Contextual Neural Machine Translation Improves Translation of Cataphoric Pronouns
Table 3: BLEU for the Transformer baseline and Transformer-HAN with following sentence (k = +1) and previous sentence (k = -1). ♠: Statistically significantly better than HAN (k = -1).
['[BOLD] Lang. Pair', '[BOLD] Baseline', '[BOLD] HAN( [ITALIC] k = +1)', '[BOLD] HAN( [ITALIC] k = -1)']
We consider two versions of the Transformer-HAN respectively trained with the following and previous source sentence as context. Further, HAN (k = +1) demonstrates statistically significant improvements over the HAN (k = -1) when translating to English. These results are quite surprising as \newciteVoita:18 report decreased translation quality in terms of BLEU when using the following sentence for English→Russian Subtitles. To identify if this discrepancy is due to the language-pair or the model, we conduct experiments with English→Russian in the same data setting as \newciteVoita:18 and find that HAN (k = +1) still significantly outperforms the Transformer and is comparable to HAN (k = -1) (more details in Appendix LABEL:section:app-enru).