Web-Based Corpus Compilation of the Emirati A rabic Dialect (2025)

Abstract: This paper displays some initial efforts conducted in the compilation pursuits of Arabic dialectal corpora in the form of raw text, the end purpose of which is to fine-tune existing Arabic large language models (LLM) to better understand and generate text in the Emirati dialect as instructed. The focus of the paper is on the process of compiling corpora from the web, which includes the exploration of possible methods, tools and techniques specific to web search, as well as examples of genres and domains to explore. The results of these efforts and the importance of native speaker contributions to corpus compilation for low-resource languages are also touched upon.

## introduction the combined efforts of researchers and professionals within arabic natural language processing (nlp) have yielded several notable achievements in the field. of these are the continued endeavors in corpus collection for under-represented dialectal arabic (da). much of the work has been notable for the egyptian dialect, for its accessibility and abundance of popular culture and media across the arabic-speaking regions @xcite . other dialects remain with less resources, due to several factors including the scarcity of their usage on the web and in published works, which are the most accessible forms of corpora compilation. collecting appropriate and satisfactory dialectal corpora is integral to the development of suitable nlp tools for their usage in further applications. while modern standard arabic (msa) still faces existing challenges in its processing, several tools have focused on solving these issues, aided by the standard rules of msa. da, however, suffers from the issues being at a larger scale, with problems mostly dealing with the inconsistent orthography of the written dialects, and in some cases (such as in egyptian, saudi, and jordanian), their regional variety. in addition, morphological and phonological differences are highly prominent between dialects, so there is little to no standard when it comes to processing dialects, and even less of a standard in the search for their web corpora. llm fine-tuning depends in its root on the availability of a large number of words serving as corpora in the dialect of choice. these corpora of mere raw text are collected and developed with multiple factors in mind, including the variety and specification of domains, the frequency of dialectal words and expressions in different contexts, and the relevance of the data to the intended applications of the language model, if they exist @xcite . it is defining for any corpus to be as representative and diverse as possible, as well as ensuring the validity of the data collected in a certain dialect. bearing the previous criteria in mind, the collection of da corpora on the web is faced with challenges in meeting them. such issues can be pointed out in the following: for this paper, there will be an exploration of the different methods used to search for and col- source genre type al-mal channel economics articles coolnona general blog hamdan bin mohammed heritage center culture docs uae.gulf7.com general forum emirates reddit general social baynounah tv culture subs this section highlights some of the existing efforts in low-resource language web corpus collection as well as specific efforts within da collection. hoenen et al. 2020 provide a documented approach to the collection of low resource languages, including different tools and scenarios. they offer a definition to low resource languages and classifications, and multiple ways to access their web corpora. these include accessing social media as well as querying search engines, namely google. the paper also contains a step-by-step guide to the manipulation of search queries, through single queries, multiple queries, or using operators. of the similar papers concerned with the same challenges and issues as this paper is the bahrain corpus by @xcite , where the authors discuss the phonological and morphological challenges in the collection of da and offer morphological annotation to a special corpus for the bahraini dialect. almeman and lee, 2013 offered the same premise, using wordlists which are specific to dialects, narrowing down search results. they highlight the need for written da corpora, as most da is spoken rather than written online. their process was concerned with four categories of dialects: gulf, egyptian, north african, and levantine, rather than country-specific dialect corpora collection, which is the purpose of this paper. regarding the collection of emirati specific corpora, efforts by alazzam et al., 2024 involve collecting idioms and phrases from the web. the sources included websites, social media, language blogs, and radio channels in the dialect. the main genre of interest to the researchers was the traditional and idiomatic usage of the dialect, and as such, the representativeness of the corpus was limited to a certain field of phrases used in emirati. the paper also offers qualitative analysis of some emirati phrases and their usages, and the data was manually gathered and extracted. ## corpus collection methodology ## search results and discussion the search efforts, focused on diversity and representation, yielded 18 different sources ready for extraction, showed in figure1. of the genres, general texts were the most prevalent. of these general texts, forums were easier to find, followed by blogs and subtitles. general texts do not cover a particsource format word count articles1 txt 2,500 articles2 doc 13,000 book1 txt 373,400 forum1 csv 272,559 forumstory1 doc 140,000 subtitles1 txt 7,000 subtitles2 doc 7,000 subtitles3 csv 3,436 the cultural resources obtained were the property of official emirati heritage preservation institutions and contained multiple heritage-related explanation chapters written in traditional emirati, making them very valuable resources. blogs found were often personal, promotional, or domainspecific regarding a certain niche. ## conclusion the scope of this paper was the search for emirati arabic sources online. while it did not touch on the cleaning and annotation efforts, it presented some of the available tools and resources which a corpus researcher may use and the process to follow when searching for emirati representative corpora. this is done in hopes of advancing the efforts in making dialectal corpora more accessible and encourage the creation of more tools to help with the search, extraction, and processing of da for the purpose of creating raw text datasets to train language models on these underrepresented arabic variations.