Here the gradient of the Q function can be measured by: The forward-backward algorithm is used to measure p(y t−1 i , y t i |x i , v i ; Λ) and p(y t−1 i , y t i |x i ; Λ).
the objective function Equation (5) is optimized as follows: for the instances i = 1, 2, ..., l, the parameters Λ are learned as the supervised manner; for the instances i = l + 1, l + 2, ..., u + l, in the E-step, the expected value of Q function is computed, based on the current model Λ g .