Viterbi training vs. Baum-Welch algorithm I'm trying to find the most probable path (i.e., sequence of states) on an hidden Markov model (HMM) using the Viterbi algorithm. However, I don't know the transition and emission matrices, which I need to estimate from the observations (data).

To estimate these matrices, which algorithm should I use: the Baum-Welch algorithm or the Viterbi Training algorithm? Why?

In case I should use the Viterbi training algorithm, can anyone provide me a good pseudocode (it's not easy to find) ?
From my comment:

This answer on crossvalidate.SE may be of use. I wasn't aware of viterbi-training. I have only used BW or other EM-based methods in the past. Based on the answer in the link, I think BW would be the most useful. It seems Viterbi-Training gives no guarantee on bounds. However, the latter does have useful application if BW takes far too long to compute.