Improving Simultaneous Translation by Incorporating Pseudo-References with Fewer Reorderings
Junkun Chen, Renjie Zheng, Atsuhito Kita, Mingbo Ma, Liang Huang · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · 2021
Simultaneous translation is vastly different from full-sentence translation, in the sense that it starts translation before the source sentence ends, with only a few words delay.However, due to the lack of large-scale, high-quality simultaneous translation datasets, most such systems are still trained on conventional fullsentence bitexts.This is far from ideal for the simultaneous scenario due to the abundance of unnecessary long-distance reorderings in those bitexts.We propose a novel method that rewrites the target side of existing fullsentence corpora into simultaneous-style translation.Experiments on Zh!En and Ja!En simultaneous translation show substantial improvements (up to +2.7 BLEU) with the addition of these generated pseudo-references.