system

Abstract

Provide a system. A method for periodically acquiring a screen image; A means for converting the acquired screen image into text data using image processing technology; A means for acquiring audio data from the terminal; A means for converting the acquired voice data into text data using voice recognition technology; A means for analyzing the converted text data using natural language processing technology to detect specific keywords and phrases; means for generating and displaying a warning message when a particular keyword or phrase is detected; A means to stop viewing certain content and switch to safe content; A system including:

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, the impact of conspiracy theory information spreading online on society has become a major concern. Elderly people, in particular, are exposed to conspiracy theories through video-sharing services and social networking sites such as YouTube (registered trademark) and Twitter, and are strongly influenced by them, resulting in an increasing number of conflicts and discord within families. Effective measures are needed to prevent addiction to conspiracy theories and the spread of false information, but currently, such measures are not adequately in place. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that constantly monitors screen images and audio, detects viewing of conspiracy theory content, and issues a warning. Specifically, the terminal is equipped with a means for acquiring screen captures at regular intervals and transmitting them to a server. It also has a means for acquiring audio data from the terminal in real time and transmitting it to the server. The server converts the acquired screen captures into text data using image processing technology and audio data into text data using speech recognition technology. It also has a means for analyzing the text data using natural language processing technology, and if conspiracy theory-related keywords are detected, it generates and displays a warning message, stops displaying the specific content, and switches to safe content. Such a system can prevent elderly people from becoming addicted to conspiracy theory content and maintain peace within the home.

[0006] "Screen image" refers to the image of the screen content that a user is viewing or operating on a terminal.

[0007] "Image processing technology" refers to technology that extracts text and other useful information from captured images of the screen.

[0008] "Text data" refers to textual information extracted from a screen or audio.

[0009] "Audio data" refers to audio information being played back by a user through a terminal.

[0010] "Speech recognition technology" refers to the technology of extracting text information from captured speech.

[0011] "Natural language processing technology" refers to the technology of analyzing text data and detecting specific keywords and phrases.

[0012] "Keywords" refer to specific words or phrases that suggest conspiracy theories.

[0013] A "phrase" is a short sentence or expression containing a series of words that suggest a conspiracy theory.

[0014] A "warning message" refers to a warning message that is displayed to a user when a conspiracy theory is detected.

[0015] "Content" refers to information such as video, text, and audio that a user is viewing or operating.

[0016] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[0017] "Server" refers to the central computer system that receives and processes screen and audio data.

[0018] "Capture" refers to the act of saving a screen image or audio exactly as it is. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[0041] Basic system configuration

[0042] Taking and processing screen captures

[0043] The device periodically captures a screen capture, which contains the content displayed on the user's screen, especially when the user is using a video sharing service or social networking site. The captured screen capture is then sent to the server and processed in the next step.

[0044] Acquiring and processing audio capture

[0045] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[0046] Convert screen captures to text using OCR

[0047] The server converts the received screen capture image into text data using image processing technology (OCR), such as Tesseract OCR, which allows the server to obtain the text information on the screen.

[0048] Converting voice data into text using voice recognition

[0049] The server converts the received voice data into text data using speech recognition technology. For example, by using Google® Cloud Speech-to-Text API, it is possible to extract accurate text information from the voice.

[0050] Text data integration and analysis

[0051] The server integrates the text data obtained through OCR and speech recognition. It then analyzes this text data using natural language processing (NLP) techniques to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[0052] Generate and display warning messages

[0053] If certain keywords or phrases are detected, the server will flag a warning and generate a warning message that will be sent to the device and displayed to the user stating, "This content may be a conspiracy theory."

[0054] Stop showing content and switch to safe content

[0055] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, minimizing the impact of conspiracy theories on users.

[0056] Specific examples

[0057] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0058] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[0059] If a certain number of conspiracy theory-related keywords (e.g., "conspiracy," "secret organization," "manipulation") are included, the server will raise a warning flag and generate a warning message, which will be sent to the user's device and displayed on the user's screen, saying, "This content may be a conspiracy theory."

[0060] Furthermore, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news. In this way, the system can provide a safe information environment for seniors without influencing them with conspiracy theory content.

[0061] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet.

[0062] The processing flow will be explained below.

[0063] Step 1: Take a screen capture

[0064] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[0065] The device will capture the current screen contents and save it as an image file.

[0066] The device sends the captured image to the server.

[0067] Step 2: Getting an Audio Capture

[0068] Set up a task for the device to capture audio in real time.

[0069] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[0070] The terminal transmits the buffered audio data to the server.

[0071] Step 3: OCR processing

[0072] The server analyzes the received screen capture image.

[0073] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[0074] The server temporarily stores the extracted text data.

[0075] Step 4: Speech Recognition Processing

[0076] The server analyzes the received audio data.

[0077] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[0078] The server temporarily stores the extracted text data.

[0079] Step 5: Integrating text data

[0080] The server integrates the text data obtained through OCR processing and speech recognition processing.

[0081] Step 6: Natural Language Processing Analysis

[0082] The server analyzes the integrated text data using natural language processing technology.

[0083] The server detects specific conspiracy theory-related keywords and phrases.

[0084] Step 7: Generate a warning message

[0085] The server will flag certain keywords or phrases as warnings if they are detected.

[0086] If the server detects a warning flag, it generates a warning message.

[0087] Step 8: Sending a warning message

[0088] Sends server-generated warning messages to the terminal.

[0089] Step 9: Displaying warning messages

[0090] The terminal displays a warning message on the user's screen.

[0091] Step 10: Pause and Switch Content

[0092] The device will stop playing the current content if necessary after displaying the warning message.

[0093] Your device will automatically switch to safe content.

[0094] Example 1

[0095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0096] Internet content contains misinformation and conspiracy theories, which can have a negative impact on users, especially vulnerable groups such as the elderly. Conventional methods lack the means to automatically detect this harmful content, warn users, and take appropriate action.

[0097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0098] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keyword or phrase is detected, and means for stopping the display of the specific content and switching to safe content, thereby making it possible to provide a safe and healthy digital environment for users without being influenced by harmful content.

[0099] "Screen" refers to the entire visual information displayed on a user's device.

[0100] "Means for periodic acquisition" refers to a function for automatically collecting screen and audio data at regular intervals.

[0101] "Image processing technology" refers to the general technology for analyzing acquired image data and converting it into text or other information.

[0102] "Means for converting into text data" refers to a function for converting visual information or audio information into text information using image processing technology or voice recognition technology.

[0103] "Audio data" refers to the audio information of the content that the user is viewing.

[0104] "Speech recognition technology" refers to technology for analyzing voice data and extracting text information from the voice.

[0105] "Natural language processing technology" refers to the general technology for analyzing text data and detecting specific keywords and phrases.

[0106] "Specific keywords and phrases" refer to words or short phrases designed to identify conspiracy theories and other harmful content.

[0107] "Means for generating and displaying a warning message" refers to a function for issuing a warning to a user when a specific keyword or phrase is detected.

[0108] "Means to stop displaying content and switch to safe content" refers to a function that stops playback of detected harmful content and automatically switches to another content that is determined to be safe.

[0109] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[0110] System basic configuration and operation

[0111] Taking and processing screen captures

[0112] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. This capture contains everything displayed on the user's screen and is implemented using the Python Pillow library, among other things. The captured screen capture is sent to the server using an HTTP POST request.

[0113] Acquiring and processing audio capture

[0114] The device also captures the audio data of the video in real time, which is divided into buffers of a certain size, captured using the Python pyaudio library, and periodically sent to the server.

[0115] Processing on the server

[0116] When the server receives the screen capture image, it converts the image into text using Tesseract OCR. It also uses the Google Cloud Speech-to-Text API to recognize the audio data and convert it into text. This allows the image and audio information to be integrated into text data.

[0117] Text data integration and analysis

[0118] The server combines the text data obtained through OCR and speech recognition and performs natural language processing (NLP) using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[0119] Generate and display warning messages

[0120] If the server detects certain keywords or phrases, it generates a warning message that is sent to the device and displayed to the user, such as "This content may be a conspiracy theory."

[0121] Stop showing content and switch to safe content

[0122] After the warning message is displayed, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news, using the YouTube API, for example.

[0123] Specific examples

[0124] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every five seconds and sends it to the server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server converts the received screen captures into text data using Tesseract OCR and converts the audio data into text information using the Google Cloud Speech-to-Text API. These text data are then combined and analyzed using natural language processing technology. If conspiracy theory-related keywords such as "conspiracy" or "secret organization" are detected, the server generates a warning message and sends it to the user's device. The user's device then stops playing the current content and automatically switches to safe content.

[0125] Prompt Sentence Examples

[0126] A user is watching a video titled "Conspiracy Theories" on YouTube. The system takes a screen capture and audio of this video and detects keywords related to conspiracy theories. Explain this process using Tesseract OCR and the Google Cloud Speech-to-Text API.

[0127] In this way, the present invention can provide a safe and healthy digital environment where users are not affected by harmful content.

[0128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0129] Step 1:

[0130] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. The input is the user's currently displayed screen image, and the output is the image data of that screen image. Specifically, the device sets a timer, takes a screenshot using the Python Pillow library, and saves it to a local temporary file.

[0131] Step 2:

[0132] The device captures the audio data of the video being played in real time. The input is the audio of the content the user is watching, and the output is a fixed-size buffer of audio data. Specifically, the device uses the Python pyaudio library to acquire audio from the system's audio output, split it into fixed-size buffers, and saves it.

[0133] Step 3:

[0134] The device sends screen captures taken every 5 seconds and real-time buffered audio data to the server using an HTTP POST request. The input is the screen capture image and audio data buffer, and the output is the data sent to the server.

[0135] Step 4:

[0136] The server receives the received screen capture image data and converts it into text data using Tesseract OCR. The input is the screen capture image and the output is text data. Specifically, the server saves the received image data to a temporary file and calls Tesseract OCR to extract text from the image.

[0137] Step 5:

[0138] The server converts the received audio data into text data using the Google Cloud Speech-to-Text API. The input is a buffer of audio data, and the output is text data. Specifically, the server saves the audio data in a temporary file and calls the Google Cloud Speech-to-Text API to extract text information from the audio.

[0139] Step 6:

[0140] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. The input is the OCR text data and speech recognition text data, and the output is the analysis results. Specifically, the server analyzes the integrated text data using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[0141] Step 7:

[0142] If the server detects a specific keyword or phrase, it generates a warning message and sends it to the terminal. The input is the analysis result, and the output is the generated warning message. Specifically, the server sets a warning flag based on the keyword detection result, generates a warning message from a template, and sends it to the terminal.

[0143] Step 8:

[0144] The device displays the received warning message, stops the display of the content being played, and switches to safe content. The input is the warning message, and the output is the content that was stopped and the switched-to safe content. Specifically, the device sends an API request to stop the content being played, and then sends a new playback request specifying the URL of the safe content.

[0145] (Application example 1)

[0146] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] In recent years, while a great deal of information is easily accessible through the internet, conspiracy theories and inaccurate information are also easily spread. Such information can have a particularly negative impact on the elderly and those with low internet literacy. This increases the risk that users will be unintentionally exposed to conspiracy theories. Therefore, it is necessary to develop a system that can detect conspiracy theory content in real time and issue warnings to users.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0149] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keywords or phrases are detected, means for stopping the display of the specific content and switching to safe content, and means for warning the user when conspiracy theory-related keywords are detected, stopping related content as necessary, and automatically switching to safe content. This reduces the risk of users being exposed to conspiracy theory content and makes it possible to provide a safe and healthy digital environment.

[0150] "Screen" refers to the content of the display on which the video or image being viewed by the user on the device is displayed.

[0151] "Periodic acquisition" means collecting specific information at regular time intervals.

[0152] "Image processing technology" is a general term for technology that analyzes and edits digital images, and specifically includes OCR (Optical Character Recognition).

[0153] "Text data" refers to data that represents character information in a digital format.

[0154] "Terminal" is a general term for electronic devices used by users, including smartphones and personal computers.

[0155] "Audio data" refers to data that records audio in digital format.

[0156] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[0157] "Natural language processing technology" is a general term for technology that uses computers to analyze, understand, and generate human language.

[0158] "Analysis" is the process of examining data in detail and extracting specific patterns and important information.

[0159] "Keywords" are important words that are set to find specific information.

[0160] A "phrase" is a combination of words that has a particular meaning.

[0161] A "warning message" is a notification displayed to alert the user.

[0162] "Stop display" means stopping the playback of the content currently being viewed.

[0163] "Safe content" is content that comes from reliable sources and does not contain conspiracy theories or harmful information.

[0164] "User" means a person who uses a system or device to view content.

[0165] "Switching automatically" means that the system autonomously transitions to the next operation without human intervention.

[0166] An embodiment of the present invention provides a system that automatically detects conspiracy theory content and takes appropriate warnings and countermeasures when a user views or interacts with content on the Internet.

[0167] 1. Hardware and Software Used

[0168] Hardware: This system uses the user's device (smartphone, PC, tablet, etc.) and a server.

[0169] Software: Use Tesseract OCR, Google Cloud Speech-to-Text API, and natural language processing libraries (e.g., NLTK and spaCy).

[0170] 2. Program Processing Overview

[0171] Taking and sending screen captures

[0172] The user's device takes a screen capture every five seconds and sends this image data to the server, which collects images of the content the user is viewing.

[0173] Acquiring and sending audio data

[0174] Similarly, the device captures audio data in real time, divides it into a certain buffer size, and transmits it to the server, thereby collecting audio information about the content being viewed.

[0175] Converting image data into text using OCR

[0176] The server converts the received screen capture into text data using Tesseract OCR, which extracts the text information on the screen as text.

[0177] Converting audio data to text

[0178] The server uses the Google Cloud Speech-to-Text API to convert the transmitted voice data into text data, extracting accurate text information from the voice.

[0179] Text data integration and analysis

[0180] The server integrates the text data extracted by OCR and speech recognition and uses natural language processing techniques (e.g., NLTK, spaCy) to detect conspiracy theory-related keywords and phrases. During this process, it analyzes whether the data contains words or phrases related to conspiracy theories.

[0181] Generate and display warning messages

[0182] If certain keywords or phrases are detected, the server generates a warning message and sends it to the user's device, which displays the message, "This content may be a conspiracy theory."

[0183] Stop showing content and switch to safe content

[0184] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, protecting users from conspiracy theory content and providing safe information.

[0185] Specific examples

[0186] For example, if an elderly person is watching a video sharing service at home, a screen capture is taken every five seconds and the image data is sent to a server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server then analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. The audio data is then converted into text information using speech recognition technology. This text data is then integrated, and conspiracy theory-related keywords and phrases are detected using natural language processing technology. For example, if the keyword "secret organization" is detected, the server generates a warning message and sends it to the user's device. A warning message appears on the user's screen stating, "This content may be a conspiracy theory." Furthermore, if necessary, the device will stop playing the current content and automatically switch to safe content.

[0187] Example prompt sentence:

[0188] "This video contains the words 'secret organization.' This content may be a conspiracy theory."

[0189] This system will enable users to enjoy a healthier digital environment, free from the influence of conspiracy theories.

[0190] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0191] Step 1:

[0192] The device takes a screen capture every 5 seconds and saves it as image data. The input of the screen capture is the screen of the user's device, and the output is image data (e.g., a PNG file). Specifically, the device's screen capture function is used to capture a still image of the entire screen.

[0193] Step 2:

[0194] The terminal transmits the acquired screen capture to the server. The input is the image data of the screen capture, and the output is the image data transmitted to the server. Specifically, the terminal uploads the screen capture to the server using network communication.

[0195] Step 3:

[0196] The device buffers audio data in real time and transmits it to the server at regular intervals. The input is audio data captured by the device's microphone, and the output is audio data transmitted to the server. Specifically, the system captures audio from the device's microphone, stores it in a buffer, and then uploads it to the server.

[0197] Step 4:

[0198] The server converts the received screen capture into text data using image processing technology (Tesseract OCR). The input is the image data of the screen capture, and the output is the text data extracted from the image. Specifically, it starts Tesseract OCR, analyzes the screen capture, and generates text data.

[0199] Step 5:

[0200] The server converts the received voice data into text data using speech recognition technology (Google Cloud Speech-to-Text API). The input is voice data, and the output is text data extracted from the voice. Specifically, it calls the Google Cloud Speech-to-Text API to convert the voice data into text.

[0201] Step 6:

[0202] The server integrates the text data generated by OCR and speech recognition and analyzes it using natural language processing technology (e.g., NLTK or spaCy). The input is each piece of text data, and the output is the analysis result, which is the detection information for specific keywords and phrases. Specifically, the integrated text data is input into an NLP library to detect conspiracy theory-related keywords and phrases.

[0203] Step 7:

[0204] The server generates a warning message when a specific keyword or phrase is detected and sends it to the user's device. The input is the analysis result (detection information for a specific keyword or phrase), and the output is the generation and transmission of a warning message. Specifically, the server generates a warning message and notifies the user's device via the network.

[0205] Step 8:

[0206] The user device receives the warning message and displays a message on the screen saying, "This content may be a conspiracy theory." At the same time, it stops displaying the current content and automatically switches to safe content. The input is the warning message from the server, and the output is the display of the warning message and the switching of content. Specifically, it displays a pop-up warning message, stops the content being viewed, and starts playing another safe content.

[0207] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0208] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content when the user is viewing or interacting with content on the Internet, recognizes the user's emotions, and takes appropriate measures.

