MDSR Based on Fuzzy Clustering Neural Network
In order to overcome Inherent bugs of basic hidden markov model (HMM), a method of speech recognition based on fuzzy clustering neural network is presented. Based on the fuzzy system model, every state (HMM) is regarded as a fuzzy system in this method. With continuous frames character vector of speech signal as the systems input, the model can forecast the probability density function of the systems output states by using improved fuzzy clustering identifying algorithm to build a novel fuzzy clustering neural network. It not only can import the relativity of frames about speech signal efficiently, it also can overcome the limit chain of mixed Gauss distributing probability density function. Speaker independent mandarin digit speech recognition which based on this method is realized. Experimental results show that the method is efficiency and has higher recognition ratio than basic HMM.
mandarin digit speech recognition fuzzy clustering neural network hidden markov model(HMM)
Peiling Zhang Hui Li
College of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, China
国际会议
长沙
英文
1806-1809
2010-05-11（万方平台首次上网日期，不代表论文的发表时间）