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
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
