System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving negative sentiment data entered by a user using an electronic device; means for converting the received negative sentiment data into positive interpretation data with a conversion device; means for analyzing user trait data and generating a user positive trait; and means for displaying the positive interpretation data and the user positive trait to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many people cite interpersonal stress and friction as reasons for changing jobs. However, it is difficult to change other people or past circumstances, and this only increases the mental burden on individuals. To solve this problem and reduce users' mental burden, an effective method is needed to transform negative emotions into positive ones and help them recognize their own positive aspects. [Means for solving the problem]

[0005] The present invention provides a system including a means for receiving negative emotional data input by a user using an electronic device, a means for converting the received negative emotional data into positive interpretation data using a conversion device, a means for analyzing the user's characteristic data and generating positive characteristics for the user, and a means for displaying the positive interpretation data and the user's positive characteristics to the user. The system further includes a means for transmitting the input negative emotional data to a server and having the server generate positive interpretation data and positive characteristics for the user, and a means for generating the user's positive characteristics based on user profile data from multiple databases. These means enable users to convert negative emotions into positive ones and recognize their own positive aspects, thereby reducing mental stress and maintaining positive feelings.

[0006] An "electronic device" is a device such as a computer, smartphone, or tablet that allows a user to manipulate input data.

[0007] "Negative emotion data" is information entered by the user that expresses negative emotions such as dissatisfaction, stress, and disgust.

[0008] "Means for receiving" refers to the equipment or functionality that refers to the network communication technology or protocol for transmitting data from an electronic device to a server and receiving the data.

[0009] "Conversion device" refers to an artificial intelligence (AI) model or algorithm that converts input negative emotional data into positive interpretation data.

[0010] "Positive interpretation data" is information that has been converted from negative emotional data into a positive perspective or interpretation.

[0011] "Characteristic data" refers to information about a user's personality, behavioral tendencies, and characteristics based on past data.

[0012] "Means for analysis" refers to data processing methods and algorithms for analyzing characteristic data and extracting users' features and strengths.

[0013] "User's positive characteristics" are characteristic data that include the user's own good points, strengths, and advantages.

[0014] "Means for displaying" refers to a display or user interface for presenting positive interpretation data and the user's positive characteristics to the user.

[0015] A "server" is a computer system that processes, stores, and transmits data over a network.

[0016] "Database" means an information management system for structuring and storing user profile data and other information.

[0017] "User profile data" is a collection of data including a user's registration information, history, behavioral trends, etc. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention is a system that receives negative emotional data input by a user using an electronic device, converts it into positive emotions, and helps the user recognize their positive side, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, and a conversion device.

[0040] User Input Processing

[0041] The user inputs his or her negative emotions into the input interface of the electronic device, for example, "I don't like that colleague because he or she is always late and doesn't help me with my work."

[0042] Processing data transmission

[0043] The device transmits the input negative emotion data to the server, preferably using a secure communication protocol.

[0044] Transforming negative emotions into positive ones

[0045] The server analyzes the received negative emotional data and converts it into positive interpretation data using a conversion device, i.e., a generative AI model. For example, the positive interpretation might be, "That colleague can do things at their own pace and is independent."

[0046] Analyzing the positive aspects of users

[0047] The server then analyzes the user's positive attributes based on the user's characteristic data, including user profile data and past behavioral data. As a result of the analysis, it generates compliments such as "You are very honest" or "You are responsible and value your time."

[0048] Displaying the results

[0049] The server sends the generated positive interpretation data and the user's good points to the device, which then displays the received data to the user. This allows the user to see how their negative emotions have been transformed into positive ones, and further reduces the burden on their mind by reaffirming their positive aspects.

[0050] Specific examples

[0051] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[0052] This system allows users to reframe negative emotions that arise in their daily lives in a positive light, rediscovering their own positive aspects and reducing mental stress.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] An interface is displayed that allows a user to input emotional data using an electronic device. For example, the user inputs negative emotional data such as "My colleague is late, so I have more work to do, which is bothering me."

[0056] Step 2:

[0057] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[0058] Step 3:

[0059] The server receives the negative emotion data and formats it into text for analysis.

[0060] Step 4:

[0061] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[0062] Step 5:

[0063] The server analyzes the user's characteristic data. The analysis uses the user's registered profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "high problem-solving ability."

[0064] Step 6:

[0065] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, also using the HTTPS protocol.

[0066] Step 7:

[0067] The terminal receives the data from the server and converts it into a displayable format.

[0068] Step 8:

[0069] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0070] Step 9:

[0071] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[0072] Example 1

[0073] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0074] In modern society, users often experience various negative emotions in their daily lives and work. These negative emotions can have a negative impact on users' mental health, as well as on their productivity and interpersonal relationships. Conventional technologies lack a means to effectively transform these negative emotions into positive ones and reduce the user's mental burden. The present invention aims to solve these problems by providing a system that transforms negative emotions into positive ones and reduces the user's mental burden by helping them recognize their positive aspects.

[0075] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0076] In this invention, the server includes means for receiving negative emotional data input by a user using an electronic device, means for transmitting the received negative emotional data to the server using a communication protocol, means for the server to convert the negative emotional data into positive interpretation data using a generative AI model, means for the server to generate positive characteristics of the user based on the user's profile data, and means for displaying the positive interpretation data and the user's positive characteristics to the user. This makes it possible to effectively convert negative emotions into positive ones and reduce the user's mental burden by helping them recognize their positive aspects.

[0077] "Negative emotion data" is data entered in text format that describes negative emotions such as dissatisfaction, stress, sadness, etc. that the user feels.

[0078] "Electronic devices" refer to devices such as smartphones, tablets, and personal computers that can be operated by the user.

[0079] A "communication protocol" is a set of rules used to ensure security and reliability when sending and receiving data between electronic devices and servers, and one example is HTTPS.

[0080] A "server" is a computer system for processing received negative emotional data and generating positive interpretation data.

[0081] A "generative AI model" is an artificial intelligence model that learns from large amounts of data to generate text, and plays a role in converting negative emotional data into positive ones.

[0082] "Positive interpretation data" is text data with positive and affirmative content generated by a generative AI model based on negative emotional data.

[0083] "User profile data" refers to a group of data in a database that includes characteristic information and past behavioral history about individual users.

[0084] "User's positive characteristics" is data that indicates the user's advantages and strengths, extracted based on the user's profile data.

[0085] The "display means" is a mechanism for visually presenting the positive interpretation data and the user's positive characteristics to the user on the screen of an electronic device.

[0086] This system receives negative emotional data input by a user using an electronic device, converts it into positive emotion, and helps the user recognize their positive side, thereby reducing their mental burden. The system is composed of multiple elements, including an electronic device, a server, and a generative AI model.

[0087] User Input Processing

[0088] The user inputs their negative emotions into the input interface of the electronic device. The input data is stored in text format. For example, a sentence such as "My colleague is late, so I have more work to do, which is a problem" is input. The input field includes a text field and a submit button.

[0089] Processing data transmission

[0090] The device sends the entered negative emotion data to the server. At this time, the data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is clicked, the device encrypts the data and sends a POST request to the server using the HTTPS protocol.

[0091] Transforming negative emotions into positive ones

[0092] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model (e.g., GPT-3). For example, a negative input such as "My colleague is always late, which causes me to have more work" can be converted into a positive interpretation such as "My colleague is able to work at his own pace and is good at managing his time."

[0093] Analyzing the positive aspects of users

[0094] The server then analyzes the user's positive aspects based on their profile data and past behavioral data. For example, it generates compliments such as, "You are a good problem-solver and a great supporter of the team." The server retrieves the user's characteristic information from the user profile database and sends prompts to the generative AI model.

[0095] Displaying the results

[0096] The server sends the generated positive interpretation data and information about the user's positive characteristics to the device, which then displays the received data to the user, allowing the user to see how their negative emotions have been transformed into positive ones and to rediscover their own positive aspects.

[0097] Specific examples

[0098] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[0099] Prompt Sentence Examples

[0100] "Generate positive interpretations of specific emotions and compliments based on the user's characteristics."

[0101] In this way, the present invention provides a concrete means for users to reframe negative emotions that arise in their daily lives in a positive light, rediscover their own positive aspects, and reduce mental burden.

[0102] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0103] Step 1:

[0104] The user inputs negative emotional data into the input interface of an electronic device. The input data is stored in text format. Specifically, the user enters "My colleague is late, so I have more work to do, which is a problem" into the text field and presses the send button. This text data is the input. The output is the input text data itself.

[0105] Step 2:

[0106] The terminal sends the entered negative emotion data to the server. The data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is pressed, the terminal encrypts the text data and sends it to the server as a POST request. The input is the text data entered by the user, and the output is the encrypted text data.

[0107] Step 3:

[0108] The server receives the negative emotion data sent. After receiving it, it analyzes the data using a generative AI model (e.g., GPT-3) and converts it into positive interpretation data. Specifically, the server receives the text "My colleague is always late, which is bothering me because it means more work," and sends it to the generative AI model along with the prompt, "Generate a positive interpretation for the specific emotion and a compliment based on the user's characteristics." The generative AI model analyzes it and outputs a positive interpretation, for example, "My colleague is able to work at his own pace and is clever about how he uses his time." The input is encrypted negative text data, and the output is text data converted into a positive one.

[0109] Step 4:

[0110] The server then generates positive traits for the user based on the user's profile data and past behavioral data. The server retrieves trait information from the user profile database and sends a prompt to the generative AI model: "Generate a compliment based on the user's traits." Specifically, the server generates a compliment such as, "You are a good problem-solver and a supportive member of the team." The input is the user's profile data, and the output is text data of the compliment.

[0111] Step 5:

[0112] The server sends the generated positive interpretation data and the user's positive characteristics information to the terminal. The terminal receives this data and displays it to the user, for example, as a pop-up message or on a dashboard. The input is the positive interpretation data and compliment text data sent from the server, and the output is a visual display of this to the user.

[0113] Through the above processing steps, this system can convert the user's negative emotions into positive ones and reduce the mental burden by helping the user to recognize their positive side.

[0114] (Application example 1)

[0115] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0116] In modern society, people often experience many negative emotions in their daily lives, which can become a mental burden. Furthermore, it is difficult to reframe negative emotions in a positive light, and there are limited means to improve self-esteem. Conventional systems face challenges in that they are unable to adequately alleviate negative emotions or suggest positive interpretations. Furthermore, they do not provide appropriate feedback to help users recognize their own positive aspects. Therefore, there is a need for a system that can effectively transform the negative emotions users experience in their daily lives into positive ones and improve self-esteem.

[0117] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0118] In this invention, the server includes means for receiving negative emotion data input by a user using an electronic device, means for converting the received negative emotion data into positive interpretation data using a conversion device, means for analyzing the user's characteristic data and generating positive characteristics for the user, means for displaying the positive interpretation data and the user's positive characteristics to the user, means for transmitting the generated data to the user's terminal via a secure communication protocol, and means for displaying a correlation between the negative emotion data input by the user and the converted positive interpretation data. This converts the negative emotion input by the user into a positive one and helps the user recognize their positive aspects, thereby reducing mental burden and improving self-esteem.

[0119] An "electronic device" is a device that allows a user to input or view information, and examples include smartphones and tablets.

[0120] "Negative emotion data" is information that expresses negative emotions such as discomfort or dissatisfaction felt by the user.

[0121] A "conversion device" is a system or module for converting input negative emotional data into positive interpretation data.

[0122] "Positive interpretation data" is information that reinterprets negative emotional data in a favorable or positive way.

[0123] "Characteristic data" is information relating to the user's personality and behavioral characteristics, and includes profile data and behavioral history.

[0124] "Positive characteristics" are information that indicates the user's good points or outstanding characteristics.

[0125] "Display means" refers to an interface for visually presenting information to a user, and includes a screen, a display, and the like.

[0126] A "secure communication protocol" is a communication standard for securely sending and receiving data, and examples include HTTPS and SSL / TLS.

[0127] A "generative AI model" is an algorithm or system that uses artificial intelligence to perform a specific task or data transformation.

[0128] A "prompt sentence" is an instruction or question sentence input to a generative AI model.

[0129] This invention is a system that converts a user's negative emotions into positive ones and reduces mental burden by helping the user recognize their positive side. This system is composed of multiple elements, including electronic devices, servers, and generative AI models.

[0130] Hardware and software used

[0131] Hardware:

[0132] Smartphone

[0133] server

[0134] software:

[0135] Application: React Native (front-end)

[0136] Server framework: Flask

[0137] Generative AI model: GPT-4 (OpenAI)

[0138] Communication protocol: HTTPS

[0139] Database: PostgreSQL

[0140] Operational Overview

[0141] 1. Receiving emotional input

[0142] A user uses a smartphone as an electronic device and inputs negative emotional data into the emotion input interface, for example, by entering an emotion such as "I failed at work. I no longer have confidence" into a text field.

[0143] 2. Data transmission

[0144] The input negative emotion data is sent to the server via a secure communication protocol (HTTPS), and the server receives this data securely.

[0145] 3. Transforming negative emotions into positive ones

[0146] The server analyzes the received negative emotion data using a generative AI model (GPT-4), which converts negative emotions into positive interpretation data based on pre-trained prompts.

[0147] Example: A negative emotion, "I failed at work. I no longer have confidence in myself," can be transformed into a positive interpretation, "This failure is an opportunity to learn a lot and rebuild my confidence."

[0148] 4. Analyzing the positive aspects of users

[0149] The server analyzes the user's characteristic data, which is based on the user's profile data and past behavior data, and generates positive attributes and traits for the user based on this data.

[0150] For example, a compliment such as "You are a great problem solver and a great support for the team" may be generated.

[0151] 5. Displaying the results

[0152] The server sends the generated positive interpretation data and the user's positive characteristics to the user's device, which receives it and displays it on the screen. The user can see how their negative emotions have been transformed into positive ones and their own positive aspects.

[0153] Prompt Sentence Examples

[0154] Negative Emotion: "I failed at work. I no longer have confidence."

[0155] Positive Transformation: "Failure is an opportunity to learn a lot and rebuild your confidence."

[0156] In this way, this invention effectively transforms the negative emotions that users have in their daily lives into positive ones, and by making users recognize their own good sides, it is possible to reduce mental burden and improve self-esteem.

[0157] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0158] Step 1:

[0159] This is a step in which the user inputs negative emotion data using an electronic device (smartphone).

[0160] Input: The user enters emotion data in the text field: "I failed at work. I no longer have confidence."

[0161] Output: The input emotion data is received by the terminal.

[0162] Specific operation: The user enters emotions in text format into the application's input interface and presses the "Send" button.

[0163] Step 2:

[0164] This is a step in which the terminal transmits the received negative emotion data to the server.

[0165] Input: User-entered negative sentiment data.

[0166] Output: Negative sentiment data sent to the server.

[0167] Specific operation: The device sends the input emotion data to the server using a secure communication protocol (HTTPS).

[0168] Step 3:

[0169] This is the step where the server analyzes the negative emotional data received using a generative AI model to generate positive interpretation data.

[0170] Input: Negative emotion data received by the server.

[0171] Output: Generated positive interpretation data.

[0172] Specific operation: The server inputs the received emotional data into a generative AI model (e.g., GPT-4) and generates positive interpretation data such as, "This is an opportunity to learn a lot from your failure and rebuild your confidence."

[0173] Step 4:

[0174] The server analyzes the user's characteristic data and generates positive characteristics for the user.

[0175] Input: User characteristic data stored on the server (profile data and past behavioral data).

[0176] Output: Generated positive trait data of the user.

[0177] Specific operation: The server retrieves the user's characteristic data from the database, analyzes it, and generates positive characteristic data such as, "You have excellent problem-solving skills and are a supportive member of the team."

[0178] Step 5:

[0179] The server transmits the generated positive interpretation data and the user's positive characteristic data to the user's terminal.

[0180] Input: Generated positive interpretation data and user positive characteristic data.

[0181] Output: Data sent to the user's device.

[0182] Specific operation: The server transmits the positive interpretation data and the user's positive characteristic data to the user's terminal using a secure communication protocol (HTTPS).

