Datasets:
Modalities:
Text
Size:
10K - 100K
metadata
task_categories:
- translation
- text-generation
language:
- bm
- fr
size_categories:
- 10K<n<100K
BAYƐLƐMABAGA: Parallel French - Bambara Dataset for Machine Learning
Overview
The Bayelemabaga dataset is a collection of 46976 aligned machine translation ready Bambara-French lines, originating from Corpus Bambara de Reference. The dataset is constitued of text extracted from 264 text files, varing from periodicals, books, short stories, blog posts, part of the Bible and the Quran.
Snapshot: 46976
Lines | 46976 |
French Tokens (spacy) | 691312 |
Bambara Tokens (daba) | 660732 |
French Types | 32018 |
Bambara Types | 29382 |
Avg. Fr line length | 77.6 |
Avg. Bam line length | 61.69 |
Number of text sources | 264 |
Data Splits
Train | 80% | 37580 |
Valid | 10% | 4698 |
Test | 10% | 4698 |
Remarks
- We are working on resolving some last minute misalignment issues.
Maintenance
- This dataset is supposed to be actively maintained.
Benchmarks:
Coming soon
Sources
To note:
- ʃ => (sh/shy) sound: Symbol left in the dataset, although not a part of bambara orthography nor French orthography.
License
CC-BY-SA-4.0
Version
1.0.1
Citation
@misc{bayelemabagamldataset2022
title={Machine Learning Dataset Development for Manding Languages},
author={
Valentin Vydrin and
Jean-Jacques Meric and
Kirill Maslinsky and
Andrij Rovenchak and
Allahsera Auguste Tapo and
Sebastien Diarra and
Christopher Homan and
Marco Zampieri and
Michael Leventhal
},
howpublished = {url{https://github.com/robotsmali-ai/datasets}},
year={2022}
}
Contacts
sdiarra <at> robotsmali <dot> org
aat3261 <at> rit <dot> edu