The Alignment Template Approach to Statistical Machine Translation

DOI10.1162/0891201042544884zbMath1234.68429OpenAlexW2119168550WikidataQ61908416 ScholiaQ61908416MaRDI QIDQ3225419

Hermann Ney, Franz Josef Och

Publication date: 20 March 2012

Published in: Computational Linguistics (Search for Journal in Brave)

Full work available at URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.1291

zbMATH Keywords

statistical machine translationalignment templatesource-channel approach

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Natural language processing (68T50) Linguistics (91F20)

Related Items (8)

Learning finite-state models for machine translation ⋮ Word-Level Confidence Estimation for Machine Translation ⋮ Hierarchical Phrase-Based Translation ⋮ \texttt{word.alignment}: an \texttt{R} package for computing statistical word alignment and its evaluation ⋮ A word alignment model based on multiobjective evolutionary algorithms ⋮ Statistical machine translation enhancements through linguistic levels ⋮ The Power of Weighted Regularity-Preserving Multi Bottom-Up Tree Transducers ⋮ Machine Translation and Type Theory

Cites Work

• A Systematic Comparison of Various Statistical Alignment Models
• Word Reordering and a Dynamic Programming Beam Search Algorithm for Statistical Machine Translation
• Generalized Iterative Scaling for Log-Linear Models

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