system

Abstract

We provide the system. [Solution] A means of analyzing text data received from users to detect personal and confidential information, Means for masking or encrypting detected information, A means for sending the generated masked or encrypted data to an external generation AI, A means of receiving the processing results from the generating AI and decrypting the original information, A means of presenting the decrypted result to the user, An information processing system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] When using generative AI, it is an issue to ensure the security of personal information and confidential information. In particular, the information input as text data often contains personal names and other confidential information, and it is required to safely input them into generative AI and receive the processing results. However, directly inputting such information raises significant security concerns, and appropriate masking and encryption are required. Furthermore, it is also important to establish a method to improve the accuracy of masking and encryption and not interfere with the processing by generative AI.

Means for Solving the Problems

[0005] This invention provides a system that analyzes text data entered by a user and provides a means for detecting personal and confidential information. The detected information is masked or encrypted using locally running artificial intelligence. This enables secure data transmission to a generating AI. Subsequently, the system includes a means for receiving the processing results returned from the generating AI and decrypting the original data. In this system, the transmission and reception of data to and from the generating AI are performed over an encrypted communication channel, further enhancing the security of the information. In this way, it becomes possible to utilize a generating AI while securely processing the user's information.

[0006] A "user" refers to an entity that uses a system to input text data and perform information processing.

[0007] "Text data" refers to document information that is entered by users and may contain personal or confidential information.

[0008] "Personal information" refers to information used to identify a specific individual, including names and telephone numbers.

[0009] "Confidential information" refers to information that should only be known to a limited number of people within a company or organization, and includes data related to business details and plans.

[0010] "Masking" refers to the process of hiding or altering certain information for the purpose of maintaining confidentiality.

[0011] "Encryption" refers to the process of transforming information based on a specific algorithm into a format that is incomprehensible to third parties.

[0012] "Generative AI" refers to artificial intelligence that processes text data based on user instructions and generates summaries, translations, and other output.

[0013] "Decryption" refers to the process of restoring encrypted information to its original form so that it can be understood by humans.

[0014] A "communication channel" refers to the network path or method used to send and receive data, and its security is ensured by encryption.

[0015] "Locally running artificial intelligence" refers to AI programs that run on a user's device or within a limited area, particularly those that perform masking and encryption. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the language used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This information processing system is designed to securely process text data provided by users. The system is configured as follows:

[0038] First, the user inputs text data into the device. This data may contain personal or confidential information. The device uses natural language processing techniques to analyze the input text data and detect personal and confidential information within it. This could involve using regular expressions or morphological analysis.

[0039] The detected information is masked or encrypted by an artificial intelligence (AI) dedicated to encryption / masking that operates within the device. This AI identifies specific patterns and temporarily hides the information based on them. The masked data is then formatted as a prompt sent to a generating AI.

[0040] Next, the server sends this masked prompt to the generating AI. The generating AI performs the necessary tasks based on the received prompt, such as summarizing data or grammatical checking of text. The processing results are returned to the terminal via the server.

[0041] When the device receives the results of the AI ​​generation from the server, it decrypts them again using a dedicated encryption / masking AI. This restores the masked information to its original form, which is then displayed to the user as the final result.

[0042] As a concrete example, if a user enters meeting minutes, the system masks the names of participants and project names within them. Once the summary generated by the AI ​​is returned, it is decoded back into the original meeting minutes format and provided to the user. This process ensures information security while allowing users to enjoy the convenience of the AI-generated format.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user enters text data into the device. This text data may contain personal or confidential information.

[0046] Step 2:

[0047] The terminal receives input text data and uses natural language processing techniques to detect personal and confidential information. This involves using regular expressions to identify phone numbers and IDs, and morphological analysis to extract names of people and organizations.

[0048] Step 3:

[0049] The device uses locally running artificial intelligence to mask or encrypt any personal and confidential information it detects. Specifically, it replaces confidential portions with symbols such as "".

[0050] Step 4:

[0051] The device formats the encrypted data and prepares it as a prompt for the generating AI. The prompt is formatted to efficiently perform the target task.

[0052] Step 5:

[0053] The server receives prompts sent from the terminal and passes them to the generating AI. The data is transmitted through a secure communication channel.

[0054] Step 6:

[0055] The server receives the processing results from the generating AI and transfers them to the terminal. The generating AI provides the results of tasks such as summarization and text proofreading.

[0056] Step 7:

[0057] The terminal receives the results from the server and decrypts the original information. A dedicated encryption / masking AI handles this task, restoring the data to a state where its original meaning is understandable.

[0058] Step 8:

[0059] The device displays the decryption results to the user. The user can then decide on their next action based on the final result.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] In information processing systems, there is a need to guarantee the security of identifying and confidential information contained in text data provided by users, while mitigating the risk of information leakage when processing data with external generative AI models. Furthermore, in order to efficiently perform data analysis and text generation using external generative AI models, means of ensuring the secure transmission and reception of data are also necessary.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for analyzing character data received from a user and detecting identification information and confidential information, means for concealing or encrypting the detected information, and means for transmitting the generated concealed or encrypted data to an external generative AI model. This enables data processing that effectively utilizes an external generative AI model while ensuring data security.

[0065] A "user" is an entity that provides text data to a system and receives the processing results.

[0066] "Text data" refers to information in text format that users input into the system.

[0067] "Analysis" refers to the process used to examine textual data and identify specific information.

[0068] "Identification information" refers to information that identifies an individual or information that has a specific level of confidentiality.

[0069] "Confidential information" refers to highly sensitive information that, if made public, could result in negative consequences.

[0070] "Detection" refers to the act of confirming and identifying identifying or confidential information within text data.

[0071] "Hiding" refers to the process of converting the original information into an invisible form in order to temporarily hide the data.

[0072] "Encryption" refers to the technique of converting information into a format that cannot be read in order to protect it using a specific algorithm.

[0073] A "generative AI model" refers to artificial intelligence that generates text or performs data analysis based on input prompts.

[0074] "Communication methods" refer to methods and technologies for sending and receiving data, and include those specifically intended to ensure security.

[0075] To implement this invention, the information processing system mainly consists of a server, a terminal, and a generative AI model.

[0076] Users can input text-based character data using a terminal. The terminal has a natural language processing library (e.g., spaCy or NLTK) implemented, which is used to analyze the input character data. This analysis makes it possible to detect identifying and confidential information. Regular expressions and morphological analysis are used for this purpose.

[0077] The device has a locally running computational model to hide or encrypt detected identification and secret information. This computational model identifies specific patterns and replaces the information with placeholders to temporarily conceal it.

[0078] The masked data is prepared as a formatted prompt. This formatted prompt is sent to the generative AI model, which then performs the necessary tasks (e.g., data summarization and grammar checking).

[0079] The processing results from the generated AI model are returned to the terminal via the server. The terminal then decodes these results again using the computational model and presents the original information to the user. This allows the user to receive the final, securely processed result.

[0080] For example, if a user enters meeting minutes, this system masks the names of participants and project names within the minutes. After this process is complete, the AI-generated summary can be decoded back into its original format and provided to the user.

[0081] An example of a prompt might be, "Please summarize the meeting content. Please omit participant names and project names." This prompt is then used as input to the generating AI model, which performs the appropriate processing.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The user inputs text data into the terminal. For example, the user might enter meeting minutes or the body of an email into a text box. This entered text data becomes the initial data for the system to process.

[0085] Step 2:

[0086] The terminal analyzes the input character data using a natural language processing library (e.g., spaCy or NLTK). The input for analysis is the user's text data, and the output is a list of identification and secret information. This process uses regular expressions for pattern matching and morphological analysis to identify names, addresses, and other sensitive information.

[0087] Step 3:

[0088] The device hides or encrypts the detected identification and confidential information. The input is a list of information detected in step 2, which is then replaced with placeholders (e.g., "NAME" or "PROJECT") by a computational model. The output is masked character data, thus protecting the user's personal information.

[0089] Step 4:

[0090] The terminal formats the masked data into a prompt message. Formatting is performed by converting the data into a format that the generative AI model can process appropriately. The input is the masked data obtained in step 3, and the output is the formatted prompt message.

[0091] Step 5:

[0092] The server sends the formatted prompt to the generating AI model. To do this, it converts the prompt text into a format compatible with the generating AI model (e.g., an API request). The input is the prompt text formatted in step 4, and the output is the result of processing by the generating AI model.

[0093] Step 6:

[0094] The server receives the processing results from the generating AI model and sends those results to the terminal. At this stage, the input is the output of the generating AI model, and the same content reaches the user's terminal as the output.

[0095] Step 7:

[0096] The terminal decodes the processing results of the generated AI model received from the server and replaces the placeholders with the original identification information. The input is the processing results from step 6 and the identification information obtained in step 2, and the output is the decoded final data. This is displayed to the user so that the user can refer to the information.

[0097] (Application Example 1)

[0098] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0099] The objective of this invention is to safely and efficiently process text data containing personal and confidential information, while presenting users with the information they need in real time. In particular, it is necessary to balance the protection of privacy and the speed of information processing when information is provided in real time through visual devices.

[0100] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0101] In this invention, the server includes means for analyzing text data received from a user to detect personal and confidential information, means for masking or encrypting the detected information, means for transmitting the generated masked or encrypted data to an external generating AI, and means for receiving the processing results from the generating AI and decrypting the original information. This enables the provision of accurate information in real time while protecting personal information.

[0102] A "user" is a person who provides text data using a specific information processing system and receives the results.

[0103] "Text data" refers to a collection of information entered as text, which may include personal or confidential information.

[0104] "Personal information" refers to information that can identify a specific individual, such as name and address.

[0105] "Confidential information" refers to information that is not publicly available and is important data for a particular organization or individual.

[0106] "Masking" is a technique used to conceal or hide personal or confidential information.

[0107] "Encryption" is a method of converting data from a decryptable format to an unreadable format to prevent unauthorized access by third parties.

[0108] "Generative AI" is an artificial intelligence technology that automatically generates text and information based on given input.

[0109] "Decryption" is the process of returning encrypted data to its original, decryptable format.

[0110] "Visual devices" are hardware that displays information visually, and include smart glasses, among other things.

[0111] "Real-time" means processing or providing information immediately, and presenting results to users without delay.

[0112] The system for carrying out this invention mainly consists of a server, a user terminal, and a visual device (e.g., smart glasses). A specific embodiment is described below.

[0113] First, the user inputs text data using a visual device. This text data is received by the user's terminal and analyzed using a natural language processing (NLP) library (e.g., spaCy, NLTK). This analysis activates an AI model (e.g., a custom model of OpenAI® GPT) to identify personal and confidential information and mask or encrypt it.

[0114] Next, the user terminal generates a prompt to send the masked data to the generative AI model. This communication takes place between the server and a cloud-based generative AI service (e.g., OpenAI GPT-3®, Google® AI API) using an encrypted channel. Based on the received prompt, the generative AI performs the specified information processing (e.g., summarization, grammar correction) and returns the result to the server.

[0115] The server sends the received processing results to the user's terminal and performs the demasking process again. The visual device displays the decoded results to the user in real time. This allows the user to immediately access the information in a privacy-protected manner.

[0116] As a concrete example, in a corporate business meeting, if a user is using smart glasses to view agenda materials, the key points will be displayed in a summarized form while protecting personal names and project names.

[0117] An example of a prompt message is, "Summarize the contents of this text and output it with confidential information masked." This system makes it possible to process and present important data quickly while maintaining information security.

[0118] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0119] Step 1:

[0120] The user inputs text data using a visual device. The user terminal receives this text data and records it as input data. This input data may contain personal or confidential information.

[0121] Step 2:

[0122] The terminal uses a natural language processing library (e.g., spaCy, NLTK) to parse the received text data. Morphological analysis and regular expressions are applied to the input text data to detect personal and sensitive information within the data. This analysis identifies data that needs to be masked or encrypted.

[0123] Step 3:

[0124] The device processes detected personal and confidential information using an AI model (e.g., a custom OpenAI GPT model) to mask or encrypt it. The input is the information identified through analysis, and the output is masked data. This masking process protects the data from unauthorized access by third parties.

[0125] Step 4:

[0126] The device generates a prompt for the generative AI from the masked data. In this process, it formats the prompt text and sends it to a cloud-based generative AI service using an encrypted communication channel. The input is masked data, and the output is the formatted prompt text.

[0127] Step 5:

[0128] The server receives the results processed by the generative AI in the cloud. These results include the output of the information processing performed by the generative AI based on the prompt. The input is the formatted prompt, and the output is the processed result.

[0129] Step 6:

[0130] The terminal decodes the processing results of the generating AI received from the server. Simultaneously, it removes the masking to reconstruct the original information. The input is the processing result of the generating AI, and the output is the decoded result.

[0131] Step 7:

[0132] A visual device displays the decoded results to the user in real time. The processed information is presented visually, allowing the user to view the necessary information. The input is the decoded result, and the output is the visually displayed information.

