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Reject Threshold Adaptation for Open-Set Model Attribution of Deepfake Audio
To address the issues, we propose a novel framework for open set model attribution of deepfake audio with rejection threshold adaptation (ReTA).
ADD 2023: Towards Audio Deepfake Detection and Analysis in the Wild
The growing prominence of the field of audio deepfake detection is driven by its wide range of applications, notably in protecting the public from potential fraud and other malicious activities, prompting the need for greater attention and research in this area.
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