[PDF][PDF] The age of synthetic realities: Challenges and opportunities

JP Cardenuto, J Yang, R Padilha… - … on Signal and …, 2023 - nowpublishers.com
Synthetic realities are digital creations or augmentations that are contextually generated
through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data …

Audio deepfake detection: A survey

J Yi, C Wang, J Tao, X Zhang, CY Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
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 …

Aasist: Audio anti-spoofing using integrated spectro-temporal graph attention networks

J Jung, HS Heo, H Tak, H Shim… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
Artefacts that differentiate spoofed from bona-fide utterances can reside in specific temporal
or spectral intervals. Their reliable detection usually depends upon computationally …

Asvspoof 2021: Towards spoofed and deepfake speech detection in the wild

X Liu, X Wang, M Sahidullah, J Patino… - … on Audio, Speech …, 2023 - ieeexplore.ieee.org
Benchmarking initiatives support the meaningful comparison of competing solutions to
prominent problems in speech and language processing. Successive benchmarking …

Add 2022: the first audio deep synthesis detection challenge

J Yi, R Fu, J Tao, S Nie, H Ma, C Wang… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
Audio deepfake detection is an emerging topic, which was included in the ASVspoof 2021.
However, the recent shared tasks have not covered many real-life and challenging …

Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentation

H Tak, M Todisco, X Wang, J Jung, J Yamagishi… - arxiv preprint arxiv …, 2022 - arxiv.org
The performance of spoofing countermeasure systems depends fundamentally upon the use
of sufficiently representative training data. With this usually being limited, current solutions …

Avoid-df: Audio-visual joint learning for detecting deepfake

W Yang, X Zhou, Z Chen, B Guo, Z Ba… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Recently, deepfakes have raised severe concerns about the authenticity of online media.
Prior works for deepfake detection have made many efforts to capture the intra-modal …

End-to-end spectro-temporal graph attention networks for speaker verification anti-spoofing and speech deepfake detection

H Tak, J Jung, J Patino, M Kamble, M Todisco… - arxiv preprint arxiv …, 2021 - arxiv.org
Artefacts that serve to distinguish bona fide speech from spoofed or deepfake speech are
known to reside in specific subbands and temporal segments. Various approaches can be …

Investigating self-supervised front ends for speech spoofing countermeasures

X Wang, J Yamagishi - arxiv preprint arxiv:2111.07725, 2021 - arxiv.org
Self-supervised speech model is a rapid progressing research topic, and many pre-trained
models have been released and used in various down stream tasks. For speech anti …

SASV 2022: The first spoofing-aware speaker verification challenge

J Jung, H Tak, H Shim, HS Heo, BJ Lee… - arxiv preprint arxiv …, 2022 - arxiv.org
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 …