Name
Abstract | ||
|---|---|---|
The NTT Statistical Machine Translation System employs a large number of feature functions. First, k-best translation candidates are generated by an efficient decoding method of hierarchical phrase-based translation. Second, the k-best translations are reranked. In both steps, sparse binary fea - tures — of the order of millions — are integrated during the search. This paper gives the details of the two steps and shows the results for the Evaluation campaign of the Interna- tional Workshop on Spoken Language Translation (IWSLT) 2007. |
Year | Venue | Keywords |
|---|---|---|
2007 | IWSLT | machine translation |
Field | DocType | Citations |
Rule-based machine translation,Example-based machine translation,Evaluation of machine translation,Computer science,Machine translation,Speech recognition,Synchronous context-free grammar,Machine translation software usability,Natural language processing,Artificial intelligence,Transfer-based machine translation,Computer-assisted translation | Conference | 2 |
PageRank | References | Authors |
0.42 | 26 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taro Watanabe | 1 | 572 | 36.86 |
| Junichi Suzuki | 2 | 1265 | 112.15 |
| Katsuhito Sudoh | 3 | 326 | 34.44 |
| Hajime Tsukada | 4 | 449 | 29.46 |
| Hideki Isozaki | 5 | 934 | 64.50 |