Coverage Embedding Models for Neural Machine Translation
Table 3: Alignment F1 scores of different models.
['system MaxEnt', 'system MaxEnt', 'pre. 74.86', 'rec. 77.10', 'F1 75.96']
The MaxEnt model is trained on 67k hand-aligned data, and achieves an F1 score of 75.96. For NMT systems, we dump alignment matrixes, then, for each target word we only add the highest probability link if it is higher than 0.2. Results show that our best coverage model, UGRU + USub, improves the F1 score by 2.2 points over the sorce of LVNMT.