A segmental HMM for speech pattern modelling

A simple segmental hidden Markov model (HMM) which addresses some of the limitations of conventional HMM-based methods is proposed. The important features of this approach are the use of an underlying semi-Markov process, in which state transitions are segment-synchronous rather than frame-synchronous and state duration is modeled explicitly, and a state segment model in which separate statistical processes are used to characterize extra-segmental and intra-segmental variability. A basic mathematical analysis of Gaussian segmental HMMs is presented, and model parameter reestimation equations are derived. The relationship between the new type of model and variable frame rate analysis and conventional Gaussian mixture based HMMs is explained.<>