[0209] Basic system configuration

[0210] Taking and processing screen captures

[0211] The terminal periodically takes a screen capture, which contains the content displayed on the user's screen, and sends the captured screen capture to the server for further processing.

[0212] Acquiring and processing audio capture

[0213] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[0214] Convert screen captures to text using OCR

[0215] The server converts the received screen capture image into text data using image processing technology (OCR), allowing the character information on the screen to be obtained.

[0216] Converting voice data into text using voice recognition

[0217] The server converts the received voice data into text data using voice recognition technology, allowing accurate extraction of text information from the voice.

[0218] Text data integration and analysis

[0219] The server integrates the text data obtained through OCR and speech recognition, then analyzes the text data using natural language processing (NLP) to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[0220] Emotion Recognition in Action

[0221] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which will recognize the user's emotions by analyzing their facial expressions and tone of voice, thereby understanding their emotional state.

[0222] Generate and display warning messages

[0223] Based on the results of keyword detection and emotion recognition, the server generates a warning message, which is sent to the device and displayed to the user, stating, "This content may be a conspiracy theory."

[0224] Stop showing content and switch to safe content

[0225] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content, such as educational videos or news, if necessary.

[0226] Specific examples

[0227] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0228] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[0229] For example, if conspiracy-theory related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[0230] Based on the emotion recognition results, the server raises a warning flag and generates a warning message. This message is sent to the device and displayed on the user's screen, stating, "This content may be a conspiracy theory." At the same time, playback of the current content is stopped and automatically switched to safe content. In this way, the system can provide a safe information environment for seniors without exposing them to conspiracy theory content.

[0231] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet. Furthermore, by adding emotion recognition, appropriate measures can be taken depending on the user's psychological state, ensuring further safety.

[0232] The processing flow will be explained below.

[0233] Step 1: Take a screen capture

[0234] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[0235] The device will capture the current screen contents and save it as an image file.

[0236] The device sends the captured image to the server.

[0237] Step 2: Getting an Audio Capture

[0238] Set up a task for the device to capture audio in real time.

[0239] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[0240] The terminal transmits the buffered audio data to the server.

[0241] Step 3: Convert screen capture to text using OCR

[0242] The server analyzes the received screen capture image.

[0243] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[0244] The server temporarily stores the extracted text data.

[0245] Step 4: Converting voice data into text using voice recognition

[0246] The server analyzes the received audio data.

[0247] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[0248] The server temporarily stores the extracted text data.

[0249] Step 5: Integrating text data

[0250] The server integrates the text data obtained through OCR processing and speech recognition processing.

[0251] Step 6: Natural Language Processing Analysis

[0252] The server analyzes the integrated text data using natural language processing technology.

[0253] The server detects specific conspiracy theory-related keywords and phrases.

[0254] Step 7: Activate the Emotion Engine

[0255] The server activates the emotion engine when certain keywords or phrases are detected.

[0256] The server analyzes the user's facial expressions and tone of voice to recognize their emotions.

[0257] Step 8: Generate a warning message

[0258] If the server detects that the user's emotions indicate anxiety or fear based on the emotion recognition results, it sets a warning flag.

[0259] If the server detects a warning flag, it generates a warning message.

[0260] Step 9: Sending a warning message

[0261] Sends server-generated warning messages to the terminal.

[0262] Step 10: Displaying warning messages

[0263] The terminal displays a warning message on the user's screen.

[0264] Step 11: Pause and Switch Content

[0265] The device will stop playing the current content after displaying the warning message.

[0266] Your device will automatically switch to safe content.

[0267] Example 2

[0268] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0269] As the amount of information on the Internet explodes, the risk of conspiracy theories and false information becoming increasingly influential is increasing. To address this issue, it is important to not only automatically analyze the content users view and detect problematic information, but also to monitor their emotional state. However, current safety measures lack systems that integrate content analysis and emotion recognition, making it difficult to quickly implement appropriate countermeasures. Furthermore, there are limited means to display appropriate warnings to users and smoothly switch them to safe content.

[0270] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0271] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of the specific content and switching to safe content, and emotion recognition means for analyzing the user's emotions. This makes it possible to detect content containing conspiracy theories or false information in real time and quickly issue a warning to the user, as well as take appropriate measures taking the user's emotional state into consideration.

[0272] The "screen capture means" is a means having a function of periodically capturing the screen of the user's terminal.

[0273] "Image processing technology" is a technology for analyzing and converting digital images to obtain the necessary information.

[0274] The "means for converting into text data" refers to a means having a function for converting information extracted from an image or sound into a character format.

[0275] The "means for acquiring voice data from the terminal" refers to a means having a function for recording the user's voice and collecting that data.

[0276] "Speech recognition technology" is a technology that analyzes acquired voice data and converts it into text data.

[0277] "Natural language processing technology" is a technology for analyzing text data and deciphering its meaning and structure.

[0278] The "means for detecting specific keywords or phrases" refers to a means having the function of identifying important words or phrases from the analyzed text data.

[0279] The "means for generating and displaying a warning message" refers to a means having a function for generating a message for notifying a user of a warning based on the detected content and displaying the message.

[0280] The "means for stopping the display of specific content and switching to safe content" refers to a means having a function for stopping the playback of problematic content and displaying safe content instead.

[0281] The "emotion recognition means" is a means having a function of analyzing the user's facial expression and tone of voice and identifying the user's emotional state.

[0282] The term "system" refers to the entire information processing device that operates by integrating these means and technologies.

[0283] This invention consists of a system based on software and a server implemented on a user's device. When a user views or interacts with content on the Internet, it can automatically detect conspiracy theory content, recognize the user's emotions, and take appropriate measures. This system is implemented using the following hardware and software:

[0284] Taking and processing screen captures

[0285] The device periodically (for example, every 5 seconds) takes a screen capture. The device takes a screen capture using a function called "GetScreenshot()" and sends the data to the server via an HTTP POST request.

[0286] Acquiring and processing audio capture

[0287] The device captures audio data in real time, divides it into a certain buffer size (for example, every second), and sends it to the server. The device collects audio data using a function called "CaptureAudio()" and sends this data to the server via an HTTP POST request.

[0288] Convert screen captures to text using OCR

[0289] The server converts the received screen capture image into text data using OCR technology called Tesseract. The server converts image data into text data using the function "TesseractOCR.Process(image)".

[0290] Converting voice data into text using voice recognition

[0291] The server converts the received voice data into text data using the Google Cloud Speech-to-Text API. The server converts the voice data into text data using the function "GoogleSpeechToTextAPI.convert(audio)".

[0292] Text data integration and analysis

[0293] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) techniques. This analysis is performed using libraries such as NLTK or SpaCy. The server uses the function "NLTK.Process(text)" to analyze the text data and detect conspiracy theory-related keywords.

[0294] Emotion Recognition in Action

[0295] If a specific keyword or phrase is detected, the server activates the emotion engine using OpenCV and the Microsoft® Azure® Emotion API. The server recognizes emotions using the functions "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)".

[0296] Generate and display warning messages

[0297] The server generates a warning message and sends it to the terminal, which then displays it to the user using the function "displayWarning(message)".

[0298] Stop showing content and switch to safe content

[0299] After the warning message is displayed, the device stops playing the current content using the function "StopCurrentContent()" and plays safe content using the function "PlaySafeContent()".

[0300] Specific examples

[0301] For example, if an elderly person is watching a video on the Internet at home, the device will take a screen capture every five seconds and send the data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0302] The server analyzes the received screen captures using Tesseract OCR and converts subtitles and on-screen comments in the video into text data. The audio data is converted into text information using the Google Cloud Speech-to-Text API. The text data is then merged and analyzed using NLTK or SpaCy.

[0303] For example, if conspiracy-related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an OpenCV-based emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[0304] Based on the emotion recognition results, the server will raise a warning flag and generate a warning message, which will be sent to the device and displayed on the user's screen, stating "This content may be a conspiracy theory." At the same time, the current content will stop playing and automatically switch to safe content.

[0305] Example prompts for generative AI models

[0306] "Please explain the program's procedures for identifying content that contains conspiracy theories and issuing warnings to users."

[0307] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0308] Step 1:

[0309] The device takes a screen capture at regular intervals (for example, every 5 seconds). The content displayed on the device's display is taken as input, and its image data is generated as output. Specifically, the "GetScreenshot()" function is used to take a screen capture, and the data is sent to the server via an HTTP POST request.

[0310] Step 2:

[0311] The device captures audio data in real time. As input, it receives audio data acquired through the device's microphone, divides the audio data into a certain buffer size (for example, every second), and sends the data to the server as output. Specifically, it uses the "CaptureAudio()" function to collect audio data and sends it to the server via an HTTP POST request.

[0312] Step 3:

[0313] The server converts the received screen capture image into text data using OCR technology. It receives the screen capture image as input, processes the image, and obtains text data as output. Specifically, it uses the "TesseractOCR.Process(image)" function to convert image data into text data.

[0314] Step 4:

[0315] The server converts the received voice data into text data using speech recognition technology. It receives voice data as input, performs speech recognition, and obtains text data as output. Specifically, it uses the "GoogleSpeechToTextAPI.convert(audio)" function to convert voice data into text data.

[0316] Step 5:

[0317] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. It integrates the text data as input, performs NLP analysis on it, and obtains data containing specific keywords and phrases as output. Specifically, it uses the "NLTK.Process(text)" function to analyze the text data and detect conspiracy theory-related keywords.

[0318] Step 6:

[0319] When a specific keyword or phrase is detected, the server analyzes the user's emotion using emotion recognition. It receives facial expressions and voice tone as input, analyzes the emotions, and obtains the user's emotional state as output. Specifically, it uses the "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)" functions to recognize emotions.

[0320] Step 7:

[0321] The server generates a warning message based on the emotion recognition results and sends it to the device. It receives the emotion recognition and keyword detection results as input, generates a warning message, and sends the warning message to the device as output. Specifically, it creates a warning message using the "GenerateWarningMessage(keywords, emotions)" function and sends it to the device via an HTTP POST request.

[0322] Step 8:

[0323] The device displays the received warning message to the user, stops playing the current content if necessary, and switches to safe content. It receives the warning message and current content information as input, and displays the warning message and starts playing safe content as output. Specifically, it displays the warning message using the "displayWarning(message)" function, stops the current content using the "StopCurrentContent()" function, and plays safe content using the "PlaySafeContent()" function.

[0324] (Application example 2)

[0325] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0326] Content provided on the Internet may contain conspiracy theories and misinformation, which poses a risk of causing anxiety and inappropriate influence to users, especially elderly people. There is a need for a system that can automatically detect such conspiracy theory content and ensure that users can view the content in a healthy and safe information environment. In addition, there is a need to develop a system that can provide greater safety and security by understanding the user's psychological state and responding appropriately.

[0327] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0328] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of specific content and switching to safe content, and means for analyzing content viewed by a user in real time, detecting conspiracy theory content, recognizing emotions, and taking appropriate measures based on the emotions. This enables automatic detection of conspiracy theory content and appropriate measures based on the user's emotional state.

[0329] "Screen" refers to the entire content displayed on a digital device's display.

[0330] "Means for periodic capture" refers to a device or process that has the function of capturing screen captures at regular time intervals.

[0331] "Image processing technology" refers to technology for extracting and analyzing specific information based on acquired image data.

[0332] "Means for converting into text data" refers to the function of extracting text information from image or audio data and converting it into text format using image processing technology, etc.

[0333] "Audio data" refers to sound information recorded or captured in real time by a digital device.

[0334] "Speech recognition technology" refers to the technology that analyzes voice data, extracts linguistic information from it, and converts it into text data.

[0335] "Natural language processing technology" refers to computational techniques for analyzing, understanding, and generating human language data.

[0336] "Keyword and phrase detection method" refers to a technique or process for identifying specific words or phrases in the analyzed text.

[0337] "Means for generating and displaying a warning message" refers to a function that generates a message to alert the user when a specific condition is met and displays the message on the user's device.

[0338] "Means to stop displaying content and switch to safe content" refers to a function that stops displaying inappropriate content and automatically switches to another safe content when inappropriate content is detected.

[0339] "Conspiracy theory content" refers to content that contains unproven theories or unfounded information.

[0340] "Emotion recognition" refers to technology that analyzes a user's facial expressions and tone of voice to identify the emotions they are feeling.

[0341] "Appropriate response based on the user's emotional state" refers to using emotion recognition technology to determine the user's psychological state and then taking appropriate action such as issuing a warning or changing the content.

[0342] "Real-time analysis" refers to processing acquired data immediately and outputting results quickly.

[0343] The following describes in detail the mode for carrying out the present invention. This system is mainly composed of a server and a terminal, and its purpose is to automatically detect conspiracy theories in the content viewed by users, analyze the users' emotions, and take appropriate measures.

[0344] First, the device has a function to periodically capture screens. This function allows the device to capture screens at regular intervals (for example, every 5 seconds) and send them to the server. The device also captures audio data in real time and periodically sends it to the server.

[0345] The server converts the received screen capture into text data using image processing technology (OCR: Optical Character Recognition). Similarly, it converts the received voice data into text data using voice recognition technology. This allows the server to obtain the character information on the screen and the voice information as text data.

[0346] The server then analyzes the converted text data using natural language processing (NLP) technology to detect specific keywords and phrases, such as "conspiracy," "secret organization," and "manipulation."

[0347] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotions, allowing the server to understand their emotional state.

[0348] If the user shows signs of anxiety or fear, the server will instantly generate a warning message and send it to the device, which will then display the message on the user's screen, stop the current content, and automatically switch to safe content, such as educational videos or news.

[0349] This system allows users to enjoy a healthy and safe information environment without being influenced by conspiracy theory content. Furthermore, emotion recognition enables more appropriate responses, ensuring the user's psychological safety.

[0350] As a concrete example, consider the case where a user is watching an internet video using smart glasses. The system analyzes the content the user is watching in real time to detect inappropriate content (e.g., conspiracy theories). Screen captures are taken every five seconds, and audio data is also captured in real time and sent to a server. If the analysis detects the keyword "manipulation" and the user shows an anxious expression, a warning appears on the smart glasses' display stating, "This content may be a conspiracy theory. It may be disturbing." The system then automatically switches to a safe news video.

[0351] Prompt Sentence Examples

[0352] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[0353] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[0354] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[0355] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[0356] 4. Recognize the user's emotional state by analyzing their facial expressions.

[0357] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[0358] Write a Python program to perform these steps.

[0359] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0360] Step 1:

[0361] The device takes a screen capture at regular intervals. The input is a real-time image of the screen, which is captured as image data. The output is the captured image data. Specifically, the device's built-in camera is used to save the contents of the screen as image data. This process is performed every 5 seconds, for example, and the captured image is used in the next step.

[0362] Step 2:

[0363] The device captures audio data in real time, divides it into a certain buffer size, and sends it to the server. The input is the audio signal obtained from the microphone. The output is the audio signal stored in the buffer as digital data. Specifically, the device's built-in microphone is used to record ambient audio, and the recorded audio data is buffered.

[0364] Step 3:

[0365] The server converts the screen capture received from the device into text data using image processing technology (OCR: Optical Character Recognition). The input is the image data of the screen capture, and the output is text data. Specifically, the OCR engine is used to extract characters from the image and obtain them as a string of characters.

[0366] Step 4:

[0367] The server converts the voice data received from the terminal into text data using voice recognition technology. The input is voice data, and the output is text data extracted from that voice. Specifically, the server uses a voice recognition engine to analyze the voice data and obtain its contents as a string of characters.

[0368] Step 5:

[0369] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) technology. The input is the integrated text data, and the output is the detection of conspiracy theory-related keywords and phrases. Specifically, the server uses a natural language processing engine to detect specific keywords (e.g., "conspiracy," "secret organization," and "manipulation") within the text data.

[0370] Step 6:

[0371] The server activates an emotion engine based on the keyword detection results. The input is data including the user's facial expressions and tone of voice, and the output is the user's emotional state. Specifically, it analyzes facial recognition camera and voice data to identify the emotion the user is expressing (e.g., anxiety, fear).

[0372] Step 7:

[0373] The server generates a warning message based on the emotion recognition results and keyword detection results and sends it to the device. The input is the emotional state and keyword detection results, and the output is a warning message. Specifically, it generates data to display a message on the device such as "This content may be a conspiracy theory."

[0374] Step 8:

[0375] The device displays the received warning message to the user, stops displaying the current content, and switches to safe content if necessary. The input is the warning message and instructions sent from the server, and the output is the warning message displayed on the user's display and the switching of the displayed content. Specifically, a warning message is displayed on the display, the current video playback is stopped, and educational content or news is played instead.

[0376] Prompt Sentence Examples

[0377] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[0378] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[0379] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[0380] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[0381] 4. Recognize the user's emotional state by analyzing their facial expressions.

[0382] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[0383] Write a Python program to perform these steps.

[0384] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0385] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0386] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0387] [Second embodiment]

[0388] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0389] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0390] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0391] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0392] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0393] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0394] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0395] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0396] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0397] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0398] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0399] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0400] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[0401] Basic system configuration

[0402] Taking and processing screen captures

[0403] The device periodically captures a screen capture, which contains the content displayed on the user's screen, especially when the user is using a video sharing service or social networking site. The captured screen capture is then sent to the server and processed in the next step.

