Goettingen University, Germany
University of Waikato, Room KG11
Hidden Markov Models have been used for more than two decades in signal-processing applications, especially in the context of automatic speech recognition. They are a class of models in which the distribution that generates an observation depends on the state of an underlying and unobserved Markov chain.
The emphasis of the talk will be to give an introduction to the application of the models, in particular touching upon the concepts of model specification, parameter estimation, model selection, diagnostic checking, and forecasting.