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Synthetic human-like fakes: Difference between revisions
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to be -> was (Interespeech 2022 was held in September in Korea)
Juho Kunsola (talk | contribs) (→2020's synthetic human-like fakes: replaced the some text moved to a dedicated article with {{#lst:Who Are You (I Really Wanna Know)? Detecting Audio DeepFakes Through Vocal Tract Reconstruction|what-is-it}} and {{#lst:Who Are You (I Really Wanna Know)? Detecting Audio DeepFakes Through Vocal Tract Reconstruction|original-reporting}}) |
Juho Kunsola (talk | contribs) m (to be -> was (Interespeech 2022 was held in September in Korea)) |
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</ref>, a review of audio deepfake detection methods by researchers Zaynab Almutairi and Hebah Elgibreen of the [[w:King Saud University]], Saudi Arabia published in [[w:Algorithms (journal)]] on Wednesday 2022-05-04 published by the [[w:MDPI]] (Multidisciplinary Digital Publishing Institute). This article belongs to the Special Issue [https://www.mdpi.com/journal/algorithms/special_issues/Adversarial_Federated_Machine_Learning ''Commemorative Special Issue: Adversarial and Federated Machine Learning: State of the Art and New Perspectives'' at mdpi.com] | </ref>, a review of audio deepfake detection methods by researchers Zaynab Almutairi and Hebah Elgibreen of the [[w:King Saud University]], Saudi Arabia published in [[w:Algorithms (journal)]] on Wednesday 2022-05-04 published by the [[w:MDPI]] (Multidisciplinary Digital Publishing Institute). This article belongs to the Special Issue [https://www.mdpi.com/journal/algorithms/special_issues/Adversarial_Federated_Machine_Learning ''Commemorative Special Issue: Adversarial and Federated Machine Learning: State of the Art and New Perspectives'' at mdpi.com] | ||
* '''2022''' | '''<font color="green">science / counter-measure</font>''' | [https://arxiv.org/abs/2203.15563 ''''''Attacker Attribution of Audio Deepfakes'''''' at arxiv.org], a pre-print | * '''2022''' | '''<font color="green">science / counter-measure</font>''' | [https://arxiv.org/abs/2203.15563 ''''''Attacker Attribution of Audio Deepfakes'''''' at arxiv.org], a pre-print was presented at the [https://www.interspeech2022.org/ Interspeech 2022 conference] organized by [[w:International Speech Communication Association]] in Korea September 18-22 2022. | ||
* '''2021''' | Science and demonstration | In the NeurIPS 2021 held virtually in December researchers from Nvidia and [[w:Aalto University]] present their paper [https://nvlabs.github.io/stylegan3/ '''''Alias-Free Generative Adversarial Networks (StyleGAN3)''''' at nvlabs.github.io] and associated [https://github.com/NVlabs/stylegan3 implementation] in [[w:PyTorch]] and the results are deceivingly human-like in appearance. [https://nvlabs-fi-cdn.nvidia.com/stylegan3/stylegan3-paper.pdf StyleGAN3 paper as .pdf at nvlabs-fi-cdn.nvidia.com] | * '''2021''' | Science and demonstration | In the NeurIPS 2021 held virtually in December researchers from Nvidia and [[w:Aalto University]] present their paper [https://nvlabs.github.io/stylegan3/ '''''Alias-Free Generative Adversarial Networks (StyleGAN3)''''' at nvlabs.github.io] and associated [https://github.com/NVlabs/stylegan3 implementation] in [[w:PyTorch]] and the results are deceivingly human-like in appearance. [https://nvlabs-fi-cdn.nvidia.com/stylegan3/stylegan3-paper.pdf StyleGAN3 paper as .pdf at nvlabs-fi-cdn.nvidia.com] | ||