NDLI: Building natural language processing tools for Runyakitara

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Building natural language processing tools for Runyakitara

Content Provider	Scilit
Author	Katushemererwe, Fridah Caines, Andrew Buttery, Paula
Copyright Year	2020
Abstract	This paper describes an endeavour to build natural language processing (NLP) tools for Runyakitara, a group of four closely related Bantu languages spoken in western Uganda. In contrast with major world languages such as English, for which corpora are comparatively abundant and NLP tools are well developed, computational linguistic resources for Runyakitara are in short supply. First therefore, we need to collect corpora for these languages, before we can proceed to the design of a spell-checker, grammar-checker and applications for computer-assisted language learning (CALL). We explain how we are collecting primary data for a new Runya Corpus of speech and writing, we outline the design of a morphological analyser, and discuss how we can use these new resources to build NLP tools. We are initially working with Runyankore–Rukiga, a closely-related pair of Runyakitara languages, and we frame our project in the context of NLP for low-resource languages, as well as CALL for the preservation of endangered languages. We put our project forward as a test case for the revitalization of endangered languages through education and technology.
Related Links	https://www.degruyter.com/downloadpdf/journals/alr/ahead-of-print/article-10.1515-applirev-2020-2004/article-10.1515-applirev-2020-2004.pdf
ISSN	18686303
e-ISSN	18686311
DOI	10.1515/applirev-2020-2004
Journal	Applied Linguistics Review
Language	English
Publisher	Walter de Gruyter GmbH
Publisher Date	2020-07-13
Access Restriction	Open
Subject Keyword	Applied Linguistics Review Language Studies Natural Language Processing Endangered Languages Language Corpus Morphological Analyser Call Journal: Applied Linguistics Review
Content Type	Text
Resource Type	Article
Subject	Linguistics and Language

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