Semi-continuous hidden Markov models for speech recognition
Xuedong Huang · ERA · 1989
Hidden Markov models, which can be based on either discrete output probability distributions or continuous mixture output density functions, have been demonstrated as one of the most powerful statistical tools available for automatic speech recognition.In this thesis, a semi-continuous hidden Markov model, which is a very general model including both discrete and continuous mixture hidden Markov models as its special forms, is proposed.It is a model in which vector quantisation, the discrete hidden Markov model, and the continuous mixture hidden Markov model are unified.Based on