[0133] By ensuring that the data entered at each step is properly processed or calculated and prepared for the next step, users can receive the necessary information safely and quickly. This entire process enables real-time information delivery while maintaining the protection of personal information.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] This invention is an information processing system that securely processes text data entered by a user, recognizes the user's emotions within that data, and generates appropriate feedback. The system is configured as follows:

[0136] First, the user enters text data into the device. Because this data may contain personal or confidential information, the device uses natural language processing technology to detect it. The detected information is then masked or encrypted by a dedicated artificial intelligence operating within the device. This AI identifies the information and uses codes to protect the data.

[0137] Next, the device receives the masked text and uses its emotion engine to recognize the user's emotional state. This emotion engine analyzes the context and tone of the text to determine whether the user is happy, angry, or sad.

[0138] The terminal then formats the recognized emotion information and masked data, preparing it as a prompt for the generative AI. The server sends the formatted prompt to the generative AI. Based on the received prompt, the generative AI summarizes the data, generates a customized response based on emotion, or performs grammatical checks on the text.

[0139] The server receives the results from the generating AI and transfers them to the terminal. After receiving the results, the terminal uses a dedicated encryption / masking AI to decrypt the original information. Furthermore, the generated results are adjusted to the user's emotions and presented in the most appropriate format for the user.

[0140] For example, if a user enters a text message about stress, the system senses the user's stress level and instructs the AI ​​to summarize the message and generate appropriate advice. Finally, the device decodes the advice and provides the user with recommendations to help reduce stress. This allows for secure data processing and the provision of valuable information while considering the user's emotions.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The user enters text data into the device. For example, the user enters the sentence, "I've been feeling stressed out by my recent projects."

[0144] Step 2:

[0145] The terminal receives the entered text data and uses natural language processing technology to detect personal and confidential information within it. For example, it identifies the term "project."

[0146] Step 3:

[0147] The device uses locally running artificial intelligence to mask or encrypt any sensitive information it detects. This temporarily protects the data, for example, by replacing "project" with "".

[0148] Step 4:

[0149] The device passes encrypted text to an emotion engine, which analyzes the user's emotional state. In this case, the engine recognizes from the text that the user is experiencing stress.

[0150] Step 5:

[0151] The device combines emotional information with encrypted text and formats it as a prompt for the generating AI. This prompt may include the fact that the user is feeling stressed.

[0152] Step 6:

[0153] The server receives a prompt sent from the terminal and forwards it to the generating AI. This prompt includes instructions for generating a response that is tailored to the user's emotional state.

[0154] Step 7:

[0155] The generating AI processes prompts and produces output results tailored to the user's emotions, such as advice for stress relief.

[0156] Step 8:

[0157] The server receives the output from the generated AI and sends it back to the terminal.

[0158] Step 9:

[0159] The device decrypts the results received from the server back into the original data and then makes adjustments based on the user's emotional state. For example, it might be formatted to say, "You may be feeling stressed, but please try the following to relax."

[0160] Step 10:

[0161] The device presents the final results to the user and provides advice from the generated AI in a usable format. The user can then implement stress management strategies based on the information provided.

[0162] (Example 2)

[0163] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0164] In information processing systems, when text data entered by users contains personal or confidential information, it is necessary to securely protect that information while simultaneously accurately recognizing the user's emotions and providing appropriate feedback. However, conventional systems face the challenge of balancing information protection with accurate emotion recognition. Furthermore, advanced text processing using generative AI models requires a secure and efficient method of data transmission.

[0165] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0166] In this invention, the server includes means for analyzing textual information received from a user and detecting personally identifiable information and confidential information, means for masking or encrypting the detected information, and means for an engine for recognizing the emotional state based on the masked text. This makes it possible to provide feedback that corresponds to the user's emotional state while protecting personal information.

[0167] "Textual information" refers to data in text format entered by users, and is subject to natural language processing.

[0168] "Personally identifiable information" refers to information that can identify an individual user, including their name, address, and contact information.

[0169] "Confidential information" refers to information that is not publicly available and is considered highly sensitive data for a particular organization or individual.

[0170] "Masking" is a process that makes personally identifiable information or confidential information unidentifiable by replacing it with information based on certain rules.

[0171] "Encryption" is the process of transforming data using a specific algorithm to make it a format that cannot be easily understood by a third party.

[0172] "Emotional state" refers to the psychological state extracted from the text information entered by the user, and includes classifications such as positive, negative, and neutral.

[0173] A "generative model" refers to artificial intelligence technology that has the ability to generate natural language by learning from large amounts of data.

[0174] A "communication channel" is a transmission path used by the server and the generative model to send and receive data, and it must be encrypted to ensure security.

[0175] This invention is an information processing system that securely processes text information entered by a user, recognizes emotions within that information, and generates appropriate feedback. The system utilizes the following hardware and software.

[0176] The user inputs text information into the terminal. This terminal is equipped with a natural language processing engine and encryption technology. The natural language processing engine analyzes the text information entered by the user to identify personally identifiable and confidential information. Common programming languages ​​and libraries, such as Python and its natural language processing library, are used for the analysis. After detecting confidential information, a dedicated AI is used to mask or encrypt the data. This AI operates within the terminal and uses standard encryption techniques, such as AES encryption.

[0177] Next, the device uses an emotion engine to identify the user's emotional state from the masked text information. This process utilizes deep learning models, such as BERT or RoBERTa, to analyze emotions from the context and tone of the text. The extracted emotional information and masked data are then formatted as prompts and sent to a generative AI model. The server receives the prompts and communicates with the external generative AI in real time. A secure communication channel is established for this communication, using encryption protocols such as SSL / TLS.

[0178] The generative AI model performs various text processing tasks based on the received prompts. For example, it summarizes user input and generates emotionally appropriate advice and feedback. This generated information is returned to the device via the server, where it is decrypted again using encryption / masking AI. Finally, the results are adjusted to the user's emotions and displayed to the user in the most optimal form.

[0179] As a concrete example, consider a scenario where a user inputs, "I'm feeling stressed and depressed." The system analyzes this information and recognizes the negative emotion of stress. It then sends a prompt to a generative AI model regarding "specific ways to relax," generating appropriate advice. Finally, the device decodes this advice and provides feedback in a format easily understood by the user. This process allows users to receive support tailored to their individual needs.

[0180] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0181] Step 1:

[0182] The user inputs text information on the terminal. This text information is then analyzed by a natural language processing engine. Raw string data is used as input for the analysis. The engine tokenizes the input text, analyzes the sentence structure, and extracts personal identification information and sensitive information. As a result, the extracted sensitive information is output.

[0183] Step 2:

[0184] The device processes the personally identifiable and confidential information extracted in Step 1 using a dedicated AI, performing masking or encryption. The input consists of identified sensitive information, and an appropriate masking pattern or encryption algorithm (e.g., AES encryption) is applied according to the importance and type of the information. As a result, protected data is output.

[0185] Step 3:

[0186] The device processes masked text information using an emotion engine to analyze the user's emotional state. The input in this step is masked text information. A deep learning model (e.g., BERT) is used to extract context and emotional characteristics from individual words and their combinations. This analysis outputs specific emotional labels (e.g., positive, negative).

[0187] Step 4:

[0188] The device integrates the emotion information obtained in step 3 with the masked data to create a prompt message to send to the generative AI model. This creation process is performed by using the emotion labels and masked data as input and applying them to a prompt template. As a result, a prompt message in a format that the generative AI can understand is output.

[0189] Step 5:

[0190] The server sends a prompt to the generative AI model, which then processes it. The input is the prompt, and the AI ​​uses natural language generation techniques to analyze this information and generate summaries and feedback sentences. This results in optimized text data for the user.

[0191] Step 6:

[0192] The server sends the output from the generating AI back to the terminal. The terminal receives the data through a secure communication channel and performs the decryption process. The input here is encrypted response data, which is decrypted back into its original form by a dedicated decryption AI. As a result, the decrypted feedback information is output.

[0193] Step 7:

[0194] The device further refines the decoded feedback based on the emotions recognized in step 3 and presents it to the user. Decoded data and emotional information are used as input for customization to enrich the user experience. Ultimately, the user receives emotionally resonant, personalized feedback.

[0195] (Application Example 2)

[0196] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0197] In modern times, text data entered by users often contains confidential or personal information, and its secure handling is essential. Furthermore, accurately recognizing user emotions from their input and providing appropriate feedback has become a critical challenge for many communication applications and security services. This invention aims to solve these problems by providing a system that securely generates and presents emotion-responsive feedback while considering the user's feelings.

[0198] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0199] In this invention, the server includes means for analyzing text information obtained from a user and identifying personal and confidential information; means for masking or encrypting the identified information; means for analyzing the masked or encrypted text information and recognizing emotions; means for shaping the recognized emotion information and masked data and generating prompts to send to a generating AI; and means for receiving feedback from the generating AI, decrypting the original information, and presenting it in a form appropriate to the emotions. This enables the secure processing of user input data while providing effective feedback tailored to their emotions.

[0200] A "user" refers to an individual who uses the system to input text information.

[0201] "Text information" refers to text data entered by users, which may contain personal information or emotions.

[0202] "Personal information" refers to information that can be used to identify a user, and includes names, addresses, and contact information.

[0203] "Confidential information" refers to important information that should not be made public, and includes business secrets and sensitive data.

[0204] "Masking" is a technique used to conceal personal or confidential information within data, thereby obscuring the true nature of the information.

[0205] "Encryption" is a technology that transforms information to prevent it from being read illegally, and is used to securely store data.

[0206] "Emotions" refer to the psychological state expressed by the user, and include types such as joy, sadness, and anger.

[0207] A "prompt" refers to formatted text data used to give instructions to a generating AI.

[0208] "Generative AI" refers to an algorithm that automatically generates feedback and content based on input data.

[0209] "Feedback" refers to replies or responses provided to users based on their emotions.

[0210] "Decryption" refers to the process of restoring encrypted information to its original format, which is done so that users can understand the data.

[0211] The system for carrying out this invention is specifically configured as follows.

[0212] First, the system receives text information entered by the user using the terminal. Because this information may contain personal or confidential data, natural language processing (NLP) technology on the terminal is used to identify this information. Software used includes natural language processing libraries (e.g., spaCy, NLTK). The identified information is then masked or encrypted by a locally running AI. For encryption, a proprietary code is used to protect the data.

[0213] Next, sentiment analysis is performed on the encrypted text. The device uses a sentiment analysis library (e.g., TextBlob) to analyze the sentiment state of the input text. The analyzed sentiment information is used to generate prompts that are sent to the generative AI model.

[0214] The generated prompt is sent by the server to the generative AI model. Based on the given prompt, the generative AI provides various feedback, summaries, or text customizations. The software used is a generative AI model (e.g., GPT-3). The server receives the response from the generative AI model and sends it to the terminal.

[0215] The device decrypts the received results and presents them to the user in a format suitable for them. This allows users to receive emotionally responsive feedback while maintaining the security of the information they entered.

[0216] For example, if a user enters text such as, "I've been feeling a lot of pressure at work lately. What are some ways to relax?", the system analyzes this text to recognize the user's emotions. It then sends a prompt to a generating AI, which generates feedback including advice to help reduce stress.

[0217] Examples of prompt statements are as follows:

[0218] "User entered the message: 'Recently, I've been experiencing increased stress from a work project. How can I relieve this stress?' Analyze the emotions the user is feeling from this message and suggest appropriate stress relief methods."

[0219] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0220] Step 1:

[0221] The user inputs text information using a terminal. The input text data is received by the terminal. This information is then prepared by the system for subsequent processing.

[0222] Step 2:

[0223] The device uses a natural language processing library to analyze text information and identify personal and confidential information. It receives text data as input, and the identified information is prepared for data masking or encryption. Through natural language processing, specific parts of the data are identified to protect user privacy.

[0224] Step 3:

[0225] A local AI within the device masks or encrypts identified personal and confidential information. It receives identified information as input and generates masked or encrypted data as output. This process ensures data protection.

[0226] Step 4:

[0227] The device uses a sentiment analysis library to analyze the sentiment of masked or encrypted text data. It receives encrypted data as input and generates data indicating the emotional state as output. Information about the emotions is analyzed, and the user's psychological state is determined.

[0228] Step 5:

[0229] The server generates prompts from sentiment information and masked data and sends them to the generative AI model. It receives sentiment information and masked text data as input and generates prompt sentences as output. These prompt sentences are sent to the generative AI model and used for content generation.

[0230] Step 6:

[0231] The generative AI model generates feedback information for the user based on prompts. It receives a prompt as input and generates feedback as output. The generative AI model creates content that is tailored to the user's emotions and needs.

[0232] Step 7:

[0233] The server receives feedback from the generated AI model and sends it to the terminal. It receives the generated feedback as input and forwards it appropriately. In this step, the information is returned to the terminal and ready to be provided to the user.

[0234] Step 8:

[0235] The device decodes the received feedback data and presents it to the user in a way that reflects their emotions. It receives feedback from the server as input and converts it into a user-understandable format as output. Based on this result, the user can decide on their next action.

