System

Abstract

A system is provided.SOLUTION: A system comprising: input means for a user to input information on a department; receiving means for a server to receive the information input from the input means; calling means for the server to call generative artificial intelligence using the information received by the receiving means and to transmit a character generation request; receiving means for the server to receive a character generation result from the generative artificial intelligence; and transmitting means for the server to transmit the character generation result to a terminal of 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 a company, it is difficult to effectively communicate the activities and business details of each department to other departments. As a result, lack of communication and information asymmetry between departments can occur, potentially hindering efficient business execution and cooperation. To solve these problems, the present invention aims to provide a system that effectively communicates internal information through the creation of original characters using generative artificial intelligence. [Means for solving the problem]

[0005] The present invention solves the problems by the following means: An input means is provided for a user to input information about a department, and a server includes a receiving means for receiving the information input from the input means. The server further includes a calling means for calling a generative AI using the information received by the receiving means and sending a character generation request. The server then includes a receiving means for receiving a character generation result from the generative AI, and finally a sending means for sending the character generation result to the user's terminal. This allows the user to use the received character generation result to create a notice about the department and effectively communicate information to other departments.

[0006] A "user" refers to a person who operates the system to input information about the department and creates announcements using the generated characters.

[0007] A "department" refers to a department in a company or organization that is responsible for a specific function or task.

[0008] "Input means" refers to the interface that allows users to input information about their department (department name, role, information to be disseminated, etc.) into the system.

[0009] "Server" refers to a computer system that receives information sent by a user, generates a character using generative artificial intelligence, and sends the results to the user's terminal.

[0010] "Receiving means" refers to the function of the server receiving information sent by the user and the character generation results from the generative artificial intelligence.

[0011] "Generative artificial intelligence" refers to algorithms or models that generate original characters based on input data.

[0012] A "character generation request" refers to a request to a generative artificial intelligence that includes information for generating a character.

[0013] "Calling means" refers to the function by which the server sends a character generation request to the generative artificial intelligence.

[0014] "Character generation results" refers to data including the character name, character description, and character image URL that the generative artificial intelligence responds to in response to a character generation request.

[0015] "Transmission means" refers to the function by which the server transmits the character generation results to the user's terminal.

[0016] "Terminal" refers to a device operated by a user to receive and display the character generation results sent from the server.

[0017] "Announcement" refers to a document created by a user to communicate information about the department, including the generated characters, to other departments. [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 showing 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 in which a user inputs information about a department, generates an original character based on that information using generative artificial intelligence, and creates a message using the generated character. Specific embodiments of the present invention are described below.

[0040] System Overview

[0041] First, the user uses a terminal to input basic information about the department, such as the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[0042] The server receives the information sent from the device and sends it to the generative AI as a character generation request. The generative AI generates an original character based on the received information and returns the generated results, such as the character name, character description, and character image URL, to the server.

[0043] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[0044] Program processing details

[0045] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[0046] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[0047] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[0048] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[0049] Specific examples

[0050] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[0051] Department name: IT department

[0052] Department role: System operation and maintenance

[0053] What we want to announce: Introducing new security rules

[0054] The server sends this information to the generative AI and receives the following as examples of generated characters:

[0055] Character Name: Security-kun

[0056] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0057] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0058] Based on the results, the user creates a message like this:

[0059] Hello everyone!

[0060] This is Security-kun.

[0061] Today I would like to inform you about the activities of our department.

[0062] A security expert working in the IT department, always providing the latest security information to everyone

[0063] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0064] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[0065] Through such specific embodiments, the present invention improves communication between departments within a company and makes it possible to disseminate information more effectively.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The user enters information about the department (e.g., department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[0069] Step 2:

[0070] The terminal serializes the information entered by the user into an appropriate format and sends an HTTP request to the server, which includes information about the department entered by the user.

[0071] Step 3:

[0072] The server receives the request sent from the device. The server analyzes the received data and checks its contents. After checking the validity of the data, it prepares to send a character generation request to the generative AI.

[0073] Step 4:

[0074] The server calls the generative AI API and sends a character generation request that includes information about the department, such as the department name, role, and desired publicity.

[0075] Step 5:

[0076] The generative AI receives and analyzes the character generation request. Based on the input information, it starts the process of generating an appropriate original character. The generation process includes the character name, character description, and character image URL.

[0077] Step 6:

[0078] The generative AI returns the generated character results to the server. The results include the character name, character description, and the URL of the character image. The server receives the generated results.

[0079] Step 7:

[0080] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[0081] Step 8:

[0082] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[0083] Step 9:

[0084] The user's device receives the generated results from the server and displays them on the screen. The user then creates a message based on this information. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[0085] Step 10:

[0086] Users can send the announcements they create to other departments within the company, thereby enabling effective information sharing using the generated characters.

[0087] Example 1

[0088] 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."

[0089] With conventional information sharing systems, communication between departments was complicated and it took a long time to create announcements. In addition, there was a lack of visually appealing means of communicating information, which made the impact on the recipient weak and sometimes led to ineffective communication of information.

[0090] 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.

[0091] In this invention, the server includes an information receiving means, an AI calling means, a generation result receiving means, a result sending means, and a display means, which allows a character to be generated by the generative AI based on the department information entered by the user, and a message to be created based on the character information.

[0092] "Information input means" refers to an input device or interface that a user uses to input information about a department.

[0093] The "information receiving means" is a function or module that allows the server to receive department information sent from the information input means.

[0094] "Artificial intelligence calling means" is a function or module for calling a generative artificial intelligence using information received by the server and sending a character generation request.

[0095] The "generation result receiving means" is a function or module that allows the server to receive character generation results from the generative artificial intelligence.

[0096] The "result transmission means" is a function or module that transmits the character generation results received by the server via the generation result receiving means to the user's terminal.

[0097] "Display means" is a function or module that allows the terminal to serialize the character generation results and display them to the user.

[0098] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[0099] The "document creation means" is a function or interface that allows the user to create a notice about the department using the character generation results.

[0100] This invention is a system in which a user inputs information about a department, an original character is generated based on that information using generative artificial intelligence, and a notice is created using the generated character.

[0101] System Overview

[0102] First, the user uses a terminal to input basic information about the department, including the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[0103] The server receives the information sent from the device and sends it to the generative AI as a character generation request. At this time, the server creates a prompt and calls the generative AI's API. The generative AI generates an original character based on the received information and returns the generation results, such as the character name, character description, and character image URL, to the server.

[0104] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[0105] Program processing details

[0106] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[0107] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[0108] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[0109] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[0110] Specific examples

[0111] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[0112] Department name: IT department

[0113] Department role: System operation and maintenance

[0114] What we want to announce: Introducing new security rules

[0115] The server sends this information to the generative AI and receives the following as examples of generated characters:

[0116] Character Name: Security-kun

[0117] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0118] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0119] Based on the results, the user creates a message like this:

[0120] Hello everyone!

[0121] This is Security-kun.

[0122] Today I would like to inform you about the activities of our department.

[0123] A security expert working in the IT department, always providing the latest security information to everyone

[0124] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0125] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1:

[0128] User enters department information

[0129] The user launches a browser on their device and accesses a web form for entering department information. This form has input fields for the department name, department role, and information to be disseminated. The user enters the necessary information into each field and presses the "Submit" button. This loads the entered information into the device. Specifically, the user launches a browser, accesses the specified URL, enters the department information, and then clicks the "Submit" button.

[0130] Input: Department name, department role, information to be disseminated

[0131] Output: Department information entry completion status on the terminal

[0132] Step 2:

[0133] The device sends the input information to the server

[0134] The device serializes the department information entered by the user into JSON format and creates an HTTP POST request. This request is sent to the server. The sent information includes the department name, department role, and the information to be disseminated. This allows data to be securely transferred from the device to the server. Specifically, the device converts the department information into JSON format and sends it to the server as an HTTP POST request.

[0135] Input: Department information entered by the user

[0136] Output: Department information sent to the server in JSON format

[0137] Step 3:

[0138] The server calls the AI ​​model to generate the character.

[0139] Based on the received department information, the server creates a prompt to call the generative AI's API. The prompt includes the department name, role, and information to be communicated. Using the created prompt, the server sends a character generation request to the generative AI. The generative AI analyzes the received information and generates an original character. Specifically, the server creates a prompt, calls the generative AI's API, and sends a character generation request.

[0140] Input: Department information received by the server

[0141] Output: A character generation request to the generative artificial intelligence

[0142] Step 4:

[0143] The server receives the generated results and sends them to the terminal.

[0144] The generative AI generates a character name, character description, and character image URL as the character generation result and sends them back to the server. The server encodes the generation result into JSON format and sends it to the terminal as an HTTP response. Specifically, the server receives the generation result, converts it into JSON format, and sends it to the terminal as an HTTP response.

[0145] Input: Character generation results returned from generative artificial intelligence

[0146] Output: JSON format character generation results sent to the terminal

[0147] Step 5:

[0148] The user creates a message based on the character information.

[0149] The user views the generated character information in the browser on the device. This information includes the character name, character description, and character image URL. The user creates a message based on this information. Specifically, the user checks the character information on the device, creates a message, and sends the content to other departments within the company via email or the internal bulletin board.

[0150] Input: Character generation results displayed on the terminal

[0151] Output: The created announcement

[0152] (Application example 1)

[0153] 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."

[0154] Traditionally, information sharing between departments within a company has been done through documents and emails, but these lacked visual appeal and often did not effectively communicate the information to the recipient. Similarly, there were limited ways to effectively inform customers about the introduction of new products and services. This resulted in problems such as it taking time for recipients to understand the content, or the intended information not being conveyed accurately.

[0155] 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.

[0156] In this invention, the server includes an input means for a user to input information about the department, a receiving means for the server to receive the information input from the input means, a calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, a receiving means for the server to receive a character generation result from the generative artificial intelligence, a sending means for the server to send the character generation result to the user's device, a push notification means for the server to create a message using the character generation result and send a push notification to the smartphone device, and a display means for receiving the push notification on the smartphone device and interactively displaying detailed information. This enables efficient and effective sharing of information within and outside the department using a visually appealing means.

[0157] A "user" is a person or organization that uses the system to input information about a department and to use the generated characters and announcements.

[0158] "Information about the department" is basic information about a specific department, such as its name, role, and the details you want to make known.

[0159] "Input means" refers to a device or software that has an interface for users to input information about departments.

[0160] A "server" is a computer system that calls a generative artificial intelligence based on received information and generates a character.

[0161] The "receiving means" is a function that allows the server to receive information sent from the input means.

[0162] The "calling means" is a function for the server to call the generative artificial intelligence based on the information received by the receiving means and send a character generation request.

[0163] "Generative AI" is an AI technology that generates original characters based on input information.

[0164] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[0165] The "transmission means" is a function for the server to transmit the character generation results to the user's terminal.

[0166] The "push notification means" is a function that sends a notification message including the character generation results generated by the server to the smartphone terminal to notify the user.

[0167] "Display means" refers to a function that allows a smartphone device to receive push notifications and interactively display detailed information.

[0168] The present invention is a system for visually and effectively sharing information between departments within a company. This system allows a user to input information about their department, and uses generative artificial intelligence to generate original characters based on that information, and then creates announcements using the generated characters. Specific embodiments of the system are described below.

[0169] First, the user uses a device (e.g., a smartphone or PC) to enter basic information about the department. This information includes, for example, the name of the department, its role, and the information to be disseminated. Input methods include text boxes and drop-down lists. Once input is complete, the device serializes the information into an appropriate format and sends it to the server.

