Machine Translation on newstest En-Cs 2015 (test2)
18.93BLEUBi-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 | 18.93 | |
| Base Character-level NMT (Row i)Target=Char, Depth=2, Attention=Concatenated, Model=Base, Ensemble=true2016.03 | 18.92 | |
| State-of-the-art Non-Neural ApproachApproach=Non-Neural2016.03 | 18.2 | |
| Base BPE-level NMT (Row h)Target=BPE, Depth=2, Attention=Concatenated, Model=Base, Ensemble=true2016.03 | 17.61 | |
| Base Character-level NMT (Row i)Target=Char, Depth=2, Attention=Concatenated, Model=Base, Ensemble=false2016.03 | 16.98 | |
| Bi-scale Character-level NMT (Row j)Target=Char, Depth=2, Attention=Concatenated, Model=Bi-S, Ensemble=false2016.03 | 16.86 | |
| Base BPE-level NMT (Row h)Target=BPE, Depth=2, Attention=Concatenated, Model=Base, Ensemble=false2016.03 | 14.63 |