Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

Speaker identity is one of the important characteristics of human speech. In voice
conversion, we change the speaker identity from one to another, while kee** the linguistic …

ASVspoof 2021 is the forth edition in the series of biannual challenges which aim to promote
the study of spoofing and the design of countermeasures to protect automatic speaker …

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

Spoofing countermeasures aim to protect automatic speaker verification systems from being
manipulated by spoofed speech signals. While results from the most recent ASVspoof 2019 …

Deep learning has been successfully applied to solve various complex problems ranging
from big data analytics to computer vision and human-level control. Deep learning advances …

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 …

Abstract Deepfakes (" deep learning"+" fake") are synthetically-generated videos from AI
algorithms. While they could be entertaining, they could also be misused for falsifying …

Human voices can be used to authenticate the identity of the speaker, but the automatic
speaker verification (ASV) systems are vulnerable to voice spoofing attacks, such as …

The performance of spoofing countermeasure systems depends fundamentally upon the use
of sufficiently representative training data. With this usually being limited, current solutions …