Synthetic human-like fakes: Difference between revisions

Synthetic human-like fakes (edit)

Revision as of 10:33, 8 November 2022

955 bytes removed , 1 year ago

→‎2020's synthetic human-like fakes: + LST transclusion from Protecting President Zelenskyy against deep fakes

Juho Kunsola

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 * '''2022''' | '''<font color="green">counter-measure</font>''' | {{#lst:Who Are You (I Really Wanna Know)? Detecting Audio DeepFakes Through Vocal Tract Reconstruction|what-is-it}}{{#lst:Who Are You (I Really Wanna Know)? Detecting Audio DeepFakes Through Vocal Tract Reconstruction|original-reporting}}
-* '''2022''' | '''<font color="green">counter-measure</font>''' | [https://arxiv.org/pdf/2206.12043.pdf '''''Protecting President Zelenskyy against deep fakes''''' a 2022 preprint at arxiv.org] by Matyáš Boháček of Johannes Kepler Gymnasium and [[w:Hany Farid]], the dean and head of of [[w:University of California, Berkeley School of Information|w:Berkeley School of Information at the University of California, Berkeley]]. This brief paper describes their automated digital look-alike detection system and evaluate its efficacy and reliability in comparison to humans with untrained eyes. Their work provides automated evaluation tools to catch so called "deep fakes" and their motivation seems to have been to find automation armor against disinformation warfare against humans and the humanity. Automated digital [[Glossary#Media forensics|media forensics]] is a very good idea explored by many.  Boháček and Farid 2022 detection system works by evaluating both facial mannerisms as well as gestural mannerisms to detect the non-human ones from the ones that are human in origin.
+* '''2022''' | '''<font color="green">counter-measure</font>''' | {{#lst:Protecting President Zelenskyy against deep fakes|what-is-it}}
 * '''2022''' | '''<font color="green">science / review of counter-measures</font>''' | [https://www.mdpi.com/1999-4893/15/5/155 ''''''A Review of Modern Audio Deepfake Detection Methods: Challenges and Future Directions'''''' at mdpi.com]<ref name="Audio Deepfake detection review 2022">