The Ghanaian NLP Landscape: A First Look

Sheriff Issaka, Zhaoyi Zhang, Mihir Heda, Keyi Wang, Yinka Ajibola +2 more
5/10/2024
cs.CL

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Abstract

Despite comprising one-third of global languages, African languages are critically underrepresented in Artificial Intelligence (AI), threatening linguistic diversity and cultural heritage. Ghanaian languages, in particular, face an alarming decline, with documented extinction and several at risk. This study pioneers a comprehensive survey of Natural Language Processing (NLP) research focused on Ghanaian languages, identifying methodologies, datasets, and techniques employed. Additionally, we create a detailed roadmap outlining challenges, best practices, and future directions, aiming to improve accessibility for researchers. This work serves as a foundational resource for Ghanaian NLP research and underscores the critical need for integrating global linguistic diversity into AI development.

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Cite this paper

@article{issaka2024ghanaian,
  title  = {The Ghanaian NLP Landscape: A First Look},
  author = {Sheriff Issaka and Zhaoyi Zhang and Mihir Heda and Keyi Wang and Yinka Ajibola and Ryan DeMar and Xuefeng Du},
  year   = {2024},
  eprint = {2405.06818},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2405.06818v1}
}

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