A Smorgasbord of Features for Statistical Machine Translation

  title={A Smorgasbord of Features for Statistical Machine Translation},
  author={U. SimonFraser and Xerox XRCE and U. JohnsHopkins and Univ Jennifer Stanford and Mt. Holyoke},
  • U. SimonFraser, Xerox XRCE, +2 authors Mt. Holyoke
  • Published 2004
We describe a methodology for rapid experimentation in statistical machine translation which we use to add a large number of features to a baseline system exploiting features from a wide range of levels of syntactic representation. Feature values were combined in a log-linear model to select the highest scoring candidate translation from an -best list. Feature weights were optimized directly against the BLEU evaluation metric on held-out data. We present results for a small selection of… CONTINUE READING
Highly Influential
This paper has highly influenced 26 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 316 citations. REVIEW CITATIONS


Publications citing this paper.

317 Citations

Citations per Year
Semantic Scholar estimates that this publication has 317 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.

Similar Papers

Loading similar papers…