system

Abstract

Provide a system. 【Solution means】 Means for obtaining user's personality information based on personality theory using personality analysis means; Means for generating advice aimed at improving relationships based on the user's consultation content; Means for presenting the generated advice to the user's device; Means for receiving an evaluation from the user and reflecting it in the analysis result; Means for improving the advice generation accuracy using the analysis result; Means for analyzing the user's consultation content using voice recognition; Means for presenting advice visually and aurally; A system including the above.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Insufficient communication or deterioration of the relationship between husband and wife often involves a psychological barrier that makes it difficult to consult others due to shame, and the problem is often left unresolved. For this reason, many couples are struggling without means to improve the deteriorated relationship. Furthermore, due to recent social changes and stress factors, problems in the marital relationship have been increasing, and there is a need for a method to easily and secretly analyze problems in the marital relationship and provide improvement measures.

Means for Solving the Problems

[0005] This invention provides a system that acquires user personality information based on personality theory using personality analysis means, and generates relationship improvement advice corresponding to the user's consultation content based on this information. The generated advice is presented to the user's terminal, and the system can receive and analyze feedback from the user to improve the accuracy of advice generation. Specifically, by using personality patterns based on multiple psychological theories, more appropriate and effective advice is provided. As a result, couples can easily obtain means to solve their problems.

[0006] A "personality analysis tool" is a method or device for acquiring and analyzing a user's personality information based on psychological theories.

[0007] "Personality theory" refers to a framework or model for classifying and understanding human personality, with MBTI and the Big Five theory being representative examples.

[0008] A "user" refers to an individual who uses this system to seek advice or suggestions for improving their marital relationship.

[0009] "Consultation details" refer to text information about marital relationship problems and inquiries that users enter into the system.

[0010] "Relationship improvement advice" refers to specific suggestions for improving communication and the relationship between spouses, generated based on the user's consultation content and personality information.

[0011] "Terminal" refers to electronic devices such as computers and smartphones that users use when accessing this system.

[0012] "Feedback" is data that contributes to improving the accuracy of a system by returning information to the system about the effectiveness and results of the advice received by the user.

[0013] "Learning" refers to the process by which a system updates its advice generation algorithm based on feedback received from users, enabling it to provide more accurate suggestions. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

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

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

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered 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 numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[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] The system according to the present invention is a system that uses personality analysis means to acquire the user's personality information and generates relationship improvement advice according to the content of the consultation, in order to solve the user's problems in their marital relationship.

[0036] Specifically, this system will be implemented in the following manner: First, the user uses a terminal to input their concerns and questions regarding their marital relationship. The user can also update previously entered personality data as needed. This information is securely encrypted and transmitted to the server.

[0037] The server analyzes the received consultation content and the user's personality information. Using personality analysis tools, it identifies the user's personality pattern based on personality theories such as MBTI and the Big Five personality theory. Based on this information, the server utilizes AI technology to generate advice that can lead to improved communication and relationships between spouses.

[0038] The generated advice is re-encrypted and sent to the user's device. The device decrypts the advice and presents it visually to the user. The user can then incorporate and implement this advice in their daily life.

[0039] For example, specific suggestions might be made, such as, "To improve communication between spouses, set aside time once a week to enjoy a shared hobby." Users can then input feedback on the effectiveness of this advice on their device.

[0040] The server receives feedback information and uses it for analysis, allowing the AI ​​model to learn and improve the accuracy of its next advice. This iterative evolution of the system enables it to provide more personalized support to each user. Through this cycle, users can improve their marital relationships.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users input their concerns and questions about their marital relationship as text using their device. At the same time, users can also pre-register basic personality information about themselves and their partner.

[0044] Step 2:

[0045] The terminal encrypts the user's input and sends the data to the server in a secure state.

[0046] Step 3:

[0047] The server decodes the received data and obtains the user's personality information and consultation details. It then applies personality analysis tools and analyzes the user's personality pattern based on MBTI and Big Five personality theories.

[0048] Step 4:

[0049] Based on the results of the personality analysis and the content of the consultation, the server uses an AI algorithm to generate advice for improving the relationship. This process includes referencing predictive models and past success stories.

[0050] Step 5:

[0051] The server re-encrypts the generated advice and sends it to the user's terminal.

[0052] Step 6:

[0053] The device receives and decodes the advice, then displays it in a format that the user can visually understand. The user can then review and act upon this advice.

[0054] Step 7:

[0055] After implementing the advice, users can input feedback on its effectiveness into their device. This feedback may include specific results and emotional reactions.

[0056] Step 8:

[0057] The device encrypts user feedback and sends it to the server.

[0058] Step 9:

[0059] The server analyzes the feedback and updates the AI ​​model. This improves the overall accuracy of the system so that the next advice is more effective and personalized.

[0060] This series of steps allows users to discreetly analyze marital relationship problems and receive support in implementing solutions.

[0061] (Example 1)

[0062] 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."

[0063] In modern society, marital problems and lack of communication have become significant social issues. However, improving these relationships requires measures tailored to individual personalities and characteristics, making it difficult to provide efficient and accurate advice. Traditional methods tend to offer only general advice and fail to provide solutions that are appropriate for individual personalities and situations.

[0064] 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.

[0065] In this invention, the server includes means for encrypting and securely transmitting personality data, means for analyzing the user's personality information based on personality theory on the server, and means for creating suggestions for improving relationships based on the user's consultation content using a generative AI model. This makes it possible to provide specific and individualized advice tailored to each user's personality.

[0066] "Encrypting and securely transmitting personality data" means encrypting the personality information entered by the user to protect it from unauthorized access by others, and then securely transmitting that information to the server via a communication line.

[0067] "Analyzing user personality information based on personality theory on the server" refers to the process of analyzing received personality data based on psychological frameworks such as MBTI and Big Five personality theory to identify the user's personality pattern.

[0068] "Using a generative AI model to create suggestions for improving relationships based on the user's consultation content" means utilizing information provided by the user and using generative AI technology to automatically generate specific advice and suggestions that are suitable for the user.

[0069] "Encrypting the generated suggestions and sending them to the user's display device for visual display" means encrypting the generated advice, sending it to the user's terminal via a communication channel, decrypting it, and then presenting it to the user visually.

[0070] "Receiving user feedback and applying it to the analysis results on the server" means collecting feedback from users and incorporating it into the evaluation process within the system to improve the accuracy of future suggestions.

[0071] "Using these analysis results to improve the accuracy of suggestion generation" refers to the process of analyzing received feedback and improving the performance of the generating AI model to provide more accurate and personalized suggestions to users.

[0072] In a mode for carrying out the invention, this system is designed as a means to resolve problems in a user's marital relationship. The system aims to provide personalized advice by integrating personality analysis technology and a generative AI model.

[0073] Users first input their concerns and questions about their marital relationship using their own devices. The devices are equipped with software to securely encrypt the information, ensuring that the collected data is transmitted securely to the server. The devices are standard computers or smartphones and require an internet connection.

[0074] The server is equipped with specialized software for performing analysis based on personality theory. The server analyzes the user's personality information using theories such as MBTI and the Big Five personality traits, extracting key characteristics. This personality information forms the basis for creating optimal advice for the user using a generative AI model. The generative AI model generates specific suggestions by considering the user's consultation content, while also referencing past data and success stories.

[0075] The generated advice is encrypted again and sent to the user's device. The device decrypts the received advice and presents it to the user in a visually verifiable format. This may include text and simple diagrams. The user can then put this advice into practice in their daily life and input the results as feedback into the system.

[0076] Based on the feedback, the server updates the AI ​​model and learns to improve the accuracy of future advice. This process allows the system to continuously evolve and meet the individual needs of each user.

[0077] As a concrete example, here is an example of a prompt: "We are a couple in our 30s and feel that we lack communication. We don't have many shared hobbies, and we would like advice on how to improve our relationship." Based on this prompt, the system generates suggestions that take into account the user's personality and situation.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] Users use their devices to input concerns and questions about their marital relationship. The input includes specific concerns (e.g., "Recently, I've been talking less with my partner") and personality data that is updated as needed. The device encrypts this data to ensure security before sending it to the server. The output is encrypted data, which is then transferred to the server.

[0081] Step 2:

[0082] The server decrypts the encrypted data received from the terminal. The input consists of encrypted consultation content and personality data. After decryption, the server proceeds to an analysis process based on personality theory. Using personality analysis technology, the server identifies the user's personality pattern based on MBTI and Big Five personality theories. The output obtained from this analysis is metadata that indicates the user's characteristics.

[0083] Step 3:

[0084] The server generates advice using a generative AI model based on the analyzed personality metadata and received consultation content. The input is the personality metadata and consultation content obtained in the server's previous step. The generative AI model uses this data to generate specific and practical advice, referencing similar cases from the database. The output is the advice text before encryption.

[0085] Step 4:

[0086] The server encrypts the generated advice and sends it to the user's terminal. The input is the generated advice itself, which is encrypted and securely sent to the terminal. The output of this step is the encrypted advice received by the user's terminal.

[0087] Step 5:

[0088] The terminal receives encrypted advice sent from the server. The input is encrypted advice text, which is then decrypted and presented visually to the user. For example, it may be displayed using text or simple diagrams to make it easier for the user to understand. The output is the decrypted advice presented to the user.

[0089] Step 6:

[0090] Users try out the provided advice in their daily lives, evaluate its effectiveness, and input feedback into their device. This feedback includes their response to the advice and the progress made in improving relationships, which is then used to improve future processes. The output is sent to the server as feedback data.

[0091] Step 7:

[0092] The server receives feedback from users and uses it as training data to improve the performance of the AI ​​model. The input is feedback data, which is analyzed and used for learning to improve the accuracy of future advice generation. The output is the improved accuracy of the improved AI model in subsequent attempts.

[0093] (Application Example 1)

[0094] 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."

[0095] In modern households, a lack of communication and deteriorating relationships between spouses are commonplace problems. To address these issues effectively, personalized advice tailored to each individual's personality and the nature of their concerns is required. However, traditional methods often only provide uniform advice. Furthermore, there are few systems that can evolve advice based on feedback, highlighting the need for technologies that can provide more individualized support.

[0096] 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.

[0097] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for analyzing the user's consultation content using speech recognition, and means for presenting advice visually and aurally. This makes it possible to provide advice tailored to the user's individual concerns through visual or auditory means, and to improve the quality of the advice by utilizing feedback from the user.

[0098] "Personality analysis means" refers to a device or method for acquiring a user's personality information based on personality theory.

[0099] "User's equipment" refers to terminals or devices used by the user to acquire or input information.

[0100] "Evaluation" refers to the feedback that users provide in response to advice, and this feedback concerns the effectiveness of the advice and areas for improvement.

[0101] "Speech recognition" is a technology that analyzes voice input from users as digital data.

[0102] "Providing advice through visual and auditory means" refers to the process of providing generated advice to the user via screen display or audio output.

[0103] "Means for receiving feedback" refers to a method or device for a server or system to receive user evaluations as data.

[0104] "Multiple psychological theories" refers to a group of theories that use different psychological frameworks and models to analyze patterns of personality and behavior.

[0105] The system for implementing this invention mainly consists of a server and user equipment. The server analyzes the user's personality information and consultation content using personality analysis means, speech recognition technology, and a generative AI model. Psychological theories such as MBTI and Big Five theory are applied to the personality analysis to accurately capture the user's personality pattern. In addition, the user's consultation content is converted into data by speech recognition and analyzed in detail.

[0106] Once data analysis on the server is complete, the generating AI model forms advice aimed at improving relationships. This advice is encrypted and then sent to the user's device. On the user's device, the advice can be presented visually or audibly through a touchscreen display or speaker. The user can accept the presented advice and put it into practice in their daily life.

[0107] User feedback is sent to the server as assessment of the effectiveness of the advice and areas for improvement. This feedback is incorporated into the AI ​​model's training and used to improve the accuracy of future advice generation. This cycle allows the system to regularly provide personalized support to individual users.

[0108] For example, if a user consults the system about the lack of communication between spouses recently, the system might suggest, "Why not plan a lunch date once a week?" The system then works by having the user implement this suggestion and provide feedback on the results, which helps improve the quality of future advice.

[0109] An example of a prompt message would be, "The user's personality type is INTJ, and they feel there is a lack of communication in their marriage. Please suggest specific actions to improve the situation." In this way, accurate and practical advice can be provided based on the user's individual needs.

