An integrated environment for hidden Markov models-a Scilab toolbox
- 24 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
A hidden Markov model toolbox is presented within the Scilab environment. In this toolbox popular methods for the resolution of HMM problems are incorporated. These methods cover the training and recognition phases. Models may be used with discret and continuous observations. This toolbox includes conventional methods as well as extensions.Keywords
This publication has 9 references indexed in Scilit:
- Maximum mutual information estimation of hidden Markov model parameters for speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- A minimum discrimination information approach for hidden Markov modelingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- On-line estimation of hidden Markov model parameters based on the Kullback-Leibler information measureIEEE Transactions on Signal Processing, 1993
- A tutorial on hidden Markov models and selected applications in speech recognitionProceedings of the IEEE, 1989
- Maximum-Likelihood Estimation for Mixture Multivariate Stochastic Observations of Markov ChainsAT&T Technical Journal, 1985
- An Introduction to the Application of the Theory of Probabilistic Functions of a Markov Process to Automatic Speech RecognitionBell System Technical Journal, 1983
- Maximum likelihood estimation for multivariate observations of Markov sourcesIEEE Transactions on Information Theory, 1982
- A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov ChainsThe Annals of Mathematical Statistics, 1970
- Error bounds for convolutional codes and an asymptotically optimum decoding algorithmIEEE Transactions on Information Theory, 1967