How HMM's are used.

The Baum-Welch algorithm is an algorithm for estimating the parameters of the HMM from training data. The HMM is a complete statistical model for the series of measurements $ {\bf z}_1,{\bf z}_2,\ldots,{\bf z}_T$ and therefore defines the probability density function $ p({\bf z}_1,{\bf z}_2,\ldots,{\bf z}_T)$. Therefore, once the parameters have been determined, it is easy to use the HMM as a classifier. Furthermore, it is also easy to generate "typical" measurement sequences. This aspect of the HMM has always fascinated me since in principle, it would be possible to train an HMM on a specific human speaker, then create totally random ``jibberish" that sounded like the same speaker. I have always wondered if certain politicians are already using such a device. For further information on HMM's, the reader is referred to the tutorial by Rabiner [57].



Baggenstoss 2017-05-19