A Smorgasbord of Features for Statistical Machine Translation

@inproceedings{SimonFraser2004ASO,
  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},
  year={2004}
}
  • 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
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