A study of speech recognition of complete Chinese syllables based on continuous Gaussian Mixture HMM

Based on a large amount of speech study and experiments,this paper gives a deep study on how HMM is applied to the Chinese speech recognition,and establishal a speech recognition system of complete Chinese syllables using the continuous Gaussian Mixture HMM. The systems does not adopt the traditional Baum-Welch Algorithm, but uses segmental K-Means Training.which needs much smaller memory,calculation and iteration times,and can give automatic segmentation of Speech.On the choise of HMM unit,unit structure,and unit parameters,the poper gives a thorough consideration for the properties of Chinese speech.The paper also gives a deep study on speech features,and employed Mel-Scaled FFT-CEP (instead of LPC-CEP) and its regression coefficients,normalized log-energy and its regression coefficients.In addition,the paper proposes the Variant Frame Shift Analysis Algorithm considering characteristics of consonants.The system recognition rate is 91.1%.