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

[0111] Step 1:

[0112] The user uses a device to input their concerns and questions about their marital relationship via voice. The voice input is captured by the device via a microphone and converted into digital data. This data is then converted into text data by speech recognition software.

[0113] Step 2:

[0114] The terminal uses speech recognition software to acquire text data, which is then sent to the server. The server uses a generative AI model based on the received text data to generate a prompt message. This prompt message combines the user's specific personality information with the content of their inquiry.

[0115] Step 3:

[0116] The server uses personality analysis tools to analyze the personality information of pre-registered users. This data is analyzed based on MBTI and Big Five personality theories. Based on the analysis, the user's specific personality type is identified. The server then uses this to complete the prompt message.

[0117] Step 4:

[0118] The server uses a generative AI model to generate advice based on prompt messages. This model utilizes a large amount of training data to output advice that helps improve relationships. The generated advice is customized to the user's specific needs.

[0119] Step 5:

[0120] The server encrypts the generated advice and sends it to the terminal. The terminal decrypts the received data and presents it to the user visually and audibly. Specifically, it is displayed as text on the touchscreen display and played back as audio through the speaker.

[0121] Step 6:

[0122] Users try out the advice presented in their daily lives and input the results as feedback on their device. This feedback is sent to the server as evaluation data. The server uses this feedback information to readjust the generated AI model and improve the quality of the advice given next time.

[0123] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0124] The system according to the present invention aims to improve marital relationships by acquiring user personality information, analyzing consultation content, generating relationship improvement advice, and receiving feedback and learning from it. This system further incorporates an emotion engine that recognizes the user's emotions, thereby improving the accuracy of the advice.

[0125] As a specific implementation, the user first uses a terminal to input details about their current marital relationship. This information, along with personality information, is sent to the server. The server uses personality analysis tools to analyze the user's personality based on multiple psychological theories, such as MBTI and the Big Five personality theory. Simultaneously, an emotion engine recognizes the user's emotional state from the consultation content and incorporates this into the advice generation.

[0126] The server uses an AI algorithm that takes into account personality information and emotional state to generate relationship improvement advice best suited to the user's situation. For example, it can provide advice such as, "Currently, a stressful emotional state has been detected, so we suggest a relaxing collaborative activity." This advice is presented on the user's device in a visually understandable format.

[0127] Users take action based on the advice provided and provide feedback on the results and their feelings at the time. This feedback is also sent to the server through the emotion engine, and the server learns from it. Through this process, the system improves the accuracy of its advice and can provide more effective advice in future consultations.

[0128] This series of processes allows users to gain a deep understanding of marital relationship problems and obtain realistic and actionable solutions without requiring specialized knowledge. In other words, this system provides users with an easy and effective means of resolving their issues, and this is an embodiment of the present invention.

[0129] The following describes the processing flow.

[0130] Step 1:

[0131] Users use their devices to input their concerns and questions regarding their marital relationship. They are encouraged to honestly describe their current emotional state during the input process. If a user's personality information is not yet registered, they will be given the option to input it by answering questions.

[0132] Step 2:

[0133] The terminal encrypts the user's entered consultation content and personality information and securely transmits it to the server. Appropriate management measures are taken beforehand to protect privacy.

[0134] Step 3:

[0135] The server decodes the received data and uses personality analysis tools to analyze the user's personality information based on multiple psychological theories. This analysis identifies the user's personality pattern.

[0136] Step 4:

[0137] The server activates an emotion engine to analyze the user's current emotional state based on their consultation content. This analysis utilizes natural language processing techniques and references to an emotion dictionary.

[0138] Step 5:

[0139] The server uses an AI algorithm to generate relationship improvement advice based on the analyzed personality patterns and emotional states. The advice is guaranteed to be particularly considerate of the user's emotional state.

[0140] Step 6:

[0141] The server re-encrypts the generated advice and sends it to the user's device, ensuring privacy while providing advice.

[0142] Step 7:

[0143] The terminal decodes the advice received from the server and displays it in a visual interface that is easy for the user to understand. The user then considers whether or not to act on the advice.

[0144] Step 8:

[0145] Users implement the provided advice and record feedback on their device regarding the results and their feelings during the implementation process.

[0146] Step 9:

[0147] The device encrypts user feedback and associated sentiment data and sends it to the server. This feedback serves as important learning data for generating advice in the future.

[0148] Step 10:

[0149] The server analyzes the received feedback and adjusts the AI ​​algorithm and emotion engine to improve the accuracy of future advice generation. This iterative learning improves the overall system performance.

[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] In modern society, relationships between spouses and partners are important, but obtaining effective advice on improving them is often difficult. In particular, there is a lack of personalized advice tailored to individual personalities and emotional states, which can lead to further deterioration of relationships. This invention aims to solve these problems and provide a means to effectively promote relationship improvement.

[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 user personality data based on psychological theories using personality evaluation means, means for generating guidelines aimed at improving relationships based on the content of the user's consultation, and means for detecting the user's emotional state using an emotion recognition device and reflecting this in the generation of guidelines. This makes it possible to provide users with personalized relationship improvement advice.

[0155] A "personality assessment tool" is a function that analyzes and acquires user personality data based on psychological theories.

[0156] A "psychological theory" is a theoretical framework used to understand an individual's personality and behavioral patterns, and generally consists of multiple theories.

[0157] "User" refers to an individual who uses this system and is the entity that provides their personality data and consultation content.

[0158] "Personality data" refers to data that quantifies or classifies a user's personality, and is generated based on psychological theories.

[0159] "Consultation content" refers to specific problems or questions related to relationships that users enter into this system.

[0160] "Guideline generation" is the process of creating specific advice or suggestions to provide to users with the aim of improving relationships.

[0161] An "emotion recognition device" is a function that identifies the emotional state of a user based on the content of their consultation and reflects it in the system's processes.

[0162] "Opinions" refer to feedback provided by users in response to advice, and this information is used to help the system learn and improve.

[0163] This system aims to improve relationships between spouses and partners by providing users with personalized advice. The system consists of a personality assessment tool, an emotion recognition device, and a guideline generation device. This allows users to easily receive practical advice for improving their relationships.

[0164] Users first input their personality data and consultation details using a device such as a smartphone, tablet, or computer. This information is securely transmitted to a server. The server runs a program based on psychological theories and analyzes the personality data through personality assessment methods. In this process, MBTI and Big Five personality theories are used.

[0165] Subsequently, the server analyzes the consultation content using an emotion recognition device and identifies the user's emotional state. This information is a crucial element in the guideline generation process by the generative AI model. The server considers personality data and emotional state together to generate the most appropriate guideline for the user's situation.

[0166] The generated guidelines are sent to the user's device in a visually easy-to-understand format. For example, if a stressful emotional state is detected, the server can offer specific advice such as, "We suggest spending some time together to relax."

[0167] Users take action based on the advice and input feedback about the results and their feelings via their device. The server receives this feedback and uses it to improve the overall accuracy of the system. Through this iterative learning process, even more accurate advice will be provided during subsequent consultations.

[0168] As a concrete example, a prompt might look like this: "Generate advice for improving the marital relationship. The user's personality type is 'ENFJ' according to the MBTI, and their current emotional state is 'anxious'. Please provide specific and appropriate advice." This prompt serves as a guide for the generating AI model to output advice tailored to the individual situation.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] Users use their devices to input their personality data and specific questions about their marital relationship. For example, "Recently, I've been talking less with my partner." This information includes personality patterns, so detailed personality data is entered.

[0172] Step 2:

[0173] The terminal sends the entered information and personality data to the server. The data is encrypted and securely transferred to the server. The input here consists of personality data and consultation details, while the output is encrypted data.

[0174] Step 3:

[0175] The server analyzes the received data and uses personality assessment tools to analyze the personality data. For example, it identifies MBTI types based on psychological theories. The input is encrypted data, and the output is a classified personality pattern.

[0176] Step 4:

[0177] The server uses an emotion recognition device to identify the user's emotional state from the consultation content. For example, it uses natural language processing to identify emotions such as "anxiety" and "stress." The input is text information of the consultation content, and the output is the identified emotional state.

[0178] Step 5:

[0179] The server uses the system's AI model to generate appropriate relationship improvement guidelines based on personality patterns and emotional states. The input here is personality patterns and emotional states, and the output is the guidelines generated through the AI ​​model. For example, one might suggest "a relaxing collaborative activity."

[0180] Step 6:

[0181] The terminal presents the generated guidelines to the user in a visually easy-to-understand format. For example, it may display them as a list or text message. The input from the server is the guidelines data, and the output is the display to the user.

[0182] Step 7:

[0183] Users take action based on the provided guidelines and input feedback on the results and their feelings into the device. This input serves as a record of their opinions and the effects of the guidelines.

[0184] Step 8:

[0185] The device sends user feedback to the server. The transmitted data includes practical results and changes in emotions. The output is feedback data sent to the server.

[0186] Step 9:

[0187] The server analyzes the feedback data and learns to improve the overall accuracy of the system. This improves the accuracy of advice generation in subsequent sessions. The input is the feedback data, and the output is the improved AI model.

[0188] (Application Example 2)

[0189] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0190] In caregiving settings, poor communication between caregivers and those receiving care, and an inability to properly understand the emotional state of those receiving care, can lead to a deterioration of relationships and inappropriate care. Therefore, it is crucial for caregivers to understand the emotional state of those receiving care and to find the most appropriate communication methods based on that state.

[0191] 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.

[0192] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for recognizing emotional states from image and audio data using emotion analysis means, and means for reflecting the recognized emotional states in advice generation. This makes it possible for caregivers to understand the emotional state of those being cared for in real time and to provide optimal communication methods and relationship improvement measures based on that understanding.

[0193] A "personality analysis method" is a technique for obtaining a user's personality information based on personality theory.

[0194] "Advice generation" is the process of creating advice aimed at improving relationships, based on the user's consultation content and emotional state.

[0195] A "device" is a device used to present generated advice to the user.

[0196] "Feedback" refers to information about the results of user actions and their emotions at the time, and is used to improve the accuracy of the system.

[0197] "Emotional analysis methods" refer to technologies that analyze image and audio data to recognize the emotional state of a user.

[0198] This invention is a system implemented to improve the relationship between caregivers and those receiving care in the field of elderly care. The system utilizes devices such as smartphones and tablets. A server processes data transmitted from users through these devices and performs necessary analysis.

[0199] The server uses TENSORFLOW®, an AI library for the Python programming language, to generate personality analysis and advice. Personality information is obtained using personality analysis methods and based on psychological theories. Furthermore, it uses emotion analysis engines such as Microsoft® Azure® Face API and Google® Cloud Vision to recognize the emotional state of the person being cared for from image and audio data.

[0200] The generated advice is visually displayed on the terminal, allowing caregivers to use it to improve communication with those they care for. The system receives feedback provided by caregivers and processes it on the server. Based on this feedback, the system iteratively improves the accuracy of its advice generation.

[0201] For example, if the server detects, based on its sentiment analysis, that the person being cared for has been feeling down recently, it will generate a prompt message such as, "Sentiment analysis indicates that the person being cared for has been feeling down recently. What activities would improve their mood?" This allows the caregiver to suggest appropriate activities.

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

[0203] Step 1:

[0204] The user uses a terminal to input personality information and consultation details about the person being cared for. The entered data is sent from the terminal to the server. The server receives this data and prepares to begin the personality analysis.

[0205] Step 2:

[0206] The server uses personality analysis tools to identify personality patterns based on the received personality information and multiple psychological theories. At this stage, the results of the personality pattern analysis are output.

[0207] Step 3:

[0208] The server uses emotion analysis tools, taking image and audio data from the device as input. It recognizes the emotional state using Microsoft Azure Face API or Google Cloud Vision. The recognized emotional state is output and used to generate advice for the next step.

[0209] Step 4:

[0210] The server utilizes a generative AI model to generate optimal advice based on personality analysis results and emotional states. In this process, the AI ​​suggests activities and communication methods that are considered effective for improving relationships.

[0211] Step 5:

[0212] The generated advice is output to the terminal and presented to the user. The terminal displays this advice in a visually easy-to-understand format, enabling the user to take action based on it.

[0213] Step 6:

[0214] The user acts based on the advice provided and inputs the result as feedback on their device. This feedback is then sent back to the server.

