Neural Machine Translation (NMT) models (Bahdanau et al., 2014;Luong et al., 2015;Wu et al., 2016;Vaswani et al., 2017) often operate with fixed word vocabularies, as their training and inference depend heavily on the vocabulary size.
limiting vocabulary size increases the amount of unknown words, which makes the translation inaccurate especially in an open vocabulary setting.