system

Abstract

We provide the system. [Solution] In an information processing device, means for obtaining input messages from a user, A means for identifying personal information from the aforementioned input message and replacing the relevant personal information with dummy words, A means for sending the message, which has been replaced with the aforementioned dummy word, to an external server, A means for restoring dummy words in a response message received from the external server to their original form based on the personal information, Means for presenting the restored response to the user, A 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] In recent years, the use of artificial intelligence agents in information processing devices has become widespread. Along with this, concerns about the accumulation of users' personal information on the cloud have been increasing. In order for users to use artificial intelligence agents with confidence, it is desirable that the data transmitted to the cloud does not contain personal information. However, in the current system, there is a problem that users' personal information may be unnecessarily transmitted to the cloud, which may cause privacy issues.

Means for Solving the Problems

[0005] This invention provides an information processing device that analyzes user input messages and includes means for identifying personal information. The identified personal information is replaced with dummy words, and the resulting message is sent to an external server. Furthermore, by providing means for restoring the dummy words contained in the response message returned from the external server to the original personal information, personal information is not stored on the cloud, thus protecting user privacy while providing users with the convenience of accurate information.

[0006] An "information processing device" is a device consisting of hardware and software for inputting, processing, and outputting data, and it enables interaction with the user.

[0007] A "user" refers to a person who operates an information processing device and utilizes its services and functions.

[0008] An "input message" is information that a user provides to an information processing device, and includes questions, instructions, and so on.

[0009] "Personal information" refers to information that can identify a specific individual, including, for example, name and address.

[0010] A "dummy word" is a placeholder word used to temporarily replace an actual word, and is used to protect privacy.

[0011] An "external server" is a server that communicates with information processing equipment via a network and performs data processing and storage.

[0012] A "response message" is information that an external server sends back to an information processing device, containing the processing results for the input message.

[0013] "Restoration" refers to the process of replacing dummy words with the original personal information. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main 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

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a tagged 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.

[0018] In the following embodiments, a tagged RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a tagged 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.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] An embodiment of the present invention is a system consisting of a terminal acting as an information processing device and an external server connected via a network. The user operates the terminal to input a question. At this time, an AI agent in the terminal analyzes the question and identifies personal information. The identified personal information is replaced with dummy words, and a newly generated message is sent to the external server via the network.

[0036] The server processes the message received from the terminal. Here, it analyzes the message, even with dummy words included, and generates a response. The generated response is then sent back to the terminal via the network. After receiving the response from the server, the terminal restores the dummy words to the original personal information. This allows the user to verify the information displayed on the terminal.

[0037] As a concrete example, consider a case where a user enters the question "What is my name?" into the device. In this question, the device recognizes the word "name" as personal information and replaces it with the dummy word "DUMMY_0" to generate the message "What is my DUMMY_0?". This message is sent to the server, which processes it and generates the response "Your DUMMY_0 is already registered". The device then restores "DUMMY_0" in the received message back to its original "name" and presents the user with the response "Your name is already registered".

[0038] In this way, users can receive information services from AI agents with peace of mind without exposing their personal information to third parties. This system plays an important role in protecting personal information and can be applied to various information processing devices and services.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user enters a question into the device. The question may include personal information, such as "What is my name?"

[0042] Step 2:

[0043] The device's AI agent receives the user's question. It analyzes each word in the question and identifies personal information based on a pre-configured list of personal information (e.g., name, address, phone number).

[0044] Step 3:

[0045] The device replaces identified personal information with dummy words. For example, "Name" is replaced with "DUMMY_0". This transforms the question into the format "What is my DUMMY_0?". The replaced personal information is stored in a mapping table that shows which dummy words represent which personal information.

[0046] Step 4:

[0047] The device sends a question, with dummy words replaced, to an external server. Since the sent message does not contain personal information, privacy is protected.

[0048] Step 5:

[0049] The server receives a message from the terminal. Because the message contains dummy words, no personal information is transmitted to the server.

[0050] Step 6:

[0051] The server processes the received message and generates the necessary response. This process is similar to normal natural language processing, creating a response sentence that takes the appropriate context into account based on dummy words.

[0052] Step 7:

[0053] The server sends the generated response to the terminal. Since the server's response also contains dummy words, there is no risk of personal information leakage.

[0054] Step 8:

[0055] The terminal receives a response from the server. It then uses a mapping table to reconstruct the original personal information by replacing dummy words in the received message. For example, in the response "Your DUMMY_0 is already registered," "DUMMY_0" is replaced with "Name."

[0056] Step 9:

[0057] The device presents the restored response to the user. Through this process, the user can confidently use the AI ​​agent's functions.

[0058] (Example 1)

[0059] 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."

[0060] Protecting personal information is a critical issue in today's information society. In particular, there is a risk of personal information being handled inappropriately when users interact with external systems via digital information processing devices. To address this problem, there is a need to provide new methods for users to obtain necessary information while safely and effectively protecting personal information.

[0061] 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.

[0062] In this invention, the server includes means for acquiring input information from a user, means for identifying personal information from the input information and replacing the corresponding personal information with a dummy representation, and means for transmitting the information replaced with the dummy representation to a data processing device. This makes it possible to provide the user with necessary information without communicating with an external system while retaining personal information.

[0063] A "user" refers to the entity that operates the system and inputs information.

[0064] "Input information" refers to the data that a user provides to an information processing device.

[0065] "Personal information" refers to information that can identify an individual, including name, address, and contact information.

[0066] "Dummy expressions" are meaningless pieces of information used to transform personal information and are used for privacy protection.

[0067] A "data processing device" refers to an external computer system that collects, processes, and generates responses for information.

[0068] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate information or provide responses.

[0069] "Restoration" refers to the process of returning converted information to its original state without losing any of the original information.

[0070] "Presentation" refers to displaying information to the user and making it available for use.

[0071] This invention is a system consisting of a terminal acting as an information processing device and a data processing device connected via a network. The user provides input information by operating the terminal. The terminal uses a built-in AI agent to analyze the input information and identify personal information. A natural language processing algorithm is used for this analysis. The identified personal information is replaced with a dummy expression to protect privacy. For example, if the input is "I want to change my password," then "password" is identified as personal information and replaced with "DUMMY_KEY."

[0072] When information containing dummy representations is generated, the terminal sends it to a data processing unit via the network. The data processing unit uses a generation AI model to analyze this dummy information and generate a response. The generated response is returned to the terminal while retaining the dummy representations. The terminal then restores the dummy representations in the received response to their original personal information. This process allows the user to receive the necessary information without exposing their privacy.

[0073] As a concrete example, consider a scenario where a user enters the prompt "Please verify my email address." In this message, the "email address" is identified and replaced with "DUMMY_EMAIL." The server generates a response stating "Your DUMMY_EMAIL is already registered," and the terminal restores and presents this message to the user as "Your email address is already registered." This is an effective way to resolve the issue without leaking personal information.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The user operates the device and enters a prompt in a specified format. This input can be a natural language question, such as "Please tell me my phone number." This input forms the basis for processing information in a privacy-protected manner.

[0077] Step 2:

[0078] The device uses a built-in AI agent to analyze the input information. Specifically, it uses natural language processing technology to identify important words and phrases in the text and identify personal information. For example, it identifies the phrase "telephone number" as personal information. The output of this analysis is the identified personal information.

[0079] Step 3:

[0080] The device replaces identified personal information with dummy representations. For example, "phone number" is replaced with "DUMMY_PHONE". This process involves data processing that generates a non-personal information format from the original input containing personal information. The output is a dummy message that reads, "Please tell me my DUMMY_PHONE".

[0081] Step 4:

[0082] The terminal sends a message, replaced with a dummy representation, to the server over the network. The transmitted message does not contain any personal information and is passed to the data processing device in a secure manner. The dummy message prepared as input is sent to the server.

[0083] Step 5:

[0084] The server analyzes the received message and generates a response. A generative AI model is used here, performing data calculations to generate an appropriate response based on the dummy content. The output is a response such as, "Your DUMMY_PHONE is registered in the system."

[0085] Step 6:

[0086] The server sends the generated response back to the terminal over the network. The terminal receives the response from the server and prepares it as input for processing.

[0087] Step 7:

[0088] The terminal restores the dummy representation of the received response message to the original personal information. Specifically, it performs string manipulation to change "DUMMY_PHONE" in the response back to the original "phone number". In this process, the restored original information is obtained as output.

[0089] Step 8:

[0090] The device presents the restored response to the user. The user can receive the information that "Your phone number is registered in the system." At this stage, the ultimate goal of providing information to the user is achieved.

[0091] (Application Example 1)

[0092] 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."

[0093] The protection of personal information has become increasingly important in recent years, and the risk of personal information leakage during data processing over networks has become a particular concern. Conventional systems sometimes do not adequately consider the security of personal information when transmitting it externally, increasing the possibility of information leakage and making it difficult for users to use services with peace of mind. This invention aims to solve these problems and enable users to use services with peace of mind by strengthening the protection of personal information.

[0094] 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.

[0095] In this invention, the server includes means for identifying and specifying personal information, means for converting the identified personal information into replacement words, and means for securely transmitting data using the replacement words to an external information processing system. This makes it possible to securely exchange data over a network while protecting personal information.

[0096] A "user" is a person or entity that operates an information processing device and provides input data.

[0097] "Input data" refers to data supplied by the user to the information processing device, and includes text and other formats that may contain personal information.

[0098] "Identifiable personal information" refers to information that can identify a user, such as name and address, and is data that can be associated with a user.

[0099] A "replacement word" is an artificial word that temporarily replaces the original personal information, enabling data protection and anonymization.

[0100] An "external information processing system" refers to a system that is connected to an information processing device via a network, independently of the information processing device, and includes servers that perform data processing and response generation.

[0101] An "identification information list" is a collection of information pre-configured to identify personal information, and it serves as a standard database.

[0102] A "restored response" is data that has been reconstructed by replacing the substitution words with the original personal information in the response received from an external information processing system.

[0103] This invention relates to an information processing system for the secure handling of user information, providing a technology that protects personal information through the collaborative operation of the user, terminal, and server. Specifically, the user operates the terminal and provides arbitrary input data. An AI agent within the terminal analyzes the input data, identifies identifiable personal information, and converts this information into replacement words. This process utilizes software such as a Python-based AI agent and a Natural Language Processing Toolkit (NLTK).

[0104] The data, converted to replacement words, is sent to the server over the network. On the server side, the data is processed using Django (a Python web framework) or Pandas to generate the necessary response. Here, security is ensured because the data does not contain any personal information and consists only of replacement words.

[0105] When the response from the server is returned to the terminal, the terminal receives it and restores the replaced words to the original personal information. This process uses the Python recovery module on the terminal. The user can then review the restored response and obtain the necessary information. For example, if the user asks, "What are my meeting times this week?", the terminal sends the message "What are my DUMMY_1 times this week?" to the server, receives the response "Your DUMMY_1 is scheduled for 3pm," and restores the information to its original state.

[0106] An example of a prompt message to be input to a generative AI model is as follows:

[0107] Prompt: Analyze the user's question ("User's Question") to identify personal information and convert it into secure replacement words. When you are ready to send it to the server, please provide a message indicating this status.

[0108] This system enables secure information exchange over the network while protecting personal information.

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The user enters a question into the device. This input data may contain personal information in text format. The device verifies whether this input data is correctly formatted.

[0112] Step 2:

[0113] The device analyzes input data using a Python®-based AI agent to identify identifiable personal information. This process utilizes the Natural Language Processing Toolkit (NLTK) to analyze the data structure. As a result of the analysis, the identified personal information is converted into replacement words.

[0114] Step 3:

[0115] The terminal prepares the data converted to replacement words and sends it to the server via the network. Before transmission, the data is encrypted to ensure security. The transmitted data consists only of replacement words and does not contain any personal information.

[0116] Step 4:

[0117] The server processes the received data using the Django framework. This process includes accessing the database, performing necessary calculations, and generating appropriate responses. Here too, a generative AI model is used to optimize response generation.

[0118] Step 5:

[0119] The response generated by the server is sent to the terminal via the network. During this process, the response data is appropriately packaged to minimize the number of bits and reduce response time.

[0120] Step 6:

[0121] The terminal restores the original personal information by replacing the words in the received response data. This restoration process uses a Python restoration module to perform the conversion quickly and accurately.

[0122] Step 7:

[0123] The recovered response is displayed on the terminal for the user to review. The user provides feedback on whether the displayed information is relevant to their needs, which helps improve the accuracy of future analyses.

[0124] 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.