[0183] Step 6:

[0184] This is the step in which the user's terminal displays the received data to the user.

[0185] Input: Positive interpretation data received from the server and positive characteristic data of the user.

[0186] Output: The data that is displayed to the user.

[0187] Specific operation: The positive interpretation data received by the terminal and the user's positive characteristic data are displayed on the application screen and presented to the user as feedback.

[0188] Step 7:

[0189] This is a step of displaying the association between the negative emotion data input by the user and the converted positive interpretation data.

[0190] Input: Negative emotion data and corresponding positive interpretation data.

[0191] Output: A screen showing the correlation.

[0192] Specific operation: The device displays negative emotion data and positive interpretation data on the screen in contrast, clearly showing the user how negative emotions have been transformed into positive ones.

[0193] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0194] This system receives negative emotional data input by a user using an electronic device, converts it into positive interpretation data, and helps the user recognize their positive aspects, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, a conversion device (generative AI model), and an emotion engine.

[0195] User Input Processing

[0196] A user inputs his / her negative emotions through an input interface of an electronic device or through input to an emotion engine. Negative emotions can be input as text into the interface of the electronic device, or the emotion engine can analyze multimodal data such as voice, facial expressions, and gestures to recognize negative emotion data. For example, a user can input "I'm having trouble because my colleague is late, which means more work for me," and the emotion engine can recognize the user's stress from their voice and facial expressions.

[0197] Processing data transmission

[0198] The device sends the input negative emotion data to the server, using a secure communication protocol (e.g., HTTPS) to ensure the safety of the data.

[0199] Transforming negative emotions into positive ones

[0200] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[0201] Analyzing the positive aspects of users

[0202] The server then analyzes the user's positive aspects based on the user's characteristic data. This analysis utilizes user profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "excellent problem-solving skills."

[0203] Displaying the results

[0204] The server transmits the generated positive interpretation data and the user's positive aspects to the device using a secure protocol.

[0205] The device then displays the received data to the user, such as a message like, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0206] Specific examples

[0207] For example, if a user types in text, "My colleague is always late, which is causing me a lot of work," that data is sent from the device to the server. Alternatively, the emotion engine can recognize the user's stress from their voice and facial expressions and send the data in a similar manner. The server then uses a generative AI model to convert this negative emotion data into, "My colleague is able to work at his or her own pace and is good at time management." Furthermore, it can generate compliments from the user's characteristic data, such as, "You are a good problem-solver and a supportive member of the team." When these results are displayed on the device, the user can confirm the positive interpretation and reaffirm their own positive aspects, thereby reducing their mental burden.

[0208] This embodiment allows users to transform negative emotions that arise in their daily lives into positive ones and to rediscover their positive aspects, thereby reducing further mental burdens. This process is an effective way to support the user's mental health.

[0209] The processing flow will be explained below.

[0210] Step 1:

[0211] A user accesses the interface of an electronic device, and either the user inputs negative emotion data in text, or the emotion engine recognizes negative emotions from the user's voice, facial expressions, gestures, etc.

[0212] Step 2:

[0213] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[0214] Step 3:

[0215] The server analyzes the received negative emotion data and formats it into text.

[0216] Step 4:

[0217] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data, for example, converting "My colleague is always late, which causes me to have more work to do" into "My colleague works at his own pace and is good at time management."

[0218] Step 5:

[0219] The server analyzes the user's characteristic data, using user profile data and past interaction data to extract the user's strengths and positive characteristics.

[0220] Step 6:

[0221] The server generates compliments based on the extracted positive characteristics of the user. For example, it recognizes user characteristics such as "valuing time" and "good problem-solving skills" and generates a compliment such as "You have good problem-solving skills and are a great support for the team."

[0222] Step 7:

[0223] The server transmits the generated positive interpretation data and the user's positive characteristics to the terminal using a secure protocol.

[0224] Step 8:

[0225] The terminal receives the data from the server and converts it into a displayable format.

[0226] Step 9:

[0227] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0228] Step 10:

[0229] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[0230] Example 2

[0231] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0232] In modern living environments, users are often exposed to negative emotions on a daily basis, which can easily increase their mental burden. However, it is not easy to deal with these negative emotions on one's own, and they often cause stress and anxiety. To address this issue, a system is needed that can reduce mental burden by helping users reframe negative emotions in a positive way.

[0233] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0234] In this invention, the server includes means for receiving negative emotion data input by a user using a communication terminal, means for analyzing the received negative emotion data and generating positive interpretation data using a generative AI model, and means for generating positive characteristics of the user based on the user's profile data and past interaction data. This allows the user to convert negative emotions into positive ones and re-identify them, thereby reducing mental burden.

[0235] A "communication terminal" is an electronic device that a user uses to input and transmit negative emotional data, and examples include smartphones and personal computers.

[0236] "Negative emotion data" is data that expresses negative emotions felt by the user, and is input in the form of text, voice, facial expressions, gestures, or the like.

[0237] A "secure communication protocol" is a set of rules for ensuring the safety of data communication, such as HTTPS.

[0238] "Server" means a computer system for analyzing received negative emotional data and generating positive interpretation data and positive characteristics of the user using a generative AI model.

[0239] A "generative AI model" is an artificial intelligence model used to convert negative emotional data into positive interpretation data, and examples include models that use natural language processing techniques.

[0240] "Profile data" is a database containing attribute information and past interaction data about a user, and is data that is referenced to generate positive characteristics of the user.

[0241] "Positive interpretation data" is data that shows a positive interpretation converted from negative emotional data by a generative AI model.

[0242] "Positive traits" are traits that show the positive aspects of a user and are generated based on the user's profile data and past interaction data.

[0243] The present invention is a system that receives negative emotional data input by a user using a communication terminal, converts it into positive interpretation data, and further generates and displays positive characteristics based on the user's characteristic data. The system of the present invention aims to convert the negative emotional data input by the user into positive data, thereby reducing the user's mental burden.

[0244] Hardware and Software Configuration

[0245] This system consists of elements such as communication terminals, servers, generative AI models, emotion engines, and databases.

[0246] communication terminal

[0247] Users input negative emotions using a communication device (e.g., smartphone or personal computer). A dedicated application or web form is installed on the communication device, and users use this to input emotions using text, voice, facial expressions, etc. The emotion engine analyzes the emotion data using voice recognition software (e.g., Google speech-to-text API) and facial expression recognition software (e.g., Microsoft Azure Face API).

[0248] server

[0249] The server receives the negative emotional data sent from the communication device. The received data is transferred using a secure communication protocol (e.g., HTTPS). The server then uses a generative AI model (e.g., OpenAI GPT-3) to convert the negative emotional data into positive interpretation data. The server then references a database that stores the user's profile data and past interaction data to extract and generate positive characteristics for the user.

[0250] Specific examples

[0251] For example, if a user uses a dedicated application to input text such as "My colleague is late, which is causing me a lot of work," the data is sent from the communication device to the server. Negative emotion data input through voice input or facial recognition is also processed in the same way.

[0252] The server sends the received data to the generative AI model as a prompt. For example, the user might input, "When a user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way." The generative AI model generates positive interpretation data, such as, "My colleague works at his own pace and is good at time management."

[0253] Next, the server checks the database for the user's characteristic of "valuing time" and generates a compliment such as "You have excellent problem-solving skills and are a great support for the team." The server then sends the generated positive interpretation data and the compliment to the communication terminal, which then displays it to the user.

[0254] This allows the user to convert the negative emotions they input into positive interpretations, and by rediscovering their positive aspects, they can reduce their mental burden. Through this process, the present invention provides an effective means of supporting the user's mental health.

[0255] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0256] Program processing flow

[0257] Step 1: User Input

[0258] Users input negative emotional data using a communication device. Specifically, they can input it as text through a dedicated application or web form displayed on the device. They can also input facial expressions and gestures using voice input or a camera.

[0259] Input: Negative emotion text, audio data, facial expression data

[0260] Output: Negative sentiment data (text format)

[0261] Examples of specific actions:

[0262] A user opens the app and types in the text, "My colleague is late, which is causing me a lot of work."

[0263] Select voice input and speak the same phrase to input.

[0264] Step 2: Send data

[0265] The device transmits the input negative emotion data to the server using a secure communication protocol (e.g., HTTPS).

[0266] Input: Negative emotion data (text format)

[0267] Output: Negative emotion data sent to the server

[0268] Examples of specific actions:

[0269] The device sends text data such as "My colleague is late, so I have more work to do and it's bothering me" to the server using the HTTPS protocol.

[0270] Step 3: Transform negative emotions into positive ones

[0271] The server analyzes the received negative emotion data and converts it into positive interpretation data using a generative AI model. The prompt text is entered as "When the user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way."

[0272] Input: Negative emotion data, prompt sentence

[0273] Output: Positive interpretation data

[0274] Examples of specific actions:

[0275] The server receives data such as "My colleague is late, which is causing me a lot of work" and sends it to the generative AI model, which then receives positive interpretation data such as "My colleague works at his own pace and is good at managing his time."

[0276] Step 4: Analyze the positive aspects of your users

[0277] The server extracts and generates positive characteristics of the user based on the user's profile data and past interaction data.

[0278] Input: User profile data, past interaction data

[0279] Output: Positive characteristic data

[0280] Examples of specific actions:

[0281] The database is used to confirm that the user has an "attitude of valuing time," and based on that characteristic, a compliment such as "You have excellent problem-solving skills and are a great support for the team" is generated.

[0282] Step 5: View the results

[0283] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, again using a secure communication protocol (e.g., HTTPS). The terminal displays the received data to the user.

[0284] Input: Positive interpretation data, positive characteristic data

[0285] Output: A positive message that the user sees

[0286] Examples of specific actions:

[0287] The device will display messages such as, "Your colleagues work at their own pace and manage their time effectively. You also have excellent problem-solving skills and are a supportive member of the team."

[0288] keyword

[0289] Generative AI model, prompt sentence

[0290] (Application example 2)

[0291] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0292] The problem that this invention aims to solve is to convert negative emotions that users experience in their daily lives into positive ones, thereby reducing the user's mental burden. Furthermore, the invention aims to support the user's mental health by analyzing their characteristics and helping them recognize their positive aspects. In particular, by providing this function in content distribution services, the invention aims to provide an environment in which users can reduce stress and have a positive experience.

[0293] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0294] In this invention, the server includes means for analyzing negative emotion data and converting it into positive interpretation data, means for generating positive characteristics of the user based on the user's characteristic data, means for displaying the positive interpretation data and the user's positive characteristics on a content distribution service terminal, means for analyzing negative emotion data based on voice and text input using an emotion engine, and means for transmitting the negative emotion data using a secure communication protocol. This allows the user to convert negative emotions into positive ones and rediscover their own positive aspects, thereby reducing mental burden.

[0295] "Electronic Device" means a device used by a user to process and display input data, such as a smartphone, computer, or tablet.

[0296] "Negative emotion data" is information entered by the user regarding negative emotions such as stress and anxiety.

[0297] A "conversion device" is a system or device for converting received data into another format or content, including a generative AI model.

[0298] "Positive interpretation data" is data that converts negative emotional data into a positive meaning.

[0299] "Characteristic data" is data including user behavior, preferences, personality traits, and the like.

[0300] "Analyzing" means using data statistics and algorithms to extract information and patterns from data.

[0301] "Display" means to visually present information to a user, such as through a device screen.

[0302] A "system" is a set of structures or devices consisting of multiple elements that are interrelated and function in concert.

[0303] A "server" is a computer system that stores and manages data over a network and provides services to client devices.

[0304] "Secure communications protocol" means a communications method used to ensure the secure transmission of data, including HTTPS.

[0305] "Content distribution services" are services that provide video, audio, text, or other content via electronic devices, including online streaming services and digital libraries.

[0306] An "emotion engine" is a software or hardware engine for analyzing emotions from speech, text, and other input data.

[0307] The present invention is a system that receives negative emotional data from a user using an electronic device, converts it into positive interpretation data, and then analyzes the user's characteristics to generate and display the user's positive characteristics. A specific example of how this system can be realized is shown below.

[0308] The system consists of the following elements:

[0309] Electronic Device: A device used by a user, such as a smartphone or tablet.

[0310] Sentiment Engine: Software that recognizes negative emotions based on voice and text input. Uses the Google Cloud Natural Language API.

[0311] Server: A device that receives and analyzes negative emotional data and converts it into positive interpretation data using a generative AI model (OpenAI GPT-4).

[0312] Generative AI model: An AI model used to convert negative sentiment data into positive interpretation data.

[0313] Secure communication protocol: A communication method that uses HTTPS to ensure data security.

[0314] Content distribution service: A service that allows users to see positive interpretation data and positive characteristics of users.

[0315] The user inputs negative emotions using an electronic device. This input can be via text or voice. The emotion engine analyzes this input and recognizes negative emotion data. The recognized negative emotion data is sent to the server using a secure communication protocol. The server converts the received data into positive interpretation data using a generative AI model, and further generates positive traits based on the user's trait data.

[0316] For example, if a user inputs "My colleague is late, which causes me to have more work to do," the emotion engine analyzes this input data and recognizes stress and frustration. The server receives this negative emotion data and inputs it into a generative AI model (OpenAI GPT-4). The generative AI model generates a positive interpretation, such as:

[0317] "My colleagues are able to work at their own pace and are good at time management." In addition, the server extracts user characteristics from the user profile and generates positive characteristics such as:

[0318] "You're a great problem solver and a great support for the team."

[0319] The results are displayed on the user's electronic device through a content distribution service, allowing the user to rediscover their positive interpretations and positive traits, and feel a reduction in their mental burden.

[0320] Example prompt sentence:

[0321] Take the negative sentence: "My coworker is late, which means I have more work to do" and turn it into a positive one.

[0322] In this way, the present invention provides an effective means for converting negative emotions into positive ones and supporting the mental health of users by further analyzing their characteristics.

[0323] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0324] Step 1:

[0325] A user inputs negative emotions using an electronic device.

[0326] Input: The user inputs negative emotions via text or voice.

[0327] Data processing / data calculation: The emotion engine analyzes the user's input data and recognizes negative emotion data.

[0328] Output: Parsed negative sentiment data.

[0329] Step 2:

[0330] The device transmits negative emotional data to a server using a secure communication protocol (HTTPS).

[0331] Input: Parsed negative sentiment data.

[0332] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[0333] Output: Securely transmitted negative sentiment data.

[0334] Step 3:

[0335] The server analyzes the negative emotional data it receives and converts it into positive interpretation data using a generative AI model.

[0336] Input: Received negative sentiment data.

[0337] Data processing / data calculation: Input data into a generative AI model, analyze it, and generate positive interpretation data.

[0338] Output: Positive interpretive data.

[0339] Step 4:

[0340] The server generates positive characteristic data based on the user's characteristic data.

[0341] Input: User profile data and past interaction data.

[0342] Data processing / data calculation: Analyze user characteristic data and extract positive characteristics.

[0343] Output: Positive trait data of the user.

[0344] Step 5:

[0345] The server transmits the generated positive interpretation data and the user's positive characteristic data to the terminal using a secure communication protocol (HTTPS).

[0346] Input: Positive interpretation data and positive user characteristic data.

[0347] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[0348] Output: Securely transmitted positive interpretation and characterization data.

[0349] Step 6:

[0350] The terminal displays the received positive interpretation data and the user's positive characteristic data to the user.

[0351] Input: Securely transmitted positive interpretation data and positive user characteristic data.

[0352] Data processing / data calculation: Analyzes received data and converts it into a display format.

[0353] Output: Positive interpretation and characteristic data displayed to the user.

[0354] As a specific example of how it works, a user might input, "My colleague is always late, which is causing me a lot of work." The emotion engine analyzes this input and recognizes negative emotions. The recognized data is sent to the server, where the generative AI model converts it into a positive interpretation: "My colleague is able to work at his own pace and is good at time management." The server then generates a positive characteristic based on the user profile: "You are a good problem-solver and a supportive member of the team," which the device displays to the user.