[0215] Step 7:

[0216] The server receives feedback and uses it to learn and improve the system's accuracy. The generative AI model is then fine-tuned to provide more accurate advice during the next consultation.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] [Second Embodiment]

[0221] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0222] 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.

[0223] 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).

[0224] 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.

[0225] 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.

[0226] 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).

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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".

[0233] The system according to the present invention is a system that uses personality analysis means to acquire the user's personality information and generates relationship improvement advice according to the content of the consultation, in order to solve the user's problems in their marital relationship.

[0234] Specifically, this system will be implemented in the following manner: First, the user uses a terminal to input their concerns and questions regarding their marital relationship. The user can also update previously entered personality data as needed. This information is securely encrypted and transmitted to the server.

[0235] The server analyzes the received consultation content and the user's personality information. Using personality analysis tools, it identifies the user's personality pattern based on personality theories such as MBTI and the Big Five personality theory. Based on this information, the server utilizes AI technology to generate advice that can lead to improved communication and relationships between spouses.

[0236] The generated advice is re-encrypted and sent to the user's device. The device decrypts the advice and presents it visually to the user. The user can then incorporate and implement this advice in their daily life.

[0237] For example, specific suggestions might be made, such as, "To improve communication between spouses, set aside time once a week to enjoy a shared hobby." Users can then input feedback on the effectiveness of this advice on their device.

[0238] The server receives feedback information and uses it for analysis, allowing the AI ​​model to learn and improve the accuracy of its next advice. This iterative evolution of the system enables it to provide more personalized support to each user. Through this cycle, users can improve their marital relationships.

[0239] The following describes the processing flow.

[0240] Step 1:

[0241] Users input their concerns and questions about their marital relationship as text using their device. At the same time, users can also pre-register basic personality information about themselves and their partner.

[0242] Step 2:

[0243] The terminal encrypts the user's input and sends the data to the server in a secure state.

[0244] Step 3:

[0245] The server decodes the received data and obtains the user's personality information and consultation details. It then applies personality analysis tools and analyzes the user's personality pattern based on MBTI and Big Five personality theories.

[0246] Step 4:

[0247] Based on the results of the personality analysis and the content of the consultation, the server uses an AI algorithm to generate advice for improving the relationship. This process includes referencing predictive models and past success stories.

[0248] Step 5:

[0249] The server re-encrypts the generated advice and sends it to the user's terminal.

[0250] Step 6:

[0251] The device receives and decodes the advice, then displays it in a format that the user can visually understand. The user can then review and act upon this advice.

[0252] Step 7:

[0253] After implementing the advice, users can input feedback on its effectiveness into their device. This feedback may include specific results and emotional reactions.

[0254] Step 8:

[0255] The device encrypts user feedback and sends it to the server.

[0256] Step 9:

[0257] The server analyzes the feedback and updates the AI ​​model. This improves the overall accuracy of the system so that the next advice is more effective and personalized.

[0258] This series of steps allows users to discreetly analyze marital relationship problems and receive support in implementing solutions.

[0259] (Example 1)

[0260] 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."

[0261] In modern society, marital problems and lack of communication have become significant social issues. However, improving these relationships requires measures tailored to individual personalities and characteristics, making it difficult to provide efficient and accurate advice. Traditional methods tend to offer only general advice and fail to provide solutions that are appropriate for individual personalities and situations.

[0262] 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.

[0263] In this invention, the server includes means for encrypting and securely transmitting personality data, means for analyzing the user's personality information based on personality theory on the server, and means for creating suggestions for improving relationships based on the user's consultation content using a generative AI model. This makes it possible to provide specific and individualized advice tailored to each user's personality.

[0264] "Encrypting and securely transmitting personality data" means encrypting the personality information entered by the user to protect it from unauthorized access by others, and then securely transmitting that information to the server via a communication line.

[0265] "Analyzing user personality information based on personality theory on the server" refers to the process of analyzing received personality data based on psychological frameworks such as MBTI and Big Five personality theory to identify the user's personality pattern.

[0266] "Using a generative AI model to create suggestions for improving relationships based on the user's consultation content" means utilizing information provided by the user and using generative AI technology to automatically generate specific advice and suggestions that are suitable for the user.

[0267] "Encrypting the generated suggestions and sending them to the user's display device for visual display" means encrypting the generated advice, sending it to the user's terminal via a communication channel, decrypting it, and then presenting it to the user visually.

[0268] "Receiving user feedback and applying it to the analysis results on the server" means collecting feedback from users and incorporating it into the evaluation process within the system to improve the accuracy of future suggestions.

[0269] "Using these analysis results to improve the accuracy of suggestion generation" refers to the process of analyzing received feedback and improving the performance of the generating AI model to provide more accurate and personalized suggestions to users.

[0270] In a mode for carrying out the invention, this system is designed as a means to resolve problems in a user's marital relationship. The system aims to provide personalized advice by integrating personality analysis technology and a generative AI model.

[0271] Users first input their concerns and questions about their marital relationship using their own devices. The devices are equipped with software to securely encrypt the information, ensuring that the collected data is transmitted securely to the server. The devices are standard computers or smartphones and require an internet connection.

[0272] The server is equipped with specialized software for performing analysis based on personality theory. The server analyzes the user's personality information using theories such as MBTI and the Big Five personality traits, extracting key characteristics. This personality information forms the basis for creating optimal advice for the user using a generative AI model. The generative AI model generates specific suggestions by considering the user's consultation content, while also referencing past data and success stories.

[0273] The generated advice is encrypted again and sent to the user's device. The device decrypts the received advice and presents it to the user in a visually verifiable format. This may include text and simple diagrams. The user can then put this advice into practice in their daily life and input the results as feedback into the system.

[0274] Based on the feedback, the server updates the AI ​​model and learns to improve the accuracy of future advice. This process allows the system to continuously evolve and meet the individual needs of each user.

[0275] As a concrete example, here is an example of a prompt: "We are a couple in our 30s and feel that we lack communication. We don't have many shared hobbies, and we would like advice on how to improve our relationship." Based on this prompt, the system generates suggestions that take into account the user's personality and situation.

[0276] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0277] Step 1:

[0278] The user uses the terminal to input their troubles and consultation content regarding the marital relationship. What is input includes specific troubles (e.g., "Recently, the conversations with my partner have decreased"), and personality data that is updated as needed. The terminal encrypts this and transmits it to the server after ensuring security. As output, encrypted data is generated and transferred to the server.

[0279] Step 2:

[0280] The server decrypts the encrypted data received from the terminal. The input is the encrypted consultation content and personality data. After decrypting this, it enters the analysis process based on personality theory. The server uses personality analysis technology to identify the user's personality pattern based on MBTI or the Big Five theory. The output obtained from this analysis is metadata indicating the user's characteristics.

[0281] Step 3:

[0282] The server generates advice by utilizing the generated AI model based on the analyzed personality metadata and the received consultation content. The input is the personality metadata and consultation content obtained in the previous step of the server. The generated AI model generates specific and practical advice while referring to similar cases from the database based on these data. What is output is the advice text before encryption.

[0283] Step 4:

[0284] The server encrypts the generated advice and transmits it to the user's terminal. The input is the generated advice itself, which is encrypted and safely delivered to the terminal. The output of this step is the encrypted advice received by the user's terminal.

[0285] Step 5:

[0286] The terminal receives the encrypted advice sent from the server. The input is the encrypted advice text, which is decoded and visually presented to the user. For example, it is presented in an easy-to-understand form for the user by using text or simple illustrations. The output is the decoded advice presented to the user.

[0287] Step 6:

[0288] The user tries the provided advice in daily life, evaluates its effect, and inputs feedback to the terminal. What is input is the reaction to the advice and the progress of relationship improvement, which becomes information useful for improving the next process. The output is transmitted to the server as feedback data.

[0289] Step 7:

[0290] The server receives the feedback from the user and uses it as learning data for improving the performance of the AI model. The input is the feedback data, which is analyzed and used for learning to improve the accuracy of the next advice generation. The output is the improvement in accuracy in subsequent times by the improved AI model.

[0291] (Application Example 1)

[0292] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0293] In modern families, insufficient communication and deteriorating relationships between spouses have become daily problems. In order to appropriately address these problems, accurate advice based on individual personalities and counseling content is required, but in conventional methods, often only uniform advice can be obtained. In addition, there are few systems that can form advice that evolves by reflecting feedback, and there is a need for technology that can provide more individualized support.

[0294] 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.

[0295] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for analyzing the user's consultation content using speech recognition, and means for presenting advice visually and aurally. This makes it possible to provide advice tailored to the user's individual concerns through visual or auditory means, and to improve the quality of the advice by utilizing feedback from the user.

[0296] "Personality analysis means" refers to a device or method for acquiring a user's personality information based on personality theory.

[0297] "User's equipment" refers to terminals or devices used by the user to acquire or input information.

[0298] "Evaluation" refers to the feedback that users provide in response to advice, and this feedback concerns the effectiveness of the advice and areas for improvement.

[0299] "Speech recognition" is a technology that analyzes voice input from users as digital data.

[0300] "Providing advice through visual and auditory means" refers to the process of providing generated advice to the user via screen display or audio output.

[0301] "Means for receiving feedback" refers to a method or device for a server or system to receive user evaluations as data.

[0302] "Multiple psychological theories" refers to a group of theories that use different psychological frameworks and models to analyze patterns of personality and behavior.

[0303] The system for implementing this invention mainly consists of a server and the user's device. The server analyzes the user's personality information and consultation content using personality analysis means, speech recognition technology, and a generative AI model. For personality analysis, psychological theories such as MBTI and the Big Five theory are applied to accurately capture the user's personality pattern. Also, the user's consultation content is digitized by speech recognition and analyzed in detail.

[0304] When the data analysis on the server is completed, the generative AI model forms advice aimed at improving the relationship. This advice is encrypted and then sent to the user's device. On the user's device, the advice can be presented visually or audibly through a touch screen display or a speaker. The user can accept the presented advice and practice it in real life.

[0305] Feedback from the user is sent to the server as the effectiveness and improvement points of the advice. This feedback is incorporated into the learning of the AI model and used to improve the accuracy in the next advice generation. Through this cycle, the system can regularly provide optimized support for individual users.

[0306] For example, when the user consults "Recently, there has been little conversation between husband and wife", the system presents advice such as "How about planning a lunch with your spouse once a week?". And by the user executing this proposal and providing feedback on the result, the quality of the next advice is improved.

[0307] An example of the prompt text is "The user's personality type is INTJ, and they feel a lack of communication between husband and wife. Please propose specific actions for improvement." In this way, accurate and practical advice can be provided based on the individual consultations of the user.

[0308] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The user uses a device to input their concerns and questions about their marital relationship via voice. The voice input is captured by the device via a microphone and converted into digital data. This data is then converted into text data by speech recognition software.

[0311] Step 2:

[0312] The terminal uses speech recognition software to acquire text data, which is then sent to the server. The server uses a generative AI model based on the received text data to generate a prompt message. This prompt message combines the user's specific personality information with the content of their inquiry.

[0313] Step 3:

[0314] The server uses personality analysis tools to analyze the personality information of pre-registered users. This data is analyzed based on MBTI and Big Five personality theories. Based on the analysis, the user's specific personality type is identified. The server then uses this to complete the prompt message.

[0315] Step 4:

[0316] The server uses a generative AI model to generate advice based on prompt messages. This model utilizes a large amount of training data to output advice that helps improve relationships. The generated advice is customized to the user's specific needs.

[0317] Step 5:

[0318] The server encrypts the generated advice and sends it to the terminal. The terminal decrypts the received data and presents it to the user visually and audibly. Specifically, it is displayed as text on the touchscreen display and played back as audio through the speaker.

[0319] Step 6:

[0320] Users try out the advice presented in their daily lives and input the results as feedback on their device. This feedback is sent to the server as evaluation data. The server uses this feedback information to readjust the generated AI model and improve the quality of the advice given next time.

[0321] 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.

[0322] The system according to the present invention aims to improve marital relationships by acquiring user personality information, analyzing consultation content, generating relationship improvement advice, and receiving feedback and learning from it. This system further incorporates an emotion engine that recognizes the user's emotions, thereby improving the accuracy of the advice.

