Simplify-then-Translate: Automatic Preprocessing for Black-Box Translation
Table 2: In-domain vs out-of-domain simplification performance. It is evident that APP models trained on an out-of-domain simplification corpus (WikiLarge) degrades performance, whereas in-domain simplification corpora (FIGS) boosts performance.
['language pair', 'original', 'FigsAPP', 'WikiApp']
FIGS (in-domain) dataset and the WikiLarge (out-of-domain) datasets on the FIGS test set using the BBMT system. The values in columns 1-3 indicate the BLEU score after translating the original sentence and after simplifying using the FigsAPP and WikiAPP models respectively. There is uniform improvement across all languages when using the FigsAPP model, ranging from 3.5% (relative) for En-Uk to 11.6% for En-Bg. On the other hand, performance degrades significantly on all languages when simplified using a model trained on the WikiLarge dataset. Fig. Mean GLEU increases for En-Hu, En-Ro, En-Ms and En-Bg.