Name
Abstract | ||
|---|---|---|
Currently there are several approaches to machine translation (MT) based on differ- ent paradigms; e.g., phrasal, hierarchical and syntax-based. These three approaches yield similar translation accuracy despite using fairly different levels of linguistic knowledge. The availability of such a variety of systems has led to a growing interest toward finding better translations by combining outputs from multiple sys- tems. This paper describes three differ- ent approaches to MT system combina- tion. These combination methods oper- ate on sentence, phrase and word level exploiting information from -best lists, system scores and target-to-source phrase alignments. The word-level combination provides the most robust gains but the best results on the development test sets (NIST MT05 and the newsgroup portion of GALE 2006 dry-run) were achieved by combining all three methods. |
Year | Venue | Keywords |
|---|---|---|
2007 | HLT-NAACL | machine translation |
DocType | Citations | PageRank |
Conference | 93 | 5.26 |
References | Authors | |
10 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antti-Veikko I. Rosti | 1 | 337 | 18.86 |
| Necip Fazil Ayan | 2 | 339 | 23.36 |
| Bing Xiang | 3 | 1409 | 78.56 |
| Spyridon Matsoukas | 4 | 180 | 10.21 |
| Richard M. Schwartz | 5 | 2839 | 717.76 |
| Bonnie J. Dorr | 6 | 2150 | 176.78 |