[0125] This invention relates to a system comprising a terminal acting as an information processing device, an external server connected via a network, and an emotion engine. The user utilizes this system by operating the terminal and inputting questions or messages. The AI ​​agent within the terminal acquires the user's input message and simultaneously activates the emotion engine to analyze the user's emotions from the input message.

[0126] The emotion engine uses a predefined emotion recognition model to extract and classify emotional information from user messages. This emotional information helps understand the user's intentions and situation, and is used as reference information in response generation. Based on the emotions extracted by the emotion engine, the AI ​​agent can generate more human-like responses that are appropriate to the user's context.

[0127] This information processing device replaces the user's personal information with dummy words, protecting the user's privacy while transmitting data to an external server. The external server processes the transmitted message, and the generated response message also contains the dummy words. This prevents the leakage of personal information on the server side.

[0128] When the terminal receives a response from an external server, it analyzes the received message, refers to its internally stored mapping table, and restores the dummy words to their original personal information. It then generates a response that takes into account the information from the emotion engine and presents it to the user.

[0129] As a concrete example, suppose a user enters a question into the device such as, "I'm tired. What's on my schedule tomorrow?" At this point, the emotion engine recognizes the emotion "tired." The device replaces the personal information "schedule" with "DUMMY_0." The generated message is sent to an external server in the format "I'm tired. What's DUMMY_0 for tomorrow?". When the server processes the message and returns it to the device, it restores the "schedule" to its original information and displays an emotion-sensitive response to the user, such as, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0130] This system balances user emotional well-being with the protection of personal information, enabling the use of more intuitive and reliable AI agents.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The user enters a question into the device, such as, "I'm tired. What's on the schedule for tomorrow?" Through this message, the user expresses their situation and questions.

[0134] Step 2:

[0135] When the device receives a message from the user, it first activates the emotion engine and analyzes emotional information from the message. From the expression "I'm tired," the emotion "fatigue" is recognized.

[0136] Step 3:

[0137] The AI ​​agent in the device analyzes the words in the user's question and identifies the word "schedule" as personal information according to a predefined list. The identified personal information is replaced with a dummy word, "DUMMY_0". The phrase "tomorrow's schedule" becomes "tomorrow's DUMMY_0".

[0138] Step 4:

[0139] The terminal constructs a message with dummy words replaced, "I'm tired. What's DUMMY_0 tomorrow?", and sends it to an external server.

[0140] Step 5:

[0141] The server receives a message from the terminal. It parses the message, including dummy words, and generates a response message such as "DUMMY_0 has a meeting tomorrow." At this stage, the server processes the message without knowing the original personal information.

[0142] Step 6:

[0143] The server sends back a response message it has generated to the terminal. The response is in the format "There is a meeting tomorrow for DUMMY_0".

[0144] Step 7:

[0145] The terminal receives a response from the server. It analyzes this response and, by referring to its internally stored mapping table, restores the dummy word "DUMMY_0" to "Scheduled".

[0146] Step 8:

[0147] Based on the emotional information, such as "fatigue," provided by the emotion engine, the AI ​​agent adjusts the tone of its response. Ultimately, it generates a response that takes the user's emotions into consideration, such as, "I understand you are tired. You have a meeting scheduled for 2 PM tomorrow."

[0148] Step 9:

[0149] The device then presents the final generated response to the user. This response allows the user to experience emotional satisfaction while simultaneously obtaining the necessary information appropriately.

[0150] (Example 2)

[0151] 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".

[0152] Conventional information processing systems have a problem of data breaches because user input is transmitted directly to external parties. Furthermore, responses often fail to consider the user's feelings, resulting in a poor user experience. This invention aims to generate appropriate responses that consider the user's feelings while protecting privacy.

[0153] 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.

[0154] In this invention, the server includes means for acquiring information from the user, means for replacing private data with alternative words, and means for classifying emotional information using an emotional analysis engine. This makes it possible to provide emotionally sensitive responses while protecting private data.

[0155] A "user" is the entity that inputs information into a system and receives the results.

[0156] "Information" refers to messages and data entered by the user.

[0157] "Private data" refers to data related to a user's personal information and privacy.

[0158] A "substitute word" is a temporary term used to replace private data.

[0159] "Other computers" refers to external processing units used to receive processed information and generate responses.

[0160] "Response information" refers to information generated by another computer and returned to the user.

[0161] An "emotion analysis engine" is a software tool for extracting and classifying emotional information based on user input.

[0162] "Emotional information" refers to categorized information that indicates a user's emotional state.

[0163] "To provide" refers to the act of presenting a response to the user.

[0164] This invention is a system that uses a terminal as an information processing device and interacts with other computers via a network. Users utilize the system by inputting questions and messages using the terminal. The terminal acquires the input information and simultaneously activates an emotion analysis engine to analyze the user's emotions from the input information. The emotion analysis engine analyzes the information using an emotion recognition model and classifies the emotional information.

[0165] The device also identifies the user's private data and replaces it with alternative language, securely transmitting the information to other computers while protecting privacy. Using alternative language prevents private data from being directly exposed externally. The other computers use a generative AI model based on the received information to generate the most appropriate response for the user. Because the response information includes alternative language, the original private data needs to be restored after the device receives it.

[0166] When the device receives a response containing alternative words, it refers to its internal mapping table and restores the original information. Then, taking into account the sentiment information obtained from the sentiment analysis engine, it provides an adjusted response that is appropriate to the user's emotions.

[0167] As a concrete example, if a user enters the question "I'm tired. What's on my schedule tomorrow?" into the device, the sentiment analysis engine recognizes the emotion of "fatigue." The device replaces the information "schedule" with "DUMMY_0" and sends it to another computer in the format "I'm tired. What's DUMMY_0 for tomorrow?". The response message generated by the other computer includes information about "DUMMY_0," which the device then uses to reconstruct "schedule," presenting the user with the response, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0168] An example of a prompt for a generative AI model might be: "Analyze the user's emotions from the following sentence and generate an appropriate response based on those emotions: 'I'm tired. What are my plans for tomorrow?'"

[0169] In this way, we provide a system that can provide accurate responses that are sensitive to user emotions while protecting user privacy.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] The user enters a text message into the device. The user can ask questions or make requests in natural language, and this becomes the input information. A specific example of this action would be the user using the device's input interface to type, "I'm tired. What's on the schedule for tomorrow?"

[0173] Step 2:

[0174] The terminal receives user input and activates the sentiment analysis engine. At this stage, the input is text sent by the user, which the terminal passes to the sentiment analysis engine. As part of the data processing, sentiment information is extracted from the text and the emotion "fatigue" is recognized. The output of this process is the extracted sentiment information. Specifically, this involves the sentiment analysis engine analyzing the text and adding the emotion label "fatigue."

[0175] Step 3:

[0176] The terminal identifies private data from the user's input text and replaces it with a substitute word. Let's assume the input is the original user text containing the private data "schedule". The data calculation involves replacing "schedule" with "DUMMY_0" to protect user privacy. The output of this process is text with the private data replaced. Specifically, the terminal recognizes certain words and converts them to predefined substitute words.

[0177] Step 4:

[0178] The terminal sends a text message containing a substitute word to the server. The input is the substitute text, and the output is this text being transferred to the server over the network. Specifically, this process involves sending the message to another computer using a network protocol.

[0179] Step 5:

[0180] The server processes the received message and generates an appropriate response using a generative AI model. The input is an alternative text message, which the generative AI model parses. The data calculation involves semantic analysis to generate a response such as "DUMMY_0 has a meeting at 2pm tomorrow." The output of this process is the response text. Specifically, the generative AI model performs natural language processing to determine the required response content.

[0181] Step 6:

[0182] The terminal receives a response from the server and, by referring to its internal mapping table, restores the substitute word to the original private data. The input is the response message in its substituted state. The data processing involves restoring the substitute word "DUMMY_0" to "scheduled," and the output is the response text with its original meaning. Specifically, the operation to restore the original word is performed using the substitute word management database.

[0183] Step 7:

[0184] The device uses information from the emotion analysis engine to provide the user with a final, adjusted response. The input is a reconstructed response message that takes into account the emotional information of "fatigue." The final output is a response that is sensitive to the user's emotions. Specific actions include the process of presenting the response message to the user visually or audibly.

[0185] (Application Example 2)

[0186] 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 device 14 will be referred to as the "terminal."

[0187] It is necessary to provide emotionally sensitive communication to elderly users and those who have difficulty expressing their emotions, while protecting personal information and enabling data communication with external systems. Currently, many systems do not accurately understand users' emotions and may respond coldly, and their protection of personal information is insufficient. This leads to problems such as systems being difficult for users to operate and a loss of trust.

[0188] 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.

[0189] In this invention, the server includes means for analyzing and classifying emotional information from the user's input message, means for identifying personal information and replacing it with dummy words, and means for sending a message containing emotional information and dummy words to an external server and generating a response. This enables secure data communication with the system while protecting personal information and generating an emotionally sensitive response.

[0190] An "input message" refers to text or audio that a user provides to the system for the purpose of providing information.

[0191] "Emotional information" refers to data that indicates the user's psychological state, analyzed from input messages, and is a classification and representation of their psychological situation.

[0192] "Personal information" refers to information related to a specific user and data that requires privacy protection.

[0193] A "dummy word" is a substitute symbol or string of characters used to conceal personal information and prevent the leakage of personal information outside of the system.

[0194] An "external server" is a device that exists on the network independently of terminals within the system and provides computing resources for message processing and response generation.

[0195] "Means of restoration" refers to the processes and technologies used to convert dummy words in messages received from external servers back into the original personal information.

[0196] "Care support" refers to services and systems aimed at providing support for daily life and psychological care to elderly people and users who have difficulty expressing their emotions.

[0197] "Considering the user's psychological state" means understanding the user's emotional information and providing appropriate responses and suggestions based on that understanding.

[0198] To realize this invention, the system consists of a user terminal, an external server, and an emotion analysis engine. The user terminal obtains messages from the user through voice input or text input, and uses these as the starting point for processing.

[0199] First, the message spoken or typed by the user is converted into text data by the speech analysis software on the user's terminal. At this time, the emotion analysis engine (EmotionML compatible) analyzes the message and classifies the user's emotional information. The analysis results are used as data indicating the user's psychological state. Next, the terminal identifies personal information from the input message and replaces it with dummy words. This protects privacy and ensures security. The replaced message is sent to an external server via network communication. Efficient data transmission is achieved by using Socket.IO as the communication middleware.

[0200] An external server utilizes a generative AI model to generate responses based on the transmitted message. In this process, the server references emotional information to create natural responses that take the user's psychological state into consideration. Dummy words in the response messages are stored in a secure format that protects the original user data, reducing the risk of personal information being leaked. When the response is returned to the terminal, the terminal uses a predefined mapping table to restore the dummy words to the original personal information. As a result, the user is presented with a response that is appropriately considerate of their original statement.

[0201] For example, if an elderly person says, "I'm a little tired today," the emotion analysis engine will extract the emotion "fatigue." Based on this, the system can make suggestions such as, "Why don't you try to set aside some time to rest today?" As an example of a prompt sentence to input into the generating AI model, the following text is provided: "User statement: 'I'm a little lonely.' Agent response: 'When you feel lonely, it's a good idea to talk to a friend or plan an outing.'" Based on this prompt sentence, the AI ​​generates an appropriate response.

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The user inputs a message via voice or text. This input is the user's raw communication data. The terminal receives this input and, in the case of voice input, converts it to text using speech analysis software. In this process, the input message is transformed from voice data to text data.

[0205] Step 2:

[0206] The terminal activates the emotion analysis engine and analyzes the acquired text data. The input here is the text data obtained in step 1. The emotion analysis engine analyzes the content of the text and extracts emotional information. For example, it identifies and classifies the emotion "fatigue" from the word "tired." In this step, the text data is processed into data that represents emotional information.

[0207] Step 3:

[0208] The device identifies personal information from the input message and replaces the relevant information with dummy words. The original text data is used as input. This data processing transforms personal information into dummy data, thus protecting privacy.

[0209] Step 4:

[0210] The terminal sends text, replaced with sentiment information and dummy words, to an external server. Socket.IO is used for communication. The server analyzes the received data and generates an appropriate response using a generative AI model. Based on the information in this prompt, the AI ​​considers a sentiment-based reply. The server's output is the response message.

[0211] Step 5:

[0212] The terminal reconstructs the dummy words in the response message received from the server into the original personal information. The input is the response message from the server. At this stage, the dummy data is converted back into the original text data, resulting in a process that presents consistent information to the user.

[0213] Step 6:

[0214] The device presents the user with a restored response message and offers thoughtful suggestions based on emotional information. This output is the final information provided to the user. For example, it might be presented as, "I understand you're tired. How about listening to some relaxing music today?"

