System for authenticating digital content

Abstract

To provide a system for authenticating digital contents so that content owners and / or distributors are not exposed to potential legal risk.SOLUTION: A system receives a digital content having an audio track including a monologue and / or a dialog, identifies an image of a person depicted in the digital content, detects at least one linguistic mannerism of the person depicted in the image, obtains one of the linguistic profiles of the person depicted in the image, performs a comparison of the detected linguistic mannerism with the linguistic mannerism contained in the linguistic profile, and determines, based on the comparison, whether the person depicted in the image is a true and accurate depiction of the person.SELECTED DRAWING: Figure 5

Description

[Background technology]

[0001] Advances in machine learning could make it possible to create realistic-looking replicas of people's images or voices. It uses deep artificial neural networks for its creation. Deepfakes are known as "deepfakes" due to the fact that they are images or The audio is made without the consent of the person whose voice is being used and does not actually say or do anything that person did. They can appear to say or do things that they did not. Fake and manipulated digital content can be used maliciously to spread misinformation.

[0002] Digital content is widely used for entertainment and news distribution Therefore, effective authentication and management of that content depends on the content creators, owners, However, as machine learning solutions continue to improve, Deepfakes are becoming harder and harder to detect as they become more common. As a result, slightly altered or completely fake digital content will be is inadvertently broadcast or distributed in violation of contractual agreements or regulatory restrictions, thereby This could potentially expose content owners and / or distributors to legal jeopardy. Summary of the Invention

[0003] A system for authenticating digital content is provided that substantially relates to at least one diagram By what has been shown and / or described in conjunction with the claims, Provided by being fully specified. [Brief explanation of the drawings]

[0004] [Figure 1] FIG. 1 shows a diagram of an exemplary system for authenticating digital content, according to one implementation. [Figure 2] FIG. 2 illustrates another exemplary implementation of a system for authenticating digital content. [Figure 3] FIG. 3 shows an exemplary diagram of authenticity analysis software code suitable for execution by the hardware processor of the system shown in FIGS. [Figure 4] FIG. 4 is a flowchart presenting an exemplary method for use by a system for authenticating digital content, according to one implementation. [Figure 5] FIG. 5 is a flowchart presenting an exemplary method for use by a system for authenticating digital content, according to another implementation. [Figure 6] FIG. 6 is a flowchart presenting an exemplary method for use by a system for authenticating digital content, according to yet another implementation. DETAILED DESCRIPTION OF THE INVENTION

[0005] The following description includes specific information regarding implementations of the present disclosure. It will be appreciated that the teachings may be implemented in ways other than those specifically discussed herein. The drawings and accompanying detailed description of the present application are directed to exemplary implementations only. Unless otherwise noted, like or corresponding elements among the figures are designated by like or corresponding reference numerals. Furthermore, the drawings and illustrations herein are generally not to scale and may be indicative of actual It is not intended to correspond to relative dimensions.

[0006] The present application provides a method for authenticating digital content that overcomes the difficulties and deficiencies in the prior art. In some implementations, the content authentication solution is may be performed as a substantially automated process by a substantially automated system As used herein, the terms "automation," "automated," And "automate" refers to systems that do not require the participation of a human user, such as a system administrator. Note that the term refers to systems and processes. In some implementations, The automated system described herein allows a system operator or administrator to The method described in this application can be used to verify the sex determination, but human involvement is optional. The method is performed under the control of the hardware processing components of the disclosed automated system. It can be carried out.

[0007] FIG. 1 illustrates an exemplary system for authenticating digital content, according to one implementation. As discussed below, the system 100 is a local area network (LAN). It may also be implemented using a computer server accessible via a LAN. Alternatively, it may be implemented as a cloud-based system. As shown in Figure 1 The system 100 includes a hardware processor 104 and a non-transitory storage device. A computing device having an installed system memory 106 and a display 108. According to this exemplary implementation, the system includes a system memory 106 biometric data including biometric profiles 122a and 122b Base 120, language profiles 126a and 126b, and scripts 127a and and 127b, and a language database 124 containing the digital content 136. and authenticity analysis software code 110 that provides an authenticity determination 138.

[0008] As also shown in FIG. 1, the system 100 includes a network communication link 132. and a user system 140 including a display 148. The user 128 interacts with the system through the use of the user system 140. The communication network 130 and the network communication link 132 The system 100 receives digital content provided by a content contributor 134 or a user 128. Receives the digital content 136 and renders it on a display 148 of the user system 140. Note that this allows the output of an authenticity determination 138 for the purpose of filtering. Alternatively or additionally, in some implementations, the authenticity determination 138 may be performed by the system 100. It may be rendered on the display 108.

[0009] In summary, the system 100 provides, for example, embedded audio, captions, and tagging. time code and other supporting metadata such as viewing ratings and / or parental guidelines. High-definition (HD) or Ultra HD (UHD) baseband video signal with Audio-Video (AV) content in linear television (TV) program streams, including It may be implemented as a quality control (QC) resource for a media entity that provides Alternatively or additionally, a media entity that includes system 100 as a QC resource. may distribute AV content via radio or satellite radio broadcasting.

[0010] According to the exemplary implementation shown in FIG. 1, the system 100 includes a content contributor 13 4 or user system 140 and receives digital content 136 from the hardware processor. The digital signature is obtained using the authenticity analysis software code 110 executed by the processor 104. The content contributor 13 is configured to determine the authenticity of the digital content 136. 4 is an authorized media entity, including another media entity, system 100. professional news reporters, such as field reporters, or those using personal communication devices or other communications devices. Digital content in the form of home videos or other AV content produced using a digital transmission system They may also be amateur content contributors who provide digital content 136. In some implementations, content contributors 134 may utilize such a communication system to communicate Digital data is transmitted to the system 100 via a network 130 and a network communication link 132. However, in other implementations, the content projection may The contributor 134 uses the communication system and the user system used by the user 128. In these latter implementations, users may present digital content 136 to the The user 128 further utilizes the user system 140 to verify authenticity. 00, or may present digital content 136 to the Thus, the user system 140 may be used to perform the authenticity determination.

[0011] Digital content 136 may include, but is not limited to, video content without audio. , audio content without video, or AV content such as movies, TV program series , episodic content, which may include web series and / or vlogs, sports Form of content, news content, advertising content, or video game content Alternatively, in some implementations, the digital content 136 may be It may also take the form of a digital photograph.

