system

Abstract

We provide the system. [Solution] Means of receiving information, A means for analyzing received information and detecting confidential and personal information, A means to automatically replace or delete detected confidential and personal information, A means of sending the processed information to an external service, A means of recording the processing steps, 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 persona chatbot control method 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When using generative AI services, many companies are concerned about the risk of leakage of confidential information and personal information to the outside. Therefore, manual confirmation and editing are required for information transmission, resulting in a problem of significantly reducing the efficiency of information utilization. The present invention aims to reduce the risk of leakage of such confidential information and personal information and enable efficient information utilization.

Means for Solving the Problems

[0005] The information processing system according to the present invention includes means for receiving information, means for analyzing the received information and detecting confidential information and personal information, means for automatically replacing or deleting the detected information, means for transmitting the processed information to an external service, and means for recording the processing process. This reduces the risk of leakage of confidential information and personal information and enables the safe and efficient use of the generated AI service.

[0006] "Means of receiving information" refers to functions that take in information entered by the user into the system.

[0007] "Means of information analysis" refers to the function of using technologies to analyze received information and detect confidential and personal information.

[0008] "Means for detecting confidential and personal information" refers to a function that identifies highly confidential data based on specific patterns from analyzed information.

[0009] "Means for automatically replacing or deleting confidential and personal information" refers to a function that replaces or deletes detected data according to a pre-configured format.

[0010] "Means for transmitting processed information to external services" refers to a function that securely transmits data to external AI generation services while appropriately masking confidential and personal information.

[0011] "Means for recording the processing process" refers to a function that records a series of processes performed by the system as a log, making them available for later review. [Brief explanation of the drawing]

[0012] [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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It 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 Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, the labeled 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.

[0016] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] The information processing system of this invention operates within a closed network within a company and is designed to reduce the risk of information leakage. The main components of the system are a server and terminals. The operation of the system is described in detail below in natural language.

[0034] First, the user inputs the document or data they want to send to the AI ​​generation service into their device. This input data is sent to the server in its original form.

[0035] Before forwarding the received information, the server prepares it for analysis on the terminal. At this stage, the data is still raw and untouched.

[0036] Next, the terminal analyzes the received information using natural language processing technology. The terminal stores pattern lists and dictionaries for detecting confidential and personal information, and uses these to scan the information. As a result of the analysis, confidential information such as names, addresses, and phone numbers is listed.

[0037] The detected information is automatically replaced or deleted by the device. For example, if the name "Taro Tanaka" is included, it will be replaced with "Name". Similarly, if it is a phone number, it will be replaced with "Phone Number". This prevents confidential information from being leaked to the outside.

[0038] The securely processed information is returned to the server and then sent to an external AI generation service. At this point, all information being sent is anonymized or masked, so there is no risk of leakage.

[0039] The information processing process and replacement details are recorded on the terminal. Each process is time-stamped, allowing for quick investigation by referring to the logs if a problem occurs.

[0040] For example, if a user wants to have an AI proofread a report, security policies may prevent them from directly naming the AI. In this case, the system can be used to securely process the information and receive the proofreading results from the AI.

[0041] In this way, this system automates information processing and enables the secure utilization of AI resources without leaking confidential corporate information to external parties.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user inputs the documents or data they want to send to the generation AI service and sends it to their device. This information arrives on the server in its raw, unprocessed state.

[0045] Step 2:

[0046] The server sends the information received from the user back to the terminal as is, preparing it for analysis. At this point, no processing has been done yet.

[0047] Step 3:

[0048] The terminal activates its natural language processing engine and begins analyzing the received information. The analysis uses internal keyword lists and patterns to identify confidential and personal information, such as names, addresses, and phone numbers.

[0049] Step 4:

[0050] The device automatically replaces or deletes information detected during analysis. Specifically, detected names are replaced with a placeholder labeled "Name," and phone numbers are similarly converted to "Phone Number." This anonymizes the information.

[0051] Step 5:

[0052] The terminal sends the securely processed information back to the server. At this point, the information is handled securely.

[0053] Step 6:

[0054] The server sends the anonymized information received from the terminal to a designated AI generating service. All personally identifiable information is removed from the information sent externally.

[0055] Step 7:

[0056] The server receives responses from the AI ​​generation service and returns the results to the user. This makes it possible to use the AI ​​results while maintaining confidentiality.

[0057] Step 8:

[0058] The terminal records the processing flow as a log. The log includes the start and end times of the process, and the type of information replaced. The log can be used for auditing and troubleshooting.

[0059] (Example 1)

[0060] 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."

[0061] In modern information processing, the risk of confidential and personal data being leaked to external parties is increasing. Especially when using AI generation technology within a company, there is a possibility that confidential information may be sent to external services, making security crucial. To address this problem, a system is needed that reliably anonymizes data during the information processing stage, thereby reducing the risk of leakage.

[0062] 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.

[0063] In this invention, the server includes a device for receiving information, a device for analyzing the received information and detecting confidential data and personal data, and a device for automatically replacing or deleting the detected confidential data and personal data. This enables companies and organizations to securely anonymize confidential data and reduce the risk of information leakage while utilizing external generative AI technology.

[0064] A "device for receiving information" refers to a function or device for receiving data entered by a user or data transmitted from an external source.

[0065] A "device for analyzing received information and detecting confidential and personal data" refers to a function or device that analyzes received data and automatically identifies highly confidential information or data that can identify a specific individual.

[0066] A "device for automatically replacing or deleting detected confidential and personal data" refers to a function or device that automatically replaces or deletes confidential and personal information identified through analysis, preventing it from being leaked externally.

[0067] A "device for transmitting anonymized or masked information to external technology" refers to a function or device for securely transmitting data that has been appropriately processed to external AI generation technology.

[0068] A "device for recording the processing process and adding time information" refers to a function or device that records each step of data processing in detail and adds information about the processing time, thereby facilitating later verification and auditing.

[0069] "Natural language processing technology" refers to a set of techniques that enable computers to understand and analyze human language, particularly those used to extract information from text.

[0070] An "identifier" is a placeholder or symbol used to represent specific data, and is typically used when confidential or personal data is being replaced.

[0071] This invention is an information processing system for utilizing generative AI technology while securely managing confidential and personal information within a company's closed network. The main components of the system are a server and terminals.

[0072] The server receives data sent from the user. Data reception is securely performed using a network protocol with HTTPS communication. This data is then transferred from the server to the terminal, and preparation for analysis begins. At this stage, the data is unmodified and in its raw state.

[0073] The device utilizes natural language processing (NLP) technology to analyze received data. Specifically, it uses NLP libraries based on Python (e.g., spaCy and NLTK) to automatically scan and detect confidential and personal information within text data. The device has pre-stored pattern lists and dictionaries for identifying confidential and personal data, and performs data analysis based on these.

[0074] The system automatically replaces or deletes any detected confidential or personal data. For example, if a name is included in the text, it will be replaced with the identifier "Name." Similarly, a phone number will be replaced with "Phone Number." This feature allows for the transmission of confidential information to external AI-generated services while maintaining its confidentiality.

[0075] The processed information is returned to the server and then sent to the AI ​​generation service. During this process, the transmitted information is in a masked format, establishing a secure foundation for using the AI ​​service.

[0076] A concrete example for users might be wanting to have a report proofread by the AI ​​generator. If a report containing specific personal information cannot be sent directly due to security policies, the information can be securely processed through this system.

[0077] An example of a prompt message that can be sent to the generating AI is: "Please proofread the following document. The document contains personal information such as names and phone numbers, but this information has already been anonymized."

[0078] Thus, the present invention provides a specific information processing method for efficiently and safely utilizing generated AI resources.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The user inputs the documents or data they want to send to the AI ​​generation service into their device. This input is done via keyboard or file upload function. The input data is in text format, and the device receives and temporarily stores it. The input data is then prepared to be sent to the server in its original form.

[0082] Step 2:

[0083] The server receives text data sent from the terminal. Upon receipt, checksum and data validation processes are applied to verify the integrity of the data. Once the integrity of the data is confirmed, it is ready to send instructions to the terminal for analysis. The output is the analysis instructions transmitted to the terminal.

[0084] Step 3:

[0085] The terminal receives instructions from the server and begins processing the received text data for analysis. This analysis employs natural language processing techniques, using Python's NLP library (e.g., spaCy or NLTK). The input is the text data received from the server, and the output of the analysis is a list of identified confidential or personal information.

[0086] Step 4:

[0087] Detected confidential or personal information is automatically replaced or deleted by the device. For example, listed names are replaced with the identifier "Name," and phone numbers with the identifier "Phone Number." This conversion is performed based on a predefined pattern list within the device. The output is the replaced, anonymized data.

[0088] Step 5:

[0089] The anonymized data is sent back to the server. The server then prepares to send the data to an external generative AI service. Before sending, a prompt is created, for example, "Please proofread the following document. The name and phone number in the document contain personal information, but it has already been anonymized." The output is the data sent to the generative AI service along with the prompt.

[0090] Step 6:

[0091] The server records logs of the information processing process and replacement details, complete with timestamps. These logs serve as crucial information for later verification and troubleshooting. Detailed processing logs are generated and stored as output.

[0092] (Application Example 1)

[0093] 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."

[0094] In modern information and communication, the risk of confidential and personal information being leaked during message exchanges is a significant concern. There is a need for methods to reduce this risk of information leakage while securely and efficiently linking information to external services.

[0095] 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.

[0096] In this invention, the server includes means for receiving information, means for analyzing the received information and detecting confidential and personal information, and communication means for anonymizing confidential information in real time. This makes it possible to share information with external services quickly and securely while reducing the risk of information leakage.

[0097] "Means of receiving information" refers to a function for taking in information transmitted from external or internal sources in data format.

[0098] "Means for analyzing received information and detecting confidential and personal information" refers to a function that analyzes the received information and identifies highly confidential data and personal information that requires protection.

[0099] "Means for automatically replacing or deleting detected confidential and personal information" refers to a function that automatically converts or deletes identified confidential and personal information into an anonymized form in order to protect it.

[0100] "Means for transmitting processed information to external services" refers to a function for transferring information that has been securely processed internally to an external service or system using an appropriate protocol.

[0101] "Means for recording the processing process" refers to a function for tracking how information was processed and saving it so that it can be analyzed and verified later.

[0102] A "communication method that anonymizes confidential information in real time" is a function that performs a conversion to maintain confidentiality immediately and without delay when messages or information are exchanged.

[0103] "A means of securely transmitting anonymized information" refers to a controlled communication function that delivers anonymized information to external recipients without risk.

[0104] In this system, the user first uses a smart device to input a message or information. This input information is processed in real time within the device. The device uses natural language processing technology to analyze the input information. Specific software used here includes natural language processing libraries such as spaCy and NLTK.

[0105] The analyzed information is scanned to identify confidential and personal information. Detected information is automatically replaced or deleted using predefined placeholders. After this anonymization process, the processed information is sent to a server. The server then delivers this information to external AI-generating services, but because it is anonymized, the risk of information leakage is low.

[0106] In terms of hardware, devices such as smartphones and smart glasses that have the functionality to receive, analyze, anonymize, and transmit information are used. These devices interact with servers via an internet connection.

[0107] For example, if a user wants to create a meeting summary and share it with team members, this system allows for automatic editing and summarization by AI, with speakers' names and confidential information anonymized.

[0108] Example of a prompt:

[0109] Parse the input message and replace sensitive information, including names and phone numbers, with tags:

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The user enters a message or information into a smart device. The entered data is captured raw within the device. In this step, the user enters a meeting summary or message, which the device receives as digital data.

[0113] Step 2:

[0114] The terminal analyzes the input information. Specifically, it uses natural language processing technology to identify confidential and personal information within the data. The input document is segmented, and data processing is performed based on specific keywords.

[0115] Step 3:

[0116] The device automatically replaces or deletes any confidential or personal information detected as a result of the analysis. Here, placeholders (e.g., "Name," "Phone Number") are used to anonymize the information. Information identified from the original input text is replaced with placeholders, enhancing the security of the information.

[0117] Step 4:

[0118] The anonymized information is returned from the terminal to the server. At this stage, the output is securely processed information. The server verifies that the information has been properly anonymized and prepares for the next step.

