeling is used.For each tone,a distinct hidden Markov model is produced by using the Baum’s forward-backward algorithm based upon the training sequences consisting of several repetition of the same tone ut- terances.Classification can be made by computing the probability of generating the test utterance with each tone model and choosing as the recognized tone the one corre- sponding to the model with the highest probability score.The recognition accuracies were found to be 98% for 24 Chinese vowels and 21 spelling syllables pronounced by standard Chinese speakers.更多还原