Refereed full papers (journals, book chapters, international conferences)

1989

@article{Rab1989,
	vgclass =	{refpap},
	author =	{Lawrence R. Rabiner},
	title =	{A Tutorial on Hidden {M}arkov Models and Selected
	Applications in Speech Recognition},
	journal =	{Proceedings of the IEEE},
	volume =	{77},
	number =	{2},
	pages =	{257--286},
	month =	{February},
	year =	{1989},
	url =	{http://ieeexplore.ieee.org/iel5/5/698/00018626.pdf},
	url1 =	{http://www.ai.mit.edu/~murphyk/Bayes/rabiner.pdf},
	abstract =	{This tutorial provides an overview of the basic theory of
	hidden Markov models (HMMs) as originated by L.E. Baum and T. Petrie
	(1966) and gives practical details on methods of implementation of the
	theory along with a description of selected applications of the theory
	to distinct problems in speech recognition. Results from a number of
	original sources are combined to provide a single source of acquiring
	the background required to pursue further this area of research. The
	author first reviews the theory of discrete Markov chains and shows how
	the concept of hidden states, where the observation is a probabilistic
	function of the state, can be used effectively. The theory is
	illustrated with two simple examples, namely coin-tossing, and the
	classic balls-in-urns system. Three fundamental problems of HMMs are
	noted and several practical techniques for solving these problems are
	given. The various types of HMMs that have been studied, including
	ergodic as well as left-right models, are described.},
}