[0170] Next, the server receives the information sent from the user's terminal using the receiving means.The server then uses the calling means to call a generative artificial intelligence (specifically, a generative AI model) based on the received information and sends a character generation request.The generative artificial intelligence generates an original character based on the received information and generates a character name, character description, and character image URL.

[0171] The server receives the generated character generation results using a receiving means and transmits them again to the user's device using a transmitting means. The user creates a message about the department based on the character generation results displayed on the device. This allows for visually appealing information communication. The message includes the name and description of the generated character, an image URL, etc. The server then transmits the created message to the smartphone device via a push notification means.

[0172] Users who receive a push notification on their smartphone can tap the notification to interactively display detailed information, making it easy to check the announcement and enabling efficient information sharing.

[0173] Hardware and software used

[0174] Hardware: Servers, smartphones, PCs

[0175] Software: Flask (Python framework), API for generative AI models

[0176] Specific examples

[0177] For example, if the New Product Development department wants to announce the introduction of a new security product, they might enter the following information:

[0178] Department name: New Product Development Department

[0179] Department Role: Developing and introducing new products and services

[0180] Just wanted to let you know: The latest electronic security gadgets have arrived!

[0181] The server sends this information to the generative AI and receives the following character generation results:

[0182] Character Name: Security Master

[0183] Character description: A master of the latest security products, providing customers with a safer life.

[0184] Character image URL: https: / / example-ai-service.com / images / securitymaster.png

[0185] Users can create a message based on the results, which will be pushed to their smartphone. For example:

[0186] "Hello everyone! This is Security Master. Today I'll be introducing the latest electronic security gadgets. For more details, please see this illustration: https: / / example-ai-service.com / images / SecurityMaster.png"

[0187] In this way, the system allows for effective dissemination of information both within and outside the department, and allows for information sharing using visually appealing means.

[0188] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0189] Step 1:

[0190] The user enters basic information about the department.

[0191] Input: Department name, department role, information to be disseminated

[0192] Users use a device (smartphone or PC) to enter the department name, department role, and information they want to share into text boxes and drop-down lists on a specific screen. Once the input is complete, the device serializes this information into an appropriate data format such as JSON.

[0193] Step 2:

[0194] The terminal transmits the input information to the server.

[0195] Output: Serialized department information

[0196] The terminal sends the serialized department information to the server as an HTTP POST request. The receiving server has a receiving means implemented, and receives this request.

[0197] Step 3:

[0198] The server calls a generative artificial intelligence based on the information received.

[0199] Input: Serialized department information

[0200] The server analyzes the received department information and sends a character generation request to the generative AI API based on that data. Specifically, it uses a calling method to send the department name, department role, and announcements to the API.

[0201] Step 4:

[0202] The generative artificial intelligence generates a character based on the character generation request and returns the result.

[0203] Output: Character generation result (character name, description, image URL)

[0204] The generative AI model analyzes the received information and generates an original character. Information about the generated character (character name, description, image URL) is sent back to the server.

[0205] Step 5:

[0206] The server receives the character generation results and sends them to the user's terminal.

[0207] Input: Character generation result

[0208] The server transmits the character generation results received from the generative AI back to the user's terminal, using the transmission means to transmit the result data as an HTTP response.

[0209] Step 6:

[0210] The user receives the character generation results on the terminal and they are displayed.

[0211] Output: Character information displayed on the screen (character name, description, image URL)

[0212] The user's device displays the character generation results received from the server, and the user checks the displayed character information.

[0213] Step 7:

[0214] The user creates a message based on the character generation results.

[0215] Input: Character generation results, information

[0216] Users create visually appealing announcements based on the displayed character names, descriptions, and image URLs. The completed announcements are saved on the device.

[0217] Step 8:

[0218] The server will push the created notice to the smartphone device.

[0219] Input: Created announcement

[0220] The server sends the message created by the user to other smartphone terminals using push notification means. Specifically, the notification content is sent through a push notification server.

[0221] Step 9:

[0222] The smartphone device receives a push notification, and the user taps the notification to display detailed information.

[0223] Output: Push notification, display of detailed information

[0224] When a push notification is received, it will be displayed on the smartphone. When the user taps on the notification, detailed information will be displayed interactively on the screen, allowing the user to check the information.

[0225] This series of steps enables effective visual information sharing both within and outside the company.

[0226] 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.

[0227] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on the information using generative artificial intelligence, and the generated character is used to create announcements. Specific embodiments of the present invention are described in detail below.

[0228] System Overview

[0229] First, a user uses a device to enter basic information about their department, such as the department's name, its role, and any information they want to share. The device then collects this information and activates an emotion engine that analyzes the user's input, typing speed, and possibly facial expressions and voice.

[0230] The emotion engine analyzes the user's input operations and real-time biometric data to recognize the user's emotions. For example, if the user is typing quickly, it can detect emotions such as "impatience" or "tension."

[0231] The recognized emotion information and department information are sent from the device to the server. Based on the received information, the server sends a character generation request to the generative AI. The generative AI adjusts the character's attributes taking the user's emotions into account and generates the character. For example, if the user is "nervous," the generated character can have a more relaxed atmosphere.

[0232] The generative AI returns the generated results, including the character name, character description, and character image URL, to the server. The server receives the generated results and sends them back to the terminal. The user uses the character generation results displayed on the terminal to create a notice for the department. This notice includes the generated character's name, description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[0233] Program processing details

[0234] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields such as text boxes and drop-down lists, which the user uses to enter the necessary information. When the user begins to enter information, the emotion engine is activated and begins analyzing the input content, the facial expressions of the user in front of the screen, and the voice.

[0235] The emotion engine recognizes a user's emotions in real time using multiple data points, including analysis of input content, keyboard typing speed, and the user's facial expressions and voice. For example, if a user types quickly, their emotion may be determined to be "impatience."

[0236] The emotion information and department information recognized by the emotion engine are serialized into an appropriate format and sent to the server. The server analyzes the received data and calls the generative artificial intelligence API. This request includes the department name, role, message content, and recognized emotion information.

[0237] The generative AI analyzes the received information and adjusts the character's attributes to match the user's emotions. For example, if the user is "worried," the generated character may be changed to a design that gives a sense of security. The generated character name, character description, and image URL are then sent back to the server as the generation result.

[0238] The server receives the generated results and sends them back to the user's device. The generated character information is displayed on the user's device, and the user can use this information to create a message. Using the character name, description, and image URL, users can create a more visually appealing message and effectively communicate information to other departments within the company.

[0239] Specific examples

[0240] For example, suppose the IT department wants to announce a new security rule. The user enters the following information:

[0241] Department name: IT department

[0242] Department role: System operation and maintenance

[0243] What we want to announce: Introducing new security rules

[0244] If the user is typing in a hurry, the emotion engine will recognize this "impatience." The server sends this information to the generative AI, which then generates a relaxed character that alleviates the "impatience."

[0245] An example of a generated character would be:

[0246] Character Name: Security-kun

[0247] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0248] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0249] Based on the results, the user creates a message like this:

[0250] Hello everyone!

[0251] This is Security-kun.

[0252] Today I would like to inform you about the activities of our department.

[0253] A security expert working in the IT department, always providing the latest security information to everyone

[0254] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0255] In this way, by using a system that combines an emotion engine and generative artificial intelligence, effective information sharing can be achieved by taking into account the user's emotions and using visually appealing characters.

[0256] The processing flow will be explained below.

[0257] Step 1:

[0258] The user enters information about the department (department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[0259] Step 2:

[0260] The device activates its emotion engine and begins analyzing the user's input operations, input content, and keyboard typing speed. It also uses a camera and microphone to capture the user's facial expressions and voice, and comprehensively recognizes emotions.

[0261] Step 3:

[0262] The emotion engine analyzes the user's emotion (e.g., "tension" or "impatience") and sends the emotion information along with the department information to the server. The device serializes this data into an appropriate format and sends it to the server as an HTTP request.

[0263] Step 4:

[0264] The server receives the request sent from the device. The server analyzes the received data and checks its validity. Then, it calls the generative AI API and prepares to send a character generation request.

[0265] Step 5:

[0266] The server calls the generative AI API and sends department information including emotion information. This request includes details of the department name, department role, desired message, and emotion information.

[0267] Step 6:

[0268] The generative AI receives and analyzes the character generation request. The generative AI adjusts the character's attributes taking into account the user's emotional information and generates an original character. For example, if the user's emotion is "tension," the character will have a relaxed atmosphere.

[0269] Step 7:

[0270] The generative AI returns the generated character results to the server, which include the character name, character description, and character image URL.

[0271] Step 8:

[0272] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[0273] Step 9:

[0274] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[0275] Step 10:

[0276] The user's device receives the generated results from the server and displays them on the screen. The user then uses this information to create a message. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[0277] Step 11:

[0278] Users can send announcements they create to other departments within the company. By using characters that reflect emotional information and detailed announcements, information can be conveyed to other departments effectively.

[0279] Example 2

[0280] 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."

[0281] Conventional information dissemination systems generate uniform characters and messages without considering the user's emotions, which can result in a lack of appeal and familiarity to the recipient. In particular, when the user is in a hurry or under stress, the messages created often lack an appropriate response to the situation. This makes it difficult to communicate information effectively.

[0282] 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.

[0283] In this invention, the server includes input means for a user to input information about the department, emotion recognition means for activating an emotion engine in the terminal when the user starts inputting information and recognizing the user's emotion, receiving means for the server to receive the information input from the input means and the emotion information recognized by the emotion recognition means, calling means for the server to call a generation AI model using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generation AI model, and sending means for the server to send the character generation result to the user's terminal. This enables character generation and message creation that take the user's emotions into consideration, improving appeal and familiarity to recipients and realizing effective information communication.

[0284] "User" refers to the person who operates this system and inputs department information.

[0285] "Department information" refers to basic information about a specific department, such as the department name, department role, and information you want to share.

[0286] A "terminal" is a device that a user uses to access the system and input information, and includes PCs, smartphones, tablets, etc.

[0287] An "emotion engine" refers to a piece of software or hardware that analyzes the user's input, typing speed, facial expressions, voice, etc., and recognizes the user's emotions.

[0288] "Emotion recognition means" refers to a function that identifies the user's emotions using an emotion engine.

[0289] "Serialization" refers to the process of converting data into a format that can be stored or transmitted.

[0290] "Server" refers to a device or system that receives and analyzes data sent from a user's device and sends a character generation request to a generative AI model.

[0291] "Generative AI model" refers to an artificial intelligence model that generates characters based on received information.

[0292] A "character generation request" is a request that instructs a generative AI model to generate a character using data that includes department information and emotional information.

[0293] "Character generation results" refers to information about the character generated by the generative AI model, including the character name, character description, and character image URL.

[0294] "Receiving means" refers to the function by which a terminal or server receives data.

[0295] "Transmission means" refers to the function of sending data from the server to the user's terminal.

[0296] The "creation means" refers to a function that allows a user to create a message using the character generation results.

[0297] The present invention is a system in which a user inputs information about their department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using a generative AI model, and the generated character is used to create announcements.

[0298] The user first uses a terminal to input basic information about the department. This basic information includes the department name, department role, and information to be disseminated. As soon as the user starts inputting, the terminal starts the emotion engine. The emotion engine analyzes the input content, keyboard typing speed, and in some cases the user's facial expressions and voice to recognize the user's emotions. The recognized emotion information and department information are sent from the terminal to the server.

[0299] The server analyzes the received information and calls the API of the generative AI model. The API request includes the department name, department role, information to be communicated, and recognized emotion information. The generative AI model adjusts the character's attributes based on the received data and generates an original character that reflects the user's emotions. For example, if the user is "nervous," it can generate a character with a relaxed atmosphere.