[0119] Step 5:

[0120] The server sends information to an external generative AI service. In this process, the server transfers information according to a predefined protocol. The output is anonymized information that is securely delivered to the generative AI service, reducing the risk of information leakage.

[0121] Step 6:

[0122] The server records the processing steps. Each processed piece of information is accompanied by a timestamp and change history, and a log is stored. The log is saved in a format that allows for future reference.

[0123] 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.

[0124] This invention provides a system for effectively processing information within a corporate network while ensuring the security of confidential and personal information by recognizing the user's emotions. This system consists of a server, terminals, and an emotion engine.

[0125] When a user uses the AI-generated service, they input information into their device. The device is equipped with an emotion engine that analyzes the user's input and context to recognize the user's emotions. This emotional information is then classified by the emotion engine as "joy," "sadness," "anger," etc.

[0126] Once information is sent to the server, it receives it and adjusts the response to an appropriate one based on the analysis results of the emotion engine. For example, if the user's input indicates anger, the system will generate a response in a calm tone.

[0127] The device then analyzes the information and detects confidential and personal information. Detected elements are automatically replaced with predefined placeholders, making it impossible to identify individuals. This processed information is then securely transmitted again via the server to an external AI generation service.

[0128] As a concrete example, suppose a user enters a document expressing dissatisfaction with an error message. The emotion engine recognizes this as "dissatisfaction," and the device prepares thoughtful feedback that takes the user's emotions into consideration. Personal information in the text is then appropriately replaced and sent to an external AI service. As a result, the user receives a safe and emotionally appropriate response.

[0129] This invention seamlessly integrates the processes of emotion recognition and information masking, enabling the safe and efficient use of generative AI within enterprises. This reduces the risk of information leakage and improves the user experience.

[0130] The following describes the processing flow.

[0131] Step 1:

[0132] The user inputs a document into the terminal as input for the AI ​​generation service. This document may take various forms, such as opinions, impressions, or inquiries.

[0133] Step 2:

[0134] The device sends the input information to an emotion engine, which analyzes the user's emotions. Here, the emotion engine uses natural language processing technology to analyze the text and identify emotional categories such as "joy," "sadness," and "anger."

[0135] Step 3:

[0136] After receiving the sentiment analysis results, the device then analyzes the content of the information to detect confidential and personal information. This process involves scanning the information using pre-configured patterns and keyword lists to find entries that fit a specific format (such as names, addresses, and phone numbers).

[0137] Step 4:

[0138] The device replaces detected confidential information with placeholders (e.g., "Name" or "Phone Number"). This prevents personal information from being explicitly displayed when data is sent to the generating AI service.

[0139] Step 5:

[0140] Based on the sentiment analysis results and anonymized information, the server generates a response. If the user expresses dissatisfaction or anger, the system maintains composure and prepares a response using a considerate tone.

[0141] Step 6:

[0142] The server sends internally generated responses and securely processed information to the AI ​​service. At this stage, all data is anonymized, minimizing the risk of external leakage.

[0143] Step 7:

[0144] The server, having received a response from the AI ​​generation service, returns the result to the user as feedback. The user receives a clean and considerate response, experiencing that their feelings have been taken into account.

[0145] Step 8:

[0146] At every processing step, the terminal logs the process details. The log includes the start and end times of the process, replaced information, and recognized sentiment categories. This record can be used later for audits and system improvements.

[0147] (Example 2)

[0148] 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".

[0149] In corporate information processing, there is a need to appropriately understand user emotions and provide responses accordingly, while securely handling confidential and personal information. However, conventional systems have insufficient emotion recognition and fail to adjust tone, sometimes resulting in inappropriate responses to users. Furthermore, there have been challenges such as incomplete detection and protection of confidential and personal information, creating a risk of information leakage.

[0150] 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.

[0151] In this invention, the server includes means for receiving information, means for analyzing the received information and recognizing an individual's emotions, and means for adjusting the response content based on the recognized emotions. This enables the provision of an appropriate response that takes the user's emotions into consideration, as well as the secure processing of confidential and personal information.

[0152] "Means of receiving information" refers to a device or process that has the ability to take in data sent from an external source.

[0153] A "means for recognizing individual emotions" refers to a device or process that has the ability to analyze user input information and identify emotional states or intentions from that information.

[0154] "Means for adjusting response content based on recognized emotions" refers to a device or process that has the ability to optimize the content and tone of the generated response using detected emotion information.

[0155] "Means for detecting confidential and personal information in analysis" refers to devices or processes that have the capability to find sensitive data contained within received information.

[0156] "Means for automatically replacing or deleting with predefined abstract elements" refers to a device or process that has the ability to convert detected confidential or personal information into pre-configured, non-individual elements, or to delete them.

[0157] "Means for sending to an external computing service" refers to a device or process that has the ability to transfer processed data to a connected external computing resource.

[0158] "Means for recording the processing process" refers to a device or process that has the ability to save each step in which data is processed.

[0159] "Natural language processing technology" refers to algorithms and methods for understanding and analyzing human language.

[0160] "Means for dynamically adjusting the tone of a response" refers to a device or process that has the ability to change the tone and expression of a response message according to the situation and the user's emotional state.

[0161] This invention is a system for safely and effectively processing information while recognizing the user's emotions. The system consists of a server, a terminal, and an emotion engine. The following describes its specific embodiments.

[0162] The user inputs information using a terminal. This input information becomes a prompt for using a generative AI model. The terminal is equipped with an emotion engine that analyzes the input data using natural language processing technology to recognize the user's emotions. These emotions are categorized into categories such as "joy," "sadness," and "anger."

[0163] For example, a user might enter the prompt "How does this system work?". The terminal recognizes through this sentence that the user is experiencing feelings of "question" or "confusion".

[0164] The analyzed information and sentiment data are sent to a server, which generates a sentiment-based response based on the received information. At this stage, it checks for the presence of confidential or personal information, and if present, replaces it with predefined abstraction elements. The processed information is then securely transmitted to an external generative AI service.

[0165] Ultimately, users receive emotionally sensitive responses on their devices. This process makes it possible to improve the user experience while ensuring information security.

[0166] A concrete example of this system is when a user inputs a document expressing dissatisfaction, such as "I don't understand the error message." The emotion engine recognizes this as dissatisfaction, and the terminal prepares polite feedback. At this point, the server generates a reassuring response, and the information is sent to an external service in a way that makes it impossible to identify the user. This ensures that the user receives a safe and emotionally appropriate response.

[0167] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0168] Step 1:

[0169] The user uses the device to enter prompts to utilize the generated AI model. The entered information is received by the emotion engine within the device. The input at this stage is text data containing the user's requests and questions, and the output becomes preparatory data for emotion recognition processing. A concrete example of this operation is when the user enters "Please tell me more about this product."

[0170] Step 2:

[0171] The device analyzes the received prompt text using an emotion engine to recognize the user's emotions. The input data is analyzed using natural language processing techniques to extract emotions from words, context, and phrasing. At this stage, the output is in the form of labels classifying emotions as "joy," "sadness," "anger," etc. Specifically, the device may recognize the user's emotions as "interest" or "question" based on positive or negative keywords in the text.

[0172] Step 3:

[0173] The terminal sends an emotion-recognized prompt message to the server. The server receives this data, analyzes its content, and generates an appropriate response based on the emotion recognition result. The server's input is an emotion-labeled prompt message, and its output is a response message with a tone and content appropriate to the emotion. Specifically, this involves a process of creating a response set to a calm and friendly tone.

[0174] Step 4:

[0175] The terminal detects sensitive and personal information within the generated response message and replaces it with predefined abstraction elements. The input for this step is the response message from the server, and the output is a modified message with personal information protected. Specifically, this involves replacing usernames and certain numerical information with placeholders such as "".

[0176] Step 5:

[0177] The terminal sends a processed response message to an external AI generation service. This service generates the final response and sends it back to the terminal. The input is the processed message, and the output is the final response message returned to the user. Specifically, the AI ​​generation service processes a more detailed answer based on additional information and sends it to the terminal via a secure communication channel.

[0178] Step 6:

[0179] The user receives a final response message displayed on their device. This output includes content that is considerate of the user's feelings, improving information security and user experience. Specifically, this includes displaying a clear and polite response on the screen to ensure the user can use the service with confidence.

[0180] (Application Example 2)

[0181] 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".

[0182] Conventional information processing systems handle information without considering user emotions, potentially increasing user stress during information transmission and responses. Furthermore, there is the challenge of simultaneously achieving both confidential information protection and improved user experience.

[0183] 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.

[0184] In this invention, the server includes means for receiving information, means for analyzing emotions and adjusting the presentation of information according to the user's emotions, and means for detecting and automatically replacing or deleting confidential and personal information. This enables the secure management of confidential information while considering the user's emotions, and stress-free information transmission.

[0185] "Means of receiving information" refers to a device or process that takes various types of data input from external sources into a system and prepares it for analysis.

[0186] "Means for detecting confidential and personal information" refers to technologies that scan incoming data and identify information that requires legal and ethical protection.

[0187] "Means of automatic replacement or deletion" refers to the process of converting or erasing detected confidential or personal information into a predefined format to ensure security.

[0188] "Means of transmission to external services" refers to communication methods for transferring processed, secure data to a designated external computer system or database.

[0189] "Means for recording the processing process" refers to technologies that record all operations performed during data processing, making them available for later review and auditing.

[0190] "Means of analyzing emotions and adjusting information presentation according to the user's emotions" refers to a process of analyzing the user's emotional state and optimizing the expression of information and responses based on the results.

[0191] This invention is a system that recognizes a user's emotional state in real time and utilizes that data for information processing. The system is installed in a device such as smart glasses and appropriately processes the information received from the user.

[0192] First, the device captures the user's facial expressions and voice via smart glasses. The hardware used here includes sensors such as cameras and microphones. The software uses OpenCV and TENSORFLOW®, Python®-based libraries for emotion analysis. Using these technologies, the device classifies the user's emotions, such as joy, sadness, and anger.

[0193] Next, the server applies natural language processing to the received information to detect personal and confidential information. Libraries such as NLTK and SpaCy, which provide natural language processing technology, are used for this process. The detected information is automatically replaced with placeholders to ensure security.

[0194] Furthermore, the server adjusts the tone of information and responses based on the user's emotions. This process allows users to receive emotionally sensitive feedback without feeling stressed.

[0195] For example, if a user is dissatisfied while participating in an online work meeting, the system can detect that emotion and automatically adjust the tone of the chat or document to be more gentle. This is designed to facilitate smoother communication.

[0196] The generative AI model receives a prompt message like this: "When a user expresses dissatisfaction, instruct the generative AI model to 'provide a message in a gentle, empathetic tone.'" Using this prompt, the generative AI model generates a response to optimize the user experience.

[0197] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0198] Step 1:

[0199] The device captures the user's facial expressions and voice using the camera and microphone of smart glasses. The input consists of real-time video and audio data. The device then inputs this data into OpenCV and TensorFlow for emotion analysis, classifying the user's emotions into categories such as "joy," "sadness," and "anger." The output is a label representing the user's emotional state. This process generates the user's emotional data.

[0200] Step 2:

[0201] The server receives text information entered by the user. This input information includes natural language data such as messages and documents. The server uses NLTK and SpaCy to analyze the text data and detect confidential and personal information. If confidential information is detected, it is automatically replaced with predefined placeholders. The output is text data masked with placeholders. This process generates data in a state where personal information is protected.

[0202] Step 3:

[0203] The server generates a response to the user using emotional state information obtained from the terminal. The input consists of emotional labels and masked text data. The generated prompt is sent to a generative AI model to create a response message with an emotional tone. In this process, the generative AI model generates an output that matches the emotion, using the prompt, "When the user is expressing dissatisfaction, please provide the message in a gentle and empathetic tone." The output is an emotionally empathetic response message. This process generates responses that improve the user experience.

[0204] Step 4:

[0205] The terminal presents the user with a response message received from the server. The input here is the response message sent from the server. The terminal displays this message on the smart glasses' screen and, if necessary, communicates it to the user verbally using speech synthesis. The output is the visual and auditory feedback presented to the user. This process allows the user to receive emotionally responsive feedback, resulting in less stressful communication.

[0206] 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.

[0207] 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.