[0355] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0356] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0357] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0358] [Second embodiment]

[0359] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0360] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0361] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0362] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0363] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0364] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0365] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0366] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0367] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0368] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0369] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0370] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0371] The present invention is a system that receives negative emotional data input by a user using an electronic device, converts it into positive emotions, and helps the user recognize their positive side, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, and a conversion device.

[0372] User Input Processing

[0373] The user inputs his or her negative emotions into the input interface of the electronic device, for example, "I don't like that colleague because he or she is always late and doesn't help me with my work."

[0374] Processing data transmission

[0375] The device transmits the input negative emotion data to the server, preferably using a secure communication protocol.

[0376] Transforming negative emotions into positive ones

[0377] The server analyzes the received negative emotional data and converts it into positive interpretation data using a conversion device, i.e., a generative AI model. For example, the positive interpretation might be, "That colleague can do things at their own pace and is independent."

[0378] Analyzing the positive aspects of users

[0379] The server then analyzes the user's positive attributes based on the user's characteristic data, including user profile data and past behavioral data. As a result of the analysis, it generates compliments such as "You are very honest" or "You are responsible and value your time."

[0380] Displaying the results

[0381] The server sends the generated positive interpretation data and the user's good points to the device, which then displays the received data to the user. This allows the user to see how their negative emotions have been transformed into positive ones, and further reduces the burden on their mind by reaffirming their positive aspects.

[0382] Specific examples

[0383] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[0384] This system allows users to reframe negative emotions that arise in their daily lives in a positive light, rediscovering their own positive aspects and reducing mental stress.

[0385] The processing flow will be explained below.

[0386] Step 1:

[0387] An interface is displayed that allows a user to input emotional data using an electronic device. For example, the user inputs negative emotional data such as "My colleague is late, so I have more work to do, which is bothering me."

[0388] Step 2:

[0389] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[0390] Step 3:

[0391] The server receives the negative emotion data and formats it into text for analysis.

[0392] Step 4:

[0393] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[0394] Step 5:

[0395] The server analyzes the user's characteristic data. The analysis uses the user's registered profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "high problem-solving ability."

[0396] Step 6:

[0397] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, also using the HTTPS protocol.

[0398] Step 7:

[0399] The terminal receives the data from the server and converts it into a displayable format.

[0400] Step 8:

[0401] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0402] Step 9:

[0403] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[0404] Example 1

[0405] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0406] In modern society, users often experience various negative emotions in their daily lives and work. These negative emotions can have a negative impact on users' mental health, as well as on their productivity and interpersonal relationships. Conventional technologies lack a means to effectively transform these negative emotions into positive ones and reduce the user's mental burden. The present invention aims to solve these problems by providing a system that transforms negative emotions into positive ones and reduces the user's mental burden by helping them recognize their positive aspects.

[0407] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0408] In this invention, the server includes means for receiving negative emotional data input by a user using an electronic device, means for transmitting the received negative emotional data to the server using a communication protocol, means for the server to convert the negative emotional data into positive interpretation data using a generative AI model, means for the server to generate positive characteristics of the user based on the user's profile data, and means for displaying the positive interpretation data and the user's positive characteristics to the user. This makes it possible to effectively convert negative emotions into positive ones and reduce the user's mental burden by helping them recognize their positive aspects.

[0409] "Negative emotion data" is data entered in text format that describes negative emotions such as dissatisfaction, stress, sadness, etc. that the user feels.

[0410] "Electronic devices" refer to devices such as smartphones, tablets, and personal computers that can be operated by the user.

[0411] A "communication protocol" is a set of rules used to ensure security and reliability when sending and receiving data between electronic devices and servers, and one example is HTTPS.

[0412] A "server" is a computer system for processing received negative emotional data and generating positive interpretation data.

[0413] A "generative AI model" is an artificial intelligence model that learns from large amounts of data to generate text, and plays a role in converting negative emotional data into positive ones.

[0414] "Positive interpretation data" is text data with positive and affirmative content generated by a generative AI model based on negative emotional data.

[0415] "User profile data" refers to a group of data in a database that includes characteristic information and past behavioral history about individual users.

[0416] "User's positive characteristics" is data that indicates the user's advantages and strengths, extracted based on the user's profile data.

[0417] The "display means" is a mechanism for visually presenting the positive interpretation data and the user's positive characteristics to the user on the screen of an electronic device.

[0418] This system receives negative emotional data input by a user using an electronic device, converts it into positive emotion, and helps the user recognize their positive side, thereby reducing their mental burden. The system is composed of multiple elements, including an electronic device, a server, and a generative AI model.

[0419] User Input Processing

[0420] The user inputs their negative emotions into the input interface of the electronic device. The input data is stored in text format. For example, a sentence such as "My colleague is late, so I have more work to do, which is a problem" is input. The input field includes a text field and a submit button.

[0421] Processing data transmission

[0422] The device sends the entered negative emotion data to the server. At this time, the data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is clicked, the device encrypts the data and sends a POST request to the server using the HTTPS protocol.

[0423] Transforming negative emotions into positive ones

[0424] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model (e.g., GPT-3). For example, a negative input such as "My colleague is always late, which causes me to have more work" can be converted into a positive interpretation such as "My colleague is able to work at his own pace and is good at managing his time."

[0425] Analyzing the positive aspects of users

[0426] The server then analyzes the user's positive aspects based on their profile data and past behavioral data. For example, it generates compliments such as, "You are a good problem-solver and a great supporter of the team." The server retrieves the user's characteristic information from the user profile database and sends prompts to the generative AI model.

[0427] Displaying the results

[0428] The server sends the generated positive interpretation data and information about the user's positive characteristics to the device, which then displays the received data to the user, allowing the user to see how their negative emotions have been transformed into positive ones and to rediscover their own positive aspects.

[0429] Specific examples

[0430] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[0431] Prompt Sentence Examples

[0432] "Generate positive interpretations of specific emotions and compliments based on the user's characteristics."

[0433] In this way, the present invention provides a concrete means for users to reframe negative emotions that arise in their daily lives in a positive light, rediscover their own positive aspects, and reduce mental burden.

[0434] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0435] Step 1:

[0436] The user inputs negative emotional data into the input interface of an electronic device. The input data is stored in text format. Specifically, the user enters "My colleague is late, so I have more work to do, which is a problem" into the text field and presses the send button. This text data is the input. The output is the input text data itself.

[0437] Step 2:

[0438] The terminal sends the entered negative emotion data to the server. The data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is pressed, the terminal encrypts the text data and sends it to the server as a POST request. The input is the text data entered by the user, and the output is the encrypted text data.

[0439] Step 3:

[0440] The server receives the negative emotion data sent. After receiving it, it analyzes the data using a generative AI model (e.g., GPT-3) and converts it into positive interpretation data. Specifically, the server receives the text "My colleague is always late, which is bothering me because it means more work," and sends it to the generative AI model along with the prompt, "Generate a positive interpretation for the specific emotion and a compliment based on the user's characteristics." The generative AI model analyzes it and outputs a positive interpretation, for example, "My colleague is able to work at his own pace and is clever about how he uses his time." The input is encrypted negative text data, and the output is text data converted into a positive one.

[0441] Step 4:

[0442] The server then generates positive traits for the user based on the user's profile data and past behavioral data. The server retrieves trait information from the user profile database and sends a prompt to the generative AI model: "Generate a compliment based on the user's traits." Specifically, the server generates a compliment such as, "You are a good problem-solver and a supportive member of the team." The input is the user's profile data, and the output is text data of the compliment.

[0443] Step 5:

[0444] The server sends the generated positive interpretation data and the user's positive characteristics information to the terminal. The terminal receives this data and displays it to the user, for example, as a pop-up message or on a dashboard. The input is the positive interpretation data and compliment text data sent from the server, and the output is a visual display of this to the user.

[0445] Through the above processing steps, this system can convert the user's negative emotions into positive ones and reduce the mental burden by helping the user to recognize their positive side.

[0446] (Application example 1)

[0447] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0448] In modern society, people often experience many negative emotions in their daily lives, which can become a mental burden. Furthermore, it is difficult to reframe negative emotions in a positive light, and there are limited means to improve self-esteem. Conventional systems face challenges in that they are unable to adequately alleviate negative emotions or suggest positive interpretations. Furthermore, they do not provide appropriate feedback to help users recognize their own positive aspects. Therefore, there is a need for a system that can effectively transform the negative emotions users experience in their daily lives into positive ones and improve self-esteem.

[0449] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0450] In this invention, the server includes means for receiving negative emotion data input by a user using an electronic device, means for converting the received negative emotion data into positive interpretation data using a conversion device, means for analyzing the user's characteristic data and generating positive characteristics for the user, means for displaying the positive interpretation data and the user's positive characteristics to the user, means for transmitting the generated data to the user's terminal via a secure communication protocol, and means for displaying a correlation between the negative emotion data input by the user and the converted positive interpretation data. This converts the negative emotion input by the user into a positive one and helps the user recognize their positive aspects, thereby reducing mental burden and improving self-esteem.

[0451] An "electronic device" is a device that allows a user to input or view information, and examples include smartphones and tablets.

[0452] "Negative emotion data" is information that expresses negative emotions such as discomfort or dissatisfaction felt by the user.

[0453] A "conversion device" is a system or module for converting input negative emotional data into positive interpretation data.

[0454] "Positive interpretation data" is information that reinterprets negative emotional data in a favorable or positive way.

[0455] "Characteristic data" is information relating to the user's personality and behavioral characteristics, and includes profile data and behavioral history.

[0456] "Positive characteristics" are information that indicates the user's good points or outstanding characteristics.

[0457] "Display means" refers to an interface for visually presenting information to a user, and includes a screen, a display, and the like.

[0458] A "secure communication protocol" is a communication standard for securely sending and receiving data, and examples include HTTPS and SSL / TLS.

[0459] A "generative AI model" is an algorithm or system that uses artificial intelligence to perform a specific task or data transformation.

[0460] A "prompt sentence" is an instruction or question sentence input to a generative AI model.

[0461] This invention is a system that converts a user's negative emotions into positive ones and reduces mental burden by helping the user recognize their positive side. This system is composed of multiple elements, including electronic devices, servers, and generative AI models.

[0462] Hardware and software used

[0463] Hardware:

[0464] Smartphone

[0465] server

[0466] software:

[0467] Application: React Native (front-end)

[0468] Server framework: Flask

[0469] Generative AI model: GPT-4 (OpenAI)

[0470] Communication protocol: HTTPS

[0471] Database: PostgreSQL

[0472] Operational Overview

[0473] 1. Receiving emotional input

[0474] A user uses a smartphone as an electronic device and inputs negative emotional data into the emotion input interface, for example, by entering an emotion such as "I failed at work. I no longer have confidence" into a text field.

[0475] 2. Data transmission

[0476] The input negative emotion data is sent to the server via a secure communication protocol (HTTPS), and the server receives this data securely.

[0477] 3. Transforming negative emotions into positive ones

[0478] The server analyzes the received negative emotion data using a generative AI model (GPT-4), which converts negative emotions into positive interpretation data based on pre-trained prompts.

[0479] Example: A negative emotion, "I failed at work. I no longer have confidence in myself," can be transformed into a positive interpretation, "This failure is an opportunity to learn a lot and rebuild my confidence."

[0480] 4. Analyzing the positive aspects of users

[0481] The server analyzes the user's characteristic data, which is based on the user's profile data and past behavior data, and generates positive attributes and traits for the user based on this data.

[0482] For example, a compliment such as "You are a great problem solver and a great support for the team" may be generated.

[0483] 5. Displaying the results

[0484] The server sends the generated positive interpretation data and the user's positive characteristics to the user's device, which receives it and displays it on the screen. The user can see how their negative emotions have been transformed into positive ones and their own positive aspects.

[0485] Prompt Sentence Examples

[0486] Negative Emotion: "I failed at work. I no longer have confidence."

[0487] Positive Transformation: "Failure is an opportunity to learn a lot and rebuild your confidence."

[0488] In this way, this invention effectively transforms the negative emotions that users have in their daily lives into positive ones, and by making users recognize their own good sides, it is possible to reduce mental burden and improve self-esteem.

[0489] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0490] Step 1:

[0491] This is a step in which the user inputs negative emotion data using an electronic device (smartphone).

[0492] Input: The user enters emotion data in the text field: "I failed at work. I no longer have confidence."

[0493] Output: The input emotion data is received by the terminal.

[0494] Specific operation: The user enters emotions in text format into the application's input interface and presses the "Send" button.

[0495] Step 2:

[0496] This is a step in which the terminal transmits the received negative emotion data to the server.

[0497] Input: User-entered negative sentiment data.

[0498] Output: Negative sentiment data sent to the server.

[0499] Specific operation: The device sends the input emotion data to the server using a secure communication protocol (HTTPS).

[0500] Step 3:

[0501] This is the step where the server analyzes the negative emotional data received using a generative AI model to generate positive interpretation data.

[0502] Input: Negative emotion data received by the server.

[0503] Output: Generated positive interpretation data.

[0504] Specific operation: The server inputs the received emotional data into a generative AI model (e.g., GPT-4) and generates positive interpretation data such as, "This is an opportunity to learn a lot from your failure and rebuild your confidence."

[0505] Step 4:

[0506] The server analyzes the user's characteristic data and generates positive characteristics for the user.

[0507] Input: User characteristic data stored on the server (profile data and past behavioral data).

[0508] Output: Generated positive trait data of the user.

[0509] Specific operation: The server retrieves the user's characteristic data from the database, analyzes it, and generates positive characteristic data such as, "You have excellent problem-solving skills and are a supportive member of the team."

[0510] Step 5:

[0511] The server transmits the generated positive interpretation data and the user's positive characteristic data to the user's terminal.

[0512] Input: Generated positive interpretation data and user positive characteristic data.

[0513] Output: Data sent to the user's device.

[0514] Specific operation: The server transmits the positive interpretation data and the user's positive characteristic data to the user's terminal using a secure communication protocol (HTTPS).

[0515] Step 6:

[0516] This is the step in which the user's terminal displays the received data to the user.

[0517] Input: Positive interpretation data received from the server and positive characteristic data of the user.

[0518] Output: The data that is displayed to the user.

[0519] Specific operation: The positive interpretation data received by the terminal and the user's positive characteristic data are displayed on the application screen and presented to the user as feedback.

[0520] Step 7:

[0521] This is a step of displaying the association between the negative emotion data input by the user and the converted positive interpretation data.

[0522] Input: Negative emotion data and corresponding positive interpretation data.

[0523] Output: A screen showing the correlation.

[0524] Specific operation: The device displays negative emotion data and positive interpretation data on the screen in contrast, clearly showing the user how negative emotions have been transformed into positive ones.

[0525] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0526] This system receives negative emotional data input by a user using an electronic device, converts it into positive interpretation data, and helps the user recognize their positive aspects, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, a conversion device (generative AI model), and an emotion engine.

[0527] User Input Processing

[0528] A user inputs his / her negative emotions through an input interface of an electronic device or through input to an emotion engine. Negative emotions can be input as text into the interface of the electronic device, or the emotion engine can analyze multimodal data such as voice, facial expressions, and gestures to recognize negative emotion data. For example, a user can input "I'm having trouble because my colleague is late, which means more work for me," and the emotion engine can recognize the user's stress from their voice and facial expressions.

[0529] Processing data transmission

[0530] The device sends the input negative emotion data to the server, using a secure communication protocol (e.g., HTTPS) to ensure the safety of the data.

[0531] Transforming negative emotions into positive ones

[0532] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[0533] Analyzing the positive aspects of users

[0534] The server then analyzes the user's positive aspects based on the user's characteristic data. This analysis utilizes user profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "excellent problem-solving skills."

[0535] Displaying the results

[0536] The server transmits the generated positive interpretation data and the user's positive aspects to the device using a secure protocol.

