A deepfake is content or material that is synthetically generated or manipulated using
artificial intelligence (AI) methods, to be passed off as real and can include audio, video …

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 …

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

Current text-to-speech algorithms produce realistic fakes of human voices, making deepfake
detection a much-needed area of research. While researchers have presented various …

This paper describes the Speech Technology Center (STC) antispoofing systems submitted
to the ASVspoof 2019 challenge. The ASVspoof2019 is the extended version of the previous …

The state-of-art models for speech synthesis and voice conversion are capable of
generating synthetic speech that is perceptually indistinguishable from bonafide human …

We present JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with
Squeeze-Excitation and Residual neTworks (ASSERT). Anti-spoofing has gathered more …

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

The now-acknowledged vulnerabilities of automatic speaker verification (ASV) technology to
spoofing attacks have spawned interests to develop so-called spoofing countermeasures …

Deep generative modeling has the potential to cause significant harm to society.
Recognizing this threat, a magnitude of research into detecting so-called" Deepfakes" has …