[0404] Acquiring and processing audio capture

[0405] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[0406] Convert screen captures to text using OCR

[0407] The server converts the received screen capture image into text data using image processing technology (OCR), such as Tesseract OCR, which allows the server to obtain the text information on the screen.

[0408] Converting voice data into text using voice recognition

[0409] The server converts the received voice data into text data using speech recognition technology. For example, by using the Google Cloud Speech-to-Text API, it is possible to extract accurate text information from the voice.

[0410] Text data integration and analysis

[0411] The server integrates the text data obtained through OCR and speech recognition. It then analyzes this text data using natural language processing (NLP) techniques to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[0412] Generate and display warning messages

[0413] If certain keywords or phrases are detected, the server will flag a warning and generate a warning message that will be sent to the device and displayed to the user stating, "This content may be a conspiracy theory."

[0414] Stop showing content and switch to safe content

[0415] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, minimizing the impact of conspiracy theories on users.

[0416] Specific examples

[0417] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0418] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[0419] If a certain number of conspiracy theory-related keywords (e.g., "conspiracy," "secret organization," "manipulation") are included, the server will raise a warning flag and generate a warning message, which will be sent to the user's device and displayed on the user's screen, saying, "This content may be a conspiracy theory."

[0420] Furthermore, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news. In this way, the system can provide a safe information environment for seniors without influencing them with conspiracy theory content.

[0421] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet.

[0422] The processing flow will be explained below.

[0423] Step 1: Take a screen capture

[0424] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[0425] The device will capture the current screen contents and save it as an image file.

[0426] The device sends the captured image to the server.

[0427] Step 2: Getting an Audio Capture

[0428] Set up a task for the device to capture audio in real time.

[0429] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[0430] The terminal transmits the buffered audio data to the server.

[0431] Step 3: OCR processing

[0432] The server analyzes the received screen capture image.

[0433] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[0434] The server temporarily stores the extracted text data.

[0435] Step 4: Speech Recognition Processing

[0436] The server analyzes the received audio data.

[0437] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[0438] The server temporarily stores the extracted text data.

[0439] Step 5: Integrating text data

[0440] The server integrates the text data obtained through OCR processing and speech recognition processing.

[0441] Step 6: Natural Language Processing Analysis

[0442] The server analyzes the integrated text data using natural language processing technology.

[0443] The server detects specific conspiracy theory-related keywords and phrases.

[0444] Step 7: Generate a warning message

[0445] The server will flag certain keywords or phrases as warnings if they are detected.

[0446] If the server detects a warning flag, it generates a warning message.

[0447] Step 8: Sending a warning message

[0448] Sends server-generated warning messages to the terminal.

[0449] Step 9: Displaying warning messages

[0450] The terminal displays a warning message on the user's screen.

[0451] Step 10: Pause and Switch Content

[0452] The device will stop playing the current content if necessary after displaying the warning message.

[0453] Your device will automatically switch to safe content.

[0454] Example 1

[0455] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0456] Internet content contains misinformation and conspiracy theories, which can have a negative impact on users, especially vulnerable groups such as the elderly. Conventional methods lack the means to automatically detect this harmful content, warn users, and take appropriate action.

[0457] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0458] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keyword or phrase is detected, and means for stopping the display of the specific content and switching to safe content, thereby making it possible to provide a safe and healthy digital environment for users without being influenced by harmful content.

[0459] "Screen" refers to the entire visual information displayed on a user's device.

[0460] "Means for periodic acquisition" refers to a function for automatically collecting screen and audio data at regular intervals.

[0461] "Image processing technology" refers to the general technology for analyzing acquired image data and converting it into text or other information.

[0462] "Means for converting into text data" refers to a function for converting visual information or audio information into text information using image processing technology or voice recognition technology.

[0463] "Audio data" refers to the audio information of the content that the user is viewing.

[0464] "Speech recognition technology" refers to technology for analyzing voice data and extracting text information from the voice.

[0465] "Natural language processing technology" refers to the general technology for analyzing text data and detecting specific keywords and phrases.

[0466] "Specific keywords and phrases" refer to words or short phrases designed to identify conspiracy theories and other harmful content.

[0467] "Means for generating and displaying a warning message" refers to a function for issuing a warning to a user when a specific keyword or phrase is detected.

[0468] "Means to stop displaying content and switch to safe content" refers to a function that stops playback of detected harmful content and automatically switches to another content that is determined to be safe.

[0469] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[0470] System basic configuration and operation

[0471] Taking and processing screen captures

[0472] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. This capture contains everything displayed on the user's screen and is implemented using the Python Pillow library, among other things. The captured screen capture is sent to the server using an HTTP POST request.

[0473] Acquiring and processing audio capture

[0474] The device also captures the audio data of the video in real time, which is divided into buffers of a certain size, captured using the Python pyaudio library, and periodically sent to the server.

[0475] Processing on the server

[0476] When the server receives the screen capture image, it converts the image into text using Tesseract OCR. It also uses the Google Cloud Speech-to-Text API to recognize the audio data and convert it into text. This allows the image and audio information to be integrated into text data.

[0477] Text data integration and analysis

[0478] The server combines the text data obtained through OCR and speech recognition and performs natural language processing (NLP) using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[0479] Generate and display warning messages

[0480] If the server detects certain keywords or phrases, it generates a warning message that is sent to the device and displayed to the user, such as "This content may be a conspiracy theory."

[0481] Stop showing content and switch to safe content

[0482] After the warning message is displayed, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news, using the YouTube API, for example.

[0483] Specific examples

[0484] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every five seconds and sends it to the server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server converts the received screen captures into text data using Tesseract OCR and converts the audio data into text information using the Google Cloud Speech-to-Text API. These text data are then combined and analyzed using natural language processing technology. If conspiracy theory-related keywords such as "conspiracy" or "secret organization" are detected, the server generates a warning message and sends it to the user's device. The user's device then stops playing the current content and automatically switches to safe content.

[0485] Prompt Sentence Examples

[0486] A user is watching a video titled "Conspiracy Theories" on YouTube. The system takes a screen capture and audio of this video and detects keywords related to conspiracy theories. Explain this process using Tesseract OCR and the Google Cloud Speech-to-Text API.

[0487] In this way, the present invention can provide a safe and healthy digital environment where users are not affected by harmful content.

[0488] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0489] Step 1:

[0490] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. The input is the user's currently displayed screen image, and the output is the image data of that screen image. Specifically, the device sets a timer, takes a screenshot using the Python Pillow library, and saves it to a local temporary file.

[0491] Step 2:

[0492] The device captures the audio data of the video being played in real time. The input is the audio of the content the user is watching, and the output is a fixed-size buffer of audio data. Specifically, the device uses the Python pyaudio library to acquire audio from the system's audio output, split it into fixed-size buffers, and saves it.

[0493] Step 3:

[0494] The device sends screen captures taken every 5 seconds and real-time buffered audio data to the server using an HTTP POST request. The input is the screen capture image and audio data buffer, and the output is the data sent to the server.

[0495] Step 4:

[0496] The server receives the received screen capture image data and converts it into text data using Tesseract OCR. The input is the screen capture image and the output is text data. Specifically, the server saves the received image data to a temporary file and calls Tesseract OCR to extract text from the image.

[0497] Step 5:

[0498] The server converts the received audio data into text data using the Google Cloud Speech-to-Text API. The input is a buffer of audio data, and the output is text data. Specifically, the server saves the audio data in a temporary file and calls the Google Cloud Speech-to-Text API to extract text information from the audio.

[0499] Step 6:

[0500] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. The input is the OCR text data and speech recognition text data, and the output is the analysis results. Specifically, the server analyzes the integrated text data using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[0501] Step 7:

[0502] If the server detects a specific keyword or phrase, it generates a warning message and sends it to the terminal. The input is the analysis result, and the output is the generated warning message. Specifically, the server sets a warning flag based on the keyword detection result, generates a warning message from a template, and sends it to the terminal.

[0503] Step 8:

[0504] The device displays the received warning message, stops the display of the content being played, and switches to safe content. The input is the warning message, and the output is the content that was stopped and the switched-to safe content. Specifically, the device sends an API request to stop the content being played, and then sends a new playback request specifying the URL of the safe content.

[0505] (Application example 1)

[0506] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0507] In recent years, while a great deal of information is easily accessible through the internet, conspiracy theories and inaccurate information are also easily spread. Such information can have a particularly negative impact on the elderly and those with low internet literacy. This increases the risk that users will be unintentionally exposed to conspiracy theories. Therefore, it is necessary to develop a system that can detect conspiracy theory content in real time and issue warnings to users.

[0508] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0509] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keywords or phrases are detected, means for stopping the display of the specific content and switching to safe content, and means for warning the user when conspiracy theory-related keywords are detected, stopping related content as necessary, and automatically switching to safe content. This reduces the risk of users being exposed to conspiracy theory content and makes it possible to provide a safe and healthy digital environment.

[0510] "Screen" refers to the content of the display on which the video or image being viewed by the user on the device is displayed.

[0511] "Periodic acquisition" means collecting specific information at regular time intervals.

[0512] "Image processing technology" is a general term for technology that analyzes and edits digital images, and specifically includes OCR (Optical Character Recognition).

[0513] "Text data" refers to data that represents character information in a digital format.

[0514] "Terminal" is a general term for electronic devices used by users, including smartphones and personal computers.

[0515] "Audio data" refers to data that records audio in digital format.

[0516] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[0517] "Natural language processing technology" is a general term for technology that uses computers to analyze, understand, and generate human language.

[0518] "Analysis" is the process of examining data in detail and extracting specific patterns and important information.

[0519] "Keywords" are important words that are set to find specific information.

[0520] A "phrase" is a combination of words that has a particular meaning.

[0521] A "warning message" is a notification displayed to alert the user.

[0522] "Stop display" means stopping the playback of the content currently being viewed.

[0523] "Safe content" is content that comes from reliable sources and does not contain conspiracy theories or harmful information.

[0524] "User" means a person who uses a system or device to view content.

[0525] "Switching automatically" means that the system autonomously transitions to the next operation without human intervention.

[0526] An embodiment of the present invention provides a system that automatically detects conspiracy theory content and takes appropriate warnings and countermeasures when a user views or interacts with content on the Internet.

[0527] 1. Hardware and Software Used

[0528] Hardware: This system uses the user's device (smartphone, PC, tablet, etc.) and a server.

[0529] Software: Use Tesseract OCR, Google Cloud Speech-to-Text API, and natural language processing libraries (e.g., NLTK and spaCy).

[0530] 2. Program Processing Overview

[0531] Taking and sending screen captures

[0532] The user's device takes a screen capture every five seconds and sends this image data to the server, which collects images of the content the user is viewing.

[0533] Acquiring and sending audio data

[0534] Similarly, the device captures audio data in real time, divides it into a certain buffer size, and transmits it to the server, thereby collecting audio information about the content being viewed.

[0535] Converting image data into text using OCR

[0536] The server converts the received screen capture into text data using Tesseract OCR, which extracts the text information on the screen as text.

[0537] Converting audio data to text

[0538] The server uses the Google Cloud Speech-to-Text API to convert the transmitted voice data into text data, extracting accurate text information from the voice.

[0539] Text data integration and analysis

[0540] The server integrates the text data extracted by OCR and speech recognition and uses natural language processing techniques (e.g., NLTK, spaCy) to detect conspiracy theory-related keywords and phrases. During this process, it analyzes whether the data contains words or phrases related to conspiracy theories.

[0541] Generate and display warning messages

[0542] If certain keywords or phrases are detected, the server generates a warning message and sends it to the user's device, which displays the message, "This content may be a conspiracy theory."

[0543] Stop showing content and switch to safe content

[0544] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, protecting users from conspiracy theory content and providing safe information.

[0545] Specific examples

[0546] For example, if an elderly person is watching a video sharing service at home, a screen capture is taken every five seconds and the image data is sent to a server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server then analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. The audio data is then converted into text information using speech recognition technology. This text data is then integrated, and conspiracy theory-related keywords and phrases are detected using natural language processing technology. For example, if the keyword "secret organization" is detected, the server generates a warning message and sends it to the user's device. A warning message appears on the user's screen stating, "This content may be a conspiracy theory." Furthermore, if necessary, the device will stop playing the current content and automatically switch to safe content.

[0547] Example prompt sentence:

[0548] "This video contains the words 'secret organization.' This content may be a conspiracy theory."

[0549] This system will enable users to enjoy a healthier digital environment, free from the influence of conspiracy theories.

[0550] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0551] Step 1:

[0552] The device takes a screen capture every 5 seconds and saves it as image data. The input of the screen capture is the screen of the user's device, and the output is image data (e.g., a PNG file). Specifically, the device's screen capture function is used to capture a still image of the entire screen.

[0553] Step 2:

[0554] The terminal transmits the acquired screen capture to the server. The input is the image data of the screen capture, and the output is the image data transmitted to the server. Specifically, the terminal uploads the screen capture to the server using network communication.

[0555] Step 3:

[0556] The device buffers audio data in real time and transmits it to the server at regular intervals. The input is audio data captured by the device's microphone, and the output is audio data transmitted to the server. Specifically, the system captures audio from the device's microphone, stores it in a buffer, and then uploads it to the server.

[0557] Step 4:

[0558] The server converts the received screen capture into text data using image processing technology (Tesseract OCR). The input is the image data of the screen capture, and the output is the text data extracted from the image. Specifically, it starts Tesseract OCR, analyzes the screen capture, and generates text data.

[0559] Step 5:

[0560] The server converts the received voice data into text data using speech recognition technology (Google Cloud Speech-to-Text API). The input is voice data, and the output is text data extracted from the voice. Specifically, it calls the Google Cloud Speech-to-Text API to convert the voice data into text.

[0561] Step 6:

[0562] The server integrates the text data generated by OCR and speech recognition and analyzes it using natural language processing technology (e.g., NLTK or spaCy). The input is each piece of text data, and the output is the analysis result, which is the detection information for specific keywords and phrases. Specifically, the integrated text data is input into an NLP library to detect conspiracy theory-related keywords and phrases.

[0563] Step 7:

[0564] The server generates a warning message when a specific keyword or phrase is detected and sends it to the user's device. The input is the analysis result (detection information for a specific keyword or phrase), and the output is the generation and transmission of a warning message. Specifically, the server generates a warning message and notifies the user's device via the network.

[0565] Step 8:

[0566] The user device receives the warning message and displays a message on the screen saying, "This content may be a conspiracy theory." At the same time, it stops displaying the current content and automatically switches to safe content. The input is the warning message from the server, and the output is the display of the warning message and the switching of content. Specifically, it displays a pop-up warning message, stops the content being viewed, and starts playing another safe content.

[0567] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0568] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content when the user is viewing or interacting with content on the Internet, recognizes the user's emotions, and takes appropriate measures.

[0569] Basic system configuration

[0570] Taking and processing screen captures

[0571] The terminal periodically takes a screen capture, which contains the content displayed on the user's screen, and sends the captured screen capture to the server for further processing.

[0572] Acquiring and processing audio capture

[0573] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[0574] Convert screen captures to text using OCR

[0575] The server converts the received screen capture image into text data using image processing technology (OCR), allowing the character information on the screen to be obtained.

[0576] Converting voice data into text using voice recognition

[0577] The server converts the received voice data into text data using voice recognition technology, allowing accurate extraction of text information from the voice.

[0578] Text data integration and analysis

[0579] The server integrates the text data obtained through OCR and speech recognition, then analyzes the text data using natural language processing (NLP) to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[0580] Emotion Recognition in Action

[0581] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which will recognize the user's emotions by analyzing their facial expressions and tone of voice, thereby understanding their emotional state.

[0582] Generate and display warning messages

[0583] Based on the results of keyword detection and emotion recognition, the server generates a warning message, which is sent to the device and displayed to the user, stating, "This content may be a conspiracy theory."

[0584] Stop showing content and switch to safe content

[0585] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content, such as educational videos or news, if necessary.

[0586] Specific examples

[0587] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0588] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[0589] For example, if conspiracy-theory related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[0590] Based on the emotion recognition results, the server raises a warning flag and generates a warning message. This message is sent to the device and displayed on the user's screen, stating, "This content may be a conspiracy theory." At the same time, playback of the current content is stopped and automatically switched to safe content. In this way, the system can provide a safe information environment for seniors without exposing them to conspiracy theory content.

[0591] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet. Furthermore, by adding emotion recognition, appropriate measures can be taken depending on the user's psychological state, ensuring further safety.

[0592] The processing flow will be explained below.

[0593] Step 1: Take a screen capture

[0594] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[0595] The device will capture the current screen contents and save it as an image file.

[0596] The device sends the captured image to the server.

[0597] Step 2: Getting an Audio Capture

[0598] Set up a task for the device to capture audio in real time.

[0599] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[0600] The terminal transmits the buffered audio data to the server.

[0601] Step 3: Convert screen capture to text using OCR

[0602] The server analyzes the received screen capture image.

[0603] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[0604] The server temporarily stores the extracted text data.

[0605] Step 4: Converting voice data into text using voice recognition

[0606] The server analyzes the received audio data.

[0607] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[0608] The server temporarily stores the extracted text data.

[0609] Step 5: Integrating text data

[0610] The server integrates the text data obtained through OCR processing and speech recognition processing.

[0611] Step 6: Natural Language Processing Analysis

[0612] The server analyzes the integrated text data using natural language processing technology.

[0613] The server detects specific conspiracy theory-related keywords and phrases.

