From Scarcity to Efficiency: Investigating the Effects of Data Augmentation on African Machine Translation

• URL: http://arxiv.org/abs/2509.07471v2
• Date: Sat, 18 Oct 2025 21:47:27 GMT
• Title: From Scarcity to Efficiency: Investigating the Effects of Data Augmentation on African Machine Translation
• Abstract summary: We focus on two data augmentation techniques: sentence concatenation with back translation and switch-out, applying them across six African languages.<n>Our experiments show significant improvements in machine translation performance, with a minimum increase of 25% in BLEU score across all six languages.
• Score: 1.041244287595653
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 languages. Our experiments show significant improvements in machine translation performance, with a minimum increase of 25\% in BLEU score across all six languages. We provide a comprehensive analysis and highlight the potential of these techniques to improve machine translation systems for low-resource languages, contributing to the development of more robust translation systems for under-resourced languages.

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