# Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021

arXiv: https://arxiv.org/abs/2403.01196 · HTML: https://mlsanity.com/paper/2403.01196/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 15 references that are in the map.
- First posted on arXiv 2 Mar 2024.

## Builds on (most cited first, 9 of 9)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://mlsanity.com/paper/1808.06226/) (2018)
- [Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation](https://mlsanity.com/paper/1609.08144/) (2016)
- [OpenNMT: Open-source Toolkit for Neural Machine Translation](https://mlsanity.com/paper/1709.03815/) (2017)
- [Revisiting Low-Resource Neural Machine Translation: A Case Study](https://mlsanity.com/paper/1905.11901/) (2019)
- [SYSTRAN's Pure Neural Machine Translation Systems](https://mlsanity.com/paper/1610.05540/) (2016)
- [Optimizing Transformer for Low-Resource Neural Machine Translation](https://mlsanity.com/paper/2011.02266/) (2020)
- [DGT-TM: A freely Available Translation Memory in 22 Languages](https://mlsanity.com/paper/1309.5226/) (2013)
- [Findings of the LoResMT 2021 Shared Task on COVID and Sign Language for Low-resource Languages](https://mlsanity.com/paper/2108.06598/) (2021)

## Built on by (most cited first, 9 of 9)

- [adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds](https://mlsanity.com/paper/2403.02370/) (2024)
- [UCCIX: Irish-eXcellence Large Language Model](https://mlsanity.com/paper/2405.13010/) (2024)
- [Human Evaluation of English--Irish Transformer-Based NMT](https://mlsanity.com/paper/2403.02366/) (2024)
- [gaHealth: An English-Irish Bilingual Corpus of Health Data](https://mlsanity.com/paper/2403.03575/) (2024)
- [adaptNMT: an open-source, language-agnostic development environment for Neural Machine Translation](https://mlsanity.com/paper/2403.02367/) (2024)
- [Leveraging LLMs for MT in Crisis Scenarios: a blueprint for low-resource languages](https://mlsanity.com/paper/2410.23890/) (2024)
- [Sociotechnical Effects of Machine Translation](https://mlsanity.com/paper/2503.20959/) (2025)
- [LLM-Powered Automatic Translation and Urgency in Crisis Scenarios](https://mlsanity.com/paper/2602.13452/) (2026)
- [Design of an Open-Source Architecture for Neural Machine Translation](https://mlsanity.com/paper/2403.03582/) (2024)

## Abstract (arXiv)

Translation models for the specific domain of translating Covid data from English to Irish were developed for the LoResMT 2021 shared task. Domain adaptation techniques, using a Covid-adapted generic 55k corpus from the Directorate General of Translation, were applied. Fine-tuning, mixed fine-tuning and combined dataset approaches were compared with models trained on an extended in-domain dataset. As part of this study, an English-Irish dataset of Covid related data, from the Health and Education domains, was developed. The highest-performing model used a Transformer architecture trained with an extended in-domain Covid dataset. In the context of this study, we have demonstrated that extending an 8k in-domain baseline dataset by just 5k lines improved the BLEU score by 27 points.