[0012] For conceptual clarity, this application will refer to the authenticity analysis software code 110 and the biometric The tricks database 120 and the language database 124 are stored in the system memory 106. Although it is referred to as being stored in system memory 106, more generally, system memory 106 may include any computer It may take the form of a computer-readable non-transitory storage medium. Thus, the expression "computer-readable non-transitory storage medium" is used to describe a computing program. to the hardware processor 104 of the platform 102 or to the user system 140 hardware processor (hardware of the user system 140 not shown in FIG. 1) refers to any medium, other than a carrier wave or other transitory signal, that provides instructions to a processor Thus, computer-readable non-transitory media includes, for example, volatile media and non-volatile media. Various types of media may be supported, such as volatile media. It may also include dynamic memory, such as dynamic random access memory (dynamic RAM). , non-volatile memory may include optical, magnetic, or electrostatic storage devices. Common forms of readable non-transitory media are, for example, optical disks, RAM, programs, PROM (Programmable Read Only Memory), Erasable PROM (EPROM), and F Includes LASH memory.

[0013] Furthermore, FIG. 1 shows an authenticity analysis software code 110 and a biometric database. The database 120 and the language database 124 are co-located in the system memory 106. Although the representation is presented as an aid to conceptual clarity, More generally, the system 100 may be implemented as, for example, a computer server. may include one or more computing platforms 102, such as The computing platform 102 may be co-located or may be, for example, , forming interconnected but distributed systems such as cloud-based systems. You may do so.

[0014] As a result, the hardware processor 104 and the system memory 106 operate in the system 10 0. Therefore, the bio See metrics database 120 and / or language database 124, and FIG. 3. and authenticity analysis software code 11, such as one or more features described below. Various features of the present invention utilize the distributed memory and / or processor resources of the system 100. It should be understood that the present invention may be used, stored, and / or executed.

[0015] According to the implementation illustrated by FIG. 1, a user 128 utilizes a user system 140. 1, interacting with the system 100 via a communication network 130 and receiving digital content 1 In one such implementation, the computing platform may determine the authenticity of the The form 102 may be accessed via a packet-switched network such as the Internet. Alternatively, the computer may correspond to one or more web-based computer servers that are accessible from the computer. The computing platform 102 is connected to a wide area network (WAN) ), supporting LANs, or other types of limited distribution or private networks. It may correspond to one or more computer servers included in the network.

[0016] FIG. 1 also illustrates a mobile communication device, such as a smartphone or tablet computer. Although the user system 140 is depicted as a More generally, the user system 140 may provide a user interface and supports connection to the communication network 130, herein referred to as the user system. Any suitable processor implementing sufficient data processing capabilities to implement the functionality attributed to system 140. In other implementations, the user system 140 may be, for example, For example, a desktop computer, laptop computer, game console, or smartphone It may also take the form of a smart device such as a smart TV.

[0017] Regarding the display 148 of the user system 140, the display 148 It may be physically integrated with the system 140 or may be in communication with the user system 140. Note that although they are coupled, they may be physically separated. For example, The system 140 may be a smartphone, a laptop computer, a tablet computer, or When implemented as a smart TV, the display 148 is typically In contrast, if the user system 140 is a desktop computer, When implemented as a computer, the display 148 may be a user interface in the form of a computer tower. It may take the form of a monitor separate from the devices of system 140. Similarly, in FIG. As shown, the display 108 of the system 100 is It may be physically integrated with the computing platform 102 or may be The device may be communicatively coupled to, but physically separated from, the device platform 102. The displays 108 and 148 may be liquid crystal displays (LCDs), light emitting diodes (LEDs), or other ) displays, organic light-emitting diode (OLED) displays, or signal-to-light It may also be implemented as any other suitable display screen that performs physical transformations.

[0018] FIG. 2 illustrates another exemplary implementation of a system for authenticating digital content. According to the exemplary implementation shown in FIG. 2, the user system 240 The system 200 is interconnected via a communication link 232. The computing platform 202 includes a hardware processor 204 and a system and a memory 206, which stores a biometric profile 222. a biometric database 220 including a and a language profile 226 a and 226b and a language database 224 including scripts 227a and 227b and an authenticity analysis software code 210a that provides an authenticity determination 238. 2 further illustrates a display 208 of the system 200.

[0019] As shown in FIG. 2, the user system 240 includes a transceiver 243 and a hardware a processor 244 and a non-transitory memory for storing the authenticity analysis software code 210b. a computing platform having a memory 246 implemented as a device; According to the exemplary implementation shown in FIG. The code 210b is used to render on the display 248 of the user system 240. The authenticity determination 238 generally corresponds to the authenticity determination in FIG. The corresponding features correspond to decision 138 and are not intended to be limiting unless they are attributed to any feature by this disclosure. Note that the objects may share any property that is unique to them.

[0020] The network communication link 232, the hardware processor 204, the system memory 2 206, and a computing platform 202 having a display 208. Each of the systems 200 generally includes a network communication link 132 in FIG. a hardware processor 104, a system memory 106, and a display 108. and a system 100 including a computing platform 102 having Furthermore, the authenticity analysis software code 210a, the biometric database 220 , and language database 224, respectively, generally correspond to the authenticity analysis software in FIG. hardware code 110, biometric database 120, and language database 124 Therefore, the biometric database 220 and the language database 22 4, and the authenticity analysis software code 210a are used to verify the respective biometrics according to the present disclosure. The trics database 120, the language database 124, and the authenticity analysis software Any characteristics attributed to the node 110 may be shared, and vice versa.

[0021] Additionally, the biometric profiles contained in the biometric database 220 The language profiles 222a and 222b are stored in a language database 224. 6a and 226b, and the scripts 227a and 227b stored in the language database 224. 7b generally refer to biometric profiles 122a and 122b in FIG. 1, respectively. 122b, language profiles 126a and 126b, and scripts 127a and 127b. That is, the biometric profiles 222a and 222b correspond to the The word profiles 226a and 226b and the scripts 227a and 227b are used in the present disclosure. The respective biometric profiles 122a and 122b and the language profile Any characteristics resulting from the files 126a and 126b and the scripts 127a and 127b They can share gender and vice versa.

[0022] The user system 240 and display 248 in FIG. 2 generally correspond to those in FIG. corresponding features of the user system 140 and display 148 are: Any property attributed to any corresponding feature by this disclosure may be shared. Thus: Similar to user system 140, user system 240 may be, for example, a smart TV, a desktop computer, or a Desktop computers, laptop computers, tablet computers, games The device may take the form of a mobile phone or a smartphone. The user system 140 includes a computing platform 242, a transceiver 24 3. Hardware processor 244 and authenticity analysis software code 210b Additionally, displays 108 and 14 may include features corresponding to memory 246. 8, each display 208 and 248 may be an LCD, LED display, or the like. , an OLED display, or any other suitable display that performs the physical conversion of a signal to light. It may be implemented as a display screen.

