El-Haj, M. and Rayson, P. and Aboelezz, Mariam (2018) Arabic dialect identification in the context of bivalency and code-switching. In: UNSPECIFIED (ed.) LREC 2018, Eleventh International Conference on Language Resources and Evaluation. Paris, France: European Language Resources Association, pp. 3622-3627. ISBN 9791095546009.
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Abstract
In this paper we use a novel approach towards Arabic dialect identification using language bivalency and written code-switching. Bivalency between languages or dialects is where a word or element is treated by language users as having a fundamentally similar semantic content in more than one language or dialect. Arabic dialect identification in writing is a difficult task even for humans due to the fact that words are used interchangeably between dialects. The task of automatically identifying dialect is harder and classifiers trained using only n-grams will perform poorly when tested on unseen data. Such approaches require significant amounts of annotated training data which is costly and time consuming to produce. Currently available Arabic dialect datasets do not exceed a few hundred thousand sentences, thus we need to extract features other than word and character n-grams. In our work we present experimental results from automatically identifying dialects from the four main Arabic dialect regions (Egypt, North Africa, Gulf and Levant) in addition to Standard Arabic. We extend previous work by incorporating additional grammatical and stylistic features and define a subtractive bivalency profiling approach to address issues of bivalent words across the examined Arabic dialects. The results show that our new methods classification accuracy can reach more than 76% and score well (66%) when tested on completely unseen data.
Metadata
| Item Type: | Book Section |
|---|---|
| Keyword(s) / Subject(s): | Arabic, language identification, dialects, machine learning, NLP, corpus linguistics |
| School: | Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Creative Arts, Culture and Communication |
| Depositing User: | Mariam Aboelezz |
| Date Deposited: | 17 Dec 2018 15:25 |
| Last Modified: | 09 Aug 2023 12:45 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/25535 |
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