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EMNLP
2009
14 years 9 months ago
Consensus Training for Consensus Decoding in Machine Translation
We propose a novel objective function for discriminatively tuning log-linear machine translation models. Our objective explicitly optimizes the BLEU score of expected n-gram count...
Adam Pauls, John DeNero, Dan Klein
EMNLP
2006
15 years 1 months ago
Phrasetable Smoothing for Statistical Machine Translation
We discuss different strategies for smoothing the phrasetable in Statistical MT, and give results over a range of translation settings. We show that any type of smoothing is a bet...
George F. Foster, Roland Kuhn, Howard Johnson
ACL
2003
15 years 1 months ago
Loosely Tree-Based Alignment for Machine Translation
We augment a model of translation based on re-ordering nodes in syntactic trees in order to allow alignments not conforming to the original tree structure, while keeping computati...
Daniel Gildea
ACL
2012
13 years 2 months ago
Improving the IBM Alignment Models Using Variational Bayes
Bayesian approaches have been shown to reduce the amount of overfitting that occurs when running the EM algorithm, by placing prior probabilities on the model parameters. We appl...
Darcey Riley, Daniel Gildea
EMNLP
2009
14 years 9 months ago
Synchronous Tree Adjoining Machine Translation
Tree Adjoining Grammars have well-known advantages, but are typically considered too difficult for practical systems. We demonstrate that, when done right, adjoining improves tran...
Steve DeNeefe, Kevin Knight