[0215] 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.

[0216] 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.

[0217] 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.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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).

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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".

[0231] An embodiment of the present invention is a system consisting of a terminal acting as an information processing device and an external server connected via a network. The user operates the terminal to input a question. At this time, an AI agent in the terminal analyzes the question and identifies personal information. The identified personal information is replaced with dummy words, and a newly generated message is sent to the external server via the network.

[0232] The server processes the message received from the terminal. Here, it analyzes the message, even with dummy words included, and generates a response. The generated response is then sent back to the terminal via the network. After receiving the response from the server, the terminal restores the dummy words to the original personal information. This allows the user to verify the information displayed on the terminal.

[0233] As a concrete example, consider a case where a user enters the question "What is my name?" into the device. In this question, the device recognizes the word "name" as personal information and replaces it with the dummy word "DUMMY_0" to generate the message "What is my DUMMY_0?". This message is sent to the server, which processes it and generates the response "Your DUMMY_0 is already registered". The device then restores "DUMMY_0" in the received message back to its original "name" and presents the user with the response "Your name is already registered".

[0234] In this way, users can receive information services from AI agents with peace of mind without exposing their personal information to third parties. This system plays an important role in protecting personal information and can be applied to various information processing devices and services.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The user enters a question into the device. The question may include personal information, such as "What is my name?"

[0238] Step 2:

[0239] The device's AI agent receives the user's question. It analyzes each word in the question and identifies personal information based on a pre-configured list of personal information (e.g., name, address, phone number).

[0240] Step 3:

[0241] The device replaces identified personal information with dummy words. For example, "Name" is replaced with "DUMMY_0". This transforms the question into the format "What is my DUMMY_0?". The replaced personal information is stored in a mapping table that shows which dummy words represent which personal information.

[0242] Step 4:

[0243] The device sends a question, with dummy words replaced, to an external server. Since the sent message does not contain personal information, privacy is protected.

[0244] Step 5:

[0245] The server receives a message from the terminal. Because the message contains dummy words, no personal information is transmitted to the server.

[0246] Step 6:

[0247] The server processes the received message and generates the necessary response. This process is similar to normal natural language processing, creating a response sentence that takes the appropriate context into account based on dummy words.

[0248] Step 7:

[0249] The server sends the generated response to the terminal. Since the server's response also contains dummy words, there is no risk of personal information leakage.

[0250] Step 8:

[0251] The terminal receives a response from the server. It then uses a mapping table to reconstruct the original personal information by replacing dummy words in the received message. For example, in the response "Your DUMMY_0 is already registered," "DUMMY_0" is replaced with "Name."

[0252] Step 9:

[0253] The device presents the restored response to the user. Through this process, the user can confidently use the AI ​​agent's functions.

[0254] (Example 1)

[0255] 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."

[0256] Protecting personal information is a critical issue in today's information society. In particular, there is a risk of personal information being handled inappropriately when users interact with external systems via digital information processing devices. To address this problem, there is a need to provide new methods for users to obtain necessary information while safely and effectively protecting personal information.

[0257] 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.

[0258] In this invention, the server includes means for acquiring input information from a user, means for identifying personal information from the input information and replacing the corresponding personal information with a dummy representation, and means for transmitting the information replaced with the dummy representation to a data processing device. This makes it possible to provide the user with necessary information without communicating with an external system while retaining personal information.

[0259] A "user" refers to the entity that operates the system and inputs information.

[0260] "Input information" refers to the data that a user provides to an information processing device.

[0261] "Personal information" refers to information that can identify an individual, including name, address, and contact information.

[0262] "Dummy expressions" are meaningless pieces of information used to transform personal information and are used for privacy protection.

[0263] A "data processing device" refers to an external computer system that collects, processes, and generates responses for information.

[0264] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate information or provide responses.

[0265] "Restoration" refers to the process of returning converted information to its original state without losing any of the original information.

[0266] "Presentation" refers to displaying information to the user and making it available for use.

[0267] This invention is a system consisting of a terminal acting as an information processing device and a data processing device connected via a network. The user provides input information by operating the terminal. The terminal uses a built-in AI agent to analyze the input information and identify personal information. A natural language processing algorithm is used for this analysis. The identified personal information is replaced with a dummy expression to protect privacy. For example, if the input is "I want to change my password," then "password" is identified as personal information and replaced with "DUMMY_KEY."

[0268] When information containing dummy representations is generated, the terminal sends it to a data processing unit via the network. The data processing unit uses a generation AI model to analyze this dummy information and generate a response. The generated response is returned to the terminal while retaining the dummy representations. The terminal then restores the dummy representations in the received response to their original personal information. This process allows the user to receive the necessary information without exposing their privacy.

[0269] As a concrete example, consider a scenario where a user enters the prompt "Please verify my email address." In this message, the "email address" is identified and replaced with "DUMMY_EMAIL." The server generates a response stating "Your DUMMY_EMAIL is already registered," and the terminal restores and presents this message to the user as "Your email address is already registered." This is an effective way to resolve the issue without leaking personal information.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] The user operates the device and enters a prompt in a specified format. This input can be a natural language question, such as "Please tell me my phone number." This input forms the basis for processing information in a privacy-protected manner.

[0273] Step 2:

[0274] The device uses a built-in AI agent to analyze the input information. Specifically, it uses natural language processing technology to identify important words and phrases in the text and identify personal information. For example, it identifies the phrase "telephone number" as personal information. The output of this analysis is the identified personal information.

[0275] Step 3:

[0276] The terminal replaces the specified personal information with a dummy representation. For example, "phone number" is replaced with "DUMMY_PHONE". In this process, data processing is performed to generate a non-personal information format from the original input containing personal information. As output, a dummy message such as "Please tell me my DUMMY_PHONE" is generated.

[0277] Step 4:

[0278] The terminal sends the message replaced with the dummy representation to the server via the network. The message sent does not contain personal information and is passed to the data processing device in a secure form. The dummy message prepared as input is sent to the server.

[0279] Step 5:

[0280] The server analyzes the received message and generates a response. Here, an AI model is used to perform data calculations to generate an appropriate response based on the dummy content. As output, a response such as "Your DUMMY_PHONE is registered in the system" is generated.

[0281] Step 6:

[0282] [ The server sends the generated response back to the terminal through the network again. The terminal receives the response from the server and prepares it as input for processing.

[0283] Step 7:

[0284] The terminal restores the dummy representation of the received response message to the original personal information. Specifically, a string operation is performed to change "DUMMY_PHONE" in the response back to the original "phone number". In this process, the restored original information is obtained as output.

[0285] Step 8:

[0286] The terminal presents the restored response to the user. The user can receive the information that "your phone number is registered in the system". At this stage, the ultimate goal of providing information to the user is achieved.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0289] The protection of personal information has been increasingly emphasized in recent years. In particular, the risk of personal information leakage during data processing via a network has become a problem. In conventional systems, the security when transmitting personal information externally may not be fully considered, and the possibility of information leakage increases, resulting in the problem that users cannot use services with confidence. The purpose of the present invention is to solve such problems and enable users to use services with confidence by strengthening the protection of personal information.

[0290] 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.

[0291] In this invention, the server includes means for identifying and specifying personal information, means for converting the specified personal information into replacement words, and means for securely transmitting data using the replacement words to an external information processing system. Thereby, it becomes possible to securely exchange data via a network while protecting personal information.

[0292] A "user" is a person or entity who operates an information processing device to provide input data.

[0293] "Input data" is data supplied from a user to an information processing device, and refers to text or other forms that may include personal information.

[0294] "Identifiable personal information" refers to information that can identify a user, such as name and address, and is data that can be associated with a user.

[0295] A "replacement word" is an artificial word that temporarily replaces the original personal information, enabling data protection and anonymization.

[0296] An "external information processing system" refers to a system that is connected to an information processing device via a network, independently of the information processing device, and includes servers that perform data processing and response generation.

[0297] An "identification information list" is a collection of information pre-configured to identify personal information, and it serves as a standard database.

[0298] A "restored response" is data that has been reconstructed by replacing the substitution words with the original personal information in the response received from an external information processing system.

[0299] This invention relates to an information processing system for the secure handling of user information, providing a technology that protects personal information through the collaborative operation of the user, terminal, and server. Specifically, the user operates the terminal and provides arbitrary input data. An AI agent within the terminal analyzes the input data, identifies identifiable personal information, and converts this information into replacement words. This process utilizes software such as a Python-based AI agent and a Natural Language Processing Toolkit (NLTK).

[0300] The data, converted to replacement words, is sent to the server over the network. On the server side, the data is processed using Django (a Python web framework) or Pandas to generate the necessary response. Here, security is ensured because the data does not contain any personal information and consists only of replacement words.

[0301] When the response from the server returns to the terminal, the terminal receives it and restores the replacement words to the original personal information. For this process, the restoration module of Python on the terminal is used. The user can check the restored response and obtain the necessary information. For example, when the user asks "Tell me the meeting time this week", the terminal sends a message "Tell me the DUMMY_1 this week" to the server, receives a response "Your DUMMY_1 is set at 3 pm", and restores it to the original information.

[0302] As an example of the prompt text input to the generative AI model, it can be described as follows.

[0303] Prompt: Analyze the user's question "User's question text" to identify personal information and convert it into a safe replacement word. When the preparation for sending to the server is complete, please present the message in that state.

[0304] With this system, it becomes possible to securely exchange information via the network while protecting personal information.

[0305] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0306] Step 1:

[0307] The user inputs a question to the terminal. This input data may include information that may contain personal information in text form. On the terminal side, it is confirmed whether this input data is correctly formatted.

[0308] Step 2:

[0309] The terminal analyzes the input data using a Python-based AI agent to identify identifiable personal information. In this process, the Natural Language Processing Toolkit (NLTK) is utilized to perform structural analysis of the data. As a result of the analysis, the identified personal information is converted into replacement words.

[0310] Step 3:

[0311] The terminal prepares the data converted to replacement words and sends it to the server via the network. Before transmission, the data is encrypted to ensure security. The transmitted data consists only of replacement words and does not contain any personal information.

[0312] Step 4:

[0313] The server processes the received data using the Django framework. This process includes accessing the database, performing necessary calculations, and generating appropriate responses. Here too, a generative AI model is used to optimize response generation.

[0314] Step 5:

[0315] The response generated by the server is sent to the terminal via the network. During this process, the response data is appropriately packaged to minimize the number of bits and reduce response time.

[0316] Step 6:

[0317] The terminal restores the original personal information by replacing the words in the received response data. This restoration process uses a Python restoration module to perform the conversion quickly and accurately.

[0318] Step 7:

[0319] The recovered response is displayed on the terminal for the user to review. The user provides feedback on whether the displayed information is relevant to their needs, which helps improve the accuracy of future analyses.

[0320] 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.

[0321] This invention relates to a system comprising a terminal acting as an information processing device, an external server connected via a network, and an emotion engine. The user utilizes this system by operating the terminal and inputting questions or messages. The AI ​​agent within the terminal acquires the user's input message and simultaneously activates the emotion engine to analyze the user's emotions from the input message.

[0322] The emotion engine uses a predefined emotion recognition model to extract and classify emotional information from user messages. This emotional information helps understand the user's intentions and situation, and is used as reference information in response generation. Based on the emotions extracted by the emotion engine, the AI ​​agent can generate more human-like responses that are appropriate to the user's context.

[0323] This information processing device replaces the user's personal information with dummy words, protecting the user's privacy while transmitting data to an external server. The external server processes the transmitted message, and the generated response message also contains the dummy words. This prevents the leakage of personal information on the server side.

[0324] When the terminal receives a response from an external server, it analyzes the received message, refers to its internally stored mapping table, and restores the dummy words to their original personal information. It then generates a response that takes into account the information from the emotion engine and presents it to the user.

[0325] As a concrete example, suppose a user enters a question into the device such as, "I'm tired. What's on my schedule tomorrow?" At this point, the emotion engine recognizes the emotion "tired." The device replaces the personal information "schedule" with "DUMMY_0." The generated message is sent to an external server in the format "I'm tired. What's DUMMY_0 for tomorrow?". When the server processes the message and returns it to the device, it restores the "schedule" to its original information and displays an emotion-sensitive response to the user, such as, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0326] This system balances user emotional well-being with the protection of personal information, enabling the use of more intuitive and reliable AI agents.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] The user enters a question into the device, such as, "I'm tired. What's on the schedule for tomorrow?" Through this message, the user expresses their situation and questions.

