期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2009
卷号：9
期号：11
页码：154-159
出版社：International Journal of Computer Science and Network Security
摘要：Arabic is considered to have a rich morphology compared to English language. This fact adversely affects the performance of English-Arabic Statistical Machine Translation (SMT). Phrase-based SMT models have a limitation of mapping phrases or blocks from the source to the target languages without any use of linguistic information. Incorporating linguistic tools, such as part-of-speech (POS) taggers can have an impact on translation quality. In this paper, the use of POS tagging is incorporated as a linguistic feature in a factored translation model. The use of factored translation model and its impact on translation quality for English-Arabic machine translation is reported.
关键词：Statistical Machine Translation; Phrase Based Model; Part of Speech Tagging; Factored Model; Decoding Algorithm
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