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 …

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 …

In this paper we perform an in depth study of how data augmentation techniques improve
synthetic or spoofed audio detection. Specifically, we propose methods to deal with channel …

Synthetic speech attacks bring more threats to Automatic Speaker Verification (ASV)
systems, thus many synthetic speech detection (SSD) systems have been proposed to help …

Audio deepfake detection (ADD) aims to detect the fake audio generated by text-to-speech
(TTS), and voice conversion (VC), etc., which is an emerging topic. Traditionally we read the …

The availability of smart devices leads to an exponential increase in multimedia content.
However, advancements in deep learning have also enabled the creation of highly …

A great deal of recent research reveals that artifacts introduced by spoofing algorithms
reside in specific frequency subbands or temporal segments. Therefore, the performance of …

Popular topics in the field of countermeasures include feature engineering and neural-
network-based models, which involve neural network architectures and loss criteria. This …

Existing deep learning models for spoofing speech detection often struggle to effectively
generalize to unseen spoofing attacks that were not present during the training stage …

Most of the voice spoofing detection methods are designed for specific kinds of spoofing
attacks, synthetic or replay. In practice, however, there is no prior information about these …