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Titles
English : Arabic to English Morphology Based Statistical Machine Translation System
Abstract The aim of this work is to improve the translation quality of state-of-the-art statistical machine translation systems. We achieve this by optimizing the training process, which is an important phase in building SMT systems. We want to optimize the training process as much as we can to get the most out of the training data available. This can be achieved in two ways: One way requires linguistic resources such as lexicons and morphological analyzers, while the other one makes no use of any linguistic resources.
Publication year 2005
Organization Name
    Central Laboratory for Agricultural Expert System (CLAES)
Department Agricultural Expert System Development
Author(s) from ARC
Agris Categories Documentation and information
Proposed Agrovoc Statistical Machine Translation; Morphology; Word Alignments; Parameter Tuning;
Publication Type Master Thesis

 
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