Artefacts that differentiate spoofed from bona-fide utterances can reside in specific temporal
or spectral intervals. Their reliable detection usually depends upon computationally …

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 …

The current neural network based anti-spoofing systems have poor robustness. Their
performance degrades further after voice activity detection (VAD) performed, making it …

Speaker verification systems have achieved great progress in recent years. Unfortunately,
they are still highly prone to different kinds of spoofing attacks such as speech synthesis …

The cues needed to detect spoofing attacks against automatic speaker verification are often
located in specific spectral sub-bands or temporal segments. Previous works show the …

The threat of spoofing can pose a risk to the reliability of automatic speaker verification.
Results from the bi-annual ASVspoof evaluations show that effective countermeasures …

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 …

In text-to-speech or voice conversion based synthetic speech detection, it is a common
practice that spectral information over the entire frequency band is used for feature …

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 …

Recent advancements in voice conversion (VC) and speech synthesis research make
speech-based biometric systems highly prone to spoofing attacks. This can provoke an …