Missing link etc...

[Mahesan Niranjan]

Some recent papers and postings on this network compare HMMs and Multi-layer
neural networks. Here is something I find missing in these discussions.

In speech pattern processing, HMMs make an inherent assumption about
the time series; - that it can be chopped up into a sequence of
piecewise stationary regions. Thus, an HMM places break-points in the
transition regions of the signal and models the steady regions by the
statistical parameters of individual states.

For speech signals, this is a bad assumption (human speech production is
not at all like this) - but the recognisers somehow seem to work!!

In neural networks (with or without feedback) what is the equivalent
assumption about the time evolution of the signal?


niranjan