[0300] The generative AI model returns the generated character information (character name, character description, character image URL) to the server. The server receives this information and sends it back to the device. The device displays the generated character information to the user. The user creates a message based on the displayed character information. This message includes the character name, character description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[0301] For example, when IT announces new security rules, users enter the following information:

[0302] Department name: IT department

[0303] Department role: System operation and maintenance

[0304] What we want to announce: Introducing new security rules

[0305] If the user is typing in a hurry, the emotion engine will recognize the "impatience." The server sends this information to the generative AI model, which then generates a relaxed character that reduces the "impatience." An example of a generated character would be:

[0306] Character Name: Security-kun

[0307] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0308] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0309] Based on the results, the user creates a message like this:

[0310] Hello everyone!

[0311] This is Security-kun.

[0312] Today I would like to inform you about the activities of our department.

[0313] A security expert working in the IT department, always providing the latest security information to everyone

[0314] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0315] In this way, a character can be generated taking into consideration the user's emotions, and visually appealing announcements can be created.

[0316] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0317] Step 1:

[0318] (User enters department information and launches emotion engine)

[0319] The user launches a dedicated application on their device and accesses a department information input form. This form contains fields for entering the department name, department role, and information they want to share. As soon as the user starts entering information in these fields, the device starts the emotion engine in the background.

[0320] input:

[0321] Department name

[0322] Roles of the Department

[0323] Information to be made known

[0324] output:

[0325] Emotional Engine Activation

[0326] Operation:

[0327] The device collects user input information in real time and provides it to the emotion engine.

[0328] Step 2:

[0329] (Emotion recognition by emotion engine)

[0330] The emotion engine analyzes input content, keyboard typing speed, the user's facial expressions, and voice to recognize the user's emotions in real time. The analyzed emotion information continues to be updated until the user completes input.

[0331] input:

[0332] User input

[0333] Keyboard typing speed

[0334] User's facial expressions and voice

[0335] output:

[0336] Recognized emotional information

[0337] Operation:

[0338] The emotion engine uses multiple sensors and data analysis techniques to determine the user's emotional state. For example, if the user types quickly, it will detect "impatience."

[0339] Step 3:

[0340] (Transmitting emotional and departmental information)

[0341] When the user completes inputting the department information, the emotion engine determines the final emotion information, and the terminal serializes this emotion information and department information and transmits them to the server.

[0342] input:

[0343] Department information

[0344] Recognized emotional information

[0345] output:

[0346] Sending serialized data

[0347] Operation:

[0348] The device converts the input data and emotional information into an appropriate format and transmits it to a server via a network.

[0349] Step 4:

[0350] (Calling the generated AI model by the server)

[0351] The server analyzes the serialized data received from the device and calls the API of the generative AI model to send a character generation request.

[0352] input:

[0353] Data received from the device

[0354] output:

[0355] Character creation request submission

[0356] Operation:

[0357] The server analyzes the data, extracts the necessary information (department name, department role, announcements, emotional information), and sends it to the API of the generative AI model.

[0358] Step 5:

[0359] (Character generation using generative AI models)

[0360] The generative AI model analyzes the data received from the server and generates a character based on the user's emotions. The generated character information includes the character name, description, and image URL.

[0361] input:

[0362] Data sent from the server

[0363] output:

[0364] Generated character information

[0365] Operation:

[0366] The generative AI model uses data analysis and character synthesis algorithms to create characters that adapt to emotions.

[0367] Step 6:

[0368] (Sending character generation results from the server to the device)

[0369] The server analyzes the character generation results received from the generation AI model and sends them back to the terminal.

[0370] input:

[0371] Character information from generative AI models

[0372] output:

[0373] Transferring character generation results

[0374] Operation:

[0375] The server organizes the generated character information (character name, description, image URL) and sends it to the user's device.

[0376] Step 7:

[0377] (Displaying character information on a device and creating announcements)

[0378] The terminal displays the character generation results to the user, allowing the user to create a message based on the results.

[0379] input:

[0380] Character generation results received from the server

[0381] output:

[0382] Character information displayed to the user

[0383] Operation:

[0384] The terminal displays character information and provides a user interface for the user to create an effective message based on the information. The user uses the displayed character information to write a specific message and confirm its content.

[0385] (Application example 2)

[0386] 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."

[0387] Conventional information transmission systems provide characters and messages uniformly generated without considering the user's emotions, making it difficult to effectively transmit information according to a specific situation or emotional state. Furthermore, because the character generation is not dependent on the user's emotions, the system may lack visual appeal and user acceptance. This results in issues such as time-consuming transmission and understanding of information, reducing efficiency.

[0388] 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.

[0389] In this invention, the server includes input means for a user to input information about the department, receiving means for the server to receive the information input from the input means, calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generative artificial intelligence, sending means for the server to send the character generation result to the user's terminal, emotion recognition means for recognizing the user's emotion, adjustment means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means, and display means for displaying visually attractive notices using the generated character. This makes it possible to generate characters and create messages that take the user's emotions into consideration, thereby realizing visually attractive and easily accepted information transmission.

[0390] The "input means" is a means for a user to input information about a department.

[0391] The "receiving means" is a means by which the server receives information input from the input means.

[0392] The "calling means" is a means by which the server calls the generative artificial intelligence using the information received by the receiving means and transmits a character generation request.

[0393] "Generative AI" is an AI system that generates characters based on user information.

[0394] "Character generation results" refers to information about a character generated by generative artificial intelligence, including the character name, character description, and character image URL.

[0395] The "transmission means" is a means by which the server transmits the character generation results to the user's terminal.

[0396] The "emotion recognition means" is a means for recognizing the user's emotions.

[0397] The "adjustment means" is a means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means.

[0398] The "display means" is a means for displaying visually appealing notices on a user terminal using the generated characters.

[0399] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using generative artificial intelligence, and the generated character is used to create announcements.

[0400] System Overview

[0401] First, the user puts on the smart glasses and begins work. Using the smart glasses' input mechanism, the user enters information about their department, including the department name, role, and any information they wish to share. The smart glasses' built-in camera and microphone capture the user's facial expressions and voice, and analyze their emotions in real time. This emotion recognition is performed using an emotion engine such as Amazon Rekognition.

[0402] Next, the server receives the input information and the recognized emotion information using the receiving means. After that, the calling means calls the generative artificial intelligence (e.g., OpenAI's GPT-4) and sends a character generation request. This request includes the department name, role, content to be communicated, and the recognized emotion information.

[0403] The generative artificial intelligence generates a character based on the received information. The generated character's information (character name, description, image URL) is sent back to the server. The server then sends this information back to the user's smart glasses using a transmission means. The smart glasses then display the character information to the user using a display means. As a result, the user can create visually appealing messages using the generated character.

[0404] The specific hardware and software used

[0405] Smart Glasses: Smart glasses such as Oculus Quest 2

[0406] Sentiment engine: Amazon Rekognition

[0407] Generative artificial intelligence: OpenAI GPT-4

[0408] Server: AWS EC2 instance

[0409] Communication protocol: HTTP / HTTPS

[0410] Data serialization: JSON

[0411] Specific examples

[0412] For example, consider the case where a safety department employee is learning new safety rules.

[0413] The user puts on the smart glasses and enters the following information:

[0414] Department name: Safety Management Department

[0415] Procedure: Applying new safety rules

[0416] If the emotion engine detects that the user is feeling "anxiety" based on their facial expression or voice, the server sends this information to the generative AI, which then sends the following prompt:

[0417] "I'm worried about the application of the Safety Management Department's new safety rules."

[0418] The generative AI generates a character based on this information and returns the following character information, for example:

[0419] Character Name: Anshin-kun

[0420] Character description: A safety management expert who relieves everyone's worries

[0421] Image URL: https: / / example-ai-service.com / images / Anshinkun.png

[0422] The user's smart glasses will display this character information, allowing the user to learn new procedures with confidence.

[0423] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0424] Step 1:

[0425] The user puts on the smart glasses and begins work. The user uses the smart glasses' input means to input department information. This input includes the department name, role, and information to be disseminated. The input data is temporarily stored in the smart glasses' memory.

[0426] Step 2:

[0427] The device captures the user's facial expressions and voice. The smart glasses' built-in camera and microphone are used to collect biometric data, which is then processed into emotion recognition data. This data is sent in real time to the emotion engine (Amazon Rekognition).

[0428] Step 3:

[0429] The emotion engine analyzes the user's facial expressions and voice data to recognize the user's emotions. The analyzed emotion information (e.g., "anxiety" or "impatience") is generated and sent to the server. This emotion information is serialized in JSON format.

[0430] Step 4:

[0431] The server receives the user's input information and the recognized emotion information. Specifically, this includes the department name, role, desired message, and emotion information. Based on the received data, the server creates a character generation request for the generative AI. The request is generated in the following format:

[0432] Text format:

[0433] "Department name: Safety Management Department, Procedure: I am concerned about the application of new safety rules."

[0434] The server sends this request to the API of the generative artificial intelligence (OpenAI GPT-4).

[0435] Step 5:

[0436] The generative AI receives the request and generates a character based on the department information and emotion information. The generated character information (character name, character description, image URL) is sent back to the server. In this process, the character design is adapted to the user's emotion.

[0437] Step 6:

[0438] The server transmits the received character generation results to the user's smart glasses. The transmitted data includes the generated character name, character description, and image URL. The data is sent to the user's terminal using a transmission means.

[0439] Step 7:

[0440] The device (smart glasses) receives the character generation results and visually displays them. The user then creates a message based on the displayed character information. Specifically, the user can insert the character name, description, and image URL into the message, making it possible to convey information in a visually appealing way.

[0441] Specific working example:

[0442] 1. The user inputs a "new safety rule" in the "Safety Management Department," and the emotion of "anxiety" is recognized.

[0443] 2. The server sends a request to the generative AI saying, "I am concerned about the application of the Safety Management Department's new safety rules."

[0444] 3. Information about the generated character, "Anshin-kun," is sent back to the server and displayed on the smart glasses.

[0445] 4. Users create announcements that include descriptions and images of Anshin-kun, and communicate them to other employees in a visually appealing way.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] [Second embodiment]

[0450] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0451] 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.

[0452] 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).

[0453] 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.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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."

[0462] The present invention is a system in which a user inputs information about a department, generates an original character based on that information using generative artificial intelligence, and creates a message using the generated character. Specific embodiments of the present invention are described below.

[0463] System Overview

[0464] First, the user uses a terminal to input basic information about the department, such as the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[0465] The server receives the information sent from the device and sends it to the generative AI as a character generation request. The generative AI generates an original character based on the received information and returns the generated results, such as the character name, character description, and character image URL, to the server.

[0466] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[0467] Program processing details

[0468] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[0469] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[0470] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[0471] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[0472] Specific examples

[0473] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[0474] Department name: IT department

[0475] Department role: System operation and maintenance

[0476] What we want to announce: Introducing new security rules

[0477] The server sends this information to the generative AI and receives the following as examples of generated characters:

[0478] Character Name: Security-kun

[0479] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0480] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0481] Based on the results, the user creates a message like this:

[0482] Hello everyone!

[0483] This is Security-kun.

[0484] Today I would like to inform you about the activities of our department.

[0485] A security expert working in the IT department, always providing the latest security information to everyone

[0486] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0487] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[0488] Through such specific embodiments, the present invention improves communication between departments within a company and makes it possible to disseminate information more effectively.

[0489] The processing flow will be explained below.

[0490] Step 1:

[0491] The user enters information about the department (e.g., department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[0492] Step 2:

[0493] The terminal serializes the information entered by the user into an appropriate format and sends an HTTP request to the server, which includes information about the department entered by the user.

