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20202025
most citedTowards localisation of keywords in speech using weak supervision

3 citations · 3 across the 3 of their papers we have counts for

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cs.CL2025

Swivuriso: The South African Next Voices Multilingual Speech Dataset

Vukosi Marivate, Kayode Olaleye, Sitwala Mundia +19

This paper introduces Swivuriso, a 3000-hour multilingual speech dataset developed as part of the African Next Voices project, to support the development and benchmarking of automa…

cs.CL2025

Mafoko: Structuring and Building Open Multilingual Terminologies for South African NLP

Vukosi Marivate, Isheanesu Dzingirai, Fiskani Banda +9

The critical lack of structured terminological data for South Africa's official languages hampers progress in multilingual NLP, despite the existence of numerous government and aca…

cs.CL20241 cited

Prompting Towards Alleviating Code-Switched Data Scarcity in Under-Resourced Languages with GPT as a Pivot

Michelle Terblanche, Kayode Olaleye, Vukosi Marivate

Many multilingual communities, including numerous in Africa, frequently engage in code-switching during conversations. This behaviour stresses the need for natural language process…

cs.CL2022

YFACC: A Yorùbá speech-image dataset for cross-lingual keyword localisation through visual grounding

Kayode Olaleye, Dan Oneata, Herman Kamper

Visually grounded speech (VGS) models are trained on images paired with unlabelled spoken captions. Such models could be used to build speech systems in settings where it is imposs…

cs.CL2021

Attention-Based Keyword Localisation in Speech using Visual Grounding

Kayode Olaleye, Herman Kamper

Visually grounded speech models learn from images paired with spoken captions. By tagging images with soft text labels using a trained visual classifier with a fixed vocabulary, pr…

cs.CL20203 cited

Towards localisation of keywords in speech using weak supervision

Kayode Olaleye, Benjamin van Niekerk, Herman Kamper

Developments in weakly supervised and self-supervised models could enable speech technology in low-resource settings where full transcriptions are not available. We consider whethe…