| Download | - View accepted manuscript: Combination of Arabic Preprocessing Schemes for Statistical Machine Translation (PDF, 276 KB)
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| Author | Search for: Sadat, F.; Search for: Habash, N. |
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| Format | Text, Article |
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| Conference | International Committee on Computational Linguistics and the Association for ComputationalLinguistics (COLING/ACL 2006), July 17-21, 2006, Sydney, Australia |
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| Abstract | Statistical machine translation is quite robust when it comes to the choice of input representation. It only requires consistency between training and testing. As a result, there is a wide range of possible preprocessing choices for data used in statistical machine translation. This is even more so for morphologically rich languages such as Arabic. In this paper, we study the effect of different word-level preprocessing schemes for Arabic on the quality of phrase-based statistical machine translation. We also present and evaluate different methods for combining preprocessing schemes resulting in improved translation quality. |
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| Publication date | 2006 |
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| In | |
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| Language | English |
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| NRC number | NRCC 48757 |
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| NPARC number | 8913505 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 21a83ebf-dbc5-49f6-9613-e92b3ecd276a |
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| Record created | 2009-04-22 |
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| Record modified | 2020-10-09 |
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