[0236] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0237] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0238] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0239] [Second Embodiment]

[0240] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0241] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0242] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0243] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0244] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0245] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0246] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0247] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0248] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0249] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0250] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0251] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0252] This information processing system is designed to securely process text data provided by users. The system is configured as follows:

[0253] First, the user inputs text data into the device. This data may contain personal or confidential information. The device uses natural language processing techniques to analyze the input text data and detect personal and confidential information within it. This could involve using regular expressions or morphological analysis.

[0254] The detected information is masked or encrypted by an artificial intelligence (AI) dedicated to encryption / masking that operates within the device. This AI identifies specific patterns and temporarily hides the information based on them. The masked data is then formatted as a prompt sent to a generating AI.

[0255] Next, the server sends this masked prompt to the generating AI. The generating AI performs the necessary tasks based on the received prompt, such as summarizing data or grammatical checking of text. The processing results are returned to the terminal via the server.

[0256] When the device receives the results of the AI ​​generation from the server, it decrypts them again using a dedicated encryption / masking AI. This restores the masked information to its original form, which is then displayed to the user as the final result.

[0257] As a concrete example, if a user enters meeting minutes, the system masks the names of participants and project names within them. Once the summary generated by the AI ​​is returned, it is decoded back into the original meeting minutes format and provided to the user. This process ensures information security while allowing users to enjoy the convenience of the AI-generated format.

[0258] The following describes the processing flow.

[0259] Step 1:

[0260] The user enters text data into the device. This text data may contain personal or confidential information.

[0261] Step 2:

[0262] The terminal receives input text data and uses natural language processing techniques to detect personal and confidential information. This involves using regular expressions to identify phone numbers and IDs, and morphological analysis to extract names of people and organizations.

[0263] Step 3:

[0264] The device uses locally running artificial intelligence to mask or encrypt any personal and confidential information it detects. Specifically, it replaces confidential portions with symbols such as "".

[0265] Step 4:

[0266] The device formats the encrypted data and prepares it as a prompt for the generating AI. The prompt is formatted to efficiently perform the target task.

[0267] Step 5:

[0268] The server receives prompts sent from the terminal and passes them to the generating AI. The data is transmitted through a secure communication channel.

[0269] Step 6:

[0270] The server receives the processing results from the generating AI and transfers them to the terminal. The generating AI provides the results of tasks such as summarization and text proofreading.

[0271] Step 7:

[0272] The terminal receives the results from the server and decrypts the original information. A dedicated encryption / masking AI handles this task, restoring the data to a state where its original meaning is understandable.

[0273] Step 8:

[0274] The device displays the decryption results to the user. The user can then decide on their next action based on the final result.

[0275] (Example 1)

[0276] Next, we will describe Example 1. 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."

[0277] In an information processing system, when processing data by an external generative AI model while ensuring the security of identification information and confidential information contained in the character data provided by the user, it is required to reduce the risk of information leakage. Also, in order to efficiently perform data analysis and text generation by utilizing an external generative AI model, means for realizing safe transmission and reception of data are also necessary.

[0278] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in the first embodiment is realized by the following means.

[0279] In this invention, the server includes means for analyzing the character data received from the user, detecting identification information and confidential information, means for making the detected information invisible or encrypting it, and means for transmitting the generated invisible or encrypted data to an external generative AI model. Thereby, while ensuring the security of the data, data processing that effectively utilizes an external generative AI model becomes possible.

[0280] A "user" is a subject that provides character data to the system and receives the processing result.

[0281] "Character data" refers to text-form information input by the user into the system.

[0282] "Analysis" refers to a process used to check character data and identify specific information.

[0283] "Identification information" refers to information for identifying an individual or information with specific confidentiality.

[0284] "Confidential information" refers to highly confidential information that may suffer disadvantages if disclosed.

[0285] "Detection" refers to the act of checking and identifying identification information and confidential information from character data.

[0286] "Non-display" refers to the process of converting original information into an invisible form in order to temporarily hide data.

[0287] "Encryption" refers to the technology of converting information into an unreadable form in order to protect it using specific algorithms.

[0288] "Generative AI model" refers to artificial intelligence that performs text generation and data analysis based on the input prompts.

[0289] "Communication means" refers to the methods and technologies for transmitting and receiving data, especially those aimed at ensuring security.

[0290] To implement this invention, the information processing system mainly consists of a server, a terminal, and a generative AI model.

[0291] The user can input text-based character data using the terminal. The terminal is equipped with natural language processing libraries (such as spaCy or NLTK), and these are used to analyze the input character data. Through analysis, it is possible to detect identification information and secret information. For this purpose, regular expressions and morphological analysis are utilized.

[0292] The terminal has a computing model that operates locally to non-display or encrypt the detected identification information and secret information. This computing model identifies specific patterns and replaces information with placeholders to temporarily hide the information.

[0293] The masked data is prepared as a formatted prompt sentence. This formatted prompt is sent to the generative AI model, and the generative AI model executes the necessary tasks (such as data summarization or grammar checking).

[0294] The processing results from the generated AI model are returned to the terminal via the server. The terminal then decodes these results again using the computational model and presents the original information to the user. This allows the user to receive the final, securely processed result.

[0295] For example, if a user enters meeting minutes, this system masks the names of participants and project names within the minutes. After this process is complete, the AI-generated summary can be decoded back into its original format and provided to the user.

[0296] An example of a prompt might be, "Please summarize the meeting content. Please omit participant names and project names." This prompt is then used as input to the generating AI model, which performs the appropriate processing.

[0297] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0298] Step 1:

[0299] The user inputs text data into the terminal. For example, the user might enter meeting minutes or the body of an email into a text box. This entered text data becomes the initial data for the system to process.

[0300] Step 2:

[0301] The terminal analyzes the input character data using a natural language processing library (e.g., spaCy or NLTK). The input for analysis is the user's text data, and the output is a list of identification and secret information. This process uses regular expressions for pattern matching and morphological analysis to identify names, addresses, and other sensitive information.

[0302] Step 3:

[0303] The terminal anonymizes or encrypts the detected identification information and the secret information. The input is the information list detected in Step 2, which is replaced by a placeholder (e.g., "NAME" or "PROJECT") by a calculation model. The output is masked character data. This protects the user's personal information.

[0304] Step 4:

[0305] The terminal formats the masked data as a prompt sentence. The formatting is done by converting the data into a format that the generative AI model can process appropriately. The input is the masked data obtained in Step 3, and the output is the formatted prompt sentence.

[0306] Step 5:

[0307] The server sends the formatted prompt to the generative AI model. For this purpose, the prompt sentence is converted into a format corresponding to the generative AI model (e.g., API request). The input is the prompt sentence formatted in Step 4, and the output is the processing result by the generative AI model.

[0308] Step 6:

[0309] The server receives the processing result from the generative AI model and sends the result to the terminal. The input at this stage is the output of the generative AI model, and the output is that the same content reaches the user's terminal.

[0310] Step 7:

[0311] The terminal decrypts the processing result of the generative AI model received from the server and returns the placeholder to the original identification information. The input is the processing result of Step 6 and the identification information obtained in Step 2, and the output is the decrypted final data. This is displayed to the user so that the user can refer to the information.

[0312] (Application Example 1)

[0313] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0314] The objective of this invention is to safely and efficiently process text data containing personal and confidential information, while presenting users with the information they need in real time. In particular, it is necessary to balance the protection of privacy and the speed of information processing when information is provided in real time through visual devices.

[0315] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0316] In this invention, the server includes means for analyzing text data received from a user to detect personal and confidential information, means for masking or encrypting the detected information, means for transmitting the generated masked or encrypted data to an external generating AI, and means for receiving the processing results from the generating AI and decrypting the original information. This enables the provision of accurate information in real time while protecting personal information.

[0317] A "user" is a person who provides text data using a specific information processing system and receives the results.

[0318] "Text data" refers to a collection of information entered as text, which may include personal or confidential information.

[0319] "Personal information" refers to information that can identify a specific individual, such as name and address.

[0320] "Confidential information" refers to information that is not publicly available and is important data for a particular organization or individual.

[0321] "Masking" is a technique used to conceal or hide personal or confidential information.

[0322] "Encryption" is a method of converting data from a decryptable format to an unreadable format to prevent unauthorized access by third parties.

[0323] "Generative AI" is an artificial intelligence technology that automatically generates text and information based on given input.

[0324] "Decryption" is the process of returning encrypted data to its original, decryptable format.

[0325] "Visual devices" are hardware that displays information visually, and include smart glasses, among other things.

[0326] "Real-time" means processing or providing information immediately, and presenting results to users without delay.

[0327] The system for carrying out this invention mainly consists of a server, a user terminal, and a visual device (e.g., smart glasses). A specific embodiment is described below.

[0328] First, the user inputs text data using a visual device. This text data is received by the user's terminal and analyzed using a natural language processing (NLP) library (e.g., spaCy, NLTK). This analysis triggers an AI model (e.g., a custom OpenAI GPT model) to identify personal and confidential information and then mask or encrypt it.

[0329] Next, the user terminal generates a prompt to send the masked data to the generative AI model. This communication takes place using an encrypted channel between the server and a cloud-based generative AI service (e.g., OpenAI GPT-3, Google AI API). Based on the received prompt, the generative AI performs the specified information processing (e.g., summarization, grammar correction) and returns the result to the server.

[0330] The server sends the received processing results to the user's terminal and performs the demasking process again. The visual device displays the decoded results to the user in real time. This allows the user to immediately access the information in a privacy-protected manner.

[0331] As a concrete example, in a corporate business meeting, if a user is using smart glasses to view agenda materials, the key points will be displayed in a summarized form while protecting personal names and project names.

[0332] An example of a prompt message is, "Summarize the contents of this text and output it with confidential information masked." This system makes it possible to process and present important data quickly while maintaining information security.

[0333] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0334] Step 1:

[0335] The user inputs text data using a visual device. The user terminal receives this text data and records it as input data. This input data may contain personal or confidential information.

[0336] Step 2:

[0337] The terminal uses a natural language processing library (e.g., spaCy, NLTK) to parse the received text data. Morphological analysis and regular expressions are applied to the input text data to detect personal and sensitive information within the data. This analysis identifies data that needs to be masked or encrypted.

[0338] Step 3:

[0339] The device processes detected personal and confidential information using an AI model (e.g., a custom OpenAI GPT model) to mask or encrypt it. The input is the information identified through analysis, and the output is masked data. This masking process protects the data from unauthorized access by third parties.

[0340] Step 4:

[0341] The device generates a prompt for the generative AI from the masked data. In this process, it formats the prompt text and sends it to a cloud-based generative AI service using an encrypted communication channel. The input is masked data, and the output is the formatted prompt text.

[0342] Step 5:

[0343] The server receives the results processed by the generative AI in the cloud. These results include the output of the information processing performed by the generative AI based on the prompt. The input is the formatted prompt, and the output is the processed result.

[0344] Step 6:

[0345] The terminal decodes the processing results of the generating AI received from the server. Simultaneously, it removes the masking to reconstruct the original information. The input is the processing result of the generating AI, and the output is the decoded result.

[0346] Step 7:

[0347] A visual device displays the decoded results to the user in real time. The processed information is presented visually, allowing the user to view the necessary information. The input is the decoded result, and the output is the visually displayed information.

[0348] By ensuring that the data entered at each step is properly processed or calculated and prepared for the next step, users can receive the necessary information safely and quickly. This entire process enables real-time information delivery while maintaining the protection of personal information.

[0349] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0350] This invention is an information processing system that securely processes text data entered by a user, recognizes the user's emotions within that data, and generates appropriate feedback. The system is configured as follows:

[0351] First, the user enters text data into the device. Because this data may contain personal or confidential information, the device uses natural language processing technology to detect it. The detected information is then masked or encrypted by a dedicated artificial intelligence operating within the device. This AI identifies the information and uses codes to protect the data.

[0352] Next, the device receives the masked text and uses its emotion engine to recognize the user's emotional state. This emotion engine analyzes the context and tone of the text to determine whether the user is happy, angry, or sad.

[0353] The terminal then formats the recognized emotion information and masked data, preparing it as a prompt for the generative AI. The server sends the formatted prompt to the generative AI. Based on the received prompt, the generative AI summarizes the data, generates a customized response based on emotion, or performs grammatical checks on the text.

[0354] The server receives the results from the generating AI and transfers them to the terminal. After receiving the results, the terminal uses a dedicated encryption / masking AI to decrypt the original information. Furthermore, the generated results are adjusted to the user's emotions and presented in the most appropriate format for the user.

[0355] For example, if a user enters a text message about stress, the system senses the user's stress level and instructs the AI ​​to summarize the message and generate appropriate advice. Finally, the device decodes the advice and provides the user with recommendations to help reduce stress. This allows for secure data processing and the provision of valuable information while considering the user's emotions.

[0356] The following describes the processing flow.

