Machine Translation on newstest En-Cs 2014 (test)
22.15BLEUBi-scale Character-level NMT (Row j)
Evaluation results
| Method | Links | |
|---|---|---|
| Bi-scale Character-level NMT (Row j)Target=Char, Depth=2, Attention=Concatenated, Model=Bi-S, Ensemble=true2016.03 | 22.15 | |
| Base Character-level NMT (Row i)Target=Char, Depth=2, Attention=Concatenated, Model=Base, Ensemble=true2016.03 | 21.95 | |
| State-of-the-art Non-Neural ApproachApproach=Non-Neural2016.03 | 21 | |
| Base BPE-level NMT (Row h)Target=BPE, Depth=2, Attention=Concatenated, Model=Base, Ensemble=true2016.03 | 20.79 | |
| Bi-scale Character-level NMT (Row j)Target=Char, Depth=2, Attention=Concatenated, Model=Bi-S, Ensemble=false2016.03 | 19.27 | |
| Base Character-level NMT (Row i)Target=Char, Depth=2, Attention=Concatenated, Model=Base, Ensemble=false2016.03 | 19.25 | |
| Base BPE-level NMT (Row h)Target=BPE, Depth=2, Attention=Concatenated, Model=Base, Ensemble=false2016.03 | 17.16 |