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

J. Tao, Jiangyan Yi, Cunhang Fan, Ruibo Fu, Shan Liang, Pengyuan Zhang, Haizhou Li, H. Meng, Dong Yu, M. Akagi
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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.
第一届音频多媒体深度伪造检测国际研讨会[j]
在过去的几年里,随着深度学习的发展,语音合成和语音转换技术取得了显著的进步。这些模型可以生成逼真的、类似人类的语音。对于大多数人来说,很难将生成的音频与真实音频区分开来。然而,如果一些攻击者和犯罪分子出于伤害的目的滥用这项技术,也会对全球政治经济和社会稳定构成巨大威胁。在本次研讨会中,我们的目标是汇集来自音频深度伪造检测、音频深度合成、音频伪造游戏和对抗性攻击领域的研究人员,进一步讨论在多媒体中检测深度伪造和操纵音频的最新研究和未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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