.png){kind=icon}
.png){kind=icon}
返回
Explicit length modelling for statistical machine translation
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patcog.2012.01.006.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
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.
Keyword:
Length modelling
Log-linear models
Phrase-based models
Statistical machine translation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。