[0330] Step 2:

[0331] When the device receives a message from the user, it first activates the emotion engine and analyzes emotional information from the message. From the expression "I'm tired," the emotion "fatigue" is recognized.

[0332] Step 3:

[0333] The AI ​​agent in the device analyzes the words in the user's question and identifies the word "schedule" as personal information according to a predefined list. The identified personal information is replaced with a dummy word, "DUMMY_0". The phrase "tomorrow's schedule" becomes "tomorrow's DUMMY_0".

[0334] Step 4:

[0335] The terminal constructs a message with dummy words replaced, "I'm tired. What's DUMMY_0 tomorrow?", and sends it to an external server.

[0336] Step 5:

[0337] The server receives a message from the terminal. It parses the message, including dummy words, and generates a response message such as "DUMMY_0 has a meeting tomorrow." At this stage, the server processes the message without knowing the original personal information.

[0338] Step 6:

[0339] The server sends back a response message it has generated to the terminal. The response is in the format "There is a meeting tomorrow for DUMMY_0".

[0340] Step 7:

[0341] The terminal receives a response from the server. It analyzes this response and, by referring to its internally stored mapping table, restores the dummy word "DUMMY_0" to "Scheduled".

[0342] Step 8:

[0343] Based on the emotional information, such as "fatigue," provided by the emotion engine, the AI ​​agent adjusts the tone of its response. Ultimately, it generates a response that takes the user's emotions into consideration, such as, "I understand you are tired. You have a meeting scheduled for 2 PM tomorrow."

[0344] Step 9:

[0345] The device then presents the final generated response to the user. This response allows the user to experience emotional satisfaction while simultaneously obtaining the necessary information appropriately.

[0346] (Example 2)

[0347] 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".

[0348] Conventional information processing systems have a problem of data breaches because user input is transmitted directly to external parties. Furthermore, responses often fail to consider the user's feelings, resulting in a poor user experience. This invention aims to generate appropriate responses that consider the user's feelings while protecting privacy.

[0349] 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.

[0350] In this invention, the server includes means for acquiring information from the user, means for replacing private data with alternative words, and means for classifying emotional information using an emotional analysis engine. This makes it possible to provide emotionally sensitive responses while protecting private data.

[0351] A "user" is the entity that inputs information into a system and receives the results.

[0352] "Information" refers to messages and data entered by the user.

[0353] "Private data" refers to data related to a user's personal information and privacy.

[0354] A "substitute word" is a temporary term used to replace private data.

[0355] "Other computers" refers to external processing units used to receive processed information and generate responses.

[0356] "Response information" refers to information generated by another computer and returned to the user.

[0357] An "emotion analysis engine" is a software tool for extracting and classifying emotional information based on user input.

[0358] "Emotional information" refers to categorized information that indicates a user's emotional state.

[0359] "To provide" refers to the act of presenting a response to the user.

[0360] This invention is a system that uses a terminal as an information processing device and interacts with other computers via a network. Users utilize the system by inputting questions and messages using the terminal. The terminal acquires the input information and simultaneously activates an emotion analysis engine to analyze the user's emotions from the input information. The emotion analysis engine analyzes the information using an emotion recognition model and classifies the emotional information.

[0361] The device also identifies the user's private data and replaces it with alternative language, securely transmitting the information to other computers while protecting privacy. Using alternative language prevents private data from being directly exposed externally. The other computers use a generative AI model based on the received information to generate the most appropriate response for the user. Because the response information includes alternative language, the original private data needs to be restored after the device receives it.

[0362] When the device receives a response containing alternative words, it refers to its internal mapping table and restores the original information. Then, taking into account the sentiment information obtained from the sentiment analysis engine, it provides an adjusted response that is appropriate to the user's emotions.

[0363] As a concrete example, if a user enters the question "I'm tired. What's on my schedule tomorrow?" into the device, the sentiment analysis engine recognizes the emotion of "fatigue." The device replaces the information "schedule" with "DUMMY_0" and sends it to another computer in the format "I'm tired. What's DUMMY_0 for tomorrow?". The response message generated by the other computer includes information about "DUMMY_0," which the device then uses to reconstruct "schedule," presenting the user with the response, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0364] An example of a prompt for a generative AI model might be: "Analyze the user's emotions from the following sentence and generate an appropriate response based on those emotions: 'I'm tired. What are my plans for tomorrow?'"

[0365] In this way, we provide a system that can provide accurate responses that are sensitive to user emotions while protecting user privacy.

[0366] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0367] Step 1:

[0368] The user enters a text message into the device. The user can ask questions or make requests in natural language, and this becomes the input information. A specific example of this action would be the user using the device's input interface to type, "I'm tired. What's on the schedule for tomorrow?"

[0369] Step 2:

[0370] The terminal receives user input and activates the sentiment analysis engine. At this stage, the input is text sent by the user, which the terminal passes to the sentiment analysis engine. As part of the data processing, sentiment information is extracted from the text and the emotion "fatigue" is recognized. The output of this process is the extracted sentiment information. Specifically, this involves the sentiment analysis engine analyzing the text and adding the emotion label "fatigue."

[0371] Step 3:

[0372] The terminal identifies private data from the user's input text and replaces it with a substitute word. Let's assume the input is the original user text containing the private data "schedule". The data calculation involves replacing "schedule" with "DUMMY_0" to protect user privacy. The output of this process is text with the private data replaced. Specifically, the terminal recognizes certain words and converts them to predefined substitute words.

[0373] Step 4:

[0374] The terminal sends a text message containing a substitute word to the server. The input is the substitute text, and the output is this text being transferred to the server over the network. Specifically, this process involves sending the message to another computer using a network protocol.

[0375] Step 5:

[0376] The server processes the received message and generates an appropriate response using a generative AI model. The input is an alternative text message, which the generative AI model parses. The data calculation involves semantic analysis to generate a response such as "DUMMY_0 has a meeting at 2pm tomorrow." The output of this process is the response text. Specifically, the generative AI model performs natural language processing to determine the required response content.

[0377] Step 6:

[0378] The terminal receives a response from the server and, by referring to its internal mapping table, restores the substitute word to the original private data. The input is the response message in its substituted state. The data processing involves restoring the substitute word "DUMMY_0" to "scheduled," and the output is the response text with its original meaning. Specifically, the operation to restore the original word is performed using the substitute word management database.

[0379] Step 7:

[0380] The device uses information from the emotion analysis engine to provide the user with a final, adjusted response. The input is a reconstructed response message that takes into account the emotional information of "fatigue." The final output is a response that is sensitive to the user's emotions. Specific actions include the process of presenting the response message to the user visually or audibly.

[0381] (Application Example 2)

[0382] 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 as the "terminal".

[0383] It is necessary to provide emotionally sensitive communication to elderly users and those who have difficulty expressing their emotions, while protecting personal information and enabling data communication with external systems. Currently, many systems do not accurately understand users' emotions and may respond coldly, and their protection of personal information is insufficient. This leads to problems such as systems being difficult for users to operate and a loss of trust.

[0384] 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.

[0385] In this invention, the server includes means for analyzing and classifying emotional information from the user's input message, means for identifying personal information and replacing it with dummy words, and means for sending a message containing emotional information and dummy words to an external server and generating a response. This enables secure data communication with the system while protecting personal information and generating an emotionally sensitive response.

[0386] An "input message" refers to text or audio that a user provides to the system for the purpose of providing information.

[0387] "Emotional information" refers to data that indicates the user's psychological state, analyzed from input messages, and is a classification and representation of their psychological situation.

[0388] "Personal information" refers to information related to a specific user and data that requires privacy protection.

[0389] A "dummy word" is a substitute symbol or string of characters used to conceal personal information and prevent the leakage of personal information outside of the system.

[0390] An "external server" is a device that exists on the network independently of terminals within the system and provides computing resources for message processing and response generation.

[0391] "Means of restoration" refers to the processes and technologies used to convert dummy words in messages received from external servers back into the original personal information.

[0392] "Care support" refers to services and systems aimed at providing support for daily life and psychological care to elderly people and users who have difficulty expressing their emotions.

[0393] "Considering the user's psychological state" means understanding the user's emotional information and providing appropriate responses and suggestions based on that understanding.

[0394] To realize this invention, the system consists of a user terminal, an external server, and an emotion analysis engine. The user terminal obtains messages from the user through voice input or text input, and uses these as the starting point for processing.

[0395] First, the message spoken or typed by the user is converted into text data by the speech analysis software on the user's terminal. At this time, the emotion analysis engine (EmotionML compatible) analyzes the message and classifies the user's emotional information. The analysis results are used as data indicating the user's psychological state. Next, the terminal identifies personal information from the input message and replaces it with dummy words. This protects privacy and ensures security. The replaced message is sent to an external server via network communication. Efficient data transmission is achieved by using Socket.IO as the communication middleware.

[0396] An external server utilizes a generative AI model to generate responses based on the transmitted message. In this process, the server references emotional information to create natural responses that take the user's psychological state into consideration. Dummy words in the response messages are stored in a secure format that protects the original user data, reducing the risk of personal information being leaked. When the response is returned to the terminal, the terminal uses a predefined mapping table to restore the dummy words to the original personal information. As a result, the user is presented with a response that is appropriately considerate of their original statement.

[0397] For example, if an elderly person says, "I'm a little tired today," the emotion analysis engine will extract the emotion "fatigue." Based on this, the system can make suggestions such as, "Why don't you try to set aside some time to rest today?" As an example of a prompt sentence to input into the generating AI model, the following text is provided: "User statement: 'I'm a little lonely.' Agent response: 'When you feel lonely, it's a good idea to talk to a friend or plan an outing.'" Based on this prompt sentence, the AI ​​generates an appropriate response.

[0398] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0399] Step 1:

[0400] The user inputs a message via voice or text. This input is the user's raw communication data. The terminal receives this input and, in the case of voice input, converts it to text using speech analysis software. In this process, the input message is transformed from voice data to text data.

[0401] Step 2:

[0402] The terminal activates the emotion analysis engine and analyzes the acquired text data. The input here is the text data obtained in step 1. The emotion analysis engine analyzes the content of the text and extracts emotional information. For example, it identifies and classifies the emotion "fatigue" from the word "tired." In this step, the text data is processed into data that represents emotional information.

[0403] Step 3:

[0404] The device identifies personal information from the input message and replaces the relevant information with dummy words. The original text data is used as input. This data processing transforms personal information into dummy data, thus protecting privacy.

[0405] Step 4:

[0406] The terminal sends text, replaced with sentiment information and dummy words, to an external server. Socket.IO is used for communication. The server analyzes the received data and generates an appropriate response using a generative AI model. Based on the information in this prompt, the AI ​​considers a sentiment-based reply. The server's output is the response message.

[0407] Step 5:

[0408] The terminal reconstructs the dummy words in the response message received from the server into the original personal information. The input is the response message from the server. At this stage, the dummy data is converted back into the original text data, resulting in a process that presents consistent information to the user.

[0409] Step 6:

[0410] The device presents the user with a restored response message and offers thoughtful suggestions based on emotional information. This output is the final information provided to the user. For example, it might be presented as, "I understand you're tired. How about listening to some relaxing music today?"

[0411] 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.

[0412] 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.

[0413] 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.

[0414] [Third Embodiment]

[0415] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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).

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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".

[0427] An embodiment of the present invention is a system consisting of a terminal acting as an information processing device and an external server connected via a network. The user operates the terminal to input a question. At this time, an AI agent in the terminal analyzes the question and identifies personal information. The identified personal information is replaced with dummy words, and a newly generated message is sent to the external server via the network.

[0428] The server processes the message received from the terminal. Here, it analyzes the message, even with dummy words included, and generates a response. The generated response is then sent back to the terminal via the network. After receiving the response from the server, the terminal restores the dummy words to the original personal information. This allows the user to verify the information displayed on the terminal.

[0429] As a concrete example, consider a case where a user enters the question "What is my name?" into the device. In this question, the device recognizes the word "name" as personal information and replaces it with the dummy word "DUMMY_0" to generate the message "What is my DUMMY_0?". This message is sent to the server, which processes it and generates the response "Your DUMMY_0 is already registered". The device then restores "DUMMY_0" in the received message back to its original "name" and presents the user with the response "Your name is already registered".

[0430] In this way, users can receive information services from AI agents with peace of mind without exposing their personal information to third parties. This system plays an important role in protecting personal information and can be applied to various information processing devices and services.

[0431] The following describes the processing flow.

[0432] Step 1:

[0433] The user enters a question into the device. The question may include personal information, such as "What is my name?"

[0434] Step 2:

[0435] The device's AI agent receives the user's question. It analyzes each word in the question and identifies personal information based on a pre-configured list of personal information (e.g., name, address, phone number).

