A New Family of Extended Baum-Welch Update Rules DimitriKanevskyauthorDanielPoveyauthorBhuvanaRamabhadranauthorIrinaRishauthorTaraSainathauthorIn this paper, we consider a generalization of the state-of-art
discriminative method for optimizing the conditional likelihood in
Hidden Markov Models (HMMs), called the Extended Baum-Welch (EBW)
algorithm, that has had significant impact on the speech recognition
community. We propose a generalized form of EBW update rules that
can be associated with a weighted sum of updated and initial models,
and demonstrate that using novel update rules can significantly
speed up parameter estimation for Gaussian mixtures.Speech2008-04-27Preprint