Generative machine learning models have made convincing voice synthesis a reality. While
such tools can be extremely useful in applications where people consent to their voices …

Speech deepfakes are artificial voices generated by machine learning models. Previous
literature has highlighted deepfakes as one of the biggest security threats arising from …

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

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 …

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 …

While the significant advancements have made in the generation of deepfakes using deep
learning technologies, its misuse is a well-known issue now. Deepfakes can cause severe …

The rise of singing voice synthesis presents critical challenges to artists and industry
stakeholders over unauthorized voice usage. Unlike synthesized speech, synthesized …

The recent emergence of deepfakes has brought manipulated and generated content to the
forefront of machine learning research. Automatic detection of deepfakes has seen many …

The rapid spread of media content synthesis technology and the potentially damaging
impact of audio and video deepfakes on people's lives have raised the need to implement …

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 …