Efficient Training Algorithms for HMMs Using Incremental Estimation (2007)
Yoshihiko Gotoh, Michael M. Hochberg, Harvey F. Silverman
Typically, parameter estimation for a hidden Markov model (HMM) is performed using an expectation-maximization (EM) algorithm with the maximum-likelihood (ML) criterion. The EM algorithm is an...
Using Map Estimated Parameters To Improve HMM Speech Recognition Performance (1994)
Yoshihiko Gotoh, Michael M. Hochberg, Harvey F. Silverman
Hidden Markov models (HMMs) have been quite successfully applied to speech recognition tasks, but many unsolved problems still remain. HMMs do not directly model all phenomena that might be useful...
Incremental Map Estimation Of HMMs For Efficient Training And Improved Performance
Yoshihoko Gotoh, Michael M. Hochberg, Daniel J. Mashao, Harvey F. Silverman
Continuous density observation hidden Markov models (CD-HMMs) have been shown to perform better than their discrete counterparts. However, because the observation distribution is usually represented...