The predictor networks are trained using large parallel texts (potentially erroneous learner sentences and their corresponding humancorrected sentences).
the knowledge from the predictor network is transferred to the estimator network that is trained to estimate the quality scorê q given the source sentence S and its corresponding system hypothesis H. a pretrained predictor network takes as input S and H (in place of the target sentence) and predicts probability scores for words in H. the intuition is that hypothesis words that are likely to match the reference sentence will be assigned higher probabilities.