Linguistic Input Features Improve Neural Machine Translation
Table 5: English→Romanian translation results: best perplexity on newsdev2016, and Bleu and chrF3 on newstest2016. Bleu scores that are significantly different (p < 0.05) from respective baseline are marked with (*).
['system', 'ppl ↓', 'Bleu ↑', 'chrF3 ↑']
With linguistic features, we observe improvements of 1.0 Bleu over the baseline, both for the systems trained on parallel data only (23.8→24.8), and the systems which use synthetic training data (28.2→29.2). According to Bleu, the best submission to WMT16 was a system combination by \newciteqt21syscomb2016. Our best system is competitive with this submission.