This phrase table is traditionally generated by going through a pipeline of two steps, first generating word (or minimal phrase) alignments, then extracting a phrase table that is consistent with these alignments.
we take a Bayesian approach, integrating over all possible values of the hidden parameters: If θ takes the form of a scored phrase table, we can use traditional methods for phrase-based SMT to find P (e|f , θ) and concentrate on creating a model for P (θ| E, F ).