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» Variational Decoding for Statistical Machine Translation
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ACL
2012
11 years 9 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
ACL
2006
13 years 8 months ago
Statistical Phrase-Based Models for Interactive Computer-Assisted Translation
Obtaining high-quality machine translations is still a long way off. A postediting phase is required to improve the output of a machine translation system. An alternative is the s...
Jesús Tomás, Francisco Casacuberta
COLING
2008
13 years 8 months ago
Improving Statistical Machine Translation using Lexicalized Rule Selection
This paper proposes a novel lexicalized approach for rule selection for syntax-based statistical machine translation (SMT). We build maximum entropy (MaxEnt) models which combine ...
Zhongjun He, Qun Liu, Shouxun Lin
COLING
2010
13 years 2 months ago
An Efficient Shift-Reduce Decoding Algorithm for Phrased-Based Machine Translation
In statistical machine translation, decoding without any reordering constraint is an NP-hard problem. Inversion Transduction Grammars (ITGs) exploit linguistic structure and can w...
Yang Feng, Haitao Mi, Yang Liu, Qun Liu
ACL
2008
13 years 8 months ago
A Discriminative Latent Variable Model for Statistical Machine Translation
Large-scale discriminative machine translation promises to further the state-of-the-art, but has failed to deliver convincing gains over current heuristic frequency count systems....
Phil Blunsom, Trevor Cohn, Miles Osborne