# Evaluating Amharic Machine Translation

arXiv: https://arxiv.org/abs/2003.14386 · HTML: https://mlsanity.com/paper/2003.14386/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Mar 2020.

## Built on by (most cited first, 3 of 3)

- [The Effect of Domain and Diacritics in Yor`ub'a-English Neural Machine Translation](https://mlsanity.com/paper/2103.08647/) (2021)
- [The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation](https://mlsanity.com/paper/2210.15224/) (2022)
- [EthioMT: Parallel Corpus for Low-resource Ethiopian Languages](https://mlsanity.com/paper/2403.19365/) (2024)

## Abstract (arXiv)

Machine translation (MT) systems are now able to provide very accurate results for high resource language pairs. However, for many low resource languages, MT is still under active research. In this paper, we develop and share a dataset to automatically evaluate the quality of MT systems for Amharic. We compare two commercially available MT systems that support translation of Amharic to and from English to assess the current state of MT for Amharic. The BLEU score results show that the results for Amharic translation are promising but still low. We hope that this dataset will be useful to the research community both in academia and industry as a benchmark to evaluate Amharic MT systems.