[0494] Step 3:

[0495] The server receives the request sent from the device. The server analyzes the received data and checks its contents. After checking the validity of the data, it prepares to send a character generation request to the generative AI.

[0496] Step 4:

[0497] The server calls the generative AI API and sends a character generation request that includes information about the department, such as the department name, role, and desired publicity.

[0498] Step 5:

[0499] The generative AI receives and analyzes the character generation request. Based on the input information, it starts the process of generating an appropriate original character. The generation process includes the character name, character description, and character image URL.

[0500] Step 6:

[0501] The generative AI returns the generated character results to the server. The results include the character name, character description, and the URL of the character image. The server receives the generated results.

[0502] Step 7:

[0503] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[0504] Step 8:

[0505] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[0506] Step 9:

[0507] The user's device receives the generated results from the server and displays them on the screen. The user then creates a message based on this information. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[0508] Step 10:

[0509] Users can send the announcements they create to other departments within the company, thereby enabling effective information sharing using the generated characters.

[0510] Example 1

[0511] 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."

[0512] With conventional information sharing systems, communication between departments was complicated and it took a long time to create announcements. In addition, there was a lack of visually appealing means of communicating information, which made the impact on the recipient weak and sometimes led to ineffective communication of information.

[0513] 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.

[0514] In this invention, the server includes an information receiving means, an AI calling means, a generation result receiving means, a result sending means, and a display means, which allows a character to be generated by the generative AI based on the department information entered by the user, and a message to be created based on the character information.

[0515] "Information input means" refers to an input device or interface that a user uses to input information about a department.

[0516] The "information receiving means" is a function or module that allows the server to receive department information sent from the information input means.

[0517] "Artificial intelligence calling means" is a function or module for calling a generative artificial intelligence using information received by the server and sending a character generation request.

[0518] The "generation result receiving means" is a function or module that allows the server to receive character generation results from the generative artificial intelligence.

[0519] The "result transmission means" is a function or module that transmits the character generation results received by the server via the generation result receiving means to the user's terminal.

[0520] "Display means" is a function or module that allows the terminal to serialize the character generation results and display them to the user.

[0521] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[0522] The "document creation means" is a function or interface that allows the user to create a notice about the department using the character generation results.

[0523] This invention is a system in which a user inputs information about a department, an original character is generated based on that information using generative artificial intelligence, and a notice is created using the generated character.

[0524] System Overview

[0525] First, the user uses a terminal to input basic information about the department, including the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[0526] The server receives the information sent from the device and sends it to the generative AI as a character generation request. At this time, the server creates a prompt and calls the generative AI's API. The generative AI generates an original character based on the received information and returns the generation results, such as the character name, character description, and character image URL, to the server.

[0527] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[0528] Program processing details

[0529] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[0530] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[0531] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[0532] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[0533] Specific examples

[0534] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[0535] Department name: IT department

[0536] Department role: System operation and maintenance

[0537] What we want to announce: Introducing new security rules

[0538] The server sends this information to the generative AI and receives the following as examples of generated characters:

[0539] Character Name: Security-kun

[0540] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0541] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0542] Based on the results, the user creates a message like this:

[0543] Hello everyone!

[0544] This is Security-kun.

[0545] Today I would like to inform you about the activities of our department.

[0546] A security expert working in the IT department, always providing the latest security information to everyone

[0547] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0548] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[0549] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0550] Step 1:

[0551] User enters department information

[0552] The user launches a browser on their device and accesses a web form for entering department information. This form has input fields for the department name, department role, and information to be disseminated. The user enters the necessary information into each field and presses the "Submit" button. This loads the entered information into the device. Specifically, the user launches a browser, accesses the specified URL, enters the department information, and then clicks the "Submit" button.

[0553] Input: Department name, department role, information to be disseminated

[0554] Output: Department information entry completion status on the terminal

[0555] Step 2:

[0556] The device sends the input information to the server

[0557] The device serializes the department information entered by the user into JSON format and creates an HTTP POST request. This request is sent to the server. The sent information includes the department name, department role, and the information to be disseminated. This allows data to be securely transferred from the device to the server. Specifically, the device converts the department information into JSON format and sends it to the server as an HTTP POST request.

[0558] Input: Department information entered by the user

[0559] Output: Department information sent to the server in JSON format

[0560] Step 3:

[0561] The server calls the AI ​​model to generate the character.

[0562] Based on the received department information, the server creates a prompt to call the generative AI's API. The prompt includes the department name, role, and information to be communicated. Using the created prompt, the server sends a character generation request to the generative AI. The generative AI analyzes the received information and generates an original character. Specifically, the server creates a prompt, calls the generative AI's API, and sends a character generation request.

[0563] Input: Department information received by the server

[0564] Output: A character generation request to the generative artificial intelligence

[0565] Step 4:

[0566] The server receives the generated results and sends them to the terminal.

[0567] The generative AI generates a character name, character description, and character image URL as the character generation result and sends them back to the server. The server encodes the generation result into JSON format and sends it to the terminal as an HTTP response. Specifically, the server receives the generation result, converts it into JSON format, and sends it to the terminal as an HTTP response.

[0568] Input: Character generation results returned from generative artificial intelligence

[0569] Output: JSON format character generation results sent to the terminal

[0570] Step 5:

[0571] The user creates a message based on the character information.

[0572] The user views the generated character information in the browser on the device. This information includes the character name, character description, and character image URL. The user creates a message based on this information. Specifically, the user checks the character information on the device, creates a message, and sends the content to other departments within the company via email or the internal bulletin board.

[0573] Input: Character generation results displayed on the terminal

[0574] Output: The created announcement

[0575] (Application example 1)

[0576] 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."

[0577] Traditionally, information sharing between departments within a company has been done through documents and emails, but these lacked visual appeal and often did not effectively communicate the information to the recipient. Similarly, there were limited ways to effectively inform customers about the introduction of new products and services. This resulted in problems such as it taking time for recipients to understand the content, or the intended information not being conveyed accurately.

[0578] 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.

[0579] In this invention, the server includes an input means for a user to input information about the department, a receiving means for the server to receive the information input from the input means, a calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, a receiving means for the server to receive a character generation result from the generative artificial intelligence, a sending means for the server to send the character generation result to the user's device, a push notification means for the server to create a message using the character generation result and send a push notification to the smartphone device, and a display means for receiving the push notification on the smartphone device and interactively displaying detailed information. This enables efficient and effective sharing of information within and outside the department using a visually appealing means.

[0580] A "user" is a person or organization that uses the system to input information about a department and to use the generated characters and announcements.

[0581] "Information about the department" is basic information about a specific department, such as its name, role, and the details you want to make known.

[0582] "Input means" refers to a device or software that has an interface for users to input information about departments.

[0583] A "server" is a computer system that calls a generative artificial intelligence based on received information and generates a character.

[0584] The "receiving means" is a function that allows the server to receive information sent from the input means.

[0585] The "calling means" is a function for the server to call the generative artificial intelligence based on the information received by the receiving means and send a character generation request.

[0586] "Generative AI" is an AI technology that generates original characters based on input information.

[0587] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[0588] The "transmission means" is a function for the server to transmit the character generation results to the user's terminal.

[0589] The "push notification means" is a function that sends a notification message including the character generation results generated by the server to the smartphone terminal to notify the user.

[0590] "Display means" refers to a function that allows a smartphone device to receive push notifications and interactively display detailed information.

[0591] The present invention is a system for visually and effectively sharing information between departments within a company. This system allows a user to input information about their department, and uses generative artificial intelligence to generate original characters based on that information, and then creates announcements using the generated characters. Specific embodiments of the system are described below.

[0592] First, the user uses a device (e.g., a smartphone or PC) to enter basic information about the department. This information includes, for example, the name of the department, its role, and the information to be disseminated. Input methods include text boxes and drop-down lists. Once input is complete, the device serializes the information into an appropriate format and sends it to the server.

[0593] Next, the server receives the information sent from the user's terminal using the receiving means.The server then uses the calling means to call a generative artificial intelligence (specifically, a generative AI model) based on the received information and sends a character generation request.The generative artificial intelligence generates an original character based on the received information and generates a character name, character description, and character image URL.

[0594] The server receives the generated character generation results using a receiving means and transmits them again to the user's device using a transmitting means. The user creates a message about the department based on the character generation results displayed on the device. This allows for visually appealing information communication. The message includes the name and description of the generated character, an image URL, etc. The server then transmits the created message to the smartphone device via a push notification means.

[0595] Users who receive a push notification on their smartphone can tap the notification to interactively display detailed information, making it easy to check the announcement and enabling efficient information sharing.

[0596] Hardware and software used

[0597] Hardware: Servers, smartphones, PCs

[0598] Software: Flask (Python framework), API for generative AI models

[0599] Specific examples

[0600] For example, if the New Product Development department wants to announce the introduction of a new security product, they might enter the following information:

[0601] Department name: New Product Development Department

[0602] Department Role: Developing and introducing new products and services

[0603] Just wanted to let you know: The latest electronic security gadgets have arrived!

[0604] The server sends this information to the generative AI and receives the following character generation results:

[0605] Character Name: Security Master

[0606] Character description: A master of the latest security products, providing customers with a safer life.

[0607] Character image URL: https: / / example-ai-service.com / images / securitymaster.png

[0608] Users can create a message based on the results, which will be pushed to their smartphone. For example:

[0609] "Hello everyone! This is Security Master. Today I'll be introducing the latest electronic security gadgets. For more details, please see this illustration: https: / / example-ai-service.com / images / SecurityMaster.png"

[0610] In this way, the system allows for effective dissemination of information both within and outside the department, and allows for information sharing using visually appealing means.

[0611] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0612] Step 1:

[0613] The user enters basic information about the department.

[0614] Input: Department name, department role, information to be disseminated

[0615] Users use a device (smartphone or PC) to enter the department name, department role, and information they want to share into text boxes and drop-down lists on a specific screen. Once the input is complete, the device serializes this information into an appropriate data format such as JSON.

[0616] Step 2:

[0617] The terminal transmits the input information to the server.

[0618] Output: Serialized department information

[0619] The terminal sends the serialized department information to the server as an HTTP POST request. The receiving server has a receiving means implemented, and receives this request.

[0620] Step 3:

[0621] The server calls a generative artificial intelligence based on the information received.

[0622] Input: Serialized department information

[0623] The server analyzes the received department information and sends a character generation request to the generative AI API based on that data. Specifically, it uses a calling method to send the department name, department role, and announcements to the API.

[0624] Step 4:

[0625] The generative artificial intelligence generates a character based on the character generation request and returns the result.

[0626] Output: Character generation result (character name, description, image URL)

[0627] The generative AI model analyzes the received information and generates an original character. Information about the generated character (character name, description, image URL) is sent back to the server.

[0628] Step 5:

[0629] The server receives the character generation results and sends them to the user's terminal.

[0630] Input: Character generation result

[0631] The server transmits the character generation results received from the generative AI back to the user's terminal, using the transmission means to transmit the result data as an HTTP response.

[0632] Step 6:

[0633] The user receives the character generation results on the terminal and they are displayed.

[0634] Output: Character information displayed on the screen (character name, description, image URL)

[0635] The user's device displays the character generation results received from the server, and the user checks the displayed character information.

[0636] Step 7:

[0637] The user creates a message based on the character generation results.

[0638] Input: Character generation results, information

[0639] Users create visually appealing announcements based on the displayed character names, descriptions, and image URLs. The completed announcements are saved on the device.

[0640] Step 8:

[0641] The server will push the created notice to the smartphone device.

[0642] Input: Created announcement

[0643] The server sends the message created by the user to other smartphone terminals using push notification means. Specifically, the notification content is sent through a push notification server.

