Building a Functional Machine Translation Corpus for Kpelle

• URL: http://arxiv.org/abs/2505.18905v1
• Date: Sat, 24 May 2025 23:39:34 GMT
• Title: Building a Functional Machine Translation Corpus for Kpelle
• Authors: Kweku Andoh Yamoah, Jackson Weako, Emmanuel J. Dorley,
• Abstract summary: This paper introduces the first publicly available English-Kpelle dataset for machine translation.<n>By fine-tuning Meta's No Language Left Behind(NLLB) model on two versions of the dataset, we achieved BLEU scores of up to 30 in the Kpelle-to-English direction.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we introduce the first publicly available English-Kpelle dataset for machine translation, comprising over 2000 sentence pairs drawn from everyday communication, religious texts, and educational materials. By fine-tuning Meta's No Language Left Behind(NLLB) model on two versions of the dataset, we achieved BLEU scores of up to 30 in the Kpelle-to-English direction, demonstrating the benefits of data augmentation. Our findings align with NLLB-200 benchmarks on other African languages, underscoring Kpelle's potential for competitive performance despite its low-resource status. Beyond machine translation, this dataset enables broader NLP tasks, including speech recognition and language modelling. We conclude with a roadmap for future dataset expansion, emphasizing orthographic consistency, community-driven validation, and interdisciplinary collaboration to advance inclusive language technology development for Kpelle and other low-resourced Mande languages.

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