Machine Translation

, 22:205

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

  • Azza Abdel Monem
  • Khaled Shaalan
  • Ahmed Rafea
  • Hoda Baraka


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.


Machine translation Interlingua Rule-based text generation Natural language generation Arabic natural language processing 

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Azza Abdel Monem
    • 1
  • Khaled Shaalan
    • 2
    • 3
  • Ahmed Rafea
    • 4
  • Hoda Baraka
    • 5
  1. 1.Faculty of Computer and Information SciencesAin Shams UniversityCairoEgypt
  2. 2.School of InformaticsUniversity of EdinburghEdinburghUK
  3. 3.Faculty of InformaticsThe British University in DubaiDubaiUAE
  4. 4.Computer Science DepartmentAmerican University in CairoCairoEgypt
  5. 5.Faculty of EngineeringCairo UniversityGizaEgypt

Personalised recommendations