Deepfakes present an emerging threat in cyberspace. Recent developments in machine learning make deepfakes highly believable, and very difficult to differentiate between what is …
T Liu, KA Lee, Q Wang, H Li - IEEE/ACM Transactions on Audio …, 2024 - ieeexplore.ieee.org
The residual neural networks (ResNet) demonstrate the impressive performance in automatic speaker verification (ASV). They treat the time and frequency dimensions equally …
Recent advancements in deep learning techniques have brought remarkable developments in synthetic media generation, leading to the creation of forged contents that are almost …
C Fan, M Ding, J Tao, R Fu, J Yi… - IEEE/ACM Transactions …, 2024 - ieeexplore.ieee.org
Most research in synthetic speech detection (SSD) focuses on improving performance on standard noise-free datasets. However, in actual situations, noise interference is usually …
In the field of synthetic speech generation, recent advancements in deep learning and speech synthesis methods have enabled the possibility of creating highly realistic fake …
TM Wani, R Gulzar, I Amerini - Proceedings of the IEEE/CVF …, 2024 - openaccess.thecvf.com
In response to the escalating challenge of audio deepfake detection this study introduces ABC-CapsNet (Attention-Based Cascaded Capsule Network) a novel architecture that …
The rise of audio deepfakes presents a significant security threat that undermines trust in digital communications and media. These synthetic audio technologies can convincingly …
Y Wang, X Wang, H Nishizaki… - 2022 13th International …, 2022 - ieeexplore.ieee.org
A reliable voice anti-spoofing countermeasure system needs to robustly protect automatic speaker verification (ASV) systems in various kinds of spoofing scenarios. However, the …
The availability of smart devices leads to an exponential increase in multimedia content. However, the rapid advancements in deep learning have given rise to sophisticated …