[0614] Step 7: Activate the Emotion Engine

[0615] The server activates the emotion engine when certain keywords or phrases are detected.

[0616] The server analyzes the user's facial expressions and tone of voice to recognize their emotions.

[0617] Step 8: Generate a warning message

[0618] If the server detects that the user's emotions indicate anxiety or fear based on the emotion recognition results, it sets a warning flag.

[0619] If the server detects a warning flag, it generates a warning message.

[0620] Step 9: Sending a warning message

[0621] Sends server-generated warning messages to the terminal.

[0622] Step 10: Displaying warning messages

[0623] The terminal displays a warning message on the user's screen.

[0624] Step 11: Pause and Switch Content

[0625] The device will stop playing the current content after displaying the warning message.

[0626] Your device will automatically switch to safe content.

[0627] Example 2

[0628] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0629] As the amount of information on the Internet explodes, the risk of conspiracy theories and false information becoming increasingly influential is increasing. To address this issue, it is important to not only automatically analyze the content users view and detect problematic information, but also to monitor their emotional state. However, current safety measures lack systems that integrate content analysis and emotion recognition, making it difficult to quickly implement appropriate countermeasures. Furthermore, there are limited means to display appropriate warnings to users and smoothly switch them to safe content.

[0630] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0631] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of the specific content and switching to safe content, and emotion recognition means for analyzing the user's emotions. This makes it possible to detect content containing conspiracy theories or false information in real time and quickly issue a warning to the user, as well as take appropriate measures taking the user's emotional state into consideration.

[0632] The "screen capture means" is a means having a function of periodically capturing the screen of the user's terminal.

[0633] "Image processing technology" is a technology for analyzing and converting digital images to obtain the necessary information.

[0634] The "means for converting into text data" refers to a means having a function for converting information extracted from an image or sound into a character format.

[0635] The "means for acquiring voice data from the terminal" refers to a means having a function for recording the user's voice and collecting that data.

[0636] "Speech recognition technology" is a technology that analyzes acquired voice data and converts it into text data.

[0637] "Natural language processing technology" is a technology for analyzing text data and deciphering its meaning and structure.

[0638] The "means for detecting specific keywords or phrases" refers to a means having the function of identifying important words or phrases from the analyzed text data.

[0639] The "means for generating and displaying a warning message" refers to a means having a function for generating a message for notifying a user of a warning based on the detected content and displaying the message.

[0640] The "means for stopping the display of specific content and switching to safe content" refers to a means having a function for stopping the playback of problematic content and displaying safe content instead.

[0641] The "emotion recognition means" is a means having a function of analyzing the user's facial expression and tone of voice and identifying the user's emotional state.

[0642] The term "system" refers to the entire information processing device that operates by integrating these means and technologies.

[0643] This invention consists of a system based on software and a server implemented on a user's device. When a user views or interacts with content on the Internet, it can automatically detect conspiracy theory content, recognize the user's emotions, and take appropriate measures. This system is implemented using the following hardware and software:

[0644] Taking and processing screen captures

[0645] The device periodically (for example, every 5 seconds) takes a screen capture. The device takes a screen capture using a function called "GetScreenshot()" and sends the data to the server via an HTTP POST request.

[0646] Acquiring and processing audio capture

[0647] The device captures audio data in real time, divides it into a certain buffer size (for example, every second), and sends it to the server. The device collects audio data using a function called "CaptureAudio()" and sends this data to the server via an HTTP POST request.

[0648] Convert screen captures to text using OCR

[0649] The server converts the received screen capture image into text data using OCR technology called Tesseract. The server converts image data into text data using the function "TesseractOCR.Process(image)".

[0650] Converting voice data into text using voice recognition

[0651] The server converts the received voice data into text data using the Google Cloud Speech-to-Text API. The server converts the voice data into text data using the function "GoogleSpeechToTextAPI.convert(audio)".

[0652] Text data integration and analysis

[0653] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) techniques. This analysis is performed using libraries such as NLTK or SpaCy. The server uses the function "NLTK.Process(text)" to analyze the text data and detect conspiracy theory-related keywords.

[0654] Emotion Recognition in Action

[0655] If a specific keyword or phrase is detected, the server activates the emotion engine using OpenCV and the Microsoft Azure Emotion API. The server uses the functions "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)" to recognize emotions.

[0656] Generate and display warning messages

[0657] The server generates a warning message and sends it to the terminal, which then displays it to the user using the function "displayWarning(message)".

[0658] Stop showing content and switch to safe content

[0659] After the warning message is displayed, the device stops playing the current content using the function "StopCurrentContent()" and plays safe content using the function "PlaySafeContent()".

[0660] Specific examples

[0661] For example, if an elderly person is watching a video on the Internet at home, the device will take a screen capture every five seconds and send the data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0662] The server analyzes the received screen captures using Tesseract OCR and converts subtitles and on-screen comments in the video into text data. The audio data is converted into text information using the Google Cloud Speech-to-Text API. The text data is then merged and analyzed using NLTK or SpaCy.

[0663] For example, if conspiracy-related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an OpenCV-based emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[0664] Based on the emotion recognition results, the server will raise a warning flag and generate a warning message, which will be sent to the device and displayed on the user's screen, stating "This content may be a conspiracy theory." At the same time, the current content will stop playing and automatically switch to safe content.

[0665] Example prompts for generative AI models

[0666] "Please explain the program's procedures for identifying content that contains conspiracy theories and issuing warnings to users."

[0667] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0668] Step 1:

[0669] The device takes a screen capture at regular intervals (for example, every 5 seconds). The content displayed on the device's display is taken as input, and its image data is generated as output. Specifically, the "GetScreenshot()" function is used to take a screen capture, and the data is sent to the server via an HTTP POST request.

[0670] Step 2:

[0671] The device captures audio data in real time. As input, it receives audio data acquired through the device's microphone, divides the audio data into a certain buffer size (for example, every second), and sends the data to the server as output. Specifically, it uses the "CaptureAudio()" function to collect audio data and sends it to the server via an HTTP POST request.

[0672] Step 3:

[0673] The server converts the received screen capture image into text data using OCR technology. It receives the screen capture image as input, processes the image, and obtains text data as output. Specifically, it uses the "TesseractOCR.Process(image)" function to convert image data into text data.

[0674] Step 4:

[0675] The server converts the received voice data into text data using speech recognition technology. It receives voice data as input, performs speech recognition, and obtains text data as output. Specifically, it uses the "GoogleSpeechToTextAPI.convert(audio)" function to convert voice data into text data.

[0676] Step 5:

[0677] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. It integrates the text data as input, performs NLP analysis on it, and obtains data containing specific keywords and phrases as output. Specifically, it uses the "NLTK.Process(text)" function to analyze the text data and detect conspiracy theory-related keywords.

[0678] Step 6:

[0679] When a specific keyword or phrase is detected, the server analyzes the user's emotion using emotion recognition. It receives facial expressions and voice tone as input, analyzes the emotions, and obtains the user's emotional state as output. Specifically, it uses the "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)" functions to recognize emotions.

[0680] Step 7:

[0681] The server generates a warning message based on the emotion recognition results and sends it to the device. It receives the emotion recognition and keyword detection results as input, generates a warning message, and sends the warning message to the device as output. Specifically, it creates a warning message using the "GenerateWarningMessage(keywords, emotions)" function and sends it to the device via an HTTP POST request.

[0682] Step 8:

[0683] The device displays the received warning message to the user, stops playing the current content if necessary, and switches to safe content. It receives the warning message and current content information as input, and displays the warning message and starts playing safe content as output. Specifically, it displays the warning message using the "displayWarning(message)" function, stops the current content using the "StopCurrentContent()" function, and plays safe content using the "PlaySafeContent()" function.

[0684] (Application example 2)

[0685] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0686] Content provided on the Internet may contain conspiracy theories and misinformation, which poses a risk of causing anxiety and inappropriate influence to users, especially elderly people. There is a need for a system that can automatically detect such conspiracy theory content and ensure that users can view the content in a healthy and safe information environment. In addition, there is a need to develop a system that can provide greater safety and security by understanding the user's psychological state and responding appropriately.

[0687] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0688] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of specific content and switching to safe content, and means for analyzing content viewed by a user in real time, detecting conspiracy theory content, recognizing emotions, and taking appropriate measures based on the emotions. This enables automatic detection of conspiracy theory content and appropriate measures based on the user's emotional state.

[0689] "Screen" refers to the entire content displayed on a digital device's display.

[0690] "Means for periodic capture" refers to a device or process that has the function of capturing screen captures at regular time intervals.

[0691] "Image processing technology" refers to technology for extracting and analyzing specific information based on acquired image data.

[0692] "Means for converting into text data" refers to the function of extracting text information from image or audio data and converting it into text format using image processing technology, etc.

[0693] "Audio data" refers to sound information recorded or captured in real time by a digital device.

[0694] "Speech recognition technology" refers to the technology that analyzes voice data, extracts linguistic information from it, and converts it into text data.

[0695] "Natural language processing technology" refers to computational techniques for analyzing, understanding, and generating human language data.

[0696] "Keyword and phrase detection method" refers to a technique or process for identifying specific words or phrases in the analyzed text.

[0697] "Means for generating and displaying a warning message" refers to a function that generates a message to alert the user when a specific condition is met and displays the message on the user's device.

[0698] "Means to stop displaying content and switch to safe content" refers to a function that stops displaying inappropriate content and automatically switches to another safe content when inappropriate content is detected.

[0699] "Conspiracy theory content" refers to content that contains unproven theories or unfounded information.

[0700] "Emotion recognition" refers to technology that analyzes a user's facial expressions and tone of voice to identify the emotions they are feeling.

[0701] "Appropriate response based on the user's emotional state" refers to using emotion recognition technology to determine the user's psychological state and then taking appropriate action such as issuing a warning or changing the content.

[0702] "Real-time analysis" refers to processing acquired data immediately and outputting results quickly.

[0703] The following describes in detail the mode for carrying out the present invention. This system is mainly composed of a server and a terminal, and its purpose is to automatically detect conspiracy theories in the content viewed by users, analyze the users' emotions, and take appropriate measures.

[0704] First, the device has a function to periodically capture screens. This function allows the device to capture screens at regular intervals (for example, every 5 seconds) and send them to the server. The device also captures audio data in real time and periodically sends it to the server.

[0705] The server converts the received screen capture into text data using image processing technology (OCR: Optical Character Recognition). Similarly, it converts the received voice data into text data using voice recognition technology. This allows the server to obtain the character information on the screen and the voice information as text data.

[0706] The server then analyzes the converted text data using natural language processing (NLP) technology to detect specific keywords and phrases, such as "conspiracy," "secret organization," and "manipulation."

[0707] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotions, allowing the server to understand their emotional state.

[0708] If the user shows signs of anxiety or fear, the server will instantly generate a warning message and send it to the device, which will then display the message on the user's screen, stop the current content, and automatically switch to safe content, such as educational videos or news.

[0709] This system allows users to enjoy a healthy and safe information environment without being influenced by conspiracy theory content. Furthermore, emotion recognition enables more appropriate responses, ensuring the user's psychological safety.

[0710] As a concrete example, consider the case where a user is watching an internet video using smart glasses. The system analyzes the content the user is watching in real time to detect inappropriate content (e.g., conspiracy theories). Screen captures are taken every five seconds, and audio data is also captured in real time and sent to a server. If the analysis detects the keyword "manipulation" and the user shows an anxious expression, a warning appears on the smart glasses' display stating, "This content may be a conspiracy theory. It may be disturbing." The system then automatically switches to a safe news video.

[0711] Prompt Sentence Examples

[0712] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[0713] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[0714] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[0715] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[0716] 4. Recognize the user's emotional state by analyzing their facial expressions.

[0717] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[0718] Write a Python program to perform these steps.

[0719] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0720] Step 1:

[0721] The device takes a screen capture at regular intervals. The input is a real-time image of the screen, which is captured as image data. The output is the captured image data. Specifically, the device's built-in camera is used to save the contents of the screen as image data. This process is performed every 5 seconds, for example, and the captured image is used in the next step.

[0722] Step 2:

[0723] The device captures audio data in real time, divides it into a certain buffer size, and sends it to the server. The input is the audio signal obtained from the microphone. The output is the audio signal stored in the buffer as digital data. Specifically, the device's built-in microphone is used to record ambient audio, and the recorded audio data is buffered.

[0724] Step 3:

[0725] The server converts the screen capture received from the device into text data using image processing technology (OCR: Optical Character Recognition). The input is the image data of the screen capture, and the output is text data. Specifically, the OCR engine is used to extract characters from the image and obtain them as a string of characters.

[0726] Step 4:

[0727] The server converts the voice data received from the terminal into text data using voice recognition technology. The input is voice data, and the output is text data extracted from that voice. Specifically, the server uses a voice recognition engine to analyze the voice data and obtain its contents as a string of characters.

[0728] Step 5:

[0729] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) technology. The input is the integrated text data, and the output is the detection of conspiracy theory-related keywords and phrases. Specifically, the server uses a natural language processing engine to detect specific keywords (e.g., "conspiracy," "secret organization," and "manipulation") within the text data.

[0730] Step 6:

[0731] The server activates an emotion engine based on the keyword detection results. The input is data including the user's facial expressions and tone of voice, and the output is the user's emotional state. Specifically, it analyzes facial recognition camera and voice data to identify the emotion the user is expressing (e.g., anxiety, fear).

[0732] Step 7:

[0733] The server generates a warning message based on the emotion recognition results and keyword detection results and sends it to the device. The input is the emotional state and keyword detection results, and the output is a warning message. Specifically, it generates data to display a message on the device such as "This content may be a conspiracy theory."

[0734] Step 8:

[0735] The device displays the received warning message to the user, stops displaying the current content, and switches to safe content if necessary. The input is the warning message and instructions sent from the server, and the output is the warning message displayed on the user's display and the switching of the displayed content. Specifically, a warning message is displayed on the display, the current video playback is stopped, and educational content or news is played instead.

[0736] Prompt Sentence Examples

[0737] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[0738] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[0739] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[0740] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[0741] 4. Recognize the user's emotional state by analyzing their facial expressions.

[0742] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[0743] Write a Python program to perform these steps.

[0744] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0745] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0746] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0747] [Third embodiment]

[0748] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0749] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0750] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0751] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0752] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0753] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0754] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0755] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0756] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0757] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0758] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0759] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0760] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[0761] Basic system configuration

[0762] Taking and processing screen captures

[0763] The device periodically captures a screen capture, which contains the content displayed on the user's screen, especially when the user is using a video sharing service or social networking site. The captured screen capture is then sent to the server and processed in the next step.

[0764] Acquiring and processing audio capture

[0765] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[0766] Convert screen captures to text using OCR

[0767] The server converts the received screen capture image into text data using image processing technology (OCR), such as Tesseract OCR, which allows the server to obtain the text information on the screen.

[0768] Converting voice data into text using voice recognition

[0769] The server converts the received voice data into text data using speech recognition technology. For example, by using the Google Cloud Speech-to-Text API, it is possible to extract accurate text information from the voice.

[0770] Text data integration and analysis

[0771] The server integrates the text data obtained through OCR and speech recognition. It then analyzes this text data using natural language processing (NLP) techniques to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[0772] Generate and display warning messages

[0773] If certain keywords or phrases are detected, the server will flag a warning and generate a warning message that will be sent to the device and displayed to the user stating, "This content may be a conspiracy theory."

[0774] Stop showing content and switch to safe content

[0775] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, minimizing the impact of conspiracy theories on users.

[0776] Specific examples

[0777] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0778] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[0779] If a certain number of conspiracy theory-related keywords (e.g., "conspiracy," "secret organization," "manipulation") are included, the server will raise a warning flag and generate a warning message, which will be sent to the user's device and displayed on the user's screen, saying, "This content may be a conspiracy theory."

[0780] Furthermore, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news. In this way, the system can provide a safe information environment for seniors without influencing them with conspiracy theory content.

[0781] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet.

[0782] The processing flow will be explained below.

[0783] Step 1: Take a screen capture

[0784] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[0785] The device will capture the current screen contents and save it as an image file.

[0786] The device sends the captured image to the server.

[0787] Step 2: Getting an Audio Capture

[0788] Set up a task for the device to capture audio in real time.

[0789] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[0790] The terminal transmits the buffered audio data to the server.

[0791] Step 3: OCR processing

[0792] The server analyzes the received screen capture image.

[0793] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[0794] The server temporarily stores the extracted text data.

[0795] Step 4: Speech Recognition Processing

[0796] The server analyzes the received audio data.

[0797] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[0798] The server temporarily stores the extracted text data.

[0799] Step 5: Integrating text data

[0800] The server integrates the text data obtained through OCR processing and speech recognition processing.

[0801] Step 6: Natural Language Processing Analysis

[0802] The server analyzes the integrated text data using natural language processing technology.

[0803] The server detects specific conspiracy theory-related keywords and phrases.

[0804] Step 7: Generate a warning message

[0805] The server will flag certain keywords or phrases as warnings if they are detected.

[0806] If the server detects a warning flag, it generates a warning message.

[0807] Step 8: Sending a warning message

[0808] Sends server-generated warning messages to the terminal.

[0809] Step 9: Displaying warning messages

[0810] The terminal displays a warning message on the user's screen.

[0811] Step 10: Pause and Switch Content

[0812] The device will stop playing the current content if necessary after displaying the warning message.

