By exponentiating and normalizing score(x, y, h; θ), we obtain a conditional log-linear model, which is useful for training criteria with probabilistic interpretations: The log loss then defines loss i) ).
3 most training procedures periodically invoke the decoder to generate new k-best lists, which are then typically merged with those from previous training iterations.