I was reading the book by Jurafsky and this is written by the author on HMM

Although in principle the forward-backward algorithm can do completely unsu- pervised learning of the A and B parameters, in practice the initial conditions are very important. For this reason the algorithm is often given extra information. For example, for HMM-based speech recognition, the HMM structure is often set by hand, and only the emission (B) and (non-zero) A transition probabilities are trained from a set of observation sequences O.

My question is, what exactly is the author trying to say? What is the extra information given? And in the example, I don't see any extra information. What does it mean to set the HMM structure by hand?



Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.