[0537] The device then displays the received data to the user, such as a message like, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0538] Specific examples

[0539] For example, if a user types in text, "My colleague is always late, which is causing me a lot of work," that data is sent from the device to the server. Alternatively, the emotion engine can recognize the user's stress from their voice and facial expressions and send the data in a similar manner. The server then uses a generative AI model to convert this negative emotion data into, "My colleague is able to work at his or her own pace and is good at time management." Furthermore, it can generate compliments from the user's characteristic data, such as, "You are a good problem-solver and a supportive member of the team." When these results are displayed on the device, the user can confirm the positive interpretation and reaffirm their own positive aspects, thereby reducing their mental burden.

[0540] This embodiment allows users to transform negative emotions that arise in their daily lives into positive ones and to rediscover their positive aspects, thereby reducing further mental burdens. This process is an effective way to support the user's mental health.

[0541] The processing flow will be explained below.

[0542] Step 1:

[0543] A user accesses the interface of an electronic device, and either the user inputs negative emotion data in text, or the emotion engine recognizes negative emotions from the user's voice, facial expressions, gestures, etc.

[0544] Step 2:

[0545] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[0546] Step 3:

[0547] The server analyzes the received negative emotion data and formats it into text.

[0548] Step 4:

[0549] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data, for example, converting "My colleague is always late, which causes me to have more work to do" into "My colleague works at his own pace and is good at time management."

[0550] Step 5:

[0551] The server analyzes the user's characteristic data, using user profile data and past interaction data to extract the user's strengths and positive characteristics.

[0552] Step 6:

[0553] The server generates compliments based on the extracted positive characteristics of the user. For example, it recognizes user characteristics such as "valuing time" and "good problem-solving skills" and generates a compliment such as "You have good problem-solving skills and are a great support for the team."

[0554] Step 7:

[0555] The server transmits the generated positive interpretation data and the user's positive characteristics to the terminal using a secure protocol.

[0556] Step 8:

[0557] The terminal receives the data from the server and converts it into a displayable format.

[0558] Step 9:

[0559] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0560] Step 10:

[0561] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[0562] Example 2

[0563] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0564] In modern living environments, users are often exposed to negative emotions on a daily basis, which can easily increase their mental burden. However, it is not easy to deal with these negative emotions on one's own, and they often cause stress and anxiety. To address this issue, a system is needed that can reduce mental burden by helping users reframe negative emotions in a positive way.

[0565] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0566] In this invention, the server includes means for receiving negative emotion data input by a user using a communication terminal, means for analyzing the received negative emotion data and generating positive interpretation data using a generative AI model, and means for generating positive characteristics of the user based on the user's profile data and past interaction data. This allows the user to convert negative emotions into positive ones and re-identify them, thereby reducing mental burden.

[0567] A "communication terminal" is an electronic device that a user uses to input and transmit negative emotional data, and examples include smartphones and personal computers.

[0568] "Negative emotion data" is data that expresses negative emotions felt by the user, and is input in the form of text, voice, facial expressions, gestures, or the like.

[0569] A "secure communication protocol" is a set of rules for ensuring the safety of data communication, such as HTTPS.

[0570] "Server" means a computer system for analyzing received negative emotional data and generating positive interpretation data and positive characteristics of the user using a generative AI model.

[0571] A "generative AI model" is an artificial intelligence model used to convert negative emotional data into positive interpretation data, and examples include models that use natural language processing techniques.

[0572] "Profile data" is a database containing attribute information and past interaction data about a user, and is data that is referenced to generate positive characteristics of the user.

[0573] "Positive interpretation data" is data that shows a positive interpretation converted from negative emotional data by a generative AI model.

[0574] "Positive traits" are traits that show the positive aspects of a user and are generated based on the user's profile data and past interaction data.

[0575] The present invention is a system that receives negative emotional data input by a user using a communication terminal, converts it into positive interpretation data, and further generates and displays positive characteristics based on the user's characteristic data. The system of the present invention aims to convert the negative emotional data input by the user into positive data, thereby reducing the user's mental burden.

[0576] Hardware and Software Configuration

[0577] This system consists of elements such as communication terminals, servers, generative AI models, emotion engines, and databases.

[0578] communication terminal

[0579] Users input negative emotions using a communication device (e.g., smartphone or personal computer). A dedicated application or web form is installed on the communication device, and users use this to input emotions using text, voice, facial expressions, etc. The emotion engine analyzes the emotion data using voice recognition software (e.g., Google speech-to-text API) and facial expression recognition software (e.g., Microsoft Azure Face API).

[0580] server

[0581] The server receives the negative emotional data sent from the communication device. The received data is transferred using a secure communication protocol (e.g., HTTPS). The server then uses a generative AI model (e.g., OpenAI GPT-3) to convert the negative emotional data into positive interpretation data. The server then references a database that stores the user's profile data and past interaction data to extract and generate positive characteristics for the user.

[0582] Specific examples

[0583] For example, if a user uses a dedicated application to input text such as "My colleague is late, which is causing me a lot of work," the data is sent from the communication device to the server. Negative emotion data input through voice input or facial recognition is also processed in the same way.

[0584] The server sends the received data to the generative AI model as a prompt. For example, the user might input, "When a user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way." The generative AI model generates positive interpretation data, such as, "My colleague works at his own pace and is good at time management."

[0585] Next, the server checks the database for the user's characteristic of "valuing time" and generates a compliment such as "You have excellent problem-solving skills and are a great support for the team." The server then sends the generated positive interpretation data and the compliment to the communication terminal, which then displays it to the user.

[0586] This allows the user to convert the negative emotions they input into positive interpretations, and by rediscovering their positive aspects, they can reduce their mental burden. Through this process, the present invention provides an effective means of supporting the user's mental health.

[0587] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0588] Program processing flow

[0589] Step 1: User Input

[0590] Users input negative emotional data using a communication device. Specifically, they can input it as text through a dedicated application or web form displayed on the device. They can also input facial expressions and gestures using voice input or a camera.

[0591] Input: Negative emotion text, audio data, facial expression data

[0592] Output: Negative sentiment data (text format)

[0593] Examples of specific actions:

[0594] A user opens the app and types in the text, "My colleague is late, which is causing me a lot of work."

[0595] Select voice input and speak the same phrase to input.

[0596] Step 2: Send data

[0597] The device transmits the input negative emotion data to the server using a secure communication protocol (e.g., HTTPS).

[0598] Input: Negative emotion data (text format)

[0599] Output: Negative emotion data sent to the server

[0600] Examples of specific actions:

[0601] The device sends text data such as "My colleague is late, so I have more work to do and it's bothering me" to the server using the HTTPS protocol.

[0602] Step 3: Transform negative emotions into positive ones

[0603] The server analyzes the received negative emotion data and converts it into positive interpretation data using a generative AI model. The prompt text is entered as "When the user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way."

[0604] Input: Negative emotion data, prompt sentence

[0605] Output: Positive interpretation data

[0606] Examples of specific actions:

[0607] The server receives data such as "My colleague is late, which is causing me a lot of work" and sends it to the generative AI model, which then receives positive interpretation data such as "My colleague works at his own pace and is good at managing his time."

[0608] Step 4: Analyze the positive aspects of your users

[0609] The server extracts and generates positive characteristics of the user based on the user's profile data and past interaction data.

[0610] Input: User profile data, past interaction data

[0611] Output: Positive characteristic data

[0612] Examples of specific actions:

[0613] The database is used to confirm that the user has an "attitude of valuing time," and based on that characteristic, a compliment such as "You have excellent problem-solving skills and are a great support for the team" is generated.

[0614] Step 5: View the results

[0615] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, again using a secure communication protocol (e.g., HTTPS). The terminal displays the received data to the user.

[0616] Input: Positive interpretation data, positive characteristic data

[0617] Output: A positive message that the user sees

[0618] Examples of specific actions:

[0619] The device will display messages such as, "Your colleagues work at their own pace and manage their time effectively. You also have excellent problem-solving skills and are a supportive member of the team."

[0620] keyword

[0621] Generative AI model, prompt sentence

[0622] (Application example 2)

[0623] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0624] The problem that this invention aims to solve is to convert negative emotions that users experience in their daily lives into positive ones, thereby reducing the user's mental burden. Furthermore, the invention aims to support the user's mental health by analyzing their characteristics and helping them recognize their positive aspects. In particular, by providing this function in content distribution services, the invention aims to provide an environment in which users can reduce stress and have a positive experience.

[0625] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0626] In this invention, the server includes means for analyzing negative emotion data and converting it into positive interpretation data, means for generating positive characteristics of the user based on the user's characteristic data, means for displaying the positive interpretation data and the user's positive characteristics on a content distribution service terminal, means for analyzing negative emotion data based on voice and text input using an emotion engine, and means for transmitting the negative emotion data using a secure communication protocol. This allows the user to convert negative emotions into positive ones and rediscover their own positive aspects, thereby reducing mental burden.

[0627] "Electronic Device" means a device used by a user to process and display input data, such as a smartphone, computer, or tablet.

[0628] "Negative emotion data" is information entered by the user regarding negative emotions such as stress and anxiety.

[0629] A "conversion device" is a system or device for converting received data into another format or content, including a generative AI model.

[0630] "Positive interpretation data" is data that converts negative emotional data into a positive meaning.

[0631] "Characteristic data" is data including user behavior, preferences, personality traits, and the like.

[0632] "Analyzing" means using data statistics and algorithms to extract information and patterns from data.

[0633] "Display" means to visually present information to a user, such as through a device screen.

[0634] A "system" is a set of structures or devices consisting of multiple elements that are interrelated and function in concert.

[0635] A "server" is a computer system that stores and manages data over a network and provides services to client devices.

[0636] "Secure communications protocol" means a communications method used to ensure the secure transmission of data, including HTTPS.

[0637] "Content distribution services" are services that provide video, audio, text, or other content via electronic devices, including online streaming services and digital libraries.

[0638] An "emotion engine" is a software or hardware engine for analyzing emotions from speech, text, and other input data.

[0639] The present invention is a system that receives negative emotional data from a user using an electronic device, converts it into positive interpretation data, and then analyzes the user's characteristics to generate and display the user's positive characteristics. A specific example of how this system can be realized is shown below.

[0640] The system consists of the following elements:

[0641] Electronic Device: A device used by a user, such as a smartphone or tablet.

[0642] Sentiment Engine: Software that recognizes negative emotions based on voice and text input. Uses the Google Cloud Natural Language API.

[0643] Server: A device that receives and analyzes negative emotional data and converts it into positive interpretation data using a generative AI model (OpenAI GPT-4).

[0644] Generative AI model: An AI model used to convert negative sentiment data into positive interpretation data.

[0645] Secure communication protocol: A communication method that uses HTTPS to ensure data security.

[0646] Content distribution service: A service that allows users to see positive interpretation data and positive characteristics of users.

[0647] The user inputs negative emotions using an electronic device. This input can be via text or voice. The emotion engine analyzes this input and recognizes negative emotion data. The recognized negative emotion data is sent to the server using a secure communication protocol. The server converts the received data into positive interpretation data using a generative AI model, and further generates positive traits based on the user's trait data.

[0648] For example, if a user inputs "My colleague is late, which causes me to have more work to do," the emotion engine analyzes this input data and recognizes stress and frustration. The server receives this negative emotion data and inputs it into a generative AI model (OpenAI GPT-4). The generative AI model generates a positive interpretation, such as:

[0649] "My colleagues are able to work at their own pace and are good at time management." In addition, the server extracts user characteristics from the user profile and generates positive characteristics such as:

[0650] "You're a great problem solver and a great support for the team."

[0651] The results are displayed on the user's electronic device through a content distribution service, allowing the user to rediscover their positive interpretations and positive traits, and feel a reduction in their mental burden.

[0652] Example prompt sentence:

[0653] Take the negative sentence: "My coworker is late, which means I have more work to do" and turn it into a positive one.

[0654] In this way, the present invention provides an effective means for converting negative emotions into positive ones and supporting the mental health of users by further analyzing their characteristics.

[0655] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0656] Step 1:

[0657] A user inputs negative emotions using an electronic device.

[0658] Input: The user inputs negative emotions via text or voice.

[0659] Data processing / data calculation: The emotion engine analyzes the user's input data and recognizes negative emotion data.

[0660] Output: Parsed negative sentiment data.

[0661] Step 2:

[0662] The device transmits negative emotional data to a server using a secure communication protocol (HTTPS).

[0663] Input: Parsed negative sentiment data.

[0664] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[0665] Output: Securely transmitted negative sentiment data.

[0666] Step 3:

[0667] The server analyzes the negative emotional data it receives and converts it into positive interpretation data using a generative AI model.

[0668] Input: Received negative sentiment data.

[0669] Data processing / data calculation: Input data into a generative AI model, analyze it, and generate positive interpretation data.

[0670] Output: Positive interpretive data.

[0671] Step 4:

[0672] The server generates positive characteristic data based on the user's characteristic data.

[0673] Input: User profile data and past interaction data.

[0674] Data processing / data calculation: Analyze user characteristic data and extract positive characteristics.

[0675] Output: Positive trait data of the user.

[0676] Step 5:

[0677] The server transmits the generated positive interpretation data and the user's positive characteristic data to the terminal using a secure communication protocol (HTTPS).

[0678] Input: Positive interpretation data and positive user characteristic data.

[0679] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[0680] Output: Securely transmitted positive interpretation and characterization data.

[0681] Step 6:

[0682] The terminal displays the received positive interpretation data and the user's positive characteristic data to the user.

[0683] Input: Securely transmitted positive interpretation data and positive user characteristic data.

[0684] Data processing / data calculation: Analyzes received data and converts it into a display format.

[0685] Output: Positive interpretation and characteristic data displayed to the user.

[0686] As a specific example of how it works, a user might input, "My colleague is always late, which is causing me a lot of work." The emotion engine analyzes this input and recognizes negative emotions. The recognized data is sent to the server, where the generative AI model converts it into a positive interpretation: "My colleague is able to work at his own pace and is good at time management." The server then generates a positive characteristic based on the user profile: "You are a good problem-solver and a supportive member of the team," which the device displays to the user.

[0687] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0688] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0689] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0690] [Third embodiment]

[0691] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0692] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0693] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0694] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0695] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0696] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0697] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0698] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0699] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0700] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0701] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0702] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0703] The present invention is a system that receives negative emotional data input by a user using an electronic device, converts it into positive emotions, and helps the user recognize their positive side, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, and a conversion device.

[0704] User Input Processing

[0705] The user inputs his or her negative emotions into the input interface of the electronic device, for example, "I don't like that colleague because he or she is always late and doesn't help me with my work."

[0706] Processing data transmission

[0707] The device transmits the input negative emotion data to the server, preferably using a secure communication protocol.

[0708] Transforming negative emotions into positive ones

[0709] The server analyzes the received negative emotional data and converts it into positive interpretation data using a conversion device, i.e., a generative AI model. For example, the positive interpretation might be, "That colleague can do things at their own pace and is independent."

[0710] Analyzing the positive aspects of users

[0711] The server then analyzes the user's positive attributes based on the user's characteristic data, including user profile data and past behavioral data. As a result of the analysis, it generates compliments such as "You are very honest" or "You are responsible and value your time."

[0712] Displaying the results

[0713] The server sends the generated positive interpretation data and the user's good points to the device, which then displays the received data to the user. This allows the user to see how their negative emotions have been transformed into positive ones, and further reduces the burden on their mind by reaffirming their positive aspects.

[0714] Specific examples

[0715] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[0716] This system allows users to reframe negative emotions that arise in their daily lives in a positive light, rediscovering their own positive aspects and reducing mental stress.

[0717] The processing flow will be explained below.

[0718] Step 1:

[0719] An interface is displayed that allows a user to input emotional data using an electronic device. For example, the user inputs negative emotional data such as "My colleague is late, so I have more work to do, which is bothering me."

[0720] Step 2:

[0721] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[0722] Step 3:

[0723] The server receives the negative emotion data and formats it into text for analysis.

[0724] Step 4:

[0725] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[0726] Step 5:

[0727] The server analyzes the user's characteristic data. The analysis uses the user's registered profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "high problem-solving ability."

[0728] Step 6:

[0729] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, also using the HTTPS protocol.

