Capturing document context inside sentence-level neural machine translation models with self-training
Table 2: Ablation study on NIST evaluation sets measuring the effect on multiple passes of decoding and the oracle on self-training procedure. BT: backtranslation. ST: self-training.
['[EMPTY]', 'Model', 'MT06', 'MT03', 'MT04', 'MT05', 'MT08', 'ΔBLEU']
First, multiple decoding passes over the document give an additional average improvement of 0.25−0.45 BLEU points compared to the single decoding pass over the document. Using oracle self-training procedure gives an average of 0.86 and 1.63 BLEU improvement over our non-backtranslated and backtranslated sentence-level baseline models respectively. Compared to using generated translations by the model, oracle self-training gives an improvement of 0.3 and 0.7 BLEU points for non-backtranslated and backtranslated models respectively.