The segmental fuzzy c-means algorithm for estimating parameters of continuous density hidden Markov models

In this paper, we propose the segmental fuzzy c-means algorithm for maximum likelihood estimating parameters of continuous density hidden Markov models (CDHMM) to substitute for the common segmental k-means algorithm, based on the analysis of two main methods for estimating parameters of CDHMM. Experimental results demonstrate the efficiency of the new algorithm.