Explicit modelling of state occupancy in hidden Markov models for automatic speech recognition

Semi-Markov models have been proposed as a mechanism for overcoming some of the limitations inherent in first-order Markov modelling of speech signals. Results have been presented which show that these models provide an appropriate framework for modelling durational structure and can lead to significant improvements in recognition accuracy.