Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models

Sandipana Dowerah; Atharva Kulkarni; Ajinkya Kulkarni; Hoan My Tran; Joonas Kalda; Artem Fedorchenko; Benoit Fauve; Damien Lolive; Tanel Alumäe; Matthew Magimai Doss

arXiv · 2509.02859

Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models

Sandipana Dowerah·Atharva Kulkarni·Ajinkya Kulkarni·Hoan My Tran·Joonas Kalda·Artem Fedorchenko·Benoit Fauve·Damien Lolive·Tanel Alumäe·Matthew Magimai Doss

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Abstract

Parallel to the development of advanced deepfake audio generation, audio deepfake detection has also seen significant progress. However, a standardized and comprehensive benchmark is still missing. To address this, we introduce Speech DeepFake (DF) Arena, the first comprehensive benchmark for audio deepfake detection. Speech DF Arena provides a toolkit to uniformly evaluate detection systems, currently across 14 diverse datasets and attack scenarios, standardized evaluation metrics and protocols for reproducibility and transparency. It also includes a leaderboard to compare and rank the systems to help researchers and developers enhance their reliability and robustness. We include 14 evaluation sets, 12 state-of-the-art open-source and 3 proprietary detection systems. Our study presents many systems exhibiting high EER in out-of-domain scenarios, highlighting the need for extensive cross-domain evaluation. The leaderboard is hosted on Huggingface1 and a toolkit for reproducing results across the listed datasets is available on GitHub.

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Sandipana Dowerah, Atharva Kulkarni, Ajinkya Kulkarni, Hoan My Tran, Joonas Kalda, Artem Fedorchenko, Benoit Fauve, Damien Lolive, Tanel Alumäe, Matthew Magimai Doss. 2025-09-02. Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models. https://arxiv.org/abs/2509.02859

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