[0644] Step 9:

[0645] The smartphone device receives a push notification, and the user taps the notification to display detailed information.

[0646] Output: Push notification, display of detailed information

[0647] When a push notification is received, it will be displayed on the smartphone. When the user taps on the notification, detailed information will be displayed interactively on the screen, allowing the user to check the information.

[0648] This series of steps enables effective visual information sharing both within and outside the company.

[0649] 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.

[0650] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on the information using generative artificial intelligence, and the generated character is used to create announcements. Specific embodiments of the present invention are described in detail below.

[0651] System Overview

[0652] First, a user uses a device to enter basic information about their department, such as the department's name, its role, and any information they want to share. The device then collects this information and activates an emotion engine that analyzes the user's input, typing speed, and possibly facial expressions and voice.

[0653] The emotion engine analyzes the user's input operations and real-time biometric data to recognize the user's emotions. For example, if the user is typing quickly, it can detect emotions such as "impatience" or "tension."

[0654] The recognized emotion information and department information are sent from the device to the server. Based on the received information, the server sends a character generation request to the generative AI. The generative AI adjusts the character's attributes taking the user's emotions into account and generates the character. For example, if the user is "nervous," the generated character can have a more relaxed atmosphere.

[0655] The generative AI returns the generated results, including the character name, character description, and character image URL, to the server. The server receives the generated results and sends them back to the terminal. The user uses the character generation results displayed on the terminal to create a notice for the department. This notice includes the generated character's name, description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[0656] Program processing details

[0657] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields such as text boxes and drop-down lists, which the user uses to enter the necessary information. When the user begins to enter information, the emotion engine is activated and begins analyzing the input content, the facial expressions of the user in front of the screen, and the voice.

[0658] The emotion engine recognizes a user's emotions in real time using multiple data points, including analysis of input content, keyboard typing speed, and the user's facial expressions and voice. For example, if a user types quickly, their emotion may be determined to be "impatience."

[0659] The emotion information and department information recognized by the emotion engine are serialized into an appropriate format and sent to the server. The server analyzes the received data and calls the generative artificial intelligence API. This request includes the department name, role, message content, and recognized emotion information.

[0660] The generative AI analyzes the received information and adjusts the character's attributes to match the user's emotions. For example, if the user is "worried," the generated character may be changed to a design that gives a sense of security. The generated character name, character description, and image URL are then sent back to the server as the generation result.

[0661] The server receives the generated results and sends them back to the user's device. The generated character information is displayed on the user's device, and the user can use this information to create a message. Using the character name, description, and image URL, users can create a more visually appealing message and effectively communicate information to other departments within the company.

[0662] Specific examples

[0663] For example, suppose the IT department wants to announce a new security rule. The user enters the following information:

[0664] Department name: IT department

[0665] Department role: System operation and maintenance

[0666] What we want to announce: Introducing new security rules

[0667] If the user is typing in a hurry, the emotion engine will recognize this "impatience." The server sends this information to the generative AI, which then generates a relaxed character that alleviates the "impatience."

[0668] An example of a generated character would be:

[0669] Character Name: Security-kun

[0670] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0671] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0672] Based on the results, the user creates a message like this:

[0673] Hello everyone!

[0674] This is Security-kun.

[0675] Today I would like to inform you about the activities of our department.

[0676] A security expert working in the IT department, always providing the latest security information to everyone

[0677] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0678] In this way, by using a system that combines an emotion engine and generative artificial intelligence, effective information sharing can be achieved by taking into account the user's emotions and using visually appealing characters.

[0679] The processing flow will be explained below.

[0680] Step 1:

[0681] The user enters information about the department (department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[0682] Step 2:

[0683] The device activates its emotion engine and begins analyzing the user's input operations, input content, and keyboard typing speed. It also uses a camera and microphone to capture the user's facial expressions and voice, and comprehensively recognizes emotions.

[0684] Step 3:

[0685] The emotion engine analyzes the user's emotion (e.g., "tension" or "impatience") and sends the emotion information along with the department information to the server. The device serializes this data into an appropriate format and sends it to the server as an HTTP request.

[0686] Step 4:

[0687] The server receives the request sent from the device. The server analyzes the received data and checks its validity. Then, it calls the generative AI API and prepares to send a character generation request.

[0688] Step 5:

[0689] The server calls the generative AI API and sends department information including emotion information. This request includes details of the department name, department role, desired message, and emotion information.

[0690] Step 6:

[0691] The generative AI receives and analyzes the character generation request. The generative AI adjusts the character's attributes taking into account the user's emotional information and generates an original character. For example, if the user's emotion is "tension," the character will have a relaxed atmosphere.

[0692] Step 7:

[0693] The generative AI returns the generated character results to the server, which include the character name, character description, and character image URL.

[0694] Step 8:

[0695] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[0696] Step 9:

[0697] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[0698] Step 10:

[0699] The user's device receives the generated results from the server and displays them on the screen. The user then uses this information to create a message. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[0700] Step 11:

[0701] Users can send announcements they create to other departments within the company. By using characters that reflect emotional information and detailed announcements, information can be conveyed to other departments effectively.

[0702] Example 2

[0703] 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."

[0704] Conventional information dissemination systems generate uniform characters and messages without considering the user's emotions, which can result in a lack of appeal and familiarity to the recipient. In particular, when the user is in a hurry or under stress, the messages created often lack an appropriate response to the situation. This makes it difficult to communicate information effectively.

[0705] 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.

[0706] In this invention, the server includes input means for a user to input information about the department, emotion recognition means for activating an emotion engine in the terminal when the user starts inputting information and recognizing the user's emotion, receiving means for the server to receive the information input from the input means and the emotion information recognized by the emotion recognition means, calling means for the server to call a generation AI model using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generation AI model, and sending means for the server to send the character generation result to the user's terminal. This enables character generation and message creation that take the user's emotions into consideration, improving appeal and familiarity to recipients and realizing effective information communication.

[0707] "User" refers to the person who operates this system and inputs department information.

[0708] "Department information" refers to basic information about a specific department, such as the department name, department role, and information you want to share.

[0709] A "terminal" is a device that a user uses to access the system and input information, and includes PCs, smartphones, tablets, etc.

[0710] An "emotion engine" refers to a piece of software or hardware that analyzes the user's input, typing speed, facial expressions, voice, etc., and recognizes the user's emotions.

[0711] "Emotion recognition means" refers to a function that identifies the user's emotions using an emotion engine.

[0712] "Serialization" refers to the process of converting data into a format that can be stored or transmitted.

[0713] "Server" refers to a device or system that receives and analyzes data sent from a user's device and sends a character generation request to a generative AI model.

[0714] "Generative AI model" refers to an artificial intelligence model that generates characters based on received information.

[0715] A "character generation request" is a request that instructs a generative AI model to generate a character using data that includes department information and emotional information.

[0716] "Character generation results" refers to information about the character generated by the generative AI model, including the character name, character description, and character image URL.

[0717] "Receiving means" refers to the function by which a terminal or server receives data.

[0718] "Transmission means" refers to the function of sending data from the server to the user's terminal.

[0719] The "creation means" refers to a function that allows a user to create a message using the character generation results.

[0720] The present invention is a system in which a user inputs information about their department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using a generative AI model, and the generated character is used to create announcements.

[0721] The user first uses a terminal to input basic information about the department. This basic information includes the department name, department role, and information to be disseminated. As soon as the user starts inputting, the terminal starts the emotion engine. The emotion engine analyzes the input content, keyboard typing speed, and in some cases the user's facial expressions and voice to recognize the user's emotions. The recognized emotion information and department information are sent from the terminal to the server.

[0722] The server analyzes the received information and calls the API of the generative AI model. The API request includes the department name, department role, information to be communicated, and recognized emotion information. The generative AI model adjusts the character's attributes based on the received data and generates an original character that reflects the user's emotions. For example, if the user is "nervous," it can generate a character with a relaxed atmosphere.

[0723] The generative AI model returns the generated character information (character name, character description, character image URL) to the server. The server receives this information and sends it back to the device. The device displays the generated character information to the user. The user creates a message based on the displayed character information. This message includes the character name, character description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[0724] For example, when IT announces new security rules, users enter the following information:

[0725] Department name: IT department

[0726] Department role: System operation and maintenance

[0727] What we want to announce: Introducing new security rules

[0728] If the user is typing in a hurry, the emotion engine will recognize the "impatience." The server sends this information to the generative AI model, which then generates a relaxed character that reduces the "impatience." An example of a generated character would be:

[0729] Character Name: Security-kun

[0730] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0731] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0732] Based on the results, the user creates a message like this:

[0733] Hello everyone!

[0734] This is Security-kun.

[0735] Today I would like to inform you about the activities of our department.

[0736] A security expert working in the IT department, always providing the latest security information to everyone

[0737] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0738] In this way, a character can be generated taking into consideration the user's emotions, and visually appealing announcements can be created.

[0739] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0740] Step 1:

[0741] (User enters department information and launches emotion engine)

[0742] The user launches a dedicated application on their device and accesses a department information input form. This form contains fields for entering the department name, department role, and information they want to share. As soon as the user starts entering information in these fields, the device starts the emotion engine in the background.

[0743] input:

[0744] Department name

[0745] Roles of the Department

[0746] Information to be made known

[0747] output:

[0748] Emotional Engine Activation

[0749] Operation:

[0750] The device collects user input information in real time and provides it to the emotion engine.

[0751] Step 2:

[0752] (Emotion recognition by emotion engine)

[0753] The emotion engine analyzes input content, keyboard typing speed, the user's facial expressions, and voice to recognize the user's emotions in real time. The analyzed emotion information continues to be updated until the user completes input.

[0754] input:

[0755] User input

[0756] Keyboard typing speed

[0757] User's facial expressions and voice

[0758] output:

[0759] Recognized emotional information

[0760] Operation:

[0761] The emotion engine uses multiple sensors and data analysis techniques to determine the user's emotional state. For example, if the user types quickly, it will detect "impatience."

[0762] Step 3:

[0763] (Transmitting emotional and departmental information)

[0764] When the user completes inputting the department information, the emotion engine determines the final emotion information, and the terminal serializes this emotion information and department information and transmits them to the server.

[0765] input:

[0766] Department information

[0767] Recognized emotional information

[0768] output:

[0769] Sending serialized data

[0770] Operation:

[0771] The device converts the input data and emotional information into an appropriate format and transmits it to a server via a network.

[0772] Step 4:

[0773] (Calling the generated AI model by the server)

[0774] The server analyzes the serialized data received from the device and calls the API of the generative AI model to send a character generation request.

[0775] input:

[0776] Data received from the device

[0777] output:

[0778] Character creation request submission

[0779] Operation:

[0780] The server analyzes the data, extracts the necessary information (department name, department role, announcements, emotional information), and sends it to the API of the generative AI model.

[0781] Step 5:

[0782] (Character generation using generative AI models)

[0783] The generative AI model analyzes the data received from the server and generates a character based on the user's emotions. The generated character information includes the character name, description, and image URL.

[0784] input:

[0785] Data sent from the server

[0786] output:

[0787] Generated character information

[0788] Operation:

[0789] The generative AI model uses data analysis and character synthesis algorithms to create characters that adapt to emotions.

[0790] Step 6:

[0791] (Sending character generation results from the server to the device)

[0792] The server analyzes the character generation results received from the generation AI model and sends them back to the terminal.

[0793] input:

[0794] Character information from generative AI models

[0795] output:

[0796] Transferring character generation results

[0797] Operation:

[0798] The server organizes the generated character information (character name, description, image URL) and sends it to the user's device.

[0799] Step 7:

[0800] (Displaying character information on a device and creating announcements)

[0801] The terminal displays the character generation results to the user, allowing the user to create a message based on the results.