[0436] Step 3:

[0437] The device replaces identified personal information with dummy words. For example, "Name" is replaced with "DUMMY_0". This transforms the question into the format "What is my DUMMY_0?". The replaced personal information is stored in a mapping table that shows which dummy words represent which personal information.

[0438] Step 4:

[0439] The device sends a question, with dummy words replaced, to an external server. Since the sent message does not contain personal information, privacy is protected.

[0440] Step 5:

[0441] The server receives a message from the terminal. Because the message contains dummy words, no personal information is transmitted to the server.

[0442] Step 6:

[0443] The server processes the received message and generates the necessary response. This process is similar to normal natural language processing, creating a response sentence that takes the appropriate context into account based on dummy words.

[0444] Step 7:

[0445] The server sends the generated response to the terminal. Since the server's response also contains dummy words, there is no risk of personal information leakage.

[0446] Step 8:

[0447] The terminal receives a response from the server. It then uses a mapping table to reconstruct the original personal information by replacing dummy words in the received message. For example, in the response "Your DUMMY_0 is already registered," "DUMMY_0" is replaced with "Name."

[0448] Step 9:

[0449] The device presents the restored response to the user. Through this process, the user can confidently use the AI ​​agent's functions.

[0450] (Example 1)

[0451] 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."

[0452] Protecting personal information is a critical issue in today's information society. In particular, there is a risk of personal information being handled inappropriately when users interact with external systems via digital information processing devices. To address this problem, there is a need to provide new methods for users to obtain necessary information while safely and effectively protecting personal information.

[0453] 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.

[0454] In this invention, the server includes means for acquiring input information from a user, means for identifying personal information from the input information and replacing the corresponding personal information with a dummy representation, and means for transmitting the information replaced with the dummy representation to a data processing device. This makes it possible to provide the user with necessary information without communicating with an external system while retaining personal information.

[0455] A "user" refers to the entity that operates the system and inputs information.

[0456] "Input information" refers to the data that a user provides to an information processing device.

[0457] "Personal information" refers to information that can identify an individual, including name, address, and contact information.

[0458] "Dummy expressions" are meaningless pieces of information used to transform personal information and are used for privacy protection.

[0459] A "data processing device" refers to an external computer system that collects, processes, and generates responses for information.

[0460] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate information or provide responses.

[0461] "Restoration" refers to the process of returning converted information to its original state without losing any of the original information.

[0462] "Presentation" refers to displaying information to the user and making it available for use.

[0463] This invention is a system consisting of a terminal acting as an information processing device and a data processing device connected via a network. The user provides input information by operating the terminal. The terminal uses a built-in AI agent to analyze the input information and identify personal information. A natural language processing algorithm is used for this analysis. The identified personal information is replaced with a dummy expression to protect privacy. For example, if the input is "I want to change my password," then "password" is identified as personal information and replaced with "DUMMY_KEY."

[0464] When information containing dummy representations is generated, the terminal sends it to a data processing unit via the network. The data processing unit uses a generation AI model to analyze this dummy information and generate a response. The generated response is returned to the terminal while retaining the dummy representations. The terminal then restores the dummy representations in the received response to their original personal information. This process allows the user to receive the necessary information without exposing their privacy.

[0465] As a concrete example, consider a scenario where a user enters the prompt "Please verify my email address." In this message, the "email address" is identified and replaced with "DUMMY_EMAIL." The server generates a response stating "Your DUMMY_EMAIL is already registered," and the terminal restores and presents this message to the user as "Your email address is already registered." This is an effective way to resolve the issue without leaking personal information.

[0466] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0467] Step 1:

[0468] The user operates the device and enters a prompt in a specified format. This input can be a natural language question, such as "Please tell me my phone number." This input forms the basis for processing information in a privacy-protected manner.

[0469] Step 2:

[0470] The device uses a built-in AI agent to analyze the input information. Specifically, it uses natural language processing technology to identify important words and phrases in the text and identify personal information. For example, it identifies the phrase "telephone number" as personal information. The output of this analysis is the identified personal information.

[0471] Step 3:

[0472] The device replaces identified personal information with dummy representations. For example, "phone number" is replaced with "DUMMY_PHONE". This process involves data processing that generates a non-personal information format from the original input containing personal information. The output is a dummy message that reads, "Please tell me my DUMMY_PHONE".

[0473] Step 4:

[0474] The terminal sends a message, replaced with a dummy representation, to the server over the network. The transmitted message does not contain any personal information and is passed to the data processing device in a secure manner. The dummy message prepared as input is sent to the server.

[0475] Step 5:

[0476] The server analyzes the received message and generates a response. A generative AI model is used here, performing data calculations to generate an appropriate response based on the dummy content. The output is a response such as, "Your DUMMY_PHONE is registered in the system."

[0477] Step 6:

[0478] The server sends the generated response back to the terminal over the network. The terminal receives the response from the server and prepares it as input for processing.

[0479] Step 7:

[0480] The terminal restores the dummy representation of the received response message to the original personal information. Specifically, it performs string manipulation to change "DUMMY_PHONE" in the response back to the original "phone number". In this process, the restored original information is obtained as output.

[0481] Step 8:

[0482] The device presents the restored response to the user. The user can receive the information that "Your phone number is registered in the system." At this stage, the ultimate goal of providing information to the user is achieved.

[0483] (Application Example 1)

[0484] 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."

[0485] The protection of personal information has become increasingly important in recent years, and the risk of personal information leakage during data processing over networks has become a particular concern. Conventional systems sometimes do not adequately consider the security of personal information when transmitting it externally, increasing the possibility of information leakage and making it difficult for users to use services with peace of mind. This invention aims to solve these problems and enable users to use services with peace of mind by strengthening the protection of personal information.

[0486] 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.

[0487] In this invention, the server includes means for identifying and specifying personal information, means for converting the identified personal information into replacement words, and means for securely transmitting data using the replacement words to an external information processing system. This makes it possible to securely exchange data over a network while protecting personal information.

[0488] A "user" is a person or entity that operates an information processing device and provides input data.

[0489] "Input data" refers to data supplied by the user to the information processing device, and includes text and other formats that may contain personal information.

[0490] "Identifiable personal information" refers to information that can identify a user, such as name and address, and is data that can be associated with a user.

[0491] A "replacement word" is an artificial word that temporarily replaces the original personal information, enabling data protection and anonymization.

[0492] An "external information processing system" refers to a system that is connected to an information processing device via a network, independently of the information processing device, and includes servers that perform data processing and response generation.

[0493] An "identification information list" is a collection of information pre-configured to identify personal information, and it serves as a standard database.

[0494] A "restored response" is data that has been reconstructed by replacing the substitution words with the original personal information in the response received from an external information processing system.

[0495] This invention relates to an information processing system for the secure handling of user information, providing a technology that protects personal information through the collaborative operation of the user, terminal, and server. Specifically, the user operates the terminal and provides arbitrary input data. An AI agent within the terminal analyzes the input data, identifies identifiable personal information, and converts this information into replacement words. This process utilizes software such as a Python-based AI agent and a Natural Language Processing Toolkit (NLTK).

[0496] The data, converted to replacement words, is sent to the server over the network. On the server side, the data is processed using Django (a Python web framework) or Pandas to generate the necessary response. Here, security is ensured because the data does not contain any personal information and consists only of replacement words.

[0497] When the response from the server is returned to the terminal, the terminal receives it and restores the replaced words to the original personal information. This process uses the Python recovery module on the terminal. The user can then review the restored response and obtain the necessary information. For example, if the user asks, "What are my meeting times this week?", the terminal sends the message "What are my DUMMY_1 times this week?" to the server, receives the response "Your DUMMY_1 is scheduled for 3pm," and restores the information to its original state.

[0498] An example of a prompt message to be input to a generative AI model is as follows:

[0499] Prompt: Analyze the user's question ("User's Question") to identify personal information and convert it into secure replacement words. When you are ready to send it to the server, please provide a message indicating this status.

[0500] This system enables secure information exchange over the network while protecting personal information.

[0501] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0502] Step 1:

[0503] The user enters a question into the device. This input data may contain personal information in text format. The device verifies whether this input data is correctly formatted.

[0504] Step 2:

[0505] The device analyzes input data using a Python-based AI agent to identify identifiable personal information. This process utilizes the Natural Language Processing Toolkit (NLTK) to analyze the data structure. The identified personal information is then converted into replacement words.

[0506] Step 3:

[0507] The terminal prepares the data converted to replacement words and sends it to the server via the network. Before transmission, the data is encrypted to ensure security. The transmitted data consists only of replacement words and does not contain any personal information.

[0508] Step 4:

[0509] The server processes the received data using the Django framework. This process includes accessing the database, performing necessary calculations, and generating appropriate responses. Here too, a generative AI model is used to optimize response generation.

[0510] Step 5:

[0511] The response generated by the server is sent to the terminal via the network. During this process, the response data is appropriately packaged to minimize the number of bits and reduce response time.

[0512] Step 6:

[0513] The terminal restores the original personal information by replacing the words in the received response data. This restoration process uses a Python restoration module to perform the conversion quickly and accurately.

[0514] Step 7:

[0515] The recovered response is displayed on the terminal for the user to review. The user provides feedback on whether the displayed information is relevant to their needs, which helps improve the accuracy of future analyses.

[0516] 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.

[0517] This invention relates to a system comprising a terminal acting as an information processing device, an external server connected via a network, and an emotion engine. The user utilizes this system by operating the terminal and inputting questions or messages. The AI ​​agent within the terminal acquires the user's input message and simultaneously activates the emotion engine to analyze the user's emotions from the input message.

[0518] The emotion engine uses a predefined emotion recognition model to extract and classify emotional information from user messages. This emotional information helps understand the user's intentions and situation, and is used as reference information in response generation. Based on the emotions extracted by the emotion engine, the AI ​​agent can generate more human-like responses that are appropriate to the user's context.

[0519] This information processing device replaces the user's personal information with dummy words, protecting the user's privacy while transmitting data to an external server. The external server processes the transmitted message, and the generated response message also contains the dummy words. This prevents the leakage of personal information on the server side.

[0520] When the terminal receives a response from an external server, it analyzes the received message, refers to its internally stored mapping table, and restores the dummy words to their original personal information. It then generates a response that takes into account the information from the emotion engine and presents it to the user.

[0521] As a concrete example, suppose a user enters a question into the device such as, "I'm tired. What's on my schedule tomorrow?" At this point, the emotion engine recognizes the emotion "tired." The device replaces the personal information "schedule" with "DUMMY_0." The generated message is sent to an external server in the format "I'm tired. What's DUMMY_0 for tomorrow?". When the server processes the message and returns it to the device, it restores the "schedule" to its original information and displays an emotion-sensitive response to the user, such as, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0522] This system balances user emotional well-being with the protection of personal information, enabling the use of more intuitive and reliable AI agents.

[0523] The following describes the processing flow.

[0524] Step 1:

[0525] The user enters a question into the device, such as, "I'm tired. What's on the schedule for tomorrow?" Through this message, the user expresses their situation and questions.

[0526] Step 2:

[0527] When the device receives a message from the user, it first activates the emotion engine and analyzes emotional information from the message. From the expression "I'm tired," the emotion "fatigue" is recognized.

[0528] Step 3:

[0529] The AI ​​agent in the device analyzes the words in the user's question and identifies the word "schedule" as personal information according to a predefined list. The identified personal information is replaced with a dummy word, "DUMMY_0". The phrase "tomorrow's schedule" becomes "tomorrow's DUMMY_0".

[0530] Step 4:

[0531] The terminal constructs a message with dummy words replaced, "I'm tired. What's DUMMY_0 tomorrow?", and sends it to an external server.

[0532] Step 5:

[0533] The server receives a message from the terminal. It parses the message, including dummy words, and generates a response message such as "DUMMY_0 has a meeting tomorrow." At this stage, the server processes the message without knowing the original personal information.

[0534] Step 6:

[0535] The server sends back a response message it has generated to the terminal. The response is in the format "There is a meeting tomorrow for DUMMY_0".

[0536] Step 7:

[0537] The terminal receives a response from the server. It analyzes this response and, by referring to its internally stored mapping table, restores the dummy word "DUMMY_0" to "Scheduled".

[0538] Step 8:

[0539] Based on the emotional information, such as "fatigue," provided by the emotion engine, the AI ​​agent adjusts the tone of its response. Ultimately, it generates a response that takes the user's emotions into consideration, such as, "I understand you are tired. You have a meeting scheduled for 2 PM tomorrow."

