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→Events against synthetic human-like fakes: + '''CVPR 2021 research areas visualization by Joshua Preston''' at public.tableau.com + tweaks
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Juho Kunsola (talk | contribs) (→Events against synthetic human-like fakes: + '''CVPR 2021 research areas visualization by Joshua Preston''' at public.tableau.com + tweaks) |
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== Singing syntheses == | == Singing syntheses == | ||
As of 2020 the digital sing-alikes may not yet be here, but when we hear a faked singing voice and we cannot hear that it is fake, then we will know. An ability to sing does not seem to add much hostile capabilities compared to the ability to thieve spoken word. | As of 2020 the '''digital sing-alikes''' may not yet be here, but when we hear a faked singing voice and we cannot hear that it is fake, then we will know. An ability to sing does not seem to add much hostile capabilities compared to the ability to thieve spoken word. | ||
* [https://arxiv.org/abs/1910.11690 ''''''Fast and High-Quality Singing Voice Synthesis System based on Convolutional Neural Networks'''''' at arxiv.org], a 2019 singing voice synthesis technique using [[w:convolutional neural network|w:convolutional neural networks (CNN)]]. Accepted into the 2020 [[w:International Conference on Acoustics, Speech, and Signal Processing|International Conference on Acoustics, Speech, and Signal Processing (ICASSP)]]. | * [https://arxiv.org/abs/1910.11690 ''''''Fast and High-Quality Singing Voice Synthesis System based on Convolutional Neural Networks'''''' at arxiv.org], a 2019 singing voice synthesis technique using [[w:convolutional neural network|w:convolutional neural networks (CNN)]]. Accepted into the 2020 [[w:International Conference on Acoustics, Speech, and Signal Processing|International Conference on Acoustics, Speech, and Signal Processing (ICASSP)]]. | ||
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* [[w:Category:Singing software synthesizers]] | * [[w:Category:Singing software synthesizers]] | ||
== Text syntheses == | == Text syntheses == | ||
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# Offensively, to thieve somebody else's handwriting style | # Offensively, to thieve somebody else's handwriting style | ||
Here we find a | If the handwriting-like synthesis passes human and media forensics testing, it is a '''digital handwrite-alike'''. | ||
Here we find a '''risk''' similar to that which realized when the '''[[w:speaker recognition]] systems''' turned out to be instrumental in the development of '''[[#Digital sound-alikes|digital sound-alikes]]'''. After the knowledge needed to recognize a speaker was [[w:Transfer learning|w:transferred]] into a generative task in 2018 by Google researchers, we no longer cannot effectively determine for English speakers which recording is human in origin and which is from a machine origin. | |||
'''Handwriting-like syntheses''': | '''Handwriting-like syntheses''': | ||
[[w:Recurrent neural network]]s (RNN) seem are a popular choice for this task. | |||
* [https://github.com/topics/handwriting-synthesis GitHub topic '''handwriting-synthesis'''] has 29 public repositories as of September 2021 | * [https://github.com/topics/handwriting-synthesis GitHub topic '''handwriting-synthesis'''] has 29 public repositories as of September 2021. | ||
* [https://github.com/topics/handwriting-generation GitHub topic '''handwriting-generation'''] has 21 public repositories as of September 2021. | * [https://github.com/topics/handwriting-generation GitHub topic '''handwriting-generation'''] has 21 public repositories as of September 2021. | ||
* [https://www.sciencedirect.com/science/article/abs/pii/S0031320319303814 '''''Deep imitator: Handwriting calligraphy imitation via deep attention networks'''' at sciencedirect.com], published in [[w:Pattern Recognition (journal)]] in August '''2020'''. | |||
* [https://greydanus.github.io/2016/08/21/handwriting/ '''Scribe''' - ''Generating Realistic Handwriting with TensorFlow'' at greydanus.github.io] blog post published on '''2016'''-08-21. [https://github.com/greydanus/scribe '''Scribe code''' at github.com] | |||
* [https://dl.acm.org/doi/10.1145/2886099 '''''My Text in Your Handwriting''''' at dl.acm.org], a system from [[w:University College London]] published on '''2016'''-05-18 in [[w:ACM Transactions on Graphics]].<ref group="1st seen in">https://www.ucl.ac.uk/news/2016/aug/new-computer-programme-replicates-handwriting via Google search for "ai handwriting generator"</ref> | * [https://dl.acm.org/doi/10.1145/2886099 '''''My Text in Your Handwriting''''' at dl.acm.org], a system from [[w:University College London]] published on '''2016'''-05-18 in [[w:ACM Transactions on Graphics]].<ref group="1st seen in">https://www.ucl.ac.uk/news/2016/aug/new-computer-programme-replicates-handwriting via Google search for "ai handwriting generator"</ref> | ||