[0208] 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.

[0209] [Second Embodiment]

[0210] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0211] 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.

[0212] 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).

[0213] 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.

[0214] 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.

[0215] 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).

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] 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.

[0221] 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".

[0222] The information processing system of this invention operates within a closed network within a company and is designed to reduce the risk of information leakage. The main components of the system are a server and terminals. The operation of the system is described in detail below in natural language.

[0223] First, the user inputs the document or data they want to send to the AI ​​generation service into their device. This input data is sent to the server in its original form.

[0224] Before forwarding the received information, the server prepares it for analysis on the terminal. At this stage, the data is still raw and untouched.

[0225] Next, the terminal analyzes the received information using natural language processing technology. The terminal stores pattern lists and dictionaries for detecting confidential and personal information, and uses these to scan the information. As a result of the analysis, confidential information such as names, addresses, and phone numbers is listed.

[0226] The detected information is automatically replaced or deleted by the device. For example, if the name "Taro Tanaka" is included, it will be replaced with "Name". Similarly, if it is a phone number, it will be replaced with "Phone Number". This prevents confidential information from being leaked to the outside.

[0227] The securely processed information is returned to the server and then sent to an external AI generation service. At this point, all information being sent is anonymized or masked, so there is no risk of leakage.

[0228] The information processing process and replacement details are recorded on the terminal. Each process is time-stamped, allowing for quick investigation by referring to the logs if a problem occurs.

[0229] For example, if a user wants to have an AI proofread a report, security policies may prevent them from directly naming the AI. In this case, the system can be used to securely process the information and receive the proofreading results from the AI.

[0230] In this way, this system automates information processing and enables the secure utilization of AI resources without leaking confidential corporate information to external parties.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The user inputs the documents or data they want to send to the generation AI service and sends it to their device. This information arrives on the server in its raw, unprocessed state.

[0234] Step 2:

[0235] The server sends the information received from the user back to the terminal as is, preparing it for analysis. At this point, no processing has been done yet.

[0236] Step 3:

[0237] The terminal activates its natural language processing engine and begins analyzing the received information. The analysis uses internal keyword lists and patterns to identify confidential and personal information, such as names, addresses, and phone numbers.

[0238] Step 4:

[0239] The device automatically replaces or deletes information detected during analysis. Specifically, detected names are replaced with a placeholder labeled "Name," and phone numbers are similarly converted to "Phone Number." This anonymizes the information.

[0240] Step 5:

[0241] The terminal sends the securely processed information back to the server. At this point, the information is handled securely.

[0242] Step 6:

[0243] The server sends the anonymized information received from the terminal to a designated AI generating service. All personally identifiable information is removed from the information sent externally.

[0244] Step 7:

[0245] The server receives responses from the AI ​​generation service and returns the results to the user. This makes it possible to use the AI ​​results while maintaining confidentiality.

[0246] Step 8:

[0247] The terminal records the processing flow as a log. The log includes the start and end times of the process, and the type of information replaced. The log can be used for auditing and troubleshooting.

[0248] (Example 1)

[0249] 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."

[0250] In modern information processing, the risk of confidential and personal data being leaked to external parties is increasing. Especially when using AI generation technology within a company, there is a possibility that confidential information may be sent to external services, making security crucial. To address this problem, a system is needed that reliably anonymizes data during the information processing stage, thereby reducing the risk of leakage.

[0251] 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.

[0252] In this invention, the server includes a device for receiving information, a device for analyzing the received information and detecting confidential data and personal data, and a device for automatically replacing or deleting the detected confidential data and personal data. This enables companies and organizations to securely anonymize confidential data and reduce the risk of information leakage while utilizing external generative AI technology.

[0253] A "device for receiving information" refers to a function or device for receiving data entered by a user or data transmitted from an external source.

[0254] A "device for analyzing received information and detecting confidential and personal data" refers to a function or device that analyzes received data and automatically identifies highly confidential information or data that can identify a specific individual.

[0255] A "device for automatically replacing or deleting detected confidential and personal data" refers to a function or device that automatically replaces or deletes confidential and personal information identified through analysis, preventing it from being leaked externally.

[0256] A "device for transmitting anonymized or masked information to external technology" refers to a function or device for securely transmitting data that has been appropriately processed to external AI generation technology.

[0257] A "device for recording the processing process and adding time information" refers to a function or device that records each step of data processing in detail and adds information about the processing time, thereby facilitating later verification and auditing.

[0258] "Natural language processing technology" refers to a set of techniques that enable computers to understand and analyze human language, particularly those used to extract information from text.

[0259] An "identifier" is a placeholder or symbol used to represent specific data, and is typically used when confidential or personal data is being replaced.

[0260] This invention is an information processing system for utilizing generative AI technology while securely managing confidential and personal information within a company's closed network. The main components of the system are a server and terminals.

[0261] The server receives data sent from the user. Data reception is securely performed using a network protocol with HTTPS communication. This data is then transferred from the server to the terminal, and preparation for analysis begins. At this stage, the data is unmodified and in its raw state.

[0262] The device utilizes natural language processing (NLP) technology to analyze received data. Specifically, it uses NLP libraries based on Python (e.g., spaCy and NLTK) to automatically scan and detect confidential and personal information within text data. The device has pre-stored pattern lists and dictionaries for identifying confidential and personal data, and performs data analysis based on these.

[0263] The system automatically replaces or deletes any detected confidential or personal data. For example, if a name is included in the text, it will be replaced with the identifier "Name." Similarly, a phone number will be replaced with "Phone Number." This feature allows for the transmission of confidential information to external AI-generated services while maintaining its confidentiality.

[0264] The processed information is returned to the server and then sent to the AI ​​generation service. During this process, the transmitted information is in a masked format, establishing a secure foundation for using the AI ​​service.

[0265] A concrete example for users might be wanting to have a report proofread by the AI ​​generator. If a report containing specific personal information cannot be sent directly due to security policies, the information can be securely processed through this system.

[0266] An example of a prompt message that can be sent to the generating AI is: "Please proofread the following document. The document contains personal information such as names and phone numbers, but this information has already been anonymized."

[0267] Thus, the present invention provides a specific information processing method for efficiently and safely utilizing generated AI resources.

[0268] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0269] Step 1:

[0270] The user inputs the documents or data they want to send to the AI ​​generation service into their device. This input is done via keyboard or file upload function. The input data is in text format, and the device receives and temporarily stores it. The input data is then prepared to be sent to the server in its original form.

[0271] Step 2:

[0272] The server receives text data sent from the terminal. Upon receipt, checksum and data validation processes are applied to verify the integrity of the data. Once the integrity of the data is confirmed, it is ready to send instructions to the terminal for analysis. The output is the analysis instructions transmitted to the terminal.

[0273] Step 3:

[0274] The terminal receives instructions from the server and begins processing the received text data for analysis. This analysis employs natural language processing techniques, using Python's NLP library (e.g., spaCy or NLTK). The input is the text data received from the server, and the output of the analysis is a list of identified confidential or personal information.

[0275] Step 4:

[0276] The detected confidential information and personal information are automatically replaced or deleted by the terminal. For example, the listed names are replaced with identifiers such as "Name", and the phone numbers are replaced with "Phone Number". This conversion is performed based on a pre-defined pattern list within the terminal. As output, anonymized data after replacement is generated.

[0277] Step 5:

[0278] The anonymized data is sent back to the server. The server proceeds with preparations to send the data to an external generative AI service. Before sending, a prompt text is created and described, for example, as "Please proofread the following document. The names and phone numbers in the text contain personal information, but they have already been anonymized." The output is the data to be sent to the generative AI service together with the prompt text.

[0279] Step 6:

[0280] The server records logs regarding the information processing process and replacement details with timestamps. This record becomes an important information source for future verification and troubleshooting. As output, detailed processing logs are generated and stored.

[0281] (Application Example 1)

[0282] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0283] In modern information communication, the risk of leakage of confidential information and personal information during message exchanges has become a problem. A method for securely and efficiently linking information to external services while reducing this risk of information leakage is being sought.

[0284] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0285] In this invention, the server includes means for receiving information, means for analyzing the received information to detect confidential information and personal information, and communication means for anonymizing confidential information in real time. As a result, it becomes possible to share information with external services quickly and securely while reducing the risk of information leakage.

[0286] The "means for receiving information" is a function for taking in information transmitted from the outside or inside in a data format.

[0287] The "means for analyzing the received information to detect confidential information and personal information" is a function for analyzing the captured information and identifying highly confidential data and information related to individuals that require protection from among it.

[0288] The "means for automatically replacing or deleting the detected confidential information and personal information" is a function for automatically converting or deleting the identified confidential information and personal information into an anonymized form in order to protect them.

[0289] The "means for transmitting the processed information to an external service" is a function for transferring the information safely processed internally to an external service or system using an appropriate protocol.

[0290] The "means for recording the process of processing" is a function for tracking how information is processed and storing it so that it can be analyzed and confirmed later.

[0291] The "communication means for anonymizing confidential information in real time" is a function for performing a conversion to immediately maintain confidentiality without delay when messages or information are exchanged.

[0292] The "transmission means for securely transmitting the anonymized information" is a controlled communication function for delivering the anonymized information to an external recipient without risk.

[0293] In this system, the user first uses a smart device to input a message or information. This input information is processed in real time within the device. The device uses natural language processing technology to analyze the input information. Specific software used here includes natural language processing libraries such as spaCy and NLTK.

[0294] The analyzed information is scanned to identify confidential and personal information. Detected information is automatically replaced or deleted using predefined placeholders. After this anonymization process, the processed information is sent to a server. The server then delivers this information to external AI-generating services, but because it is anonymized, the risk of information leakage is low.

[0295] In terms of hardware, devices such as smartphones and smart glasses that have the functionality to receive, analyze, anonymize, and transmit information are used. These devices interact with servers via an internet connection.

[0296] For example, if a user wants to create a meeting summary and share it with team members, this system allows for automatic editing and summarization by AI, with speakers' names and confidential information anonymized.

[0297] Example of a prompt:

[0298] Parse the input message and replace sensitive information, including names and phone numbers, with tags:

[0299] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0300] Step 1:

[0301] The user inputs a message or information into the smart device. The input data here is directly taken into the terminal as it is. In this step, the user inputs the summary or message of the meeting, and the terminal receives it as digital data.

[0302] Step 2:

[0303] The terminal analyzes the input information. Specifically, using natural language processing technology, it performs the process of identifying confidential information and personal information from within the information. The document obtained from the input is word-segmented, and data processing based on specific keywords is carried out.

[0304] Step 3:

[0305] Regarding the confidential information and personal information detected as a result of the analysis, the terminal automatically replaces or deletes them. Here, the information is anonymized using placeholders (e.g., "Name", "Phone number"). The information identified from the original input text is replaced with placeholders, enhancing the security of the information.

[0306] Step 4:

[0307] The anonymized information is returned from the terminal to the server. The output at this stage is the safely processed information. The server checks whether the information is appropriately anonymized and prepares for the next step.

[0308] Step 5:

[0309] The server sends the information to an external generative AI service. In this process, the server transfers the information according to a pre-defined protocol. The output is anonymized information that is safely delivered to the generative AI service, reducing the risk of information leakage.

[0310] Step 6:

[0311] The server records the processing steps. Each processed piece of information is accompanied by a timestamp and change history, and a log is stored. The log is saved in a format that allows for future reference.

[0312] 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.

[0313] This invention provides a system for effectively processing information within a corporate network while ensuring the security of confidential and personal information by recognizing the user's emotions. This system consists of a server, terminals, and an emotion engine.

[0314] When a user uses the AI-generated service, they input information into their device. The device is equipped with an emotion engine that analyzes the user's input and context to recognize the user's emotions. This emotional information is then classified by the emotion engine as "joy," "sadness," "anger," etc.

[0315] Once information is sent to the server, it receives it and adjusts the response to an appropriate one based on the analysis results of the emotion engine. For example, if the user's input indicates anger, the system will generate a response in a calm tone.

[0316] The device then analyzes the information and detects confidential and personal information. Detected elements are automatically replaced with predefined placeholders, making it impossible to identify individuals. This processed information is then securely transmitted again via the server to an external AI generation service.

