A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Approximation of Discrete Phase-Type Distributions
ANSS '05 Proceedings of the 38th annual Symposium on Simulation
| Hi-index | 0.00 |
In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develop an algorithm that adapts known Hidden Markov Model algorithms for use with proxel-based simulation. It is shown how the Forward- and Viterbi-algorithms can be directly integrated in the proxel-method. The possibility of integrating the more complex Baum-Welch-algorithm is theoretically addressed. Experiments are conducted to determine the practicability of the new approach and to illustrate the type of analysis that is possible.