Difference between revisions of "Watanabe et al., EMNLP 2007. Online Large-Margin Training for Statistical Machine Translation"
From Cohen Courses
Jump to navigationJump to search| Line 6: | Line 6: | ||
== Summary == | == Summary == | ||
| − | This paper basically introduces an online discriminative large-margin training approach to statistical machine translation. The authors achieved the then state of the art performance on an Arabic-English translation task by tuning a combination of millions of features in an MT system. | + | This paper basically introduces an online discriminative large-margin training approach to statistical machine translation. The authors achieved the then state of the art performance on an Arabic-English translation task by tuning a combination of millions of features in an MT system. By following this approach the authors also addressed the problem of scaling machine translation systems with a large number of features of the order of millions. |
== Method == | == Method == | ||
Revision as of 23:49, 23 September 2011
Citation
Taro Watanabe, Jun Suzuki, Hajime Tsukada, Hideki Isozaki. 2007. Online large-margin training for statistical machine translation. In Proceedings of EMNLP-CoNLL. pp 764–773
Online Version
Online large-margin training for statistical machine translation
Summary
This paper basically introduces an online discriminative large-margin training approach to statistical machine translation. The authors achieved the then state of the art performance on an Arabic-English translation task by tuning a combination of millions of features in an MT system. By following this approach the authors also addressed the problem of scaling machine translation systems with a large number of features of the order of millions.
