DDAM '22: 1st International Workshop on Deepfake Detection for Audio Multimedia

Jianhua Tao, Jiangyan Yi, Cunhang Fan, Ruibo Fu, Shan Liang, Pengyuan Zhang, Haizhou Li, Helen Meng, Dong Yu, Masato Akagi

Abstract: Over the last few years, the technology of speech synthesis and voice conversion has made significant improvement with the development of deep learning. The models can generate realistic and human-like speech. It is difficult for most people to distinguish the generated audio from the real. However, this technology also poses a great threat to the global political economy and social stability if some attackers and criminals misuse it with the intent to cause harm. In this workshop, we aim to bring together researchers from the fields of audio deepfake detection, audio deep synthesis, audio fake game and adversarial attacks to further discuss recent research and future directions for detecting deepfake and manipulated audios in multimedia.