[0023] The transceiver 243 allows the user system 240 to communicate over the network communication link 232. wirelessly to enable data exchange with the computing platform 202. For example, the transceiver 243 may be implemented as a fourth generation (4G) ) as a radio transceiver or as an IM established by the International Telecommunications Union (ITU) Implemented as a 5G radio transceiver configured to meet the requirements of T-2020 Regarding the authenticity analysis software code 210b, FIG. 1 can be combined with FIG. Referring to the above, in some implementations, the authenticity analysis software code 210b The digital content 136 is presented to the system 100 / 200, and the system 100 / 200 A sinker that can simply be used to render an authenticity decision 138 / 238 received from Note that the application may be a client application.

[0024] However, in other implementations, the authenticity analysis software code 210b may A software application that includes all the features of analysis software code 210a. may be able to perform all the same functionality. In one implementation, the authenticity analysis software code 210b performs the authenticity analysis Any feature corresponding to the analysis software code 110 and attributed thereto by this disclosure. may share the same characteristics.

[0025] According to the exemplary implementation shown in FIG. 2, the authenticity analysis software code 210b , located in memory 246, and the computing platform 202 or the authenticity analysis software Software Code 210b may collect network communications from any of its authorized third party sources. The signal is received by the user system 240 via the communication link 232. In this embodiment, the network communication link 232 may be, for example, a packet-switched network such as the Internet. The authentication analysis software code 210b can be transferred over the network.

[0026] Once transferred, it may be downloaded, for example, via network communications link 232. Thus, the authenticity analysis software code 210b is permanently stored in the memory 246. may be executed locally on the user system 240 by a hardware processor 244 The hardware processor 244 may be implemented, for example, in the user system 240. The CPU may be a central processing unit (CPU), and its role may be a hardware processor 2 44 runs the operating system of the user system 240 and performs authenticity analysis software. The wear code 210b is executed.

[0027] As shown in FIG. 1, in some implementations, a digital content authentication system is used to authenticate digital content. The computing platform 102 of the system 100 may include one or more web servers. Note that the data may take the form of a web-based computer server. In another implementation, the user system 240 may be implemented as a It may be configured to provide substantially all functionality. In its implementation, the computing platform of the system for authenticating digital content The platform is operated by the computing platform 242 of the user system 240. That is, in some implementations, the digital content may be authenticated. The computing platform 242 of the user system 240 for For example, computers on mobile communication devices such as smartphones or tablet computers. It may take the form of a mobile platform.

[0028] FIG. 3 illustrates the hardware processor 104 of the system 100 / 200 according to one implementation. / 204 or by the hardware processor 244 of the user system 240 An exemplary diagram of authenticity analysis software code 310 suitable for execution is shown in FIG. As shown in FIG. 1, the authenticity analysis software code 310 performs content reception and identification. module 312, biometric comparison module 314, and linguistic comparison module 31 6 and authentication module 318. Furthermore, FIG. 3 shows an authenticity analysis software component. The digital content 336 received as input to the card 310 and the biometric ratio Comparison 354, Comparison of Language Mannerisms 356, Comparison of Monologues or Dialogues 358 , as well as the authenticity determination provided as output by the authenticity analysis software code 310. 3 shows biometric profiles 322a and 322b. and a biometric database 320 including language profiles 326a and 326b. and a language database 324 containing scripts 327a and 327b.

[0029] Digital content 336 generally corresponds to digital content 136 in FIG. corresponding features are not intended to be limiting unless otherwise specified, and their ... intended to be limiting unless otherwise specified, and In FIG. 3, the authenticity determination 338 and the biometrics database 320 biometric profiles 322a and 322b; and a language database 324. The language profiles 326a and 326b and the scripts 327a and 327b are Generally, the authenticity determination 138 / 238 and the biometrics in FIGS. 1 and 2 are The database 120 / 220 and the biometric profile 122a / 222a and 122b / 222b, language database 124 / 224, and language profile 126a / 226a and 126b / 226b and scripts 127a / 227a and 127b / 2 27b and share any characteristics attributed to those corresponding features by this disclosure. obtain.

[0030] The authenticity analysis software code 310 in FIG. 3 generally corresponds to the , corresponding to the authenticity analysis software code 110 / 210a, and in some implementations, This may correspond to the authenticity analysis software code 210b in FIG. , authenticity analysis software code 110 / 210a and authenticity analysis software code 2 10b is a diagram illustrating the process of detecting any characteristics attributable to the authenticity analysis software code 310 according to the present disclosure. Therefore, the authenticity analysis software As with the code 310, the authenticity analysis software code 110 / 210a and the authenticity analysis software The software code 210b includes a content receiving and identification module 312 and a biometric a linguistic comparison module 314, a linguistic comparison module 316, and an authentication module 318. may include modules corresponding to the above.

[0031] Authenticity analysis software code 110 / 210a / 310 and authenticity analysis software The functionality of Code 210b / 310 is shown in Figures 4, 5 and 6 in combination with Figures 1, 2 and 3. 4 illustrates, according to one implementation, 1 presents an exemplary method for use by a system to authenticate digital content. FIG. 5 shows a flowchart 460 for recognizing digital content according to another implementation. Flowchart 570 presenting an exemplary method for use by the system to authenticate FIG. 6 shows a system for authenticating digital content according to yet another implementation. 4 shows a flowchart 680 presenting an exemplary method for use by the system. 5 and the method outlined in Figure 6 so as not to obscure the discussion of the inventive features in this application. For clarity, specific details and features are provided in the respective flowcharts 460, 570, and 68. Note that it is omitted from the 0.

[0032] Referring to FIG. 4 in combination with FIGS. 1, 2, and 3, a flowchart 460 illustrates: It starts by receiving the digital content 136 / 336 (action 461). As mentioned above, in some implementations, the digital content 136 / 336 may be Some examples include video content without sound, or AV content such as movies, television, etc. Episode content may include TV series, web series and / or vlogs content, sports content, news content, advertising content, or video games Alternatively, in some implementations, the content may take the form of digital content. Content 136 may take the form of a digital photograph.

[0033] As shown by FIG. 1, in one implementation, the digital content 136 is via network 130 and network communication link 132, content contributor 134 or may be received by the system 100 from a user system 140. In this paper, digital content 136 / 336 is a computing platform 10 2 / 202, and is executed by the hardware processor 104 / 204 of and the identification module 312 to analyze the authenticity of the software code 110 / 210a. However, referring to FIG. 2 in combination with FIG. In another implementation, the digital content 136 / 336 may be transmitted using a transceiver 243. and may be received by the user system 140 / 240 from the content contributor 134. In these implementations, the digital content 136 / 336 is transmitted to the user system 140. The content reception and identification module is executed by the hardware processor 244 of the The authenticity analysis software code 210b / 310 uses module 312 to It can be believed.