[0317] As a concrete example, suppose a user enters a document expressing dissatisfaction with an error message. The emotion engine recognizes this as "dissatisfaction," and the device prepares thoughtful feedback that takes the user's emotions into consideration. Personal information in the text is then appropriately replaced and sent to an external AI service. As a result, the user receives a safe and emotionally appropriate response.

[0318] This invention seamlessly integrates the processes of emotion recognition and information masking, enabling the safe and efficient use of generative AI within enterprises. This reduces the risk of information leakage and improves the user experience.

[0319] The following describes the processing flow.

[0320] Step 1:

[0321] The user inputs a document into the terminal as input for the AI ​​generation service. This document may take various forms, such as opinions, impressions, or inquiries.

[0322] Step 2:

[0323] The device sends the input information to an emotion engine, which analyzes the user's emotions. Here, the emotion engine uses natural language processing technology to analyze the text and identify emotional categories such as "joy," "sadness," and "anger."

[0324] Step 3:

[0325] After receiving the sentiment analysis results, the device then analyzes the content of the information to detect confidential and personal information. This process involves scanning the information using pre-configured patterns and keyword lists to find entries that fit a specific format (such as names, addresses, and phone numbers).

[0326] Step 4:

[0327] The device replaces detected confidential information with placeholders (e.g., "Name" or "Phone Number"). This prevents personal information from being explicitly displayed when data is sent to the generating AI service.

[0328] Step 5:

[0329] Based on the sentiment analysis results and anonymized information, the server generates a response. If the user expresses dissatisfaction or anger, the system maintains composure and prepares a response using a considerate tone.

[0330] Step 6:

[0331] The server sends internally generated responses and securely processed information to the AI ​​service. At this stage, all data is anonymized, minimizing the risk of external leakage.

[0332] Step 7:

[0333] The server, having received a response from the AI ​​generation service, returns the result to the user as feedback. The user receives a clean and considerate response, experiencing that their feelings have been taken into account.

[0334] Step 8:

[0335] At every processing step, the terminal logs the process details. The log includes the start and end times of the process, replaced information, and recognized sentiment categories. This record can be used later for audits and system improvements.

[0336] (Example 2)

[0337] 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".

[0338] In corporate information processing, there is a need to appropriately understand user emotions and provide responses accordingly, while securely handling confidential and personal information. However, conventional systems have insufficient emotion recognition and fail to adjust tone, sometimes resulting in inappropriate responses to users. Furthermore, there have been challenges such as incomplete detection and protection of confidential and personal information, creating a risk of information leakage.

[0339] 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.

[0340] In this invention, the server includes means for receiving information, means for analyzing the received information and recognizing an individual's emotions, and means for adjusting the response content based on the recognized emotions. This enables the provision of an appropriate response that takes the user's emotions into consideration, as well as the secure processing of confidential and personal information.

[0341] "Means of receiving information" refers to a device or process that has the ability to take in data sent from an external source.

[0342] A "means for recognizing individual emotions" refers to a device or process that has the ability to analyze user input information and identify emotional states or intentions from that information.

[0343] "Means for adjusting response content based on recognized emotions" refers to a device or process that has the ability to optimize the content and tone of the generated response using detected emotion information.

[0344] "Means for detecting confidential and personal information in analysis" refers to devices or processes that have the capability to find sensitive data contained within received information.

[0345] "Means for automatically replacing or deleting with predefined abstract elements" refers to a device or process that has the ability to convert detected confidential or personal information into pre-configured, non-individual elements, or to delete them.

[0346] "Means for sending to an external computing service" refers to a device or process that has the ability to transfer processed data to a connected external computing resource.

[0347] "Means for recording the processing process" refers to a device or process that has the ability to save each step in which data is processed.

[0348] "Natural language processing technology" refers to algorithms and methods for understanding and analyzing human language.

[0349] "Means for dynamically adjusting the tone of a response" refers to a device or process that has the ability to change the tone and expression of a response message according to the situation and the user's emotional state.

[0350] This invention is a system for safely and effectively processing information while recognizing the user's emotions. The system consists of a server, a terminal, and an emotion engine. The following describes its specific embodiments.

[0351] The user inputs information using a terminal. This input information becomes a prompt for using a generative AI model. The terminal is equipped with an emotion engine that analyzes the input data using natural language processing technology to recognize the user's emotions. These emotions are categorized into categories such as "joy," "sadness," and "anger."

[0352] For example, a user might enter the prompt "How does this system work?". The terminal recognizes through this sentence that the user is experiencing feelings of "question" or "confusion".

[0353] The analyzed information and sentiment data are sent to a server, which generates a sentiment-based response based on the received information. At this stage, it checks for the presence of confidential or personal information, and if present, replaces it with predefined abstraction elements. The processed information is then securely transmitted to an external generative AI service.

[0354] Ultimately, users receive emotionally sensitive responses on their devices. This process makes it possible to improve the user experience while ensuring information security.

[0355] A concrete example of this system is when a user inputs a document expressing dissatisfaction, such as "I don't understand the error message." The emotion engine recognizes this as dissatisfaction, and the terminal prepares polite feedback. At this point, the server generates a reassuring response, and the information is sent to an external service in a way that makes it impossible to identify the user. This ensures that the user receives a safe and emotionally appropriate response.

[0356] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0357] Step 1:

[0358] The user uses the device to enter prompts to utilize the generated AI model. The entered information is received by the emotion engine within the device. The input at this stage is text data containing the user's requests and questions, and the output becomes preparatory data for emotion recognition processing. A concrete example of this operation is when the user enters "Please tell me more about this product."

[0359] Step 2:

[0360] The device analyzes the received prompt text using an emotion engine to recognize the user's emotions. The input data is analyzed using natural language processing techniques to extract emotions from words, context, and phrasing. At this stage, the output is in the form of labels classifying emotions as "joy," "sadness," "anger," etc. Specifically, the device may recognize the user's emotions as "interest" or "question" based on positive or negative keywords in the text.

[0361] Step 3:

[0362] The terminal sends an emotion-recognized prompt message to the server. The server receives this data, analyzes its content, and generates an appropriate response based on the emotion recognition result. The server's input is an emotion-labeled prompt message, and its output is a response message with a tone and content appropriate to the emotion. Specifically, this involves a process of creating a response set to a calm and friendly tone.

[0363] Step 4:

[0364] The terminal detects sensitive and personal information within the generated response message and replaces it with predefined abstraction elements. The input for this step is the response message from the server, and the output is a modified message with personal information protected. Specifically, this involves replacing usernames and certain numerical information with placeholders such as "".

[0365] Step 5:

[0366] The terminal sends a processed response message to an external AI generation service. This service generates the final response and sends it back to the terminal. The input is the processed message, and the output is the final response message returned to the user. Specifically, the AI ​​generation service processes a more detailed answer based on additional information and sends it to the terminal via a secure communication channel.

[0367] Step 6:

[0368] The user receives a final response message displayed on their device. This output includes content that is considerate of the user's feelings, improving information security and user experience. Specifically, this includes displaying a clear and polite response on the screen to ensure the user can use the service with confidence.

[0369] (Application Example 2)

[0370] 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."

[0371] Conventional information processing systems handle information without considering user emotions, potentially increasing user stress during information transmission and responses. Furthermore, there is the challenge of simultaneously achieving both confidential information protection and improved user experience.

[0372] 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.

[0373] In this invention, the server includes means for receiving information, means for analyzing emotions and adjusting the presentation of information according to the user's emotions, and means for detecting and automatically replacing or deleting confidential and personal information. This enables the secure management of confidential information while considering the user's emotions, and stress-free information transmission.

[0374] "Means of receiving information" refers to a device or process that takes various types of data input from external sources into a system and prepares it for analysis.

[0375] "Means for detecting confidential and personal information" refers to technologies that scan incoming data and identify information that requires legal and ethical protection.

[0376] "Means of automatic replacement or deletion" refers to the process of converting or erasing detected confidential or personal information into a predefined format to ensure security.

[0377] "Means of transmission to external services" refers to communication methods for transferring processed, secure data to a designated external computer system or database.

[0378] "Means for recording the processing process" refers to technologies that record all operations performed during data processing, making them available for later review and auditing.

[0379] "Means of analyzing emotions and adjusting information presentation according to the user's emotions" refers to a process of analyzing the user's emotional state and optimizing the expression of information and responses based on the results.

[0380] This invention is a system that recognizes a user's emotional state in real time and utilizes that data for information processing. The system is installed in a device such as smart glasses and appropriately processes the information received from the user.

[0381] First, the device captures the user's facial expressions and voice via smart glasses. The hardware used here includes sensors such as cameras and microphones. The software uses OpenCV and TensorFlow, Python-based libraries for emotion analysis. Using these technologies, the device classifies the user's emotions, such as joy, sadness, and anger.

[0382] Next, the server applies natural language processing to the received information to detect personal and confidential information. Libraries such as NLTK and SpaCy, which provide natural language processing technology, are used for this process. The detected information is automatically replaced with placeholders to ensure security.

[0383] Furthermore, the server adjusts the tone of information and responses based on the user's emotions. This process allows users to receive emotionally sensitive feedback without feeling stressed.

[0384] For example, if a user is dissatisfied while participating in an online work meeting, the system can detect that emotion and automatically adjust the tone of the chat or document to be more gentle. This is designed to facilitate smoother communication.

[0385] The generative AI model receives a prompt message like this: "When a user expresses dissatisfaction, instruct the generative AI model to 'provide a message in a gentle, empathetic tone.'" Using this prompt, the generative AI model generates a response to optimize the user experience.

[0386] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0387] Step 1:

[0388] The device captures the user's facial expressions and voice using the camera and microphone of smart glasses. The input consists of real-time video and audio data. The device then inputs this data into OpenCV and TensorFlow for emotion analysis, classifying the user's emotions into categories such as "joy," "sadness," and "anger." The output is a label representing the user's emotional state. This process generates the user's emotional data.

[0389] Step 2:

[0390] The server receives text information entered by the user. This input information includes natural language data such as messages and documents. The server uses NLTK and SpaCy to analyze the text data and detect confidential and personal information. If confidential information is detected, it is automatically replaced with predefined placeholders. The output is text data masked with placeholders. This process generates data in a state where personal information is protected.

[0391] Step 3:

[0392] The server generates a response to the user using emotional state information obtained from the terminal. The input consists of emotional labels and masked text data. The generated prompt is sent to a generative AI model to create a response message with an emotional tone. In this process, the generative AI model generates an output that matches the emotion, using the prompt, "When the user is expressing dissatisfaction, please provide the message in a gentle and empathetic tone." The output is an emotionally empathetic response message. This process generates responses that improve the user experience.

[0393] Step 4:

[0394] The terminal presents the user with a response message received from the server. The input here is the response message sent from the server. The terminal displays this message on the smart glasses' screen and, if necessary, communicates it to the user verbally using speech synthesis. The output is the visual and auditory feedback presented to the user. This process allows the user to receive emotionally responsive feedback, resulting in less stressful communication.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] [Third Embodiment]

[0399] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0400] 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.

[0401] 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).

[0402] 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.

[0403] 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.

[0404] 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).

[0405] 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.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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".

[0411] The information processing system of this invention operates within a closed network within a company and is designed to reduce the risk of information leakage. The main components of the system are a server and terminals. The operation of the system is described in detail below in natural language.

[0412] First, the user inputs the document or data they want to send to the AI ​​generation service into their device. This input data is sent to the server in its original form.

[0413] Before forwarding the received information, the server prepares it for analysis on the terminal. At this stage, the data is still raw and untouched.

[0414] Next, the terminal analyzes the received information using natural language processing technology. The terminal stores pattern lists and dictionaries for detecting confidential and personal information, and uses these to scan the information. As a result of the analysis, confidential information such as names, addresses, and phone numbers is listed.

[0415] The detected information is automatically replaced or deleted by the device. For example, if the name "Taro Tanaka" is included, it will be replaced with "Name". Similarly, if it is a phone number, it will be replaced with "Phone Number". This prevents confidential information from being leaked to the outside.

[0416] The securely processed information is returned to the server and then sent to an external AI generation service. At this point, all information being sent is anonymized or masked, so there is no risk of leakage.

