Dear Friends; I have implemented Segmental K-means algorithm for better HMM parameter initialization (Rabiner: A tutorial on Hidden Markov models and selected applications in speech recognition 1989). But I have some problems: 1- After some iteration of running Viterbi algorithm for each training sample of the word and segmenting it according to the optimal path, observation vectors of some states are less than number of predefined Gaussian mixture models. So the algorithm can not reestimate mean vector, covariance matrix and mixture gains of these states. 2-During HMM learning process with Segmental K-means, some times log of likelihood is decreased suddenly and the algorithm can not converge. Any comments would be helpful.
Problems in Segmental K-means algorithm
Started by ●November 27, 2006