[0034] Flowchart 460 then continues with the person depicted in digital content 136 / 336. An image of the object is identified (act 462). In some implementations, the digital content Tsu 136 / 336 is a widely recognized name, for example, a celebrity athlete, actor, or politician. It may also be digital photographs, videos or audiovisual content containing images of people. While more commonly depicted in digital content, action The person identified in 462 has one or more corresponding biometric profiles. biometrics database 120 / 220 / 320 metric profile 122a / 222a / 322a and / or biometric profile It can be any person who has a file 122b / 222b / 322b. For example, a media entity that includes system 100 / 200 as a QC resource Thus, they may be hired actors, reporters, newsreaders, or other talent.

[0035] The same person may have multiple biometrics stored in the biometric database 120 / 220 / 320. Note that an actor may have a biometric profile of age, As you progress through your career, you will have different biometric profiles for different stages of your career. Alternatively or additionally, actors may have a voice actor for each character they play, or They will have a different biometric profile for each movie or other AV function they attend. Furthermore, in some implementations, for a person, each focuses on a particular biometric parameter(s), It may be advantageous or desirable to have a biometric profile. That is, for example, the same person may have a first biometric test for ear shape parameters over time. eye profile, a second biometric profile of eye shape parameters over time file, a third biometric profile of facial symmetry over time, etc. It may be possible.

[0036] In action 461, digital content 136 / 336 is transferred to system 100 / 20 In an implementation received by the . The identity of the person depicted in the The content receiving and identifying module is executed by the hardware processor 104 / 204. Authenticity analysis software code 110 / 210a / 310 using rule 312 However, in action 461, the digital content 136 / 3 In an implementation where 36 is received by the user system 140 / 240, the digital content The identification of the person depicted in the image contained in content 136 / 336 is performed by the user system 140 / 240 by the hardware processor 244, and the content reception and identification module 312, performed by the authenticity analysis software code 210b / 310. It can be done.

[0037] Flowchart 460 continues with the steps depicted in the image and identified in action 462. The shape parameters of the ears of the person are determined (action 463). The ear shape parameter determined by the method is a single parameter such as a single dimension of the ear of a person depicted in an image. parameters, or the sum of two or more dimensions of the ear, or the hash value of two or more dimensions of the ear The ear shape parameter in action 463 may be a combination of ear dimensions. The ear dimensions relevant to data determination are ear length, i.e., the distance from the top to the bottom of the ear; width of the ear perpendicular to the length of the ear; shape of the earlobe, e.g., pointed, round, square; and / or the location of the ear relative to one or more cranial landmarks of the person depicted in the image. The shape of the ear is quite unique and may vary between different individuals. In this regard, ear shape parameters can be particularly useful for authenticating identity. Please note:

[0038] In action 461, digital content 136 / 336 is transferred to system 100 / 20 In an implementation received by action 462, the image depicted in the image identified in action 462 is The ear shape parameters of the person are determined by the computing platform 102 / 202 hardware processor 104 / 204, and the biometric ratio The comparison module 314 is used to verify the authenticity of the software code 110 / 210a / 31 However, in action 461, the digital content In implementations where 136 / 336 is received by the user system 140 / 240, Determining the shape parameters of the ears of the person depicted in the image identified in step 462 includes: Executed by the hardware processor 244 of the user system 140 / 240, The authenticity analysis software code 210b uses the metric comparison module 314 This can be done by / 310.

[0039] Flowchart 460 continues with action 462 depicting the identified image. Determine biometric parameters of the selected person (action 464), where biometric parameters are The metric parameters are different from the ear shape parameters described above. In some implementations, the biometric parameters determined in action 464 are the distance between the eyes of the person depicted in the image (hereinafter referred to as "interpupillary distance"), or the shape or It can be a single facial parameter, such as an eye shape parameter. In this implementation, the biometric parameters determined in action 464 are two the sum of two or more facial parameters, or the hash value of two or more facial parameters, It may also be a combination of parameters of a face.

[0040] In action 461, digital content 136 / 336 is transferred to system 100 / 20 In an implementation received by the .sigma.com / 32000, the image is depicted in the image and identified in action 462. The determination of the biometric parameters of the selected person is carried out by a computing platform. 102 / 202 is executed by the hardware processor 104 / 204, and The authenticity analysis software code 110 / 210 is used to compare the However, in action 461, the digital code can be executed by In an implementation where the content 136 / 336 is received by a user system 140 / 240, The biometric parameters of the person depicted in the image identified in action 462 are used to identify the person depicted in the image. The meter determination is performed by the hardware processor 244 of the user system 140 / 240. The authenticity analysis software uses a biometric comparison module 314 to It can be implemented by Accord 210b / 310.

[0041] Flowchart 460 continues with action 463, where the determined The shape parameters of the ears of the person depicted in the image are determined in action 464. calculate a ratio for the biometric parameters of the identified person (action 465) The ratio calculated in Action 465 is a dimensionless, purely numerical ratio. It can be expressed as a ratio with units or as a hash value. and an implementation in which the digital content 136 / 336 is received by the system 100 / 200. In the morphology, the shape parameters of the ears of the person depicted in the image are compared with the The calculation of ratios for metric parameters is performed on the computing platform 1 02 / 202 is executed by the hardware processor 104 / 204, and the biometric The authenticity analysis software code 110 / 210a uses the block comparison module 314 However, in action 461, the digital In an implementation where the content 136 / 336 is received by the user system 140 / 240, , the shape parameters of the ears of the person depicted in the image, the biometry of the person depicted in the image The calculation of the ratio for the clock parameters is based on the hardware program of the user system 140 / 240. 3. The biometric comparison module 314 executes the biometric comparison process. This can be performed by the authenticity analysis software code 210b / 310.

[0042] For example, the biometric comparison module 314 may include a classification of other biometric features. The ear classifier as well as the classifier are implemented using neural networks (NNs). The classifiers may include multiple feature classifiers for ear and other biometric features. Each NN is trained on a feature to discriminate between samples, e.g., in the case of the ear classifier, , ear length, ear width, earlobe shape, etc. For example, to compare ears Then, the feature vectors for each ear sample are calculated, as well as the distance between those vectors. The more similar the samples from one ear are to the samples from another ear, the more similar their respective feature bases become. The distance between the spheres will become closer.