[0417] The information processing process and replacement details are recorded on the terminal. Each process is time-stamped, allowing for quick investigation by referring to the logs if a problem occurs.

[0418] For example, if a user wants to have an AI proofread a report, security policies may prevent them from directly naming the AI. In this case, the system can be used to securely process the information and receive the proofreading results from the AI.

[0419] In this way, this system automates information processing and enables the secure utilization of AI resources without leaking confidential corporate information to external parties.

[0420] The following describes the processing flow.

[0421] Step 1:

[0422] The user inputs the documents or data they want to send to the generation AI service and sends it to their device. This information arrives on the server in its raw, unprocessed state.

[0423] Step 2:

[0424] The server sends the information received from the user back to the terminal as is, preparing it for analysis. At this point, no processing has been done yet.

[0425] Step 3:

[0426] The terminal activates its natural language processing engine and begins analyzing the received information. The analysis uses internal keyword lists and patterns to identify confidential and personal information, such as names, addresses, and phone numbers.

[0427] Step 4:

[0428] The device automatically replaces or deletes information detected during analysis. Specifically, detected names are replaced with a placeholder labeled "Name," and phone numbers are similarly converted to "Phone Number." This anonymizes the information.

[0429] Step 5:

[0430] The terminal sends the securely processed information back to the server. At this point, the information is handled securely.

[0431] Step 6:

[0432] The server sends the anonymized information received from the terminal to a designated AI generating service. All personally identifiable information is removed from the information sent externally.

[0433] Step 7:

[0434] The server receives responses from the AI ​​generation service and returns the results to the user. This makes it possible to use the AI ​​results while maintaining confidentiality.

[0435] Step 8:

[0436] The terminal records the processing flow as a log. The log includes the start and end times of the process, and the type of information replaced. The log can be used for auditing and troubleshooting.

[0437] (Example 1)

[0438] 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."

[0439] In modern information processing, the risk of confidential and personal data being leaked to external parties is increasing. Especially when using AI generation technology within a company, there is a possibility that confidential information may be sent to external services, making security crucial. To address this problem, a system is needed that reliably anonymizes data during the information processing stage, thereby reducing the risk of leakage.

[0440] 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.

[0441] In this invention, the server includes a device for receiving information, a device for analyzing the received information and detecting confidential data and personal data, and a device for automatically replacing or deleting the detected confidential data and personal data. This enables companies and organizations to securely anonymize confidential data and reduce the risk of information leakage while utilizing external generative AI technology.

[0442] A "device for receiving information" refers to a function or device for receiving data entered by a user or data transmitted from an external source.

[0443] A "device for analyzing received information and detecting confidential and personal data" refers to a function or device that analyzes received data and automatically identifies highly confidential information or data that can identify a specific individual.

[0444] A "device for automatically replacing or deleting detected confidential and personal data" refers to a function or device that automatically replaces or deletes confidential and personal information identified through analysis, preventing it from being leaked externally.

[0445] A "device for transmitting anonymized or masked information to external technology" refers to a function or device for securely transmitting data that has been appropriately processed to external AI generation technology.

[0446] A "device for recording the processing process and adding time information" refers to a function or device that records each step of data processing in detail and adds information about the processing time, thereby facilitating later verification and auditing.

[0447] "Natural language processing technology" refers to a set of techniques that enable computers to understand and analyze human language, particularly those used to extract information from text.

[0448] An "identifier" is a placeholder or symbol used to represent specific data, and is typically used when confidential or personal data is being replaced.

[0449] This invention is an information processing system for utilizing generative AI technology while securely managing confidential and personal information within a company's closed network. The main components of the system are a server and terminals.

[0450] The server receives data sent from the user. Data reception is securely performed using a network protocol with HTTPS communication. This data is then transferred from the server to the terminal, and preparation for analysis begins. At this stage, the data is unmodified and in its raw state.

[0451] The device utilizes natural language processing (NLP) technology to analyze received data. Specifically, it uses NLP libraries based on Python (e.g., spaCy and NLTK) to automatically scan and detect confidential and personal information within text data. The device has pre-stored pattern lists and dictionaries for identifying confidential and personal data, and performs data analysis based on these.

[0452] The system automatically replaces or deletes any detected confidential or personal data. For example, if a name is included in the text, it will be replaced with the identifier "Name." Similarly, a phone number will be replaced with "Phone Number." This feature allows for the transmission of confidential information to external AI-generated services while maintaining its confidentiality.

[0453] The processed information is returned to the server and then sent to the AI ​​generation service. During this process, the transmitted information is in a masked format, establishing a secure foundation for using the AI ​​service.

[0454] A concrete example for users might be wanting to have a report proofread by the AI ​​generator. If a report containing specific personal information cannot be sent directly due to security policies, the information can be securely processed through this system.

[0455] An example of a prompt message that can be sent to the generating AI is: "Please proofread the following document. The document contains personal information such as names and phone numbers, but this information has already been anonymized."

[0456] Thus, the present invention provides a specific information processing method for efficiently and safely utilizing generated AI resources.

[0457] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0458] Step 1:

[0459] The user inputs the documents or data they want to send to the AI ​​generation service into their device. This input is done via keyboard or file upload function. The input data is in text format, and the device receives and temporarily stores it. The input data is then prepared to be sent to the server in its original form.

[0460] Step 2:

[0461] The server receives text data sent from the terminal. Upon receipt, checksum and data validation processes are applied to verify the integrity of the data. Once the integrity of the data is confirmed, it is ready to send instructions to the terminal for analysis. The output is the analysis instructions transmitted to the terminal.

[0462] Step 3:

[0463] The terminal receives instructions from the server and begins processing the received text data for analysis. This analysis employs natural language processing techniques, using Python's NLP library (e.g., spaCy or NLTK). The input is the text data received from the server, and the output of the analysis is a list of identified confidential or personal information.

[0464] Step 4:

[0465] Detected confidential or personal information is automatically replaced or deleted by the device. For example, listed names are replaced with the identifier "Name," and phone numbers with the identifier "Phone Number." This conversion is performed based on a predefined pattern list within the device. The output is the replaced, anonymized data.

[0466] Step 5:

[0467] The anonymized data is sent back to the server. The server then prepares to send the data to an external generative AI service. Before sending, a prompt is created, for example, "Please proofread the following document. The name and phone number in the document contain personal information, but it has already been anonymized." The output is the data sent to the generative AI service along with the prompt.

[0468] Step 6:

[0469] The server records logs of the information processing process and replacement details, complete with timestamps. These logs serve as crucial information for later verification and troubleshooting. Detailed processing logs are generated and stored as output.

[0470] (Application Example 1)

[0471] 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."

[0472] In modern information and communication, the risk of confidential and personal information being leaked during message exchanges is a significant concern. There is a need for methods to reduce this risk of information leakage while securely and efficiently linking information to external services.

[0473] 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.

[0474] In this invention, the server includes means for receiving information, means for analyzing the received information and detecting confidential and personal information, and communication means for anonymizing confidential information in real time. This makes it possible to share information with external services quickly and securely while reducing the risk of information leakage.

[0475] "Means of receiving information" refers to a function for taking in information transmitted from external or internal sources in data format.

[0476] "Means for analyzing received information and detecting confidential and personal information" refers to a function that analyzes the received information and identifies highly confidential data and personal information that requires protection.

[0477] "Means for automatically replacing or deleting detected confidential and personal information" refers to a function that automatically converts or deletes identified confidential and personal information into an anonymized form in order to protect it.

[0478] "Means for transmitting processed information to external services" refers to a function for transferring information that has been securely processed internally to an external service or system using an appropriate protocol.

[0479] "Means for recording the processing process" refers to a function for tracking how information was processed and saving it so that it can be analyzed and verified later.

[0480] A "communication method that anonymizes confidential information in real time" is a function that performs a conversion to maintain confidentiality immediately and without delay when messages or information are exchanged.

[0481] "A means of securely transmitting anonymized information" refers to a controlled communication function that delivers anonymized information to external recipients without risk.

[0482] In this system, the user first uses a smart device to input a message or information. This input information is processed in real time within the device. The device uses natural language processing technology to analyze the input information. Specific software used here includes natural language processing libraries such as spaCy and NLTK.

[0483] The analyzed information is scanned to identify confidential and personal information. Detected information is automatically replaced or deleted using predefined placeholders. After this anonymization process, the processed information is sent to a server. The server then delivers this information to external AI-generating services, but because it is anonymized, the risk of information leakage is low.

[0484] In terms of hardware, devices such as smartphones and smart glasses that have the functionality to receive, analyze, anonymize, and transmit information are used. These devices interact with servers via an internet connection.

[0485] For example, if a user wants to create a meeting summary and share it with team members, this system allows for automatic editing and summarization by AI, with speakers' names and confidential information anonymized.

[0486] Example of a prompt:

[0487] Parse the input message and replace sensitive information, including names and phone numbers, with tags:

[0488] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0489] Step 1:

[0490] The user enters a message or information into a smart device. The entered data is captured raw within the device. In this step, the user enters a meeting summary or message, which the device receives as digital data.

[0491] Step 2:

[0492] The terminal analyzes the input information. Specifically, it uses natural language processing technology to identify confidential and personal information within the data. The input document is segmented, and data processing is performed based on specific keywords.

[0493] Step 3:

[0494] The device automatically replaces or deletes any confidential or personal information detected as a result of the analysis. Here, placeholders (e.g., "Name," "Phone Number") are used to anonymize the information. Information identified from the original input text is replaced with placeholders, enhancing the security of the information.

[0495] Step 4:

[0496] The anonymized information is returned from the terminal to the server. At this stage, the output is securely processed information. The server verifies that the information has been properly anonymized and prepares for the next step.

[0497] Step 5:

[0498] The server sends information to an external generative AI service. In this process, the server transfers information according to a predefined protocol. The output is anonymized information that is securely delivered to the generative AI service, reducing the risk of information leakage.

[0499] Step 6:

[0500] The server records the processing steps. Each processed piece of information is accompanied by a timestamp and change history, and a log is stored. The log is saved in a format that allows for future reference.

[0501] 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.

[0502] This invention provides a system for effectively processing information within a corporate network while ensuring the security of confidential and personal information by recognizing the user's emotions. This system consists of a server, terminals, and an emotion engine.

[0503] When a user uses the AI-generated service, they input information into their device. The device is equipped with an emotion engine that analyzes the user's input and context to recognize the user's emotions. This emotional information is then classified by the emotion engine as "joy," "sadness," "anger," etc.

[0504] Once information is sent to the server, it receives it and adjusts the response to an appropriate one based on the analysis results of the emotion engine. For example, if the user's input indicates anger, the system will generate a response in a calm tone.

[0505] The device then analyzes the information and detects confidential and personal information. Detected elements are automatically replaced with predefined placeholders, making it impossible to identify individuals. This processed information is then securely transmitted again via the server to an external AI generation service.

[0506] As a concrete example, suppose a user enters a document expressing dissatisfaction with an error message. The emotion engine recognizes this as "dissatisfaction," and the device prepares thoughtful feedback that takes the user's emotions into consideration. Personal information in the text is then appropriately replaced and sent to an external AI service. As a result, the user receives a safe and emotionally appropriate response.

[0507] This invention seamlessly integrates the processes of emotion recognition and information masking, enabling the safe and efficient use of generative AI within enterprises. This reduces the risk of information leakage and improves the user experience.

[0508] The following describes the processing flow.

[0509] Step 1:

[0510] The user inputs a document into the terminal as input for the AI ​​generation service. This document may take various forms, such as opinions, impressions, or inquiries.

[0511] Step 2:

[0512] The device sends the input information to an emotion engine, which analyzes the user's emotions. Here, the emotion engine uses natural language processing technology to analyze the text and identify emotional categories such as "joy," "sadness," and "anger."

[0513] Step 3:

[0514] After receiving the sentiment analysis results, the device then analyzes the content of the information to detect confidential and personal information. This process involves scanning the information using pre-configured patterns and keyword lists to find entries that fit a specific format (such as names, addresses, and phone numbers).

[0515] Step 4:

[0516] The device replaces detected confidential information with placeholders (e.g., "Name" or "Phone Number"). This prevents personal information from being explicitly displayed when data is sent to the generating AI service.

