π-yalli: un nouveau corpus pour le nahuatl

Juan-Manuel Torres-Moreno, Juan-José Guzmán-Landa, Graham Ranger, Martha Lorena Avendaño Garrido, Miguel Figueroa-Saavedra +5 more
12/20/2024
cs.CLcs.AI

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Abstract

The NAHU$^2$ project is a Franco-Mexican collaboration aimed at building the $π$-YALLI corpus adapted to machine learning, which will subsequently be used to develop computer resources for the Nahuatl language. Nahuatl is a language with few computational resources, even though it is a living language spoken by around 2 million people. We have decided to build $π$-YALLI, a corpus that will enable to carry out research on Nahuatl in order to develop Language Models (LM), whether dynamic or not, which will make it possible to in turn enable the development of Natural Language Processing (NLP) tools such as: a) a grapheme unifier, b) a word segmenter, c) a POS grammatical analyser, d) a content-based Automatic Text Summarization; and possibly, e) a translator translator (probabilistic or learning-based).

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Cite this paper

@article{torresmoreno2024yalli,
  title  = {π-yalli: un nouveau corpus pour le nahuatl},
  author = {Juan-Manuel Torres-Moreno and Juan-José Guzmán-Landa and Graham Ranger and Martha Lorena Avendaño Garrido and Miguel Figueroa-Saavedra and Ligia Quintana-Torres and Carlos-Emiliano González-Gallardo and Elvys Linhares Pontes and Patricia Velázquez Morales and Luis-Gil Moreno Jiménez},
  year   = {2024},
  eprint = {2412.15821},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.15821v1}
}

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