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:# [https://www.calligrapher.ai/ '''Calligrapher.ai''' - ''Realistic computer-generated handwriting''] - The user may control parameters: speed, legibility, stroke width and style. The domain is registered by some organization in Iceland and the website offers no about-page<ref group="note">https://seanvasquez.com/handwriting-generation redirects to Calligrapher.ai - seen in https://www.reddit.com/r/MachineLearning/comments/gh9cbg/p_generate_handwriting_with_an_inbrowser/</ref>. According to [https://www.reddit.com/r/MachineLearning/comments/gh9cbg/p_generate_handwriting_with_an_inbrowser/ this reddit post] Calligrapher.ai is based on Graves' 2013 work, but "''adds an [[w:inference]] model to allow for sampling latent style vectors (similar to the VAE model used by SketchRNN)''".<ref>https://www.reddit.com/r/MachineLearning/comments/gh9cbg/p_generate_handwriting_with_an_inbrowser/</ref> | :# [https://www.calligrapher.ai/ '''Calligrapher.ai''' - ''Realistic computer-generated handwriting''] - The user may control parameters: speed, legibility, stroke width and style. The domain is registered by some organization in Iceland and the website offers no about-page<ref group="note">https://seanvasquez.com/handwriting-generation redirects to Calligrapher.ai - seen in https://www.reddit.com/r/MachineLearning/comments/gh9cbg/p_generate_handwriting_with_an_inbrowser/</ref>. According to [https://www.reddit.com/r/MachineLearning/comments/gh9cbg/p_generate_handwriting_with_an_inbrowser/ this reddit post] Calligrapher.ai is based on Graves' 2013 work, but "''adds an [[w:inference]] model to allow for sampling latent style vectors (similar to the VAE model used by SketchRNN)''".<ref>https://www.reddit.com/r/MachineLearning/comments/gh9cbg/p_generate_handwriting_with_an_inbrowser/</ref> | ||
''' Handwriting recognition ''' | |||
''' Handwriting recognition ''' | * '''[[w:Handwriting recognition]]''' ('''HWR'''), also known as '''Handwritten Text Recognition''' ('''HTR'''), is the ability of a computer to receive and interpret intelligible [[w:handwriting|w:handwritten]] input (Wikipedia) | ||
* '''[[w:Intelligent word recognition]]''', or '''IWR''', is the recognition of unconstrained handwritten words.<ref> | |||
{{Cite web | |||
|url=https://www.efilecabinet.com/what-is-iwr-intelligent-word-recognition-how-is-it-related-to-document-management/ | |||
|title=What is IWR? (Intelligent Word Recognition) | |||
|date=2016-01-04 | |||
|website=eFileCabinet | |||
|language=en-US | |||
|access-date=2021-09-21 | |||
}} | |||
</ref> (Wikipedia) | |||
* [https://github.com/topics/handwriting-recognition GitHub topic '''handwriting-recognition'''] contains 238 repositories as of September 2021. | * [https://github.com/topics/handwriting-recognition GitHub topic '''handwriting-recognition'''] contains 238 repositories as of September 2021. | ||
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</ref> - ''Open Media Forensics Challenge Evaluation (OpenMFC) is an open evaluation series organized by the NIST to assess and measure the capability of media forensic algorithms and systems.''<ref>https://www.nist.gov/itl/iad/mig/open-media-forensics-challenge</ref> | </ref> - ''Open Media Forensics Challenge Evaluation (OpenMFC) is an open evaluation series organized by the NIST to assess and measure the capability of media forensic algorithms and systems.''<ref>https://www.nist.gov/itl/iad/mig/open-media-forensics-challenge</ref> | ||
* '''2021''' | '''[[w:Conference on Computer Vision and Pattern Recognition]] (CVPR)''' 2021 | * '''2021''' | '''[[w:Conference on Computer Vision and Pattern Recognition]] (CVPR)''' 2021 | ||
** [https://public.tableau.com/app/profile/joshpreston/viz/CVPR2021/Dashboard1 '''CVPR 2021 research areas visualization by Joshua Preston''' at public.tableau.com] | |||
** [https://sites.google.com/view/mediaforensics2021 2021 ''''Workshop on Media Forensics'''' in CVPR 2021 at sites.google.com], a '''June 2021''' workshop at the Conference on Computer Vision and Pattern Recognition. | |||
* '''2020''' | [http://cvpr2020.thecvf.com/ '''CVPR''' 2020] | [https://sites.google.com/view/wmediaforensics2020/home 2020 Conference on Computer Vision and Pattern Recognition: ''''Workshop on Media Forensics'''' at sites.google.com], a '''June 2020''' workshop at the Conference on Computer Vision and Pattern Recognition. | * '''2020''' | [http://cvpr2020.thecvf.com/ '''CVPR''' 2020] | [https://sites.google.com/view/wmediaforensics2020/home 2020 Conference on Computer Vision and Pattern Recognition: ''''Workshop on Media Forensics'''' at sites.google.com], a '''June 2020''' workshop at the Conference on Computer Vision and Pattern Recognition. | ||