Syntactic Generation

Abdel-Monem, A., K. Shaalan, A. Rafea, and H. Baraka, "A Proposed Approach for Generating Arabic from Interlingua in a Multilingual Machine Translation System", Language Engineering conference, Cairo, Egypt, Ain Shams University, pp. 197–206, Oct, 2003. Abstractgen_paper_nlg_conf.pdf

Intelingua (meaning) representation has been successfully used in multilingual machine translation. This paper reports our attempt to generate Arabic sentence from interlingua. The proposed system will be compatible with the NESPOLE consortium. In NESPOLE an Interlingua called interchange format or IF, designed for travel planning is used. Our approach describes how to generate grammatically correct Arabic sentence from Interlingua. It involves two main components a mapper for converting intelingua into syntactic structure (feature-structure) and a generator for generating the target Arabic sentence that represents the intended meaning. A translation example is provided to explain the inner working of the system.

Shaalan, K., A. Abdel-Monem, A. Rafea, and H. Baraka, "Mapping Interlingua Representations to Feature Structures of Arabic Sentences", The Challenge of Arabic for NLP/MT International Conference, the British Computer Society, London, UK, British Computer Society (BCS), pp. 149–159, oct, 2006. Abstractmapping_interlingua2arabic.pdf

The interlingua approach to Machine Translation (MT) aims to achieve the translation task in two independent steps. First, the meanings of source language sentences are represented in an intermediate (interlingua) representation. Then, sentences of the target language are generated from those meaning representations. In the generation of the target sentence, determining sentence structures becomes more difficult, especially when the interlingua does not contain any syntactic information. Hence, the sentence structures cannot be transferred exactly from the interlingua representations. In this paper, we present a mapping approach for taskoriented interlingua-based spoken dialogue that transforms an interlingua representation, so-called Interchange Format (IF), into a feature structure (FS) that reflects the syntactic structure of the target Arabic sentence. This approach addresses the handling of the problem of Arabic syntactic structure determination in the interlingua approach. A mapper 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 FS mapper is implemented in SICStus Prolog. Examples of Arabic syntactic mapping, using the output from the English analyzer provided by Carnegie Mellon University (CMU), will illustrate how the system works.

Shaalan, K., A. A. Monem, A. Rafea, and H. Baraka, "Generating Arabic text from Interlingua", the 2nd Workshop on Computational Approaches to Arabic Script-based Languages (CAASL), Stanford, California, USA, Linguistic Society of America Summer Institute, Stanford University, pp. 137–144, jul, 2007. Abstractcaasl2_mt.pdf

In this paper, we describe a grammar-based generation approach for task-oriented interlingua-based spoken dialogue that transforms a shallow semantic interlingua representation called Interchange Format (IF) into Arabic Text that corresponds to the intentions underlying the speakers' utterances. 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 an evaluation experiment using the output from the English analyzer provided by Carnegie Mellon University (CMU). The results of this experiment were promising and assured the ability of the generation approach in generating Arabic text form the interlingua taken from the travel and tourism domain.

Abdel-Monem, A., K. Shaalan, A. Rafea, and H. Baraka, "Generating Arabic text in multilingual speech-to-speech machine translation framework", Machine Translation, vol. 22, no. 4, Hingham, MA, USA, Kluwer Academic Publishers, pp. 205–258, 2008. Abstractgenerating_arabic_mt_journal.pdfWebsite

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.

Shaalan, K., A. Abdel-Monem, and A. Rafea, "Syntactic Generation of Arabic in Interlingua-based Machine Translation Framework", Third workshop on Computational Approaches to Arabic Script-based Languages (CAASL3), Machine Translation Summit XII: ACL, 2009. Abstractsyntactic_gen_arabic_caasl3.pdf

Arabic is a highly inflectional language, with a rich morphology, relatively free word order, and two types of sentences: nominal and verbal. Arabic natural language processing in general is still underdeveloped and Arabic natural language generation (NLG) is even less developed. In particular, Arabic natural language generation from Interlingua was only investigated using template-based approaches. Moreover, tools used for other languages are not easily adaptable to Arabic due to the Arabic language complexity at both the morphological and syntactic levels. In this paper, we report our attempt at developing a rule-based Arabic generator for task-oriented interlingua-based spoken dialogues. Examples of syntactic generation results from the Arabic generator will be given and will illustrate how the system works. Our proposed syntactic generator has been effectively evaluated using real test data and achieved satisfactory results.

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