[0323] As a specific implementation, the user first uses a terminal to input details about their current marital relationship. This information, along with personality information, is sent to the server. The server uses personality analysis tools to analyze the user's personality based on multiple psychological theories, such as MBTI and the Big Five personality theory. Simultaneously, an emotion engine recognizes the user's emotional state from the consultation content and incorporates this into the advice generation.

[0324] The server uses an AI algorithm that takes into account personality information and emotional state to generate relationship improvement advice best suited to the user's situation. For example, it can provide advice such as, "Currently, a stressful emotional state has been detected, so we suggest a relaxing collaborative activity." This advice is presented on the user's device in a visually understandable format.

[0325] Users take action based on the advice provided and provide feedback on the results and their feelings at the time. This feedback is also sent to the server through the emotion engine, and the server learns from it. Through this process, the system improves the accuracy of its advice and can provide more effective advice in future consultations.

[0326] This series of processes allows users to gain a deep understanding of marital relationship problems and obtain realistic and actionable solutions without requiring specialized knowledge. In other words, this system provides users with an easy and effective means of resolving their issues, and this is an embodiment of the present invention.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] Users use their devices to input their concerns and questions regarding their marital relationship. They are encouraged to honestly describe their current emotional state during the input process. If a user's personality information is not yet registered, they will be given the option to input it by answering questions.

[0330] Step 2:

[0331] The terminal encrypts the user's entered consultation content and personality information and securely transmits it to the server. Appropriate management measures are taken beforehand to protect privacy.

[0332] Step 3:

[0333] The server decodes the received data and uses personality analysis tools to analyze the user's personality information based on multiple psychological theories. This analysis identifies the user's personality pattern.

[0334] Step 4:

[0335] The server activates an emotion engine to analyze the user's current emotional state based on their consultation content. This analysis utilizes natural language processing techniques and references to an emotion dictionary.

[0336] Step 5:

[0337] The server uses an AI algorithm to generate relationship improvement advice based on the analyzed personality patterns and emotional states. The advice is guaranteed to be particularly considerate of the user's emotional state.

[0338] Step 6:

[0339] The server re-encrypts the generated advice and sends it to the user's device, ensuring privacy while providing advice.

[0340] Step 7:

[0341] The terminal decodes the advice received from the server and displays it in a visual interface that is easy for the user to understand. The user then considers whether or not to act on the advice.

[0342] Step 8:

[0343] Users implement the provided advice and record feedback on their device regarding the results and their feelings during the implementation process.

[0344] Step 9:

[0345] The device encrypts user feedback and associated sentiment data and sends it to the server. This feedback serves as important learning data for generating advice in the future.

[0346] Step 10:

[0347] The server analyzes the received feedback and adjusts the AI ​​algorithm and emotion engine to improve the accuracy of future advice generation. This iterative learning improves the overall system performance.

[0348] (Example 2)

[0349] 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".

[0350] In modern society, relationships between spouses and partners are important, but obtaining effective advice on improving them is often difficult. In particular, there is a lack of personalized advice tailored to individual personalities and emotional states, which can lead to further deterioration of relationships. This invention aims to solve these problems and provide a means to effectively promote relationship improvement.

[0351] 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.

[0352] In this invention, the server includes means for acquiring user personality data based on psychological theories using personality evaluation means, means for generating guidelines aimed at improving relationships based on the content of the user's consultation, and means for detecting the user's emotional state using an emotion recognition device and reflecting this in the generation of guidelines. This makes it possible to provide users with personalized relationship improvement advice.

[0353] A "personality assessment tool" is a function that analyzes and acquires user personality data based on psychological theories.

[0354] A "psychological theory" is a theoretical framework used to understand an individual's personality and behavioral patterns, and generally consists of multiple theories.

[0355] "User" refers to an individual who uses this system and is the entity that provides their personality data and consultation content.

[0356] "Personality data" refers to data that quantifies or classifies a user's personality, and is generated based on psychological theories.

[0357] "Consultation content" refers to specific problems or questions related to relationships that users enter into this system.

[0358] "Guideline generation" is the process of creating specific advice or suggestions to provide to users with the aim of improving relationships.

[0359] An "emotion recognition device" is a function that identifies the emotional state of a user based on the content of their consultation and reflects it in the system's processes.

[0360] "Opinions" refer to feedback provided by users in response to advice, and this information is used to help the system learn and improve.

[0361] This system aims to improve relationships between spouses and partners by providing users with personalized advice. The system consists of a personality assessment tool, an emotion recognition device, and a guideline generation device. This allows users to easily receive practical advice for improving their relationships.

[0362] Users first input their personality data and consultation details using a device such as a smartphone, tablet, or computer. This information is securely transmitted to a server. The server runs a program based on psychological theories and analyzes the personality data through personality assessment methods. In this process, MBTI and Big Five personality theories are used.

[0363] Subsequently, the server analyzes the consultation content using an emotion recognition device and identifies the user's emotional state. This information is a crucial element in the guideline generation process by the generative AI model. The server considers personality data and emotional state together to generate the most appropriate guideline for the user's situation.

[0364] The generated guidelines are sent to the user's device in a visually easy-to-understand format. For example, if a stressful emotional state is detected, the server can offer specific advice such as, "We suggest spending some time together to relax."

[0365] Users take action based on the advice and input feedback about the results and their feelings via their device. The server receives this feedback and uses it to improve the overall accuracy of the system. Through this iterative learning process, even more accurate advice will be provided during subsequent consultations.

[0366] As a concrete example, a prompt might look like this: "Generate advice for improving the marital relationship. The user's personality type is 'ENFJ' according to the MBTI, and their current emotional state is 'anxious'. Please provide specific and appropriate advice." This prompt serves as a guide for the generating AI model to output advice tailored to the individual situation.

[0367] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0368] Step 1:

[0369] Users use their devices to input their personality data and specific questions about their marital relationship. For example, "Recently, I've been talking less with my partner." This information includes personality patterns, so detailed personality data is entered.

[0370] Step 2:

[0371] The terminal sends the entered information and personality data to the server. The data is encrypted and securely transferred to the server. The input here consists of personality data and consultation details, while the output is encrypted data.

[0372] Step 3:

[0373] The server analyzes the received data and uses personality assessment tools to analyze the personality data. For example, it identifies MBTI types based on psychological theories. The input is encrypted data, and the output is a classified personality pattern.

[0374] Step 4:

[0375] The server uses an emotion recognition device to identify the user's emotional state from the consultation content. For example, it uses natural language processing to identify emotions such as "anxiety" and "stress." The input is text information of the consultation content, and the output is the identified emotional state.

[0376] Step 5:

[0377] The server uses the system's AI model to generate appropriate relationship improvement guidelines based on personality patterns and emotional states. The input here is personality patterns and emotional states, and the output is the guidelines generated through the AI ​​model. For example, one might suggest "a relaxing collaborative activity."

[0378] Step 6:

[0379] The terminal presents the generated guidelines to the user in a visually easy-to-understand format. For example, it may display them as a list or text message. The input from the server is the guidelines data, and the output is the display to the user.

[0380] Step 7:

[0381] Users take action based on the provided guidelines and input feedback on the results and their feelings into the device. This input serves as a record of their opinions and the effects of the guidelines.

[0382] Step 8:

[0383] The device sends user feedback to the server. The transmitted data includes practical results and changes in emotions. The output is feedback data sent to the server.

[0384] Step 9:

[0385] The server analyzes the feedback data and learns to improve the overall accuracy of the system. This improves the accuracy of advice generation in subsequent sessions. The input is the feedback data, and the output is the improved AI model.

[0386] (Application Example 2)

[0387] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0388] In caregiving settings, poor communication between caregivers and those receiving care, and an inability to properly understand the emotional state of those receiving care, can lead to a deterioration of relationships and inappropriate care. Therefore, it is crucial for caregivers to understand the emotional state of those receiving care and to find the most appropriate communication methods based on that state.

[0389] 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.

[0390] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for recognizing emotional states from image and audio data using emotion analysis means, and means for reflecting the recognized emotional states in advice generation. This makes it possible for caregivers to understand the emotional state of those being cared for in real time and to provide optimal communication methods and relationship improvement measures based on that understanding.

[0391] A "personality analysis method" is a technique for obtaining a user's personality information based on personality theory.

[0392] "Advice generation" is the process of creating advice aimed at improving relationships, based on the user's consultation content and emotional state.

[0393] A "device" is a device used to present generated advice to the user.

[0394] "Feedback" refers to information about the results of user actions and their emotions at the time, and is used to improve the accuracy of the system.

[0395] "Emotional analysis methods" refer to technologies that analyze image and audio data to recognize the emotional state of a user.

[0396] This invention is a system implemented to improve the relationship between caregivers and those receiving care in the field of elderly care. The system utilizes devices such as smartphones and tablets. A server processes data transmitted from users through these devices and performs necessary analysis.

[0397] The server uses TensorFlow, an AI library for the Python programming language, to analyze personality information and generate advice. Personality information is obtained using personality analysis tools and based on psychological theories. Furthermore, it uses emotion analysis engines such as Microsoft Azure Face API and Google Cloud Vision to recognize the emotional state of the person being cared for from image and audio data.

[0398] The generated advice is visually displayed on the terminal, allowing caregivers to use it to improve communication with those they care for. The system receives feedback provided by caregivers and processes it on the server. Based on this feedback, the system iteratively improves the accuracy of its advice generation.

[0399] For example, if the server detects, based on its sentiment analysis, that the person being cared for has been feeling down recently, it will generate a prompt message such as, "Sentiment analysis indicates that the person being cared for has been feeling down recently. What activities would improve their mood?" This allows the caregiver to suggest appropriate activities.

[0400] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0401] Step 1:

[0402] The user uses a terminal to input personality information and consultation details about the person being cared for. The entered data is sent from the terminal to the server. The server receives this data and prepares to begin the personality analysis.

[0403] Step 2:

[0404] The server uses personality analysis tools to identify personality patterns based on the received personality information and multiple psychological theories. At this stage, the results of the personality pattern analysis are output.

[0405] Step 3:

[0406] The server uses emotion analysis tools, taking image and audio data from the device as input. It recognizes the emotional state using Microsoft Azure Face API or Google Cloud Vision. The recognized emotional state is output and used to generate advice for the next step.

[0407] Step 4:

[0408] The server utilizes a generative AI model to generate optimal advice based on personality analysis results and emotional states. In this process, the AI ​​suggests activities and communication methods that are considered effective for improving relationships.

[0409] Step 5:

[0410] The generated advice is output to the terminal and presented to the user. The terminal displays this advice in a visually easy-to-understand format, enabling the user to take action based on it.

[0411] Step 6:

[0412] The user acts based on the advice provided and inputs the result as feedback on their device. This feedback is then sent back to the server.

[0413] Step 7:

[0414] The server receives feedback and uses it to learn and improve the system's accuracy. The generative AI model is then fine-tuned to provide more accurate advice during the next consultation.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] [Third Embodiment]

[0419] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0420] 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.

[0421] 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).

[0422] 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.

[0423] 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.

[0424] 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).

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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".

[0431] The system according to the present invention is a system that uses personality analysis means to acquire the user's personality information and generates relationship improvement advice according to the content of the consultation, in order to solve the user's problems in their marital relationship.

[0432] Specifically, this system will be implemented in the following manner: First, the user uses a terminal to input their concerns and questions regarding their marital relationship. The user can also update previously entered personality data as needed. This information is securely encrypted and transmitted to the server.

[0433] The server analyzes the received consultation content and the user's personality information. Using personality analysis tools, it identifies the user's personality pattern based on personality theories such as MBTI and the Big Five personality theory. Based on this information, the server utilizes AI technology to generate advice that can lead to improved communication and relationships between spouses.

[0434] The generated advice is re-encrypted and sent to the user's device. The device decrypts the advice and presents it visually to the user. The user can then incorporate and implement this advice in their daily life.

[0435] For example, specific suggestions might be made, such as, "To improve communication between spouses, set aside time once a week to enjoy a shared hobby." Users can then input feedback on the effectiveness of this advice on their device.

[0436] The server receives feedback information and uses it for analysis, allowing the AI ​​model to learn and improve the accuracy of its next advice. This iterative evolution of the system enables it to provide more personalized support to each user. Through this cycle, users can improve their marital relationships.

[0437] The following describes the processing flow.