[0802] input:

[0803] Character generation results received from the server

[0804] output:

[0805] Character information displayed to the user

[0806] Operation:

[0807] The terminal displays character information and provides a user interface for the user to create an effective message based on the information. The user uses the displayed character information to write a specific message and confirm its content.

[0808] (Application example 2)

[0809] 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."

[0810] Conventional information transmission systems provide characters and messages uniformly generated without considering the user's emotions, making it difficult to effectively transmit information according to a specific situation or emotional state. Furthermore, because the character generation is not dependent on the user's emotions, the system may lack visual appeal and user acceptance. This results in issues such as time-consuming transmission and understanding of information, reducing efficiency.

[0811] 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.

[0812] In this invention, the server includes input means for a user to input information about the department, receiving means for the server to receive the information input from the input means, calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generative artificial intelligence, sending means for the server to send the character generation result to the user's terminal, emotion recognition means for recognizing the user's emotion, adjustment means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means, and display means for displaying visually attractive notices using the generated character. This makes it possible to generate characters and create messages that take the user's emotions into consideration, thereby realizing visually attractive and easily accepted information transmission.

[0813] The "input means" is a means for a user to input information about a department.

[0814] The "receiving means" is a means by which the server receives information input from the input means.

[0815] The "calling means" is a means by which the server calls the generative artificial intelligence using the information received by the receiving means and transmits a character generation request.

[0816] "Generative AI" is an AI system that generates characters based on user information.

[0817] "Character generation results" refers to information about a character generated by generative artificial intelligence, including the character name, character description, and character image URL.

[0818] The "transmission means" is a means by which the server transmits the character generation results to the user's terminal.

[0819] The "emotion recognition means" is a means for recognizing the user's emotions.

[0820] The "adjustment means" is a means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means.

[0821] The "display means" is a means for displaying visually appealing notices on a user terminal using the generated characters.

[0822] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using generative artificial intelligence, and the generated character is used to create announcements.

[0823] System Overview

[0824] First, the user puts on the smart glasses and begins work. Using the smart glasses' input mechanism, the user enters information about their department, including the department name, role, and any information they wish to share. The smart glasses' built-in camera and microphone capture the user's facial expressions and voice, and analyze their emotions in real time. This emotion recognition is performed using an emotion engine such as Amazon Rekognition.

[0825] Next, the server receives the input information and the recognized emotion information using the receiving means. After that, the calling means calls the generative artificial intelligence (e.g., OpenAI's GPT-4) and sends a character generation request. This request includes the department name, role, content to be communicated, and the recognized emotion information.

[0826] The generative artificial intelligence generates a character based on the received information. The generated character's information (character name, description, image URL) is sent back to the server. The server then sends this information back to the user's smart glasses using a transmission means. The smart glasses then display the character information to the user using a display means. As a result, the user can create visually appealing messages using the generated character.

[0827] The specific hardware and software used

[0828] Smart Glasses: Smart glasses such as Oculus Quest 2

[0829] Sentiment engine: Amazon Rekognition

[0830] Generative artificial intelligence: OpenAI GPT-4

[0831] Server: AWS EC2 instance

[0832] Communication protocol: HTTP / HTTPS

[0833] Data serialization: JSON

[0834] Specific examples

[0835] For example, consider the case where a safety department employee is learning new safety rules.

[0836] The user puts on the smart glasses and enters the following information:

[0837] Department name: Safety Management Department

[0838] Procedure: Applying new safety rules

[0839] If the emotion engine detects that the user is feeling "anxiety" based on their facial expression or voice, the server sends this information to the generative AI, which then sends the following prompt:

[0840] "I'm worried about the application of the Safety Management Department's new safety rules."

[0841] The generative AI generates a character based on this information and returns the following character information, for example:

[0842] Character Name: Anshin-kun

[0843] Character description: A safety management expert who relieves everyone's worries

[0844] Image URL: https: / / example-ai-service.com / images / Anshinkun.png

[0845] The user's smart glasses will display this character information, allowing the user to learn new procedures with confidence.

[0846] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0847] Step 1:

[0848] The user puts on the smart glasses and begins work. The user uses the smart glasses' input means to input department information. This input includes the department name, role, and information to be disseminated. The input data is temporarily stored in the smart glasses' memory.

[0849] Step 2:

[0850] The device captures the user's facial expressions and voice. The smart glasses' built-in camera and microphone are used to collect biometric data, which is then processed into emotion recognition data. This data is sent in real time to the emotion engine (Amazon Rekognition).

[0851] Step 3:

[0852] The emotion engine analyzes the user's facial expressions and voice data to recognize the user's emotions. The analyzed emotion information (e.g., "anxiety" or "impatience") is generated and sent to the server. This emotion information is serialized in JSON format.

[0853] Step 4:

[0854] The server receives the user's input information and the recognized emotion information. Specifically, this includes the department name, role, desired message, and emotion information. Based on the received data, the server creates a character generation request for the generative AI. The request is generated in the following format:

[0855] Text format:

[0856] "Department name: Safety Management Department, Procedure: I am concerned about the application of new safety rules."

[0857] The server sends this request to the API of the generative artificial intelligence (OpenAI GPT-4).

[0858] Step 5:

[0859] The generative AI receives the request and generates a character based on the department information and emotion information. The generated character information (character name, character description, image URL) is sent back to the server. In this process, the character design is adapted to the user's emotion.

[0860] Step 6:

[0861] The server transmits the received character generation results to the user's smart glasses. The transmitted data includes the generated character name, character description, and image URL. The data is sent to the user's terminal using a transmission means.

[0862] Step 7:

[0863] The device (smart glasses) receives the character generation results and visually displays them. The user then creates a message based on the displayed character information. Specifically, the user can insert the character name, description, and image URL into the message, making it possible to convey information in a visually appealing way.

[0864] Specific working example:

[0865] 1. The user inputs a "new safety rule" in the "Safety Management Department," and the emotion of "anxiety" is recognized.

[0866] 2. The server sends a request to the generative AI saying, "I am concerned about the application of the Safety Management Department's new safety rules."

[0867] 3. Information about the generated character, "Anshin-kun," is sent back to the server and displayed on the smart glasses.

[0868] 4. Users create announcements that include descriptions and images of Anshin-kun, and communicate them to other employees in a visually appealing way.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] [Third embodiment]

[0873] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0874] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0875] 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).

[0876] 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.

[0877] 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.

[0878] 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).

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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."

[0885] The present invention is a system in which a user inputs information about a department, generates an original character based on that information using generative artificial intelligence, and creates a message using the generated character. Specific embodiments of the present invention are described below.

[0886] System Overview

[0887] First, the user uses a terminal to input basic information about the department, such as the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[0888] The server receives the information sent from the device and sends it to the generative AI as a character generation request. The generative AI generates an original character based on the received information and returns the generated results, such as the character name, character description, and character image URL, to the server.

[0889] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[0890] Program processing details

[0891] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[0892] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[0893] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[0894] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[0895] Specific examples

[0896] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[0897] Department name: IT department

[0898] Department role: System operation and maintenance

[0899] What we want to announce: Introducing new security rules

[0900] The server sends this information to the generative AI and receives the following as examples of generated characters:

[0901] Character Name: Security-kun

[0902] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0903] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0904] Based on the results, the user creates a message like this:

[0905] Hello everyone!

[0906] This is Security-kun.

[0907] Today I would like to inform you about the activities of our department.

[0908] A security expert working in the IT department, always providing the latest security information to everyone

[0909] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0910] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[0911] Through such specific embodiments, the present invention improves communication between departments within a company and makes it possible to disseminate information more effectively.

[0912] The processing flow will be explained below.

[0913] Step 1:

[0914] The user enters information about the department (e.g., department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[0915] Step 2:

[0916] The terminal serializes the information entered by the user into an appropriate format and sends an HTTP request to the server, which includes information about the department entered by the user.

[0917] Step 3:

[0918] The server receives the request sent from the device. The server analyzes the received data and checks its contents. After checking the validity of the data, it prepares to send a character generation request to the generative AI.

[0919] Step 4:

[0920] The server calls the generative AI API and sends a character generation request that includes information about the department, such as the department name, role, and desired publicity.

[0921] Step 5:

[0922] The generative AI receives and analyzes the character generation request. Based on the input information, it starts the process of generating an appropriate original character. The generation process includes the character name, character description, and character image URL.

[0923] Step 6:

[0924] The generative AI returns the generated character results to the server. The results include the character name, character description, and the URL of the character image. The server receives the generated results.

[0925] Step 7:

[0926] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[0927] Step 8:

[0928] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[0929] Step 9:

[0930] The user's device receives the generated results from the server and displays them on the screen. The user then creates a message based on this information. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[0931] Step 10:

[0932] Users can send the announcements they create to other departments within the company, thereby enabling effective information sharing using the generated characters.

[0933] Example 1

[0934] 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."

[0935] With conventional information sharing systems, communication between departments was complicated and it took a long time to create announcements. In addition, there was a lack of visually appealing means of communicating information, which made the impact on the recipient weak and sometimes led to ineffective communication of information.

[0936] 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.

[0937] In this invention, the server includes an information receiving means, an AI calling means, a generation result receiving means, a result sending means, and a display means, which allows a character to be generated by the generative AI based on the department information entered by the user, and a message to be created based on the character information.

[0938] "Information input means" refers to an input device or interface that a user uses to input information about a department.

[0939] The "information receiving means" is a function or module that allows the server to receive department information sent from the information input means.

[0940] "Artificial intelligence calling means" is a function or module for calling a generative artificial intelligence using information received by the server and sending a character generation request.

[0941] The "generation result receiving means" is a function or module that allows the server to receive character generation results from the generative artificial intelligence.

[0942] The "result transmission means" is a function or module that transmits the character generation results received by the server via the generation result receiving means to the user's terminal.

[0943] "Display means" is a function or module that allows the terminal to serialize the character generation results and display them to the user.

[0944] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[0945] The "document creation means" is a function or interface that allows the user to create a notice about the department using the character generation results.

[0946] This invention is a system in which a user inputs information about a department, an original character is generated based on that information using generative artificial intelligence, and a notice is created using the generated character.

[0947] System Overview

[0948] First, the user uses a terminal to input basic information about the department, including the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[0949] The server receives the information sent from the device and sends it to the generative AI as a character generation request. At this time, the server creates a prompt and calls the generative AI's API. The generative AI generates an original character based on the received information and returns the generation results, such as the character name, character description, and character image URL, to the server.

[0950] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[0951] Program processing details

[0952] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[0953] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[0954] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[0955] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[0956] Specific examples

[0957] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[0958] Department name: IT department

[0959] Department role: System operation and maintenance

[0960] What we want to announce: Introducing new security rules

[0961] The server sends this information to the generative AI and receives the following as examples of generated characters:

[0962] Character Name: Security-kun

[0963] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[0964] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[0965] Based on the results, the user creates a message like this:

[0966] Hello everyone!

[0967] This is Security-kun.

[0968] Today I would like to inform you about the activities of our department.

[0969] A security expert working in the IT department, always providing the latest security information to everyone

[0970] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[0971] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[0972] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0973] Step 1:

[0974] User enters department information

[0975] The user launches a browser on their device and accesses a web form for entering department information. This form has input fields for the department name, department role, and information to be disseminated. The user enters the necessary information into each field and presses the "Submit" button. This loads the entered information into the device. Specifically, the user launches a browser, accesses the specified URL, enters the department information, and then clicks the "Submit" button.

