Abstract:
This paper presents a new hybrid framework of hidden Markov model (HMM )and radial basis function (RBF) neural network for Chinese Mandarin digit speech recognition.Here, the HMM is employed to produce a best speech state sequence, which is warped to a fixed dimension vector and neural network is used as classifier.Results show that the new hybrid system works better than others.
摘要: 提出一种离散隐马尔科夫模型(hidden Markov model,HMM)和径向基函数(radial basis function,RBF)神经网络相结合应用于汉语数码语音识别(Mmandarin Ddigit Speech Recognition,MDSR)的方法。同时采用了一系列改进方法,使汉语数码语音的识别率达到了99.7%。
关键词:
汉语,
数码语音识别,
隐马尔科夫模型,
径向基函数
CLC Number:
WANG Peng,CHEN Shuzhong. MDSR Based on Hybrid HMM/ RBF[J]. , 2002, 28(12): 141-143.
王朋,陈树中. 基于混合模型HMM/RBF的数字语音识别[J]. , 2002, 28(12): 141-143.