[0517] Step 5:

[0518] Based on the sentiment analysis results and anonymized information, the server generates a response. If the user expresses dissatisfaction or anger, the system maintains composure and prepares a response using a considerate tone.

[0519] Step 6:

[0520] The server sends internally generated responses and securely processed information to the AI ​​service. At this stage, all data is anonymized, minimizing the risk of external leakage.

[0521] Step 7:

[0522] The server, having received a response from the AI ​​generation service, returns the result to the user as feedback. The user receives a clean and considerate response, experiencing that their feelings have been taken into account.

[0523] Step 8:

[0524] At every processing step, the terminal logs the process details. The log includes the start and end times of the process, replaced information, and recognized sentiment categories. This record can be used later for audits and system improvements.

[0525] (Example 2)

[0526] 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."

[0527] In corporate information processing, there is a need to appropriately understand user emotions and provide responses accordingly, while securely handling confidential and personal information. However, conventional systems have insufficient emotion recognition and fail to adjust tone, sometimes resulting in inappropriate responses to users. Furthermore, there have been challenges such as incomplete detection and protection of confidential and personal information, creating a risk of information leakage.

[0528] 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.

[0529] In this invention, the server includes means for receiving information, means for analyzing the received information and recognizing an individual's emotions, and means for adjusting the response content based on the recognized emotions. This enables the provision of an appropriate response that takes the user's emotions into consideration, as well as the secure processing of confidential and personal information.

[0530] "Means of receiving information" refers to a device or process that has the ability to take in data sent from an external source.

[0531] A "means for recognizing individual emotions" refers to a device or process that has the ability to analyze user input information and identify emotional states or intentions from that information.

[0532] "Means for adjusting response content based on recognized emotions" refers to a device or process that has the ability to optimize the content and tone of the generated response using detected emotion information.

[0533] "Means for detecting confidential and personal information in analysis" refers to devices or processes that have the capability to find sensitive data contained within received information.

[0534] "Means for automatically replacing or deleting with predefined abstract elements" refers to a device or process that has the ability to convert detected confidential or personal information into pre-configured, non-individual elements, or to delete them.

[0535] "Means for sending to an external computing service" refers to a device or process that has the ability to transfer processed data to a connected external computing resource.

[0536] "Means for recording the processing process" refers to a device or process that has the ability to save each step in which data is processed.

[0537] "Natural language processing technology" refers to algorithms and methods for understanding and analyzing human language.

[0538] "Means for dynamically adjusting the tone of a response" refers to a device or process that has the ability to change the tone and expression of a response message according to the situation and the user's emotional state.

[0539] This invention is a system for safely and effectively processing information while recognizing the user's emotions. The system consists of a server, a terminal, and an emotion engine. The following describes its specific embodiments.

[0540] The user inputs information using a terminal. This input information becomes a prompt for using a generative AI model. The terminal is equipped with an emotion engine that analyzes the input data using natural language processing technology to recognize the user's emotions. These emotions are categorized into categories such as "joy," "sadness," and "anger."

[0541] For example, a user might enter the prompt "How does this system work?". The terminal recognizes through this sentence that the user is experiencing feelings of "question" or "confusion".

[0542] The analyzed information and sentiment data are sent to a server, which generates a sentiment-based response based on the received information. At this stage, it checks for the presence of confidential or personal information, and if present, replaces it with predefined abstraction elements. The processed information is then securely transmitted to an external generative AI service.

[0543] Ultimately, users receive emotionally sensitive responses on their devices. This process makes it possible to improve the user experience while ensuring information security.

[0544] A concrete example of this system is when a user inputs a document expressing dissatisfaction, such as "I don't understand the error message." The emotion engine recognizes this as dissatisfaction, and the terminal prepares polite feedback. At this point, the server generates a reassuring response, and the information is sent to an external service in a way that makes it impossible to identify the user. This ensures that the user receives a safe and emotionally appropriate response.

[0545] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0546] Step 1:

[0547] The user uses the device to enter prompts to utilize the generated AI model. The entered information is received by the emotion engine within the device. The input at this stage is text data containing the user's requests and questions, and the output becomes preparatory data for emotion recognition processing. A concrete example of this operation is when the user enters "Please tell me more about this product."

[0548] Step 2:

[0549] The device analyzes the received prompt text using an emotion engine to recognize the user's emotions. The input data is analyzed using natural language processing techniques to extract emotions from words, context, and phrasing. At this stage, the output is in the form of labels classifying emotions as "joy," "sadness," "anger," etc. Specifically, the device may recognize the user's emotions as "interest" or "question" based on positive or negative keywords in the text.

[0550] Step 3:

[0551] The terminal sends an emotion-recognized prompt message to the server. The server receives this data, analyzes its content, and generates an appropriate response based on the emotion recognition result. The server's input is an emotion-labeled prompt message, and its output is a response message with a tone and content appropriate to the emotion. Specifically, this involves a process of creating a response set to a calm and friendly tone.

[0552] Step 4:

[0553] The terminal detects sensitive and personal information within the generated response message and replaces it with predefined abstraction elements. The input for this step is the response message from the server, and the output is a modified message with personal information protected. Specifically, this involves replacing usernames and certain numerical information with placeholders such as "".

[0554] Step 5:

[0555] The terminal sends a processed response message to an external AI generation service. This service generates the final response and sends it back to the terminal. The input is the processed message, and the output is the final response message returned to the user. Specifically, the AI ​​generation service processes a more detailed answer based on additional information and sends it to the terminal via a secure communication channel.

[0556] Step 6:

[0557] The user receives a final response message displayed on their device. This output includes content that is considerate of the user's feelings, improving information security and user experience. Specifically, this includes displaying a clear and polite response on the screen to ensure the user can use the service with confidence.

[0558] (Application Example 2)

[0559] 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."

[0560] Conventional information processing systems handle information without considering user emotions, potentially increasing user stress during information transmission and responses. Furthermore, there is the challenge of simultaneously achieving both confidential information protection and improved user experience.

[0561] 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.

[0562] In this invention, the server includes means for receiving information, means for analyzing emotions and adjusting the presentation of information according to the user's emotions, and means for detecting and automatically replacing or deleting confidential and personal information. This enables the secure management of confidential information while considering the user's emotions, and stress-free information transmission.

[0563] "Means of receiving information" refers to a device or process that takes various types of data input from external sources into a system and prepares it for analysis.

[0564] "Means for detecting confidential and personal information" refers to technologies that scan incoming data and identify information that requires legal and ethical protection.

[0565] "Means of automatic replacement or deletion" refers to the process of converting or erasing detected confidential or personal information into a predefined format to ensure security.

[0566] "Means of transmission to external services" refers to communication methods for transferring processed, secure data to a designated external computer system or database.

[0567] "Means for recording the processing process" refers to technologies that record all operations performed during data processing, making them available for later review and auditing.

[0568] "Means of analyzing emotions and adjusting information presentation according to the user's emotions" refers to a process of analyzing the user's emotional state and optimizing the expression of information and responses based on the results.

[0569] This invention is a system that recognizes a user's emotional state in real time and utilizes that data for information processing. The system is installed in a device such as smart glasses and appropriately processes the information received from the user.

[0570] First, the device captures the user's facial expressions and voice via smart glasses. The hardware used here includes sensors such as cameras and microphones. The software uses OpenCV and TensorFlow, Python-based libraries for emotion analysis. Using these technologies, the device classifies the user's emotions, such as joy, sadness, and anger.

[0571] Next, the server applies natural language processing to the received information to detect personal and confidential information. Libraries such as NLTK and SpaCy, which provide natural language processing technology, are used for this process. The detected information is automatically replaced with placeholders to ensure security.

[0572] Furthermore, the server adjusts the tone of information and responses based on the user's emotions. This process allows users to receive emotionally sensitive feedback without feeling stressed.

[0573] For example, if a user is dissatisfied while participating in an online work meeting, the system can detect that emotion and automatically adjust the tone of the chat or document to be more gentle. This is designed to facilitate smoother communication.

[0574] The generative AI model receives a prompt message like this: "When a user expresses dissatisfaction, instruct the generative AI model to 'provide a message in a gentle, empathetic tone.'" Using this prompt, the generative AI model generates a response to optimize the user experience.

[0575] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0576] Step 1:

[0577] The device captures the user's facial expressions and voice using the camera and microphone of smart glasses. The input consists of real-time video and audio data. The device then inputs this data into OpenCV and TensorFlow for emotion analysis, classifying the user's emotions into categories such as "joy," "sadness," and "anger." The output is a label representing the user's emotional state. This process generates the user's emotional data.

[0578] Step 2:

[0579] The server receives text information entered by the user. This input information includes natural language data such as messages and documents. The server uses NLTK and SpaCy to analyze the text data and detect confidential and personal information. If confidential information is detected, it is automatically replaced with predefined placeholders. The output is text data masked with placeholders. This process generates data in a state where personal information is protected.

[0580] Step 3:

[0581] The server generates a response to the user using emotional state information obtained from the terminal. The input consists of emotional labels and masked text data. The generated prompt is sent to a generative AI model to create a response message with an emotional tone. In this process, the generative AI model generates an output that matches the emotion, using the prompt, "When the user is expressing dissatisfaction, please provide the message in a gentle and empathetic tone." The output is an emotionally empathetic response message. This process generates responses that improve the user experience.

[0582] Step 4:

[0583] The terminal presents the user with a response message received from the server. The input here is the response message sent from the server. The terminal displays this message on the smart glasses' screen and, if necessary, communicates it to the user verbally using speech synthesis. The output is the visual and auditory feedback presented to the user. This process allows the user to receive emotionally responsive feedback, resulting in less stressful communication.

[0584] 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.

[0585] 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.

[0586] 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.

[0587] [Fourth Embodiment]

[0588] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0589] 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.

[0590] 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).

[0591] 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.

[0592] 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.

[0593] 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).

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] 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".

[0601] The information processing system of this invention operates within a closed network within a company and is designed to reduce the risk of information leakage. The main components of the system are a server and terminals. The operation of the system is described in detail below in natural language.

[0602] First, the user inputs the document or data they want to send to the AI ​​generation service into their device. This input data is sent to the server in its original form.

[0603] Before forwarding the received information, the server prepares it for analysis on the terminal. At this stage, the data is still raw and untouched.

[0604] Next, the terminal analyzes the received information using natural language processing technology. The terminal stores pattern lists and dictionaries for detecting confidential and personal information, and uses these to scan the information. As a result of the analysis, confidential information such as names, addresses, and phone numbers is listed.

[0605] The detected information is automatically replaced or deleted by the device. For example, if the name "Taro Tanaka" is included, it will be replaced with "Name". Similarly, if it is a phone number, it will be replaced with "Phone Number". This prevents confidential information from being leaked to the outside.

[0606] The securely processed information is returned to the server and then sent to an external AI generation service. At this point, all information being sent is anonymized or masked, so there is no risk of leakage.

[0607] The information processing process and replacement details are recorded on the terminal. Each process is time-stamped, allowing for quick investigation by referring to the logs if a problem occurs.

[0608] For example, if a user wants to have an AI proofread a report, security policies may prevent them from directly naming the AI. In this case, the system can be used to securely process the information and receive the proofreading results from the AI.

[0609] In this way, this system automates information processing and enables the secure utilization of AI resources without leaking confidential corporate information to external parties.

[0610] The following describes the processing flow.

[0611] Step 1:

[0612] The user inputs the documents or data they want to send to the generation AI service and sends it to their device. This information arrives on the server in its raw, unprocessed state.

[0613] Step 2:

[0614] The server sends the information received from the user back to the terminal as is, preparing it for analysis. At this point, no processing has been done yet.

[0615] Step 3:

[0616] The terminal activates its natural language processing engine and begins analyzing the received information. The analysis uses internal keyword lists and patterns to identify confidential and personal information, such as names, addresses, and phone numbers.

[0617] Step 4:

[0618] The device automatically replaces or deletes information detected during analysis. Specifically, detected names are replaced with a placeholder labeled "Name," and phone numbers are similarly converted to "Phone Number." This anonymizes the information.

[0619] Step 5:

[0620] The terminal sends the securely processed information back to the server. At this point, the information is handled securely.

[0621] Step 6:

[0622] The server sends the anonymized information received from the terminal to a designated AI generating service. All personally identifiable information is removed from the information sent externally.

