@inproceedings{alhammad-aldahlawi-2026-thakaa,
title = "Thakaa at {A}r{A}-{DF} 2026: Fusing Self-Supervised and Signal-Processing Detectors for {A}rabic Speech Deepfake Detection",
author = "Alhammad, Abeer and
Aldahlawi, Abdullah",
editor = "Abdul-Mageed, Muhammad and
Elsayed, Tamer and
Bouamor, Houda and
El-Beltagy, Samhaa and
Al-Khalifa, Hend and
Abdelali, Ahmed and
Elmadany, AbdelRahim and
El Mekki, Abdellah and
Darwish, Kareem and
Alkhereyf, Sakhar and
Luqman, Hamzah and
Khalifa, Salam and
Magdy, Samar and
Alyafeai, Zaid and
Hamed, Injy and
Zaghouani, Wajdi and
Zitouni, Imed",
booktitle = "Proceedings of The Fourth {A}rabic Natural Language Processing Conference: Shared Tasks",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.arabicnlp-sharedtasks.194/",
pages = "1507--1511",
ISBN = "979-8-89176-497-2",
abstract = "ArA-DF 2026 is a shared task on binary Arabic speech deepfake detection, with two tracks: dialect generalisation and acoustic robustness. For both we submit rank-normalised score fusions of complementary detectors. Track 1 fuses five components in two stages: three fine-tuned XLS-R-300M networks and two ResNet-18 classifiers over linear-prediction residual and group-delay representations. Track 2 fuses two XLS-R-300M detectors differing in augmentation strategy. We reach 2.8961 EER on Track 1 and 2.7626 on Track 2, against baselines of 14.54 and 27.11. Our analysis on the released test labels shows individual EER to be a poor guide to fusion contribution, which depends on error independence: both fusions improve on their best member by over 40{\%}, and components far weaker in isolation than any we submitted improve them further."
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<abstract>ArA-DF 2026 is a shared task on binary Arabic speech deepfake detection, with two tracks: dialect generalisation and acoustic robustness. For both we submit rank-normalised score fusions of complementary detectors. Track 1 fuses five components in two stages: three fine-tuned XLS-R-300M networks and two ResNet-18 classifiers over linear-prediction residual and group-delay representations. Track 2 fuses two XLS-R-300M detectors differing in augmentation strategy. We reach 2.8961 EER on Track 1 and 2.7626 on Track 2, against baselines of 14.54 and 27.11. Our analysis on the released test labels shows individual EER to be a poor guide to fusion contribution, which depends on error independence: both fusions improve on their best member by over 40%, and components far weaker in isolation than any we submitted improve them further.</abstract>
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%0 Conference Proceedings
%T Thakaa at ArA-DF 2026: Fusing Self-Supervised and Signal-Processing Detectors for Arabic Speech Deepfake Detection
%A Alhammad, Abeer
%A Aldahlawi, Abdullah
%Y Abdul-Mageed, Muhammad
%Y Elsayed, Tamer
%Y Bouamor, Houda
%Y El-Beltagy, Samhaa
%Y Al-Khalifa, Hend
%Y Abdelali, Ahmed
%Y Elmadany, AbdelRahim
%Y El Mekki, Abdellah
%Y Darwish, Kareem
%Y Alkhereyf, Sakhar
%Y Luqman, Hamzah
%Y Khalifa, Salam
%Y Magdy, Samar
%Y Alyafeai, Zaid
%Y Hamed, Injy
%Y Zaghouani, Wajdi
%Y Zitouni, Imed
%S Proceedings of The Fourth Arabic Natural Language Processing Conference: Shared Tasks
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-497-2
%F alhammad-aldahlawi-2026-thakaa
%X ArA-DF 2026 is a shared task on binary Arabic speech deepfake detection, with two tracks: dialect generalisation and acoustic robustness. For both we submit rank-normalised score fusions of complementary detectors. Track 1 fuses five components in two stages: three fine-tuned XLS-R-300M networks and two ResNet-18 classifiers over linear-prediction residual and group-delay representations. Track 2 fuses two XLS-R-300M detectors differing in augmentation strategy. We reach 2.8961 EER on Track 1 and 2.7626 on Track 2, against baselines of 14.54 and 27.11. Our analysis on the released test labels shows individual EER to be a poor guide to fusion contribution, which depends on error independence: both fusions improve on their best member by over 40%, and components far weaker in isolation than any we submitted improve them further.
%U https://aclanthology.org/2026.arabicnlp-sharedtasks.194/
%P 1507-1511
Markdown (Informal)
[Thakaa at ArA-DF 2026: Fusing Self-Supervised and Signal-Processing Detectors for Arabic Speech Deepfake Detection](https://aclanthology.org/2026.arabicnlp-sharedtasks.194/) (Alhammad & Aldahlawi, ArabicNLP 2026)
ACL