Morphological Generation

Showing results in 'Publications'. Show all posts
Shaalan, K., Y. Samih, M. Attia, P. Pecina, and J. van Genabith, "Arabic Word Generation and Modelling for Spell Checking", The eighth international conference on Language Resources and Evaluation (LREC'12), Istanbul, Turkey, 24 May , 2012. Abstract603_paper.pdf

Arabic is a language known for its rich and complex morphology. Although many research projects have focused on the problem of Arabic morphological analysis using different techniques and approaches, very few have addressed the issue of generation of fully inflected words for the purpose of text authoring.
Available open-source spell checking resources for Arabic are too small and inadequate. Ayaspell, for example, the official resource used with OpenOffice applications, contains only 300,000 fully inflected words. We try to bridge this critical gap by creating an adequate, open-source and large-coverage word list for Arabic containing 9,000,000 fully inflected surface words. Furthermore, from a large list of valid forms and invalid forms we create a character-based tri-gram language model to approximate knowledge about permissible character clusters in Arabic, creating a novel method for detecting spelling errors. Testing of his language model gives a precision of 98.2% at a recall of 100%. We take our research a step further by creating a context-independent spelling correction tool using a finite-state automaton that measures the edit distance between input words and candidate corrections, the Noisy Channel Model, and knowledge-based rules. Our system performs significantly better than Hunspell in choosing the best solution, but it is still below the MS Spell Checker.

Shaalan, K., H. Talhami, and I. Kamel, "Automatic Morphological Generation for the Indexing of Arabic Speech Recordings", The International Journal of Computer Processing of Oriental Languages (IJCPOL), vol. 20, no. 1, pp. 1–14, 2007. Abstractijcpol2.pdfWebsite

This paper presents a novel Arabic morphological generator (AMG) for Modern Standard Arabic (MSA) which is designed and implemented using Prolog. The AMG is used to generate inflected forms of words used for the indexing of Arabic audio. These words are also the relevant terms in the Arab authority system (library information retrieval system) used in this study. The AMG generates inflected Arabic words from the root according to pre-specified morphological features that can be extended as needed. The Arabic word is represented as a feature structure which is handled through unification during the morphological generation process. The inflected forms can then be inserted automatically into a speech recognition grammar which is used to identify these words in an audio sequence or utterance.

Shaalan, K., A. Abdel-Monem, and A. Rafea, "Arabic Morphological Generation from Interlingua: A Rule-based Approach", Intelligent Information Processing III, vol. 228: Springer US, pp. 441-451, 2007. Abstractmorph_gen_mt.pdf

Arabic is a Semitic language that is rich in its morphology. Arabic has very numerous and complex morphological rules. Arabic morphological analysis has gained the focus of Arabic natural language processing research for a long time in order to achieve the automated understanding of Arabic. With the recent technological advances, Arabic natural language generation has received attentions in order to allow for a room for wider applications such as machine translation. For machine translation systems that support a large number of languages, interlingua-based machine translation approaches are particularly attractive. In this paper, we report our attempt at developing a rule-based Arabic morphological generator for task-oriented interlingua-based spoken dialogues. Examples of morphological generation results from the Arabic morphological generator will be given and will illustrate how the system works. Nevertheless, we will discuss the issues related to the morphological generation of Arabic words from an interlingua representation, and present how we have handled them.

Shaalan, K., H. Talhami, and I. Kamel, "A Morphological Generator for the Indexing of Arabic Audio", the Proceedings of The IASTED International Conference on Artificial Intelligence and Soft Computing (ASC), Benidorm, Spain, ACTA Press, pp. 307–312, September, 2005. Abstractmorph_audio.pdf

This paper presents a novel Arabic morphological generator (AMG) for Modern Standard Arabic (MSA) which is designed and implemented using Prolog. The AMG is used to generate inflected forms of words used for the indexing of Arabic audio. These words are also the relevant terms in the Arab authority system (library information retrieval system) used in this study. The AMG generates inflected Arabic words from the root according to pre-specified morphological features that can be extended as needed. The Arabic word is represented as a feature structure which is handled through unification during the morphological generation process. The inflected forms can then be inserted automatically into a speech recognition grammar which is used to identify these words in an audio sequence or utterance.