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Explicit length modelling for statistical machine translation
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DOI：10.1016/j.patcog.2012.01.006.png)
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Abstract
En 中文
Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods and two alternative parametrisations for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit bilingual length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, a systematic evaluation on reference SMT tasks considering different language pairs proves the benefits of explicit length modelling. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords:
Length modelling
Log-linear models
Phrase-based models
Statistical machine translation
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