|
--- |
|
license: cc-by-nc-sa-4.0 |
|
language: |
|
- fr |
|
- fon |
|
- multilingual |
|
configs: |
|
- config_name: FFRv2 |
|
data_files: |
|
- split: train |
|
path: data/ffr_dataset_v2.txt |
|
- config_name: FFR_Daily_dialog |
|
data_files: |
|
- split: train |
|
path: data/Fon_French_Parallel_Data.txt |
|
task_categories: |
|
- translation |
|
--- |
|
|
|
> [!NOTE] |
|
> Dataset origin: https://github.com/bonaventuredossou/ffr-v1 |
|
|
|
|
|
# Description |
|
The authors of the dataset provide a description in the following PDFs: [here](https://huggingface.co/datasets/de-francophones/FFR/blob/main/FFR_Dataset_Documentation.pdf) and [here](https://huggingface.co/datasets/de-francophones/FFR/blob/main/Data_Statement_FFR_Dataset.pdf). |
|
|
|
|
|
# Citation |
|
|
|
``` |
|
@inproceedings{emezue-dossou-2020-ffr, |
|
title = "{FFR} v1.1: {F}on-{F}rench Neural Machine Translation", |
|
author = "Emezue, Chris Chinenye and |
|
Dossou, Femi Pancrace Bonaventure", |
|
editor = "Cunha, Rossana and |
|
Shaikh, Samira and |
|
Varis, Erika and |
|
Georgi, Ryan and |
|
Tsai, Alicia and |
|
Anastasopoulos, Antonios and |
|
Chandu, Khyathi Raghavi", |
|
booktitle = "Proceedings of the Fourth Widening Natural Language Processing Workshop", |
|
month = jul, |
|
year = "2020", |
|
address = "Seattle, USA", |
|
publisher = "Association for Computational Linguistics", |
|
url = "https://aclanthology.org/2020.winlp-1.21", |
|
doi = "10.18653/v1/2020.winlp-1.21", |
|
pages = "83--87", |
|
abstract = "All over the world and especially in Africa, researchers are putting efforts into building Neural Machine Translation (NMT) systems to help tackle the language barriers in Africa, a continent of over 2000 different languages. However, the low-resourceness, diacritical, and tonal complexities of African languages are major issues being faced. The FFR project is a major step towards creating a robust translation model from Fon, a very low-resource and tonal language, to French, for research and public use. In this paper, we introduce FFR Dataset, a corpus of Fon-to-French translations, describe the diacritical encoding process, and introduce our FFR v1.1 model, trained on the dataset. The dataset and model are made publicly available, to promote collaboration and reproducibility.", |
|
} |
|
``` |