[0813] Your device will automatically switch to safe content.

[0814] Example 1

[0815] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0816] Internet content contains misinformation and conspiracy theories, which can have a negative impact on users, especially vulnerable groups such as the elderly. Conventional methods lack the means to automatically detect this harmful content, warn users, and take appropriate action.

[0817] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0818] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keyword or phrase is detected, and means for stopping the display of the specific content and switching to safe content, thereby making it possible to provide a safe and healthy digital environment for users without being influenced by harmful content.

[0819] "Screen" refers to the entire visual information displayed on a user's device.

[0820] "Means for periodic acquisition" refers to a function for automatically collecting screen and audio data at regular intervals.

[0821] "Image processing technology" refers to the general technology for analyzing acquired image data and converting it into text or other information.

[0822] "Means for converting into text data" refers to a function for converting visual information or audio information into text information using image processing technology or voice recognition technology.

[0823] "Audio data" refers to the audio information of the content that the user is viewing.

[0824] "Speech recognition technology" refers to technology for analyzing voice data and extracting text information from the voice.

[0825] "Natural language processing technology" refers to the general technology for analyzing text data and detecting specific keywords and phrases.

[0826] "Specific keywords and phrases" refer to words or short phrases designed to identify conspiracy theories and other harmful content.

[0827] "Means for generating and displaying a warning message" refers to a function for issuing a warning to a user when a specific keyword or phrase is detected.

[0828] "Means to stop displaying content and switch to safe content" refers to a function that stops playback of detected harmful content and automatically switches to another content that is determined to be safe.

[0829] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[0830] System basic configuration and operation

[0831] Taking and processing screen captures

[0832] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. This capture contains everything displayed on the user's screen and is implemented using the Python Pillow library, among other things. The captured screen capture is sent to the server using an HTTP POST request.

[0833] Acquiring and processing audio capture

[0834] The device also captures the audio data of the video in real time, which is divided into buffers of a certain size, captured using the Python pyaudio library, and periodically sent to the server.

[0835] Processing on the server

[0836] When the server receives the screen capture image, it converts the image into text using Tesseract OCR. It also uses the Google Cloud Speech-to-Text API to recognize the audio data and convert it into text. This allows the image and audio information to be integrated into text data.

[0837] Text data integration and analysis

[0838] The server combines the text data obtained through OCR and speech recognition and performs natural language processing (NLP) using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[0839] Generate and display warning messages

[0840] If the server detects certain keywords or phrases, it generates a warning message that is sent to the device and displayed to the user, such as "This content may be a conspiracy theory."

[0841] Stop showing content and switch to safe content

[0842] After the warning message is displayed, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news, using the YouTube API, for example.

[0843] Specific examples

[0844] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every five seconds and sends it to the server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server converts the received screen captures into text data using Tesseract OCR and converts the audio data into text information using the Google Cloud Speech-to-Text API. These text data are then combined and analyzed using natural language processing technology. If conspiracy theory-related keywords such as "conspiracy" or "secret organization" are detected, the server generates a warning message and sends it to the user's device. The user's device then stops playing the current content and automatically switches to safe content.

[0845] Prompt Sentence Examples

[0846] A user is watching a video titled "Conspiracy Theories" on YouTube. The system takes a screen capture and audio of this video and detects keywords related to conspiracy theories. Explain this process using Tesseract OCR and the Google Cloud Speech-to-Text API.

[0847] In this way, the present invention can provide a safe and healthy digital environment where users are not affected by harmful content.

[0848] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0849] Step 1:

[0850] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. The input is the user's currently displayed screen image, and the output is the image data of that screen image. Specifically, the device sets a timer, takes a screenshot using the Python Pillow library, and saves it to a local temporary file.

[0851] Step 2:

[0852] The device captures the audio data of the video being played in real time. The input is the audio of the content the user is watching, and the output is a fixed-size buffer of audio data. Specifically, the device uses the Python pyaudio library to acquire audio from the system's audio output, split it into fixed-size buffers, and saves it.

[0853] Step 3:

[0854] The device sends screen captures taken every 5 seconds and real-time buffered audio data to the server using an HTTP POST request. The input is the screen capture image and audio data buffer, and the output is the data sent to the server.

[0855] Step 4:

[0856] The server receives the received screen capture image data and converts it into text data using Tesseract OCR. The input is the screen capture image and the output is text data. Specifically, the server saves the received image data to a temporary file and calls Tesseract OCR to extract text from the image.

[0857] Step 5:

[0858] The server converts the received audio data into text data using the Google Cloud Speech-to-Text API. The input is a buffer of audio data, and the output is text data. Specifically, the server saves the audio data in a temporary file and calls the Google Cloud Speech-to-Text API to extract text information from the audio.

[0859] Step 6:

[0860] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. The input is the OCR text data and speech recognition text data, and the output is the analysis results. Specifically, the server analyzes the integrated text data using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[0861] Step 7:

[0862] If the server detects a specific keyword or phrase, it generates a warning message and sends it to the terminal. The input is the analysis result, and the output is the generated warning message. Specifically, the server sets a warning flag based on the keyword detection result, generates a warning message from a template, and sends it to the terminal.

[0863] Step 8:

[0864] The device displays the received warning message, stops the display of the content being played, and switches to safe content. The input is the warning message, and the output is the content that was stopped and the switched-to safe content. Specifically, the device sends an API request to stop the content being played, and then sends a new playback request specifying the URL of the safe content.

[0865] (Application example 1)

[0866] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0867] In recent years, while a great deal of information is easily accessible through the internet, conspiracy theories and inaccurate information are also easily spread. Such information can have a particularly negative impact on the elderly and those with low internet literacy. This increases the risk that users will be unintentionally exposed to conspiracy theories. Therefore, it is necessary to develop a system that can detect conspiracy theory content in real time and issue warnings to users.

[0868] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0869] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keywords or phrases are detected, means for stopping the display of the specific content and switching to safe content, and means for warning the user when conspiracy theory-related keywords are detected, stopping related content as necessary, and automatically switching to safe content. This reduces the risk of users being exposed to conspiracy theory content and makes it possible to provide a safe and healthy digital environment.

[0870] "Screen" refers to the content of the display on which the video or image being viewed by the user on the device is displayed.

[0871] "Periodic acquisition" means collecting specific information at regular time intervals.

[0872] "Image processing technology" is a general term for technology that analyzes and edits digital images, and specifically includes OCR (Optical Character Recognition).

[0873] "Text data" refers to data that represents character information in a digital format.

[0874] "Terminal" is a general term for electronic devices used by users, including smartphones and personal computers.

[0875] "Audio data" refers to data that records audio in digital format.

[0876] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[0877] "Natural language processing technology" is a general term for technology that uses computers to analyze, understand, and generate human language.

[0878] "Analysis" is the process of examining data in detail and extracting specific patterns and important information.

[0879] "Keywords" are important words that are set to find specific information.

[0880] A "phrase" is a combination of words that has a particular meaning.

[0881] A "warning message" is a notification displayed to alert the user.

[0882] "Stop display" means stopping the playback of the content currently being viewed.

[0883] "Safe content" is content that comes from reliable sources and does not contain conspiracy theories or harmful information.

[0884] "User" means a person who uses a system or device to view content.

[0885] "Switching automatically" means that the system autonomously transitions to the next operation without human intervention.

[0886] An embodiment of the present invention provides a system that automatically detects conspiracy theory content and takes appropriate warnings and countermeasures when a user views or interacts with content on the Internet.

[0887] 1. Hardware and Software Used

[0888] Hardware: This system uses the user's device (smartphone, PC, tablet, etc.) and a server.

[0889] Software: Use Tesseract OCR, Google Cloud Speech-to-Text API, and natural language processing libraries (e.g., NLTK and spaCy).

[0890] 2. Program Processing Overview

[0891] Taking and sending screen captures

[0892] The user's device takes a screen capture every five seconds and sends this image data to the server, which collects images of the content the user is viewing.

[0893] Acquiring and sending audio data

[0894] Similarly, the device captures audio data in real time, divides it into a certain buffer size, and transmits it to the server, thereby collecting audio information about the content being viewed.

[0895] Converting image data into text using OCR

[0896] The server converts the received screen capture into text data using Tesseract OCR, which extracts the text information on the screen as text.

[0897] Converting audio data to text

[0898] The server uses the Google Cloud Speech-to-Text API to convert the transmitted voice data into text data, extracting accurate text information from the voice.

[0899] Text data integration and analysis

[0900] The server integrates the text data extracted by OCR and speech recognition and uses natural language processing techniques (e.g., NLTK, spaCy) to detect conspiracy theory-related keywords and phrases. During this process, it analyzes whether the data contains words or phrases related to conspiracy theories.

[0901] Generate and display warning messages

[0902] If certain keywords or phrases are detected, the server generates a warning message and sends it to the user's device, which displays the message, "This content may be a conspiracy theory."

[0903] Stop showing content and switch to safe content

[0904] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, protecting users from conspiracy theory content and providing safe information.

[0905] Specific examples

[0906] For example, if an elderly person is watching a video sharing service at home, a screen capture is taken every five seconds and the image data is sent to a server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server then analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. The audio data is then converted into text information using speech recognition technology. This text data is then integrated, and conspiracy theory-related keywords and phrases are detected using natural language processing technology. For example, if the keyword "secret organization" is detected, the server generates a warning message and sends it to the user's device. A warning message appears on the user's screen stating, "This content may be a conspiracy theory." Furthermore, if necessary, the device will stop playing the current content and automatically switch to safe content.

[0907] Example prompt sentence:

[0908] "This video contains the words 'secret organization.' This content may be a conspiracy theory."

[0909] This system will enable users to enjoy a healthier digital environment, free from the influence of conspiracy theories.

[0910] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0911] Step 1:

[0912] The device takes a screen capture every 5 seconds and saves it as image data. The input of the screen capture is the screen of the user's device, and the output is image data (e.g., a PNG file). Specifically, the device's screen capture function is used to capture a still image of the entire screen.

[0913] Step 2:

[0914] The terminal transmits the acquired screen capture to the server. The input is the image data of the screen capture, and the output is the image data transmitted to the server. Specifically, the terminal uploads the screen capture to the server using network communication.

[0915] Step 3:

[0916] The device buffers audio data in real time and transmits it to the server at regular intervals. The input is audio data captured by the device's microphone, and the output is audio data transmitted to the server. Specifically, the system captures audio from the device's microphone, stores it in a buffer, and then uploads it to the server.

[0917] Step 4:

[0918] The server converts the received screen capture into text data using image processing technology (Tesseract OCR). The input is the image data of the screen capture, and the output is the text data extracted from the image. Specifically, it starts Tesseract OCR, analyzes the screen capture, and generates text data.

[0919] Step 5:

[0920] The server converts the received voice data into text data using speech recognition technology (Google Cloud Speech-to-Text API). The input is voice data, and the output is text data extracted from the voice. Specifically, it calls the Google Cloud Speech-to-Text API to convert the voice data into text.

[0921] Step 6:

[0922] The server integrates the text data generated by OCR and speech recognition and analyzes it using natural language processing technology (e.g., NLTK or spaCy). The input is each piece of text data, and the output is the analysis result, which is the detection information for specific keywords and phrases. Specifically, the integrated text data is input into an NLP library to detect conspiracy theory-related keywords and phrases.

[0923] Step 7:

[0924] The server generates a warning message when a specific keyword or phrase is detected and sends it to the user's device. The input is the analysis result (detection information for a specific keyword or phrase), and the output is the generation and transmission of a warning message. Specifically, the server generates a warning message and notifies the user's device via the network.

[0925] Step 8:

[0926] The user device receives the warning message and displays a message on the screen saying, "This content may be a conspiracy theory." At the same time, it stops displaying the current content and automatically switches to safe content. The input is the warning message from the server, and the output is the display of the warning message and the switching of content. Specifically, it displays a pop-up warning message, stops the content being viewed, and starts playing another safe content.

[0927] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0928] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content when the user is viewing or interacting with content on the Internet, recognizes the user's emotions, and takes appropriate measures.

[0929] Basic system configuration

[0930] Taking and processing screen captures

[0931] The terminal periodically takes a screen capture, which contains the content displayed on the user's screen, and sends the captured screen capture to the server for further processing.

[0932] Acquiring and processing audio capture

[0933] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[0934] Convert screen captures to text using OCR

[0935] The server converts the received screen capture image into text data using image processing technology (OCR), allowing the character information on the screen to be obtained.

[0936] Converting voice data into text using voice recognition

[0937] The server converts the received voice data into text data using voice recognition technology, allowing accurate extraction of text information from the voice.

[0938] Text data integration and analysis

[0939] The server integrates the text data obtained through OCR and speech recognition, then analyzes the text data using natural language processing (NLP) to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[0940] Emotion Recognition in Action

[0941] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which will recognize the user's emotions by analyzing their facial expressions and tone of voice, thereby understanding their emotional state.

[0942] Generate and display warning messages

[0943] Based on the results of keyword detection and emotion recognition, the server generates a warning message, which is sent to the device and displayed to the user, stating, "This content may be a conspiracy theory."

[0944] Stop showing content and switch to safe content

[0945] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content, such as educational videos or news, if necessary.

[0946] Specific examples

[0947] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[0948] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[0949] For example, if conspiracy-theory related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[0950] Based on the emotion recognition results, the server raises a warning flag and generates a warning message. This message is sent to the device and displayed on the user's screen, stating, "This content may be a conspiracy theory." At the same time, playback of the current content is stopped and automatically switched to safe content. In this way, the system can provide a safe information environment for seniors without exposing them to conspiracy theory content.

[0951] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet. Furthermore, by adding emotion recognition, appropriate measures can be taken depending on the user's psychological state, ensuring further safety.

[0952] The processing flow will be explained below.

[0953] Step 1: Take a screen capture

[0954] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[0955] The device will capture the current screen contents and save it as an image file.

[0956] The device sends the captured image to the server.

[0957] Step 2: Getting an Audio Capture

[0958] Set up a task for the device to capture audio in real time.

[0959] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[0960] The terminal transmits the buffered audio data to the server.

[0961] Step 3: Convert screen capture to text using OCR

[0962] The server analyzes the received screen capture image.

[0963] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[0964] The server temporarily stores the extracted text data.

[0965] Step 4: Converting voice data into text using voice recognition

[0966] The server analyzes the received audio data.

[0967] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[0968] The server temporarily stores the extracted text data.

[0969] Step 5: Integrating text data

[0970] The server integrates the text data obtained through OCR processing and speech recognition processing.

[0971] Step 6: Natural Language Processing Analysis

[0972] The server analyzes the integrated text data using natural language processing technology.

[0973] The server detects specific conspiracy theory-related keywords and phrases.

[0974] Step 7: Activate the Emotion Engine

[0975] The server activates the emotion engine when certain keywords or phrases are detected.

[0976] The server analyzes the user's facial expressions and tone of voice to recognize their emotions.

[0977] Step 8: Generate a warning message

[0978] If the server detects that the user's emotions indicate anxiety or fear based on the emotion recognition results, it sets a warning flag.

[0979] If the server detects a warning flag, it generates a warning message.

[0980] Step 9: Sending a warning message

[0981] Sends server-generated warning messages to the terminal.

[0982] Step 10: Displaying warning messages

[0983] The terminal displays a warning message on the user's screen.

[0984] Step 11: Pause and Switch Content

[0985] The device will stop playing the current content after displaying the warning message.

[0986] Your device will automatically switch to safe content.

[0987] Example 2

[0988] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0989] As the amount of information on the Internet explodes, the risk of conspiracy theories and false information becoming increasingly influential is increasing. To address this issue, it is important to not only automatically analyze the content users view and detect problematic information, but also to monitor their emotional state. However, current safety measures lack systems that integrate content analysis and emotion recognition, making it difficult to quickly implement appropriate countermeasures. Furthermore, there are limited means to display appropriate warnings to users and smoothly switch them to safe content.

[0990] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0991] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of the specific content and switching to safe content, and emotion recognition means for analyzing the user's emotions. This makes it possible to detect content containing conspiracy theories or false information in real time and quickly issue a warning to the user, as well as take appropriate measures taking the user's emotional state into consideration.

[0992] The "screen capture means" is a means having a function of periodically capturing the screen of the user's terminal.

[0993] "Image processing technology" is a technology for analyzing and converting digital images to obtain the necessary information.

[0994] The "means for converting into text data" refers to a means having a function for converting information extracted from an image or sound into a character format.

[0995] The "means for acquiring voice data from the terminal" refers to a means having a function for recording the user's voice and collecting that data.

[0996] "Speech recognition technology" is a technology that analyzes acquired voice data and converts it into text data.

[0997] "Natural language processing technology" is a technology for analyzing text data and deciphering its meaning and structure.

[0998] The "means for detecting specific keywords or phrases" refers to a means having the function of identifying important words or phrases from the analyzed text data.

[0999] The "means for generating and displaying a warning message" refers to a means having a function for generating a message for notifying a user of a warning based on the detected content and displaying the message.

[1000] The "means for stopping the display of specific content and switching to safe content" refers to a means having a function for stopping the playback of problematic content and displaying safe content instead.

[1001] The "emotion recognition means" is a means having a function of analyzing the user's facial expression and tone of voice and identifying the user's emotional state.

[1002] The term "system" refers to the entire information processing device that operates by integrating these means and technologies.