[0730] Step 7:

[0731] The terminal receives the data from the server and converts it into a displayable format.

[0732] Step 8:

[0733] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0734] Step 9:

[0735] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[0736] Example 1

[0737] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0738] In modern society, users often experience various negative emotions in their daily lives and work. These negative emotions can have a negative impact on users' mental health, as well as on their productivity and interpersonal relationships. Conventional technologies lack a means to effectively transform these negative emotions into positive ones and reduce the user's mental burden. The present invention aims to solve these problems by providing a system that transforms negative emotions into positive ones and reduces the user's mental burden by helping them recognize their positive aspects.

[0739] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0740] In this invention, the server includes means for receiving negative emotional data input by a user using an electronic device, means for transmitting the received negative emotional data to the server using a communication protocol, means for the server to convert the negative emotional data into positive interpretation data using a generative AI model, means for the server to generate positive characteristics of the user based on the user's profile data, and means for displaying the positive interpretation data and the user's positive characteristics to the user. This makes it possible to effectively convert negative emotions into positive ones and reduce the user's mental burden by helping them recognize their positive aspects.

[0741] "Negative emotion data" is data entered in text format that describes negative emotions such as dissatisfaction, stress, sadness, etc. that the user feels.

[0742] "Electronic devices" refer to devices such as smartphones, tablets, and personal computers that can be operated by the user.

[0743] A "communication protocol" is a set of rules used to ensure security and reliability when sending and receiving data between electronic devices and servers, and one example is HTTPS.

[0744] A "server" is a computer system for processing received negative emotional data and generating positive interpretation data.

[0745] A "generative AI model" is an artificial intelligence model that learns from large amounts of data to generate text, and plays a role in converting negative emotional data into positive ones.

[0746] "Positive interpretation data" is text data with positive and affirmative content generated by a generative AI model based on negative emotional data.

[0747] "User profile data" refers to a group of data in a database that includes characteristic information and past behavioral history about individual users.

[0748] "User's positive characteristics" is data that indicates the user's advantages and strengths, extracted based on the user's profile data.

[0749] The "display means" is a mechanism for visually presenting the positive interpretation data and the user's positive characteristics to the user on the screen of an electronic device.

[0750] This system receives negative emotional data input by a user using an electronic device, converts it into positive emotion, and helps the user recognize their positive side, thereby reducing their mental burden. The system is composed of multiple elements, including an electronic device, a server, and a generative AI model.

[0751] User Input Processing

[0752] The user inputs their negative emotions into the input interface of the electronic device. The input data is stored in text format. For example, a sentence such as "My colleague is late, so I have more work to do, which is a problem" is input. The input field includes a text field and a submit button.

[0753] Processing data transmission

[0754] The device sends the entered negative emotion data to the server. At this time, the data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is clicked, the device encrypts the data and sends a POST request to the server using the HTTPS protocol.

[0755] Transforming negative emotions into positive ones

[0756] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model (e.g., GPT-3). For example, a negative input such as "My colleague is always late, which causes me to have more work" can be converted into a positive interpretation such as "My colleague is able to work at his own pace and is good at managing his time."

[0757] Analyzing the positive aspects of users

[0758] The server then analyzes the user's positive aspects based on their profile data and past behavioral data. For example, it generates compliments such as, "You are a good problem-solver and a great supporter of the team." The server retrieves the user's characteristic information from the user profile database and sends prompts to the generative AI model.

[0759] Displaying the results

[0760] The server sends the generated positive interpretation data and information about the user's positive characteristics to the device, which then displays the received data to the user, allowing the user to see how their negative emotions have been transformed into positive ones and to rediscover their own positive aspects.

[0761] Specific examples

[0762] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[0763] Prompt Sentence Examples

[0764] "Generate positive interpretations of specific emotions and compliments based on the user's characteristics."

[0765] In this way, the present invention provides a concrete means for users to reframe negative emotions that arise in their daily lives in a positive light, rediscover their own positive aspects, and reduce mental burden.

[0766] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0767] Step 1:

[0768] The user inputs negative emotional data into the input interface of an electronic device. The input data is stored in text format. Specifically, the user enters "My colleague is late, so I have more work to do, which is a problem" into the text field and presses the send button. This text data is the input. The output is the input text data itself.

[0769] Step 2:

[0770] The terminal sends the entered negative emotion data to the server. The data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is pressed, the terminal encrypts the text data and sends it to the server as a POST request. The input is the text data entered by the user, and the output is the encrypted text data.

[0771] Step 3:

[0772] The server receives the negative emotion data sent. After receiving it, it analyzes the data using a generative AI model (e.g., GPT-3) and converts it into positive interpretation data. Specifically, the server receives the text "My colleague is always late, which is bothering me because it means more work," and sends it to the generative AI model along with the prompt, "Generate a positive interpretation for the specific emotion and a compliment based on the user's characteristics." The generative AI model analyzes it and outputs a positive interpretation, for example, "My colleague is able to work at his own pace and is clever about how he uses his time." The input is encrypted negative text data, and the output is text data converted into a positive one.

[0773] Step 4:

[0774] The server then generates positive traits for the user based on the user's profile data and past behavioral data. The server retrieves trait information from the user profile database and sends a prompt to the generative AI model: "Generate a compliment based on the user's traits." Specifically, the server generates a compliment such as, "You are a good problem-solver and a supportive member of the team." The input is the user's profile data, and the output is text data of the compliment.

[0775] Step 5:

[0776] The server sends the generated positive interpretation data and the user's positive characteristics information to the terminal. The terminal receives this data and displays it to the user, for example, as a pop-up message or on a dashboard. The input is the positive interpretation data and compliment text data sent from the server, and the output is a visual display of this to the user.

[0777] Through the above processing steps, this system can convert the user's negative emotions into positive ones and reduce the mental burden by helping the user to recognize their positive side.

[0778] (Application example 1)

[0779] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0780] In modern society, people often experience many negative emotions in their daily lives, which can become a mental burden. Furthermore, it is difficult to reframe negative emotions in a positive light, and there are limited means to improve self-esteem. Conventional systems face challenges in that they are unable to adequately alleviate negative emotions or suggest positive interpretations. Furthermore, they do not provide appropriate feedback to help users recognize their own positive aspects. Therefore, there is a need for a system that can effectively transform the negative emotions users experience in their daily lives into positive ones and improve self-esteem.

[0781] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0782] In this invention, the server includes means for receiving negative emotion data input by a user using an electronic device, means for converting the received negative emotion data into positive interpretation data using a conversion device, means for analyzing the user's characteristic data and generating positive characteristics for the user, means for displaying the positive interpretation data and the user's positive characteristics to the user, means for transmitting the generated data to the user's terminal via a secure communication protocol, and means for displaying a correlation between the negative emotion data input by the user and the converted positive interpretation data. This converts the negative emotion input by the user into a positive one and helps the user recognize their positive aspects, thereby reducing mental burden and improving self-esteem.

[0783] An "electronic device" is a device that allows a user to input or view information, and examples include smartphones and tablets.

[0784] "Negative emotion data" is information that expresses negative emotions such as discomfort or dissatisfaction felt by the user.

[0785] A "conversion device" is a system or module for converting input negative emotional data into positive interpretation data.

[0786] "Positive interpretation data" is information that reinterprets negative emotional data in a favorable or positive way.

[0787] "Characteristic data" is information relating to the user's personality and behavioral characteristics, and includes profile data and behavioral history.

[0788] "Positive characteristics" are information that indicates the user's good points or outstanding characteristics.

[0789] "Display means" refers to an interface for visually presenting information to a user, and includes a screen, a display, and the like.

[0790] A "secure communication protocol" is a communication standard for securely sending and receiving data, and examples include HTTPS and SSL / TLS.

[0791] A "generative AI model" is an algorithm or system that uses artificial intelligence to perform a specific task or data transformation.

[0792] A "prompt sentence" is an instruction or question sentence input to a generative AI model.

[0793] This invention is a system that converts a user's negative emotions into positive ones and reduces mental burden by helping the user recognize their positive side. This system is composed of multiple elements, including electronic devices, servers, and generative AI models.

[0794] Hardware and software used

[0795] Hardware:

[0796] Smartphone

[0797] server

[0798] software:

[0799] Application: React Native (front-end)

[0800] Server framework: Flask

[0801] Generative AI model: GPT-4 (OpenAI)

[0802] Communication protocol: HTTPS

[0803] Database: PostgreSQL

[0804] Operational Overview

[0805] 1. Receiving emotional input

[0806] A user uses a smartphone as an electronic device and inputs negative emotional data into the emotion input interface, for example, by entering an emotion such as "I failed at work. I no longer have confidence" into a text field.

[0807] 2. Data transmission

[0808] The input negative emotion data is sent to the server via a secure communication protocol (HTTPS), and the server receives this data securely.

[0809] 3. Transforming negative emotions into positive ones

[0810] The server analyzes the received negative emotion data using a generative AI model (GPT-4), which converts negative emotions into positive interpretation data based on pre-trained prompts.

[0811] Example: A negative emotion, "I failed at work. I no longer have confidence in myself," can be transformed into a positive interpretation, "This failure is an opportunity to learn a lot and rebuild my confidence."

[0812] 4. Analyzing the positive aspects of users

[0813] The server analyzes the user's characteristic data, which is based on the user's profile data and past behavior data, and generates positive attributes and traits for the user based on this data.

[0814] For example, a compliment such as "You are a great problem solver and a great support for the team" may be generated.

[0815] 5. Displaying the results

[0816] The server sends the generated positive interpretation data and the user's positive characteristics to the user's device, which receives it and displays it on the screen. The user can see how their negative emotions have been transformed into positive ones and their own positive aspects.

[0817] Prompt Sentence Examples

[0818] Negative Emotion: "I failed at work. I no longer have confidence."

[0819] Positive Transformation: "Failure is an opportunity to learn a lot and rebuild your confidence."

[0820] In this way, this invention effectively transforms the negative emotions that users have in their daily lives into positive ones, and by making users recognize their own good sides, it is possible to reduce mental burden and improve self-esteem.

[0821] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0822] Step 1:

[0823] This is a step in which the user inputs negative emotion data using an electronic device (smartphone).

[0824] Input: The user enters emotion data in the text field: "I failed at work. I no longer have confidence."

[0825] Output: The input emotion data is received by the terminal.

[0826] Specific operation: The user enters emotions in text format into the application's input interface and presses the "Send" button.

[0827] Step 2:

[0828] This is a step in which the terminal transmits the received negative emotion data to the server.

[0829] Input: User-entered negative sentiment data.

[0830] Output: Negative sentiment data sent to the server.

[0831] Specific operation: The device sends the input emotion data to the server using a secure communication protocol (HTTPS).

[0832] Step 3:

[0833] This is the step where the server analyzes the negative emotional data received using a generative AI model to generate positive interpretation data.

[0834] Input: Negative emotion data received by the server.

[0835] Output: Generated positive interpretation data.

[0836] Specific operation: The server inputs the received emotional data into a generative AI model (e.g., GPT-4) and generates positive interpretation data such as, "This is an opportunity to learn a lot from your failure and rebuild your confidence."

[0837] Step 4:

[0838] The server analyzes the user's characteristic data and generates positive characteristics for the user.

[0839] Input: User characteristic data stored on the server (profile data and past behavioral data).

[0840] Output: Generated positive trait data of the user.

[0841] Specific operation: The server retrieves the user's characteristic data from the database, analyzes it, and generates positive characteristic data such as, "You have excellent problem-solving skills and are a supportive member of the team."

[0842] Step 5:

[0843] The server transmits the generated positive interpretation data and the user's positive characteristic data to the user's terminal.

[0844] Input: Generated positive interpretation data and user positive characteristic data.

[0845] Output: Data sent to the user's device.

[0846] Specific operation: The server transmits the positive interpretation data and the user's positive characteristic data to the user's terminal using a secure communication protocol (HTTPS).

[0847] Step 6:

[0848] This is the step in which the user's terminal displays the received data to the user.

[0849] Input: Positive interpretation data received from the server and positive characteristic data of the user.

[0850] Output: The data that is displayed to the user.

[0851] Specific operation: The positive interpretation data received by the terminal and the user's positive characteristic data are displayed on the application screen and presented to the user as feedback.

[0852] Step 7:

[0853] This is a step of displaying the association between the negative emotion data input by the user and the converted positive interpretation data.

[0854] Input: Negative emotion data and corresponding positive interpretation data.

[0855] Output: A screen showing the correlation.

[0856] Specific operation: The device displays negative emotion data and positive interpretation data on the screen in contrast, clearly showing the user how negative emotions have been transformed into positive ones.

[0857] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0858] This system receives negative emotional data input by a user using an electronic device, converts it into positive interpretation data, and helps the user recognize their positive aspects, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, a conversion device (generative AI model), and an emotion engine.

[0859] User Input Processing

[0860] A user inputs his / her negative emotions through an input interface of an electronic device or through input to an emotion engine. Negative emotions can be input as text into the interface of the electronic device, or the emotion engine can analyze multimodal data such as voice, facial expressions, and gestures to recognize negative emotion data. For example, a user can input "I'm having trouble because my colleague is late, which means more work for me," and the emotion engine can recognize the user's stress from their voice and facial expressions.

[0861] Processing data transmission

[0862] The device sends the input negative emotion data to the server, using a secure communication protocol (e.g., HTTPS) to ensure the safety of the data.

[0863] Transforming negative emotions into positive ones

[0864] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[0865] Analyzing the positive aspects of users

[0866] The server then analyzes the user's positive aspects based on the user's characteristic data. This analysis utilizes user profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "excellent problem-solving skills."

[0867] Displaying the results

[0868] The server transmits the generated positive interpretation data and the user's positive aspects to the device using a secure protocol.

[0869] The device then displays the received data to the user, such as a message like, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0870] Specific examples

[0871] For example, if a user types in text, "My colleague is always late, which is causing me a lot of work," that data is sent from the device to the server. Alternatively, the emotion engine can recognize the user's stress from their voice and facial expressions and send the data in a similar manner. The server then uses a generative AI model to convert this negative emotion data into, "My colleague is able to work at his or her own pace and is good at time management." Furthermore, it can generate compliments from the user's characteristic data, such as, "You are a good problem-solver and a supportive member of the team." When these results are displayed on the device, the user can confirm the positive interpretation and reaffirm their own positive aspects, thereby reducing their mental burden.

[0872] This embodiment allows users to transform negative emotions that arise in their daily lives into positive ones and to rediscover their positive aspects, thereby reducing further mental burdens. This process is an effective way to support the user's mental health.

[0873] The processing flow will be explained below.

[0874] Step 1:

[0875] A user accesses the interface of an electronic device, and either the user inputs negative emotion data in text, or the emotion engine recognizes negative emotions from the user's voice, facial expressions, gestures, etc.

[0876] Step 2:

[0877] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[0878] Step 3:

[0879] The server analyzes the received negative emotion data and formats it into text.

[0880] Step 4:

[0881] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data, for example, converting "My colleague is always late, which causes me to have more work to do" into "My colleague works at his own pace and is good at time management."

[0882] Step 5:

[0883] The server analyzes the user's characteristic data, using user profile data and past interaction data to extract the user's strengths and positive characteristics.

[0884] Step 6:

[0885] The server generates compliments based on the extracted positive characteristics of the user. For example, it recognizes user characteristics such as "valuing time" and "good problem-solving skills" and generates a compliment such as "You have good problem-solving skills and are a great support for the team."

[0886] Step 7:

[0887] The server transmits the generated positive interpretation data and the user's positive characteristics to the terminal using a secure protocol.

[0888] Step 8:

[0889] The terminal receives the data from the server and converts it into a displayable format.

[0890] Step 9:

[0891] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[0892] Step 10:

[0893] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[0894] Example 2

[0895] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0896] In modern living environments, users are often exposed to negative emotions on a daily basis, which can easily increase their mental burden. However, it is not easy to deal with these negative emotions on one's own, and they often cause stress and anxiety. To address this issue, a system is needed that can reduce mental burden by helping users reframe negative emotions in a positive way.

