Name
Title | ||
|---|---|---|
Alignment Symmetrization Optimization Targeting Phrase Pivot Statistical Machine Translation |
Abstract | ||
|---|---|---|
An important step in mainstream statistical machine translation (SMT) is combining bidirectional alignments into one alignment model. This process is called symmetrization. Most of the symmetrization heuristics and models are focused on direct translation (source-to-target). In this paper, we present symmetrization heuristic relaxation to improve the quality of phrasepivot SMT (source-[pivot]-target). We show positive results (1.2 BLEU points) on Hebrew-to-Arabic SMT pivoting on English. |
Year | Venue | DocType |
|---|---|---|
2014 | EAMT | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmed El Kholy | 1 | 182 | 9.82 |
| Nizar Habash | 2 | 0 | 1.35 |