Feriji / README.md
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metadata
configs:
  - config_name: corpus
    data_files:
      - split: train
        path:
          - corpus/fr_dje.jsonl
  - config_name: glossary
    data_files:
      - split: train
        path:
          - glossary/glossary.csv
  - config_name: monolingual_zarma
    data_files:
      - split: train
        path:
          - monolingual/monolingual_zarma.jsonl
license: cc-by-nc-4.0
task_categories:
  - text-classification
  - zero-shot-classification
  - translation
  - token-classification
  - fill-mask

Feriji: A French-Zarma Parallel Corpus, Glossary & Translator

This dataset repository contains Feriji, the first robust French-Zarma parallel corpus and glossary designed for machine translation (MT), as introduced in the paper "Feriji: A French-Zarma Parallel Corpus, Glossary & Translator" published at ACL 2024 (Student Research Workshop). Zarma, a dialect of Songhay within the Nilo-Saharan language family, is spoken by over 5 million people across Niger and neighboring countries. Feriji addresses the critical need for linguistic resources for this underrepresented African language.

Dataset Overview

The Feriji dataset includes three components:

  • French-Zarma Parallel Corpus: Located in corpus/fr_dje.csv, this contains 61,085 sentences in Zarma and 42,789 in French, forming a robust aligned corpus for MT.
  • French-Zarma Glossary: Found in glossary/glossary.csv, this includes 4,062 word pairs, serving as a lexical resource.
  • Monolingual Zarma Text: Stored in monolingual/monolingual_zarma.txt, this provides additional Zarma-only text for language modeling or analysis.

These resources were used to fine-tune three large language models, achieving a BLEU score of 30.06 on the best-performing model, with further evaluation based on human judgments of fluency, comprehension, and readability.

Repository Structure

  • corpus/fr_dje.csv: Aligned French-Zarma sentence pairs.
  • glossary/glossary.csv: French-Zarma word glossary.
  • monolingual/monolingual_zarma.txt: Monolingual Zarma text.

Acknowledgments

We gratefully acknowledge the Computer Science Department of Ashesi University for funding the annotation of the Feriji project.

Paper Details

For full details on the creation, evaluation, and impact of Feriji, see the original paper: - Link: https://aclanthology.org/2024.acl-srw.1/ - Citation:

@misc{keita2024ferijifrenchzarmaparallelcorpus,
      title={Feriji: A French-Zarma Parallel Corpus, Glossary & Translator}, 
      author={Mamadou K. Keita and Elysabhete Amadou Ibrahim and Habibatou Abdoulaye Alfari and Christopher Homan},
      year={2024},
      eprint={2406.05888},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2406.05888}, 
}