[0897] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0898] In this invention, the server includes means for receiving negative emotion data input by a user using a communication terminal, means for analyzing the received negative emotion data and generating positive interpretation data using a generative AI model, and means for generating positive characteristics of the user based on the user's profile data and past interaction data. This allows the user to convert negative emotions into positive ones and re-identify them, thereby reducing mental burden.

[0899] A "communication terminal" is an electronic device that a user uses to input and transmit negative emotional data, and examples include smartphones and personal computers.

[0900] "Negative emotion data" is data that expresses negative emotions felt by the user, and is input in the form of text, voice, facial expressions, gestures, or the like.

[0901] A "secure communication protocol" is a set of rules for ensuring the safety of data communication, such as HTTPS.

[0902] "Server" means a computer system for analyzing received negative emotional data and generating positive interpretation data and positive characteristics of the user using a generative AI model.

[0903] A "generative AI model" is an artificial intelligence model used to convert negative emotional data into positive interpretation data, and examples include models that use natural language processing techniques.

[0904] "Profile data" is a database containing attribute information and past interaction data about a user, and is data that is referenced to generate positive characteristics of the user.

[0905] "Positive interpretation data" is data that shows a positive interpretation converted from negative emotional data by a generative AI model.

[0906] "Positive traits" are traits that show the positive aspects of a user and are generated based on the user's profile data and past interaction data.

[0907] The present invention is a system that receives negative emotional data input by a user using a communication terminal, converts it into positive interpretation data, and further generates and displays positive characteristics based on the user's characteristic data. The system of the present invention aims to convert the negative emotional data input by the user into positive data, thereby reducing the user's mental burden.

[0908] Hardware and Software Configuration

[0909] This system consists of elements such as communication terminals, servers, generative AI models, emotion engines, and databases.

[0910] communication terminal

[0911] Users input negative emotions using a communication device (e.g., smartphone or personal computer). A dedicated application or web form is installed on the communication device, and users use this to input emotions using text, voice, facial expressions, etc. The emotion engine analyzes the emotion data using voice recognition software (e.g., Google speech-to-text API) and facial expression recognition software (e.g., Microsoft Azure Face API).

[0912] server

[0913] The server receives the negative emotional data sent from the communication device. The received data is transferred using a secure communication protocol (e.g., HTTPS). The server then uses a generative AI model (e.g., OpenAI GPT-3) to convert the negative emotional data into positive interpretation data. The server then references a database that stores the user's profile data and past interaction data to extract and generate positive characteristics for the user.

[0914] Specific examples

[0915] For example, if a user uses a dedicated application to input text such as "My colleague is late, which is causing me a lot of work," the data is sent from the communication device to the server. Negative emotion data input through voice input or facial recognition is also processed in the same way.

[0916] The server sends the received data to the generative AI model as a prompt. For example, the user might input, "When a user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way." The generative AI model generates positive interpretation data, such as, "My colleague works at his own pace and is good at time management."

[0917] Next, the server checks the database for the user's characteristic of "valuing time" and generates a compliment such as "You have excellent problem-solving skills and are a great support for the team." The server then sends the generated positive interpretation data and the compliment to the communication terminal, which then displays it to the user.

[0918] This allows the user to convert the negative emotions they input into positive interpretations, and by rediscovering their positive aspects, they can reduce their mental burden. Through this process, the present invention provides an effective means of supporting the user's mental health.

[0919] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0920] Program processing flow

[0921] Step 1: User Input

[0922] Users input negative emotional data using a communication device. Specifically, they can input it as text through a dedicated application or web form displayed on the device. They can also input facial expressions and gestures using voice input or a camera.

[0923] Input: Negative emotion text, audio data, facial expression data

[0924] Output: Negative sentiment data (text format)

[0925] Examples of specific actions:

[0926] A user opens the app and types in the text, "My colleague is late, which is causing me a lot of work."

[0927] Select voice input and speak the same phrase to input.

[0928] Step 2: Send data

[0929] The device transmits the input negative emotion data to the server using a secure communication protocol (e.g., HTTPS).

[0930] Input: Negative emotion data (text format)

[0931] Output: Negative emotion data sent to the server

[0932] Examples of specific actions:

[0933] The device sends text data such as "My colleague is late, so I have more work to do and it's bothering me" to the server using the HTTPS protocol.

[0934] Step 3: Transform negative emotions into positive ones

[0935] The server analyzes the received negative emotion data and converts it into positive interpretation data using a generative AI model. The prompt text is entered as "When the user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way."

[0936] Input: Negative emotion data, prompt sentence

[0937] Output: Positive interpretation data

[0938] Examples of specific actions:

[0939] The server receives data such as "My colleague is late, which is causing me a lot of work" and sends it to the generative AI model, which then receives positive interpretation data such as "My colleague works at his own pace and is good at managing his time."

[0940] Step 4: Analyze the positive aspects of your users

[0941] The server extracts and generates positive characteristics of the user based on the user's profile data and past interaction data.

[0942] Input: User profile data, past interaction data

[0943] Output: Positive characteristic data

[0944] Examples of specific actions:

[0945] The database is used to confirm that the user has an "attitude of valuing time," and based on that characteristic, a compliment such as "You have excellent problem-solving skills and are a great support for the team" is generated.

[0946] Step 5: View the results

[0947] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, again using a secure communication protocol (e.g., HTTPS). The terminal displays the received data to the user.

[0948] Input: Positive interpretation data, positive characteristic data

[0949] Output: A positive message that the user sees

[0950] Examples of specific actions:

[0951] The device will display messages such as, "Your colleagues work at their own pace and manage their time effectively. You also have excellent problem-solving skills and are a supportive member of the team."

[0952] keyword

[0953] Generative AI model, prompt sentence

[0954] (Application example 2)

[0955] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0956] The problem that this invention aims to solve is to convert negative emotions that users experience in their daily lives into positive ones, thereby reducing the user's mental burden. Furthermore, the invention aims to support the user's mental health by analyzing their characteristics and helping them recognize their positive aspects. In particular, by providing this function in content distribution services, the invention aims to provide an environment in which users can reduce stress and have a positive experience.

[0957] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0958] In this invention, the server includes means for analyzing negative emotion data and converting it into positive interpretation data, means for generating positive characteristics of the user based on the user's characteristic data, means for displaying the positive interpretation data and the user's positive characteristics on a content distribution service terminal, means for analyzing negative emotion data based on voice and text input using an emotion engine, and means for transmitting the negative emotion data using a secure communication protocol. This allows the user to convert negative emotions into positive ones and rediscover their own positive aspects, thereby reducing mental burden.

[0959] "Electronic Device" means a device used by a user to process and display input data, such as a smartphone, computer, or tablet.

[0960] "Negative emotion data" is information entered by the user regarding negative emotions such as stress and anxiety.

[0961] A "conversion device" is a system or device for converting received data into another format or content, including a generative AI model.

[0962] "Positive interpretation data" is data that converts negative emotional data into a positive meaning.

[0963] "Characteristic data" is data including user behavior, preferences, personality traits, and the like.

[0964] "Analyzing" means using data statistics and algorithms to extract information and patterns from data.

[0965] "Display" means to visually present information to a user, such as through a device screen.

[0966] A "system" is a set of structures or devices consisting of multiple elements that are interrelated and function in concert.

[0967] A "server" is a computer system that stores and manages data over a network and provides services to client devices.

[0968] "Secure communications protocol" means a communications method used to ensure the secure transmission of data, including HTTPS.

[0969] "Content distribution services" are services that provide video, audio, text, or other content via electronic devices, including online streaming services and digital libraries.

[0970] An "emotion engine" is a software or hardware engine for analyzing emotions from speech, text, and other input data.

[0971] The present invention is a system that receives negative emotional data from a user using an electronic device, converts it into positive interpretation data, and then analyzes the user's characteristics to generate and display the user's positive characteristics. A specific example of how this system can be realized is shown below.

[0972] The system consists of the following elements:

[0973] Electronic Device: A device used by a user, such as a smartphone or tablet.

[0974] Sentiment Engine: Software that recognizes negative emotions based on voice and text input. Uses the Google Cloud Natural Language API.

[0975] Server: A device that receives and analyzes negative emotional data and converts it into positive interpretation data using a generative AI model (OpenAI GPT-4).

[0976] Generative AI model: An AI model used to convert negative sentiment data into positive interpretation data.

[0977] Secure communication protocol: A communication method that uses HTTPS to ensure data security.

[0978] Content distribution service: A service that allows users to see positive interpretation data and positive characteristics of users.

[0979] The user inputs negative emotions using an electronic device. This input can be via text or voice. The emotion engine analyzes this input and recognizes negative emotion data. The recognized negative emotion data is sent to the server using a secure communication protocol. The server converts the received data into positive interpretation data using a generative AI model, and further generates positive traits based on the user's trait data.

[0980] For example, if a user inputs "My colleague is late, which causes me to have more work to do," the emotion engine analyzes this input data and recognizes stress and frustration. The server receives this negative emotion data and inputs it into a generative AI model (OpenAI GPT-4). The generative AI model generates a positive interpretation, such as:

[0981] "My colleagues are able to work at their own pace and are good at time management." In addition, the server extracts user characteristics from the user profile and generates positive characteristics such as:

[0982] "You're a great problem solver and a great support for the team."

[0983] The results are displayed on the user's electronic device through a content distribution service, allowing the user to rediscover their positive interpretations and positive traits, and feel a reduction in their mental burden.

[0984] Example prompt sentence:

[0985] Take the negative sentence: "My coworker is late, which means I have more work to do" and turn it into a positive one.

[0986] In this way, the present invention provides an effective means for converting negative emotions into positive ones and supporting the mental health of users by further analyzing their characteristics.

[0987] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0988] Step 1:

[0989] A user inputs negative emotions using an electronic device.

[0990] Input: The user inputs negative emotions via text or voice.

[0991] Data processing / data calculation: The emotion engine analyzes the user's input data and recognizes negative emotion data.

[0992] Output: Parsed negative sentiment data.

[0993] Step 2:

[0994] The device transmits negative emotional data to a server using a secure communication protocol (HTTPS).

[0995] Input: Parsed negative sentiment data.

[0996] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[0997] Output: Securely transmitted negative sentiment data.

[0998] Step 3:

[0999] The server analyzes the negative emotional data it receives and converts it into positive interpretation data using a generative AI model.

[1000] Input: Received negative sentiment data.

[1001] Data processing / data calculation: Input data into a generative AI model, analyze it, and generate positive interpretation data.

[1002] Output: Positive interpretive data.

[1003] Step 4:

[1004] The server generates positive characteristic data based on the user's characteristic data.

[1005] Input: User profile data and past interaction data.

[1006] Data processing / data calculation: Analyze user characteristic data and extract positive characteristics.

[1007] Output: Positive trait data of the user.

[1008] Step 5:

[1009] The server transmits the generated positive interpretation data and the user's positive characteristic data to the terminal using a secure communication protocol (HTTPS).

[1010] Input: Positive interpretation data and positive user characteristic data.

[1011] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[1012] Output: Securely transmitted positive interpretation and characterization data.

[1013] Step 6:

[1014] The terminal displays the received positive interpretation data and the user's positive characteristic data to the user.

[1015] Input: Securely transmitted positive interpretation data and positive user characteristic data.

[1016] Data processing / data calculation: Analyzes received data and converts it into a display format.

[1017] Output: Positive interpretation and characteristic data displayed to the user.

[1018] As a specific example of how it works, a user might input, "My colleague is always late, which is causing me a lot of work." The emotion engine analyzes this input and recognizes negative emotions. The recognized data is sent to the server, where the generative AI model converts it into a positive interpretation: "My colleague is able to work at his own pace and is good at time management." The server then generates a positive characteristic based on the user profile: "You are a good problem-solver and a supportive member of the team," which the device displays to the user.

[1019] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1020] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1021] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1022] [Fourth embodiment]

[1023] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1024] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1026] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1027] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1028] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1030] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1031] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1032] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1034] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1036] The present invention is a system that receives negative emotional data input by a user using an electronic device, converts it into positive emotions, and helps the user recognize their positive side, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, and a conversion device.

[1037] User Input Processing

[1038] The user inputs his or her negative emotions into the input interface of the electronic device, for example, "I don't like that colleague because he or she is always late and doesn't help me with my work."

[1039] Processing data transmission

[1040] The device transmits the input negative emotion data to the server, preferably using a secure communication protocol.

[1041] Transforming negative emotions into positive ones

[1042] The server analyzes the received negative emotional data and converts it into positive interpretation data using a conversion device, i.e., a generative AI model. For example, the positive interpretation might be, "That colleague can do things at their own pace and is independent."

[1043] Analyzing the positive aspects of users

[1044] The server then analyzes the user's positive attributes based on the user's characteristic data, including user profile data and past behavioral data. As a result of the analysis, it generates compliments such as "You are very honest" or "You are responsible and value your time."

[1045] Displaying the results

[1046] The server sends the generated positive interpretation data and the user's good points to the device, which then displays the received data to the user. This allows the user to see how their negative emotions have been transformed into positive ones, and further reduces the burden on their mind by reaffirming their positive aspects.

[1047] Specific examples

[1048] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[1049] This system allows users to reframe negative emotions that arise in their daily lives in a positive light, rediscovering their own positive aspects and reducing mental stress.

[1050] The processing flow will be explained below.

[1051] Step 1:

[1052] An interface is displayed that allows a user to input emotional data using an electronic device. For example, the user inputs negative emotional data such as "My colleague is late, so I have more work to do, which is bothering me."

[1053] Step 2:

[1054] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[1055] Step 3:

[1056] The server receives the negative emotion data and formats it into text for analysis.

[1057] Step 4:

[1058] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[1059] Step 5:

[1060] The server analyzes the user's characteristic data. The analysis uses the user's registered profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "high problem-solving ability."

[1061] Step 6:

[1062] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, also using the HTTPS protocol.

[1063] Step 7:

[1064] The terminal receives the data from the server and converts it into a displayable format.

[1065] Step 8:

[1066] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[1067] Step 9:

[1068] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[1069] Example 1

[1070] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1071] In modern society, users often experience various negative emotions in their daily lives and work. These negative emotions can have a negative impact on users' mental health, as well as on their productivity and interpersonal relationships. Conventional technologies lack a means to effectively transform these negative emotions into positive ones and reduce the user's mental burden. The present invention aims to solve these problems by providing a system that transforms negative emotions into positive ones and reduces the user's mental burden by helping them recognize their positive aspects.

[1072] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1073] In this invention, the server includes means for receiving negative emotional data input by a user using an electronic device, means for transmitting the received negative emotional data to the server using a communication protocol, means for the server to convert the negative emotional data into positive interpretation data using a generative AI model, means for the server to generate positive characteristics of the user based on the user's profile data, and means for displaying the positive interpretation data and the user's positive characteristics to the user. This makes it possible to effectively convert negative emotions into positive ones and reduce the user's mental burden by helping them recognize their positive aspects.

[1074] "Negative emotion data" is data entered in text format that describes negative emotions such as dissatisfaction, stress, sadness, etc. that the user feels.

[1075] "Electronic devices" refer to devices such as smartphones, tablets, and personal computers that can be operated by the user.

[1076] A "communication protocol" is a set of rules used to ensure security and reliability when sending and receiving data between electronic devices and servers, and one example is HTTPS.

[1077] A "server" is a computer system for processing received negative emotional data and generating positive interpretation data.

[1078] A "generative AI model" is an artificial intelligence model that learns from large amounts of data to generate text, and plays a role in converting negative emotional data into positive ones.

[1079] "Positive interpretation data" is text data with positive and affirmative content generated by a generative AI model based on negative emotional data.

[1080] "User profile data" refers to a group of data in a database that includes characteristic information and past behavioral history about individual users.

[1081] "User's positive characteristics" is data that indicates the user's advantages and strengths, extracted based on the user's profile data.

[1082] The "display means" is a mechanism for visually presenting the positive interpretation data and the user's positive characteristics to the user on the screen of an electronic device.

