Bidirectional Awngi (አዊኛ)–Amharic Machine Translation research
# Bidirectional-Awngi-Amharic-Machine-Translation
Bidirectional Awngi (አዊኛ)–Amharic Machine Translation research
# Bidirectional Awngi–Amharic Machine Translation: A Deep Learning Approach
This repository accompanies the paper:
**"Bidirectional Awngi (አዊኛ)–Amharic Machine Translation: A Deep Learning Approach"**
by Melak Teshome, Zewdu Ayinie, and Habtamu Abate (Wollo University, Ethiopia).
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## 📖 Overview
We present the first bidirectional neural machine translation (NMT) system for the low-resource Ethiopian languages **Awngi** and **Amharic**.
We compiled a new parallel corpus (~15,000 sentence pairs) and trained Transformer-based models in both directions.
| Direction | Model | BLEU |
|------------|--------|------|
| Awngi → Amharic | Transformer | **33.12** |
| Amharic → Awngi | Transformer | **34.24** |
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## 📂 Repository Structure
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## ⚙️ Requirements
- Python ≥ 3.8
- PyTorch ≥ 1.13
- OpenNMT-py or Fairseq
- sentencepiece (for BPE tokenization)
- sacrebleu (for evaluation)
Install dependencies:
```bash
pip install torch sentencepiece sacrebleu
🧰 Dataset
The Awngi–Amharic parallel corpus consists of approximately 15,000 sentence pairs collected from:
Amhara Media Corporation’s official Facebook page
Awngi and Amharic school textbooks
Awngi newspaper (ቺርቤዋ ጋዜጣ)
Community-verified translations
Data split:
Training: 90%
Testing: 10%
Note: The dataset is available upon reasonable request from the authors.
pgsql
@article{teshome2025awngi_amharic_mt,
title={Bidirectional Awngi--Amharic Machine Translation: A Deep Learning Approach},
author={Teshome, Melak and Ayinie, Zewdu and Abate, Habtamu},
year={2025},
institution={Wollo University},
note={Manuscript submitted to Natural Language Engineering}
}
📫 Contact
For questions or collaboration, please contact:
Melak Teshome
Department of Information Technology, Wollo University
📧 melak.teshome@wu.edu.et
or melemelak@gmail.com
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