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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 51–74 of 74 papers

TitleStatusHype
Heterogeneity over Homogeneity: Investigating Multilingual Speech Pre-Trained Models for Detecting Audio DeepfakeCode0
Exploring Green AI for Audio Deepfake DetectionCode0
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake DetectionCode1
Audio Deepfake Detection with Self-Supervised WavLM and Multi-Fusion Attentive Classifier—0
HM-Conformer: A Conformer-based audio deepfake detection system with hierarchical pooling and multi-level classification token aggregation methodsCode1
Towards generalisable and calibrated synthetic speech detection with self-supervised representations—0
FSD: An Initial Chinese Dataset for Fake Song DetectionCode1
Complex-valued neural networks for voice anti-spoofing—0
The DKU-DUKEECE System for the Manipulation Region Location Task of ADD 2023—0
TranssionADD: A multi-frame reinforcement based sequence tagging model for audio deepfake detection—0
Betray Oneself: A Novel Audio DeepFake Detection Model via Mono-to-Stereo ConversionCode0
Bts-e: Audio deepfake detection using breathing-talking-silence encoderCode1
Defense Against Adversarial Attacks on Audio DeepFake DetectionCode1
SpecRNet: Towards Faster and More Accessible Audio DeepFake DetectionCode1
Audio Deepfake Detection Based on a Combination of F0 Information and Real Plus Imaginary Spectrogram Features—0
Attack Agnostic Dataset: Towards Generalization and Stabilization of Audio DeepFake DetectionCode1
Does Audio Deepfake Detection Generalize?—0
The Vicomtech Audio Deepfake Detection System based on Wav2Vec2 for the 2022 ADD Challenge—0
Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentationCode1
ADD 2022: the First Audio Deep Synthesis Detection Challenge—0
WaveFake: A Data Set to Facilitate Audio Deepfake DetectionCode1
AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention NetworksCode1
End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake DetectionCode1
End-to-end anti-spoofing with RawNet2Code1
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