[1083] This system receives negative emotional data input by a user using an electronic device, converts it into positive emotion, and helps the user recognize their positive side, thereby reducing their mental burden. The system is composed of multiple elements, including an electronic device, a server, and a generative AI model.

[1084] User Input Processing

[1085] The user inputs their negative emotions into the input interface of the electronic device. The input data is stored in text format. For example, a sentence such as "My colleague is late, so I have more work to do, which is a problem" is input. The input field includes a text field and a submit button.

[1086] Processing data transmission

[1087] The device sends the entered negative emotion data to the server. At this time, the data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is clicked, the device encrypts the data and sends a POST request to the server using the HTTPS protocol.

[1088] Transforming negative emotions into positive ones

[1089] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model (e.g., GPT-3). For example, a negative input such as "My colleague is always late, which causes me to have more work" can be converted into a positive interpretation such as "My colleague is able to work at his own pace and is good at managing his time."

[1090] Analyzing the positive aspects of users

[1091] The server then analyzes the user's positive aspects based on their profile data and past behavioral data. For example, it generates compliments such as, "You are a good problem-solver and a great supporter of the team." The server retrieves the user's characteristic information from the user profile database and sends prompts to the generative AI model.

[1092] Displaying the results

[1093] The server sends the generated positive interpretation data and information about the user's positive characteristics to the device, which then displays the received data to the user, allowing the user to see how their negative emotions have been transformed into positive ones and to rediscover their own positive aspects.

[1094] Specific examples

[1095] For example, if a user inputs "My colleague is always late, which is bothering me because it means more work," the data is sent from the device to the server. The server then uses generative AI to convert this negative emotional data into a positive interpretation, generating the sentence, "My colleague is able to work at her own pace and is creative in how she uses her time." Furthermore, it uses the user's characteristic data to generate a compliment, such as, "You have excellent problem-solving skills and are a great support for the team." When the device displays these results to the user, the user's negative emotions are alleviated and they are able to rediscover their positive aspects.

[1096] Prompt Sentence Examples

[1097] "Generate positive interpretations of specific emotions and compliments based on the user's characteristics."

[1098] In this way, the present invention provides a concrete means for users to reframe negative emotions that arise in their daily lives in a positive light, rediscover their own positive aspects, and reduce mental burden.

[1099] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1100] Step 1:

[1101] The user inputs negative emotional data into the input interface of an electronic device. The input data is stored in text format. Specifically, the user enters "My colleague is late, so I have more work to do, which is a problem" into the text field and presses the send button. This text data is the input. The output is the input text data itself.

[1102] Step 2:

[1103] The terminal sends the entered negative emotion data to the server. The data is sent securely using a secure communication protocol (e.g., HTTPS). When the send button is pressed, the terminal encrypts the text data and sends it to the server as a POST request. The input is the text data entered by the user, and the output is the encrypted text data.

[1104] Step 3:

[1105] The server receives the negative emotion data sent. After receiving it, it analyzes the data using a generative AI model (e.g., GPT-3) and converts it into positive interpretation data. Specifically, the server receives the text "My colleague is always late, which is bothering me because it means more work," and sends it to the generative AI model along with the prompt, "Generate a positive interpretation for the specific emotion and a compliment based on the user's characteristics." The generative AI model analyzes it and outputs a positive interpretation, for example, "My colleague is able to work at his own pace and is clever about how he uses his time." The input is encrypted negative text data, and the output is text data converted into a positive one.

[1106] Step 4:

[1107] The server then generates positive traits for the user based on the user's profile data and past behavioral data. The server retrieves trait information from the user profile database and sends a prompt to the generative AI model: "Generate a compliment based on the user's traits." Specifically, the server generates a compliment such as, "You are a good problem-solver and a supportive member of the team." The input is the user's profile data, and the output is text data of the compliment.

[1108] Step 5:

[1109] The server sends the generated positive interpretation data and the user's positive characteristics information to the terminal. The terminal receives this data and displays it to the user, for example, as a pop-up message or on a dashboard. The input is the positive interpretation data and compliment text data sent from the server, and the output is a visual display of this to the user.

[1110] Through the above processing steps, this system can convert the user's negative emotions into positive ones and reduce the mental burden by helping the user to recognize their positive side.

[1111] (Application example 1)

[1112] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1113] In modern society, people often experience many negative emotions in their daily lives, which can become a mental burden. Furthermore, it is difficult to reframe negative emotions in a positive light, and there are limited means to improve self-esteem. Conventional systems face challenges in that they are unable to adequately alleviate negative emotions or suggest positive interpretations. Furthermore, they do not provide appropriate feedback to help users recognize their own positive aspects. Therefore, there is a need for a system that can effectively transform the negative emotions users experience in their daily lives into positive ones and improve self-esteem.

[1114] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1115] In this invention, the server includes means for receiving negative emotion data input by a user using an electronic device, means for converting the received negative emotion data into positive interpretation data using a conversion device, means for analyzing the user's characteristic data and generating positive characteristics for the user, means for displaying the positive interpretation data and the user's positive characteristics to the user, means for transmitting the generated data to the user's terminal via a secure communication protocol, and means for displaying a correlation between the negative emotion data input by the user and the converted positive interpretation data. This converts the negative emotion input by the user into a positive one and helps the user recognize their positive aspects, thereby reducing mental burden and improving self-esteem.

[1116] An "electronic device" is a device that allows a user to input or view information, and examples include smartphones and tablets.

[1117] "Negative emotion data" is information that expresses negative emotions such as discomfort or dissatisfaction felt by the user.

[1118] A "conversion device" is a system or module for converting input negative emotional data into positive interpretation data.

[1119] "Positive interpretation data" is information that reinterprets negative emotional data in a favorable or positive way.

[1120] "Characteristic data" is information relating to the user's personality and behavioral characteristics, and includes profile data and behavioral history.

[1121] "Positive characteristics" are information that indicates the user's good points or outstanding characteristics.

[1122] "Display means" refers to an interface for visually presenting information to a user, and includes a screen, a display, and the like.

[1123] A "secure communication protocol" is a communication standard for securely sending and receiving data, and examples include HTTPS and SSL / TLS.

[1124] A "generative AI model" is an algorithm or system that uses artificial intelligence to perform a specific task or data transformation.

[1125] A "prompt sentence" is an instruction or question sentence input to a generative AI model.

[1126] This invention is a system that converts a user's negative emotions into positive ones and reduces mental burden by helping the user recognize their positive side. This system is composed of multiple elements, including electronic devices, servers, and generative AI models.

[1127] Hardware and software used

[1128] Hardware:

[1129] Smartphone

[1130] server

[1131] software:

[1132] Application: React Native (front-end)

[1133] Server framework: Flask

[1134] Generative AI model: GPT-4 (OpenAI)

[1135] Communication protocol: HTTPS

[1136] Database: PostgreSQL

[1137] Operational Overview

[1138] 1. Receiving emotional input

[1139] A user uses a smartphone as an electronic device and inputs negative emotional data into the emotion input interface, for example, by entering an emotion such as "I failed at work. I no longer have confidence" into a text field.

[1140] 2. Data transmission

[1141] The input negative emotion data is sent to the server via a secure communication protocol (HTTPS), and the server receives this data securely.

[1142] 3. Transforming negative emotions into positive ones

[1143] The server analyzes the received negative emotion data using a generative AI model (GPT-4), which converts negative emotions into positive interpretation data based on pre-trained prompts.

[1144] Example: A negative emotion, "I failed at work. I no longer have confidence in myself," can be transformed into a positive interpretation, "This failure is an opportunity to learn a lot and rebuild my confidence."

[1145] 4. Analyzing the positive aspects of users

[1146] The server analyzes the user's characteristic data, which is based on the user's profile data and past behavior data, and generates positive attributes and traits for the user based on this data.

[1147] For example, a compliment such as "You are a great problem solver and a great support for the team" may be generated.

[1148] 5. Displaying the results

[1149] The server sends the generated positive interpretation data and the user's positive characteristics to the user's device, which receives it and displays it on the screen. The user can see how their negative emotions have been transformed into positive ones and their own positive aspects.

[1150] Prompt Sentence Examples

[1151] Negative Emotion: "I failed at work. I no longer have confidence."

[1152] Positive Transformation: "Failure is an opportunity to learn a lot and rebuild your confidence."

[1153] In this way, this invention effectively transforms the negative emotions that users have in their daily lives into positive ones, and by making users recognize their own good sides, it is possible to reduce mental burden and improve self-esteem.

[1154] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1155] Step 1:

[1156] This is a step in which the user inputs negative emotion data using an electronic device (smartphone).

[1157] Input: The user enters emotion data in the text field: "I failed at work. I no longer have confidence."

[1158] Output: The input emotion data is received by the terminal.

[1159] Specific operation: The user enters emotions in text format into the application's input interface and presses the "Send" button.

[1160] Step 2:

[1161] This is a step in which the terminal transmits the received negative emotion data to the server.

[1162] Input: User-entered negative sentiment data.

[1163] Output: Negative sentiment data sent to the server.

[1164] Specific operation: The device sends the input emotion data to the server using a secure communication protocol (HTTPS).

[1165] Step 3:

[1166] This is the step where the server analyzes the negative emotional data received using a generative AI model to generate positive interpretation data.

[1167] Input: Negative emotion data received by the server.

[1168] Output: Generated positive interpretation data.

[1169] Specific operation: The server inputs the received emotional data into a generative AI model (e.g., GPT-4) and generates positive interpretation data such as, "This is an opportunity to learn a lot from your failure and rebuild your confidence."

[1170] Step 4:

[1171] The server analyzes the user's characteristic data and generates positive characteristics for the user.

[1172] Input: User characteristic data stored on the server (profile data and past behavioral data).

[1173] Output: Generated positive trait data of the user.

[1174] Specific operation: The server retrieves the user's characteristic data from the database, analyzes it, and generates positive characteristic data such as, "You have excellent problem-solving skills and are a supportive member of the team."

[1175] Step 5:

[1176] The server transmits the generated positive interpretation data and the user's positive characteristic data to the user's terminal.

[1177] Input: Generated positive interpretation data and user positive characteristic data.

[1178] Output: Data sent to the user's device.

[1179] Specific operation: The server transmits the positive interpretation data and the user's positive characteristic data to the user's terminal using a secure communication protocol (HTTPS).

[1180] Step 6:

[1181] This is the step in which the user's terminal displays the received data to the user.

[1182] Input: Positive interpretation data received from the server and positive characteristic data of the user.

[1183] Output: The data that is displayed to the user.

[1184] Specific operation: The positive interpretation data received by the terminal and the user's positive characteristic data are displayed on the application screen and presented to the user as feedback.

[1185] Step 7:

[1186] This is a step of displaying the association between the negative emotion data input by the user and the converted positive interpretation data.

[1187] Input: Negative emotion data and corresponding positive interpretation data.

[1188] Output: A screen showing the correlation.

[1189] Specific operation: The device displays negative emotion data and positive interpretation data on the screen in contrast, clearly showing the user how negative emotions have been transformed into positive ones.

[1190] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1191] This system receives negative emotional data input by a user using an electronic device, converts it into positive interpretation data, and helps the user recognize their positive aspects, thereby reducing their mental burden. This system is composed of multiple elements, including an electronic device, a server, a conversion device (generative AI model), and an emotion engine.

[1192] User Input Processing

[1193] A user inputs his / her negative emotions through an input interface of an electronic device or through input to an emotion engine. Negative emotions can be input as text into the interface of the electronic device, or the emotion engine can analyze multimodal data such as voice, facial expressions, and gestures to recognize negative emotion data. For example, a user can input "I'm having trouble because my colleague is late, which means more work for me," and the emotion engine can recognize the user's stress from their voice and facial expressions.

[1194] Processing data transmission

[1195] The device sends the input negative emotion data to the server, using a secure communication protocol (e.g., HTTPS) to ensure the safety of the data.

[1196] Transforming negative emotions into positive ones

[1197] The server analyzes the received negative emotional data and converts it into positive interpretation data using a generative AI model. For example, "My colleague is always late, which causes me to have more work to do" is converted into a positive interpretation: "My colleague works at his own pace and is good at time management."

[1198] Analyzing the positive aspects of users

[1199] The server then analyzes the user's positive aspects based on the user's characteristic data. This analysis utilizes user profile data and past interaction data. The server extracts the user's strengths and generates compliments. For example, the server recognizes user characteristics such as "valuing time" and "excellent problem-solving skills."

[1200] Displaying the results

[1201] The server transmits the generated positive interpretation data and the user's positive aspects to the device using a secure protocol.

[1202] The device then displays the received data to the user, such as a message like, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[1203] Specific examples

[1204] For example, if a user types in text, "My colleague is always late, which is causing me a lot of work," that data is sent from the device to the server. Alternatively, the emotion engine can recognize the user's stress from their voice and facial expressions and send the data in a similar manner. The server then uses a generative AI model to convert this negative emotion data into, "My colleague is able to work at his or her own pace and is good at time management." Furthermore, it can generate compliments from the user's characteristic data, such as, "You are a good problem-solver and a supportive member of the team." When these results are displayed on the device, the user can confirm the positive interpretation and reaffirm their own positive aspects, thereby reducing their mental burden.

[1205] This embodiment allows users to transform negative emotions that arise in their daily lives into positive ones and to rediscover their positive aspects, thereby reducing further mental burdens. This process is an effective way to support the user's mental health.

[1206] The processing flow will be explained below.

[1207] Step 1:

[1208] A user accesses the interface of an electronic device, and either the user inputs negative emotion data in text, or the emotion engine recognizes negative emotions from the user's voice, facial expressions, gestures, etc.

[1209] Step 2:

[1210] The device sends the negative emotion data entered to the server, using the HTTPS protocol to ensure data security.

[1211] Step 3:

[1212] The server analyzes the received negative emotion data and formats it into text.

[1213] Step 4:

[1214] The server invokes the generative AI model and converts the received negative emotional data into positive interpretation data, for example, converting "My colleague is always late, which causes me to have more work to do" into "My colleague works at his own pace and is good at time management."

[1215] Step 5:

[1216] The server analyzes the user's characteristic data, using user profile data and past interaction data to extract the user's strengths and positive characteristics.

[1217] Step 6:

[1218] The server generates compliments based on the extracted positive characteristics of the user. For example, it recognizes user characteristics such as "valuing time" and "good problem-solving skills" and generates a compliment such as "You have good problem-solving skills and are a great support for the team."

[1219] Step 7:

[1220] The server transmits the generated positive interpretation data and the user's positive characteristics to the terminal using a secure protocol.

[1221] Step 8:

[1222] The terminal receives the data from the server and converts it into a displayable format.

[1223] Step 9:

[1224] The device displays positive interpretations and highlights the user's positive traits, such as, "Your colleagues work at their own pace and are good at time management. You are also a good problem-solver and a supportive team member."

[1225] Step 10:

[1226] The user can see the positive interpretation data and compliments displayed and feel their negative emotions ease. The user can reduce their mental burden through the positive perspective provided by the system.

[1227] Example 2

[1228] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1229] In modern living environments, users are often exposed to negative emotions on a daily basis, which can easily increase their mental burden. However, it is not easy to deal with these negative emotions on one's own, and they often cause stress and anxiety. To address this issue, a system is needed that can reduce mental burden by helping users reframe negative emotions in a positive way.

[1230] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1231] In this invention, the server includes means for receiving negative emotion data input by a user using a communication terminal, means for analyzing the received negative emotion data and generating positive interpretation data using a generative AI model, and means for generating positive characteristics of the user based on the user's profile data and past interaction data. This allows the user to convert negative emotions into positive ones and re-identify them, thereby reducing mental burden.

[1232] A "communication terminal" is an electronic device that a user uses to input and transmit negative emotional data, and examples include smartphones and personal computers.

[1233] "Negative emotion data" is data that expresses negative emotions felt by the user, and is input in the form of text, voice, facial expressions, gestures, or the like.

[1234] A "secure communication protocol" is a set of rules for ensuring the safety of data communication, such as HTTPS.

[1235] "Server" means a computer system for analyzing received negative emotional data and generating positive interpretation data and positive characteristics of the user using a generative AI model.

