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Audio Deepfake Detection

Nowadays, deepfake is now generically used by the media or people to refer to any audio or video in which important attributes have been either digitally altered or swapped, with the help of artificial intelligence (AI). Audio deepfake detection is a task that aims to distinguish genuine utterances from fake ones via machine learning techniques.

Papers

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Showing 61–70 of 74 papers

TitleStatusHype
Deepfake Audio Detection Using Spectrogram-based Feature and Ensemble of Deep Learning Models—0
ADD 2022: the First Audio Deep Synthesis Detection Challenge—0
Temporal Variability and Multi-Viewed Self-Supervised Representations to Tackle the ASVspoof5 Deepfake Challenge—0
Does Audio Deepfake Detection Generalize?—0
Audio Deepfake Detection with Self-Supervised WavLM and Multi-Fusion Attentive Classifier—0
The DKU-DUKEECE System for the Manipulation Region Location Task of ADD 2023—0
The Vicomtech Audio Deepfake Detection System based on Wav2Vec2 for the 2022 ADD Challenge—0
EnvSDD: Benchmarking Environmental Sound Deepfake Detection—0
Forensic deepfake audio detection using segmental speech features—0
Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap—0
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