[1003] This invention consists of a system based on software and a server implemented on a user's device. When a user views or interacts with content on the Internet, it can automatically detect conspiracy theory content, recognize the user's emotions, and take appropriate measures. This system is implemented using the following hardware and software:

[1004] Taking and processing screen captures

[1005] The device periodically (for example, every 5 seconds) takes a screen capture. The device takes a screen capture using a function called "GetScreenshot()" and sends the data to the server via an HTTP POST request.

[1006] Acquiring and processing audio capture

[1007] The device captures audio data in real time, divides it into a certain buffer size (for example, every second), and sends it to the server. The device collects audio data using a function called "CaptureAudio()" and sends this data to the server via an HTTP POST request.

[1008] Convert screen captures to text using OCR

[1009] The server converts the received screen capture image into text data using OCR technology called Tesseract. The server converts image data into text data using the function "TesseractOCR.Process(image)".

[1010] Converting voice data into text using voice recognition

[1011] The server converts the received voice data into text data using the Google Cloud Speech-to-Text API. The server converts the voice data into text data using the function "GoogleSpeechToTextAPI.convert(audio)".

[1012] Text data integration and analysis

[1013] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) techniques. This analysis is performed using libraries such as NLTK or SpaCy. The server uses the function "NLTK.Process(text)" to analyze the text data and detect conspiracy theory-related keywords.

[1014] Emotion Recognition in Action

[1015] If a specific keyword or phrase is detected, the server activates the emotion engine using OpenCV and the Microsoft Azure Emotion API. The server uses the functions "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)" to recognize emotions.

[1016] Generate and display warning messages

[1017] The server generates a warning message and sends it to the terminal, which then displays it to the user using the function "displayWarning(message)".

[1018] Stop showing content and switch to safe content

[1019] After the warning message is displayed, the device stops playing the current content using the function "StopCurrentContent()" and plays safe content using the function "PlaySafeContent()".

[1020] Specific examples

[1021] For example, if an elderly person is watching a video on the Internet at home, the device will take a screen capture every five seconds and send the data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[1022] The server analyzes the received screen captures using Tesseract OCR and converts subtitles and on-screen comments in the video into text data. The audio data is converted into text information using the Google Cloud Speech-to-Text API. The text data is then merged and analyzed using NLTK or SpaCy.

[1023] For example, if conspiracy-related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an OpenCV-based emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[1024] Based on the emotion recognition results, the server will raise a warning flag and generate a warning message, which will be sent to the device and displayed on the user's screen, stating "This content may be a conspiracy theory." At the same time, the current content will stop playing and automatically switch to safe content.

[1025] Example prompts for generative AI models

[1026] "Please explain the program's procedures for identifying content that contains conspiracy theories and issuing warnings to users."

[1027] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1028] Step 1:

[1029] The device takes a screen capture at regular intervals (for example, every 5 seconds). The content displayed on the device's display is taken as input, and its image data is generated as output. Specifically, the "GetScreenshot()" function is used to take a screen capture, and the data is sent to the server via an HTTP POST request.

[1030] Step 2:

[1031] The device captures audio data in real time. As input, it receives audio data acquired through the device's microphone, divides the audio data into a certain buffer size (for example, every second), and sends the data to the server as output. Specifically, it uses the "CaptureAudio()" function to collect audio data and sends it to the server via an HTTP POST request.

[1032] Step 3:

[1033] The server converts the received screen capture image into text data using OCR technology. It receives the screen capture image as input, processes the image, and obtains text data as output. Specifically, it uses the "TesseractOCR.Process(image)" function to convert image data into text data.

[1034] Step 4:

[1035] The server converts the received voice data into text data using speech recognition technology. It receives voice data as input, performs speech recognition, and obtains text data as output. Specifically, it uses the "GoogleSpeechToTextAPI.convert(audio)" function to convert voice data into text data.

[1036] Step 5:

[1037] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. It integrates the text data as input, performs NLP analysis on it, and obtains data containing specific keywords and phrases as output. Specifically, it uses the "NLTK.Process(text)" function to analyze the text data and detect conspiracy theory-related keywords.

[1038] Step 6:

[1039] When a specific keyword or phrase is detected, the server analyzes the user's emotion using emotion recognition. It receives facial expressions and voice tone as input, analyzes the emotions, and obtains the user's emotional state as output. Specifically, it uses the "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)" functions to recognize emotions.

[1040] Step 7:

[1041] The server generates a warning message based on the emotion recognition results and sends it to the device. It receives the emotion recognition and keyword detection results as input, generates a warning message, and sends the warning message to the device as output. Specifically, it creates a warning message using the "GenerateWarningMessage(keywords, emotions)" function and sends it to the device via an HTTP POST request.

[1042] Step 8:

[1043] The device displays the received warning message to the user, stops playing the current content if necessary, and switches to safe content. It receives the warning message and current content information as input, and displays the warning message and starts playing safe content as output. Specifically, it displays the warning message using the "displayWarning(message)" function, stops the current content using the "StopCurrentContent()" function, and plays safe content using the "PlaySafeContent()" function.

[1044] (Application example 2)

[1045] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1046] Content provided on the Internet may contain conspiracy theories and misinformation, which poses a risk of causing anxiety and inappropriate influence to users, especially elderly people. There is a need for a system that can automatically detect such conspiracy theory content and ensure that users can view the content in a healthy and safe information environment. In addition, there is a need to develop a system that can provide greater safety and security by understanding the user's psychological state and responding appropriately.

[1047] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1048] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of specific content and switching to safe content, and means for analyzing content viewed by a user in real time, detecting conspiracy theory content, recognizing emotions, and taking appropriate measures based on the emotions. This enables automatic detection of conspiracy theory content and appropriate measures based on the user's emotional state.

[1049] "Screen" refers to the entire content displayed on a digital device's display.

[1050] "Means for periodic capture" refers to a device or process that has the function of capturing screen captures at regular time intervals.

[1051] "Image processing technology" refers to technology for extracting and analyzing specific information based on acquired image data.

[1052] "Means for converting into text data" refers to the function of extracting text information from image or audio data and converting it into text format using image processing technology, etc.

[1053] "Audio data" refers to sound information recorded or captured in real time by a digital device.

[1054] "Speech recognition technology" refers to the technology that analyzes voice data, extracts linguistic information from it, and converts it into text data.

[1055] "Natural language processing technology" refers to computational techniques for analyzing, understanding, and generating human language data.

[1056] "Keyword and phrase detection method" refers to a technique or process for identifying specific words or phrases in the analyzed text.

[1057] "Means for generating and displaying a warning message" refers to a function that generates a message to alert the user when a specific condition is met and displays the message on the user's device.

[1058] "Means to stop displaying content and switch to safe content" refers to a function that stops displaying inappropriate content and automatically switches to another safe content when inappropriate content is detected.

[1059] "Conspiracy theory content" refers to content that contains unproven theories or unfounded information.

[1060] "Emotion recognition" refers to technology that analyzes a user's facial expressions and tone of voice to identify the emotions they are feeling.

[1061] "Appropriate response based on the user's emotional state" refers to using emotion recognition technology to determine the user's psychological state and then taking appropriate action such as issuing a warning or changing the content.

[1062] "Real-time analysis" refers to processing acquired data immediately and outputting results quickly.

[1063] The following describes in detail the mode for carrying out the present invention. This system is mainly composed of a server and a terminal, and its purpose is to automatically detect conspiracy theories in the content viewed by users, analyze the users' emotions, and take appropriate measures.

[1064] First, the device has a function to periodically capture screens. This function allows the device to capture screens at regular intervals (for example, every 5 seconds) and send them to the server. The device also captures audio data in real time and periodically sends it to the server.

[1065] The server converts the received screen capture into text data using image processing technology (OCR: Optical Character Recognition). Similarly, it converts the received voice data into text data using voice recognition technology. This allows the server to obtain the character information on the screen and the voice information as text data.

[1066] The server then analyzes the converted text data using natural language processing (NLP) technology to detect specific keywords and phrases, such as "conspiracy," "secret organization," and "manipulation."

[1067] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotions, allowing the server to understand their emotional state.

[1068] If the user shows signs of anxiety or fear, the server will instantly generate a warning message and send it to the device, which will then display the message on the user's screen, stop the current content, and automatically switch to safe content, such as educational videos or news.

[1069] This system allows users to enjoy a healthy and safe information environment without being influenced by conspiracy theory content. Furthermore, emotion recognition enables more appropriate responses, ensuring the user's psychological safety.

[1070] As a concrete example, consider the case where a user is watching an internet video using smart glasses. The system analyzes the content the user is watching in real time to detect inappropriate content (e.g., conspiracy theories). Screen captures are taken every five seconds, and audio data is also captured in real time and sent to a server. If the analysis detects the keyword "manipulation" and the user shows an anxious expression, a warning appears on the smart glasses' display stating, "This content may be a conspiracy theory. It may be disturbing." The system then automatically switches to a safe news video.

[1071] Prompt Sentence Examples

[1072] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[1073] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[1074] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[1075] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[1076] 4. Recognize the user's emotional state by analyzing their facial expressions.

[1077] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[1078] Write a Python program to perform these steps.

[1079] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1080] Step 1:

[1081] The device takes a screen capture at regular intervals. The input is a real-time image of the screen, which is captured as image data. The output is the captured image data. Specifically, the device's built-in camera is used to save the contents of the screen as image data. This process is performed every 5 seconds, for example, and the captured image is used in the next step.

[1082] Step 2:

[1083] The device captures audio data in real time, divides it into a certain buffer size, and sends it to the server. The input is the audio signal obtained from the microphone. The output is the audio signal stored in the buffer as digital data. Specifically, the device's built-in microphone is used to record ambient audio, and the recorded audio data is buffered.

[1084] Step 3:

[1085] The server converts the screen capture received from the device into text data using image processing technology (OCR: Optical Character Recognition). The input is the image data of the screen capture, and the output is text data. Specifically, the OCR engine is used to extract characters from the image and obtain them as a string of characters.

[1086] Step 4:

[1087] The server converts the voice data received from the terminal into text data using voice recognition technology. The input is voice data, and the output is text data extracted from that voice. Specifically, the server uses a voice recognition engine to analyze the voice data and obtain its contents as a string of characters.

[1088] Step 5:

[1089] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) technology. The input is the integrated text data, and the output is the detection of conspiracy theory-related keywords and phrases. Specifically, the server uses a natural language processing engine to detect specific keywords (e.g., "conspiracy," "secret organization," and "manipulation") within the text data.

[1090] Step 6:

[1091] The server activates an emotion engine based on the keyword detection results. The input is data including the user's facial expressions and tone of voice, and the output is the user's emotional state. Specifically, it analyzes facial recognition camera and voice data to identify the emotion the user is expressing (e.g., anxiety, fear).

[1092] Step 7:

[1093] The server generates a warning message based on the emotion recognition results and keyword detection results and sends it to the device. The input is the emotional state and keyword detection results, and the output is a warning message. Specifically, it generates data to display a message on the device such as "This content may be a conspiracy theory."

[1094] Step 8:

[1095] The device displays the received warning message to the user, stops displaying the current content, and switches to safe content if necessary. The input is the warning message and instructions sent from the server, and the output is the warning message displayed on the user's display and the switching of the displayed content. Specifically, a warning message is displayed on the display, the current video playback is stopped, and educational content or news is played instead.

[1096] Prompt Sentence Examples

[1097] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[1098] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[1099] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[1100] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[1101] 4. Recognize the user's emotional state by analyzing their facial expressions.

[1102] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[1103] Write a Python program to perform these steps.

[1104] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1105] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1106] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1107] [Fourth embodiment]

[1108] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1109] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1110] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1111] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1112] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1113] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1114] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1115] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1116] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1117] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1118] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1119] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1120] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1121] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[1122] Basic system configuration

[1123] Taking and processing screen captures

[1124] The device periodically captures a screen capture, which contains the content displayed on the user's screen, especially when the user is using a video sharing service or social networking site. The captured screen capture is then sent to the server and processed in the next step.

[1125] Acquiring and processing audio capture

[1126] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[1127] Convert screen captures to text using OCR

[1128] The server converts the received screen capture image into text data using image processing technology (OCR), such as Tesseract OCR, which allows the server to obtain the text information on the screen.

[1129] Converting voice data into text using voice recognition

[1130] The server converts the received voice data into text data using speech recognition technology. For example, by using the Google Cloud Speech-to-Text API, it is possible to extract accurate text information from the voice.

[1131] Text data integration and analysis

[1132] The server integrates the text data obtained through OCR and speech recognition. It then analyzes this text data using natural language processing (NLP) techniques to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[1133] Generate and display warning messages

[1134] If certain keywords or phrases are detected, the server will flag a warning and generate a warning message that will be sent to the device and displayed to the user stating, "This content may be a conspiracy theory."

[1135] Stop showing content and switch to safe content

[1136] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, minimizing the impact of conspiracy theories on users.

[1137] Specific examples

[1138] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[1139] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[1140] If a certain number of conspiracy theory-related keywords (e.g., "conspiracy," "secret organization," "manipulation") are included, the server will raise a warning flag and generate a warning message, which will be sent to the user's device and displayed on the user's screen, saying, "This content may be a conspiracy theory."

[1141] Furthermore, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news. In this way, the system can provide a safe information environment for seniors without influencing them with conspiracy theory content.

[1142] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet.

[1143] The processing flow will be explained below.

[1144] Step 1: Take a screen capture

[1145] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[1146] The device will capture the current screen contents and save it as an image file.

[1147] The device sends the captured image to the server.

[1148] Step 2: Getting an Audio Capture

[1149] Set up a task for the device to capture audio in real time.

[1150] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[1151] The terminal transmits the buffered audio data to the server.

[1152] Step 3: OCR processing

[1153] The server analyzes the received screen capture image.

[1154] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[1155] The server temporarily stores the extracted text data.

[1156] Step 4: Speech Recognition Processing

[1157] The server analyzes the received audio data.

[1158] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[1159] The server temporarily stores the extracted text data.

[1160] Step 5: Integrating text data

[1161] The server integrates the text data obtained through OCR processing and speech recognition processing.

[1162] Step 6: Natural Language Processing Analysis

[1163] The server analyzes the integrated text data using natural language processing technology.

[1164] The server detects specific conspiracy theory-related keywords and phrases.

[1165] Step 7: Generate a warning message

[1166] The server will flag certain keywords or phrases as warnings if they are detected.

[1167] If the server detects a warning flag, it generates a warning message.

[1168] Step 8: Sending a warning message

[1169] Sends server-generated warning messages to the terminal.

[1170] Step 9: Displaying warning messages

[1171] The terminal displays a warning message on the user's screen.

[1172] Step 10: Pause and Switch Content

[1173] The device will stop playing the current content if necessary after displaying the warning message.

[1174] Your device will automatically switch to safe content.

[1175] Example 1

[1176] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1177] Internet content contains misinformation and conspiracy theories, which can have a negative impact on users, especially vulnerable groups such as the elderly. Conventional methods lack the means to automatically detect this harmful content, warn users, and take appropriate action.

[1178] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1179] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keyword or phrase is detected, and means for stopping the display of the specific content and switching to safe content, thereby making it possible to provide a safe and healthy digital environment for users without being influenced by harmful content.

[1180] "Screen" refers to the entire visual information displayed on a user's device.

[1181] "Means for periodic acquisition" refers to a function for automatically collecting screen and audio data at regular intervals.

[1182] "Image processing technology" refers to the general technology for analyzing acquired image data and converting it into text or other information.

[1183] "Means for converting into text data" refers to a function for converting visual information or audio information into text information using image processing technology or voice recognition technology.

[1184] "Audio data" refers to the audio information of the content that the user is viewing.

[1185] "Speech recognition technology" refers to technology for analyzing voice data and extracting text information from the voice.

[1186] "Natural language processing technology" refers to the general technology for analyzing text data and detecting specific keywords and phrases.

[1187] "Specific keywords and phrases" refer to words or short phrases designed to identify conspiracy theories and other harmful content.

[1188] "Means for generating and displaying a warning message" refers to a function for issuing a warning to a user when a specific keyword or phrase is detected.

[1189] "Means to stop displaying content and switch to safe content" refers to a function that stops playback of detected harmful content and automatically switches to another content that is determined to be safe.

[1190] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content, warns the user, and takes appropriate measures when the user views or interacts with content on the Internet.

[1191] System basic configuration and operation

[1192] Taking and processing screen captures

[1193] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. This capture contains everything displayed on the user's screen and is implemented using the Python Pillow library, among other things. The captured screen capture is sent to the server using an HTTP POST request.

[1194] Acquiring and processing audio capture

[1195] The device also captures the audio data of the video in real time, which is divided into buffers of a certain size, captured using the Python pyaudio library, and periodically sent to the server.

[1196] Processing on the server

[1197] When the server receives the screen capture image, it converts the image into text using Tesseract OCR. It also uses the Google Cloud Speech-to-Text API to recognize the audio data and convert it into text. This allows the image and audio information to be integrated into text data.

[1198] Text data integration and analysis

[1199] The server combines the text data obtained through OCR and speech recognition and performs natural language processing (NLP) using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[1200] Generate and display warning messages

[1201] If the server detects certain keywords or phrases, it generates a warning message that is sent to the device and displayed to the user, such as "This content may be a conspiracy theory."

[1202] Stop showing content and switch to safe content

[1203] After the warning message is displayed, the device will stop playing the current content and automatically switch to safe content, such as educational videos or news, using the YouTube API, for example.

