Original Research

A brief study of the Autshumato Machine Translation Web Service for South African languages

Nomsa J. Skosana, Respect Mlambo
Literator | Vol 42, No 1 | a1766 | DOI: https://doi.org/10.4102/lit.v42i1.1766 | © 2021 Nomsa J. Skosana, Respect Mlambo | This work is licensed under CC Attribution 4.0
Submitted: 08 December 2020 | Published: 29 October 2021

About the author(s)

Nomsa J. Skosana, South African Centre for Digital Language Resources, Faculty of Humanities, North-West University, Potchefstroom, South Africa
Respect Mlambo, South African Centre for Digital Language Resources, Faculty of Humanities, North-West University, Potchefstroom, South Africa


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Abstract

The scarcity of adequate resources for South African languages poses a huge challenge for their functional development in specialised fields such as science and technology. The study examines the Autshumato Machine Translation (MT) Web Service, created by the Centre for Text Technology at the North-West University. This software supports both formal and informal translations as a machine-aided human translation tool. We investigate the system in terms of its advantages and limitations and suggest possible solutions for South African languages. The results show that the system is essential as it offers high-speed translation and operates as an open-source platform. It also provides multiple translations from sentences, documents and web pages. Some South African languages were included whilst others were excluded and we find this to be a limitation of the system. We also find that the system was trained with a limited amount of data, and this has an adverse effect on the quality of the output. The study suggests that adding specialised parallel corpora from various contemporary fields for all official languages and involving language experts in the pre-editing of training data can be a major step towards improving the quality of the system’s output. The study also outlines that developers should consider integrating the system with other natural language processing applications. Finally, the initiatives discussed in this study will help to improve this MT system to be a more effective translation tool for all the official languages of South Africa.

Keywords

Autshumato project; Autshumato machine translation web service; South African languages; translation output; machine translation system; parallel corpora

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