Lecturer, University of Johannesburg, South Africa
KR Mabokela is a South African PhD candidate in Computer Science at the University of the Witwatersrand (2020–2024). With a background in Speech Technology, he holds a Master of Science in Computer Science (2012–2014) and a Bachelor of Science in Computer Science and Mathematics (2008–2010), both from the University of Limpopo. Currently, he serves as Acting Deputy Head of Department for Continuing Education Programs (CEPs) and Online Learning at the University of Johannesburg, where he contributes to academic leadership and strategic planning. His research interests focus on multilingual sentiment analysis, language identification for under-resourced languages, and speech technology. 🧑💻📚
Publication Profile
Google scholar
Education
KR Mabokela’s academic journey began at the University of Limpopo, where he earned his Bachelor of Science (Computer Science and Mathematics, 2008–2010), followed by a Bachelor of Science Honours in Computer Science (2011). He continued his studies with a Master of Science in Computer Science, specializing in Speech Technology (2012–2014). He is now pursuing a Doctor of Philosophy (PhD) in Computer Science at the University of the Witwatersrand (2020–2024), focusing on advancing research in speech technology and multilingual systems. 🎓🔬
Experience
Mabokela has built a strong academic career, currently serving as the Acting Deputy Head of the Department of Applied Information Systems at the University of Johannesburg, where he leads the Continuing Education Programs (CEPs) and Online initiatives. His responsibilities include academic leadership, strategic direction, coordinating training for staff and students, and ensuring the quality of postgraduate teaching in online settings. He has also played a pivotal role in the development of online education and the integration of emerging technologies into curriculum delivery. 💼👨🏫
Research Interests
KR Mabokela’s research revolves around multilingual sentiment analysis, language identification, and speech technology, with a specific focus on under-resourced languages. He investigates how to build efficient systems for multilingual sentiment analysis and address challenges posed by code-switching in speech. His goal is to create tools that improve the processing and understanding of languages that lack sufficient resources and support technological growth in African languages. 🌍💡
Awards
Mabokela’s work has been recognized for its innovation and contribution to speech technology, especially in the context of under-resourced languages. His research has been cited in numerous papers and has received acknowledgment in the academic community for its practical applications in multilingual sentiment analysis and language identification. 🏅🔍
Publications
Multilingual Sentiment Analysis for Under-Resourced Languages: A Systematic Review of the Landscape
Published in IEEE Access (2023)
Cited by: 34
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Modeling code-Switching speech on under-resourced languages for language identification
Published in SLTU (2014)
Cited by: 30
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An integrated language identification for code-switched speech using decoded-phonemes and support vector machine
Published in Speech Technology and Human-Computer Dialogue (SpeD), 7th Conference (2013)
Cited by: 13
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A sentiment corpus for South African under-resourced languages in a multilingual context
Published in TBD Journal
Cited by: TBD
Read here