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

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

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.

Original languageEnglish
Title of host publicationMM 2022 - Proceedings of the 30th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages7405-7406
Number of pages2
ISBN (Electronic)9781450392037
DOIs
Publication statusPublished - 10 Oct 2022
Externally publishedYes
Event30th ACM International Conference on Multimedia, MM 2022 - Lisboa, Portugal
Duration: 10 Oct 202214 Oct 2022

Conference

Conference30th ACM International Conference on Multimedia, MM 2022
Country/TerritoryPortugal
CityLisboa
Period10/10/2214/10/22

Keywords

  • audio multimedia
  • deepfake detection

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