The Zeno's Paradox of `Low-Resource' Languages

Hellina Hailu Nigatu, Atnafu Lambebo Tonja, Benjamin Rosman, Thamar Solorio, Monojit Choudhury
10/28/2024
cs.CL

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Abstract

The disparity in the languages commonly studied in Natural Language Processing (NLP) is typically reflected by referring to languages as low vs high-resourced. However, there is limited consensus on what exactly qualifies as a `low-resource language.' To understand how NLP papers define and study `low resource' languages, we qualitatively analyzed 150 papers from the ACL Anthology and popular speech-processing conferences that mention the keyword `low-resource.' Based on our analysis, we show how several interacting axes contribute to `low-resourcedness' of a language and why that makes it difficult to track progress for each individual language. We hope our work (1) elicits explicit definitions of the terminology when it is used in papers and (2) provides grounding for the different axes to consider when connoting a language as low-resource.

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Cite this paper

@article{nigatu2024zenos,
  title  = {The Zeno's Paradox of `Low-Resource' Languages},
  author = {Hellina Hailu Nigatu and Atnafu Lambebo Tonja and Benjamin Rosman and Thamar Solorio and Monojit Choudhury},
  year   = {2024},
  eprint = {2410.20817},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2410.20817v1}
}

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