[0976] Input: Department name, department role, information to be disseminated

[0977] Output: Department information entry completion status on the terminal

[0978] Step 2:

[0979] The device sends the input information to the server

[0980] The device serializes the department information entered by the user into JSON format and creates an HTTP POST request. This request is sent to the server. The sent information includes the department name, department role, and the information to be disseminated. This allows data to be securely transferred from the device to the server. Specifically, the device converts the department information into JSON format and sends it to the server as an HTTP POST request.

[0981] Input: Department information entered by the user

[0982] Output: Department information sent to the server in JSON format

[0983] Step 3:

[0984] The server calls the AI ​​model to generate the character.

[0985] Based on the received department information, the server creates a prompt to call the generative AI's API. The prompt includes the department name, role, and information to be communicated. Using the created prompt, the server sends a character generation request to the generative AI. The generative AI analyzes the received information and generates an original character. Specifically, the server creates a prompt, calls the generative AI's API, and sends a character generation request.

[0986] Input: Department information received by the server

[0987] Output: A character generation request to the generative artificial intelligence

[0988] Step 4:

[0989] The server receives the generated results and sends them to the terminal.

[0990] The generative AI generates a character name, character description, and character image URL as the character generation result and sends them back to the server. The server encodes the generation result into JSON format and sends it to the terminal as an HTTP response. Specifically, the server receives the generation result, converts it into JSON format, and sends it to the terminal as an HTTP response.

[0991] Input: Character generation results returned from generative artificial intelligence

[0992] Output: JSON format character generation results sent to the terminal

[0993] Step 5:

[0994] The user creates a message based on the character information.

[0995] The user views the generated character information in the browser on the device. This information includes the character name, character description, and character image URL. The user creates a message based on this information. Specifically, the user checks the character information on the device, creates a message, and sends the content to other departments within the company via email or the internal bulletin board.

[0996] Input: Character generation results displayed on the terminal

[0997] Output: The created announcement

[0998] (Application example 1)

[0999] 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."

[1000] Traditionally, information sharing between departments within a company has been done through documents and emails, but these lacked visual appeal and often did not effectively communicate the information to the recipient. Similarly, there were limited ways to effectively inform customers about the introduction of new products and services. This resulted in problems such as it taking time for recipients to understand the content, or the intended information not being conveyed accurately.

[1001] 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.

[1002] In this invention, the server includes an input means for a user to input information about the department, a receiving means for the server to receive the information input from the input means, a calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, a receiving means for the server to receive a character generation result from the generative artificial intelligence, a sending means for the server to send the character generation result to the user's device, a push notification means for the server to create a message using the character generation result and send a push notification to the smartphone device, and a display means for receiving the push notification on the smartphone device and interactively displaying detailed information. This enables efficient and effective sharing of information within and outside the department using a visually appealing means.

[1003] A "user" is a person or organization that uses the system to input information about a department and to use the generated characters and announcements.

[1004] "Information about the department" is basic information about a specific department, such as its name, role, and the details you want to make known.

[1005] "Input means" refers to a device or software that has an interface for users to input information about departments.

[1006] A "server" is a computer system that calls a generative artificial intelligence based on received information and generates a character.

[1007] The "receiving means" is a function that allows the server to receive information sent from the input means.

[1008] The "calling means" is a function for the server to call the generative artificial intelligence based on the information received by the receiving means and send a character generation request.

[1009] "Generative AI" is an AI technology that generates original characters based on input information.

[1010] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[1011] The "transmission means" is a function for the server to transmit the character generation results to the user's terminal.

[1012] The "push notification means" is a function that sends a notification message including the character generation results generated by the server to the smartphone terminal to notify the user.

[1013] "Display means" refers to a function that allows a smartphone device to receive push notifications and interactively display detailed information.

[1014] The present invention is a system for visually and effectively sharing information between departments within a company. This system allows a user to input information about their department, and uses generative artificial intelligence to generate original characters based on that information, and then creates announcements using the generated characters. Specific embodiments of the system are described below.

[1015] First, the user uses a device (e.g., a smartphone or PC) to enter basic information about the department. This information includes, for example, the name of the department, its role, and the information to be disseminated. Input methods include text boxes and drop-down lists. Once input is complete, the device serializes the information into an appropriate format and sends it to the server.

[1016] Next, the server receives the information sent from the user's terminal using the receiving means.The server then uses the calling means to call a generative artificial intelligence (specifically, a generative AI model) based on the received information and sends a character generation request.The generative artificial intelligence generates an original character based on the received information and generates a character name, character description, and character image URL.

[1017] The server receives the generated character generation results using a receiving means and transmits them again to the user's device using a transmitting means. The user creates a message about the department based on the character generation results displayed on the device. This allows for visually appealing information communication. The message includes the name and description of the generated character, an image URL, etc. The server then transmits the created message to the smartphone device via a push notification means.

[1018] Users who receive a push notification on their smartphone can tap the notification to interactively display detailed information, making it easy to check the announcement and enabling efficient information sharing.

[1019] Hardware and software used

[1020] Hardware: Servers, smartphones, PCs

[1021] Software: Flask (Python framework), API for generative AI models

[1022] Specific examples

[1023] For example, if the New Product Development department wants to announce the introduction of a new security product, they might enter the following information:

[1024] Department name: New Product Development Department

[1025] Department Role: Developing and introducing new products and services

[1026] Just wanted to let you know: The latest electronic security gadgets have arrived!

[1027] The server sends this information to the generative AI and receives the following character generation results:

[1028] Character Name: Security Master

[1029] Character description: A master of the latest security products, providing customers with a safer life.

[1030] Character image URL: https: / / example-ai-service.com / images / securitymaster.png

[1031] Users can create a message based on the results, which will be pushed to their smartphone. For example:

[1032] "Hello everyone! This is Security Master. Today I'll be introducing the latest electronic security gadgets. For more details, please see this illustration: https: / / example-ai-service.com / images / SecurityMaster.png"

[1033] In this way, the system allows for effective dissemination of information both within and outside the department, and allows for information sharing using visually appealing means.

[1034] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1035] Step 1:

[1036] The user enters basic information about the department.

[1037] Input: Department name, department role, information to be disseminated

[1038] Users use a device (smartphone or PC) to enter the department name, department role, and information they want to share into text boxes and drop-down lists on a specific screen. Once the input is complete, the device serializes this information into an appropriate data format such as JSON.

[1039] Step 2:

[1040] The terminal transmits the input information to the server.

[1041] Output: Serialized department information

[1042] The terminal sends the serialized department information to the server as an HTTP POST request. The receiving server has a receiving means implemented, and receives this request.

[1043] Step 3:

[1044] The server calls a generative artificial intelligence based on the information received.

[1045] Input: Serialized department information

[1046] The server analyzes the received department information and sends a character generation request to the generative AI API based on that data. Specifically, it uses a calling method to send the department name, department role, and announcements to the API.

[1047] Step 4:

[1048] The generative artificial intelligence generates a character based on the character generation request and returns the result.

[1049] Output: Character generation result (character name, description, image URL)

[1050] The generative AI model analyzes the received information and generates an original character. Information about the generated character (character name, description, image URL) is sent back to the server.

[1051] Step 5:

[1052] The server receives the character generation results and sends them to the user's terminal.

[1053] Input: Character generation result

[1054] The server transmits the character generation results received from the generative AI back to the user's terminal, using the transmission means to transmit the result data as an HTTP response.

[1055] Step 6:

[1056] The user receives the character generation results on the terminal and they are displayed.

[1057] Output: Character information displayed on the screen (character name, description, image URL)

[1058] The user's device displays the character generation results received from the server, and the user checks the displayed character information.

[1059] Step 7:

[1060] The user creates a message based on the character generation results.

[1061] Input: Character generation results, information

[1062] Users create visually appealing announcements based on the displayed character names, descriptions, and image URLs. The completed announcements are saved on the device.

[1063] Step 8:

[1064] The server will push the created notice to the smartphone device.

[1065] Input: Created announcement

[1066] The server sends the message created by the user to other smartphone terminals using push notification means. Specifically, the notification content is sent through a push notification server.

[1067] Step 9:

[1068] The smartphone device receives a push notification, and the user taps the notification to display detailed information.

[1069] Output: Push notification, display of detailed information

[1070] When a push notification is received, it will be displayed on the smartphone. When the user taps on the notification, detailed information will be displayed interactively on the screen, allowing the user to check the information.

[1071] This series of steps enables effective visual information sharing both within and outside the company.

[1072] 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.

[1073] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on the information using generative artificial intelligence, and the generated character is used to create announcements. Specific embodiments of the present invention are described in detail below.

[1074] System Overview

[1075] First, a user uses a device to enter basic information about their department, such as the department's name, its role, and any information they want to share. The device then collects this information and activates an emotion engine that analyzes the user's input, typing speed, and possibly facial expressions and voice.

[1076] The emotion engine analyzes the user's input operations and real-time biometric data to recognize the user's emotions. For example, if the user is typing quickly, it can detect emotions such as "impatience" or "tension."

[1077] The recognized emotion information and department information are sent from the device to the server. Based on the received information, the server sends a character generation request to the generative AI. The generative AI adjusts the character's attributes taking the user's emotions into account and generates the character. For example, if the user is "nervous," the generated character can have a more relaxed atmosphere.

[1078] The generative AI returns the generated results, including the character name, character description, and character image URL, to the server. The server receives the generated results and sends them back to the terminal. The user uses the character generation results displayed on the terminal to create a notice for the department. This notice includes the generated character's name, description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[1079] Program processing details

[1080] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields such as text boxes and drop-down lists, which the user uses to enter the necessary information. When the user begins to enter information, the emotion engine is activated and begins analyzing the input content, the facial expressions of the user in front of the screen, and the voice.

[1081] The emotion engine recognizes a user's emotions in real time using multiple data points, including analysis of input content, keyboard typing speed, and the user's facial expressions and voice. For example, if a user types quickly, their emotion may be determined to be "impatience."

[1082] The emotion information and department information recognized by the emotion engine are serialized into an appropriate format and sent to the server. The server analyzes the received data and calls the generative artificial intelligence API. This request includes the department name, role, message content, and recognized emotion information.

[1083] The generative AI analyzes the received information and adjusts the character's attributes to match the user's emotions. For example, if the user is "worried," the generated character may be changed to a design that gives a sense of security. The generated character name, character description, and image URL are then sent back to the server as the generation result.

[1084] The server receives the generated results and sends them back to the user's device. The generated character information is displayed on the user's device, and the user can use this information to create a message. Using the character name, description, and image URL, users can create a more visually appealing message and effectively communicate information to other departments within the company.

[1085] Specific examples

[1086] For example, suppose the IT department wants to announce a new security rule. The user enters the following information:

[1087] Department name: IT department

[1088] Department role: System operation and maintenance

[1089] What we want to announce: Introducing new security rules

[1090] If the user is typing in a hurry, the emotion engine will recognize this "impatience." The server sends this information to the generative AI, which then generates a relaxed character that alleviates the "impatience."

[1091] An example of a generated character would be:

[1092] Character Name: Security-kun

[1093] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[1094] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[1095] Based on the results, the user creates a message like this:

[1096] Hello everyone!

[1097] This is Security-kun.

[1098] Today I would like to inform you about the activities of our department.

[1099] A security expert working in the IT department, always providing the latest security information to everyone

[1100] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[1101] In this way, by using a system that combines an emotion engine and generative artificial intelligence, effective information sharing can be achieved by taking into account the user's emotions and using visually appealing characters.

[1102] The processing flow will be explained below.

[1103] Step 1:

[1104] The user enters information about the department (department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[1105] Step 2:

[1106] The device activates its emotion engine and begins analyzing the user's input operations, input content, and keyboard typing speed. It also uses a camera and microphone to capture the user's facial expressions and voice, and comprehensively recognizes emotions.

