基于ZCPA和DHMM的孤立词语音识别系统  

A Speech Recognition System of Isolated Words Based on ZCPA and DHMM

作　　者：赵姝彦[1] 张雪英[1] 焦志平[1] 

机构地区：[1]太原理工大学信息工程学院,山西太原030024

出　　处：《太原理工大学学报》2005年第3期246-249,共4页Journal of Taiyuan University of Technology

基　　金：国家自然科学基金(60472094);教育部留学回国科研基金(教外司留[2004]176 号);山西省留学回国人员科研基金(No.200224);山西省高等学校青年学术带头人科研基金(晋教科[2004]13号)

摘　　要：介绍了用离散隐马尔可夫模型(DHMM)构造孤立词语音识别系统的过程,重点针对软件实现中的问题重新推导了Baum Welch算法的重估公式,引入一种抗噪性能很好的特征参数:过零率与峰值幅度特征,将该特征与DHMM结合用于孤立词识别系统。结果表明,此系统训练时收敛很快并且识别效果好。This paper described the whole process of building a speech recognition system of isolated words using discrete HMM(Hidden Markov Model) and derived the reestimate formula of Baum-Welch algorithm again with respect to the problems in the process of software implement. This paper also introduced a kind of feature parameter which has excellent anti-noise capability: ZCPA feature. Combining this kind of feature with DHMM can form a recognition system of isolated words. The experiment showed that it can converge rapidly in system training process and the recognition results are satisfactory.

关 键 词：语音识别 隐马尔可夫模型 特征提取 

分 类 号：TN912.3[电子电信—通信与信息系统]