Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation
TABLE II: Domain adaptation results (BLEU-4 scores) with one out-of-domain corpus for ALT-JE using KFTT-JE, IWSLT-JE and IWSLT-CE. The numbers in bold indicate the best scores using the same data. The numbers marked with “†” indicate that the results using our proposed methods are significantly better (p <0.05) than the existing black-box methods for the same data setting.
['[BOLD] No.', '[BOLD] KFTT-JE+ALT-JE', '[BOLD] ALT-JE']
We also conducted NMT experiments that simply concatenated the corpora, denoting as “concat” in the table. We can see that using a single out-of-domain corpus improves the in-domain translation. Although the corpus size of KFTT-JE is two times larger than that of IWSLT-JE, the performance is not better besides using mixed fine tuning. This indicates that the size of the out-of-domain corpus is not the only decisive factor for domain adaptation but the method also matters, which also can be indicated in the multiple domain and multilingual multi-domain adaptation results.