@proceedings {4534,
	title = {A smorgasbord of features for statistical machine translation.},
	year = {2004},
	month = {2004 May},
	abstract = {<p>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 n-best list. Feature weights were optimized directly against the BLEU evaluation metric on held-out data. We present results for a small selection of features at each level of syntactic representation.</p>
},
	author = {Och, Franz J. and Gildea, Daniel and Khudanpur, Sanjeev and Sarkar, Anoop and Yamada, Kenji and Fraser, Alex and Kumar, Shankar and Shen, Libin and Smith, David and Eng, Katherine and Jain, Viren and Jin, Zhen and Radev, Dragomir}
}