[0623] Step 7:

[0624] The server receives responses from the AI ​​generation service and returns the results to the user. This makes it possible to use the AI ​​results while maintaining confidentiality.

[0625] Step 8:

[0626] The terminal records the processing flow as a log. The log includes the start and end times of the process, and the type of information replaced. The log can be used for auditing and troubleshooting.

[0627] (Example 1)

[0628] 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".

[0629] In modern information processing, the risk of confidential and personal data being leaked to external parties is increasing. Especially when using AI generation technology within a company, there is a possibility that confidential information may be sent to external services, making security crucial. To address this problem, a system is needed that reliably anonymizes data during the information processing stage, thereby reducing the risk of leakage.

[0630] 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.

[0631] In this invention, the server includes a device for receiving information, a device for analyzing the received information and detecting confidential data and personal data, and a device for automatically replacing or deleting the detected confidential data and personal data. This enables companies and organizations to securely anonymize confidential data and reduce the risk of information leakage while utilizing external generative AI technology.

[0632] A "device for receiving information" refers to a function or device for receiving data entered by a user or data transmitted from an external source.

[0633] A "device for analyzing received information and detecting confidential and personal data" refers to a function or device that analyzes received data and automatically identifies highly confidential information or data that can identify a specific individual.

[0634] A "device for automatically replacing or deleting detected confidential and personal data" refers to a function or device that automatically replaces or deletes confidential and personal information identified through analysis, preventing it from being leaked externally.

[0635] A "device for transmitting anonymized or masked information to external technology" refers to a function or device for securely transmitting data that has been appropriately processed to external AI generation technology.

[0636] A "device for recording the processing process and adding time information" refers to a function or device that records each step of data processing in detail and adds information about the processing time, thereby facilitating later verification and auditing.

[0637] "Natural language processing technology" refers to a set of techniques that enable computers to understand and analyze human language, particularly those used to extract information from text.

[0638] An "identifier" is a placeholder or symbol used to represent specific data, and is typically used when confidential or personal data is being replaced.

[0639] This invention is an information processing system for utilizing generative AI technology while securely managing confidential and personal information within a company's closed network. The main components of the system are a server and terminals.

[0640] The server receives data sent from the user. Data reception is securely performed using a network protocol with HTTPS communication. This data is then transferred from the server to the terminal, and preparation for analysis begins. At this stage, the data is unmodified and in its raw state.

[0641] The device utilizes natural language processing (NLP) technology to analyze received data. Specifically, it uses NLP libraries based on Python (e.g., spaCy and NLTK) to automatically scan and detect confidential and personal information within text data. The device has pre-stored pattern lists and dictionaries for identifying confidential and personal data, and performs data analysis based on these.

[0642] The system automatically replaces or deletes any detected confidential or personal data. For example, if a name is included in the text, it will be replaced with the identifier "Name." Similarly, a phone number will be replaced with "Phone Number." This feature allows for the transmission of confidential information to external AI-generated services while maintaining its confidentiality.

[0643] The processed information is returned to the server and then sent to the AI ​​generation service. During this process, the transmitted information is in a masked format, establishing a secure foundation for using the AI ​​service.

[0644] A concrete example for users might be wanting to have a report proofread by the AI ​​generator. If a report containing specific personal information cannot be sent directly due to security policies, the information can be securely processed through this system.

[0645] An example of a prompt message that can be sent to the generating AI is: "Please proofread the following document. The document contains personal information such as names and phone numbers, but this information has already been anonymized."

[0646] Thus, the present invention provides a specific information processing method for efficiently and safely utilizing generated AI resources.

[0647] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0648] Step 1:

[0649] The user inputs the documents or data they want to send to the AI ​​generation service into their device. This input is done via keyboard or file upload function. The input data is in text format, and the device receives and temporarily stores it. The input data is then prepared to be sent to the server in its original form.

[0650] Step 2:

[0651] The server receives text data sent from the terminal. Upon receipt, checksum and data validation processes are applied to verify the integrity of the data. Once the integrity of the data is confirmed, it is ready to send instructions to the terminal for analysis. The output is the analysis instructions transmitted to the terminal.

[0652] Step 3:

[0653] The terminal receives instructions from the server and begins processing the received text data for analysis. This analysis employs natural language processing techniques, using Python's NLP library (e.g., spaCy or NLTK). The input is the text data received from the server, and the output of the analysis is a list of identified confidential or personal information.

[0654] Step 4:

[0655] Detected confidential or personal information is automatically replaced or deleted by the device. For example, listed names are replaced with the identifier "Name," and phone numbers with the identifier "Phone Number." This conversion is performed based on a predefined pattern list within the device. The output is the replaced, anonymized data.

[0656] Step 5:

[0657] The anonymized data is sent back to the server. The server then prepares to send the data to an external generative AI service. Before sending, a prompt is created, for example, "Please proofread the following document. The name and phone number in the document contain personal information, but it has already been anonymized." The output is the data sent to the generative AI service along with the prompt.

[0658] Step 6:

[0659] The server records logs of the information processing process and replacement details, complete with timestamps. These logs serve as crucial information for later verification and troubleshooting. Detailed processing logs are generated and stored as output.

[0660] (Application Example 1)

[0661] 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".

[0662] In modern information and communication, the risk of confidential and personal information being leaked during message exchanges is a significant concern. There is a need for methods to reduce this risk of information leakage while securely and efficiently linking information to external services.

[0663] 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.

[0664] In this invention, the server includes means for receiving information, means for analyzing the received information and detecting confidential and personal information, and communication means for anonymizing confidential information in real time. This makes it possible to share information with external services quickly and securely while reducing the risk of information leakage.

[0665] "Means of receiving information" refers to a function for taking in information transmitted from external or internal sources in data format.

[0666] "Means for analyzing received information and detecting confidential and personal information" refers to a function that analyzes the received information and identifies highly confidential data and personal information that requires protection.

[0667] "Means for automatically replacing or deleting detected confidential and personal information" refers to a function that automatically converts or deletes identified confidential and personal information into an anonymized form in order to protect it.

[0668] "Means for transmitting processed information to external services" refers to a function for transferring information that has been securely processed internally to an external service or system using an appropriate protocol.

[0669] "Means for recording the processing process" refers to a function for tracking how information was processed and saving it so that it can be analyzed and verified later.

[0670] A "communication method that anonymizes confidential information in real time" is a function that performs a conversion to maintain confidentiality immediately and without delay when messages or information are exchanged.

[0671] "A means of securely transmitting anonymized information" refers to a controlled communication function that delivers anonymized information to external recipients without risk.

[0672] In this system, the user first uses a smart device to input a message or information. This input information is processed in real time within the device. The device uses natural language processing technology to analyze the input information. Specific software used here includes natural language processing libraries such as spaCy and NLTK.

[0673] The analyzed information is scanned to identify confidential and personal information. Detected information is automatically replaced or deleted using predefined placeholders. After this anonymization process, the processed information is sent to a server. The server then delivers this information to external AI-generating services, but because it is anonymized, the risk of information leakage is low.

[0674] In terms of hardware, devices such as smartphones and smart glasses that have the functionality to receive, analyze, anonymize, and transmit information are used. These devices interact with servers via an internet connection.

[0675] For example, if a user wants to create a meeting summary and share it with team members, this system allows for automatic editing and summarization by AI, with speakers' names and confidential information anonymized.

[0676] Example of a prompt:

[0677] Parse the input message and replace sensitive information, including names and phone numbers, with tags:

[0678] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0679] Step 1:

[0680] The user enters a message or information into a smart device. The entered data is captured raw within the device. In this step, the user enters a meeting summary or message, which the device receives as digital data.

[0681] Step 2:

[0682] The terminal analyzes the input information. Specifically, it uses natural language processing technology to identify confidential and personal information within the data. The input document is segmented, and data processing is performed based on specific keywords.

[0683] Step 3:

[0684] The device automatically replaces or deletes any confidential or personal information detected as a result of the analysis. Here, placeholders (e.g., "Name," "Phone Number") are used to anonymize the information. Information identified from the original input text is replaced with placeholders, enhancing the security of the information.

[0685] Step 4:

[0686] The anonymized information is returned from the terminal to the server. At this stage, the output is securely processed information. The server verifies that the information has been properly anonymized and prepares for the next step.

[0687] Step 5:

[0688] The server sends information to an external generative AI service. In this process, the server transfers information according to a predefined protocol. The output is anonymized information that is securely delivered to the generative AI service, reducing the risk of information leakage.

[0689] Step 6:

[0690] The server records the processing steps. Each processed piece of information is accompanied by a timestamp and change history, and a log is stored. The log is saved in a format that allows for future reference.

[0691] 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.

[0692] This invention provides a system for effectively processing information within a corporate network while ensuring the security of confidential and personal information by recognizing the user's emotions. This system consists of a server, terminals, and an emotion engine.

[0693] When a user uses the AI-generated service, they input information into their device. The device is equipped with an emotion engine that analyzes the user's input and context to recognize the user's emotions. This emotional information is then classified by the emotion engine as "joy," "sadness," "anger," etc.

[0694] Once information is sent to the server, it receives it and adjusts the response to an appropriate one based on the analysis results of the emotion engine. For example, if the user's input indicates anger, the system will generate a response in a calm tone.

[0695] The device then analyzes the information and detects confidential and personal information. Detected elements are automatically replaced with predefined placeholders, making it impossible to identify individuals. This processed information is then securely transmitted again via the server to an external AI generation service.

[0696] As a concrete example, suppose a user enters a document expressing dissatisfaction with an error message. The emotion engine recognizes this as "dissatisfaction," and the device prepares thoughtful feedback that takes the user's emotions into consideration. Personal information in the text is then appropriately replaced and sent to an external AI service. As a result, the user receives a safe and emotionally appropriate response.

[0697] This invention seamlessly integrates the processes of emotion recognition and information masking, enabling the safe and efficient use of generative AI within enterprises. This reduces the risk of information leakage and improves the user experience.

[0698] The following describes the processing flow.

[0699] Step 1:

[0700] The user inputs a document into the terminal as input for the AI ​​generation service. This document may take various forms, such as opinions, impressions, or inquiries.

[0701] Step 2:

[0702] The device sends the input information to an emotion engine, which analyzes the user's emotions. Here, the emotion engine uses natural language processing technology to analyze the text and identify emotional categories such as "joy," "sadness," and "anger."

[0703] Step 3:

[0704] After receiving the sentiment analysis results, the device then analyzes the content of the information to detect confidential and personal information. This process involves scanning the information using pre-configured patterns and keyword lists to find entries that fit a specific format (such as names, addresses, and phone numbers).

[0705] Step 4:

[0706] The device replaces detected confidential information with placeholders (e.g., "Name" or "Phone Number"). This prevents personal information from being explicitly displayed when data is sent to the generating AI service.

[0707] Step 5:

[0708] Based on the sentiment analysis results and anonymized information, the server generates a response. If the user expresses dissatisfaction or anger, the system maintains composure and prepares a response using a considerate tone.

[0709] Step 6:

[0710] The server sends internally generated responses and securely processed information to the AI ​​service. At this stage, all data is anonymized, minimizing the risk of external leakage.

[0711] Step 7:

[0712] The server, having received a response from the AI ​​generation service, returns the result to the user as feedback. The user receives a clean and considerate response, experiencing that their feelings have been taken into account.

[0713] Step 8:

[0714] At every processing step, the terminal logs the process details. The log includes the start and end times of the process, replaced information, and recognized sentiment categories. This record can be used later for audits and system improvements.

[0715] (Example 2)

[0716] 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".

[0717] In corporate information processing, there is a need to appropriately understand user emotions and provide responses accordingly, while securely handling confidential and personal information. However, conventional systems have insufficient emotion recognition and fail to adjust tone, sometimes resulting in inappropriate responses to users. Furthermore, there have been challenges such as incomplete detection and protection of confidential and personal information, creating a risk of information leakage.

[0718] 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.

[0719] In this invention, the server includes means for receiving information, means for analyzing the received information and recognizing an individual's emotions, and means for adjusting the response content based on the recognized emotions. This enables the provision of an appropriate response that takes the user's emotions into consideration, as well as the secure processing of confidential and personal information.