[0540] Step 9:

[0541] The device then presents the final generated response to the user. This response allows the user to experience emotional satisfaction while simultaneously obtaining the necessary information appropriately.

[0542] (Example 2)

[0543] 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."

[0544] Conventional information processing systems have a problem of data breaches because user input is transmitted directly to external parties. Furthermore, responses often fail to consider the user's feelings, resulting in a poor user experience. This invention aims to generate appropriate responses that consider the user's feelings while protecting privacy.

[0545] 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.

[0546] In this invention, the server includes means for acquiring information from the user, means for replacing private data with alternative words, and means for classifying emotional information using an emotional analysis engine. This makes it possible to provide emotionally sensitive responses while protecting private data.

[0547] A "user" is the entity that inputs information into a system and receives the results.

[0548] "Information" refers to messages and data entered by the user.

[0549] "Private data" refers to data related to a user's personal information and privacy.

[0550] A "substitute word" is a temporary term used to replace private data.

[0551] "Other computers" refers to external processing units used to receive processed information and generate responses.

[0552] "Response information" refers to information generated by another computer and returned to the user.

[0553] An "emotion analysis engine" is a software tool for extracting and classifying emotional information based on user input.

[0554] "Emotional information" refers to categorized information that indicates a user's emotional state.

[0555] "To provide" refers to the act of presenting a response to the user.

[0556] This invention is a system that uses a terminal as an information processing device and interacts with other computers via a network. Users utilize the system by inputting questions and messages using the terminal. The terminal acquires the input information and simultaneously activates an emotion analysis engine to analyze the user's emotions from the input information. The emotion analysis engine analyzes the information using an emotion recognition model and classifies the emotional information.

[0557] The device also identifies the user's private data and replaces it with alternative language, securely transmitting the information to other computers while protecting privacy. Using alternative language prevents private data from being directly exposed externally. The other computers use a generative AI model based on the received information to generate the most appropriate response for the user. Because the response information includes alternative language, the original private data needs to be restored after the device receives it.

[0558] When the device receives a response containing alternative words, it refers to its internal mapping table and restores the original information. Then, taking into account the sentiment information obtained from the sentiment analysis engine, it provides an adjusted response that is appropriate to the user's emotions.

[0559] As a concrete example, if a user enters the question "I'm tired. What's on my schedule tomorrow?" into the device, the sentiment analysis engine recognizes the emotion of "fatigue." The device replaces the information "schedule" with "DUMMY_0" and sends it to another computer in the format "I'm tired. What's DUMMY_0 for tomorrow?". The response message generated by the other computer includes information about "DUMMY_0," which the device then uses to reconstruct "schedule," presenting the user with the response, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0560] An example of a prompt for a generative AI model might be: "Analyze the user's emotions from the following sentence and generate an appropriate response based on those emotions: 'I'm tired. What are my plans for tomorrow?'"

[0561] In this way, we provide a system that can provide accurate responses that are sensitive to user emotions while protecting user privacy.

[0562] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0563] Step 1:

[0564] The user enters a text message into the device. The user can ask questions or make requests in natural language, and this becomes the input information. A specific example of this action would be the user using the device's input interface to type, "I'm tired. What's on the schedule for tomorrow?"

[0565] Step 2:

[0566] The terminal receives user input and activates the sentiment analysis engine. At this stage, the input is text sent by the user, which the terminal passes to the sentiment analysis engine. As part of the data processing, sentiment information is extracted from the text and the emotion "fatigue" is recognized. The output of this process is the extracted sentiment information. Specifically, this involves the sentiment analysis engine analyzing the text and adding the emotion label "fatigue."

[0567] Step 3:

[0568] The terminal identifies private data from the user's input text and replaces it with a substitute word. Let's assume the input is the original user text containing the private data "schedule". The data calculation involves replacing "schedule" with "DUMMY_0" to protect user privacy. The output of this process is text with the private data replaced. Specifically, the terminal recognizes certain words and converts them to predefined substitute words.

[0569] Step 4:

[0570] The terminal sends a text message containing a substitute word to the server. The input is the substitute text, and the output is this text being transferred to the server over the network. Specifically, this process involves sending the message to another computer using a network protocol.

[0571] Step 5:

[0572] The server processes the received message and generates an appropriate response using a generative AI model. The input is an alternative text message, which the generative AI model parses. The data calculation involves semantic analysis to generate a response such as "DUMMY_0 has a meeting at 2pm tomorrow." The output of this process is the response text. Specifically, the generative AI model performs natural language processing to determine the required response content.

[0573] Step 6:

[0574] The terminal receives a response from the server and, by referring to its internal mapping table, restores the substitute word to the original private data. The input is the response message in its substituted state. The data processing involves restoring the substitute word "DUMMY_0" to "scheduled," and the output is the response text with its original meaning. Specifically, the operation to restore the original word is performed using the substitute word management database.

[0575] Step 7:

[0576] The device uses information from the emotion analysis engine to provide the user with a final, adjusted response. The input is a reconstructed response message that takes into account the emotional information of "fatigue." The final output is a response that is sensitive to the user's emotions. Specific actions include the process of presenting the response message to the user visually or audibly.

[0577] (Application Example 2)

[0578] 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."

[0579] It is necessary to provide emotionally sensitive communication to elderly users and those who have difficulty expressing their emotions, while protecting personal information and enabling data communication with external systems. Currently, many systems do not accurately understand users' emotions and may respond coldly, and their protection of personal information is insufficient. This leads to problems such as systems being difficult for users to operate and a loss of trust.

[0580] 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.

[0581] In this invention, the server includes means for analyzing and classifying emotional information from the user's input message, means for identifying personal information and replacing it with dummy words, and means for sending a message containing emotional information and dummy words to an external server and generating a response. This enables secure data communication with the system while protecting personal information and generating an emotionally sensitive response.

[0582] An "input message" refers to text or audio that a user provides to the system for the purpose of providing information.

[0583] "Emotional information" refers to data that indicates the user's psychological state, analyzed from input messages, and is a classification and representation of their psychological situation.

[0584] "Personal information" refers to information related to a specific user and data that requires privacy protection.

[0585] A "dummy word" is a substitute symbol or string of characters used to conceal personal information and prevent the leakage of personal information outside of the system.

[0586] An "external server" is a device that exists on the network independently of terminals within the system and provides computing resources for message processing and response generation.

[0587] "Means of restoration" refers to the processes and technologies used to convert dummy words in messages received from external servers back into the original personal information.

[0588] "Care support" refers to services and systems aimed at providing support for daily life and psychological care to elderly people and users who have difficulty expressing their emotions.

[0589] "Considering the user's psychological state" means understanding the user's emotional information and providing appropriate responses and suggestions based on that understanding.

[0590] To realize this invention, the system consists of a user terminal, an external server, and an emotion analysis engine. The user terminal obtains messages from the user through voice input or text input, and uses these as the starting point for processing.

[0591] First, the message spoken or typed by the user is converted into text data by the speech analysis software on the user's terminal. At this time, the emotion analysis engine (EmotionML compatible) analyzes the message and classifies the user's emotional information. The analysis results are used as data indicating the user's psychological state. Next, the terminal identifies personal information from the input message and replaces it with dummy words. This protects privacy and ensures security. The replaced message is sent to an external server via network communication. Efficient data transmission is achieved by using Socket.IO as the communication middleware.

[0592] An external server utilizes a generative AI model to generate responses based on the transmitted message. In this process, the server references emotional information to create natural responses that take the user's psychological state into consideration. Dummy words in the response messages are stored in a secure format that protects the original user data, reducing the risk of personal information being leaked. When the response is returned to the terminal, the terminal uses a predefined mapping table to restore the dummy words to the original personal information. As a result, the user is presented with a response that is appropriately considerate of their original statement.

[0593] For example, if an elderly person says, "I'm a little tired today," the emotion analysis engine will extract the emotion "fatigue." Based on this, the system can make suggestions such as, "Why don't you try to set aside some time to rest today?" As an example of a prompt sentence to input into the generating AI model, the following text is provided: "User statement: 'I'm a little lonely.' Agent response: 'When you feel lonely, it's a good idea to talk to a friend or plan an outing.'" Based on this prompt sentence, the AI ​​generates an appropriate response.

[0594] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0595] Step 1:

[0596] The user inputs a message via voice or text. This input is the user's raw communication data. The terminal receives this input and, in the case of voice input, converts it to text using speech analysis software. In this process, the input message is transformed from voice data to text data.

[0597] Step 2:

[0598] The terminal activates the emotion analysis engine and analyzes the acquired text data. The input here is the text data obtained in step 1. The emotion analysis engine analyzes the content of the text and extracts emotional information. For example, it identifies and classifies the emotion "fatigue" from the word "tired." In this step, the text data is processed into data that represents emotional information.

[0599] Step 3:

[0600] The device identifies personal information from the input message and replaces the relevant information with dummy words. The original text data is used as input. This data processing transforms personal information into dummy data, thus protecting privacy.

[0601] Step 4:

[0602] The terminal sends text, replaced with sentiment information and dummy words, to an external server. Socket.IO is used for communication. The server analyzes the received data and generates an appropriate response using a generative AI model. Based on the information in this prompt, the AI ​​considers a sentiment-based reply. The server's output is the response message.

[0603] Step 5:

[0604] The terminal reconstructs the dummy words in the response message received from the server into the original personal information. The input is the response message from the server. At this stage, the dummy data is converted back into the original text data, resulting in a process that presents consistent information to the user.

[0605] Step 6:

[0606] The device presents the user with a restored response message and offers thoughtful suggestions based on emotional information. This output is the final information provided to the user. For example, it might be presented as, "I understand you're tired. How about listening to some relaxing music today?"

[0607] 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.

[0608] 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.

[0609] 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.

[0610] [Fourth Embodiment]

[0611] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0612] 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.

[0613] 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).

[0614] 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.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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".

[0624] An embodiment of the present invention is a system consisting of a terminal acting as an information processing device and an external server connected via a network. The user operates the terminal to input a question. At this time, an AI agent in the terminal analyzes the question and identifies personal information. The identified personal information is replaced with dummy words, and a newly generated message is sent to the external server via the network.

[0625] The server processes the message received from the terminal. Here, it analyzes the message, even with dummy words included, and generates a response. The generated response is then sent back to the terminal via the network. After receiving the response from the server, the terminal restores the dummy words to the original personal information. This allows the user to verify the information displayed on the terminal.

[0626] As a concrete example, consider a case where a user enters the question "What is my name?" into the device. In this question, the device recognizes the word "name" as personal information and replaces it with the dummy word "DUMMY_0" to generate the message "What is my DUMMY_0?". This message is sent to the server, which processes it and generates the response "Your DUMMY_0 is already registered". The device then restores "DUMMY_0" in the received message back to its original "name" and presents the user with the response "Your name is already registered".

[0627] In this way, users can receive information services from AI agents with peace of mind without exposing their personal information to third parties. This system plays an important role in protecting personal information and can be applied to various information processing devices and services.

[0628] The following describes the processing flow.

[0629] Step 1:

[0630] The user enters a question into the device. The question may include personal information, such as "What is my name?"

[0631] Step 2:

[0632] The device's AI agent receives the user's question. It analyzes each word in the question and identifies personal information based on a pre-configured list of personal information (e.g., name, address, phone number).

[0633] Step 3:

[0634] The device replaces identified personal information with dummy words. For example, "Name" is replaced with "DUMMY_0". This transforms the question into the format "What is my DUMMY_0?". The replaced personal information is stored in a mapping table that shows which dummy words represent which personal information.

[0635] Step 4:

[0636] The device sends a question, with dummy words replaced, to an external server. Since the sent message does not contain personal information, privacy is protected.

[0637] Step 5:

[0638] The server receives a message from the terminal. Because the message contains dummy words, no personal information is transmitted to the server.

[0639] Step 6:

[0640] The server processes the received message and generates the necessary response. This process is similar to normal natural language processing, creating a response sentence that takes the appropriate context into account based on dummy words.

[0641] Step 7:

[0642] The server sends the generated response to the terminal. Since the server's response also contains dummy words, there is no risk of personal information leakage.

[0643] Step 8:

[0644] The terminal receives a response from the server. It then uses a mapping table to reconstruct the original personal information by replacing dummy words in the received message. For example, in the response "Your DUMMY_0 is already registered," "DUMMY_0" is replaced with "Name."

[0645] Step 9:

[0646] The device presents the restored response to the user. Through this process, the user can confidently use the AI ​​agent's functions.

[0647] (Example 1)

[0648] 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".

[0649] Protecting personal information is a critical issue in today's information society. In particular, there is a risk of personal information being handled inappropriately when users interact with external systems via digital information processing devices. To address this problem, there is a need to provide new methods for users to obtain necessary information while safely and effectively protecting personal information.