[1204] Specific examples

[1205] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every five seconds and sends it to the server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server converts the received screen captures into text data using Tesseract OCR and converts the audio data into text information using the Google Cloud Speech-to-Text API. These text data are then combined and analyzed using natural language processing technology. If conspiracy theory-related keywords such as "conspiracy" or "secret organization" are detected, the server generates a warning message and sends it to the user's device. The user's device then stops playing the current content and automatically switches to safe content.

[1206] Prompt Sentence Examples

[1207] A user is watching a video titled "Conspiracy Theories" on YouTube. The system takes a screen capture and audio of this video and detects keywords related to conspiracy theories. Explain this process using Tesseract OCR and the Google Cloud Speech-to-Text API.

[1208] In this way, the present invention can provide a safe and healthy digital environment where users are not affected by harmful content.

[1209] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1210] Step 1:

[1211] The device takes a screen capture every 5 seconds while the user is using a video sharing service or social networking site. The input is the user's currently displayed screen image, and the output is the image data of that screen image. Specifically, the device sets a timer, takes a screenshot using the Python Pillow library, and saves it to a local temporary file.

[1212] Step 2:

[1213] The device captures the audio data of the video being played in real time. The input is the audio of the content the user is watching, and the output is a fixed-size buffer of audio data. Specifically, the device uses the Python pyaudio library to acquire audio from the system's audio output, split it into fixed-size buffers, and saves it.

[1214] Step 3:

[1215] The device sends screen captures taken every 5 seconds and real-time buffered audio data to the server using an HTTP POST request. The input is the screen capture image and audio data buffer, and the output is the data sent to the server.

[1216] Step 4:

[1217] The server receives the received screen capture image data and converts it into text data using Tesseract OCR. The input is the screen capture image and the output is text data. Specifically, the server saves the received image data to a temporary file and calls Tesseract OCR to extract text from the image.

[1218] Step 5:

[1219] The server converts the received audio data into text data using the Google Cloud Speech-to-Text API. The input is a buffer of audio data, and the output is text data. Specifically, the server saves the audio data in a temporary file and calls the Google Cloud Speech-to-Text API to extract text information from the audio.

[1220] Step 6:

[1221] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. The input is the OCR text data and speech recognition text data, and the output is the analysis results. Specifically, the server analyzes the integrated text data using Python's NLTK and spaCy libraries to detect conspiracy theory-related keywords and phrases.

[1222] Step 7:

[1223] If the server detects a specific keyword or phrase, it generates a warning message and sends it to the terminal. The input is the analysis result, and the output is the generated warning message. Specifically, the server sets a warning flag based on the keyword detection result, generates a warning message from a template, and sends it to the terminal.

[1224] Step 8:

[1225] The device displays the received warning message, stops the display of the content being played, and switches to safe content. The input is the warning message, and the output is the content that was stopped and the switched-to safe content. Specifically, the device sends an API request to stop the content being played, and then sends a new playback request specifying the URL of the safe content.

[1226] (Application example 1)

[1227] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1228] In recent years, while a great deal of information is easily accessible through the internet, conspiracy theories and inaccurate information are also easily spread. Such information can have a particularly negative impact on the elderly and those with low internet literacy. This increases the risk that users will be unintentionally exposed to conspiracy theories. Therefore, it is necessary to develop a system that can detect conspiracy theory content in real time and issue warnings to users.

[1229] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1230] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when the specific keywords or phrases are detected, means for stopping the display of the specific content and switching to safe content, and means for warning the user when conspiracy theory-related keywords are detected, stopping related content as necessary, and automatically switching to safe content. This reduces the risk of users being exposed to conspiracy theory content and makes it possible to provide a safe and healthy digital environment.

[1231] "Screen" refers to the content of the display on which the video or image being viewed by the user on the device is displayed.

[1232] "Periodic acquisition" means collecting specific information at regular time intervals.

[1233] "Image processing technology" is a general term for technology that analyzes and edits digital images, and specifically includes OCR (Optical Character Recognition).

[1234] "Text data" refers to data that represents character information in a digital format.

[1235] "Terminal" is a general term for electronic devices used by users, including smartphones and personal computers.

[1236] "Audio data" refers to data that records audio in digital format.

[1237] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[1238] "Natural language processing technology" is a general term for technology that uses computers to analyze, understand, and generate human language.

[1239] "Analysis" is the process of examining data in detail and extracting specific patterns and important information.

[1240] "Keywords" are important words that are set to find specific information.

[1241] A "phrase" is a combination of words that has a particular meaning.

[1242] A "warning message" is a notification displayed to alert the user.

[1243] "Stop display" means stopping the playback of the content currently being viewed.

[1244] "Safe content" is content that comes from reliable sources and does not contain conspiracy theories or harmful information.

[1245] "User" means a person who uses a system or device to view content.

[1246] "Switching automatically" means that the system autonomously transitions to the next operation without human intervention.

[1247] An embodiment of the present invention provides a system that automatically detects conspiracy theory content and takes appropriate warnings and countermeasures when a user views or interacts with content on the Internet.

[1248] 1. Hardware and Software Used

[1249] Hardware: This system uses the user's device (smartphone, PC, tablet, etc.) and a server.

[1250] Software: Use Tesseract OCR, Google Cloud Speech-to-Text API, and natural language processing libraries (e.g., NLTK and spaCy).

[1251] 2. Program Processing Overview

[1252] Taking and sending screen captures

[1253] The user's device takes a screen capture every five seconds and sends this image data to the server, which collects images of the content the user is viewing.

[1254] Acquiring and sending audio data

[1255] Similarly, the device captures audio data in real time, divides it into a certain buffer size, and transmits it to the server, thereby collecting audio information about the content being viewed.

[1256] Converting image data into text using OCR

[1257] The server converts the received screen capture into text data using Tesseract OCR, which extracts the text information on the screen as text.

[1258] Converting audio data to text

[1259] The server uses the Google Cloud Speech-to-Text API to convert the transmitted voice data into text data, extracting accurate text information from the voice.

[1260] Text data integration and analysis

[1261] The server integrates the text data extracted by OCR and speech recognition and uses natural language processing techniques (e.g., NLTK, spaCy) to detect conspiracy theory-related keywords and phrases. During this process, it analyzes whether the data contains words or phrases related to conspiracy theories.

[1262] Generate and display warning messages

[1263] If certain keywords or phrases are detected, the server generates a warning message and sends it to the user's device, which displays the message, "This content may be a conspiracy theory."

[1264] Stop showing content and switch to safe content

[1265] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content if necessary, protecting users from conspiracy theory content and providing safe information.

[1266] Specific examples

[1267] For example, if an elderly person is watching a video sharing service at home, a screen capture is taken every five seconds and the image data is sent to a server. At the same time, audio data from the video being played is also captured in real time and sent to the server. The server then analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. The audio data is then converted into text information using speech recognition technology. This text data is then integrated, and conspiracy theory-related keywords and phrases are detected using natural language processing technology. For example, if the keyword "secret organization" is detected, the server generates a warning message and sends it to the user's device. A warning message appears on the user's screen stating, "This content may be a conspiracy theory." Furthermore, if necessary, the device will stop playing the current content and automatically switch to safe content.

[1268] Example prompt sentence:

[1269] "This video contains the words 'secret organization.' This content may be a conspiracy theory."

[1270] This system will enable users to enjoy a healthier digital environment, free from the influence of conspiracy theories.

[1271] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1272] Step 1:

[1273] The device takes a screen capture every 5 seconds and saves it as image data. The input of the screen capture is the screen of the user's device, and the output is image data (e.g., a PNG file). Specifically, the device's screen capture function is used to capture a still image of the entire screen.

[1274] Step 2:

[1275] The terminal transmits the acquired screen capture to the server. The input is the image data of the screen capture, and the output is the image data transmitted to the server. Specifically, the terminal uploads the screen capture to the server using network communication.

[1276] Step 3:

[1277] The device buffers audio data in real time and transmits it to the server at regular intervals. The input is audio data captured by the device's microphone, and the output is audio data transmitted to the server. Specifically, the system captures audio from the device's microphone, stores it in a buffer, and then uploads it to the server.

[1278] Step 4:

[1279] The server converts the received screen capture into text data using image processing technology (Tesseract OCR). The input is the image data of the screen capture, and the output is the text data extracted from the image. Specifically, it starts Tesseract OCR, analyzes the screen capture, and generates text data.

[1280] Step 5:

[1281] The server converts the received voice data into text data using speech recognition technology (Google Cloud Speech-to-Text API). The input is voice data, and the output is text data extracted from the voice. Specifically, it calls the Google Cloud Speech-to-Text API to convert the voice data into text.

[1282] Step 6:

[1283] The server integrates the text data generated by OCR and speech recognition and analyzes it using natural language processing technology (e.g., NLTK or spaCy). The input is each piece of text data, and the output is the analysis result, which is the detection information for specific keywords and phrases. Specifically, the integrated text data is input into an NLP library to detect conspiracy theory-related keywords and phrases.

[1284] Step 7:

[1285] The server generates a warning message when a specific keyword or phrase is detected and sends it to the user's device. The input is the analysis result (detection information for a specific keyword or phrase), and the output is the generation and transmission of a warning message. Specifically, the server generates a warning message and notifies the user's device via the network.

[1286] Step 8:

[1287] The user device receives the warning message and displays a message on the screen saying, "This content may be a conspiracy theory." At the same time, it stops displaying the current content and automatically switches to safe content. The input is the warning message from the server, and the output is the display of the warning message and the switching of content. Specifically, it displays a pop-up warning message, stops the content being viewed, and starts playing another safe content.

[1288] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1289] This invention consists of a system based on software and a server that is implemented on a user's device, which automatically detects conspiracy theory content when the user is viewing or interacting with content on the Internet, recognizes the user's emotions, and takes appropriate measures.

[1290] Basic system configuration

[1291] Taking and processing screen captures

[1292] The terminal periodically takes a screen capture, which contains the content displayed on the user's screen, and sends the captured screen capture to the server for further processing.

[1293] Acquiring and processing audio capture

[1294] The device also captures audio data in real time, which is divided into buffers of a certain size and periodically sent to the server.

[1295] Convert screen captures to text using OCR

[1296] The server converts the received screen capture image into text data using image processing technology (OCR), allowing the character information on the screen to be obtained.

[1297] Converting voice data into text using voice recognition

[1298] The server converts the received voice data into text data using voice recognition technology, allowing accurate extraction of text information from the voice.

[1299] Text data integration and analysis

[1300] The server integrates the text data obtained through OCR and speech recognition, then analyzes the text data using natural language processing (NLP) to detect conspiracy theory-related keywords and phrases. The keyword list includes commonly used conspiracy theory-related items.

[1301] Emotion Recognition in Action

[1302] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which will recognize the user's emotions by analyzing their facial expressions and tone of voice, thereby understanding their emotional state.

[1303] Generate and display warning messages

[1304] Based on the results of keyword detection and emotion recognition, the server generates a warning message, which is sent to the device and displayed to the user, stating, "This content may be a conspiracy theory."

[1305] Stop showing content and switch to safe content

[1306] After the warning message is displayed, the device will stop displaying the current content and automatically switch to safe content, such as educational videos or news, if necessary.

[1307] Specific examples

[1308] For example, consider an elderly person watching YouTube at home. The device takes a screen capture every 5 seconds and sends the image data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[1309] The server analyzes the received screen capture using OCR technology and converts subtitles and on-screen comments into text data. Audio data is converted into text information using speech recognition technology. This text data is then integrated and analyzed using natural language processing technology.

[1310] For example, if conspiracy-theory related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[1311] Based on the emotion recognition results, the server raises a warning flag and generates a warning message. This message is sent to the device and displayed on the user's screen, stating, "This content may be a conspiracy theory." At the same time, playback of the current content is stopped and automatically switched to safe content. In this way, the system can provide a safe information environment for seniors without exposing them to conspiracy theory content.

[1312] This invention is extremely effective in providing a safe and healthy digital environment without being influenced by conspiracy theory information on the Internet. Furthermore, by adding emotion recognition, appropriate measures can be taken depending on the user's psychological state, ensuring further safety.

[1313] The processing flow will be explained below.

[1314] Step 1: Take a screen capture

[1315] Set up a task that causes the device to take a screen capture at regular intervals (for example, every 5 seconds).

[1316] The device will capture the current screen contents and save it as an image file.

[1317] The device sends the captured image to the server.

[1318] Step 2: Getting an Audio Capture

[1319] Set up a task for the device to capture audio in real time.

[1320] The terminal buffers the audio data with a fixed buffer size (for example, 5 seconds).

[1321] The terminal transmits the buffered audio data to the server.

[1322] Step 3: Convert screen capture to text using OCR

[1323] The server analyzes the received screen capture image.

[1324] The server extracts text from the image using image processing techniques (e.g., Tesseract OCR).

[1325] The server temporarily stores the extracted text data.

[1326] Step 4: Converting voice data into text using voice recognition

[1327] The server analyzes the received audio data.

[1328] The server extracts text from the audio using speech recognition technology (e.g., Google Cloud Speech-to-Text API).

[1329] The server temporarily stores the extracted text data.

[1330] Step 5: Integrating text data

[1331] The server integrates the text data obtained through OCR processing and speech recognition processing.

[1332] Step 6: Natural Language Processing Analysis

[1333] The server analyzes the integrated text data using natural language processing technology.

[1334] The server detects specific conspiracy theory-related keywords and phrases.

[1335] Step 7: Activate the Emotion Engine

[1336] The server activates the emotion engine when certain keywords or phrases are detected.

[1337] The server analyzes the user's facial expressions and tone of voice to recognize their emotions.

[1338] Step 8: Generate a warning message

[1339] If the server detects that the user's emotions indicate anxiety or fear based on the emotion recognition results, it sets a warning flag.

[1340] If the server detects a warning flag, it generates a warning message.

[1341] Step 9: Sending a warning message

[1342] Sends server-generated warning messages to the terminal.

[1343] Step 10: Displaying warning messages

[1344] The terminal displays a warning message on the user's screen.

[1345] Step 11: Pause and Switch Content

[1346] The device will stop playing the current content after displaying the warning message.

[1347] Your device will automatically switch to safe content.

[1348] Example 2

[1349] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1350] As the amount of information on the Internet explodes, the risk of conspiracy theories and false information becoming increasingly influential is increasing. To address this issue, it is important to not only automatically analyze the content users view and detect problematic information, but also to monitor their emotional state. However, current safety measures lack systems that integrate content analysis and emotion recognition, making it difficult to quickly implement appropriate countermeasures. Furthermore, there are limited means to display appropriate warnings to users and smoothly switch them to safe content.

[1351] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1352] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of the specific content and switching to safe content, and emotion recognition means for analyzing the user's emotions. This makes it possible to detect content containing conspiracy theories or false information in real time and quickly issue a warning to the user, as well as take appropriate measures taking the user's emotional state into consideration.

[1353] The "screen capture means" is a means having a function of periodically capturing the screen of the user's terminal.

[1354] "Image processing technology" is a technology for analyzing and converting digital images to obtain the necessary information.

[1355] The "means for converting into text data" refers to a means having a function for converting information extracted from an image or sound into a character format.

[1356] The "means for acquiring voice data from the terminal" refers to a means having a function for recording the user's voice and collecting that data.

[1357] "Speech recognition technology" is a technology that analyzes acquired voice data and converts it into text data.

[1358] "Natural language processing technology" is a technology for analyzing text data and deciphering its meaning and structure.

[1359] The "means for detecting specific keywords or phrases" refers to a means having the function of identifying important words or phrases from the analyzed text data.

[1360] The "means for generating and displaying a warning message" refers to a means having a function for generating a message for notifying a user of a warning based on the detected content and displaying the message.

[1361] The "means for stopping the display of specific content and switching to safe content" refers to a means having a function for stopping the playback of problematic content and displaying safe content instead.

[1362] The "emotion recognition means" is a means having a function of analyzing the user's facial expression and tone of voice and identifying the user's emotional state.

[1363] The term "system" refers to the entire information processing device that operates by integrating these means and technologies.

[1364] This invention consists of a system based on software and a server implemented on a user's device. When a user views or interacts with content on the Internet, it can automatically detect conspiracy theory content, recognize the user's emotions, and take appropriate measures. This system is implemented using the following hardware and software:

[1365] Taking and processing screen captures

[1366] The device periodically (for example, every 5 seconds) takes a screen capture. The device takes a screen capture using a function called "GetScreenshot()" and sends the data to the server via an HTTP POST request.

[1367] Acquiring and processing audio capture

[1368] The device captures audio data in real time, divides it into a certain buffer size (for example, every second), and sends it to the server. The device collects audio data using a function called "CaptureAudio()" and sends this data to the server via an HTTP POST request.

[1369] Convert screen captures to text using OCR

[1370] The server converts the received screen capture image into text data using OCR technology called Tesseract. The server converts image data into text data using the function "TesseractOCR.Process(image)".

[1371] Converting voice data into text using voice recognition

[1372] The server converts the received voice data into text data using the Google Cloud Speech-to-Text API. The server converts the voice data into text data using the function "GoogleSpeechToTextAPI.convert(audio)".

[1373] Text data integration and analysis

[1374] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) techniques. This analysis is performed using libraries such as NLTK or SpaCy. The server uses the function "NLTK.Process(text)" to analyze the text data and detect conspiracy theory-related keywords.

