Introducing termination probabilities to HMM
HMM is very well suited to model sequential patterns. This paper introduces a new parameter, called the termination probability, to a hidden Markov model (HMM). The new parameter provides a better initialization for the backward variable during the training and evaluation phases. This improves the discriminatory power of HMM by allowing the system to judge the input observation sequence based on where it is completed. Experimental results show the improvement was achieved by this parameter.