[0043] Flowchart 460 continues in action 465 by comparing the calculated ratio with a predetermined A comparison is performed with the value (action 466). For example, The person who has been authorized to use the system 100 / 200 as a QC resource is authorized to use the system 100 / 200 as a QC resource. If you are an actor, reporter, newsreader, or other talent employed by the The predetermined value of the ratio calculated in section 465 may be, for example, a value determined by the biometric profile. Part of one of the following rules: 122a / 220a / 322a or 122b / 22b / 322b and a biometric database 120 / 220 / 320 for each such individual. The data may be stored as follows:

[0044] In action 461, digital content 136 / 336 is transferred to system 100 / 20 In an implementation where the ratio calculated in action 465 is received by Comparison with predetermined values ​​stored in the Metrics database 120 / 220 / 320 Hardware processor 104 / 2 of computing platform 102 / 202 04 and using a biometric comparison module 314, It can be implemented by software code 110 / 210a / 310. In the application 461, the digital content 136 / 336 is transmitted to the user system 140 / 2. In an implementation received by 40, the ratio calculated in action 465 and the balance Comparison with predetermined values ​​stored in the Geometrics Database 120 / 220 / 320 Executed by the hardware processor 244 of the user system 140 / 240, The authenticity analysis software code 210b uses the metric comparison module 314 For example, in these latter implementations, the user system 140 / 240 utilizes a transceiver 243 and a communication network 130, and the system The 100 / 200 computing platform 102 / 202 stores the You may access Geometrics Database 120 / 220 / 320. Action 466 is a biometric comparison module 314 that performs authentication analysis software Code 110 / 210a / 310 or Authenticity Analysis Software Code 210b / 310 resulting in a biometric comparison 354 that is provided as input to the authentication module 318 Please note that.

[0045] The exemplary method outlined by flowchart 460 begins in action 465 with The calculated ratio and the data stored in the biometric database 120 / 220 / 320 Based on a biometric comparison 354 with a predetermined value, the person depicted in the image is identified as that person. It may end by determining whether it is a true representation of the object (action 467). For example, biometric comparison 354 compares the ratio calculated in action 465 with the biometric Matches between a given value stored in the Ometrics database 120 / 220 / 320 In this case, authenticity determination 138 / 238 / 338 determines whether the person depicted in the image is Additionally, in some implementations, the action Based on the calculated ratio and a comparison with a predetermined value, the algorithm 467 determines whether the person depicted in the image is As a result of determining that the digital content is an authentic depiction of that person, 336 may include determining that the information is authentic.

[0046] As defined for purposes of this disclosure, the term "match" means to be substantially the same as or Note that refers to the result of a comparison of values ​​that are similar within a given tolerance. As an example implementation, if a ten percent (10%) tolerance for variance is predetermined, Ratio calculated in action 465 and biometric database 120 / 22 A "match" between the predetermined value stored in 0 / 320 is calculated in action 465. The ratio is then compared to the predetermined ratio stored in the biometric database 120 / 220 / 320. It can occur any time between 90% and 110% of the value.

[0047] In action 461, digital content 136 / 336 is transferred to system 100 / 20 In an implementation received by the computing platform, action 467 Executed by the hardware processor 104 / 204 of the form 102 / 202, and recognized The authentication module 318 is used to verify the authenticity of the software code 110 / 210a / 31 0 and may output an authenticity decision of 138 / 238 / 338. In action 461, the digital content 136 / 336 is transmitted to the user system 140 / In an implementation received by the user system 140 / 240, the action 467 240 and executed by the hardware processor 244, using the authentication module 318. and the authenticity analysis software code 210b / 310 executes the authenticity determination 1 It can output 38 / 238 / 338.

[0048] In some implementations, actions are taken in an automated process that may omit human involvement. To perform 461, 462, 463, 464, 465, 466, and 467, The hardware processor 104 / 204 executes the authenticity analysis software code 110 / 210a. / 310 or the hardware processor of the user system 140 / 240. The processor 244 can execute the authenticity analysis software code 210b / 310. Please note.

[0049] Referring now to FIG. 5 in combination with FIGS. 1, 2, and 3, as described above, FIG. 5 illustrates a system for authenticating digital content according to another implementation. 5 shows a flowchart 570 presenting an exemplary method for use. is a digital computer having an audio track containing monologue and / or dialogue. The process starts by receiving the content 136 / 336 (action 571). As noted above, in some implementations, the digital content 136 / 336 may include some Examples include movies and other audiovisual content, television series, web series, and or episodic content, which may include video logs, sports content, news content Content, advertising content, or audio including monologue and / or dialogue. The content may take the form of a video game content having an audio track.

[0050] As shown by FIG. 1, in one implementation, the digital content 136 is via network 130 and network communication link 132, content contributor 134 or may be received by the system 100 from a user system 140. In this paper, digital content 136 / 336 is a computing platform 10 2 / 202, and is executed by the hardware processor 104 / 204 of and the identification module 312 to analyze the authenticity of the software code 110 / 210a. However, referring to FIG. 2 in combination with FIG. In another implementation, the digital content 136 / 336 may be transmitted using a transceiver 243. and may be received by the user system 140 / 240 from the content contributor 134. In these implementations, the digital content 136 / 336 is transmitted to the user system 140. The content reception and identification module is executed by the hardware processor 244 of the / 240. The authenticity analysis software code 210b / 310 uses module 312 to It can be believed.

[0051] Flowchart 570 then continues with the process of converting the person depicted in digital content 136 / 336. Identifying an image of the object (action 572), where the depiction is by a person depicted in the image. In some implementations, digital The content 136 / 336 may be advertising material, such as a celebrity athlete, actor, or politician. However, more generally, Specifically, the digital content 136 / 336 is depicted and identified in action 572. The person to be identified has one or more corresponding language profiles, e.g., a language database 12 Language profiles 126a / 226a / 326a and / stored in 4 / 224 / 324 Or it can be any person with language profile 126b / 226b / 326b. Such a person may, for example, be a media engineer with a System 100 / 200 as a QC resource. whether an actor, reporter, newsreader, or other talent employed by the good.

[0052] Digital Content 136 / 336 contains more than one person as a participant, but In implementations where only one person is interested in authenticating that person's identity, The audio track included in the digital content 136 / 336 may be, for example, A diarization algorithm is used to separate the audio signals into different signals that separate each participant. Note that the audio for each person's speech can be separated into its own audio file. and the actions outlined by flowchart 570 correspond to persons of interest. It may be performed on the audio data and not on other people.

[0053] Furthermore, the same person may be represented in multiple languages ​​stored in the language database 124 / 224 / 324. Note that actors may have different profiles as they age. They may have different language profiles for different stages of their career. Additionally, actors may receive a commission for each role they take on or each film or other production in which they participate. It may have different language profiles for the audio performance. In some implementations, each of the different language mannerisms or attributes for a single person may be It may be advantageous or desirable to have multiple language profiles, each focused on That is, for example, the same actor may have different experiences that they have had, overcome, or performed over time. The first language profile was about the language impairments they had experienced, and the accents they had assumed over time. It may have a second biometric profile, etc.

