Single-Queue Decoding for Neural Machine Translation
Table 1: Evaluation results on ASPEC En-Ja task with a beam size of 5
['[EMPTY]', 'BLEU(%) valid', 'BLEU(%) test', '#step', 'time (ms)']
The results show that the proposed single-queue decoding (SQD) algorithm significantly improves the quality of translations. With the length matching penalty (LMP), SQD outperforms beam search with length-normalization by 1.14 BLEU on test set. Without the progress penalty (PG), the scores are much worse.