Translating Pro-Drop Languages with Reconstruction Models
Table 9: Translation performance gap (“△”) between manually (“Manual”) and automatically (“Automatic”) labelling DPs for input sentences in testing.
['[BOLD] Model', '[BOLD] Automatic', '[BOLD] Manual', '△']
For each sentence in testing, the DPs are labelled automatically by a DP generator model, the accuracy of which is 65.21% measured in F1 score. The labelling errors may propagate to the NMT models, and have the potential to negatively affect translation performance. The analysis firstly shows that there still exists a significant gap in performance, and this could be improved by improving the accuracy of DP generator. Secondly, our models show a relatively smaller distance in performance from the oracle performance (“Manual”), indicating that the proposed approach is more robust to labelling errors.