[0054] In action 571, digital content 136 / 336 is transferred to system 100 / 20 In an implementation received by the . The identity of the person depicted in the The content receiving and identifying module is executed by the hardware processor 104 / 204. Authenticity analysis software code 110 / 210a / 310 using rule 312 However, in action 571, the digital content 136 / 3 In an implementation where 36 is received by the user system 140 / 240, the digital content The identification of the person depicted in the image contained in content 136 / 336 is performed by the user system 140 / 240 by the hardware processor 244, and the content reception and identification module 312, performed by the authenticity analysis software code 210b / 310. It can be done.

[0055] Flowchart 570 continues by providing a monologue and / or dialogue-based and, in action 572, identifying at least one language of the person depicted in the identified image. Detect word mannerisms (action 573). The language mannerism(s) may be a misreading of the person depicted in the image, to name a few. Speech affectation, speech intonation, regional accent, or In action 571, the digital content may include one or more of the following dialects: In implementations where 136 / 336 is received by the system 100 / 200, the action Examination of one or more language mannerisms of the person depicted in the image identified in 572 The output is the hardware processor 1 of the computing platform 102 / 202. 04 / 204 and uses a linguistic comparison module 316 to perform the authenticity analysis software. However, the action can be performed by the software code 110 / 210a / 310. In the application 571, the digital content 136 / 336 is transmitted to the user system 140 / 240. In an implementation where the image is received by the The detection of one or more language mannerisms of a person may be performed by the hand of the user system 140 / 240. Executed by the hardware processor 244 and using the linguistic comparison module 316, This can be performed by the authenticity analysis software code 210b / 310.

[0056] Flowchart 570 continues with action 572, where the identified image is depicted. The language profile of the person specified is 126a / 226a / 326a or 126b / 226b / 326b (action 574), where the language profile is Includes one or more predetermined linguistic mannerisms of the person depicted in the statue. Action 571 The digital content 136 / 336 is received by the system 100 / 200 at In some implementations, the language profile 126a / 226a / 326a or 126b / 226 One of the b / 326b is the hardware of the computing platform 102 / 202. Executed by the hardware processor 104 / 204 and using the linguistic comparison module 316 The authenticity analysis software code 110 / 210a / 310 is used to analyze the language database. It can be obtained from source 124 / 224 / 324.

[0057] However, in action 571, the digital content 136 / 336 is In an implementation received by the system 140 / 240, the language profile 126a / One of 226a / 326a or 126b / 226b / 326b is the user system 140 / 240 hardware processor 244, and a language comparison module 316 to analyze the language data by the authenticity analysis software code 210b / 310 It can be obtained from base 124 / 224 / 324. For example, in the latter implementation The user system 140 / 240 uses a transceiver 243 and a communication network 130. Utilizing the computing platform 102 / 202 of the system 100 / 200 Access the language database 124 / 224 / 324 stored on the Obtain one of the following rules: 126a / 226a / 326a or 126b / 226b / 326b You may do so.

[0058] Flowchart 570 continues with action 573, where the detected one or more Linguistic mannerisms and language profiles 126a / 226a / 326a or 126b / 226b / 326b with one or more predetermined linguistic mannerisms A comparison is performed (action 575), e.g., the person identified as being depicted in the image employed by a media entity that includes a System 100 / 200 as a QC resource If you are a featured actor, reporter, newsreader, or other talent, A language profile containing one or more language mannerisms of an individual may be, for example, One of files 126a / 226a / 326a or 126b / 226b / 326b It may be stored as part of the language database 124 / 224 / 324. 575 uses speech-to-text algorithms to translate speech and compare it with other people. This can be done by identifying frequently occurring words from a person. A metric that may be used is term frequency-inverse document frequency, as known in the art. The degree of correlation is (TF-IDF).

[0059] In action 571, digital content 136 / 336 is transferred to system 100 / 20 In an implementation where the received signal is one or more of the received signals detected in action 573, Linguistic mannerisms and language profiles 126a / 226a / 326a or 126b / 226b / 326b with one or more predetermined linguistic mannerisms Comparison is based on the hardware processor of the computing platform 102 / 202. 104 / 204 and uses a linguistic comparison module 316 to perform the authenticity analysis. However, the software code 110 / 210a / 310 may be executed by the access In the session 571, the digital content 136 / 336 is transmitted to the user system 140 / 24. In an implementation where the received signal is one or more of the received signals detected in action 573, Linguistic mannerisms and language profiles 126a / 226a / 326a or 126b / 226b / 326b with one or more predetermined linguistic mannerisms The comparison is performed by the hardware processor 244 of the user system 140 / 240. and using a linguistic comparison module 316 to analyze the authenticity of the software code 210b / 3 10. Action 575 may be performed by the linguistic comparison module 316: Authenticity analysis software code 110 / 210a / 310 or authenticity analysis software The language mannerisms provided as input to the authentication module 318 of code 210b / 310 Note that this results in a rhythm comparison 356.

[0060] In implementations where the person whose identity is being authenticated is an actor or other type of performer, The author uses certain language mannerisms while the person is "in character" to express their authentic self. It is advantageous to distinguish between the specific linguistic mannerisms that are exhibited when speaking as a person and the specific linguistic mannerisms that are exhibited when speaking as a person. For example, such a distinction can be made to avoid falsely representing oneself as one's true self. The actors in the program demonstrate the language mannerisms of characters or roles they have previously played. Such a distinction would also facilitate the identification of counterfeit digital content. Deepfake generator trains based on interviews with actors as their real selves Deepfakes are used to portray characters as if they are playing a role. This will facilitate the identification of fake digital content.

[0061] The exemplary method outlined by flowchart 570 begins in action 573 with The detected language mannerism or mannerisms and the language profile 126a / 226a / 326a or 126b / 226b / 326b Based on the comparison of language mannerisms with the language mannerisms of may end by determining whether the image is an authentic depiction of the person (action 57 6) For example, the comparison of linguistic mannerisms 356 may be performed within a given tolerance range, in accordance with the action 573 one or more linguistic mannerisms detected in the language profile 126a / 2 One or more of the following in one of 26a / 326a or 126b / 226b / 326b Authenticity test 138 / 23 when it reveals a correspondence between a number of given linguistic mannerisms 8 / 338 identifies the person depicted in the image as an authentic depiction of that person. In some implementations, action 576 may include: based on a comparison of the file with one or more predetermined language profiles, Digital content is considered authentic when a person matches a genuine depiction of that person. This may include determining that the result is positive.

