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Arabic Morphological Representations for Machine Translation

  • Chapter
Arabic Computational Morphology

Part of the book series: Text, Speech and Language Technology ((TLTB,volume 38))

Abstract

Arabic has a very rich morphology characterized by a combination of templatic and affixational morphemes, complex morphological rules, and a rich feature system. This complexity makes working with Arabic as a source of target language in machine translation (MT) a challenge for two reasons. First, it is not clear what the right representation is for two reasons. First, it is not clear what the right representation is for Arabic words given a specific MT approach or system. And secondly, there are many MT-relevant resources for Arabic morphology, lexicography and syntax (e.g., morphological analyzers, dictionaries and treebanks) that adopt various representations that are not necessarily compatible with each other. The result is that for MT researchers, there is a need to experiment with and to relate multiple representations used by different resources or components to each other within a single system. In this chapter, we describe different Arabic morphological representations used by MT-relevant natural language processing resources and tools and we discuss their usability in different MT approaches. We also present a common framework for relating different levels of representations to each other

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Author information

Authors and Affiliations

  1. Center for Computational Learning Systems, Columbia University, 3022 Broadway, New York

    Nizar Habash

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  1. Nizar Habash
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Editor information

Editors and Affiliations

  1. Ecole Nationale de I’Industrie Minérale, Rabat, Morocco

    Abdelhadi Soudi

  2. Tilburg University, The Netherlands

    Antal van den Bosch

  3. Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken, Germany

    Günter Neumann

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Habash, N. (2007). Arabic Morphological Representations for Machine Translation. In: Soudi, A., Bosch, A.v., Neumann, G. (eds) Arabic Computational Morphology. Text, Speech and Language Technology, vol 38. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6046-5_14

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