[0720] "Means of receiving information" refers to a device or process that has the ability to take in data sent from an external source.

[0721] A "means for recognizing individual emotions" refers to a device or process that has the ability to analyze user input information and identify emotional states or intentions from that information.

[0722] "Means for adjusting response content based on recognized emotions" refers to a device or process that has the ability to optimize the content and tone of the generated response using detected emotion information.

[0723] "Means for detecting confidential and personal information in analysis" refers to devices or processes that have the capability to find sensitive data contained within received information.

[0724] "Means for automatically replacing or deleting with predefined abstract elements" refers to a device or process that has the ability to convert detected confidential or personal information into pre-configured, non-individual elements, or to delete them.

[0725] "Means for sending to an external computing service" refers to a device or process that has the ability to transfer processed data to a connected external computing resource.

[0726] "Means for recording the processing process" refers to a device or process that has the ability to save each step in which data is processed.

[0727] "Natural language processing technology" refers to algorithms and methods for understanding and analyzing human language.

[0728] "Means for dynamically adjusting the tone of a response" refers to a device or process that has the ability to change the tone and expression of a response message according to the situation and the user's emotional state.

[0729] This invention is a system for safely and effectively processing information while recognizing the user's emotions. The system consists of a server, a terminal, and an emotion engine. The following describes its specific embodiments.

[0730] The user inputs information using a terminal. This input information becomes a prompt for using a generative AI model. The terminal is equipped with an emotion engine that analyzes the input data using natural language processing technology to recognize the user's emotions. These emotions are categorized into categories such as "joy," "sadness," and "anger."

[0731] For example, a user might enter the prompt "How does this system work?". The terminal recognizes through this sentence that the user is experiencing feelings of "question" or "confusion".

[0732] The analyzed information and sentiment data are sent to a server, which generates a sentiment-based response based on the received information. At this stage, it checks for the presence of confidential or personal information, and if present, replaces it with predefined abstraction elements. The processed information is then securely transmitted to an external generative AI service.

[0733] Ultimately, users receive emotionally sensitive responses on their devices. This process makes it possible to improve the user experience while ensuring information security.

[0734] A concrete example of this system is when a user inputs a document expressing dissatisfaction, such as "I don't understand the error message." The emotion engine recognizes this as dissatisfaction, and the terminal prepares polite feedback. At this point, the server generates a reassuring response, and the information is sent to an external service in a way that makes it impossible to identify the user. This ensures that the user receives a safe and emotionally appropriate response.

[0735] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0736] Step 1:

[0737] The user uses the device to enter prompts to utilize the generated AI model. The entered information is received by the emotion engine within the device. The input at this stage is text data containing the user's requests and questions, and the output becomes preparatory data for emotion recognition processing. A concrete example of this operation is when the user enters "Please tell me more about this product."

[0738] Step 2:

[0739] The device analyzes the received prompt text using an emotion engine to recognize the user's emotions. The input data is analyzed using natural language processing techniques to extract emotions from words, context, and phrasing. At this stage, the output is in the form of labels classifying emotions as "joy," "sadness," "anger," etc. Specifically, the device may recognize the user's emotions as "interest" or "question" based on positive or negative keywords in the text.

[0740] Step 3:

[0741] The terminal sends an emotion-recognized prompt message to the server. The server receives this data, analyzes its content, and generates an appropriate response based on the emotion recognition result. The server's input is an emotion-labeled prompt message, and its output is a response message with a tone and content appropriate to the emotion. Specifically, this involves a process of creating a response set to a calm and friendly tone.

[0742] Step 4:

[0743] The terminal detects sensitive and personal information within the generated response message and replaces it with predefined abstraction elements. The input for this step is the response message from the server, and the output is a modified message with personal information protected. Specifically, this involves replacing usernames and certain numerical information with placeholders such as "".

[0744] Step 5:

[0745] The terminal sends a processed response message to an external AI generation service. This service generates the final response and sends it back to the terminal. The input is the processed message, and the output is the final response message returned to the user. Specifically, the AI ​​generation service processes a more detailed answer based on additional information and sends it to the terminal via a secure communication channel.

[0746] Step 6:

[0747] The user receives a final response message displayed on their device. This output includes content that is considerate of the user's feelings, improving information security and user experience. Specifically, this includes displaying a clear and polite response on the screen to ensure the user can use the service with confidence.

[0748] (Application Example 2)

[0749] 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".

[0750] Conventional information processing systems handle information without considering user emotions, potentially increasing user stress during information transmission and responses. Furthermore, there is the challenge of simultaneously achieving both confidential information protection and improved user experience.

[0751] 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.

[0752] In this invention, the server includes means for receiving information, means for analyzing emotions and adjusting the presentation of information according to the user's emotions, and means for detecting and automatically replacing or deleting confidential and personal information. This enables the secure management of confidential information while considering the user's emotions, and stress-free information transmission.

[0753] "Means of receiving information" refers to a device or process that takes various types of data input from external sources into a system and prepares it for analysis.

[0754] "Means for detecting confidential and personal information" refers to technologies that scan incoming data and identify information that requires legal and ethical protection.

[0755] "Means of automatic replacement or deletion" refers to the process of converting or erasing detected confidential or personal information into a predefined format to ensure security.

[0756] "Means of transmission to external services" refers to communication methods for transferring processed, secure data to a designated external computer system or database.

[0757] "Means for recording the processing process" refers to technologies that record all operations performed during data processing, making them available for later review and auditing.

[0758] "Means of analyzing emotions and adjusting information presentation according to the user's emotions" refers to a process of analyzing the user's emotional state and optimizing the expression of information and responses based on the results.

[0759] This invention is a system that recognizes a user's emotional state in real time and utilizes that data for information processing. The system is installed in a device such as smart glasses and appropriately processes the information received from the user.

[0760] First, the device captures the user's facial expressions and voice via smart glasses. The hardware used here includes sensors such as cameras and microphones. The software uses OpenCV and TensorFlow, Python-based libraries for emotion analysis. Using these technologies, the device classifies the user's emotions, such as joy, sadness, and anger.

[0761] Next, the server applies natural language processing to the received information to detect personal and confidential information. Libraries such as NLTK and SpaCy, which provide natural language processing technology, are used for this process. The detected information is automatically replaced with placeholders to ensure security.

[0762] Furthermore, the server adjusts the tone of information and responses based on the user's emotions. This process allows users to receive emotionally sensitive feedback without feeling stressed.

[0763] For example, if a user is dissatisfied while participating in an online work meeting, the system can detect that emotion and automatically adjust the tone of the chat or document to be more gentle. This is designed to facilitate smoother communication.

[0764] The generative AI model receives a prompt message like this: "When a user expresses dissatisfaction, instruct the generative AI model to 'provide a message in a gentle, empathetic tone.'" Using this prompt, the generative AI model generates a response to optimize the user experience.

[0765] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0766] Step 1:

[0767] The device captures the user's facial expressions and voice using the camera and microphone of smart glasses. The input consists of real-time video and audio data. The device then inputs this data into OpenCV and TensorFlow for emotion analysis, classifying the user's emotions into categories such as "joy," "sadness," and "anger." The output is a label representing the user's emotional state. This process generates the user's emotional data.

[0768] Step 2:

[0769] The server receives text information entered by the user. This input information includes natural language data such as messages and documents. The server uses NLTK and SpaCy to analyze the text data and detect confidential and personal information. If confidential information is detected, it is automatically replaced with predefined placeholders. The output is text data masked with placeholders. This process generates data in a state where personal information is protected.

[0770] Step 3:

[0771] The server generates a response to the user using emotional state information obtained from the terminal. The input consists of emotional labels and masked text data. The generated prompt is sent to a generative AI model to create a response message with an emotional tone. In this process, the generative AI model generates an output that matches the emotion, using the prompt, "When the user is expressing dissatisfaction, please provide the message in a gentle and empathetic tone." The output is an emotionally empathetic response message. This process generates responses that improve the user experience.

[0772] Step 4:

[0773] The terminal presents the user with a response message received from the server. The input here is the response message sent from the server. The terminal displays this message on the smart glasses' screen and, if necessary, communicates it to the user verbally using speech synthesis. The output is the visual and auditory feedback presented to the user. This process allows the user to receive emotionally responsive feedback, resulting in less stressful communication.

[0774] 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.

[0775] 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.

[0776] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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."

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] The following is further disclosed regarding the embodiments described above.

[0796] (Claim 1)

[0797] Means of receiving information,

[0798] A means for analyzing received information and detecting confidential and personal information,

[0799] A means to automatically replace or delete detected confidential and personal information,

[0800] A means of sending the processed information to an external service,

[0801] A means of recording the processing steps,

[0802] An information processing system that includes this.

[0803] (Claim 2)

[0804] The information processing system according to claim 1, comprising means for detecting confidential information and personal information using natural language processing technology in the analysis of information.

[0805] (Claim 3)

[0806] The information processing system according to claim 1, comprising means for using predefined placeholders in the process of replacing confidential information and personal information.

[0807] "Example 1"

[0808] (Claim 1)

[0809] A device that receives information,

[0810] A device that analyzes received information and detects confidential and personal data,

[0811] A device that automatically replaces or deletes detected confidential and personal data,

[0812] A device that transmits anonymized or masked information to an external technology,

[0813] A device that records the processing steps and adds time information,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, comprising a device that uses natural language processing technology to detect confidential data and personal data in the analysis of information.

[0817] (Claim 3)

[0818] The system according to claim 1, comprising a device that uses a predefined identifier in the process of replacing confidential data and personal data.

[0819] "Application Example 1"

[0820] (Claim 1)

[0821] Means of receiving information,

[0822] A means for analyzing received information and detecting confidential and personal information,

[0823] A means to automatically replace or delete detected confidential and personal information,

[0824] A means of sending the processed information to an external service,

[0825] A means of recording the processing steps,

[0826] A communication method that anonymizes confidential information in real time,

[0827] A means of securely transmitting anonymized information,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, comprising means for detecting confidential information and personal information using natural language processing technology in the analysis of information and anonymizing it in real time.

[0831] (Claim 3)

[0832] The system according to claim 1, comprising means for real-time communication using predefined placeholders in the process of replacing confidential and personal information.

[0833] "Example 2 of combining an emotion engine"

[0834] (Claim 1)

[0835] Means of receiving information,

[0836] A means of analyzing received information and recognizing an individual's emotions,

[0837] Means for adjusting response content based on recognized emotions,

[0838] Means for detecting confidential and personal information in the analysis,

[0839] A means for automatically replacing or deleting detected confidential and personal information with predefined abstraction elements,

[0840] A means for sending the processed information to an external computing service,

[0841] A means of recording the processing steps,

[0842] A system that includes this.

[0843] (Claim 2)

[0844] The system according to claim 1, comprising means for performing emotion recognition using natural language processing technology in the analysis of information.

[0845] (Claim 3)

[0846] The system according to claim 1, comprising means for dynamically adjusting the tone of a response in accordance with recognized emotions.

[0847] "Application example 2 when combining with an emotional engine"

[0848] (Claim 1)

[0849] Means of receiving information,

[0850] A means for analyzing received information and detecting confidential and personal information,

[0851] A means to automatically replace or delete detected confidential and personal information,

[0852] A means of sending the processed information to an external service,

[0853] A means of recording the processing steps,

[0854] A means of analyzing emotions and adjusting the information presented according to the user's emotions,

[0855] A system that includes this.

[0856] (Claim 2)

[0857] The system according to claim 1, comprising means for detecting confidential information and personal information using natural language processing technology in the analysis of information, and generating user-emotion-based feedback.

[0858] (Claim 3)

[0859] The system according to claim 1, comprising means for using predefined placeholders and means for adjusting the tone according to the user's emotions in the process of replacing confidential and personal information. [Explanation of Symbols]

[0860] 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. Means of receiving information, A means for analyzing received information and detecting confidential and personal information, A means to automatically replace or delete detected confidential and personal information, A means of sending the processed information to an external service, A means of recording the processing steps, An information processing system that includes this.

2. The information processing system according to claim 1, comprising means for detecting confidential information and personal information using natural language processing technology in the analysis of information.

3. The information processing system according to claim 1, comprising means for using predefined placeholders in the process of replacing confidential information and personal information.

Images