# YAD: Leveraging T5 for Improved Automatic Diacritization of Yor`ub'a Text

arXiv: https://arxiv.org/abs/2412.20218 · HTML: https://mlsanity.com/paper/2412.20218/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 18 references that are in the map.
- First posted on arXiv 28 Dec 2024.

## Builds on (most cited first, 11 of 11)

- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [mT5: A massively multilingual pre-trained text-to-text transformer](https://mlsanity.com/paper/2010.11934/) (2020)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretraining](https://mlsanity.com/paper/2304.09151/) (2023)
- [A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation](https://mlsanity.com/paper/2205.02022/) (2022)
- [The Effect of Domain and Diacritics in Yor`ub'a-English Neural Machine Translation](https://mlsanity.com/paper/2103.08647/) (2021)
- [Attentive Sequence-to-Sequence Learning for Diacritic Restoration of Yor`ub'a Language Text](https://mlsanity.com/paper/1804.00832/) (2018)
- [Diacritics Restoration using BERT with Analysis on Czech language](https://mlsanity.com/paper/2105.11408/) (2021)
- [Correcting diacritics and typos with a ByT5 transformer model](https://mlsanity.com/paper/2201.13242/) (2022)
- [Improving Yor`ub'a Diacritic Restoration](https://mlsanity.com/paper/2003.10564/) (2020)
- [Arabic Text Diacritization In The Age Of Transfer Learning: Token Classification Is All You Need](https://mlsanity.com/paper/2401.04848/) (2024)

## Built on by (most cited first, 4 of 4)

- [Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead](https://mlsanity.com/paper/2505.21315/) (2025)
- [Are LLMs Good Text Diacritizers? An Arabic and Yoruba Case Study](https://mlsanity.com/paper/2506.11602/) (2025)
- [Accent Placement Models for Rigvedic Sanskrit Text](https://mlsanity.com/paper/2511.23088/) (2025)
- [Yo-ByT5: Efficient and High-Fidelity Diacritic Restoration for Yor`ub'a](https://mlsanity.com/paper/2610.01634/) (2026)

## Abstract (arXiv)

In this work, we present Yor`ub'a automatic diacritization (YAD) benchmark dataset for evaluating Yor`ub'a diacritization systems. In addition, we pre-train text-to-text transformer, T5 model for Yor`ub'a and showed that this model outperform several multilingually trained T5 models. Lastly, we showed that more data and larger models are better at diacritization for Yor`ub'a