[0357] Step 1:

[0358] The user enters text data into the device. For example, the user enters the sentence, "I've been feeling stressed out by my recent projects."

[0359] Step 2:

[0360] The terminal receives the entered text data and uses natural language processing technology to detect personal and confidential information within it. For example, it identifies the term "project."

[0361] Step 3:

[0362] The device uses locally running artificial intelligence to mask or encrypt any sensitive information it detects. This temporarily protects the data, for example, by replacing "project" with "".

[0363] Step 4:

[0364] The device passes encrypted text to an emotion engine, which analyzes the user's emotional state. In this case, the engine recognizes from the text that the user is experiencing stress.

[0365] Step 5:

[0366] The device combines emotional information with encrypted text and formats it as a prompt for the generating AI. This prompt may include the fact that the user is feeling stressed.

[0367] Step 6:

[0368] The server receives a prompt sent from the terminal and forwards it to the generating AI. This prompt includes instructions for generating a response that is tailored to the user's emotional state.

[0369] Step 7:

[0370] The generating AI processes prompts and produces output results tailored to the user's emotions, such as advice for stress relief.

[0371] Step 8:

[0372] The server receives the output from the generated AI and sends it back to the terminal.

[0373] Step 9:

[0374] The device decrypts the results received from the server back into the original data and then makes adjustments based on the user's emotional state. For example, it might be formatted to say, "You may be feeling stressed, but please try the following to relax."

[0375] Step 10:

[0376] The device presents the final results to the user and provides advice from the generated AI in a usable format. The user can then implement stress management strategies based on the information provided.

[0377] (Example 2)

[0378] Next, we will describe Example 2. 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".

[0379] In information processing systems, when text data entered by users contains personal or confidential information, it is necessary to securely protect that information while simultaneously accurately recognizing the user's emotions and providing appropriate feedback. However, conventional systems face the challenge of balancing information protection with accurate emotion recognition. Furthermore, advanced text processing using generative AI models requires a secure and efficient method of data transmission.

[0380] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0381] In this invention, the server includes means for analyzing textual information received from a user and detecting personally identifiable information and confidential information, means for masking or encrypting the detected information, and means for an engine for recognizing the emotional state based on the masked text. This makes it possible to provide feedback that corresponds to the user's emotional state while protecting personal information.

[0382] "Textual information" refers to data in text format entered by users, and is subject to natural language processing.

[0383] "Personally identifiable information" refers to information that can identify an individual user, including their name, address, and contact information.

[0384] "Confidential information" refers to information that is not publicly available and is considered highly sensitive data for a particular organization or individual.

[0385] "Masking" is a process that makes personally identifiable information or confidential information unidentifiable by replacing it with information based on certain rules.

[0386] "Encryption" is the process of transforming data using a specific algorithm to make it a format that cannot be easily understood by a third party.

[0387] "Emotional state" refers to the psychological state extracted from the text information entered by the user, and includes classifications such as positive, negative, and neutral.

[0388] A "generative model" refers to artificial intelligence technology that has the ability to generate natural language by learning from large amounts of data.

[0389] A "communication channel" is a transmission path used by the server and the generative model to send and receive data, and it must be encrypted to ensure security.

[0390] This invention is an information processing system that securely processes text information entered by a user, recognizes emotions within that information, and generates appropriate feedback. The system utilizes the following hardware and software.

[0391] The user inputs text information into the terminal. This terminal is equipped with a natural language processing engine and encryption technology. The natural language processing engine analyzes the text information entered by the user to identify personally identifiable and confidential information. Common programming languages ​​and libraries, such as Python and its natural language processing library, are used for the analysis. After detecting confidential information, a dedicated AI is used to mask or encrypt the data. This AI operates within the terminal and uses standard encryption techniques, such as AES encryption.

[0392] Next, the device uses an emotion engine to identify the user's emotional state from the masked text information. This process utilizes deep learning models, such as BERT or RoBERTa, to analyze emotions from the context and tone of the text. The extracted emotional information and masked data are then formatted as prompts and sent to a generative AI model. The server receives the prompts and communicates with the external generative AI in real time. A secure communication channel is established for this communication, using encryption protocols such as SSL / TLS.

[0393] The generative AI model performs various text processing tasks based on the received prompts. For example, it summarizes user input and generates emotionally appropriate advice and feedback. This generated information is returned to the device via the server, where it is decrypted again using encryption / masking AI. Finally, the results are adjusted to the user's emotions and displayed to the user in the most optimal form.

[0394] As a concrete example, consider a scenario where a user inputs, "I'm feeling stressed and depressed." The system analyzes this information and recognizes the negative emotion of stress. It then sends a prompt to a generative AI model regarding "specific ways to relax," generating appropriate advice. Finally, the device decodes this advice and provides feedback in a format easily understood by the user. This process allows users to receive support tailored to their individual needs.

[0395] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0396] Step 1:

[0397] The user inputs text information on the terminal. This text information is then analyzed by a natural language processing engine. Raw string data is used as input for the analysis. The engine tokenizes the input text, analyzes the sentence structure, and extracts personal identification information and sensitive information. As a result, the extracted sensitive information is output.

[0398] Step 2:

[0399] The device processes the personally identifiable and confidential information extracted in Step 1 using a dedicated AI, performing masking or encryption. The input consists of identified sensitive information, and an appropriate masking pattern or encryption algorithm (e.g., AES encryption) is applied according to the importance and type of the information. As a result, protected data is output.

[0400] Step 3:

[0401] The device processes masked text information using an emotion engine to analyze the user's emotional state. The input in this step is masked text information. A deep learning model (e.g., BERT) is used to extract context and emotional characteristics from individual words and their combinations. This analysis outputs specific emotional labels (e.g., positive, negative).

[0402] Step 4:

[0403] The device integrates the emotion information obtained in step 3 with the masked data to create a prompt message to send to the generative AI model. This creation process is performed by using the emotion labels and masked data as input and applying them to a prompt template. As a result, a prompt message in a format that the generative AI can understand is output.

[0404] Step 5:

[0405] The server sends a prompt to the generative AI model, which then processes it. The input is the prompt, and the AI ​​uses natural language generation techniques to analyze this information and generate summaries and feedback sentences. This results in optimized text data for the user.

[0406] Step 6:

[0407] The server sends the output from the generating AI back to the terminal. The terminal receives the data through a secure communication channel and performs the decryption process. The input here is encrypted response data, which is decrypted back into its original form by a dedicated decryption AI. As a result, the decrypted feedback information is output.

[0408] Step 7:

[0409] The device further refines the decoded feedback based on the emotions recognized in step 3 and presents it to the user. Decoded data and emotional information are used as input for customization to enrich the user experience. Ultimately, the user receives emotionally resonant, personalized feedback.

[0410] (Application Example 2)

[0411] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0412] In modern times, text data entered by users often contains confidential or personal information, and its secure handling is essential. Furthermore, accurately recognizing user emotions from their input and providing appropriate feedback has become a critical challenge for many communication applications and security services. This invention aims to solve these problems by providing a system that securely generates and presents emotion-responsive feedback while considering the user's feelings.

[0413] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0414] In this invention, the server includes means for analyzing text information obtained from a user and identifying personal and confidential information; means for masking or encrypting the identified information; means for analyzing the masked or encrypted text information and recognizing emotions; means for shaping the recognized emotion information and masked data and generating prompts to send to a generating AI; and means for receiving feedback from the generating AI, decrypting the original information, and presenting it in a form appropriate to the emotions. This enables the secure processing of user input data while providing effective feedback tailored to their emotions.

[0415] A "user" refers to an individual who uses the system to input text information.

[0416] "Text information" refers to text data entered by users, which may contain personal information or emotions.

[0417] "Personal information" refers to information that can be used to identify a user, and includes names, addresses, and contact information.

[0418] "Confidential information" refers to important information that should not be made public, and includes business secrets and sensitive data.

[0419] "Masking" is a technique used to conceal personal or confidential information within data, thereby obscuring the true nature of the information.

[0420] "Encryption" is a technology that transforms information to prevent it from being read illegally, and is used to securely store data.

[0421] "Emotions" refer to the psychological state expressed by the user, and include types such as joy, sadness, and anger.

[0422] A "prompt" refers to formatted text data used to give instructions to a generating AI.

[0423] "Generative AI" refers to an algorithm that automatically generates feedback and content based on input data.

[0424] "Feedback" refers to replies or responses provided to users based on their emotions.

[0425] "Decryption" refers to the process of restoring encrypted information to its original format, which is done so that users can understand the data.

[0426] The system for carrying out this invention is specifically configured as follows.

[0427] First, the system receives text information entered by the user using the terminal. Because this information may contain personal or confidential data, natural language processing (NLP) technology on the terminal is used to identify this information. Software used includes natural language processing libraries (e.g., spaCy, NLTK). The identified information is then masked or encrypted by a locally running AI. For encryption, a proprietary code is used to protect the data.

[0428] Next, sentiment analysis is performed on the encrypted text. The device uses a sentiment analysis library (e.g., TextBlob) to analyze the sentiment state of the input text. The analyzed sentiment information is used to generate prompts that are sent to the generative AI model.

[0429] The generated prompt is sent by the server to the generative AI model. Based on the given prompt, the generative AI provides various feedback, summaries, or text customizations. The software used is a generative AI model (e.g., GPT-3). The server receives the response from the generative AI model and sends it to the terminal.

[0430] The device decrypts the received results and presents them to the user in a format suitable for them. This allows users to receive emotionally responsive feedback while maintaining the security of the information they entered.

[0431] For example, if a user enters text such as, "I've been feeling a lot of pressure at work lately. What are some ways to relax?", the system analyzes this text to recognize the user's emotions. It then sends a prompt to a generating AI, which generates feedback including advice to help reduce stress.

[0432] Examples of prompt statements are as follows:

[0433] "User entered the message: 'Recently, I've been experiencing increased stress from a work project. How can I relieve this stress?' Analyze the emotions the user is feeling from this message and suggest appropriate stress relief methods."

[0434] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0435] Step 1:

[0436] The user inputs text information using a terminal. The input text data is received by the terminal. This information is then prepared by the system for subsequent processing.

[0437] Step 2:

[0438] The device uses a natural language processing library to analyze text information and identify personal and confidential information. It receives text data as input, and the identified information is prepared for data masking or encryption. Through natural language processing, specific parts of the data are identified to protect user privacy.

[0439] Step 3:

[0440] A local AI within the device masks or encrypts identified personal and confidential information. It receives identified information as input and generates masked or encrypted data as output. This process ensures data protection.

[0441] Step 4:

[0442] The device uses a sentiment analysis library to analyze the sentiment of masked or encrypted text data. It receives encrypted data as input and generates data indicating the emotional state as output. Information about the emotions is analyzed, and the user's psychological state is determined.

[0443] Step 5:

[0444] The server generates prompts from sentiment information and masked data and sends them to the generative AI model. It receives sentiment information and masked text data as input and generates prompt sentences as output. These prompt sentences are sent to the generative AI model and used for content generation.

[0445] Step 6:

[0446] The generative AI model generates feedback information for the user based on prompts. It receives a prompt as input and generates feedback as output. The generative AI model creates content that is tailored to the user's emotions and needs.

[0447] Step 7:

[0448] The server receives feedback from the generated AI model and sends it to the terminal. It receives the generated feedback as input and forwards it appropriately. In this step, the information is returned to the terminal and ready to be provided to the user.

[0449] Step 8:

[0450] The device decodes the received feedback data and presents it to the user in a way that reflects their emotions. It receives feedback from the server as input and converts it into a user-understandable format as output. Based on this result, the user can decide on their next action.

[0451] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0452] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0453] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0454] [Third Embodiment]

[0455] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0456] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0457] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0458] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0459] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0460] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0461] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0462] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0463] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0464] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0465] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0466] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0467] This information processing system is designed to securely process text data provided by users. The system is configured as follows:

[0468] First, the user inputs text data into the device. This data may contain personal or confidential information. The device uses natural language processing techniques to analyze the input text data and detect personal and confidential information within it. This could involve using regular expressions or morphological analysis.

[0469] The detected information is masked or encrypted by an artificial intelligence (AI) dedicated to encryption / masking that operates within the device. This AI identifies specific patterns and temporarily hides the information based on them. The masked data is then formatted as a prompt sent to a generating AI.

[0470] Next, the server sends this masked prompt to the generating AI. The generating AI performs the necessary tasks based on the received prompt, such as summarizing data or grammatical checking of text. The processing results are returned to the terminal via the server.

[0471] When the device receives the results of the AI ​​generation from the server, it decrypts them again using a dedicated encryption / masking AI. This restores the masked information to its original form, which is then displayed to the user as the final result.

[0472] As a concrete example, if a user enters meeting minutes, the system masks the names of participants and project names within them. Once the summary generated by the AI ​​is returned, it is decoded back into the original meeting minutes format and provided to the user. This process ensures information security while allowing users to enjoy the convenience of the AI-generated format.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The user enters text data into the device. This text data may contain personal or confidential information.

