The first large scale collection of diverse Hausa language datasets

• URL: http://arxiv.org/abs/2102.06991v2
• Date: Tue, 16 Feb 2021 20:13:34 GMT
• Title: The first large scale collection of diverse Hausa language datasets
• Authors: Isa Inuwa-Dutse
• Abstract summary: Hausa is considered well-studied and documented language among the sub-Saharan African languages. It is estimated that over 100 million people speak the language. We provide an expansive collection of curated datasets consisting of both formal and informal forms of the language.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Hausa language belongs to the Afroasiatic phylum, and with more first-language speakers than any other sub-Saharan African language. With a majority of its speakers residing in the Northern and Southern areas of Nigeria and the Republic of Niger, respectively, it is estimated that over 100 million people speak the language. Hence, making it one of the most spoken Chadic language. While Hausa is considered well-studied and documented language among the sub-Saharan African languages, it is viewed as a low resource language from the perspective of natural language processing (NLP) due to limited resources to utilise in NLP-related tasks. This is common to most languages in Africa; thus, it is crucial to enrich such languages with resources that will support and speed the pace of conducting various downstream tasks to meet the demand of the modern society. While there exist useful datasets, notably from news sites and religious texts, more diversity is needed in the corpus. We provide an expansive collection of curated datasets consisting of both formal and informal forms of the language from refutable websites and online social media networks, respectively. The collection is large and more diverse than the existing corpora by providing the first and largest set of Hausa social media data posts to capture the peculiarities in the language. The collection also consists of a parallel dataset, which can be used for tasks such as machine translation with applications in areas such as the detection of spurious or inciteful online content. We describe the curation process -- from the collection, preprocessing and how to obtain the data -- and proffer some research problems that could be addressed using the data.

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