Orthography Standardization in Arabic Dialects Abstract Christian Cayralat1 1 Charles University Spontaneous orthography in Arabic dialects poses one of the biggest ob- stacles in the way of Dialectal Arabic NLP applications. As the Arab world enjoys a wide array of these widely spoken and recently written, non-standard, low-resource varieties, this thesis presents a detailed account of this relatively overlooked phenomenon. It sets out to show that continuously creating addi- tional noise-free, manually standardized corpora of Dialectal Arabic does not free us from the shackles of non-standard (spontaneous) orthography. Because real-world data will most often come in a noisy format, it also investigates ways to ease the amount of noise in textual data. As a proof of concept, we restrict ourselves to one of the dialectal varieties, namely, Lebanese Arabic. It also strives to gain a better understanding of the nature of the noise and its distri- bution. All of this is done by leveraging various spelling correction and morpho- logical tagging neural architectures in a multi-task setting, and by annotating a Lebanese Arabic corpus for spontaneous orthography standardization, and morphological segmentation and tagging, among other features. Additionally, a detailed taxonomy of spelling inconsistencies for...
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:451841 |
| Date | January 2021 |
| Creators | Cayralat, Christian |
| Contributors | Zeman, Daniel, Straňák, Pavel |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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