Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation
TABLE IV: Multilingual multi-domain adaptation results (BLEU-4 scores) for ALT-EJ using IWSLT-EC, IWSLT-EJ and KFTT-EJ where multiple target languages exist. The numbers in bold indicate the best scores over all settings.
['No.', 'System', 'ALT-EJ (in-domain)', 'KFTT-EJ', 'IWSLT-EJ', 'IWSLT-EC']
We also conduced experiments when there are multiple target languages. We flipped the translation directions and trained multilingual, multi-domain models for ALT-EJ, KFTT-EJ, IWSLT-EJ and IWSLT-EC. The datasets and model training settings were the same as mentioned in the experimental setting section. Lines 1 and 2 give the scores of the vanilla SMT and NMT models for the tasks. Lines 3 to 8 contain the results of 3 data settings for adaptation (IWSLT-EC for ALT-EJ, IWSLT-EJ_IWSLT-EC for ALT-EJ, and KFTT-EJ_IWSLT-EJ_IWSLT -EC for ALT-EJ) where 2 target languages are available. We skipped other data settings, because they do not involve multiple target languages.