[0062] In action 571, digital content 136 / 336 is transferred to system 100 / 20 In an implementation received by the computing platform, action 576 Executed by the hardware processor 104 / 204 of the form 102 / 202, and recognized The authentication module 318 is used to verify the authenticity of the software code 110 / 210a / 31 0 and may output an authenticity decision of 138 / 238 / 338. In action 571, the digital content 136 / 336 is transmitted to the user system 140 / In an implementation received by the user system 140 / 240, the action 576 240 and executed by the hardware processor 244, using the authentication module 318. and the authenticity analysis software code 210b / 310 executes the authenticity determination 1 It can output 38 / 238 / 338.

[0063] In some implementations, actions are taken in an automated process where human involvement may be omitted. To execute programs 571, 572, 573, 574, 575, and 576, The processor 104 / 204 includes the authenticity analysis software code 110 / 210a / 31 0, or the hardware processor 244 of the user system 140 / 240 It should be noted that the authenticity analysis software code 210b / 310 may be executed.

[0064] Referring now to FIG. 6 in combination with FIGS. 1, 2, and 3, as described above, FIG. 6 illustrates a system for authenticating digital content according to yet another implementation. 6 shows a flowchart 680 presenting an exemplary method for use by 680 is a digital audio file having an audio track containing monologue and / or dialogue. The process starts by receiving the mobile content 136 / 336 (action 681). As mentioned above, in some implementations, the digital content 136 / 336 may be Some examples include audio content without video, or AV content such as movies. , episodes which may include television series, web series and / or vlogs Content, sports content, news content, advertising content, or mono Video game content with audio tracks containing gameplay and / or dialogue The device may take the form of a pouch.

[0065] As shown by FIG. 1, in one implementation, the digital content 136 is via network 130 and network communication link 132, content contributor 134 or may be received by the system 100 from a user system 140. In this paper, digital content 136 / 336 is a computing platform 10 2 / 202, and is executed by the hardware processor 104 / 204 of and the identification module 312 to analyze the authenticity of the software code 110 / 210a. However, referring to FIG. 2 in combination with FIG. In another implementation, the digital content 136 / 336 may be transmitted using a transceiver 243. and may be received by the user system 140 / 240 from the content contributor 134. In these implementations, the digital content 136 / 336 is transmitted to the user system 140. The content reception and identification module is executed by the hardware processor 244 of the The authenticity analysis software code 210b / 310 uses module 312 to It can be believed.

[0066] The flowchart 680 continues by converting the digital content 136 / 336 into language data. Existing content with corresponding scripts stored in base 124 / 224 / 324 In some implementations, the digital content is identified as 136 / 336 is for example AV content in the form of previously produced movies, TV episodes, Sword, newscast, sportscast, interview, advertisement, or video game However, more generally, in action 682, an existing component may be The digital content 136 / 336 identified as content may include a corresponding script, e.g. For example, script 127a / 227a / 327a or 127b / 227b / 327b is the language Monologues and / or dialogues stored in database 124 / 224 / 324 The content may be any digital content, including music.

[0067] In action 681, digital content 136 / 336 is transferred to system 100 / 20 In the implementation received by 0, the language stored in the language database 124 / 224 / 324 Digital content 136 / as existing content with corresponding scripts The identification of 336 is based on the hardware program of the computing platform 102 / 202. The content receiving and identifying module 312 is executed by the processor 104 / 204. can be executed by the authenticity analysis software code 110 / 210a / 310 using However, in action 681, the digital content 136 / 336 is In an implementation received by the user system 140 / 240, the language database 124 / Digital content as existing content with corresponding scripts stored in 224 / 324 The identification of the data content 136 / 336 is based on the hardware of the user system 140 / 240. Executed by the processor 244 and using the content receiving and identification module 312 and can be executed by the authenticity analysis software code 210b / 310.

[0068] Flowchart 680 continues by showing the items included in digital content 136 / 336. A log and / or dialogue sample is extracted (action 683). Depending on the scale, Action 683 is included in Digital Content 136 / 336 The entire monologue and / or dialogue, or a portion of the monologue and / or dialogue This may involve sampling less than the entirety of a monologue. In use cases where less than the entire dialogue and / or the entire A single sample or multiple samples are extracted from the digital content 136 / 336. When multiple samples are extracted, the samples may be At random intervals within 136 / 336, or at time code positions or intervals, or The data may be extracted at predetermined positions or intervals, such as frame numbers or intervals.

[0069] In action 681, digital content 136 / 336 is transferred to system 100 / 20 In an implementation where the digital content 136 / 336 is received by Extraction of multiple monologue and / or dialogue samples may be performed using a computing platform. executed by the hardware processor 104 / 204 of the platform 102 / 202 , using the linguistic comparison module 316, the authenticity analysis software code 110 / 210 However, in action 681, the digital code can be executed by In an implementation where the content 136 / 336 is received by a user system 140 / 240, may include one or more monologues and / or dictionaries from the digital content 136 / 336. The sample of the algorithm is extracted from the hardware processor of the user system 140 / 240. 244, using a linguistic comparison module 316, It can be implemented by Accord 210b / 310.

[0070] Flowchart 680 continues with action 683, where the extracted monologue and and / or dialogue samples and scripts 127a / 227a / 327a or 12 Perform a comparison with the corresponding sample from one of the 7b / 227b / 327b (A For example, digital content 136 / 336 is used as a QC resource. Produced by a media entity using the system 100 / 200 or If the content is owned by a media entity, Included in each item of digital content 136 / 336 created or owned by All monologues and / or dialogue and / or closed captions (CC ) files are stored in the language database 124 / 224 / 324. Good too.

[0071] Action 684 uses a speech-to-text algorithm to translate the speech and convert the translation into One of scripts 127a / 227a / 327a or 127b / 227b / 327b Action 684 may be performed by comparing the two parts of the script. This involves aligning speech-to-text translations with the script to identify equivalents. Note that this may appear to be a

[0072] In action 681, digital content 136 / 336 is transferred to system 100 / 20 In the implementation received by the . and / or dialogue samples and scripts 127a / 227a / 327a or 12 Comparison with the corresponding sample in one of 7b / 227b / 327b is computationally by the hardware processor 104 / 204 of the operating platform 102 / 202 Executing and using the linguistic comparison module 316, the authenticity analysis software code 110 However, in action 681, The digital content 136 / 336 is received by the user system 140 / 240. In the implementation, the monologue and / or dialogue extracted in action 683 Sample and script 127a / 227a / 327a or 127b / 227b / 327 The comparison with the corresponding sample of one of b is performed by the hardware of the user system 140 / 240. The hardware processor 244 executes the linguistic comparison module 316 to compare the authenticity of the The latter may be implemented by the sex analysis software code 210b / 310. In these implementations, the user system 140 / 240 includes a transceiver 243 and a communication network. Network 130 is used to run the computing platform of System 100 / 200. Access the language database 124 / 224 / 324 stored on the system 102 / 202. , script 127a / 227a / 327a or 127b / 227b / 327b Action 684 may be performed by the linguistic comparison module 3. 16, authenticity analysis software code 110 / 210a / 310, or authenticity solution provided as input to authentication module 318 of analysis software code 210b / 310. Note that this results in a monologue and / or dialogue comparison 358.

