I've been using Hidden Markov Models (HMM) for some time. Now I would like to know about any other statistical model that can prove to be as useful as HMM. For example I was exploiting HMM for gesture recognition. Can other statistical concepts work like HMM, i.e. statistical inference for finding the different parameters such as transition probabilities?
I have heard of Neural Networks and Bayesian statistical inference. Are these concept similar to HMM?
Best Answer
There are some good answers here already, but I thought I'd chime in with one more, which has been used in areas related to gesture recognition.
This paper by Taylor, Hinton, and Roweis is similar to an HMM in the sense that it's a time series model with latent states, but:
1) the structure of the hidden states can be much more complex (many many more possible states) and
2) many of the connections are undirected (as in a conditional random field or a Markov random field) rather than directed.
Figure 2 shows a diagram of the basic model, and the authors have some great videos of what the model can learn on their websites.