LEADER 01720nam  2200337   450 
001 9910623979103321
005 20230830152813.0
035   $a(CKB)5710000000060812
035   $a(NjHacI)995710000000060812
035   $a(EXLCZ)995710000000060812
100   $a20230830d2022      uy             0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aProceedings of the 1st International Workshop on Deepfake Detection for Audio Multimedia /$fJianhua Tao [and nine others]
210  1$aNew York :$cAssociation for Computing Machinery,$d2022.
215   $a1 online resource (101 pages)
311   $a1-4503-9496-5 
330   $aIt is our great pleasure to welcome you to the 1st International Workshop on Deepfake Detection for Audio Multimedia - DDAM 2022. Audio deepfake detection is an emerging topic in multimedia fields, which was included in the ASVspoof 2021. 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. As far as we know, we are the first workshop to focus on deepfake detection of audio multimedia, which is of great significance.
606   $aSignal processing
615  0$aSignal processing.
676   $a621.3822
700   $aTao$b Jianhua$01063415
801  0$bNjHacI
801  1$bNjHacl
906   $aBOOK
912   $a9910623979103321
996   $aProceedings of the 1st International Workshop on Deepfake Detection for Audio Multimedia$93549468
997   $aUNINA