[0438] Step 1:

[0439] Users input their concerns and questions about their marital relationship as text using their device. At the same time, users can also pre-register basic personality information about themselves and their partner.

[0440] Step 2:

[0441] The terminal encrypts the user's input and sends the data to the server in a secure state.

[0442] Step 3:

[0443] The server decodes the received data and obtains the user's personality information and consultation details. It then applies personality analysis tools and analyzes the user's personality pattern based on MBTI and Big Five personality theories.

[0444] Step 4:

[0445] Based on the results of the personality analysis and the content of the consultation, the server uses an AI algorithm to generate advice for improving the relationship. This process includes referencing predictive models and past success stories.

[0446] Step 5:

[0447] The server re-encrypts the generated advice and sends it to the user's terminal.

[0448] Step 6:

[0449] The device receives and decodes the advice, then displays it in a format that the user can visually understand. The user can then review and act upon this advice.

[0450] Step 7:

[0451] After implementing the advice, users can input feedback on its effectiveness into their device. This feedback may include specific results and emotional reactions.

[0452] Step 8:

[0453] The device encrypts user feedback and sends it to the server.

[0454] Step 9:

[0455] The server analyzes the feedback and updates the AI ​​model. This improves the overall accuracy of the system so that the next advice is more effective and personalized.

[0456] This series of steps allows users to discreetly analyze marital relationship problems and receive support in implementing solutions.

[0457] (Example 1)

[0458] 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."

[0459] In modern society, marital problems and lack of communication have become significant social issues. However, improving these relationships requires measures tailored to individual personalities and characteristics, making it difficult to provide efficient and accurate advice. Traditional methods tend to offer only general advice and fail to provide solutions that are appropriate for individual personalities and situations.

[0460] 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.

[0461] In this invention, the server includes means for encrypting and securely transmitting personality data, means for analyzing the user's personality information based on personality theory on the server, and means for creating suggestions for improving relationships based on the user's consultation content using a generative AI model. This makes it possible to provide specific and individualized advice tailored to each user's personality.

[0462] "Encrypting and securely transmitting personality data" means encrypting the personality information entered by the user to protect it from unauthorized access by others, and then securely transmitting that information to the server via a communication line.

[0463] "Analyzing user personality information based on personality theory on the server" refers to the process of analyzing received personality data based on psychological frameworks such as MBTI and Big Five personality theory to identify the user's personality pattern.

[0464] "Using a generative AI model to create suggestions for improving relationships based on the user's consultation content" means utilizing information provided by the user and using generative AI technology to automatically generate specific advice and suggestions that are suitable for the user.

[0465] "Encrypting the generated suggestions and sending them to the user's display device for visual display" means encrypting the generated advice, sending it to the user's terminal via a communication channel, decrypting it, and then presenting it to the user visually.

[0466] "Receiving user feedback and applying it to the analysis results on the server" means collecting feedback from users and incorporating it into the evaluation process within the system to improve the accuracy of future suggestions.

[0467] "Using these analysis results to improve the accuracy of suggestion generation" refers to the process of analyzing received feedback and improving the performance of the generating AI model to provide more accurate and personalized suggestions to users.

[0468] In a mode for carrying out the invention, this system is designed as a means to resolve problems in a user's marital relationship. The system aims to provide personalized advice by integrating personality analysis technology and a generative AI model.

[0469] Users first input their concerns and questions about their marital relationship using their own devices. The devices are equipped with software to securely encrypt the information, ensuring that the collected data is transmitted securely to the server. The devices are standard computers or smartphones and require an internet connection.

[0470] The server is equipped with specialized software for performing analysis based on personality theory. The server analyzes the user's personality information using theories such as MBTI and the Big Five personality traits, extracting key characteristics. This personality information forms the basis for creating optimal advice for the user using a generative AI model. The generative AI model generates specific suggestions by considering the user's consultation content, while also referencing past data and success stories.

[0471] The generated advice is encrypted again and sent to the user's device. The device decrypts the received advice and presents it to the user in a visually verifiable format. This may include text and simple diagrams. The user can then put this advice into practice in their daily life and input the results as feedback into the system.

[0472] Based on the feedback, the server updates the AI ​​model and learns to improve the accuracy of future advice. This process allows the system to continuously evolve and meet the individual needs of each user.

[0473] As a concrete example, here is an example of a prompt: "We are a couple in our 30s and feel that we lack communication. We don't have many shared hobbies, and we would like advice on how to improve our relationship." Based on this prompt, the system generates suggestions that take into account the user's personality and situation.

[0474] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0475] Step 1:

[0476] Users use their devices to input concerns and questions about their marital relationship. The input includes specific concerns (e.g., "Recently, I've been talking less with my partner") and personality data that is updated as needed. The device encrypts this data to ensure security before sending it to the server. The output is encrypted data, which is then transferred to the server.

[0477] Step 2:

[0478] The server decrypts the encrypted data received from the terminal. The input consists of encrypted consultation content and personality data. After decryption, the server proceeds to an analysis process based on personality theory. Using personality analysis technology, the server identifies the user's personality pattern based on MBTI and Big Five personality theories. The output obtained from this analysis is metadata that indicates the user's characteristics.

[0479] Step 3:

[0480] The server generates advice using a generative AI model based on the analyzed personality metadata and received consultation content. The input is the personality metadata and consultation content obtained in the server's previous step. The generative AI model uses this data to generate specific and practical advice, referencing similar cases from the database. The output is the advice text before encryption.

[0481] Step 4:

[0482] The server encrypts the generated advice and sends it to the user's terminal. The input is the generated advice itself, which is encrypted and securely sent to the terminal. The output of this step is the encrypted advice received by the user's terminal.

[0483] Step 5:

[0484] The terminal receives encrypted advice sent from the server. The input is encrypted advice text, which is then decrypted and presented visually to the user. For example, it may be displayed using text or simple diagrams to make it easier for the user to understand. The output is the decrypted advice presented to the user.

[0485] Step 6:

[0486] Users try out the provided advice in their daily lives, evaluate its effectiveness, and input feedback into their device. This feedback includes their response to the advice and the progress made in improving relationships, which is then used to improve future processes. The output is sent to the server as feedback data.

[0487] Step 7:

[0488] The server receives feedback from users and uses it as training data to improve the performance of the AI ​​model. The input is feedback data, which is analyzed and used for learning to improve the accuracy of future advice generation. The output is the improved accuracy of the improved AI model in subsequent attempts.

[0489] (Application Example 1)

[0490] 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."

[0491] In modern households, a lack of communication and deteriorating relationships between spouses are commonplace problems. To address these issues effectively, personalized advice tailored to each individual's personality and the nature of their concerns is required. However, traditional methods often only provide uniform advice. Furthermore, there are few systems that can evolve advice based on feedback, highlighting the need for technologies that can provide more individualized support.

[0492] 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.

[0493] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for analyzing the user's consultation content using speech recognition, and means for presenting advice visually and aurally. This makes it possible to provide advice tailored to the user's individual concerns through visual or auditory means, and to improve the quality of the advice by utilizing feedback from the user.

[0494] "Personality analysis means" refers to a device or method for acquiring a user's personality information based on personality theory.

[0495] "User's equipment" refers to terminals or devices used by the user to acquire or input information.

[0496] "Evaluation" refers to the feedback that users provide in response to advice, and this feedback concerns the effectiveness of the advice and areas for improvement.

[0497] "Speech recognition" is a technology that analyzes voice input from users as digital data.

[0498] "Providing advice through visual and auditory means" refers to the process of providing generated advice to the user via screen display or audio output.

[0499] "Means for receiving feedback" refers to a method or device for a server or system to receive user evaluations as data.

[0500] "Multiple psychological theories" refers to a group of theories that use different psychological frameworks and models to analyze patterns of personality and behavior.

[0501] The system for implementing this invention mainly consists of a server and user equipment. The server analyzes the user's personality information and consultation content using personality analysis means, speech recognition technology, and a generative AI model. Psychological theories such as MBTI and Big Five theory are applied to the personality analysis to accurately capture the user's personality pattern. In addition, the user's consultation content is converted into data by speech recognition and analyzed in detail.

[0502] Once data analysis on the server is complete, the generating AI model forms advice aimed at improving relationships. This advice is encrypted and then sent to the user's device. On the user's device, the advice can be presented visually or audibly through a touchscreen display or speaker. The user can accept the presented advice and put it into practice in their daily life.

[0503] User feedback is sent to the server as assessment of the effectiveness of the advice and areas for improvement. This feedback is incorporated into the AI ​​model's training and used to improve the accuracy of future advice generation. This cycle allows the system to regularly provide personalized support to individual users.

[0504] For example, if a user consults the system about the lack of communication between spouses recently, the system might suggest, "Why not plan a lunch date once a week?" The system then works by having the user implement this suggestion and provide feedback on the results, which helps improve the quality of future advice.

[0505] An example of a prompt message would be, "The user's personality type is INTJ, and they feel there is a lack of communication in their marriage. Please suggest specific actions to improve the situation." In this way, accurate and practical advice can be provided based on the user's individual needs.

[0506] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0507] Step 1:

[0508] The user uses a device to input their concerns and questions about their marital relationship via voice. The voice input is captured by the device via a microphone and converted into digital data. This data is then converted into text data by speech recognition software.

[0509] Step 2:

[0510] The terminal uses speech recognition software to acquire text data, which is then sent to the server. The server uses a generative AI model based on the received text data to generate a prompt message. This prompt message combines the user's specific personality information with the content of their inquiry.

[0511] Step 3:

[0512] The server uses personality analysis tools to analyze the personality information of pre-registered users. This data is analyzed based on MBTI and Big Five personality theories. Based on the analysis, the user's specific personality type is identified. The server then uses this to complete the prompt message.

[0513] Step 4:

[0514] The server uses a generative AI model to generate advice based on prompt messages. This model utilizes a large amount of training data to output advice that helps improve relationships. The generated advice is customized to the user's specific needs.

[0515] Step 5:

[0516] The server encrypts the generated advice and sends it to the terminal. The terminal decrypts the received data and presents it to the user visually and audibly. Specifically, it is displayed as text on the touchscreen display and played back as audio through the speaker.

[0517] Step 6:

[0518] Users try out the advice presented in their daily lives and input the results as feedback on their device. This feedback is sent to the server as evaluation data. The server uses this feedback information to readjust the generated AI model and improve the quality of the advice given next time.

[0519] 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.

[0520] The system according to the present invention aims to improve marital relationships by acquiring user personality information, analyzing consultation content, generating relationship improvement advice, and receiving feedback and learning from it. This system further incorporates an emotion engine that recognizes the user's emotions, thereby improving the accuracy of the advice.

[0521] As a specific implementation, the user first uses a terminal to input details about their current marital relationship. This information, along with personality information, is sent to the server. The server uses personality analysis tools to analyze the user's personality based on multiple psychological theories, such as MBTI and the Big Five personality theory. Simultaneously, an emotion engine recognizes the user's emotional state from the consultation content and incorporates this into the advice generation.

[0522] The server uses an AI algorithm that takes into account personality information and emotional state to generate relationship improvement advice best suited to the user's situation. For example, it can provide advice such as, "Currently, a stressful emotional state has been detected, so we suggest a relaxing collaborative activity." This advice is presented on the user's device in a visually understandable format.

[0523] Users take action based on the advice provided and provide feedback on the results and their feelings at the time. This feedback is also sent to the server through the emotion engine, and the server learns from it. Through this process, the system improves the accuracy of its advice and can provide more effective advice in future consultations.

[0524] This series of processes allows users to gain a deep understanding of marital relationship problems and obtain realistic and actionable solutions without requiring specialized knowledge. In other words, this system provides users with an easy and effective means of resolving their issues, and this is an embodiment of the present invention.

[0525] The following describes the processing flow.

[0526] Step 1:

[0527] Users use their devices to input their concerns and questions regarding their marital relationship. They are encouraged to honestly describe their current emotional state during the input process. If a user's personality information is not yet registered, they will be given the option to input it by answering questions.

[0528] Step 2:

[0529] The terminal encrypts the user's entered consultation content and personality information and securely transmits it to the server. Appropriate management measures are taken beforehand to protect privacy.

[0530] Step 3:

[0531] The server decodes the received data and uses personality analysis tools to analyze the user's personality information based on multiple psychological theories. This analysis identifies the user's personality pattern.