[0650] 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.

[0651] In this invention, the server includes means for acquiring input information from a user, means for identifying personal information from the input information and replacing the corresponding personal information with a dummy representation, and means for transmitting the information replaced with the dummy representation to a data processing device. This makes it possible to provide the user with necessary information without communicating with an external system while retaining personal information.

[0652] A "user" refers to the entity that operates the system and inputs information.

[0653] "Input information" refers to the data that a user provides to an information processing device.

[0654] "Personal information" refers to information that can identify an individual, including name, address, and contact information.

[0655] "Dummy expressions" are meaningless pieces of information used to transform personal information and are used for privacy protection.

[0656] A "data processing device" refers to an external computer system that collects, processes, and generates responses for information.

[0657] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate information or provide responses.

[0658] "Restoration" refers to the process of returning converted information to its original state without losing any of the original information.

[0659] "Presentation" refers to displaying information to the user and making it available for use.

[0660] This invention is a system consisting of a terminal acting as an information processing device and a data processing device connected via a network. The user provides input information by operating the terminal. The terminal uses a built-in AI agent to analyze the input information and identify personal information. A natural language processing algorithm is used for this analysis. The identified personal information is replaced with a dummy expression to protect privacy. For example, if the input is "I want to change my password," then "password" is identified as personal information and replaced with "DUMMY_KEY."

[0661] When information containing dummy representations is generated, the terminal sends it to a data processing unit via the network. The data processing unit uses a generation AI model to analyze this dummy information and generate a response. The generated response is returned to the terminal while retaining the dummy representations. The terminal then restores the dummy representations in the received response to their original personal information. This process allows the user to receive the necessary information without exposing their privacy.

[0662] As a concrete example, consider a scenario where a user enters the prompt "Please verify my email address." In this message, the "email address" is identified and replaced with "DUMMY_EMAIL." The server generates a response stating "Your DUMMY_EMAIL is already registered," and the terminal restores and presents this message to the user as "Your email address is already registered." This is an effective way to resolve the issue without leaking personal information.

[0663] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0664] Step 1:

[0665] The user operates the device and enters a prompt in a specified format. This input can be a natural language question, such as "Please tell me my phone number." This input forms the basis for processing information in a privacy-protected manner.

[0666] Step 2:

[0667] The device uses a built-in AI agent to analyze the input information. Specifically, it uses natural language processing technology to identify important words and phrases in the text and identify personal information. For example, it identifies the phrase "telephone number" as personal information. The output of this analysis is the identified personal information.

[0668] Step 3:

[0669] The device replaces identified personal information with dummy representations. For example, "phone number" is replaced with "DUMMY_PHONE". This process involves data processing that generates a non-personal information format from the original input containing personal information. The output is a dummy message that reads, "Please tell me my DUMMY_PHONE".

[0670] Step 4:

[0671] The terminal sends a message, replaced with a dummy representation, to the server over the network. The transmitted message does not contain any personal information and is passed to the data processing device in a secure manner. The dummy message prepared as input is sent to the server.

[0672] Step 5:

[0673] The server analyzes the received message and generates a response. A generative AI model is used here, performing data calculations to generate an appropriate response based on the dummy content. The output is a response such as, "Your DUMMY_PHONE is registered in the system."

[0674] Step 6:

[0675] The server sends the generated response back to the terminal over the network. The terminal receives the response from the server and prepares it as input for processing.

[0676] Step 7:

[0677] The terminal restores the dummy representation of the received response message to the original personal information. Specifically, it performs string manipulation to change "DUMMY_PHONE" in the response back to the original "phone number". In this process, the restored original information is obtained as output.

[0678] Step 8:

[0679] The device presents the restored response to the user. The user can receive the information that "Your phone number is registered in the system." At this stage, the ultimate goal of providing information to the user is achieved.

[0680] (Application Example 1)

[0681] 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".

[0682] The protection of personal information has become increasingly important in recent years, and the risk of personal information leakage during data processing over networks has become a particular concern. Conventional systems sometimes do not adequately consider the security of personal information when transmitting it externally, increasing the possibility of information leakage and making it difficult for users to use services with peace of mind. This invention aims to solve these problems and enable users to use services with peace of mind by strengthening the protection of personal information.

[0683] 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.

[0684] In this invention, the server includes means for identifying and specifying personal information, means for converting the identified personal information into replacement words, and means for securely transmitting data using the replacement words to an external information processing system. This makes it possible to securely exchange data over a network while protecting personal information.

[0685] A "user" is a person or entity that operates an information processing device and provides input data.

[0686] "Input data" refers to data supplied by the user to the information processing device, and includes text and other formats that may contain personal information.

[0687] "Identifiable personal information" refers to information that can identify a user, such as name and address, and is data that can be associated with a user.

[0688] A "replacement word" is an artificial word that temporarily replaces the original personal information, enabling data protection and anonymization.

[0689] An "external information processing system" refers to a system that is connected to an information processing device via a network, independently of the information processing device, and includes servers that perform data processing and response generation.

[0690] An "identification information list" is a collection of information pre-configured to identify personal information, and it serves as a standard database.

[0691] A "restored response" is data that has been reconstructed by replacing the substitution words with the original personal information in the response received from an external information processing system.

[0692] This invention relates to an information processing system for the secure handling of user information, providing a technology that protects personal information through the collaborative operation of the user, terminal, and server. Specifically, the user operates the terminal and provides arbitrary input data. An AI agent within the terminal analyzes the input data, identifies identifiable personal information, and converts this information into replacement words. This process utilizes software such as a Python-based AI agent and a Natural Language Processing Toolkit (NLTK).

[0693] The data, converted to replacement words, is sent to the server over the network. On the server side, the data is processed using Django (a Python web framework) or Pandas to generate the necessary response. Here, security is ensured because the data does not contain any personal information and consists only of replacement words.

[0694] When the response from the server is returned to the terminal, the terminal receives it and restores the replaced words to the original personal information. This process uses the Python recovery module on the terminal. The user can then review the restored response and obtain the necessary information. For example, if the user asks, "What are my meeting times this week?", the terminal sends the message "What are my DUMMY_1 times this week?" to the server, receives the response "Your DUMMY_1 is scheduled for 3pm," and restores the information to its original state.

[0695] An example of a prompt message to be input to a generative AI model is as follows:

[0696] Prompt: Analyze the user's question ("User's Question") to identify personal information and convert it into secure replacement words. When you are ready to send it to the server, please provide a message indicating this status.

[0697] This system enables secure information exchange over the network while protecting personal information.

[0698] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0699] Step 1:

[0700] The user enters a question into the device. This input data may contain personal information in text format. The device verifies whether this input data is correctly formatted.

[0701] Step 2:

[0702] The device analyzes input data using a Python-based AI agent to identify identifiable personal information. This process utilizes the Natural Language Processing Toolkit (NLTK) to analyze the data structure. The identified personal information is then converted into replacement words.

[0703] Step 3:

[0704] The terminal prepares the data converted to replacement words and sends it to the server via the network. Before transmission, the data is encrypted to ensure security. The transmitted data consists only of replacement words and does not contain any personal information.

[0705] Step 4:

[0706] The server processes the received data using the Django framework. This process includes accessing the database, performing necessary calculations, and generating appropriate responses. Here too, a generative AI model is used to optimize response generation.

[0707] Step 5:

[0708] The response generated by the server is sent to the terminal via the network. During this process, the response data is appropriately packaged to minimize the number of bits and reduce response time.

[0709] Step 6:

[0710] The terminal restores the original personal information by replacing the words in the received response data. This restoration process uses a Python restoration module to perform the conversion quickly and accurately.

[0711] Step 7:

[0712] The recovered response is displayed on the terminal for the user to review. The user provides feedback on whether the displayed information is relevant to their needs, which helps improve the accuracy of future analyses.

[0713] 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.

[0714] This invention relates to a system comprising a terminal acting as an information processing device, an external server connected via a network, and an emotion engine. The user utilizes this system by operating the terminal and inputting questions or messages. The AI ​​agent within the terminal acquires the user's input message and simultaneously activates the emotion engine to analyze the user's emotions from the input message.

[0715] The emotion engine uses a predefined emotion recognition model to extract and classify emotional information from user messages. This emotional information helps understand the user's intentions and situation, and is used as reference information in response generation. Based on the emotions extracted by the emotion engine, the AI ​​agent can generate more human-like responses that are appropriate to the user's context.

[0716] This information processing device replaces the user's personal information with dummy words, protecting the user's privacy while transmitting data to an external server. The external server processes the transmitted message, and the generated response message also contains the dummy words. This prevents the leakage of personal information on the server side.

[0717] When the terminal receives a response from an external server, it analyzes the received message, refers to its internally stored mapping table, and restores the dummy words to their original personal information. It then generates a response that takes into account the information from the emotion engine and presents it to the user.

[0718] As a concrete example, suppose a user enters a question into the device such as, "I'm tired. What's on my schedule tomorrow?" At this point, the emotion engine recognizes the emotion "tired." The device replaces the personal information "schedule" with "DUMMY_0." The generated message is sent to an external server in the format "I'm tired. What's DUMMY_0 for tomorrow?". When the server processes the message and returns it to the device, it restores the "schedule" to its original information and displays an emotion-sensitive response to the user, such as, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0719] This system balances user emotional well-being with the protection of personal information, enabling the use of more intuitive and reliable AI agents.

[0720] The following describes the processing flow.

[0721] Step 1:

[0722] The user enters a question into the device, such as, "I'm tired. What's on the schedule for tomorrow?" Through this message, the user expresses their situation and questions.

[0723] Step 2:

[0724] When the device receives a message from the user, it first activates the emotion engine and analyzes emotional information from the message. From the expression "I'm tired," the emotion "fatigue" is recognized.

[0725] Step 3:

[0726] The AI ​​agent in the device analyzes the words in the user's question and identifies the word "schedule" as personal information according to a predefined list. The identified personal information is replaced with a dummy word, "DUMMY_0". The phrase "tomorrow's schedule" becomes "tomorrow's DUMMY_0".

[0727] Step 4:

[0728] The terminal constructs a message with dummy words replaced, "I'm tired. What's DUMMY_0 tomorrow?", and sends it to an external server.

[0729] Step 5:

[0730] The server receives a message from the terminal. It parses the message, including dummy words, and generates a response message such as "DUMMY_0 has a meeting tomorrow." At this stage, the server processes the message without knowing the original personal information.

[0731] Step 6:

[0732] The server sends back a response message it has generated to the terminal. The response is in the format "There is a meeting tomorrow for DUMMY_0".

[0733] Step 7:

[0734] The terminal receives a response from the server. It analyzes this response and, by referring to its internally stored mapping table, restores the dummy word "DUMMY_0" to "Scheduled".

[0735] Step 8:

[0736] Based on the emotional information, such as "fatigue," provided by the emotion engine, the AI ​​agent adjusts the tone of its response. Ultimately, it generates a response that takes the user's emotions into consideration, such as, "I understand you are tired. You have a meeting scheduled for 2 PM tomorrow."

[0737] Step 9:

[0738] The device then presents the final generated response to the user. This response allows the user to experience emotional satisfaction while simultaneously obtaining the necessary information appropriately.

[0739] (Example 2)

[0740] 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".

[0741] Conventional information processing systems have a problem of data breaches because user input is transmitted directly to external parties. Furthermore, responses often fail to consider the user's feelings, resulting in a poor user experience. This invention aims to generate appropriate responses that consider the user's feelings while protecting privacy.

[0742] 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.

[0743] In this invention, the server includes means for acquiring information from the user, means for replacing private data with alternative words, and means for classifying emotional information using an emotional analysis engine. This makes it possible to provide emotionally sensitive responses while protecting private data.

[0744] A "user" is the entity that inputs information into a system and receives the results.

[0745] "Information" refers to messages and data entered by the user.

[0746] "Private data" refers to data related to a user's personal information and privacy.

[0747] A "substitute word" is a temporary term used to replace private data.

[0748] "Other computers" refers to external processing units used to receive processed information and generate responses.

[0749] "Response information" refers to information generated by another computer and returned to the user.

[0750] An "emotion analysis engine" is a software tool for extracting and classifying emotional information based on user input.

[0751] "Emotional information" refers to categorized information that indicates a user's emotional state.

[0752] "To provide" refers to the act of presenting a response to the user.

[0753] This invention is a system that uses a terminal as an information processing device and interacts with other computers via a network. Users utilize the system by inputting questions and messages using the terminal. The terminal acquires the input information and simultaneously activates an emotion analysis engine to analyze the user's emotions from the input information. The emotion analysis engine analyzes the information using an emotion recognition model and classifies the emotional information.

