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IBM alignment models

IBM alignment models are a sequence of increasingly complex models used in statistical machine translation to train a translation model and an… 
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Related topics

Related topics

3 relations
Hidden Markov modelStatistical machine translation

Broader (1)

Machine translation

Papers overview

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2011
2011
Unsupervised Concept Annotation using Latent Dirichlet Allocation and Segmental Methods
Training efficient statistical approaches for natural language understanding generally requires data with segmental semantic… 
2010
2010
Refining Word Alignment with Discriminative Training
The quality of statistical machine translation systems depends on the quality of the word alignments that are computed during the… 
2010
2010
It Depends on the Translation: Unsupervised Dependency Parsing via Word Alignment
We reveal a previously unnoticed connection between dependency parsing and statistical machine translation (SMT), by formulating… 
2005
2005
Maximum Entropy Modeling: A Suitable Framework to Learn Context-Dependent Lexicon Models for Statistical Machine Translation
Current statistical machine translation systems are mainly based on statistical word lexicons. However, these models are usually… 
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