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 …

The revolutionary breakthroughs in Machine Learning (ML) and Artificial Intelligence (AI) are
extensively being harnessed across a diverse range of domains, eg, forensic science …

Advancements in AI-synthesized human voices have created a growing threat of
impersonation and disinformation, making it crucial to develop methods to detect synthetic …

Fake audio detection is a growing concern and some relevant datasets have been designed
for research. However, there is no standard public Chinese dataset under complex …

Thanks to recent advances in deep leaning, sophisticated generation tools exist, nowadays,
that produce extremely realistic synthetic speech. However, malicious uses of such tools are …

Generative deep learning techniques have invaded the public discourse recently. Despite
the advantages, the applications to disinformation are concerning as the counter-measures …

The rapid evolution of speech synthesis and voice conversion has raised substantial
concerns due to the potential misuse of such technology, prompting a pressing need for …

Current fake audio detection algorithms have achieved promising performances on most
datasets. However, their performance may be significantly degraded when dealing with …

In this paper the current status and open challenges of synthetic speech detection are
addressed. The work comprises an initial analysis of available open datasets and of existing …

Methods that can generate synthetic speech which is perceptually indistinguishable from
speech recorded by a human speaker are easily available. Several incidents report misuse …