configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: audio
dtype: audio
- name: dialect
dtype: string
splits:
- name: train
num_bytes: 137857739325
num_examples: 186366
- name: validation
num_bytes: 382155829
num_examples: 2249
- name: test
num_bytes: 1569934935
num_examples: 2307
download_size: 63077132529
dataset_size: 139809830089
ADI-20: Arabic Dialect Identification dataset and models
Contact : haroun.elleuch@elyadata.com and fethi.bougares@elyadata.com
We present ADI-20, an extension of the previously published ADI-17 Arabic Dialect Identification (ADI) dataset. ADI-20 covers all Arabic-speaking countries’ dialects. It comprises 3,556 hours from 19 Arabic dialects in addition to Modern Standard Arabic (MSA). We used this dataset to train and evaluate various state-of-the-art ADI systems.
The ADI-20 data set is proposed to broaden the dialectal coverage of ADI-17 and include MSA. First, we incorporated MSA to differentiate between regional dialects and the more formal, standardized Arabic. Second, Tunisian and Bahraini dialects were added to the dataset. Overall, ADI-20 contains 68 hours of MSA speech (MSA dev and test are the same as dev and test sets used in ADI5). Regarding the Tunisian dialect, the whole TunSwitch dataset was used, including the code-switched subset, for a combined duration of 142.7 hours. The train and dev splits were also based on TunSwitch splits but were augmented with content scraped from YouTube to reach 2 hours for each. Lastly, Bahraini content is composed exclusively of content sourced from YouTube, with approximately 271 hours for training and 2 hours for validation and testing each.
If you are willing to use ADI20, you need to download first ADI17.
The additional files also include the CSV manifests for ADI-20-53h, the sampled training subset used in the paper for controlled-data experiments.
Paper
https://arxiv.org/pdf/2511.10070
Dataset Description
- Curated by: Haroun Elleuch
- Shared by [optional]: Fethi Bougares
- Language(s) (NLP) : Arabic
BibTeX:
@inproceedings{Elleuch_2025, series={interspeech_2025},
title={ADI-20: Arabic Dialect Identification dataset and models},
url={http://dx.doi.org/10.21437/Interspeech.2025-884},
DOI={10.21437/interspeech.2025-884},
booktitle={Interspeech 2025},
publisher={ISCA},
author={Elleuch, Haroun and Mdhaffar, Salima and Estève, Yannick and Bougares, Fethi},
year={2025},
month=Aug, pages={2775–2779},
collection={interspeech_2025}
}