1 illustrates the scoring process: when a partial translation hypothesis H is expanded by covering a new source phrasef , the model returns the log-probability of translating the words off in that particular order, just after the last translated word of H. In details, this is done by converting the phraseinternal word alignment 4 to a source permutation, in just the same way it was done to produce the model's training examples.
the global score is independent from phrase segmentation, and normalized across outputs of different lengths: that is, the probability of any complete hypothesis decomposes into J factors, where J is the length of the input sentence.