[1236] A "generative AI model" is an artificial intelligence model used to convert negative emotional data into positive interpretation data, and examples include models that use natural language processing techniques.

[1237] "Profile data" is a database containing attribute information and past interaction data about a user, and is data that is referenced to generate positive characteristics of the user.

[1238] "Positive interpretation data" is data that shows a positive interpretation converted from negative emotional data by a generative AI model.

[1239] "Positive traits" are traits that show the positive aspects of a user and are generated based on the user's profile data and past interaction data.

[1240] The present invention is a system that receives negative emotional data input by a user using a communication terminal, converts it into positive interpretation data, and further generates and displays positive characteristics based on the user's characteristic data. The system of the present invention aims to convert the negative emotional data input by the user into positive data, thereby reducing the user's mental burden.

[1241] Hardware and Software Configuration

[1242] This system consists of elements such as communication terminals, servers, generative AI models, emotion engines, and databases.

[1243] communication terminal

[1244] Users input negative emotions using a communication device (e.g., smartphone or personal computer). A dedicated application or web form is installed on the communication device, and users use this to input emotions using text, voice, facial expressions, etc. The emotion engine analyzes the emotion data using voice recognition software (e.g., Google speech-to-text API) and facial expression recognition software (e.g., Microsoft Azure Face API).

[1245] server

[1246] The server receives the negative emotional data sent from the communication device. The received data is transferred using a secure communication protocol (e.g., HTTPS). The server then uses a generative AI model (e.g., OpenAI GPT-3) to convert the negative emotional data into positive interpretation data. The server then references a database that stores the user's profile data and past interaction data to extract and generate positive characteristics for the user.

[1247] Specific examples

[1248] For example, if a user uses a dedicated application to input text such as "My colleague is late, which is causing me a lot of work," the data is sent from the communication device to the server. Negative emotion data input through voice input or facial recognition is also processed in the same way.

[1249] The server sends the received data to the generative AI model as a prompt. For example, the user might input, "When a user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way." The generative AI model generates positive interpretation data, such as, "My colleague works at his own pace and is good at time management."

[1250] Next, the server checks the database for the user's characteristic of "valuing time" and generates a compliment such as "You have excellent problem-solving skills and are a great support for the team." The server then sends the generated positive interpretation data and the compliment to the communication terminal, which then displays it to the user.

[1251] This allows the user to convert the negative emotions they input into positive interpretations, and by rediscovering their positive aspects, they can reduce their mental burden. Through this process, the present invention provides an effective means of supporting the user's mental health.

[1252] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1253] Program processing flow

[1254] Step 1: User Input

[1255] Users input negative emotional data using a communication device. Specifically, they can input it as text through a dedicated application or web form displayed on the device. They can also input facial expressions and gestures using voice input or a camera.

[1256] Input: Negative emotion text, audio data, facial expression data

[1257] Output: Negative sentiment data (text format)

[1258] Examples of specific actions:

[1259] A user opens the app and types in the text, "My colleague is late, which is causing me a lot of work."

[1260] Select voice input and speak the same phrase to input.

[1261] Step 2: Send data

[1262] The device transmits the input negative emotion data to the server using a secure communication protocol (e.g., HTTPS).

[1263] Input: Negative emotion data (text format)

[1264] Output: Negative emotion data sent to the server

[1265] Examples of specific actions:

[1266] The device sends text data such as "My colleague is late, so I have more work to do and it's bothering me" to the server using the HTTPS protocol.

[1267] Step 3: Transform negative emotions into positive ones

[1268] The server analyzes the received negative emotion data and converts it into positive interpretation data using a generative AI model. The prompt text is entered as "When the user feels that 'my colleague is late and I have more work to do,' please interpret this in a positive way."

[1269] Input: Negative emotion data, prompt sentence

[1270] Output: Positive interpretation data

[1271] Examples of specific actions:

[1272] The server receives data such as "My colleague is late, which is causing me a lot of work" and sends it to the generative AI model, which then receives positive interpretation data such as "My colleague works at his own pace and is good at managing his time."

[1273] Step 4: Analyze the positive aspects of your users

[1274] The server extracts and generates positive characteristics of the user based on the user's profile data and past interaction data.

[1275] Input: User profile data, past interaction data

[1276] Output: Positive characteristic data

[1277] Examples of specific actions:

[1278] The database is used to confirm that the user has an "attitude of valuing time," and based on that characteristic, a compliment such as "You have excellent problem-solving skills and are a great support for the team" is generated.

[1279] Step 5: View the results

[1280] The server sends the generated positive interpretation data and the user's positive characteristics to the terminal, again using a secure communication protocol (e.g., HTTPS). The terminal displays the received data to the user.

[1281] Input: Positive interpretation data, positive characteristic data

[1282] Output: A positive message that the user sees

[1283] Examples of specific actions:

[1284] The device will display messages such as, "Your colleagues work at their own pace and manage their time effectively. You also have excellent problem-solving skills and are a supportive member of the team."

[1285] keyword

[1286] Generative AI model, prompt sentence

[1287] (Application example 2)

[1288] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1289] The problem that this invention aims to solve is to convert negative emotions that users experience in their daily lives into positive ones, thereby reducing the user's mental burden. Furthermore, the invention aims to support the user's mental health by analyzing their characteristics and helping them recognize their positive aspects. In particular, by providing this function in content distribution services, the invention aims to provide an environment in which users can reduce stress and have a positive experience.

[1290] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1291] In this invention, the server includes means for analyzing negative emotion data and converting it into positive interpretation data, means for generating positive characteristics of the user based on the user's characteristic data, means for displaying the positive interpretation data and the user's positive characteristics on a content distribution service terminal, means for analyzing negative emotion data based on voice and text input using an emotion engine, and means for transmitting the negative emotion data using a secure communication protocol. This allows the user to convert negative emotions into positive ones and rediscover their own positive aspects, thereby reducing mental burden.

[1292] "Electronic Device" means a device used by a user to process and display input data, such as a smartphone, computer, or tablet.

[1293] "Negative emotion data" is information entered by the user regarding negative emotions such as stress and anxiety.

[1294] A "conversion device" is a system or device for converting received data into another format or content, including a generative AI model.

[1295] "Positive interpretation data" is data that converts negative emotional data into a positive meaning.

[1296] "Characteristic data" is data including user behavior, preferences, personality traits, and the like.

[1297] "Analyzing" means using data statistics and algorithms to extract information and patterns from data.

[1298] "Display" means to visually present information to a user, such as through a device screen.

[1299] A "system" is a set of structures or devices consisting of multiple elements that are interrelated and function in concert.

[1300] A "server" is a computer system that stores and manages data over a network and provides services to client devices.

[1301] "Secure communications protocol" means a communications method used to ensure the secure transmission of data, including HTTPS.

[1302] "Content distribution services" are services that provide video, audio, text, or other content via electronic devices, including online streaming services and digital libraries.

[1303] An "emotion engine" is a software or hardware engine for analyzing emotions from speech, text, and other input data.

[1304] The present invention is a system that receives negative emotional data from a user using an electronic device, converts it into positive interpretation data, and then analyzes the user's characteristics to generate and display the user's positive characteristics. A specific example of how this system can be realized is shown below.

[1305] The system consists of the following elements:

[1306] Electronic Device: A device used by a user, such as a smartphone or tablet.

[1307] Sentiment Engine: Software that recognizes negative emotions based on voice and text input. Uses the Google Cloud Natural Language API.

[1308] Server: A device that receives and analyzes negative emotional data and converts it into positive interpretation data using a generative AI model (OpenAI GPT-4).

[1309] Generative AI model: An AI model used to convert negative sentiment data into positive interpretation data.

[1310] Secure communication protocol: A communication method that uses HTTPS to ensure data security.

[1311] Content distribution service: A service that allows users to see positive interpretation data and positive characteristics of users.

[1312] The user inputs negative emotions using an electronic device. This input can be via text or voice. The emotion engine analyzes this input and recognizes negative emotion data. The recognized negative emotion data is sent to the server using a secure communication protocol. The server converts the received data into positive interpretation data using a generative AI model, and further generates positive traits based on the user's trait data.

[1313] For example, if a user inputs "My colleague is late, which causes me to have more work to do," the emotion engine analyzes this input data and recognizes stress and frustration. The server receives this negative emotion data and inputs it into a generative AI model (OpenAI GPT-4). The generative AI model generates a positive interpretation, such as:

[1314] "My colleagues are able to work at their own pace and are good at time management." In addition, the server extracts user characteristics from the user profile and generates positive characteristics such as:

[1315] "You're a great problem solver and a great support for the team."

[1316] The results are displayed on the user's electronic device through a content distribution service, allowing the user to rediscover their positive interpretations and positive traits, and feel a reduction in their mental burden.

[1317] Example prompt sentence:

[1318] Take the negative sentence: "My coworker is late, which means I have more work to do" and turn it into a positive one.

[1319] In this way, the present invention provides an effective means for converting negative emotions into positive ones and supporting the mental health of users by further analyzing their characteristics.

[1320] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1321] Step 1:

[1322] A user inputs negative emotions using an electronic device.

[1323] Input: The user inputs negative emotions via text or voice.

[1324] Data processing / data calculation: The emotion engine analyzes the user's input data and recognizes negative emotion data.

[1325] Output: Parsed negative sentiment data.

[1326] Step 2:

[1327] The device transmits negative emotional data to a server using a secure communication protocol (HTTPS).

[1328] Input: Parsed negative sentiment data.

[1329] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[1330] Output: Securely transmitted negative sentiment data.

[1331] Step 3:

[1332] The server analyzes the negative emotional data it receives and converts it into positive interpretation data using a generative AI model.

[1333] Input: Received negative sentiment data.

[1334] Data processing / data calculation: Input data into a generative AI model, analyze it, and generate positive interpretation data.

[1335] Output: Positive interpretive data.

[1336] Step 4:

[1337] The server generates positive characteristic data based on the user's characteristic data.

[1338] Input: User profile data and past interaction data.

[1339] Data processing / data calculation: Analyze user characteristic data and extract positive characteristics.

[1340] Output: Positive trait data of the user.

[1341] Step 5:

[1342] The server transmits the generated positive interpretation data and the user's positive characteristic data to the terminal using a secure communication protocol (HTTPS).

[1343] Input: Positive interpretation data and positive user characteristic data.

[1344] Data processing / data calculation: Data is encrypted and sent using the HTTPS protocol.

[1345] Output: Securely transmitted positive interpretation and characterization data.

[1346] Step 6:

[1347] The terminal displays the received positive interpretation data and the user's positive characteristic data to the user.

[1348] Input: Securely transmitted positive interpretation data and positive user characteristic data.

[1349] Data processing / data calculation: Analyzes received data and converts it into a display format.

[1350] Output: Positive interpretation and characteristic data displayed to the user.

[1351] As a specific example of how it works, a user might input, "My colleague is always late, which is causing me a lot of work." The emotion engine analyzes this input and recognizes negative emotions. The recognized data is sent to the server, where the generative AI model converts it into a positive interpretation: "My colleague is able to work at his own pace and is good at time management." The server then generates a positive characteristic based on the user profile: "You are a good problem-solver and a supportive member of the team," which the device displays to the user.

[1352] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1353] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1354] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1355] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1356] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1357] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1358] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1359] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1360] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1361] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1362] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1363] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1364] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1365] 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.

[1366] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1367] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1368] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1369] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1370] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1371] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1372] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1373] The following is further disclosed regarding the above embodiment.

[1374] (Claim 1)

[1375] means for receiving negative emotion data input by a user using an electronic device;

[1376] means for converting the received negative emotional data into positive interpretation data by a conversion device;

[1377] means for analyzing the user's characteristic data and generating a positive characteristic of the user;

[1378] A system including means for displaying positive interpretation data and positive characteristics of the user to the user.

[1379] (Claim 2)

[1380] 2. The system of claim 1, wherein the input negative emotion data is sent to a server, and the server generates positive interpretation data and positive characteristics of the user.

[1381] (Claim 3)

[1382] 10. The system of claim 1, wherein the positive characteristics of the user are generated based on user profile data from a plurality of databases.

[1383] "Example 1"

[1384] (Claim 1)

[1385] means for receiving negative emotion data input by a user using an electronic device;

[1386] means for transmitting the received negative emotion data to a server using a communication protocol;

[1387] A means for the server to convert negative emotional data into positive interpretation data using a generative AI model;

[1388] means for the server to generate positive characteristics of the user based on the user's profile data;

[1389] A system including means for displaying positive interpretation data and positive characteristics of the user to the user.

[1390] (Claim 2)

[1391] 2. The system according to claim 1, wherein the input negative emotion data is encrypted and transmitted to the server using a communication protocol.

[1392] (Claim 3)

[1393] 10. The system of claim 1, wherein the server generates positive characteristics of the user based on user profile data from a plurality of databases.

[1394] "Application Example 1"

[1395] (Claim 1)

[1396] means for receiving negative emotion data input by a user using an electronic device;

[1397] means for converting the received negative emotional data into positive interpretation data by a conversion device;

[1398] means for analyzing the user's characteristic data and generating a positive characteristic of the user;

[1399] means for displaying the positive interpretation data and the positive characteristics of the user to the user;

[1400] means for transmitting the generated data to a user's terminal via a secure communication protocol;

[1401] The system includes means for displaying a correlation between negative emotion data entered by a user and the converted positive interpretation data.

[1402] (Claim 2)

[1403] 2. The system of claim 1, wherein the input negative emotion data is sent to a server, and the server generates positive interpretation data and positive characteristics of the user.

[1404] (Claim 3)

[1405] The system of claim 1, wherein the positive characteristics of a user are generated based on user profile data from multiple databases, and the generated data is analyzed using a generative AI model.

[1406] "Example 2: Combining Emotion Engines"

[1407] (Claim 1)

[1408] means for receiving negative emotion data input by a user using a communication terminal;

[1409] means for transmitting the received negative emotion data to a server using a secure communication protocol;

[1410] A means for analyzing negative emotional data received on a server and converting it into positive interpretation data using a generative AI model;

[1411] A means for identifying and generating positive user characteristics based on user profile data and past interaction data through analysis;

[1412] means for transmitting and displaying the generated positive interpretation data and the positive characteristics of the user to a communication terminal;

[1413] A system including:

[1414] (Claim 2)

[1415] 10. The system of claim 1, wherein the server generates the generated positive interpretation data and the positive characteristics of the user.

[1416] (Claim 3)

[1417] 10. The system of claim 1, wherein the positive characteristics of the user are generated based on user profile data from a plurality of databases.

[1418] "Application example 2 when combining emotion engines"

[1419] (Claim 1)

[1420] means for receiving negative emotion data input by a user using an electronic device;

[1421] means for converting the received negative emotional data into positive interpretation data by a conversion device;

[1422] means for analyzing the user's characteristic data and generating a positive characteristic of the user;

[1423] means for displaying the positive interpretation data and the positive characteristics of the user to the user;

[1424] means for displaying the positive interpretation data and the positive characteristics of the user on a terminal of the content distribution service;

[1425] means for analyzing negative emotion data based on voice and text inputs using an emotion engine;

[1426] A system including means for transmitting negative emotional data using a secure communication protocol.

[1427] (Claim 2)

[1428] 2. The system of claim 1, wherein the input negative emotion data is sent to a server, and the server generates positive interpretation data and positive characteristics of the user.

[1429] (Claim 3)

[1430] 10. The system of claim 1, wherein the positive characteristics of the user are generated based on user profile data from a plurality of databases. [Explanation of symbols]

[1431] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving negative emotion data input by a user using an electronic device; means for converting the received negative emotional data into positive interpretation data by a conversion device; means for analyzing the user's characteristic data and generating a positive characteristic of the user; A system including means for displaying positive interpretation data and positive characteristics of the user to the user.

2. 2. The system according to claim 1, wherein the input negative emotion data is sent to a server, and the server generates positive interpretation data and positive characteristics of the user.

3. 10. The system of claim 1, wherein the positive characteristics of the user are generated based on user profile data from a plurality of databases.

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