Finally, instead of building a parametric predictor for log linear weights, we experimented with a simple nearest-neighbor approach: where M j ranges over the linearly interpolated phrase tables, and λ i (M ) returns the stored optimal value for the i th log-linear weight, and: where s is the monolingual sample on which we want to calculate the BLEU-PT and s ranges over the source sides of our available parallel development sets.
a BLEU-PT of a model is calculated on the source sample to be translated and the log-linear weight is chosen which corresponds to BLEU-PT , where BLEU-PT is a training data point closest to BLEU-PT.