# Improving Yor`ub'a Diacritic Restoration

arXiv: https://arxiv.org/abs/2003.10564 · HTML: https://mlsanity.com/paper/2003.10564/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Mar 2020.

## Built on by (most cited first, 5 of 5)

- [The Effect of Domain and Diacritics in Yor`ub'a-English Neural Machine Translation](https://mlsanity.com/paper/2103.08647/) (2021)
- [AI4D -- African Language Program](https://mlsanity.com/paper/2104.02516/) (2021)
- [YAD: Leveraging T5 for Improved Automatic Diacritization of Yor`ub'a Text](https://mlsanity.com/paper/2412.20218/) (2024)
- [Visually Grounded Keyword Detection and Localisation for Low-Resource Languages](https://mlsanity.com/paper/2302.00765/) (2023)
- [NaijaNLP: A Survey of Nigerian Low-Resource Languages](https://mlsanity.com/paper/2502.19784/) (2025)

## Abstract (arXiv)

Yor`ub'a is a widely spoken West African language with a writing system rich in orthographic and tonal diacritics. They provide morphological information, are crucial for lexical disambiguation, pronunciation and are vital for any computational Speech or Natural Language Processing tasks. However diacritic marks are commonly excluded from electronic texts due to limited device and application support as well as general education on proper usage. We report on recent efforts at dataset cultivation. By aggregating and improving disparate texts from the web and various personal libraries, we were able to significantly grow our clean Yor`ub'a dataset from a majority Bibilical text corpora with three sources to millions of tokens from over a dozen sources. We evaluate updated diacritic restoration models on a new, general purpose, public-domain Yor`ub'a evaluation dataset of modern journalistic news text, selected to be multi-purpose and reflecting contemporary usage. All pre-trained models, datasets and source-code have been released as an open-source project to advance efforts on Yor`ub'a language technology.