[1375] Emotion Recognition in Action

[1376] If a specific keyword or phrase is detected, the server activates the emotion engine using OpenCV and the Microsoft Azure Emotion API. The server uses the functions "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)" to recognize emotions.

[1377] Generate and display warning messages

[1378] The server generates a warning message and sends it to the terminal, which then displays it to the user using the function "displayWarning(message)".

[1379] Stop showing content and switch to safe content

[1380] After the warning message is displayed, the device stops playing the current content using the function "StopCurrentContent()" and plays safe content using the function "PlaySafeContent()".

[1381] Specific examples

[1382] For example, if an elderly person is watching a video on the Internet at home, the device will take a screen capture every five seconds and send the data to the server. At the same time, the audio data of the video being played is also captured in real time and sent to the server.

[1383] The server analyzes the received screen captures using Tesseract OCR and converts subtitles and on-screen comments in the video into text data. The audio data is converted into text information using the Google Cloud Speech-to-Text API. The text data is then merged and analyzed using NLTK or SpaCy.

[1384] For example, if conspiracy-related keywords such as "conspiracy," "secret organization," and "manipulation" are detected, the server activates an OpenCV-based emotion engine that analyzes the user's facial expressions and tone of voice to recognize emotional states such as anxiety or fear.

[1385] Based on the emotion recognition results, the server will raise a warning flag and generate a warning message, which will be sent to the device and displayed on the user's screen, stating "This content may be a conspiracy theory." At the same time, the current content will stop playing and automatically switch to safe content.

[1386] Example prompts for generative AI models

[1387] "Please explain the program's procedures for identifying content that contains conspiracy theories and issuing warnings to users."

[1388] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1389] Step 1:

[1390] The device takes a screen capture at regular intervals (for example, every 5 seconds). The content displayed on the device's display is taken as input, and its image data is generated as output. Specifically, the "GetScreenshot()" function is used to take a screen capture, and the data is sent to the server via an HTTP POST request.

[1391] Step 2:

[1392] The device captures audio data in real time. As input, it receives audio data acquired through the device's microphone, divides the audio data into a certain buffer size (for example, every second), and sends the data to the server as output. Specifically, it uses the "CaptureAudio()" function to collect audio data and sends it to the server via an HTTP POST request.

[1393] Step 3:

[1394] The server converts the received screen capture image into text data using OCR technology. It receives the screen capture image as input, processes the image, and obtains text data as output. Specifically, it uses the "TesseractOCR.Process(image)" function to convert image data into text data.

[1395] Step 4:

[1396] The server converts the received voice data into text data using speech recognition technology. It receives voice data as input, performs speech recognition, and obtains text data as output. Specifically, it uses the "GoogleSpeechToTextAPI.convert(audio)" function to convert voice data into text data.

[1397] Step 5:

[1398] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing technology. It integrates the text data as input, performs NLP analysis on it, and obtains data containing specific keywords and phrases as output. Specifically, it uses the "NLTK.Process(text)" function to analyze the text data and detect conspiracy theory-related keywords.

[1399] Step 6:

[1400] When a specific keyword or phrase is detected, the server analyzes the user's emotion using emotion recognition. It receives facial expressions and voice tone as input, analyzes the emotions, and obtains the user's emotional state as output. Specifically, it uses the "OpenCV.detectEmotion(face_image)" and "AzureEmotionAPI.analyze(voice_tone)" functions to recognize emotions.

[1401] Step 7:

[1402] The server generates a warning message based on the emotion recognition results and sends it to the device. It receives the emotion recognition and keyword detection results as input, generates a warning message, and sends the warning message to the device as output. Specifically, it creates a warning message using the "GenerateWarningMessage(keywords, emotions)" function and sends it to the device via an HTTP POST request.

[1403] Step 8:

[1404] The device displays the received warning message to the user, stops playing the current content if necessary, and switches to safe content. It receives the warning message and current content information as input, and displays the warning message and starts playing safe content as output. Specifically, it displays the warning message using the "displayWarning(message)" function, stops the current content using the "StopCurrentContent()" function, and plays safe content using the "PlaySafeContent()" function.

[1405] (Application example 2)

[1406] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1407] Content provided on the Internet may contain conspiracy theories and misinformation, which poses a risk of causing anxiety and inappropriate influence to users, especially elderly people. There is a need for a system that can automatically detect such conspiracy theory content and ensure that users can view the content in a healthy and safe information environment. In addition, there is a need to develop a system that can provide greater safety and security by understanding the user's psychological state and responding appropriately.

[1408] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1409] In this invention, the server includes means for periodically acquiring a screen image, means for converting the acquired screen image into text data using image processing technology, means for acquiring voice data from the terminal, means for converting the acquired voice data into text data using voice recognition technology, means for analyzing the converted text data using natural language processing technology to detect specific keywords or phrases, means for generating and displaying a warning message when a specific keyword or phrase is detected, means for canceling the display of specific content and switching to safe content, and means for analyzing content viewed by a user in real time, detecting conspiracy theory content, recognizing emotions, and taking appropriate measures based on the emotions. This enables automatic detection of conspiracy theory content and appropriate measures based on the user's emotional state.

[1410] "Screen" refers to the entire content displayed on a digital device's display.

[1411] "Means for periodic capture" refers to a device or process that has the function of capturing screen captures at regular time intervals.

[1412] "Image processing technology" refers to technology for extracting and analyzing specific information based on acquired image data.

[1413] "Means for converting into text data" refers to the function of extracting text information from image or audio data and converting it into text format using image processing technology, etc.

[1414] "Audio data" refers to sound information recorded or captured in real time by a digital device.

[1415] "Speech recognition technology" refers to the technology that analyzes voice data, extracts linguistic information from it, and converts it into text data.

[1416] "Natural language processing technology" refers to computational techniques for analyzing, understanding, and generating human language data.

[1417] "Keyword and phrase detection method" refers to a technique or process for identifying specific words or phrases in the analyzed text.

[1418] "Means for generating and displaying a warning message" refers to a function that generates a message to alert the user when a specific condition is met and displays the message on the user's device.

[1419] "Means to stop displaying content and switch to safe content" refers to a function that stops displaying inappropriate content and automatically switches to another safe content when inappropriate content is detected.

[1420] "Conspiracy theory content" refers to content that contains unproven theories or unfounded information.

[1421] "Emotion recognition" refers to technology that analyzes a user's facial expressions and tone of voice to identify the emotions they are feeling.

[1422] "Appropriate response based on the user's emotional state" refers to using emotion recognition technology to determine the user's psychological state and then taking appropriate action such as issuing a warning or changing the content.

[1423] "Real-time analysis" refers to processing acquired data immediately and outputting results quickly.

[1424] The following describes in detail the mode for carrying out the present invention. This system is mainly composed of a server and a terminal, and its purpose is to automatically detect conspiracy theories in the content viewed by users, analyze the users' emotions, and take appropriate measures.

[1425] First, the device has a function to periodically capture screens. This function allows the device to capture screens at regular intervals (for example, every 5 seconds) and send them to the server. The device also captures audio data in real time and periodically sends it to the server.

[1426] The server converts the received screen capture into text data using image processing technology (OCR: Optical Character Recognition). Similarly, it converts the received voice data into text data using voice recognition technology. This allows the server to obtain the character information on the screen and the voice information as text data.

[1427] The server then analyzes the converted text data using natural language processing (NLP) technology to detect specific keywords and phrases, such as "conspiracy," "secret organization," and "manipulation."

[1428] If a specific keyword or phrase is detected, the server will then activate an emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotions, allowing the server to understand their emotional state.

[1429] If the user shows signs of anxiety or fear, the server will instantly generate a warning message and send it to the device, which will then display the message on the user's screen, stop the current content, and automatically switch to safe content, such as educational videos or news.

[1430] This system allows users to enjoy a healthy and safe information environment without being influenced by conspiracy theory content. Furthermore, emotion recognition enables more appropriate responses, ensuring the user's psychological safety.

[1431] As a concrete example, consider the case where a user is watching an internet video using smart glasses. The system analyzes the content the user is watching in real time to detect inappropriate content (e.g., conspiracy theories). Screen captures are taken every five seconds, and audio data is also captured in real time and sent to a server. If the analysis detects the keyword "manipulation" and the user shows an anxious expression, a warning appears on the smart glasses' display stating, "This content may be a conspiracy theory. It may be disturbing." The system then automatically switches to a safe news video.

[1432] Prompt Sentence Examples

[1433] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[1434] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[1435] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[1436] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[1437] 4. Recognize the user's emotional state by analyzing their facial expressions.

[1438] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[1439] Write a Python program to perform these steps.

[1440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1441] Step 1:

[1442] The device takes a screen capture at regular intervals. The input is a real-time image of the screen, which is captured as image data. The output is the captured image data. Specifically, the device's built-in camera is used to save the contents of the screen as image data. This process is performed every 5 seconds, for example, and the captured image is used in the next step.

[1443] Step 2:

[1444] The device captures audio data in real time, divides it into a certain buffer size, and sends it to the server. The input is the audio signal obtained from the microphone. The output is the audio signal stored in the buffer as digital data. Specifically, the device's built-in microphone is used to record ambient audio, and the recorded audio data is buffered.

[1445] Step 3:

[1446] The server converts the screen capture received from the device into text data using image processing technology (OCR: Optical Character Recognition). The input is the image data of the screen capture, and the output is text data. Specifically, the OCR engine is used to extract characters from the image and obtain them as a string of characters.

[1447] Step 4:

[1448] The server converts the voice data received from the terminal into text data using voice recognition technology. The input is voice data, and the output is text data extracted from that voice. Specifically, the server uses a voice recognition engine to analyze the voice data and obtain its contents as a string of characters.

[1449] Step 5:

[1450] The server integrates the text data obtained through OCR and speech recognition and analyzes it using natural language processing (NLP) technology. The input is the integrated text data, and the output is the detection of conspiracy theory-related keywords and phrases. Specifically, the server uses a natural language processing engine to detect specific keywords (e.g., "conspiracy," "secret organization," and "manipulation") within the text data.

[1451] Step 6:

[1452] The server activates an emotion engine based on the keyword detection results. The input is data including the user's facial expressions and tone of voice, and the output is the user's emotional state. Specifically, it analyzes facial recognition camera and voice data to identify the emotion the user is expressing (e.g., anxiety, fear).

[1453] Step 7:

[1454] The server generates a warning message based on the emotion recognition results and keyword detection results and sends it to the device. The input is the emotional state and keyword detection results, and the output is a warning message. Specifically, it generates data to display a message on the device such as "This content may be a conspiracy theory."

[1455] Step 8:

[1456] The device displays the received warning message to the user, stops displaying the current content, and switches to safe content if necessary. The input is the warning message and instructions sent from the server, and the output is the warning message displayed on the user's display and the switching of the displayed content. Specifically, a warning message is displayed on the display, the current video playback is stopped, and educational content or news is played instead.

[1457] Prompt Sentence Examples

[1458] We want to develop an application that detects inappropriate content (e.g., conspiracy theories) and displays a warning message when a user is watching online videos using smart glasses. To achieve this, we will implement a system that combines screen capture, speech recognition, natural language processing, and emotion recognition technologies. Specifically, we will perform the following steps:

[1459] 1. Take screen captures at regular intervals and convert them into text data using OCR.

[1460] 2. Capture voice data in real time and convert it into text data using voice recognition technology.

[1461] 3. Text data is integrated and conspiracy theory-related keywords are detected using natural language processing technology.

[1462] 4. Recognize the user's emotional state by analyzing their facial expressions.

[1463] 5. If inappropriate content is detected, display a warning message and automatically switch to safe content.

[1464] Write a Python program to perform these steps.

[1465] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1466] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1467] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1468] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1469] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1470] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1471] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1472] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1473] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1474] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1475] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1476] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1477] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1478] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1479] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1480] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1481] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1482] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1483] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1484] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1485] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1486] The following is further disclosed regarding the above embodiment.

[1487] (Claim 1)

[1488] a means for periodically capturing the screen image;

[1489] A means for converting the acquired screen image into text data using image processing technology;

[1490] A means for acquiring audio data from the terminal;

[1491] A means for converting the acquired voice data into text data using voice recognition technology;

[1492] A means for analyzing the converted text data using natural language processing technology to detect specific keywords and phrases;

[1493] means for generating and displaying a warning message when a particular keyword or phrase is detected;

[1494] A means to stop viewing certain content and switch to safe content;

[1495] A system including:

[1496] (Claim 2)

[1497] 2. The system according to claim 1, wherein the means for periodically capturing a screen capture captures a screen image every five seconds and transmits the screen image to a server.

[1498] (Claim 3)

[1499] 2. The system according to claim 1, wherein the means for acquiring the audio data buffers the audio data in real time and periodically transmits the audio data to a server.

[1500] "Example 1"

[1501] (Claim 1)

[1502] a means for periodically capturing the screen image;

[1503] A means for converting the acquired screen image into text data using image processing technology;

[1504] A means for acquiring audio data from the terminal;

[1505] A means for converting the acquired voice data into text data using voice recognition technology;

[1506] A means for analyzing the converted text data using natural language processing technology to detect specific keywords and phrases;

[1507] means for generating and displaying a warning message when a particular keyword or phrase is detected;

[1508] A means to stop viewing certain content and switch to safe content;

[1509] A system including:

[1510] (Claim 2)

[1511] 2. The system according to claim 1, wherein the means for periodically capturing a screen capture captures a screen image every five seconds and transmits the screen image to a server.

[1512] (Claim 3)

[1513] 2. The system according to claim 1, wherein the means for acquiring the audio data buffers the audio data in real time and periodically transmits the audio data to a server.

[1514] "Application Example 1"

[1515] (Claim 1)

[1516] a means for periodically capturing the screen image;

[1517] A means for converting the acquired screen image into text data using image processing technology;

[1518] A means for acquiring audio data from the terminal;

[1519] A means for converting the acquired voice data into text data using voice recognition technology;

[1520] A means for analyzing the converted text data using natural language processing technology to detect specific keywords and phrases;

[1521] means for generating and displaying a warning message when a particular keyword or phrase is detected;

[1522] A means to stop viewing certain content and switch to safe content;

[1523] A way to warn users when conspiracy theory-related keywords are detected, and if necessary, to stop related content and automatically switch to safe content;

[1524] A system including:

[1525] (Claim 2)

[1526] 2. The system according to claim 1, wherein the means for periodically capturing a screen capture captures a screen image every five seconds and transmits the screen image to a server.

[1527] (Claim 3)

[1528] 2. The system according to claim 1, wherein the means for acquiring the audio data buffers the audio data in real time and periodically transmits the audio data to a server.

[1529] "Example 2: Combining Emotion Engines"

[1530] (Claim 1)

[1531] a means for periodically capturing the screen image;

[1532] A means for converting the acquired screen image into text data using image processing technology;

[1533] A means for acquiring audio data from the terminal;

[1534] A means for converting the acquired voice data into text data using voice recognition technology;

[1535] A means for analyzing the converted text data using natural language processing technology to detect specific keywords and phrases;

[1536] means for generating and displaying a warning message when a particular keyword or phrase is detected;

[1537] A means to stop viewing certain content and switch to safe content;

[1538] emotion recognition means for analyzing the emotion of a user;

[1539] A system including:

[1540] (Claim 2)

[1541] 2. The system according to claim 1, wherein the means for periodically capturing a screen capture captures a screen image every five seconds and transmits the screen image to a server.

[1542] (Claim 3)

[1543] 2. The system according to claim 1, wherein the means for acquiring the audio data buffers the audio data in real time and periodically transmits the audio data to a server.

[1544] "Application example 2 when combining emotion engines"

[1545] (Claim 1)

[1546] a means for periodically capturing the screen image;

[1547] A means for converting the acquired screen image into text data using image processing technology;

[1548] A means for acquiring audio data from the terminal;

[1549] A means for converting the acquired voice data into text data using voice recognition technology;

[1550] A means for analyzing the converted text data using natural language processing technology to detect specific keywords and phrases;

[1551] means for generating and displaying a warning message when a particular keyword or phrase is detected;

[1552] A means to stop viewing certain content and switch to safe content;

[1553] A means for analyzing content viewed by users in real time, detecting conspiracy theory content, recognizing emotions, and taking appropriate action based on emotions;

[1554] A system including:

[1555] (Claim 2)

[1556] 2. The system according to claim 1, wherein the means for periodically capturing a screen capture captures a screen capture every 5 seconds and transmits the screen capture to the server.

[1557] (Claim 3)

[1558] 2. The system according to claim 1, wherein the means for acquiring the audio data buffers the audio data in real time and periodically transmits the audio data to the server. [Explanation of symbols]

[1559] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for periodically capturing the screen image; A means for converting the acquired screen image into text data using image processing technology; A means for acquiring audio data from the terminal; A means for converting the acquired voice data into text data using voice recognition technology; A means for analyzing the converted text data using natural language processing technology to detect specific keywords and phrases; means for generating and displaying a warning message when a particular keyword or phrase is detected; A means to stop viewing certain content and switch to safe content; A system including:

2. 2. The system according to claim 1, wherein the means for periodically capturing a screen capture captures a screen image every five seconds and transmits the captured image to a server.

3. 2. The system according to claim 1, wherein the means for acquiring the audio data buffers the audio data in real time and periodically transmits the audio data to a server.

Images