Benchmarking initiatives support the meaningful comparison of competing solutions to
prominent problems in speech and language processing. Successive benchmarking …

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 …

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 …

Deepfakes, particularly audio deepfakes, have become pervasive and pose unique, ever‐
changing threats to society. This paper reviews the current research landscape on audio …

Thanks to advancements in deep learning, speech generation systems now power a variety
of real-world applications, such as text-to-speech for individuals with speech disorders …

The current speech anti-spoofing countermeasures (CMs) show excellent performance on
specific datasets. However, removing the silence of test speech through Voice Activity …

With the rapid development of deep learning techniques, the generation and counterfeiting
of multimedia material has become increasingly simple. Current technology enables the …

Substantial progress in spoofing and deepfake detection has been made in recent years.
Nonetheless, the community has yet to make notable inroads in providing an explanation for …

Text-to-Speech (TTS) technology brings significant advantages, such as giving a voice to
those with speech impairments, but also enables audio deepfakes and spoofs. The former …

A good training set for speech spoofing countermeasures requires diverse TTS and VC
spoofing attacks, but generating TTS and VC spoofed trials for a target speaker may be …