Datasets:
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---
configs:
- config_name: tech
data_files:
- split: train
path: data/sentence/Tech/train.csv
- split: test
path: data/sentence/Tech/test.csv
- split: validation
path: data/sentence/Tech/dev.csv
- config_name: health
data_files:
- split: train
path: data/sentence/Health/train.csv
- split: test
path: data/sentence/Health/test.csv
- split: validation
path: data/sentence/Health/dev.csv
- config_name: doc_tech
data_files:
- split: train
path: data/document_new/Tech/train.csv
- split: test
path: data/document_new/Tech/test.csv
- split: validation
path: data/document_new/Tech/dev.csv
- config_name: doc_health
data_files:
- split: train
path: data/document_new/Health/train.csv
- split: test
path: data/document_new/Health/test.csv
- split: validation
path: data/document_new/Health/dev.csv
- config_name: doc_tech_25
data_files:
- split: train
path: data/document_25/Tech/train.csv
- split: test
path: data/document_25/Tech/test.csv
- split: validation
path: data/document_25/Tech/dev.csv
- config_name: doc_health_25
data_files:
- split: train
path: data/document_25/Health/train.csv
- split: test
path: data/document_25/Health/test.csv
- split: validation
path: data/document_25/Health/dev.csv
- config_name: doc_tech_5
data_files:
- split: train
path: data/document_5/Tech/train.csv
- split: test
path: data/document_5/Tech/test.csv
- split: validation
path: data/document_5/Tech/dev.csv
- config_name: doc_health_5
data_files:
- split: train
path: data/document_5/Health/train.csv
- split: test
path: data/document_5/Health/test.csv
- split: validation
path: data/document_5/Health/dev.csv
- config_name: doc_tech_10
data_files:
- split: train
path: data/document_10/Tech/train.csv
- split: test
path: data/document_10/Tech/test.csv
- split: validation
path: data/document_10/Tech/dev.csv
- config_name: doc_health_10
data_files:
- split: train
path: data/document_10/Health/train.csv
- split: test
path: data/document_10/Health/test.csv
- split: validation
path: data/document_10/Health/dev.csv
task_categories:
- translation
language:
- en
- am
- ha
- sw
- yo
- zu
tags:
- health
- IT
---
```
data
├── document
│ ├── Health
│ │ ├── dev.csv
│ │ ├── test.csv
│ │ └── train.csv
│ └── Tech
│ ├── dev.csv
│ ├── test.csv
│ └── train.csv
└── sentence
├── Health
│ ├── dev.csv
│ ├── test.csv
│ └── train.csv
└── Tech
├── dev.csv
├── test.csv
└── train.csv
```
AFRIDOC-MT is a document-level multi-parallel translation dataset covering English and five African languages: Amharic, Hausa, Swahili, Yorùbá, and Zulu. The dataset comprises 334 health and 271 information technology news documents, all human-translated from English to these languages.
The project was generously funded by Lacuna Fund.
```
@misc{alabi2025afridocmtdocumentlevelmtcorpus,
title={AFRIDOC-MT: Document-level MT Corpus for African Languages},
author={Jesujoba O. Alabi and Israel Abebe Azime and Miaoran Zhang and Cristina España-Bonet and Rachel Bawden and Dawei Zhu and David Ifeoluwa Adelani and Clement Oyeleke Odoje and Idris Akinade and Iffat Maab and Davis David and Shamsuddeen Hassan Muhammad and Neo Putini and David O. Ademuyiwa and Andrew Caines and Dietrich Klakow},
year={2025},
eprint={2501.06374},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2501.06374},
}
``` |