Morat's answer is false on one point: Baum-Welch is an Expectation-Maximization algorithm, used to train an HMM's parameters. It uses the forward-backward algorithm during each iteration. The forward-backward algorithm really is just a combination of the forward and backward algorithms: one forward pass, one backward pass. On its own, the forward-backward algorithm is not used for training an HMM's parameters, but only for smoothing: computing the marginal likelihoods of a sequence of states.
https://en.wikipedia.org/wiki/Forward%E2%80%93backward_algorithm