[0476] Step 2:

[0477] The terminal receives input text data and uses natural language processing techniques to detect personal and confidential information. This involves using regular expressions to identify phone numbers and IDs, and morphological analysis to extract names of people and organizations.

[0478] Step 3:

[0479] The device uses locally running artificial intelligence to mask or encrypt any personal and confidential information it detects. Specifically, it replaces confidential portions with symbols such as "".

[0480] Step 4:

[0481] The device formats the encrypted data and prepares it as a prompt for the generating AI. The prompt is formatted to efficiently perform the target task.

[0482] Step 5:

[0483] The server receives prompts sent from the terminal and passes them to the generating AI. The data is transmitted through a secure communication channel.

[0484] Step 6:

[0485] The server receives the processing results from the generating AI and transfers them to the terminal. The generating AI provides the results of tasks such as summarization and text proofreading.

[0486] Step 7:

[0487] The terminal receives the results from the server and decrypts the original information. A dedicated encryption / masking AI handles this task, restoring the data to a state where its original meaning is understandable.

[0488] Step 8:

[0489] The device displays the decryption results to the user. The user can then decide on their next action based on the final result.

[0490] (Example 1)

[0491] Next, we will describe Example 1. 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."

[0492] In information processing systems, there is a need to guarantee the security of identifying and confidential information contained in text data provided by users, while mitigating the risk of information leakage when processing data with external generative AI models. Furthermore, in order to efficiently perform data analysis and text generation using external generative AI models, means of ensuring the secure transmission and reception of data are also necessary.

[0493] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0494] In this invention, the server includes means for analyzing character data received from a user and detecting identification information and confidential information, means for concealing or encrypting the detected information, and means for transmitting the generated concealed or encrypted data to an external generative AI model. This enables data processing that effectively utilizes an external generative AI model while ensuring data security.

[0495] A "user" is an entity that provides text data to a system and receives the processing results.

[0496] "Text data" refers to information in text format that users input into the system.

[0497] "Analysis" refers to the process used to examine textual data and identify specific information.

[0498] "Identification information" refers to information that identifies an individual or information that has a specific level of confidentiality.

[0499] "Confidential information" refers to highly sensitive information that, if made public, could result in negative consequences.

[0500] "Detection" refers to the act of confirming and identifying identifying or confidential information within text data.

[0501] "Hiding" refers to the process of converting the original information into an invisible form in order to temporarily hide the data.

[0502] "Encryption" refers to the technique of converting information into a format that cannot be read in order to protect it using a specific algorithm.

[0503] A "generative AI model" refers to artificial intelligence that generates text or performs data analysis based on input prompts.

[0504] "Communication methods" refer to methods and technologies for sending and receiving data, and include those specifically intended to ensure security.

[0505] To implement this invention, the information processing system mainly consists of a server, a terminal, and a generative AI model.

[0506] Users can input text-based character data using a terminal. The terminal has a natural language processing library (e.g., spaCy or NLTK) implemented, which is used to analyze the input character data. This analysis makes it possible to detect identifying and confidential information. Regular expressions and morphological analysis are used for this purpose.

[0507] The device has a locally running computational model to hide or encrypt detected identification and secret information. This computational model identifies specific patterns and replaces the information with placeholders to temporarily conceal it.

[0508] The masked data is prepared as a formatted prompt. This formatted prompt is sent to the generative AI model, which then performs the necessary tasks (e.g., data summarization and grammar checking).

[0509] The processing results from the generated AI model are returned to the terminal via the server. The terminal then decodes these results again using the computational model and presents the original information to the user. This allows the user to receive the final, securely processed result.

[0510] For example, if a user enters meeting minutes, this system masks the names of participants and project names within the minutes. After this process is complete, the AI-generated summary can be decoded back into its original format and provided to the user.

[0511] An example of a prompt might be, "Please summarize the meeting content. Please omit participant names and project names." This prompt is then used as input to the generating AI model, which performs the appropriate processing.

[0512] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0513] Step 1:

[0514] The user inputs text data into the terminal. For example, the user might enter meeting minutes or the body of an email into a text box. This entered text data becomes the initial data for the system to process.

[0515] Step 2:

[0516] The terminal analyzes the input character data using a natural language processing library (e.g., spaCy or NLTK). The input for analysis is the user's text data, and the output is a list of identification and secret information. This process uses regular expressions for pattern matching and morphological analysis to identify names, addresses, and other sensitive information.

[0517] Step 3:

[0518] The device hides or encrypts the detected identification and confidential information. The input is a list of information detected in step 2, which is then replaced with placeholders (e.g., "NAME" or "PROJECT") by a computational model. The output is masked character data, thus protecting the user's personal information.

[0519] Step 4:

[0520] The terminal formats the masked data into a prompt message. Formatting is performed by converting the data into a format that the generative AI model can process appropriately. The input is the masked data obtained in step 3, and the output is the formatted prompt message.

[0521] Step 5:

[0522] The server sends the formatted prompt to the generating AI model. To do this, it converts the prompt text into a format compatible with the generating AI model (e.g., an API request). The input is the prompt text formatted in step 4, and the output is the result of processing by the generating AI model.

[0523] Step 6:

[0524] The server receives the processing results from the generating AI model and sends those results to the terminal. At this stage, the input is the output of the generating AI model, and the same content reaches the user's terminal as the output.

[0525] Step 7:

[0526] The terminal decodes the processing results of the generated AI model received from the server and replaces the placeholders with the original identification information. The input is the processing results from step 6 and the identification information obtained in step 2, and the output is the decoded final data. This is displayed to the user so that the user can refer to the information.

[0527] (Application Example 1)

[0528] Next, we will explain Application Example 1. In the following explanation, 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."

[0529] The objective of this invention is to safely and efficiently process text data containing personal and confidential information, while presenting users with the information they need in real time. In particular, it is necessary to balance the protection of privacy and the speed of information processing when information is provided in real time through visual devices.

[0530] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0531] In this invention, the server includes means for analyzing text data received from a user to detect personal and confidential information, means for masking or encrypting the detected information, means for transmitting the generated masked or encrypted data to an external generating AI, and means for receiving the processing results from the generating AI and decrypting the original information. This enables the provision of accurate information in real time while protecting personal information.

[0532] A "user" is a person who provides text data using a specific information processing system and receives the results.

[0533] "Text data" refers to a collection of information entered as text, which may include personal or confidential information.

[0534] "Personal information" refers to information that can identify a specific individual, such as name and address.

[0535] "Confidential information" refers to information that is not publicly available and is important data for a particular organization or individual.

[0536] "Masking" is a technique used to conceal or hide personal or confidential information.

[0537] "Encryption" is a method of converting data from a decryptable format to an unreadable format to prevent unauthorized access by third parties.

[0538] "Generative AI" is an artificial intelligence technology that automatically generates text and information based on given input.

[0539] "Decryption" is the process of returning encrypted data to its original, decryptable format.

[0540] "Visual devices" are hardware that displays information visually, and include smart glasses, among other things.

[0541] "Real-time" means processing or providing information immediately, and presenting results to users without delay.

[0542] The system for carrying out this invention mainly consists of a server, a user terminal, and a visual device (e.g., smart glasses). A specific embodiment is described below.

[0543] First, the user inputs text data using a visual device. This text data is received by the user's terminal and analyzed using a natural language processing (NLP) library (e.g., spaCy, NLTK). This analysis triggers an AI model (e.g., a custom OpenAI GPT model) to identify personal and confidential information and then mask or encrypt it.

[0544] Next, the user terminal generates a prompt to send the masked data to the generative AI model. This communication takes place using an encrypted channel between the server and a cloud-based generative AI service (e.g., OpenAI GPT-3, Google AI API). Based on the received prompt, the generative AI performs the specified information processing (e.g., summarization, grammar correction) and returns the result to the server.

[0545] The server sends the received processing results to the user's terminal and performs the demasking process again. The visual device displays the decoded results to the user in real time. This allows the user to immediately access the information in a privacy-protected manner.

[0546] As a concrete example, in a corporate business meeting, if a user is using smart glasses to view agenda materials, the key points will be displayed in a summarized form while protecting personal names and project names.

[0547] An example of a prompt message is, "Summarize the contents of this text and output it with confidential information masked." This system makes it possible to process and present important data quickly while maintaining information security.

[0548] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0549] Step 1:

[0550] The user inputs text data using a visual device. The user terminal receives this text data and records it as input data. This input data may contain personal or confidential information.

[0551] Step 2:

[0552] The terminal uses a natural language processing library (e.g., spaCy, NLTK) to parse the received text data. Morphological analysis and regular expressions are applied to the input text data to detect personal and sensitive information within the data. This analysis identifies data that needs to be masked or encrypted.

[0553] Step 3:

[0554] The device processes detected personal and confidential information using an AI model (e.g., a custom OpenAI GPT model) to mask or encrypt it. The input is the information identified through analysis, and the output is masked data. This masking process protects the data from unauthorized access by third parties.

[0555] Step 4:

[0556] The device generates a prompt for the generative AI from the masked data. In this process, it formats the prompt text and sends it to a cloud-based generative AI service using an encrypted communication channel. The input is masked data, and the output is the formatted prompt text.

[0557] Step 5:

[0558] The server receives the results processed by the generative AI in the cloud. These results include the output of the information processing performed by the generative AI based on the prompt. The input is the formatted prompt, and the output is the processed result.

[0559] Step 6:

[0560] The terminal decodes the processing results of the generating AI received from the server. Simultaneously, it removes the masking to reconstruct the original information. The input is the processing result of the generating AI, and the output is the decoded result.

[0561] Step 7:

[0562] A visual device displays the decoded results to the user in real time. The processed information is presented visually, allowing the user to view the necessary information. The input is the decoded result, and the output is the visually displayed information.

[0563] By ensuring that the data entered at each step is properly processed or calculated and prepared for the next step, users can receive the necessary information safely and quickly. This entire process enables real-time information delivery while maintaining the protection of personal information.

[0564] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0565] This invention is an information processing system that securely processes text data entered by a user, recognizes the user's emotions within that data, and generates appropriate feedback. The system is configured as follows:

[0566] First, the user enters text data into the device. Because this data may contain personal or confidential information, the device uses natural language processing technology to detect it. The detected information is then masked or encrypted by a dedicated artificial intelligence operating within the device. This AI identifies the information and uses codes to protect the data.

[0567] Next, the device receives the masked text and uses its emotion engine to recognize the user's emotional state. This emotion engine analyzes the context and tone of the text to determine whether the user is happy, angry, or sad.

[0568] The terminal then formats the recognized emotion information and masked data, preparing it as a prompt for the generative AI. The server sends the formatted prompt to the generative AI. Based on the received prompt, the generative AI summarizes the data, generates a customized response based on emotion, or performs grammatical checks on the text.

[0569] The server receives the results from the generating AI and transfers them to the terminal. After receiving the results, the terminal uses a dedicated encryption / masking AI to decrypt the original information. Furthermore, the generated results are adjusted to the user's emotions and presented in the most appropriate format for the user.

[0570] For example, if a user enters a text message about stress, the system senses the user's stress level and instructs the AI ​​to summarize the message and generate appropriate advice. Finally, the device decodes the advice and provides the user with recommendations to help reduce stress. This allows for secure data processing and the provision of valuable information while considering the user's emotions.

[0571] The following describes the processing flow.

[0572] Step 1:

[0573] The user enters text data into the device. For example, the user enters the sentence, "I've been feeling stressed out by my recent projects."

[0574] Step 2:

[0575] The terminal receives the entered text data and uses natural language processing technology to detect personal and confidential information within it. For example, it identifies the term "project."

[0576] Step 3:

[0577] The device uses locally running artificial intelligence to mask or encrypt any sensitive information it detects. This temporarily protects the data, for example, by replacing "project" with "".

[0578] Step 4:

[0579] The device passes encrypted text to an emotion engine, which analyzes the user's emotional state. In this case, the engine recognizes from the text that the user is experiencing stress.

[0580] Step 5:

[0581] The device combines emotional information with encrypted text and formats it as a prompt for the generating AI. This prompt may include the fact that the user is feeling stressed.

[0582] Step 6:

[0583] The server receives a prompt sent from the terminal and forwards it to the generating AI. This prompt includes instructions for generating a response that is tailored to the user's emotional state.

[0584] Step 7:

[0585] The generating AI processes prompts and produces output results tailored to the user's emotions, such as advice for stress relief.

[0586] Step 8:

[0587] The server receives the output from the generated AI and sends it back to the terminal.

[0588] Step 9:

[0589] The device decrypts the results received from the server back into the original data and then makes adjustments based on the user's emotional state. For example, it might be formatted to say, "You may be feeling stressed, but please try the following to relax."

[0590] Step 10:

[0591] The device presents the final results to the user and provides advice from the generated AI in a usable format. The user can then implement stress management strategies based on the information provided.

[0592] (Example 2)

[0593] Next, we will describe Example 2. 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."

