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Synthetic human-like fakes: Difference between revisions
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* '''2016''' | science | '''[http://www.niessnerlab.org/projects/thies2016face.html 'Face2Face: Real-time Face Capture and Reenactment of RGB Videos' at Niessnerlab.org]''' A paper (with videos) on the semi-real-time 2D video manipulation with gesture forcing and lip sync forcing synthesis by Thies et al, Stanford. <font color="green">'''Relevancy: certain'''</font> | * '''2016''' | science | '''[http://www.niessnerlab.org/projects/thies2016face.html 'Face2Face: Real-time Face Capture and Reenactment of RGB Videos' at Niessnerlab.org]''' A paper (with videos) on the semi-real-time 2D video manipulation with gesture forcing and lip sync forcing synthesis by Thies et al, Stanford. <font color="green">'''Relevancy: certain'''</font> | ||
[[File:Adobe Corporate Logo.png|thumb|right|300px|[[w:Adobe Inc.]]'s logo. We can thank Adobe for publicly demonstrating their sound-like-anyone machine before an implementation was sold to criminal organizations.]] | [[File:Adobe Corporate Logo.png|thumb|right|300px|[[w:Adobe Inc.]]'s logo. We can thank Adobe for publicly demonstrating their sound-like-anyone-machine in '''2016''' before an implementation was sold to criminal organizations.]] | ||
* '''<font color="red">2018</font>''' | <font color="red">science</font> and demonstration | '''[[w:Adobe Inc.]]''' publicly demonstrates '''[[w:Adobe Voco]]''', a '''sound-like-anyone machine''' [https://www.youtube.com/watch?v=I3l4XLZ59iw '#VoCo. Adobe Audio Manipulator Sneak Peak with Jordan Peele | Adobe Creative Cloud' on Youtube]. THe original Adobe Voco required '''20 minutes''' of sample '''to thieve a voice'''. <font color="green">'''Relevancy: certain'''</font>. | * '''<font color="red">2018</font>''' | <font color="red">science</font> and demonstration | '''[[w:Adobe Inc.]]''' publicly demonstrates '''[[w:Adobe Voco]]''', a '''sound-like-anyone machine''' [https://www.youtube.com/watch?v=I3l4XLZ59iw '#VoCo. Adobe Audio Manipulator Sneak Peak with Jordan Peele | Adobe Creative Cloud' on Youtube]. THe original Adobe Voco required '''20 minutes''' of sample '''to thieve a voice'''. <font color="green">'''Relevancy: certain'''</font>. | ||
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</ref> <font color="green">'''Relevancy: certain'''</font> | </ref> <font color="green">'''Relevancy: certain'''</font> | ||
[[File:GoogleLogoSept12015.png|thumb|right|300px|[[w:Google|Google]]'s logo. Google Research demonstrated their [https://google.github.io/tacotron/publications/speaker_adaptation/ sound-like-anyone-machine] at the 2018 [[w:Conference on Neural Information Processing Systems]] (NeurIPS). It requires only 5 seconds of sample to steal a voice.]] | [[File:GoogleLogoSept12015.png|thumb|right|300px|[[w:Google|Google]]'s logo. Google Research demonstrated their '''[https://google.github.io/tacotron/publications/speaker_adaptation/ sound-like-anyone-machine]''' at the '''2018''' [[w:Conference on Neural Information Processing Systems|Conference on Neural Information Processing Systems]] (NeurIPS). It requires only 5 seconds of sample to steal a voice.]] | ||
* '''<font color="red">2018</font>''' | <font color="red">science</font> and <font color="red">demonstration</font> | The work [http://papers.nips.cc/paper/7700-transfer-learning-from-speaker-verification-to-multispeaker-text-to-speech-synthesis 'Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis'] ([https://arxiv.org/abs/1806.04558 at arXiv.org]) was presented at the 2018 [[w:Conference on Neural Information Processing Systems]] (NeurIPS). The pre-trained model is able to steal voices from a sample of only '''5 seconds''' with almost convincing results. | * '''<font color="red">2018</font>''' | <font color="red">science</font> and <font color="red">demonstration</font> | The work [http://papers.nips.cc/paper/7700-transfer-learning-from-speaker-verification-to-multispeaker-text-to-speech-synthesis 'Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis'] ([https://arxiv.org/abs/1806.04558 at arXiv.org]) was presented at the 2018 [[w:Conference on Neural Information Processing Systems]] (NeurIPS). The pre-trained model is able to steal voices from a sample of only '''5 seconds''' with almost convincing results. | ||