Bootstrapping Siswati lexical resources from isiZulu

IsiZulu and Siswati are closely related languages that share significant morphosyntactic characteristics. Systematic differences between these languages have been identified at the phonological and morphosyntactic levels. Due to the resource-scarce status of these languages, this similarity has led to bootstrapping of computational language resources at the morphological and syntactic levels. In this work, we investigate the feasibility of adapting lexical items in a computational lexicon from isiZulu to Siswati. We use Grammatical Framework resource grammars for both languages to analyse and transform lexical items, which are then evaluated against a parallel term list. An iterative process yields a success rate of 70.5 %, indicating that this approach is largely viable as a means of significantly reducing the manual effort needed to develop lexicons for computational resources for Siswati.

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Publication Details

Journal
Journal of the Digital Humanities Association of Southern Africa
Published
2025-12-31
DOI
https://doi.org/10.55492/v6i02.6738
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Bootstrapping Siswati lexical resources from isiZulu

Roné Wierenga, Ilana Wilken, Laurette Marais
Journal of the Digital Humanities Association of Southern Africa
Natural Language Processing Techniques
article

Bootstrapping Siswati lexical resources from isiZulu

Roné Wierenga, Ilana Wilken, Laurette Marais
article en

Abstract

IsiZulu and Siswati are closely related languages that share significant morphosyntactic characteristics. Systematic differences between these languages have been identified at the phonological and morphosyntactic levels. Due to the resource-scarce status of these languages, this similarity has led to bootstrapping of computational language resources at the morphological and syntactic levels. In this work, we investigate the feasibility of adapting lexical items in a computational lexicon from isiZulu to Siswati. We use Grammatical Framework resource grammars for both languages to analyse and transform lexical items, which are then evaluated against a parallel term list. An iterative process yields a success rate of 70.5 %, indicating that this approach is largely viable as a means of significantly reducing the manual effort needed to develop lexicons for computational resources for Siswati.

Journal of the Digital Humanities Association of Southern AfricaVol. 6(2)
Council for Scientific and Industrial Research (ZA), North-West University (ZA), Ghent University Hospital (BE)
Quality Education
Openalex Percentile: Top 16%
Natural Language Processing Techniques
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