[0594] In information processing systems, when text data entered by users contains personal or confidential information, it is necessary to securely protect that information while simultaneously accurately recognizing the user's emotions and providing appropriate feedback. However, conventional systems face the challenge of balancing information protection with accurate emotion recognition. Furthermore, advanced text processing using generative AI models requires a secure and efficient method of data transmission.

[0595] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0596] In this invention, the server includes means for analyzing textual information received from a user and detecting personally identifiable information and confidential information, means for masking or encrypting the detected information, and means for an engine for recognizing the emotional state based on the masked text. This makes it possible to provide feedback that corresponds to the user's emotional state while protecting personal information.

[0597] "Textual information" refers to data in text format entered by users, and is subject to natural language processing.

[0598] "Personally identifiable information" refers to information that can identify an individual user, including their name, address, and contact information.

[0599] "Confidential information" refers to information that is not publicly available and is considered highly sensitive data for a particular organization or individual.

[0600] "Masking" is a process that makes personally identifiable information or confidential information unidentifiable by replacing it with information based on certain rules.

[0601] "Encryption" is the process of transforming data using a specific algorithm to make it a format that cannot be easily understood by a third party.

[0602] "Emotional state" refers to the psychological state extracted from the text information entered by the user, and includes classifications such as positive, negative, and neutral.

[0603] A "generative model" refers to artificial intelligence technology that has the ability to generate natural language by learning from large amounts of data.

[0604] A "communication channel" is a transmission path used by the server and the generative model to send and receive data, and it must be encrypted to ensure security.

[0605] This invention is an information processing system that securely processes text information entered by a user, recognizes emotions within that information, and generates appropriate feedback. The system utilizes the following hardware and software.

[0606] The user inputs text information into the terminal. This terminal is equipped with a natural language processing engine and encryption technology. The natural language processing engine analyzes the text information entered by the user to identify personally identifiable and confidential information. Common programming languages ​​and libraries, such as Python and its natural language processing library, are used for the analysis. After detecting confidential information, a dedicated AI is used to mask or encrypt the data. This AI operates within the terminal and uses standard encryption techniques, such as AES encryption.

[0607] Next, the device uses an emotion engine to identify the user's emotional state from the masked text information. This process utilizes deep learning models, such as BERT or RoBERTa, to analyze emotions from the context and tone of the text. The extracted emotional information and masked data are then formatted as prompts and sent to a generative AI model. The server receives the prompts and communicates with the external generative AI in real time. A secure communication channel is established for this communication, using encryption protocols such as SSL / TLS.

[0608] The generative AI model performs various text processing tasks based on the received prompts. For example, it summarizes user input and generates emotionally appropriate advice and feedback. This generated information is returned to the device via the server, where it is decrypted again using encryption / masking AI. Finally, the results are adjusted to the user's emotions and displayed to the user in the most optimal form.

[0609] As a concrete example, consider a scenario where a user inputs, "I'm feeling stressed and depressed." The system analyzes this information and recognizes the negative emotion of stress. It then sends a prompt to a generative AI model regarding "specific ways to relax," generating appropriate advice. Finally, the device decodes this advice and provides feedback in a format easily understood by the user. This process allows users to receive support tailored to their individual needs.

[0610] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0611] Step 1:

[0612] The user inputs text information on the terminal. This text information is then analyzed by a natural language processing engine. Raw string data is used as input for the analysis. The engine tokenizes the input text, analyzes the sentence structure, and extracts personal identification information and sensitive information. As a result, the extracted sensitive information is output.

[0613] Step 2:

[0614] The device processes the personally identifiable and confidential information extracted in Step 1 using a dedicated AI, performing masking or encryption. The input consists of identified sensitive information, and an appropriate masking pattern or encryption algorithm (e.g., AES encryption) is applied according to the importance and type of the information. As a result, protected data is output.

[0615] Step 3:

[0616] The device processes masked text information using an emotion engine to analyze the user's emotional state. The input in this step is masked text information. A deep learning model (e.g., BERT) is used to extract context and emotional characteristics from individual words and their combinations. This analysis outputs specific emotional labels (e.g., positive, negative).

[0617] Step 4:

[0618] The device integrates the emotion information obtained in step 3 with the masked data to create a prompt message to send to the generative AI model. This creation process is performed by using the emotion labels and masked data as input and applying them to a prompt template. As a result, a prompt message in a format that the generative AI can understand is output.

[0619] Step 5:

[0620] The server sends a prompt to the generative AI model, which then processes it. The input is the prompt, and the AI ​​uses natural language generation techniques to analyze this information and generate summaries and feedback sentences. This results in optimized text data for the user.

[0621] Step 6:

[0622] The server sends the output from the generating AI back to the terminal. The terminal receives the data through a secure communication channel and performs the decryption process. The input here is encrypted response data, which is decrypted back into its original form by a dedicated decryption AI. As a result, the decrypted feedback information is output.

[0623] Step 7:

[0624] The device further refines the decoded feedback based on the emotions recognized in step 3 and presents it to the user. Decoded data and emotional information are used as input for customization to enrich the user experience. Ultimately, the user receives emotionally resonant, personalized feedback.

[0625] (Application Example 2)

[0626] Next, we will explain application example 2. In the following explanation, 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."

[0627] In modern times, text data entered by users often contains confidential or personal information, and its secure handling is essential. Furthermore, accurately recognizing user emotions from their input and providing appropriate feedback has become a critical challenge for many communication applications and security services. This invention aims to solve these problems by providing a system that securely generates and presents emotion-responsive feedback while considering the user's feelings.

[0628] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0629] In this invention, the server includes means for analyzing text information obtained from a user and identifying personal and confidential information; means for masking or encrypting the identified information; means for analyzing the masked or encrypted text information and recognizing emotions; means for shaping the recognized emotion information and masked data and generating prompts to send to a generating AI; and means for receiving feedback from the generating AI, decrypting the original information, and presenting it in a form appropriate to the emotions. This enables the secure processing of user input data while providing effective feedback tailored to their emotions.

[0630] A "user" refers to an individual who uses the system to input text information.

[0631] "Text information" refers to text data entered by users, which may contain personal information or emotions.

[0632] "Personal information" refers to information that can be used to identify a user, and includes names, addresses, and contact information.

[0633] "Confidential information" refers to important information that should not be made public, and includes business secrets and sensitive data.

[0634] "Masking" is a technique used to conceal personal or confidential information within data, thereby obscuring the true nature of the information.

[0635] "Encryption" is a technology that transforms information to prevent it from being read illegally, and is used to securely store data.

[0636] "Emotions" refer to the psychological state expressed by the user, and include types such as joy, sadness, and anger.

[0637] A "prompt" refers to formatted text data used to give instructions to a generating AI.

[0638] "Generative AI" refers to an algorithm that automatically generates feedback and content based on input data.

[0639] "Feedback" refers to replies or responses provided to users based on their emotions.

[0640] "Decryption" refers to the process of restoring encrypted information to its original format, which is done so that users can understand the data.

[0641] The system for carrying out this invention is specifically configured as follows.

[0642] First, the system receives text information entered by the user using the terminal. Because this information may contain personal or confidential data, natural language processing (NLP) technology on the terminal is used to identify this information. Software used includes natural language processing libraries (e.g., spaCy, NLTK). The identified information is then masked or encrypted by a locally running AI. For encryption, a proprietary code is used to protect the data.

[0643] Next, sentiment analysis is performed on the encrypted text. The device uses a sentiment analysis library (e.g., TextBlob) to analyze the sentiment state of the input text. The analyzed sentiment information is used to generate prompts that are sent to the generative AI model.

[0644] The generated prompt is sent by the server to the generative AI model. Based on the given prompt, the generative AI provides various feedback, summaries, or text customizations. The software used is a generative AI model (e.g., GPT-3). The server receives the response from the generative AI model and sends it to the terminal.

[0645] The device decrypts the received results and presents them to the user in a format suitable for them. This allows users to receive emotionally responsive feedback while maintaining the security of the information they entered.

[0646] For example, if a user enters text such as, "I've been feeling a lot of pressure at work lately. What are some ways to relax?", the system analyzes this text to recognize the user's emotions. It then sends a prompt to a generating AI, which generates feedback including advice to help reduce stress.

[0647] Examples of prompt statements are as follows:

[0648] "User entered the message: 'Recently, I've been experiencing increased stress from a work project. How can I relieve this stress?' Analyze the emotions the user is feeling from this message and suggest appropriate stress relief methods."

[0649] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0650] Step 1:

[0651] The user inputs text information using a terminal. The input text data is received by the terminal. This information is then prepared by the system for subsequent processing.

[0652] Step 2:

[0653] The device uses a natural language processing library to analyze text information and identify personal and confidential information. It receives text data as input, and the identified information is prepared for data masking or encryption. Through natural language processing, specific parts of the data are identified to protect user privacy.

[0654] Step 3:

[0655] A local AI within the device masks or encrypts identified personal and confidential information. It receives identified information as input and generates masked or encrypted data as output. This process ensures data protection.

[0656] Step 4:

[0657] The device uses a sentiment analysis library to analyze the sentiment of masked or encrypted text data. It receives encrypted data as input and generates data indicating the emotional state as output. Information about the emotions is analyzed, and the user's psychological state is determined.

[0658] Step 5:

[0659] The server generates prompts from sentiment information and masked data and sends them to the generative AI model. It receives sentiment information and masked text data as input and generates prompt sentences as output. These prompt sentences are sent to the generative AI model and used for content generation.

[0660] Step 6:

[0661] The generative AI model generates feedback information for the user based on prompts. It receives a prompt as input and generates feedback as output. The generative AI model creates content that is tailored to the user's emotions and needs.

[0662] Step 7:

[0663] The server receives feedback from the generated AI model and sends it to the terminal. It receives the generated feedback as input and forwards it appropriately. In this step, the information is returned to the terminal and ready to be provided to the user.

[0664] Step 8:

[0665] The device decodes the received feedback data and presents it to the user in a way that reflects their emotions. It receives feedback from the server as input and converts it into a user-understandable format as output. Based on this result, the user can decide on their next action.

[0666] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0667] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0668] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0669] [Fourth Embodiment]

[0670] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0671] As shown in Figure 7, the 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.

[0672] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0673] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0674] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0675] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0676] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0677] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0678] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0679] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0680] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0681] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0682] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0683] This information processing system is designed to securely process text data provided by users. The system is configured as follows:

[0684] First, the user inputs text data into the device. This data may contain personal or confidential information. The device uses natural language processing techniques to analyze the input text data and detect personal and confidential information within it. This could involve using regular expressions or morphological analysis.

[0685] The detected information is masked or encrypted by an artificial intelligence (AI) dedicated to encryption / masking that operates within the device. This AI identifies specific patterns and temporarily hides the information based on them. The masked data is then formatted as a prompt sent to a generating AI.

[0686] Next, the server sends this masked prompt to the generating AI. The generating AI performs the necessary tasks based on the received prompt, such as summarizing data or grammatical checking of text. The processing results are returned to the terminal via the server.

[0687] When the device receives the results of the AI ​​generation from the server, it decrypts them again using a dedicated encryption / masking AI. This restores the masked information to its original form, which is then displayed to the user as the final result.

[0688] As a concrete example, if a user enters meeting minutes, the system masks the names of participants and project names within them. Once the summary generated by the AI ​​is returned, it is decoded back into the original meeting minutes format and provided to the user. This process ensures information security while allowing users to enjoy the convenience of the AI-generated format.

[0689] The following describes the processing flow.

[0690] Step 1:

[0691] The user enters text data into the device. This text data may contain personal or confidential information.

[0692] Step 2:

[0693] The terminal receives input text data and uses natural language processing techniques to detect personal and confidential information. This involves using regular expressions to identify phone numbers and IDs, and morphological analysis to extract names of people and organizations.

[0694] Step 3:

[0695] The device uses locally running artificial intelligence to mask or encrypt any personal and confidential information it detects. Specifically, it replaces confidential portions with symbols such as "".

[0696] Step 4:

[0697] The device formats the encrypted data and prepares it as a prompt for the generating AI. The prompt is formatted to efficiently perform the target task.

[0698] Step 5:

[0699] The server receives prompts sent from the terminal and passes them to the generating AI. The data is transmitted through a secure communication channel.

[0700] Step 6:

[0701] The server receives the processing results from the generating AI and transfers them to the terminal. The generating AI provides the results of tasks such as summarization and text proofreading.

[0702] Step 7:

[0703] The terminal receives the results from the server and decrypts the original information. A dedicated encryption / masking AI handles this task, restoring the data to a state where its original meaning is understandable.

[0704] Step 8:

[0705] The device displays the decryption results to the user. The user can then decide on their next action based on the final result.

[0706] (Example 1)

[0707] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0708] In information processing systems, there is a need to guarantee the security of identifying and confidential information contained in text data provided by users, while mitigating the risk of information leakage when processing data with external generative AI models. Furthermore, in order to efficiently perform data analysis and text generation using external generative AI models, means of ensuring the secure transmission and reception of data are also necessary.