[0754] The device also identifies the user's private data and replaces it with alternative language, securely transmitting the information to other computers while protecting privacy. Using alternative language prevents private data from being directly exposed externally. The other computers use a generative AI model based on the received information to generate the most appropriate response for the user. Because the response information includes alternative language, the original private data needs to be restored after the device receives it.

[0755] When the device receives a response containing alternative words, it refers to its internal mapping table and restores the original information. Then, taking into account the sentiment information obtained from the sentiment analysis engine, it provides an adjusted response that is appropriate to the user's emotions.

[0756] As a concrete example, if a user enters the question "I'm tired. What's on my schedule tomorrow?" into the device, the sentiment analysis engine recognizes the emotion of "fatigue." The device replaces the information "schedule" with "DUMMY_0" and sends it to another computer in the format "I'm tired. What's DUMMY_0 for tomorrow?". The response message generated by the other computer includes information about "DUMMY_0," which the device then uses to reconstruct "schedule," presenting the user with the response, "I understand you're tired. You have a meeting at 2pm tomorrow."

[0757] An example of a prompt for a generative AI model might be: "Analyze the user's emotions from the following sentence and generate an appropriate response based on those emotions: 'I'm tired. What are my plans for tomorrow?'"

[0758] In this way, we provide a system that can provide accurate responses that are sensitive to user emotions while protecting user privacy.

[0759] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0760] Step 1:

[0761] The user enters a text message into the device. The user can ask questions or make requests in natural language, and this becomes the input information. A specific example of this action would be the user using the device's input interface to type, "I'm tired. What's on the schedule for tomorrow?"

[0762] Step 2:

[0763] The terminal receives user input and activates the sentiment analysis engine. At this stage, the input is text sent by the user, which the terminal passes to the sentiment analysis engine. As part of the data processing, sentiment information is extracted from the text and the emotion "fatigue" is recognized. The output of this process is the extracted sentiment information. Specifically, this involves the sentiment analysis engine analyzing the text and adding the emotion label "fatigue."

[0764] Step 3:

[0765] The terminal identifies private data from the user's input text and replaces it with a substitute word. Let's assume the input is the original user text containing the private data "schedule". The data calculation involves replacing "schedule" with "DUMMY_0" to protect user privacy. The output of this process is text with the private data replaced. Specifically, the terminal recognizes certain words and converts them to predefined substitute words.

[0766] Step 4:

[0767] The terminal sends a text message containing a substitute word to the server. The input is the substitute text, and the output is this text being transferred to the server over the network. Specifically, this process involves sending the message to another computer using a network protocol.

[0768] Step 5:

[0769] The server processes the received message and generates an appropriate response using a generative AI model. The input is an alternative text message, which the generative AI model parses. The data calculation involves semantic analysis to generate a response such as "DUMMY_0 has a meeting at 2pm tomorrow." The output of this process is the response text. Specifically, the generative AI model performs natural language processing to determine the required response content.

[0770] Step 6:

[0771] The terminal receives a response from the server and, by referring to its internal mapping table, restores the substitute word to the original private data. The input is the response message in its substituted state. The data processing involves restoring the substitute word "DUMMY_0" to "scheduled," and the output is the response text with its original meaning. Specifically, the operation to restore the original word is performed using the substitute word management database.

[0772] Step 7:

[0773] The device uses information from the emotion analysis engine to provide the user with a final, adjusted response. The input is a reconstructed response message that takes into account the emotional information of "fatigue." The final output is a response that is sensitive to the user's emotions. Specific actions include the process of presenting the response message to the user visually or audibly.

[0774] (Application Example 2)

[0775] 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".

[0776] It is necessary to provide emotionally sensitive communication to elderly users and those who have difficulty expressing their emotions, while protecting personal information and enabling data communication with external systems. Currently, many systems do not accurately understand users' emotions and may respond coldly, and their protection of personal information is insufficient. This leads to problems such as systems being difficult for users to operate and a loss of trust.

[0777] 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.

[0778] In this invention, the server includes means for analyzing and classifying emotional information from the user's input message, means for identifying personal information and replacing it with dummy words, and means for sending a message containing emotional information and dummy words to an external server and generating a response. This enables secure data communication with the system while protecting personal information and generating an emotionally sensitive response.

[0779] An "input message" refers to text or audio that a user provides to the system for the purpose of providing information.

[0780] "Emotional information" refers to data that indicates the user's psychological state, analyzed from input messages, and is a classification and representation of their psychological situation.

[0781] "Personal information" refers to information related to a specific user and data that requires privacy protection.

[0782] A "dummy word" is a substitute symbol or string of characters used to conceal personal information and prevent the leakage of personal information outside of the system.

[0783] An "external server" is a device that exists on the network independently of terminals within the system and provides computing resources for message processing and response generation.

[0784] "Means of restoration" refers to the processes and technologies used to convert dummy words in messages received from external servers back into the original personal information.

[0785] "Care support" refers to services and systems aimed at providing support for daily life and psychological care to elderly people and users who have difficulty expressing their emotions.

[0786] "Considering the user's psychological state" means understanding the user's emotional information and providing appropriate responses and suggestions based on that understanding.

[0787] To realize this invention, the system consists of a user terminal, an external server, and an emotion analysis engine. The user terminal obtains messages from the user through voice input or text input, and uses these as the starting point for processing.

[0788] First, the message spoken or typed by the user is converted into text data by the speech analysis software on the user's terminal. At this time, the emotion analysis engine (EmotionML compatible) analyzes the message and classifies the user's emotional information. The analysis results are used as data indicating the user's psychological state. Next, the terminal identifies personal information from the input message and replaces it with dummy words. This protects privacy and ensures security. The replaced message is sent to an external server via network communication. Efficient data transmission is achieved by using Socket.IO as the communication middleware.

[0789] An external server utilizes a generative AI model to generate responses based on the transmitted message. In this process, the server references emotional information to create natural responses that take the user's psychological state into consideration. Dummy words in the response messages are stored in a secure format that protects the original user data, reducing the risk of personal information being leaked. When the response is returned to the terminal, the terminal uses a predefined mapping table to restore the dummy words to the original personal information. As a result, the user is presented with a response that is appropriately considerate of their original statement.

[0790] For example, if an elderly person says, "I'm a little tired today," the emotion analysis engine will extract the emotion "fatigue." Based on this, the system can make suggestions such as, "Why don't you try to set aside some time to rest today?" As an example of a prompt sentence to input into the generating AI model, the following text is provided: "User statement: 'I'm a little lonely.' Agent response: 'When you feel lonely, it's a good idea to talk to a friend or plan an outing.'" Based on this prompt sentence, the AI ​​generates an appropriate response.

[0791] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0792] Step 1:

[0793] The user inputs a message via voice or text. This input is the user's raw communication data. The terminal receives this input and, in the case of voice input, converts it to text using speech analysis software. In this process, the input message is transformed from voice data to text data.

[0794] Step 2:

[0795] The terminal activates the emotion analysis engine and analyzes the acquired text data. The input here is the text data obtained in step 1. The emotion analysis engine analyzes the content of the text and extracts emotional information. For example, it identifies and classifies the emotion "fatigue" from the word "tired." In this step, the text data is processed into data that represents emotional information.

[0796] Step 3:

[0797] The device identifies personal information from the input message and replaces the relevant information with dummy words. The original text data is used as input. This data processing transforms personal information into dummy data, thus protecting privacy.

[0798] Step 4:

[0799] The terminal sends text, replaced with sentiment information and dummy words, to an external server. Socket.IO is used for communication. The server analyzes the received data and generates an appropriate response using a generative AI model. Based on the information in this prompt, the AI ​​considers a sentiment-based reply. The server's output is the response message.

[0800] Step 5:

[0801] The terminal reconstructs the dummy words in the response message received from the server into the original personal information. The input is the response message from the server. At this stage, the dummy data is converted back into the original text data, resulting in a process that presents consistent information to the user.

[0802] Step 6:

[0803] The device presents the user with a restored response message and offers thoughtful suggestions based on emotional information. This output is the final information provided to the user. For example, it might be presented as, "I understand you're tired. How about listening to some relaxing music today?"

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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."

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] The following is further disclosed regarding the embodiments described above.

[0826] (Claim 1)

[0827] In an information processing device, means for obtaining input messages from a user,

[0828] A means for identifying personal information from the aforementioned input message and replacing the relevant personal information with dummy words,

[0829] A means for sending the message, which has been replaced with the aforementioned dummy word, to an external server,

[0830] A means for restoring dummy words in a response message received from the external server to their original form based on the personal information,

[0831] Means for presenting the restored response to the user,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, characterized in that the means for identifying the personal information is performed based on a predefined list of personal information.

[0835] (Claim 3)

[0836] The system according to claim 1, characterized in that the message sent to the external server does not retain personal information and consists only of dummy words.

[0837] "Example 1"

[0838] (Claim 1)

[0839] Means for obtaining user input information,

[0840] A means for identifying personal information from the aforementioned input information and replacing the relevant personal information with a dummy expression,

[0841] Means for transmitting the information replaced with the aforementioned dummy representation to a data processing device,

[0842] A means for restoring a dummy representation in the response information received from the data processing device to the original information based on the personal information,

[0843] Means for presenting the restored response to the user,

[0844] The data processing device includes means including a generated AI model when generating a response,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, characterized in that the means for identifying the personal information is performed based on a pre-configured list of personal information.

[0848] (Claim 3)

[0849] The system according to claim 1, characterized in that the information transmitted to the data processing device does not include personal information and consists only of dummy representations.

[0850] "Application Example 1"

[0851] (Claim 1)

[0852] Means for obtaining input data from users,

[0853] A means for identifying identifiable personal information from the aforementioned input data and converting the corresponding personal information into replacement words,

[0854] A means for transmitting data using the aforementioned replacement word to an external information processing system,

[0855] A means for restoring the replaced word in the response data received from the external information processing system to the original data based on identification information,

[0856] Means for displaying the restored response to the user,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, characterized in that the means for identifying the personal information is performed based on a pre-set list of identification information.

[0860] (Claim 3)

[0861] The system according to claim 1, characterized in that the data transmitted to the external information processing system does not retain identification information and consists only of replacement words.

[0862] "Example 2 of combining an emotion engine"

[0863] (Claim 1)

[0864] Means of obtaining information from users,

[0865] A means for identifying private data from the aforementioned information and replacing the corresponding private data with alternative words,

[0866] Means for transmitting the information replaced with the aforementioned substitute word to another computer,

[0867] Means for restoring the substitute word in the response information received from the aforementioned other computer to the original information based on the aforementioned private data,

[0868] Means for providing a restored response,

[0869] A means of classifying emotional information using an emotion analysis engine based on the content of user statements,

[0870] A means for adjusting the response based on the aforementioned emotional information,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, characterized in that the means for identifying the private data is performed based on a predefined list of private data.

[0874] (Claim 3)

[0875] The system according to claim 1, characterized in that the information transmitted to the other computer does not retain private data and consists only of substitute words.

[0876] "Application example 2 when combining with an emotional engine"

[0877] (Claim 1)

[0878] A means of obtaining user input messages,

[0879] A means for analyzing emotional information from the input message and classifying the corresponding emotional information,

[0880] A means for identifying personal information from the aforementioned input message and replacing the relevant personal information with dummy words,

[0881] A means for sending the message, which has been replaced with the aforementioned emotional information and dummy words, to an external server and generating a corresponding response,

[0882] A means for restoring dummy words in a response message received from the external server to their original form based on the personal information,

[0883] A means for presenting the restored response to the user and generating a response based on emotional information,

[0884] In care support, the means of providing appropriate responses and action suggestions while considering the psychological state of the user,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, characterized in that the means for identifying the personal information is performed based on a predefined list of personal information.

[0888] (Claim 3)

[0889] The system according to claim 1, characterized in that the message sent to the external server does not retain personal information and consists only of dummy words. [Explanation of symbols]

[0890] 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. In an information processing device, means for obtaining input messages from a user, A means for identifying personal information from the aforementioned input message and replacing the relevant personal information with dummy words, A means for sending the message, which has been replaced with the aforementioned dummy word, to an external server, A means for restoring dummy words in a response message received from the external server to their original form based on the personal information, Means for presenting the restored response to the user, A system that includes this.

2. The system according to claim 1, characterized in that the means for identifying the personal information is performed based on a predefined list of personal information.

3. The system according to claim 1, characterized in that the message sent to the external server does not retain personal information and consists only of dummy words.

Images