[0073] The exemplary method outlined by flowchart 680 begins in action 683 with Extracted monologue and / or dialogue samples and scripts 127a / 22 with one of the corresponding samples: 7a / 327a or 127b / 227b / 327b , based on the monologue and / or dialogue comparison 358, the digital content 136 Determine whether the monologue and / or dialogue contained in / 336 is authentic. For example, a monologue and / or dialogue may be terminated by The group comparison 358 is performed to determine whether the extracted monologue in action 683 matches the extracted monologue within a predetermined tolerance. Samples of the scripts and / or dialogues, including scripts 127a / 227a / 327a or 1 reveal a match between the corresponding samples of one of 27b / 227b / 327b In this case, the authenticity determination 138 / 238 / 338 is based on the information contained in the digital content 136 / 336. Identify the monologue and / or dialogue included in the recording as authentic. In some implementations, action 685 may include: Sample scripts and scripts 127a / 227a / 327a or 127b / 227b / 3 27b. / 336 is authentic, and such corresponding sample is It may contain the contents of the CC file and / or dialogue and / or CC file.

[0074] In action 681, digital content 136 / 336 is transferred to system 100 / 20 In an implementation received by the computing platform, action 685 Executed by the hardware processor 104 / 204 of the form 102 / 202, and recognized The authentication module 318 is used to verify the authenticity of the software code 110 / 210a / 31 0 and may output an authenticity decision of 138 / 238 / 338. In action 681, the digital content 136 / 336 is transmitted to the user system 140 / In an implementation received by the user system 140 / 240, the action 685 240 and executed by the hardware processor 244, using the authentication module 318. and the authenticity analysis software code 210b / 310 executes the authenticity determination 1 It can output 38 / 238 / 338.

[0075] In some implementations, the activity is performed in an automated process that may omit human intervention. To execute operations 681, 682, 683, 684, and 685, a hardware processor is required. The processor 104 / 204 uses the authenticity analysis software code 110 / 210a / 310. The hardware processor 244 of the user system 140 / 240 executes the Note that the analysis software code 210b / 310 may be executed. 4, 5, and 6 may be used to recognize digital content. Note that these may be performed in combination to demonstrate the In an implementation, the method outlined by flowcharts 460 and 570 In other implementations, the flow The methods outlined by Charts 460 and 680 are part of the authenticity assessment. In other implementations, flowcharts 570 and 680 The methods illustrated in the diagram may be performed together. The methods generally illustrated by charts 460, 570, and 680 are These may be run together to determine the authenticity of the

[0076] Thus, the present application provides a digital content program that overcomes the difficulties and deficiencies in the prior art. From the above description, it can be seen that various techniques are applicable to the present invention. may be used to implement concepts without departing from the scope of those concepts. Furthermore, although the concepts have been described with specific reference to particular implementations, Those skilled in the art will appreciate that changes may be made in form and detail without departing from the scope of these concepts. As such, the described implementation is in all respects exemplary. The present application should be considered as illustrative and not restrictive. It is not limited to any particular implementation, and many variations may be made without departing from the scope of this disclosure. It should be understood that configurations, modifications, and substitutions are possible.

Claims

1. 1. A system for authenticating digital content, comprising: a computing platform including a hardware processor and a system memory; software code stored in the system memory; the hardware processor executes the software code; receiving digital content having an audio track including at least one of a monologue or a dialogue; identifying an image of a person depicted in the digital content, the depiction including participation in the at least one of the monologue or the dialogue by the person depicted in the image; detecting at least one language mannerism of the person depicted in the image based on the participation in the at least one of the monologue or the dialogue; obtaining a language profile of the person depicted in the image, the language profile including at least one predetermined language mannerism of the person depicted in the image; performing a comparison of the at least one detected language mannerism with the at least one predetermined language mannerism; determining whether the person depicted in the image is an authentic depiction of the person based on the comparison of the at least one detected language mannerism to the at least one predetermined language mannerism; A system that is configured to:

2. 2. The system of claim 1, wherein the hardware processor is further configured to execute the software code and determine that the digital content is authentic as a result of determining that the person depicted in the image is the authentic depiction of the person based on the comparison of the at least one detected language mannerism to the at least one predetermined language mannerism.

3. The system of claim 1 , wherein the at least one predetermined language mannerism comprises at least one of a speech impediment or a speaking style of the person depicted in the image.

4. The system of claim 1 , wherein the at least one predetermined language mannerism comprises at least one of a speech intonation, a regional accent, or a regional dialect of the person depicted in the image.

5. The system of claim 1 , wherein the received digital content comprises at least one of sports content, television program content, movie content, advertising content, or video game content.

6. The system of claim 1 , wherein the computing platform includes at least one web-based computer server.

7. The system of claim 1 , wherein the computing platform comprises a mobile communication device.

8. A method for authenticating digital content executed by a hardware processor of a computing platform, comprising: receiving digital content having an audio track including at least one of a monologue or a dialogue; identifying an image of a person depicted in the digital content, the depiction including participation in the at least one of the monologue or the dialogue by the person depicted in the image; detecting at least one language mannerism of the person depicted in the image based on the participation in the at least one of the monologue or the dialogue; obtaining a language profile of the person depicted in the image, the language profile including at least one predetermined language mannerism of the person depicted in the image; performing a comparison of the at least one detected language mannerism with the at least one predetermined language mannerism; determining whether the person depicted in the image is an authentic depiction of the person based on the comparison of the at least one detected language mannerism with the at least one predetermined language mannerism; A method comprising:

9. The method of claim 8, further comprising determining that the digital content is authentic as a result of determining that the person depicted in the image is the authentic depiction of the person based on the comparison of the at least one detected linguistic mannerism with the at least one predetermined linguistic mannerism.

10. The method of claim 8, wherein the at least one predetermined language mannerism includes at least one of a speech impediment or speech pattern of the person depicted in the image.

11. The method of claim 8, wherein the at least one predetermined linguistic mannerism includes at least one of a speech intonation, a regional accent, or a regional dialect of the person depicted in the image.

12. The method of claim 8, wherein the received digital content includes at least one of sports content, television program content, movie content, advertising content, or video game content.

13. The method of claim 8, wherein the computing platform includes at least one web-based computer server.

14. The method of claim 8, wherein the computing platform includes a mobile communications device.

Images