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Generating Arabic text in multilingual speech-to-speech machine translation framework

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Machine Translation

Abstract

The interlingual approach to machine translation (MT) is used successfully in multilingual translation. It aims to achieve the translation task in two independent steps. First, meanings of the source-language sentences are represented in an intermediate language-independent (Interlingua) representation. Then, sentences of the target language are generated from those meaning representations. Arabic natural language processing in general is still underdeveloped and Arabic natural language generation (NLG) is even less developed. In particular, Arabic NLG from Interlinguas was only investigated using template-based approaches. Moreover, tools used for other languages are not easily adaptable to Arabic due to the language complexity at both the morphological and syntactic levels. In this paper, we describe a rule-based generation approach for task-oriented Interlingua-based spoken dialogue that transforms a relatively shallow semantic interlingual representation, called interchange format (IF), into Arabic text that corresponds to the intentions underlying the speaker’s utterances. This approach addresses the handling of the problems of Arabic syntactic structure determination, and Arabic morphological and syntactic generation within the Interlingual MT approach. The generation approach is developed primarily within the framework of the NESPOLE! (NEgotiating through SPOken Language in E-commerce) multilingual speech-to-speech MT project. The IF-to-Arabic generator is implemented in SICStus Prolog. We conducted evaluation experiments using the input and output from the English analyzer that was developed by the NESPOLE! team at Carnegie Mellon University. The results of these experiments were promising and confirmed the ability of the rule-based approach in generating Arabic translation from the Interlingua taken from the travel and tourism domain.

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Authors and Affiliations

  1. Faculty of Computer and Information Sciences, Ain Shams University, Abbassia, Cairo, 11566, Egypt

    Azza Abdel Monem

  2. School of Informatics, University of Edinburgh, Edinburgh, UK

    Khaled Shaalan

  3. Faculty of Informatics, The British University in Dubai, P.O. Box 502216, Dubai, UAE

    Khaled Shaalan

  4. Computer Science Department, American University in Cairo, 113, Sharia Kasr El-Aini, P.O. Box 2511, Cairo, 11511, Egypt

    Ahmed Rafea

  5. Faculty of Engineering, Cairo University, Dokki, Orman, Giza, 12613, Egypt

    Hoda Baraka

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  1. Azza Abdel Monem
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  2. Khaled Shaalan
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  3. Ahmed Rafea
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Correspondence to Khaled Shaalan.

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Abdel Monem, A., Shaalan, K., Rafea, A. et al. Generating Arabic text in multilingual speech-to-speech machine translation framework. Machine Translation 22, 205–258 (2008). https://doi.org/10.1007/s10590-009-9054-9

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