Audio deepfake detection: A survey
Audio deepfake detection is an emerging active topic. A growing number of literatures have
aimed to study deepfake detection algorithms and achieved effective performance, the …
aimed to study deepfake detection algorithms and achieved effective performance, the …
Aasist: Audio anti-spoofing using integrated spectro-temporal graph attention networks
Artefacts that differentiate spoofed from bona-fide utterances can reside in specific temporal
or spectral intervals. Their reliable detection usually depends upon computationally …
or spectral intervals. Their reliable detection usually depends upon computationally …
Deepfakes as a threat to a speaker and facial recognition: An overview of tools and attack vectors
Deepfakes present an emerging threat in cyberspace. Recent developments in machine
learning make deepfakes highly believable, and very difficult to differentiate between what is …
learning make deepfakes highly believable, and very difficult to differentiate between what is …
Does audio deepfake detection generalize?
NM Müller, P Czempin, F Dieckmann… - arxiv preprint arxiv …, 2022 - arxiv.org
Current text-to-speech algorithms produce realistic fakes of human voices, making deepfake
detection a much-needed area of research. While researchers have presented various …
detection a much-needed area of research. While researchers have presented various …
SASV 2022: The first spoofing-aware speaker verification challenge
The first spoofing-aware speaker verification (SASV) challenge aims to integrate research
efforts in speaker verification and anti-spoofing. We extend the speaker verification scenario …
efforts in speaker verification and anti-spoofing. We extend the speaker verification scenario …
Rawboost: A raw data boosting and augmentation method applied to automatic speaker verification anti-spoofing
This paper introduces RawBoost, a data boosting and augmentation method for the design
of more reliable spoofing detection solutions which operate directly upon raw waveform …
of more reliable spoofing detection solutions which operate directly upon raw waveform …
Fake audio detection based on unsupervised pretraining models
Z Lv, S Zhang, K Tang, P Hu - ICASSP 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
This work presents our systems for the ADD2022 challenge. The ADD2022 challenge is the
first audio deep synthesis detection challenge, which aims to spot various kinds of fake …
first audio deep synthesis detection challenge, which aims to spot various kinds of fake …
Discriminative frequency information learning for end-to-end speech anti-spoofing
End-to-end technology is an active research topic in speech anti-spoofing. Although end-to-
end methods have achieved remarkable success in the speech anti-spoofing, channel …
end methods have achieved remarkable success in the speech anti-spoofing, channel …
FairSSD: Understanding Bias in Synthetic Speech Detectors
AKS Yadav, K Bhagtani, D Salvi… - Proceedings of the …, 2024 - openaccess.thecvf.com
Methods that can generate synthetic speech which is perceptually indistinguishable from
speech recorded by a human speaker are easily available. Several incidents report misuse …
speech recorded by a human speaker are easily available. Several incidents report misuse …
Domain generalization via aggregation and separation for audio deepfake detection
In this paper, we propose an Aggregation and Separation Domain Generalization (ASDG)
method for Audio DeepFake Detection (ADD). Fake speech generated from different …
method for Audio DeepFake Detection (ADD). Fake speech generated from different …