This is the SSF! wiki glossary. See resources for examples you will often find linked for your convenience.
- 1 Adequate Porn Watcher AI
- 2 Appearance and voice theft
- 3 Bidirectional reflectance distribution function
- 4 Burqa
- 5 Covert modeling
- 6 Deepfake
- 7 DARPA
- 8 Digital look-alike
- 9 Digital sound-alike
- 10 Generative adversial network
- 11 Human image synthesis
- 12 Light stage
- 13 Media forensics
- 14 Niqāb
- 15 No camera
- 16 No microphone
- 17 Reflectance capture
- 18 Spectrogram
- 19 Speech synthesis
- 20 Synthetic porn
- 21 Transfer learning
- 22 Voice changer
- 23 References
Adequate Porn Watcher AI
Appearance and voice theft
Appearance is thieved with digital look-alikes and voice is thieved with digital sound-alikes. These are new and very extreme forms of identity theft. Ban covert modeling and possession and doing anything with a model of a human's voice, but don't ban the Adequate Porn Watcher AI.
Bidirectional reflectance distribution function
“The bidirectional reflectance distribution function (BRDF) is a function of four real variables that defines how light is reflected at an opaque surface. It is employed in the optics of real-world light, in computer graphics algorithms, and in computer vision algorithms.”
A BRDF model is a 7 dimensional model containing geometry, textures and reflectance of the subject.
The seven dimensions of the BRDF model are as follows:
- 3 cartesian X,Y,Z
- 2 for the entry angle
- 2 for the exit angle of the light.
Covert modeling refers to both covertly modeling aspects of a subject i.e. without express consent.
Main known cases are
- Covertly modeling the human appearance into 7-dimensional Bidirectional reflectance distribution function model or other type of model.
- Covertly modeling the human voice
There is work ongoing to model e.g. human's style of writing, but this is probably not as drastic a threat as the covert modeling of appearance and of voice.
“Deepfake (a portmanteau of "deep learning" and "fake") is a technique for human image synthesis based on artificial intelligence. It is used to combine and superimpose existing images and videos onto source images or videos using a machine learning technique called a "generative adversarial network" (GAN).”
The Defense Advanced Research Projects Agency (w:DARPA) is an agency of the w:United States Department of Defense responsible for the development of emerging technologies for use by the military. (Wikipedia)
- DARPA program: 'Media Forensics (MediFor)' at darpa.mil since 2016
- DARPA program: 'Semantic Forensics (SemaFor) at darpa.mil since 2019
When the camera does not exist, but the subject being imaged with a simulation of a (movie) camera deceives the watcher to believe it is some living or dead person it is a digital look-alike.
When it cannot be determined by human testing, is some synthesized recording a simulation of some person's speech, or is it a recording made of that person's actual real voice, it is a digital sound-alike.
Generative adversial network
“A generative adversarial network (GAN) is a class of g systems. Two neural networks contest with each other in a zero-sum game framework. This technique can generate photographs that look at least superficially authentic to human observers, having many realistic characteristics. It is a form of unsupervised learning]].”
Human image synthesis
“Human image synthesis can be applied to make believable and even photorealistic of human-likenesses, moving or still. This has effectively been the situation since the early 2000s. Many films using computer generated imagery have featured synthetic images of human-like characters digitally composited onto the real or other simulated film material.”
Media forensics deal with ascertaining genuinity of media.
“Wikipedia does not have an article on w:Media forensics”
No camera (!) refers to the fact that a simulation of a camera is not a camera. If people realize the differences, and thus the different restrictions by many types of laws e.g. physics, physiology. Analogously see #No microphone, usually seen below this entry.
No microphone is needed when using synthetic voices as you just model them, without needing to capture. Analogously see the entry #No camera, usually seen above this entry.
Reflectance capture is made by measuring the reflected light for each incoming light direction and every exit direction, often with many different wavelengths. Using polarisers allow to separately capture the specular and the diffuse reflected light. The first known reflectance capture over the human face was made in 1999 by Paul Debevec et al at the w:University of Southern California.
w:Spectrograms are used extensively in the fields of w:music, w:linguistics, w:sonar, w:radar, w:speech processing, w:seismology, and others. Spectrograms of audio can be used to identify spoken words phonetically, and to analyse the various calls of animals. (Wikipedia)
“Speech synthesis is the artificial production of human speech”
Synthetic terror porn
Synthetic terror porn is pornography synthesized with terrorist intent. Synthetic rape porn is probably by far the most prevalent form of this, but it must be noted that synthesizing concentual looking sex scenes can also be terroristic in intent and effect.
“Transfer learning (TL) is a research problem in machine learning (ML) that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem.”
“The term voice changer (also known as voice enhancer) refers to a device which can change the tone or pitch of or add distortion to the user's voice, or a combination and vary greatly in price and sophistication.”
Please see Resources#List of voice changers for some alternatives.