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Titles
English : Tuning Statistical Machine Translation Parameters
Abstract Word alignment is the basis of statistical machine translation. GIZA++ is a popular tool for producing word alignments and translation models. It uses a set of parameters that affect the quality of word alignments and translation models. These parameters exist to overcome some problems such as overfitting. This paper addresses the problem of tuning GIZA++ parameter for better translation quality. The results show that our systematic procedure for parameter tuning can improve the translation quality.
URL
Publication year 2004
Pages 15-18
Organization Name
    Central Laboratory for Agricultural Expert System (CLAES)
Country Turkey
Publisher Name: ENFORMATIKA
serial title International Journal of Information Technology
Web Page
ISSN 1305-2403
Volume VOLUME 1 .
Author(s) from ARC
Agris Categories Documentation and information
Proposed Agrovoc Parameter tuning; smoothing factors; training;
Publication Type Journal

 
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