To search, Click below search items. |
| All Published Papers Search Service |
|
|
|
Title |
Linguistic Factors in Statistical Machine Translation Involving Arabic Language |
|
Author |
Islam Youssef, Mohamed Sakr, Mohamed Kouta |
| Citation |
Vol. 9 No. 11 pp. 154-159 |
|
Abstract |
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. |
|
Keywords |
Statistical Machine Translation, Phrase Based Model, Part of Speech Tagging, Factored Model, Decoding Algorithm |
|
URL |
