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ACL
2012
11 years 8 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
13 years 4 months ago
Extending Statistical Machine Translation with Discriminative and Trigger-Based Lexicon Models
In this work, we propose two extensions of standard word lexicons in statistical machine translation: A discriminative word lexicon that uses sentence-level source information to ...
Arne Mauser, Sasa Hasan, Hermann Ney
ACL
2008
13 years 7 months ago
Better Alignments = Better Translations?
Automatic word alignment is a key step in training statistical machine translation systems. Despite much recent work on word alignment methods, alignment accuracy increases often ...
Kuzman Ganchev, João Graça, Ben Task...
ACL
2007
13 years 7 months ago
Guiding Statistical Word Alignment Models With Prior Knowledge
We present a general framework to incorporate prior knowledge such as heuristics or linguistic features in statistical generative word alignment models. Prior knowledge plays a ro...
Yonggang Deng, Yuqing Gao
IBPRIA
2003
Springer
13 years 11 months ago
Combining Phrase-Based and Template-Based Alignment Models in Statistical Translation
In statistical machine translation, single-word based models have an important deficiency; they do not take contextual information into account for the translation decision. A poss...
Jesús Tomás, Francisco Casacuberta