期刊名称：DESIDOC Journal of Library & Information Technology
电子版ISSN：0976-4658
出版年度：2010
卷号：30
期号：4
页码：25-32
DOI：10.14429/djlit.30.4.457
语种：English
出版社：DESIDOC, Ministry of Defence, India
摘要：Statistical Machine Translation (SMT) systems are based on bilingual sentence aligned data. The quality of translation depends on the data provided for translation learning. A huge parallel corpus is required for performing the statistical machine translation. The aim of this paper is to explore SMT using the Moses toolkit for creating a German-English translator. To perform the German to English translation, a parallel corpus of this language pair has been provided. Larger the size of the data provided for the training of the Moses decoder, more accurate is the translated output.DOI: 10.14429/djlit.30.457
关键词：Statistical machine translation; machine learning; natural language processing; bilingual corpus
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