[0532] Step 4:

[0533] The server activates an emotion engine to analyze the user's current emotional state based on their consultation content. This analysis utilizes natural language processing techniques and references to an emotion dictionary.

[0534] Step 5:

[0535] The server uses an AI algorithm to generate relationship improvement advice based on the analyzed personality patterns and emotional states. The advice is guaranteed to be particularly considerate of the user's emotional state.

[0536] Step 6:

[0537] The server re-encrypts the generated advice and sends it to the user's device, ensuring privacy while providing advice.

[0538] Step 7:

[0539] The terminal decodes the advice received from the server and displays it in a visual interface that is easy for the user to understand. The user then considers whether or not to act on the advice.

[0540] Step 8:

[0541] Users implement the provided advice and record feedback on their device regarding the results and their feelings during the implementation process.

[0542] Step 9:

[0543] The device encrypts user feedback and associated sentiment data and sends it to the server. This feedback serves as important learning data for generating advice in the future.

[0544] Step 10:

[0545] The server analyzes the received feedback and adjusts the AI ​​algorithm and emotion engine to improve the accuracy of future advice generation. This iterative learning improves the overall system performance.

[0546] (Example 2)

[0547] 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."

[0548] In modern society, relationships between spouses and partners are important, but obtaining effective advice on improving them is often difficult. In particular, there is a lack of personalized advice tailored to individual personalities and emotional states, which can lead to further deterioration of relationships. This invention aims to solve these problems and provide a means to effectively promote relationship improvement.

[0549] 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.

[0550] In this invention, the server includes means for acquiring user personality data based on psychological theories using personality evaluation means, means for generating guidelines aimed at improving relationships based on the content of the user's consultation, and means for detecting the user's emotional state using an emotion recognition device and reflecting this in the generation of guidelines. This makes it possible to provide users with personalized relationship improvement advice.

[0551] A "personality assessment tool" is a function that analyzes and acquires user personality data based on psychological theories.

[0552] A "psychological theory" is a theoretical framework used to understand an individual's personality and behavioral patterns, and generally consists of multiple theories.

[0553] "User" refers to an individual who uses this system and is the entity that provides their personality data and consultation content.

[0554] "Personality data" refers to data that quantifies or classifies a user's personality, and is generated based on psychological theories.

[0555] "Consultation content" refers to specific problems or questions related to relationships that users enter into this system.

[0556] "Guideline generation" is the process of creating specific advice or suggestions to provide to users with the aim of improving relationships.

[0557] An "emotion recognition device" is a function that identifies the emotional state of a user based on the content of their consultation and reflects it in the system's processes.

[0558] "Opinions" refer to feedback provided by users in response to advice, and this information is used to help the system learn and improve.

[0559] This system aims to improve relationships between spouses and partners by providing users with personalized advice. The system consists of a personality assessment tool, an emotion recognition device, and a guideline generation device. This allows users to easily receive practical advice for improving their relationships.

[0560] Users first input their personality data and consultation details using a device such as a smartphone, tablet, or computer. This information is securely transmitted to a server. The server runs a program based on psychological theories and analyzes the personality data through personality assessment methods. In this process, MBTI and Big Five personality theories are used.

[0561] Subsequently, the server analyzes the consultation content using an emotion recognition device and identifies the user's emotional state. This information is a crucial element in the guideline generation process by the generative AI model. The server considers personality data and emotional state together to generate the most appropriate guideline for the user's situation.

[0562] The generated guidelines are sent to the user's device in a visually easy-to-understand format. For example, if a stressful emotional state is detected, the server can offer specific advice such as, "We suggest spending some time together to relax."

[0563] Users take action based on the advice and input feedback about the results and their feelings via their device. The server receives this feedback and uses it to improve the overall accuracy of the system. Through this iterative learning process, even more accurate advice will be provided during subsequent consultations.

[0564] As a concrete example, a prompt might look like this: "Generate advice for improving the marital relationship. The user's personality type is 'ENFJ' according to the MBTI, and their current emotional state is 'anxious'. Please provide specific and appropriate advice." This prompt serves as a guide for the generating AI model to output advice tailored to the individual situation.

[0565] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0566] Step 1:

[0567] Users use their devices to input their personality data and specific questions about their marital relationship. For example, "Recently, I've been talking less with my partner." This information includes personality patterns, so detailed personality data is entered.

[0568] Step 2:

[0569] The terminal sends the entered information and personality data to the server. The data is encrypted and securely transferred to the server. The input here consists of personality data and consultation details, while the output is encrypted data.

[0570] Step 3:

[0571] The server analyzes the received data and uses personality assessment tools to analyze the personality data. For example, it identifies MBTI types based on psychological theories. The input is encrypted data, and the output is a classified personality pattern.

[0572] Step 4:

[0573] The server uses an emotion recognition device to identify the user's emotional state from the consultation content. For example, it uses natural language processing to identify emotions such as "anxiety" and "stress." The input is text information of the consultation content, and the output is the identified emotional state.

[0574] Step 5:

[0575] The server uses the system's AI model to generate appropriate relationship improvement guidelines based on personality patterns and emotional states. The input here is personality patterns and emotional states, and the output is the guidelines generated through the AI ​​model. For example, one might suggest "a relaxing collaborative activity."

[0576] Step 6:

[0577] The terminal presents the generated guidelines to the user in a visually easy-to-understand format. For example, it may display them as a list or text message. The input from the server is the guidelines data, and the output is the display to the user.

[0578] Step 7:

[0579] Users take action based on the provided guidelines and input feedback on the results and their feelings into the device. This input serves as a record of their opinions and the effects of the guidelines.

[0580] Step 8:

[0581] The device sends user feedback to the server. The transmitted data includes practical results and changes in emotions. The output is feedback data sent to the server.

[0582] Step 9:

[0583] The server analyzes the feedback data and learns to improve the overall accuracy of the system. This improves the accuracy of advice generation in subsequent sessions. The input is the feedback data, and the output is the improved AI model.

[0584] (Application Example 2)

[0585] 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."

[0586] In caregiving settings, poor communication between caregivers and those receiving care, and an inability to properly understand the emotional state of those receiving care, can lead to a deterioration of relationships and inappropriate care. Therefore, it is crucial for caregivers to understand the emotional state of those receiving care and to find the most appropriate communication methods based on that state.

[0587] 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.

[0588] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for recognizing emotional states from image and audio data using emotion analysis means, and means for reflecting the recognized emotional states in advice generation. This makes it possible for caregivers to understand the emotional state of those being cared for in real time and to provide optimal communication methods and relationship improvement measures based on that understanding.

[0589] A "personality analysis method" is a technique for obtaining a user's personality information based on personality theory.

[0590] "Advice generation" is the process of creating advice aimed at improving relationships, based on the user's consultation content and emotional state.

[0591] A "device" is a device used to present generated advice to the user.

[0592] "Feedback" refers to information about the results of user actions and their emotions at the time, and is used to improve the accuracy of the system.

[0593] "Emotional analysis methods" refer to technologies that analyze image and audio data to recognize the emotional state of a user.

[0594] This invention is a system implemented to improve the relationship between caregivers and those receiving care in the field of elderly care. The system utilizes devices such as smartphones and tablets. A server processes data transmitted from users through these devices and performs necessary analysis.

[0595] The server uses TensorFlow, an AI library for the Python programming language, to analyze personality information and generate advice. Personality information is obtained using personality analysis tools and based on psychological theories. Furthermore, it uses emotion analysis engines such as Microsoft Azure Face API and Google Cloud Vision to recognize the emotional state of the person being cared for from image and audio data.

[0596] The generated advice is visually displayed on the terminal, allowing caregivers to use it to improve communication with those they care for. The system receives feedback provided by caregivers and processes it on the server. Based on this feedback, the system iteratively improves the accuracy of its advice generation.

[0597] For example, if the server detects, based on its sentiment analysis, that the person being cared for has been feeling down recently, it will generate a prompt message such as, "Sentiment analysis indicates that the person being cared for has been feeling down recently. What activities would improve their mood?" This allows the caregiver to suggest appropriate activities.

[0598] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0599] Step 1:

[0600] The user uses a terminal to input personality information and consultation details about the person being cared for. The entered data is sent from the terminal to the server. The server receives this data and prepares to begin the personality analysis.

[0601] Step 2:

[0602] The server uses personality analysis tools to identify personality patterns based on the received personality information and multiple psychological theories. At this stage, the results of the personality pattern analysis are output.

[0603] Step 3:

[0604] The server uses emotion analysis tools, taking image and audio data from the device as input. It recognizes the emotional state using Microsoft Azure Face API or Google Cloud Vision. The recognized emotional state is output and used to generate advice for the next step.

[0605] Step 4:

[0606] The server utilizes a generative AI model to generate optimal advice based on personality analysis results and emotional states. In this process, the AI ​​suggests activities and communication methods that are considered effective for improving relationships.

[0607] Step 5:

[0608] The generated advice is output to the terminal and presented to the user. The terminal displays this advice in a visually easy-to-understand format, enabling the user to take action based on it.

[0609] Step 6:

[0610] The user acts based on the advice provided and inputs the result as feedback on their device. This feedback is then sent back to the server.

[0611] Step 7:

[0612] The server receives feedback and uses it to learn and improve the system's accuracy. The generative AI model is then fine-tuned to provide more accurate advice during the next consultation.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] [Fourth Embodiment]

[0617] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0618] 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.

[0619] 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).

[0620] 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.

[0621] 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.

[0622] 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).

[0623] 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.

[0624] 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.

[0625] 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.

[0626] 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.

[0627] 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.

[0628] 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.

[0629] 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".

[0630] The system according to the present invention is a system that uses personality analysis means to acquire the user's personality information and generates relationship improvement advice according to the content of the consultation, in order to solve the user's problems in their marital relationship.

[0631] Specifically, this system will be implemented in the following manner: First, the user uses a terminal to input their concerns and questions regarding their marital relationship. The user can also update previously entered personality data as needed. This information is securely encrypted and transmitted to the server.

[0632] The server analyzes the received consultation content and the user's personality information. Using personality analysis tools, it identifies the user's personality pattern based on personality theories such as MBTI and the Big Five personality theory. Based on this information, the server utilizes AI technology to generate advice that can lead to improved communication and relationships between spouses.

[0633] The generated advice is re-encrypted and sent to the user's device. The device decrypts the advice and presents it visually to the user. The user can then incorporate and implement this advice in their daily life.

[0634] For example, specific suggestions might be made, such as, "To improve communication between spouses, set aside time once a week to enjoy a shared hobby." Users can then input feedback on the effectiveness of this advice on their device.

[0635] The server receives feedback information and uses it for analysis, allowing the AI ​​model to learn and improve the accuracy of its next advice. This iterative evolution of the system enables it to provide more personalized support to each user. Through this cycle, users can improve their marital relationships.

[0636] The following describes the processing flow.

[0637] Step 1:

[0638] Users input their concerns and questions about their marital relationship as text using their device. At the same time, users can also pre-register basic personality information about themselves and their partner.

[0639] Step 2:

[0640] The terminal encrypts the user's input and sends the data to the server in a secure state.

[0641] Step 3:

[0642] The server decodes the received data and obtains the user's personality information and consultation details. It then applies personality analysis tools and analyzes the user's personality pattern based on MBTI and Big Five personality theories.

[0643] Step 4:

[0644] Based on the results of the personality analysis and the content of the consultation, the server uses an AI algorithm to generate advice for improving the relationship. This process includes referencing predictive models and past success stories.

[0645] Step 5:

[0646] The server re-encrypts the generated advice and sends it to the user's terminal.

[0647] Step 6:

[0648] The device receives and decodes the advice, then displays it in a format that the user can visually understand. The user can then review and act upon this advice.

[0649] Step 7:

[0650] After implementing the advice, users can input feedback on its effectiveness into their device. This feedback may include specific results and emotional reactions.

[0651] Step 8:

[0652] The device encrypts user feedback and sends it to the server.

[0653] Step 9:

[0654] The server analyzes the feedback and updates the AI ​​model. This improves the overall accuracy of the system so that the next advice is more effective and personalized.

[0655] This series of steps allows users to discreetly analyze marital relationship problems and receive support in implementing solutions.

[0656] (Example 1)

[0657] 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".