[0709] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0710] In this invention, the server includes means for analyzing character data received from a user and detecting identification information and confidential information, means for concealing or encrypting the detected information, and means for transmitting the generated concealed or encrypted data to an external generative AI model. This enables data processing that effectively utilizes an external generative AI model while ensuring data security.

[0711] A "user" is an entity that provides text data to a system and receives the processing results.

[0712] "Text data" refers to information in text format that users input into the system.

[0713] "Analysis" refers to the process used to examine textual data and identify specific information.

[0714] "Identification information" refers to information that identifies an individual or information that has a specific level of confidentiality.

[0715] "Confidential information" refers to highly sensitive information that, if made public, could result in negative consequences.

[0716] "Detection" refers to the act of confirming and identifying identifying or confidential information within text data.

[0717] "Hiding" refers to the process of converting the original information into an invisible form in order to temporarily hide the data.

[0718] "Encryption" refers to the technique of converting information into a format that cannot be read in order to protect it using a specific algorithm.

[0719] A "generative AI model" refers to artificial intelligence that generates text or performs data analysis based on input prompts.

[0720] "Communication methods" refer to methods and technologies for sending and receiving data, and include those specifically intended to ensure security.

[0721] To implement this invention, the information processing system mainly consists of a server, a terminal, and a generative AI model.

[0722] Users can input text-based character data using a terminal. The terminal has a natural language processing library (e.g., spaCy or NLTK) implemented, which is used to analyze the input character data. This analysis makes it possible to detect identifying and confidential information. Regular expressions and morphological analysis are used for this purpose.

[0723] The device has a locally running computational model to hide or encrypt detected identification and secret information. This computational model identifies specific patterns and replaces the information with placeholders to temporarily conceal it.

[0724] The masked data is prepared as a formatted prompt. This formatted prompt is sent to the generative AI model, which then performs the necessary tasks (e.g., data summarization and grammar checking).

[0725] The processing results from the generated AI model are returned to the terminal via the server. The terminal then decodes these results again using the computational model and presents the original information to the user. This allows the user to receive the final, securely processed result.

[0726] For example, if a user enters meeting minutes, this system masks the names of participants and project names within the minutes. After this process is complete, the AI-generated summary can be decoded back into its original format and provided to the user.

[0727] An example of a prompt might be, "Please summarize the meeting content. Please omit participant names and project names." This prompt is then used as input to the generating AI model, which performs the appropriate processing.

[0728] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0729] Step 1:

[0730] The user inputs text data into the terminal. For example, the user might enter meeting minutes or the body of an email into a text box. This entered text data becomes the initial data for the system to process.

[0731] Step 2:

[0732] The terminal analyzes the input character data using a natural language processing library (e.g., spaCy or NLTK). The input for analysis is the user's text data, and the output is a list of identification and secret information. This process uses regular expressions for pattern matching and morphological analysis to identify names, addresses, and other sensitive information.

[0733] Step 3:

[0734] The device hides or encrypts the detected identification and confidential information. The input is a list of information detected in step 2, which is then replaced with placeholders (e.g., "NAME" or "PROJECT") by a computational model. The output is masked character data, thus protecting the user's personal information.

[0735] Step 4:

[0736] The terminal formats the masked data into a prompt message. Formatting is performed by converting the data into a format that the generative AI model can process appropriately. The input is the masked data obtained in step 3, and the output is the formatted prompt message.

[0737] Step 5:

[0738] The server sends the formatted prompt to the generating AI model. To do this, it converts the prompt text into a format compatible with the generating AI model (e.g., an API request). The input is the prompt text formatted in step 4, and the output is the result of processing by the generating AI model.

[0739] Step 6:

[0740] The server receives the processing results from the generating AI model and sends those results to the terminal. At this stage, the input is the output of the generating AI model, and the same content reaches the user's terminal as the output.

[0741] Step 7:

[0742] The terminal decodes the processing results of the generated AI model received from the server and replaces the placeholders with the original identification information. The input is the processing results from step 6 and the identification information obtained in step 2, and the output is the decoded final data. This is displayed to the user so that the user can refer to the information.

[0743] (Application Example 1)

[0744] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0745] The objective of this invention is to safely and efficiently process text data containing personal and confidential information, while presenting users with the information they need in real time. In particular, it is necessary to balance the protection of privacy and the speed of information processing when information is provided in real time through visual devices.

[0746] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0747] In this invention, the server includes means for analyzing text data received from a user to detect personal and confidential information, means for masking or encrypting the detected information, means for transmitting the generated masked or encrypted data to an external generating AI, and means for receiving the processing results from the generating AI and decrypting the original information. This enables the provision of accurate information in real time while protecting personal information.

[0748] A "user" is a person who provides text data using a specific information processing system and receives the results.

[0749] "Text data" refers to a collection of information entered as text, which may include personal or confidential information.

[0750] "Personal information" refers to information that can identify a specific individual, such as name and address.

[0751] "Confidential information" refers to information that is not publicly available and is important data for a particular organization or individual.

[0752] "Masking" is a technique used to conceal or hide personal or confidential information.

[0753] "Encryption" is a method of converting data from a decryptable format to an unreadable format to prevent unauthorized access by third parties.

[0754] "Generative AI" is an artificial intelligence technology that automatically generates text and information based on given input.

[0755] "Decryption" is the process of returning encrypted data to its original, decryptable format.

[0756] "Visual devices" are hardware that displays information visually, and include smart glasses, among other things.

[0757] "Real-time" means processing or providing information immediately, and presenting results to users without delay.

[0758] The system for carrying out this invention mainly consists of a server, a user terminal, and a visual device (e.g., smart glasses). A specific embodiment is described below.

[0759] First, the user inputs text data using a visual device. This text data is received by the user's terminal and analyzed using a natural language processing (NLP) library (e.g., spaCy, NLTK). This analysis triggers an AI model (e.g., a custom OpenAI GPT model) to identify personal and confidential information and then mask or encrypt it.

[0760] Next, the user terminal generates a prompt to send the masked data to the generative AI model. This communication takes place using an encrypted channel between the server and a cloud-based generative AI service (e.g., OpenAI GPT-3, Google AI API). Based on the received prompt, the generative AI performs the specified information processing (e.g., summarization, grammar correction) and returns the result to the server.

[0761] The server sends the received processing results to the user's terminal and performs the demasking process again. The visual device displays the decoded results to the user in real time. This allows the user to immediately access the information in a privacy-protected manner.

[0762] As a concrete example, in a corporate business meeting, if a user is using smart glasses to view agenda materials, the key points will be displayed in a summarized form while protecting personal names and project names.

[0763] An example of a prompt message is, "Summarize the contents of this text and output it with confidential information masked." This system makes it possible to process and present important data quickly while maintaining information security.

[0764] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0765] Step 1:

[0766] The user inputs text data using a visual device. The user terminal receives this text data and records it as input data. This input data may contain personal or confidential information.

[0767] Step 2:

[0768] The terminal uses a natural language processing library (e.g., spaCy, NLTK) to parse the received text data. Morphological analysis and regular expressions are applied to the input text data to detect personal and sensitive information within the data. This analysis identifies data that needs to be masked or encrypted.

[0769] Step 3:

[0770] The device processes detected personal and confidential information using an AI model (e.g., a custom OpenAI GPT model) to mask or encrypt it. The input is the information identified through analysis, and the output is masked data. This masking process protects the data from unauthorized access by third parties.

[0771] Step 4:

[0772] The device generates a prompt for the generative AI from the masked data. In this process, it formats the prompt text and sends it to a cloud-based generative AI service using an encrypted communication channel. The input is masked data, and the output is the formatted prompt text.

[0773] Step 5:

[0774] The server receives the results processed by the generative AI in the cloud. These results include the output of the information processing performed by the generative AI based on the prompt. The input is the formatted prompt, and the output is the processed result.

[0775] Step 6:

[0776] The terminal decodes the processing results of the generating AI received from the server. Simultaneously, it removes the masking to reconstruct the original information. The input is the processing result of the generating AI, and the output is the decoded result.

[0777] Step 7:

[0778] A visual device displays the decoded results to the user in real time. The processed information is presented visually, allowing the user to view the necessary information. The input is the decoded result, and the output is the visually displayed information.

[0779] By ensuring that the data entered at each step is properly processed or calculated and prepared for the next step, users can receive the necessary information safely and quickly. This entire process enables real-time information delivery while maintaining the protection of personal information.

[0780] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0781] This invention is an information processing system that securely processes text data entered by a user, recognizes the user's emotions within that data, and generates appropriate feedback. The system is configured as follows:

[0782] First, the user enters text data into the device. Because this data may contain personal or confidential information, the device uses natural language processing technology to detect it. The detected information is then masked or encrypted by a dedicated artificial intelligence operating within the device. This AI identifies the information and uses codes to protect the data.

[0783] Next, the device receives the masked text and uses its emotion engine to recognize the user's emotional state. This emotion engine analyzes the context and tone of the text to determine whether the user is happy, angry, or sad.

[0784] The terminal then formats the recognized emotion information and masked data, preparing it as a prompt for the generative AI. The server sends the formatted prompt to the generative AI. Based on the received prompt, the generative AI summarizes the data, generates a customized response based on emotion, or performs grammatical checks on the text.

[0785] The server receives the results from the generating AI and transfers them to the terminal. After receiving the results, the terminal uses a dedicated encryption / masking AI to decrypt the original information. Furthermore, the generated results are adjusted to the user's emotions and presented in the most appropriate format for the user.

[0786] For example, if a user enters a text message about stress, the system senses the user's stress level and instructs the AI ​​to summarize the message and generate appropriate advice. Finally, the device decodes the advice and provides the user with recommendations to help reduce stress. This allows for secure data processing and the provision of valuable information while considering the user's emotions.

[0787] The following describes the processing flow.

[0788] Step 1:

[0789] The user enters text data into the device. For example, the user enters the sentence, "I've been feeling stressed out by my recent projects."

[0790] Step 2:

[0791] The terminal receives the entered text data and uses natural language processing technology to detect personal and confidential information within it. For example, it identifies the term "project."

[0792] Step 3:

[0793] The device uses locally running artificial intelligence to mask or encrypt any sensitive information it detects. This temporarily protects the data, for example, by replacing "project" with "".

[0794] Step 4:

[0795] The device passes encrypted text to an emotion engine, which analyzes the user's emotional state. In this case, the engine recognizes from the text that the user is experiencing stress.

[0796] Step 5:

[0797] The device combines emotional information with encrypted text and formats it as a prompt for the generating AI. This prompt may include the fact that the user is feeling stressed.

[0798] Step 6:

[0799] The server receives a prompt sent from the terminal and forwards it to the generating AI. This prompt includes instructions for generating a response that is tailored to the user's emotional state.

[0800] Step 7:

[0801] The generating AI processes prompts and produces output results tailored to the user's emotions, such as advice for stress relief.

[0802] Step 8:

[0803] The server receives the output from the generated AI and sends it back to the terminal.

[0804] Step 9:

[0805] The device decrypts the results received from the server back into the original data and then makes adjustments based on the user's emotional state. For example, it might be formatted to say, "You may be feeling stressed, but please try the following to relax."

[0806] Step 10:

[0807] The device presents the final results to the user and provides advice from the generated AI in a usable format. The user can then implement stress management strategies based on the information provided.

[0808] (Example 2)

[0809] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0810] In information processing systems, when text data entered by users contains personal or confidential information, it is necessary to securely protect that information while simultaneously accurately recognizing the user's emotions and providing appropriate feedback. However, conventional systems face the challenge of balancing information protection with accurate emotion recognition. Furthermore, advanced text processing using generative AI models requires a secure and efficient method of data transmission.

[0811] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0812] In this invention, the server includes means for analyzing textual information received from a user and detecting personally identifiable information and confidential information, means for masking or encrypting the detected information, and means for an engine for recognizing the emotional state based on the masked text. This makes it possible to provide feedback that corresponds to the user's emotional state while protecting personal information.

[0813] "Textual information" refers to data in text format entered by users, and is subject to natural language processing.

[0814] "Personally identifiable information" refers to information that can identify an individual user, including their name, address, and contact information.

[0815] "Confidential information" refers to information that is not publicly available and is considered highly sensitive data for a particular organization or individual.

[0816] "Masking" is a process that makes personally identifiable information or confidential information unidentifiable by replacing it with information based on certain rules.

[0817] "Encryption" is the process of transforming data using a specific algorithm to make it a format that cannot be easily understood by a third party.

[0818] "Emotional state" refers to the psychological state extracted from the text information entered by the user, and includes classifications such as positive, negative, and neutral.

[0819] A "generative model" refers to artificial intelligence technology that has the ability to generate natural language by learning from large amounts of data.

[0820] A "communication channel" is a transmission path used by the server and the generative model to send and receive data, and it must be encrypted to ensure security.

