We consider those in the remainder of this section.
a hidden Markov model (HMM) specifies a normalized joint distribution p θ (x, y) = exp G T over state sequence y and observation sequence x, 3 the posterior p θ (y | x) is proportional to exp G T , as required by equation (1).