[0658] In modern society, marital problems and lack of communication have become significant social issues. However, improving these relationships requires measures tailored to individual personalities and characteristics, making it difficult to provide efficient and accurate advice. Traditional methods tend to offer only general advice and fail to provide solutions that are appropriate for individual personalities and situations.

[0659] 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.

[0660] In this invention, the server includes means for encrypting and securely transmitting personality data, means for analyzing the user's personality information based on personality theory on the server, and means for creating suggestions for improving relationships based on the user's consultation content using a generative AI model. This makes it possible to provide specific and individualized advice tailored to each user's personality.

[0661] "Encrypting and securely transmitting personality data" means encrypting the personality information entered by the user to protect it from unauthorized access by others, and then securely transmitting that information to the server via a communication line.

[0662] "Analyzing user personality information based on personality theory on the server" refers to the process of analyzing received personality data based on psychological frameworks such as MBTI and Big Five personality theory to identify the user's personality pattern.

[0663] "Using a generative AI model to create suggestions for improving relationships based on the user's consultation content" means utilizing information provided by the user and using generative AI technology to automatically generate specific advice and suggestions that are suitable for the user.

[0664] "Encrypting the generated suggestions and sending them to the user's display device for visual display" means encrypting the generated advice, sending it to the user's terminal via a communication channel, decrypting it, and then presenting it to the user visually.

[0665] "Receiving user feedback and applying it to the analysis results on the server" means collecting feedback from users and incorporating it into the evaluation process within the system to improve the accuracy of future suggestions.

[0666] "Using these analysis results to improve the accuracy of suggestion generation" refers to the process of analyzing received feedback and improving the performance of the generating AI model to provide more accurate and personalized suggestions to users.

[0667] In a mode for carrying out the invention, this system is designed as a means to resolve problems in a user's marital relationship. The system aims to provide personalized advice by integrating personality analysis technology and a generative AI model.

[0668] Users first input their concerns and questions about their marital relationship using their own devices. The devices are equipped with software to securely encrypt the information, ensuring that the collected data is transmitted securely to the server. The devices are standard computers or smartphones and require an internet connection.

[0669] The server is equipped with specialized software for performing analysis based on personality theory. The server analyzes the user's personality information using theories such as MBTI and the Big Five personality traits, extracting key characteristics. This personality information forms the basis for creating optimal advice for the user using a generative AI model. The generative AI model generates specific suggestions by considering the user's consultation content, while also referencing past data and success stories.

[0670] The generated advice is encrypted again and sent to the user's device. The device decrypts the received advice and presents it to the user in a visually verifiable format. This may include text and simple diagrams. The user can then put this advice into practice in their daily life and input the results as feedback into the system.

[0671] Based on the feedback, the server updates the AI ​​model and learns to improve the accuracy of future advice. This process allows the system to continuously evolve and meet the individual needs of each user.

[0672] As a concrete example, here is an example of a prompt: "We are a couple in our 30s and feel that we lack communication. We don't have many shared hobbies, and we would like advice on how to improve our relationship." Based on this prompt, the system generates suggestions that take into account the user's personality and situation.

[0673] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0674] Step 1:

[0675] Users use their devices to input concerns and questions about their marital relationship. The input includes specific concerns (e.g., "Recently, I've been talking less with my partner") and personality data that is updated as needed. The device encrypts this data to ensure security before sending it to the server. The output is encrypted data, which is then transferred to the server.

[0676] Step 2:

[0677] The server decrypts the encrypted data received from the terminal. The input consists of encrypted consultation content and personality data. After decryption, the server proceeds to an analysis process based on personality theory. Using personality analysis technology, the server identifies the user's personality pattern based on MBTI and Big Five personality theories. The output obtained from this analysis is metadata that indicates the user's characteristics.

[0678] Step 3:

[0679] The server generates advice using a generative AI model based on the analyzed personality metadata and received consultation content. The input is the personality metadata and consultation content obtained in the server's previous step. The generative AI model uses this data to generate specific and practical advice, referencing similar cases from the database. The output is the advice text before encryption.

[0680] Step 4:

[0681] The server encrypts the generated advice and sends it to the user's terminal. The input is the generated advice itself, which is encrypted and securely sent to the terminal. The output of this step is the encrypted advice received by the user's terminal.

[0682] Step 5:

[0683] The terminal receives encrypted advice sent from the server. The input is encrypted advice text, which is then decrypted and presented visually to the user. For example, it may be displayed using text or simple diagrams to make it easier for the user to understand. The output is the decrypted advice presented to the user.

[0684] Step 6:

[0685] Users try out the provided advice in their daily lives, evaluate its effectiveness, and input feedback into their device. This feedback includes their response to the advice and the progress made in improving relationships, which is then used to improve future processes. The output is sent to the server as feedback data.

[0686] Step 7:

[0687] The server receives feedback from users and uses it as training data to improve the performance of the AI ​​model. The input is feedback data, which is analyzed and used for learning to improve the accuracy of future advice generation. The output is the improved accuracy of the improved AI model in subsequent attempts.

[0688] (Application Example 1)

[0689] 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".

[0690] In modern households, a lack of communication and deteriorating relationships between spouses are commonplace problems. To address these issues effectively, personalized advice tailored to each individual's personality and the nature of their concerns is required. However, traditional methods often only provide uniform advice. Furthermore, there are few systems that can evolve advice based on feedback, highlighting the need for technologies that can provide more individualized support.

[0691] 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.

[0692] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for analyzing the user's consultation content using speech recognition, and means for presenting advice visually and aurally. This makes it possible to provide advice tailored to the user's individual concerns through visual or auditory means, and to improve the quality of the advice by utilizing feedback from the user.

[0693] "Personality analysis means" refers to a device or method for acquiring a user's personality information based on personality theory.

[0694] "User's equipment" refers to terminals or devices used by the user to acquire or input information.

[0695] "Evaluation" refers to the feedback that users provide in response to advice, and this feedback concerns the effectiveness of the advice and areas for improvement.

[0696] "Speech recognition" is a technology that analyzes voice input from users as digital data.

[0697] "Providing advice through visual and auditory means" refers to the process of providing generated advice to the user via screen display or audio output.

[0698] "Means for receiving feedback" refers to a method or device for a server or system to receive user evaluations as data.

[0699] "Multiple psychological theories" refers to a group of theories that use different psychological frameworks and models to analyze patterns of personality and behavior.

[0700] The system for implementing this invention mainly consists of a server and user equipment. The server analyzes the user's personality information and consultation content using personality analysis means, speech recognition technology, and a generative AI model. Psychological theories such as MBTI and Big Five theory are applied to the personality analysis to accurately capture the user's personality pattern. In addition, the user's consultation content is converted into data by speech recognition and analyzed in detail.

[0701] Once data analysis on the server is complete, the generating AI model forms advice aimed at improving relationships. This advice is encrypted and then sent to the user's device. On the user's device, the advice can be presented visually or audibly through a touchscreen display or speaker. The user can accept the presented advice and put it into practice in their daily life.

[0702] User feedback is sent to the server as assessment of the effectiveness of the advice and areas for improvement. This feedback is incorporated into the AI ​​model's training and used to improve the accuracy of future advice generation. This cycle allows the system to regularly provide personalized support to individual users.

[0703] For example, if a user consults the system about the lack of communication between spouses recently, the system might suggest, "Why not plan a lunch date once a week?" The system then works by having the user implement this suggestion and provide feedback on the results, which helps improve the quality of future advice.

[0704] An example of a prompt message would be, "The user's personality type is INTJ, and they feel there is a lack of communication in their marriage. Please suggest specific actions to improve the situation." In this way, accurate and practical advice can be provided based on the user's individual needs.

[0705] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0706] Step 1:

[0707] The user uses a device to input their concerns and questions about their marital relationship via voice. The voice input is captured by the device via a microphone and converted into digital data. This data is then converted into text data by speech recognition software.

[0708] Step 2:

[0709] The terminal uses speech recognition software to acquire text data, which is then sent to the server. The server uses a generative AI model based on the received text data to generate a prompt message. This prompt message combines the user's specific personality information with the content of their inquiry.

[0710] Step 3:

[0711] The server uses personality analysis tools to analyze the personality information of pre-registered users. This data is analyzed based on MBTI and Big Five personality theories. Based on the analysis, the user's specific personality type is identified. The server then uses this to complete the prompt message.

[0712] Step 4:

[0713] The server uses a generative AI model to generate advice based on prompt messages. This model utilizes a large amount of training data to output advice that helps improve relationships. The generated advice is customized to the user's specific needs.

[0714] Step 5:

[0715] The server encrypts the generated advice and sends it to the terminal. The terminal decrypts the received data and presents it to the user visually and audibly. Specifically, it is displayed as text on the touchscreen display and played back as audio through the speaker.

[0716] Step 6:

[0717] Users try out the advice presented in their daily lives and input the results as feedback on their device. This feedback is sent to the server as evaluation data. The server uses this feedback information to readjust the generated AI model and improve the quality of the advice given next time.

[0718] 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.

[0719] The system according to the present invention aims to improve marital relationships by acquiring user personality information, analyzing consultation content, generating relationship improvement advice, and receiving feedback and learning from it. This system further incorporates an emotion engine that recognizes the user's emotions, thereby improving the accuracy of the advice.

[0720] As a specific implementation, the user first uses a terminal to input details about their current marital relationship. This information, along with personality information, is sent to the server. The server uses personality analysis tools to analyze the user's personality based on multiple psychological theories, such as MBTI and the Big Five personality theory. Simultaneously, an emotion engine recognizes the user's emotional state from the consultation content and incorporates this into the advice generation.

[0721] The server uses an AI algorithm that takes into account personality information and emotional state to generate relationship improvement advice best suited to the user's situation. For example, it can provide advice such as, "Currently, a stressful emotional state has been detected, so we suggest a relaxing collaborative activity." This advice is presented on the user's device in a visually understandable format.

[0722] Users take action based on the advice provided and provide feedback on the results and their feelings at the time. This feedback is also sent to the server through the emotion engine, and the server learns from it. Through this process, the system improves the accuracy of its advice and can provide more effective advice in future consultations.

[0723] This series of processes allows users to gain a deep understanding of marital relationship problems and obtain realistic and actionable solutions without requiring specialized knowledge. In other words, this system provides users with an easy and effective means of resolving their issues, and this is an embodiment of the present invention.

[0724] The following describes the processing flow.

[0725] Step 1:

[0726] Users use their devices to input their concerns and questions regarding their marital relationship. They are encouraged to honestly describe their current emotional state during the input process. If a user's personality information is not yet registered, they will be given the option to input it by answering questions.

[0727] Step 2:

[0728] The terminal encrypts the user's entered consultation content and personality information and securely transmits it to the server. Appropriate management measures are taken beforehand to protect privacy.

[0729] Step 3:

[0730] The server decodes the received data and uses personality analysis tools to analyze the user's personality information based on multiple psychological theories. This analysis identifies the user's personality pattern.

[0731] Step 4:

[0732] The server activates an emotion engine to analyze the user's current emotional state based on their consultation content. This analysis utilizes natural language processing techniques and references to an emotion dictionary.

[0733] Step 5:

[0734] The server uses an AI algorithm to generate relationship improvement advice based on the analyzed personality patterns and emotional states. The advice is guaranteed to be particularly considerate of the user's emotional state.

[0735] Step 6:

[0736] The server re-encrypts the generated advice and sends it to the user's device, ensuring privacy while providing advice.

[0737] Step 7:

[0738] The terminal decodes the advice received from the server and displays it in a visual interface that is easy for the user to understand. The user then considers whether or not to act on the advice.

[0739] Step 8:

[0740] Users implement the provided advice and record feedback on their device regarding the results and their feelings during the implementation process.

[0741] Step 9:

[0742] The device encrypts user feedback and associated sentiment data and sends it to the server. This feedback serves as important learning data for generating advice in the future.

[0743] Step 10:

[0744] The server analyzes the received feedback and adjusts the AI ​​algorithm and emotion engine to improve the accuracy of future advice generation. This iterative learning improves the overall system performance.

[0745] (Example 2)

[0746] 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".

[0747] In modern society, relationships between spouses and partners are important, but obtaining effective advice on improving them is often difficult. In particular, there is a lack of personalized advice tailored to individual personalities and emotional states, which can lead to further deterioration of relationships. This invention aims to solve these problems and provide a means to effectively promote relationship improvement.

[0748] 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.