[0821] This invention is an information processing system that securely processes text information entered by a user, recognizes emotions within that information, and generates appropriate feedback. The system utilizes the following hardware and software.

[0822] The user inputs text information into the terminal. This terminal is equipped with a natural language processing engine and encryption technology. The natural language processing engine analyzes the text information entered by the user to identify personally identifiable and confidential information. Common programming languages ​​and libraries, such as Python and its natural language processing library, are used for the analysis. After detecting confidential information, a dedicated AI is used to mask or encrypt the data. This AI operates within the terminal and uses standard encryption techniques, such as AES encryption.

[0823] Next, the device uses an emotion engine to identify the user's emotional state from the masked text information. This process utilizes deep learning models, such as BERT or RoBERTa, to analyze emotions from the context and tone of the text. The extracted emotional information and masked data are then formatted as prompts and sent to a generative AI model. The server receives the prompts and communicates with the external generative AI in real time. A secure communication channel is established for this communication, using encryption protocols such as SSL / TLS.

[0824] The generative AI model performs various text processing tasks based on the received prompts. For example, it summarizes user input and generates emotionally appropriate advice and feedback. This generated information is returned to the device via the server, where it is decrypted again using encryption / masking AI. Finally, the results are adjusted to the user's emotions and displayed to the user in the most optimal form.

[0825] As a concrete example, consider a scenario where a user inputs, "I'm feeling stressed and depressed." The system analyzes this information and recognizes the negative emotion of stress. It then sends a prompt to a generative AI model regarding "specific ways to relax," generating appropriate advice. Finally, the device decodes this advice and provides feedback in a format easily understood by the user. This process allows users to receive support tailored to their individual needs.

[0826] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0827] Step 1:

[0828] The user inputs text information on the terminal. This text information is then analyzed by a natural language processing engine. Raw string data is used as input for the analysis. The engine tokenizes the input text, analyzes the sentence structure, and extracts personal identification information and sensitive information. As a result, the extracted sensitive information is output.

[0829] Step 2:

[0830] The device processes the personally identifiable and confidential information extracted in Step 1 using a dedicated AI, performing masking or encryption. The input consists of identified sensitive information, and an appropriate masking pattern or encryption algorithm (e.g., AES encryption) is applied according to the importance and type of the information. As a result, protected data is output.

[0831] Step 3:

[0832] The device processes masked text information using an emotion engine to analyze the user's emotional state. The input in this step is masked text information. A deep learning model (e.g., BERT) is used to extract context and emotional characteristics from individual words and their combinations. This analysis outputs specific emotional labels (e.g., positive, negative).

[0833] Step 4:

[0834] The device integrates the emotion information obtained in step 3 with the masked data to create a prompt message to send to the generative AI model. This creation process is performed by using the emotion labels and masked data as input and applying them to a prompt template. As a result, a prompt message in a format that the generative AI can understand is output.

[0835] Step 5:

[0836] The server sends a prompt to the generative AI model, which then processes it. The input is the prompt, and the AI ​​uses natural language generation techniques to analyze this information and generate summaries and feedback sentences. This results in optimized text data for the user.

[0837] Step 6:

[0838] The server sends the output from the generating AI back to the terminal. The terminal receives the data through a secure communication channel and performs the decryption process. The input here is encrypted response data, which is decrypted back into its original form by a dedicated decryption AI. As a result, the decrypted feedback information is output.

[0839] Step 7:

[0840] The device further refines the decoded feedback based on the emotions recognized in step 3 and presents it to the user. Decoded data and emotional information are used as input for customization to enrich the user experience. Ultimately, the user receives emotionally resonant, personalized feedback.

[0841] (Application Example 2)

[0842] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0843] In modern times, text data entered by users often contains confidential or personal information, and its secure handling is essential. Furthermore, accurately recognizing user emotions from their input and providing appropriate feedback has become a critical challenge for many communication applications and security services. This invention aims to solve these problems by providing a system that securely generates and presents emotion-responsive feedback while considering the user's feelings.

[0844] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0845] In this invention, the server includes means for analyzing text information obtained from a user and identifying personal and confidential information; means for masking or encrypting the identified information; means for analyzing the masked or encrypted text information and recognizing emotions; means for shaping the recognized emotion information and masked data and generating prompts to send to a generating AI; and means for receiving feedback from the generating AI, decrypting the original information, and presenting it in a form appropriate to the emotions. This enables the secure processing of user input data while providing effective feedback tailored to their emotions.

[0846] A "user" refers to an individual who uses the system to input text information.

[0847] "Text information" refers to text data entered by users, which may contain personal information or emotions.

[0848] "Personal information" refers to information that can be used to identify a user, and includes names, addresses, and contact information.

[0849] "Confidential information" refers to important information that should not be made public, and includes business secrets and sensitive data.

[0850] "Masking" is a technique used to conceal personal or confidential information within data, thereby obscuring the true nature of the information.

[0851] "Encryption" is a technology that transforms information to prevent it from being read illegally, and is used to securely store data.

[0852] "Emotions" refer to the psychological state expressed by the user, and include types such as joy, sadness, and anger.

[0853] A "prompt" refers to formatted text data used to give instructions to a generating AI.

[0854] "Generative AI" refers to an algorithm that automatically generates feedback and content based on input data.

[0855] "Feedback" refers to replies or responses provided to users based on their emotions.

[0856] "Decryption" refers to the process of restoring encrypted information to its original format, which is done so that users can understand the data.

[0857] The system for carrying out this invention is specifically configured as follows.

[0858] First, the system receives text information entered by the user using the terminal. Because this information may contain personal or confidential data, natural language processing (NLP) technology on the terminal is used to identify this information. Software used includes natural language processing libraries (e.g., spaCy, NLTK). The identified information is then masked or encrypted by a locally running AI. For encryption, a proprietary code is used to protect the data.

[0859] Next, sentiment analysis is performed on the encrypted text. The device uses a sentiment analysis library (e.g., TextBlob) to analyze the sentiment state of the input text. The analyzed sentiment information is used to generate prompts that are sent to the generative AI model.

[0860] The generated prompt is sent by the server to the generative AI model. Based on the given prompt, the generative AI provides various feedback, summaries, or text customizations. The software used is a generative AI model (e.g., GPT-3). The server receives the response from the generative AI model and sends it to the terminal.

[0861] The device decrypts the received results and presents them to the user in a format suitable for them. This allows users to receive emotionally responsive feedback while maintaining the security of the information they entered.

[0862] For example, if a user enters text such as, "I've been feeling a lot of pressure at work lately. What are some ways to relax?", the system analyzes this text to recognize the user's emotions. It then sends a prompt to a generating AI, which generates feedback including advice to help reduce stress.

[0863] Examples of prompt statements are as follows:

[0864] "User entered the message: 'Recently, I've been experiencing increased stress from a work project. How can I relieve this stress?' Analyze the emotions the user is feeling from this message and suggest appropriate stress relief methods."

[0865] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0866] Step 1:

[0867] The user inputs text information using a terminal. The input text data is received by the terminal. This information is then prepared by the system for subsequent processing.

[0868] Step 2:

[0869] The device uses a natural language processing library to analyze text information and identify personal and confidential information. It receives text data as input, and the identified information is prepared for data masking or encryption. Through natural language processing, specific parts of the data are identified to protect user privacy.

[0870] Step 3:

[0871] A local AI within the device masks or encrypts identified personal and confidential information. It receives identified information as input and generates masked or encrypted data as output. This process ensures data protection.

[0872] Step 4:

[0873] The device uses a sentiment analysis library to analyze the sentiment of masked or encrypted text data. It receives encrypted data as input and generates data indicating the emotional state as output. Information about the emotions is analyzed, and the user's psychological state is determined.

[0874] Step 5:

[0875] The server generates prompts from sentiment information and masked data and sends them to the generative AI model. It receives sentiment information and masked text data as input and generates prompt sentences as output. These prompt sentences are sent to the generative AI model and used for content generation.

[0876] Step 6:

[0877] The generative AI model generates feedback information for the user based on prompts. It receives a prompt as input and generates feedback as output. The generative AI model creates content that is tailored to the user's emotions and needs.

[0878] Step 7:

[0879] The server receives feedback from the generated AI model and sends it to the terminal. It receives the generated feedback as input and forwards it appropriately. In this step, the information is returned to the terminal and ready to be provided to the user.

[0880] Step 8:

[0881] The device decodes the received feedback data and presents it to the user in a way that reflects their emotions. It receives feedback from the server as input and converts it into a user-understandable format as output. Based on this result, the user can decide on their next action.

[0882] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0883] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0884] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0885] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0886] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0887] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0888] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0889] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0890] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0891] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0892] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0893] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0894] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0895] 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.

[0896] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0897] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0898] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0899] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0900] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0901] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0902] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0903] The following is further disclosed regarding the embodiments described above.

[0904] (Claim 1)

[0905] A means of analyzing text data received from users to detect personal and confidential information,

[0906] Means for masking or encrypting detected information,

[0907] A means for sending the generated masked or encrypted data to an external generation AI,

[0908] A means of receiving the processing results from the generating AI and decrypting the original information,

[0909] A means of presenting the decrypted result to the user,

[0910] An information processing system that includes this.

[0911] (Claim 2)

[0912] The information processing system according to claim 1, characterized by comprising locally operating artificial intelligence for performing data masking or encryption.

[0913] (Claim 3)

[0914] The information processing system according to claim 1, characterized by using an encrypted communication channel for securely transmitting and receiving data to and from the generating AI.

[0915] "Example 1"

[0916] (Claim 1)

[0917] A means for analyzing text data received from a user and detecting identification information and confidential information,

[0918] Means for concealing or encrypting detected information,

[0919] A means for sending the generated hidden or encrypted data to an external generation AI model,

[0920] A means of receiving the processing results from a generative AI model and decrypting the original information,

[0921] A means of presenting the decrypted result to the user,

[0922] A data processing system that includes this.

[0923] (Claim 2)

[0924] The data processing system according to claim 1, characterized by comprising a locally operating computational model for performing data concealment or encryption.

[0925] (Claim 3)

[0926] The data processing system according to claim 1, characterized by using encrypted communication means for securely transmitting and receiving data to and from a generated AI model.

[0927] "Application Example 1"

[0928] (Claim 1)

[0929] A means of analyzing text data received from users to detect personal and confidential information,

[0930] Means for masking or encrypting detected information,

[0931] A means for sending the generated masked or encrypted data to an external generation AI,

[0932] A means of receiving the processing results from the generating AI and decrypting the original information,

[0933] A means of presenting the decrypted result to the user,

[0934] Means for displaying information in a visual device,

[0935] Means for real-time data processing,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, characterized by comprising locally operating artificial intelligence for performing data masking or encryption.

[0939] (Claim 3)

[0940] The system according to claim 1, characterized by using an encrypted communication channel for securely transmitting and receiving data to and from the generating AI.

[0941] "Example 2 of combining an emotion engine"

[0942] (Claim 1)

[0943] A means for analyzing textual information received from a user and detecting personally identifiable information and confidential information,

[0944] Means for masking or encrypting detected information,

[0945] A means equipped with an engine for recognizing emotional states based on masked text,

[0946] A means for transmitting generated masked or encrypted data and emotional information to an external generative model,

[0947] A means of receiving the processing results from the generative model and decrypting the original information,

[0948] A means of adjusting the decrypted results to match the user's emotions and presenting them to the user,

[0949] A system that includes this.

[0950] (Claim 2)

[0951] The system according to claim 1, characterized by having locally operating machine intelligence for performing data masking or encryption.

[0952] (Claim 3)

[0953] The system according to claim 1, characterized by using an encrypted communication channel for securely transmitting and receiving data to and from a generative model.

[0954] "Application example 2 when combining with an emotional engine"

[0955] (Claim 1)

[0956] A means of analyzing text information obtained from users to identify personal and confidential information,

[0957] Means for masking or encrypting identified information,

[0958] A means of analyzing masked or encrypted text information to recognize emotions,

[0959] A means for formatting recognized emotional information and masked data, and generating prompts to send to a generative AI,

[0960] A means of receiving feedback from a generating AI, decrypting the original information, and presenting it in a way that responds to emotions,

[0961] A system that includes this.

[0962] (Claim 2)

[0963] The system according to claim 1, characterized by comprising artificial intelligence operating in a local environment for masking or encrypting data.

[0964] (Claim 3)

[0965] The system according to claim 1, characterized in that it uses an encrypted communication path to securely send and receive data to and from the generating AI. [Explanation of Symbols]

[0966] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of analyzing text data received from users to detect personal and confidential information, Means for masking or encrypting detected information, A means for sending the generated masked or encrypted data to an external generation AI, A means of receiving the processing results from the generating AI and decrypting the original information, A means of presenting the decrypted result to the user, An information processing system that includes this.

2. The information processing system according to claim 1, characterized by comprising locally operating artificial intelligence for performing data masking or encryption.

3. The information processing system according to claim 1, characterized by using an encrypted communication channel for securely transmitting and receiving data to and from the generating AI.

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