# Natural Language Processing for Tigrinya: Current State and Future Directions

arXiv: https://arxiv.org/abs/2507.17974 · HTML: https://mlsanity.com/paper/2507.17974/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 61 references that are in the map.
- First posted on arXiv 23 Jul 2025.

## Builds on (most cited first, 14 of 14)

- [Neural Machine Translation of Rare Words with Subword Units](https://mlsanity.com/paper/1508.07909/) (2015)
- [The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://mlsanity.com/paper/2004.09095/) (2020)
- [Scaling Speech Technology to 1,000+ Languages](https://mlsanity.com/paper/2305.13516/) (2023)
- [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://mlsanity.com/paper/2308.16884/) (2023)
- [Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning](https://mlsanity.com/paper/2402.06619/) (2024)
- [MasakhaNEWS: News Topic Classification for African languages](https://mlsanity.com/paper/2304.09972/) (2023)
- [Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunities](https://mlsanity.com/paper/2303.14406/) (2023)
- [AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages](https://mlsanity.com/paper/2501.08284/) (2025)
- [Transferring Monolingual Model to Low-Resource Language: The Case of Tigrinya](https://mlsanity.com/paper/2006.07698/) (2020)
- [An Exploration of Data Augmentation Techniques for Improving English to Tigrinya Translation](https://mlsanity.com/paper/2103.16789/) (2021)
- [Tigrinya Neural Machine Translation with Transfer Learning for Humanitarian Response](https://mlsanity.com/paper/2003.11523/) (2020)
- [Lesan -- Machine Translation for Low Resource Languages](https://mlsanity.com/paper/2112.08191/) (2021)
- [TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya](https://mlsanity.com/paper/2404.17194/) (2024)
- [A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings](https://mlsanity.com/paper/2505.12116/) (2025)

## Built on by (most cited first, 2 of 2)

- [Tigrinya Number Verbalization: Rules, Algorithm, and Implementation](https://mlsanity.com/paper/2601.03403/) (2026)
- [LLM Probe: Evaluating LLMs for Low-Resource Languages](https://mlsanity.com/paper/2603.29517/) (2026)

## Abstract (arXiv)

Despite being spoken by millions of people, Tigrinya remains severely underrepresented in Natural Language Processing (NLP) research. This work presents a comprehensive survey of NLP research for Tigrinya, analyzing over 50 studies from 2011 to 2025. We systematically review the current state of computational resources, models, and applications across fifteen downstream tasks, including morphological processing, part-of-speech tagging, named entity recognition, machine translation, question-answering, speech recognition, and synthesis. Our analysis reveals a clear trajectory from foundational, rule-based systems to modern neural architectures, with progress consistently driven by milestones in resource creation. We identify key challenges rooted in Tigrinya's morphological properties and resource scarcity, and highlight promising research directions, including morphology-aware modeling, cross-lingual transfer, and community-centered resource development. This work serves both as a reference for researchers and as a roadmap for advancing Tigrinya NLP. An anthology of surveyed studies and resources is publicly available.