[0749] In this invention, the server includes means for acquiring user personality data based on psychological theories using personality evaluation means, means for generating guidelines aimed at improving relationships based on the content of the user's consultation, and means for detecting the user's emotional state using an emotion recognition device and reflecting this in the generation of guidelines. This makes it possible to provide users with personalized relationship improvement advice.

[0750] A "personality assessment tool" is a function that analyzes and acquires user personality data based on psychological theories.

[0751] A "psychological theory" is a theoretical framework used to understand an individual's personality and behavioral patterns, and generally consists of multiple theories.

[0752] "User" refers to an individual who uses this system and is the entity that provides their personality data and consultation content.

[0753] "Personality data" refers to data that quantifies or classifies a user's personality, and is generated based on psychological theories.

[0754] "Consultation content" refers to specific problems or questions related to relationships that users enter into this system.

[0755] "Guideline generation" is the process of creating specific advice or suggestions to provide to users with the aim of improving relationships.

[0756] An "emotion recognition device" is a function that identifies the emotional state of a user based on the content of their consultation and reflects it in the system's processes.

[0757] "Opinions" refer to feedback provided by users in response to advice, and this information is used to help the system learn and improve.

[0758] This system aims to improve relationships between spouses and partners by providing users with personalized advice. The system consists of a personality assessment tool, an emotion recognition device, and a guideline generation device. This allows users to easily receive practical advice for improving their relationships.

[0759] Users first input their personality data and consultation details using a device such as a smartphone, tablet, or computer. This information is securely transmitted to a server. The server runs a program based on psychological theories and analyzes the personality data through personality assessment methods. In this process, MBTI and Big Five personality theories are used.

[0760] Subsequently, the server analyzes the consultation content using an emotion recognition device and identifies the user's emotional state. This information is a crucial element in the guideline generation process by the generative AI model. The server considers personality data and emotional state together to generate the most appropriate guideline for the user's situation.

[0761] The generated guidelines are sent to the user's device in a visually easy-to-understand format. For example, if a stressful emotional state is detected, the server can offer specific advice such as, "We suggest spending some time together to relax."

[0762] Users take action based on the advice and input feedback about the results and their feelings via their device. The server receives this feedback and uses it to improve the overall accuracy of the system. Through this iterative learning process, even more accurate advice will be provided during subsequent consultations.

[0763] As a concrete example, a prompt might look like this: "Generate advice for improving the marital relationship. The user's personality type is 'ENFJ' according to the MBTI, and their current emotional state is 'anxious'. Please provide specific and appropriate advice." This prompt serves as a guide for the generating AI model to output advice tailored to the individual situation.

[0764] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0765] Step 1:

[0766] Users use their devices to input their personality data and specific questions about their marital relationship. For example, "Recently, I've been talking less with my partner." This information includes personality patterns, so detailed personality data is entered.

[0767] Step 2:

[0768] The terminal sends the entered information and personality data to the server. The data is encrypted and securely transferred to the server. The input here consists of personality data and consultation details, while the output is encrypted data.

[0769] Step 3:

[0770] The server analyzes the received data and uses personality assessment tools to analyze the personality data. For example, it identifies MBTI types based on psychological theories. The input is encrypted data, and the output is a classified personality pattern.

[0771] Step 4:

[0772] The server uses an emotion recognition device to identify the user's emotional state from the consultation content. For example, it uses natural language processing to identify emotions such as "anxiety" and "stress." The input is text information of the consultation content, and the output is the identified emotional state.

[0773] Step 5:

[0774] The server uses the system's AI model to generate appropriate relationship improvement guidelines based on personality patterns and emotional states. The input here is personality patterns and emotional states, and the output is the guidelines generated through the AI ​​model. For example, one might suggest "a relaxing collaborative activity."

[0775] Step 6:

[0776] The terminal presents the generated guidelines to the user in a visually easy-to-understand format. For example, it may display them as a list or text message. The input from the server is the guidelines data, and the output is the display to the user.

[0777] Step 7:

[0778] Users take action based on the provided guidelines and input feedback on the results and their feelings into the device. This input serves as a record of their opinions and the effects of the guidelines.

[0779] Step 8:

[0780] The device sends user feedback to the server. The transmitted data includes practical results and changes in emotions. The output is feedback data sent to the server.

[0781] Step 9:

[0782] The server analyzes the feedback data and learns to improve the overall accuracy of the system. This improves the accuracy of advice generation in subsequent sessions. The input is the feedback data, and the output is the improved AI model.

[0783] (Application Example 2)

[0784] 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".

[0785] In caregiving settings, poor communication between caregivers and those receiving care, and an inability to properly understand the emotional state of those receiving care, can lead to a deterioration of relationships and inappropriate care. Therefore, it is crucial for caregivers to understand the emotional state of those receiving care and to find the most appropriate communication methods based on that state.

[0786] 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.

[0787] In this invention, the server includes means for acquiring user personality information based on personality theory using personality analysis means, means for recognizing emotional states from image and audio data using emotion analysis means, and means for reflecting the recognized emotional states in advice generation. This makes it possible for caregivers to understand the emotional state of those being cared for in real time and to provide optimal communication methods and relationship improvement measures based on that understanding.

[0788] A "personality analysis method" is a technique for obtaining a user's personality information based on personality theory.

[0789] "Advice generation" is the process of creating advice aimed at improving relationships, based on the user's consultation content and emotional state.

[0790] A "device" is a device used to present generated advice to the user.

[0791] "Feedback" refers to information about the results of user actions and their emotions at the time, and is used to improve the accuracy of the system.

[0792] "Emotional analysis methods" refer to technologies that analyze image and audio data to recognize the emotional state of a user.

[0793] This invention is a system implemented to improve the relationship between caregivers and those receiving care in the field of elderly care. The system utilizes devices such as smartphones and tablets. A server processes data transmitted from users through these devices and performs necessary analysis.

[0794] The server uses TensorFlow, an AI library for the Python programming language, to analyze personality information and generate advice. Personality information is obtained using personality analysis tools and based on psychological theories. Furthermore, it uses emotion analysis engines such as Microsoft Azure Face API and Google Cloud Vision to recognize the emotional state of the person being cared for from image and audio data.

[0795] The generated advice is visually displayed on the terminal, allowing caregivers to use it to improve communication with those they care for. The system receives feedback provided by caregivers and processes it on the server. Based on this feedback, the system iteratively improves the accuracy of its advice generation.

[0796] For example, if the server detects, based on its sentiment analysis, that the person being cared for has been feeling down recently, it will generate a prompt message such as, "Sentiment analysis indicates that the person being cared for has been feeling down recently. What activities would improve their mood?" This allows the caregiver to suggest appropriate activities.

[0797] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0798] Step 1:

[0799] The user uses a terminal to input personality information and consultation details about the person being cared for. The entered data is sent from the terminal to the server. The server receives this data and prepares to begin the personality analysis.

[0800] Step 2:

[0801] The server uses personality analysis tools to identify personality patterns based on the received personality information and multiple psychological theories. At this stage, the results of the personality pattern analysis are output.

[0802] Step 3:

[0803] The server uses emotion analysis tools, taking image and audio data from the device as input. It recognizes the emotional state using Microsoft Azure Face API or Google Cloud Vision. The recognized emotional state is output and used to generate advice for the next step.

[0804] Step 4:

[0805] The server utilizes a generative AI model to generate optimal advice based on personality analysis results and emotional states. In this process, the AI ​​suggests activities and communication methods that are considered effective for improving relationships.

[0806] Step 5:

[0807] The generated advice is output to the terminal and presented to the user. The terminal displays this advice in a visually easy-to-understand format, enabling the user to take action based on it.

[0808] Step 6:

[0809] The user acts based on the advice provided and inputs the result as feedback on their device. This feedback is then sent back to the server.

[0810] Step 7:

[0811] The server receives feedback and uses it to learn and improve the system's accuracy. The generative AI model is then fine-tuned to provide more accurate advice during the next consultation.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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."

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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 as being incorporated by reference.

[0833] The following is further disclosed regarding the embodiments described above.

[0834] (Claim 1)

[0835] A means for acquiring user personality information based on personality theory using personality analysis methods,

[0836] A means of generating advice aimed at improving relationships based on the user's consultation content,

[0837] A means of displaying the generated advice on the user's device,

[0838] A means of receiving user feedback and reflecting it in the analysis results,

[0839] A means to improve the accuracy of advice generation using the analysis results,

[0840] A system that includes this.

[0841] (Claim 2)

[0842] The system according to claim 1, wherein the user's personality information includes personality patterns based on multiple psychological theories.

[0843] (Claim 3)

[0844] The system according to claim 1, which iteratively learns using user feedback to improve the accuracy of the system.

[0845] "Example 1"

[0846] (Claim 1)

[0847] A means of encrypting and securely transmitting personality data,

[0848] A means of analyzing user personality information on a server based on personality theory,

[0849] A means of creating suggestions for improving relationships based on the user's consultation content using a generative AI model,

[0850] A means of encrypting the generated proposal, sending it to the user's display device, and visually displaying it,

[0851] A means of receiving user evaluations and applying them to the analysis results on the server,

[0852] A means to improve the accuracy of proposal generation using these analysis results,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] The system according to claim 1, wherein the user's personality information includes personality patterns based on multiple psychological frameworks.

[0856] (Claim 3)

[0857] The system according to claim 1, which iteratively learns using user reputation to improve the accuracy of the system.

[0858] "Application Example 1"

[0859] (Claim 1)

[0860] A means of obtaining user personality information based on personality theory using personality analysis methods,

[0861] A means of generating advice aimed at improving relationships based on the content of the user's consultation,

[0862] A means of displaying the generated advice on the user's device,

[0863] A means of receiving user feedback and reflecting it in the analysis results,

[0864] A means to improve the accuracy of advice generation using the analysis results,

[0865] A means of analyzing the content of user consultations using speech recognition,

[0866] Means of presenting advice through visual and auditory means,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, wherein the user's personality information includes personality patterns based on multiple psychological theories.

[0870] (Claim 3)

[0871] The system according to claim 1, which improves the accuracy of the system by iteratively learning using evaluations from users.

[0872] "Example 2 of combining an emotion engine"

[0873] (Claim 1)

[0874] A means of acquiring user personality data based on psychological theories using personality assessment methods,

[0875] A means of generating guidelines aimed at improving relationships based on the content of user consultations,

[0876] A means of detecting the user's emotional state using an emotion recognition device and reflecting it in the generation of guidelines,

[0877] A means of displaying the generated guidelines on the user's information terminal,

[0878] A means of receiving feedback from users and reflecting it in the analysis results,

[0879] A means to improve the accuracy of guideline generation using the analysis results,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, wherein the user's personality data includes personality classifications based on multiple psychological theories.

[0883] (Claim 3)

[0884] The system according to claim 1, which improves the accuracy of the system by iteratively learning using feedback from users.

[0885] "Application example 2 when combining with an emotional engine"

[0886] (Claim 1)

[0887] A means of obtaining user personality information based on personality theory using personality analysis methods,

[0888] A means of generating advice aimed at improving relationships based on the content of the user's consultation,

[0889] A means of presenting the generated advice to the user's device,

[0890] A means of receiving feedback from users and reflecting it in the analysis results,

[0891] A means to improve the accuracy of advice generation using the analysis results,

[0892] A means of recognizing emotional states from image and audio data using emotion analysis methods,

[0893] A means of reflecting the recognized emotional state in the generation of advice,

[0894] A system that includes this.

[0895] (Claim 2)

[0896] The system according to claim 1, wherein the user's personality information includes personality patterns based on multiple psychological theories.

[0897] (Claim 3)

[0898] The system according to claim 1, which improves the accuracy of the system by iteratively learning using feedback from users. [Explanation of Symbols]

[0899] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining user personality information based on personality theory using personality analysis methods, A means of generating advice aimed at improving relationships based on the content of the user's consultation, A means of displaying the generated advice on the user's device, A means of receiving user feedback and reflecting it in the analysis results, A means to improve the accuracy of advice generation using the analysis results, A means of analyzing the content of user consultations using speech recognition, Means of presenting advice through visual and auditory means, A system that includes this.

2. The system according to claim 1, wherein the user's personality information includes personality patterns based on multiple psychological theories.

3. The system according to claim 1, which improves the accuracy of the system by iteratively learning using evaluations from users.

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