TUNIFRA: A Tunisian Arabic Speech Corpus with Orthographic Transcriptions and French Translations

Contact person : fethi.bougares@elyadata.com

We introduce TUNIFRA, a novel and comprehensive corpus developed to advance research in Automatic Speech Recognition (ASR) and Speech-to-Text Translation (STT) for Tunisian Arabic, a notably low-resourced language variety. The TUNIFRA corpus comprises 15 hours of native Tunisian Arabic speech, carefully transcribed and manually translated into French. While the development of ASR and STT systems for major languages is supported by extensive datasets, low-resource languages such as Tunisian Arabic face significant challenges due to limited training data, particularly for speech technologies. TUNIFRA addresses this gap by offering a valuable resource tailored for both ASR and STT tasks in the Tunisian dialect. We describe our methodology for data collection, transcription, and annotation, and present initial baseline results for both Tunisian Arabic speech recognition and Tunisian Arabic–French speech translation.

Paper

https://aclanthology.org/2025.arabicnlp-main.5.pdf

Dataset Description

• Curated by: Fethi Bougares
• Shared by [optional]: Fethi Bougares
• Language(s) (NLP) : Tunisian Arabic
• License: CC BY-NC-ND 4.0 license

Enjoy using this data set and don't forget to cite the related paper :) Below the bibtext entry if you use this data set :

BibTeX:

@inproceedings{choux-etal-2025-tunifra,
    title = "{T}uni{F}ra: A {T}unisian {A}rabic Speech Corpus with Orthographic Transcriptions and {F}rench Translations",
    author = "Choux, Alex  and Avila, Marko  and Crego, Josep  and  Bougares, Fethi  and Laurent, Antoine",
    booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.arabicnlp-main.22/",
    doi = "10.18653/v1/2025.arabicnlp-main.22",
    pages = "278--287",
    ISBN = "979-8-89176-352-4"
}