[1107] Step 3:

[1108] The emotion engine analyzes the user's emotion (e.g., "tension" or "impatience") and sends the emotion information along with the department information to the server. The device serializes this data into an appropriate format and sends it to the server as an HTTP request.

[1109] Step 4:

[1110] The server receives the request sent from the device. The server analyzes the received data and checks its validity. Then, it calls the generative AI API and prepares to send a character generation request.

[1111] Step 5:

[1112] The server calls the generative AI API and sends department information including emotion information. This request includes details of the department name, department role, desired message, and emotion information.

[1113] Step 6:

[1114] The generative AI receives and analyzes the character generation request. The generative AI adjusts the character's attributes taking into account the user's emotional information and generates an original character. For example, if the user's emotion is "tension," the character will have a relaxed atmosphere.

[1115] Step 7:

[1116] The generative AI returns the generated character results to the server, which include the character name, character description, and character image URL.

[1117] Step 8:

[1118] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[1119] Step 9:

[1120] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[1121] Step 10:

[1122] The user's device receives the generated results from the server and displays them on the screen. The user then uses this information to create a message. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[1123] Step 11:

[1124] Users can send announcements they create to other departments within the company. By using characters that reflect emotional information and detailed announcements, information can be conveyed to other departments effectively.

[1125] Example 2

[1126] 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."

[1127] Conventional information dissemination systems generate uniform characters and messages without considering the user's emotions, which can result in a lack of appeal and familiarity to the recipient. In particular, when the user is in a hurry or under stress, the messages created often lack an appropriate response to the situation. This makes it difficult to communicate information effectively.

[1128] 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.

[1129] In this invention, the server includes input means for a user to input information about the department, emotion recognition means for activating an emotion engine in the terminal when the user starts inputting information and recognizing the user's emotion, receiving means for the server to receive the information input from the input means and the emotion information recognized by the emotion recognition means, calling means for the server to call a generation AI model using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generation AI model, and sending means for the server to send the character generation result to the user's terminal. This enables character generation and message creation that take the user's emotions into consideration, improving appeal and familiarity to recipients and realizing effective information communication.

[1130] "User" refers to the person who operates this system and inputs department information.

[1131] "Department information" refers to basic information about a specific department, such as the department name, department role, and information you want to share.

[1132] A "terminal" is a device that a user uses to access the system and input information, and includes PCs, smartphones, tablets, etc.

[1133] An "emotion engine" refers to a piece of software or hardware that analyzes the user's input, typing speed, facial expressions, voice, etc., and recognizes the user's emotions.

[1134] "Emotion recognition means" refers to a function that identifies the user's emotions using an emotion engine.

[1135] "Serialization" refers to the process of converting data into a format that can be stored or transmitted.

[1136] "Server" refers to a device or system that receives and analyzes data sent from a user's device and sends a character generation request to a generative AI model.

[1137] "Generative AI model" refers to an artificial intelligence model that generates characters based on received information.

[1138] A "character generation request" is a request that instructs a generative AI model to generate a character using data that includes department information and emotional information.

[1139] "Character generation results" refers to information about the character generated by the generative AI model, including the character name, character description, and character image URL.

[1140] "Receiving means" refers to the function by which a terminal or server receives data.

[1141] "Transmission means" refers to the function of sending data from the server to the user's terminal.

[1142] The "creation means" refers to a function that allows a user to create a message using the character generation results.

[1143] The present invention is a system in which a user inputs information about their department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using a generative AI model, and the generated character is used to create announcements.

[1144] The user first uses a terminal to input basic information about the department. This basic information includes the department name, department role, and information to be disseminated. As soon as the user starts inputting, the terminal starts the emotion engine. The emotion engine analyzes the input content, keyboard typing speed, and in some cases the user's facial expressions and voice to recognize the user's emotions. The recognized emotion information and department information are sent from the terminal to the server.

[1145] The server analyzes the received information and calls the API of the generative AI model. The API request includes the department name, department role, information to be communicated, and recognized emotion information. The generative AI model adjusts the character's attributes based on the received data and generates an original character that reflects the user's emotions. For example, if the user is "nervous," it can generate a character with a relaxed atmosphere.

[1146] The generative AI model returns the generated character information (character name, character description, character image URL) to the server. The server receives this information and sends it back to the device. The device displays the generated character information to the user. The user creates a message based on the displayed character information. This message includes the character name, character description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[1147] For example, when IT announces new security rules, users enter the following information:

[1148] Department name: IT department

[1149] Department role: System operation and maintenance

[1150] What we want to announce: Introducing new security rules

[1151] If the user is typing in a hurry, the emotion engine will recognize the "impatience." The server sends this information to the generative AI model, which then generates a relaxed character that reduces the "impatience." An example of a generated character would be:

[1152] Character Name: Security-kun

[1153] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[1154] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[1155] Based on the results, the user creates a message like this:

[1156] Hello everyone!

[1157] This is Security-kun.

[1158] Today I would like to inform you about the activities of our department.

[1159] A security expert working in the IT department, always providing the latest security information to everyone

[1160] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[1161] In this way, a character can be generated taking into consideration the user's emotions, and visually appealing announcements can be created.

[1162] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1163] Step 1:

[1164] (User enters department information and launches emotion engine)

[1165] The user launches a dedicated application on their device and accesses a department information input form. This form contains fields for entering the department name, department role, and information they want to share. As soon as the user starts entering information in these fields, the device starts the emotion engine in the background.

[1166] input:

[1167] Department name

[1168] Roles of the Department

[1169] Information to be made known

[1170] output:

[1171] Emotional Engine Activation

[1172] Operation:

[1173] The device collects user input information in real time and provides it to the emotion engine.

[1174] Step 2:

[1175] (Emotion recognition by emotion engine)

[1176] The emotion engine analyzes input content, keyboard typing speed, the user's facial expressions, and voice to recognize the user's emotions in real time. The analyzed emotion information continues to be updated until the user completes input.

[1177] input:

[1178] User input

[1179] Keyboard typing speed

[1180] User's facial expressions and voice

[1181] output:

[1182] Recognized emotional information

[1183] Operation:

[1184] The emotion engine uses multiple sensors and data analysis techniques to determine the user's emotional state. For example, if the user types quickly, it will detect "impatience."

[1185] Step 3:

[1186] (Transmitting emotional and departmental information)

[1187] When the user completes inputting the department information, the emotion engine determines the final emotion information, and the terminal serializes this emotion information and department information and transmits them to the server.

[1188] input:

[1189] Department information

[1190] Recognized emotional information

[1191] output:

[1192] Sending serialized data

[1193] Operation:

[1194] The device converts the input data and emotional information into an appropriate format and transmits it to a server via a network.

[1195] Step 4:

[1196] (Calling the generated AI model by the server)

[1197] The server analyzes the serialized data received from the device and calls the API of the generative AI model to send a character generation request.

[1198] input:

[1199] Data received from the device

[1200] output:

[1201] Character creation request submission

[1202] Operation:

[1203] The server analyzes the data, extracts the necessary information (department name, department role, announcements, emotional information), and sends it to the API of the generative AI model.

[1204] Step 5:

[1205] (Character generation using generative AI models)

[1206] The generative AI model analyzes the data received from the server and generates a character based on the user's emotions. The generated character information includes the character name, description, and image URL.

[1207] input:

[1208] Data sent from the server

[1209] output:

[1210] Generated character information

[1211] Operation:

[1212] The generative AI model uses data analysis and character synthesis algorithms to create characters that adapt to emotions.

[1213] Step 6:

[1214] (Sending character generation results from the server to the device)

[1215] The server analyzes the character generation results received from the generation AI model and sends them back to the terminal.

[1216] input:

[1217] Character information from generative AI models

[1218] output:

[1219] Transferring character generation results

[1220] Operation:

[1221] The server organizes the generated character information (character name, description, image URL) and sends it to the user's device.

[1222] Step 7:

[1223] (Displaying character information on a device and creating announcements)

[1224] The terminal displays the character generation results to the user, allowing the user to create a message based on the results.

[1225] input:

[1226] Character generation results received from the server

[1227] output:

[1228] Character information displayed to the user

[1229] Operation:

[1230] The terminal displays character information and provides a user interface for the user to create an effective message based on the information. The user uses the displayed character information to write a specific message and confirm its content.

[1231] (Application example 2)

[1232] 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."

[1233] Conventional information transmission systems provide characters and messages uniformly generated without considering the user's emotions, making it difficult to effectively transmit information according to a specific situation or emotional state. Furthermore, because the character generation is not dependent on the user's emotions, the system may lack visual appeal and user acceptance. This results in issues such as time-consuming transmission and understanding of information, reducing efficiency.

[1234] 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.

[1235] In this invention, the server includes input means for a user to input information about the department, receiving means for the server to receive the information input from the input means, calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generative artificial intelligence, sending means for the server to send the character generation result to the user's terminal, emotion recognition means for recognizing the user's emotion, adjustment means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means, and display means for displaying visually attractive notices using the generated character. This makes it possible to generate characters and create messages that take the user's emotions into consideration, thereby realizing visually attractive and easily accepted information transmission.

[1236] The "input means" is a means for a user to input information about a department.

[1237] The "receiving means" is a means by which the server receives information input from the input means.

[1238] The "calling means" is a means by which the server calls the generative artificial intelligence using the information received by the receiving means and transmits a character generation request.

[1239] "Generative AI" is an AI system that generates characters based on user information.

[1240] "Character generation results" refers to information about a character generated by generative artificial intelligence, including the character name, character description, and character image URL.

[1241] The "transmission means" is a means by which the server transmits the character generation results to the user's terminal.

[1242] The "emotion recognition means" is a means for recognizing the user's emotions.

[1243] The "adjustment means" is a means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means.

[1244] The "display means" is a means for displaying visually appealing notices on a user terminal using the generated characters.

[1245] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using generative artificial intelligence, and the generated character is used to create announcements.

[1246] System Overview

[1247] First, the user puts on the smart glasses and begins work. Using the smart glasses' input mechanism, the user enters information about their department, including the department name, role, and any information they wish to share. The smart glasses' built-in camera and microphone capture the user's facial expressions and voice, and analyze their emotions in real time. This emotion recognition is performed using an emotion engine such as Amazon Rekognition.

[1248] Next, the server receives the input information and the recognized emotion information using the receiving means. After that, the calling means calls the generative artificial intelligence (e.g., OpenAI's GPT-4) and sends a character generation request. This request includes the department name, role, content to be communicated, and the recognized emotion information.

[1249] The generative artificial intelligence generates a character based on the received information. The generated character's information (character name, description, image URL) is sent back to the server. The server then sends this information back to the user's smart glasses using a transmission means. The smart glasses then display the character information to the user using a display means. As a result, the user can create visually appealing messages using the generated character.

[1250] The specific hardware and software used

[1251] Smart Glasses: Smart glasses such as Oculus Quest 2

[1252] Sentiment engine: Amazon Rekognition

[1253] Generative artificial intelligence: OpenAI GPT-4

[1254] Server: AWS EC2 instance

[1255] Communication protocol: HTTP / HTTPS

[1256] Data serialization: JSON

[1257] Specific examples

[1258] For example, consider the case where a safety department employee is learning new safety rules.

[1259] The user puts on the smart glasses and enters the following information:

[1260] Department name: Safety Management Department

[1261] Procedure: Applying new safety rules

[1262] If the emotion engine detects that the user is feeling "anxiety" based on their facial expression or voice, the server sends this information to the generative AI, which then sends the following prompt:

[1263] "I'm worried about the application of the Safety Management Department's new safety rules."

[1264] The generative AI generates a character based on this information and returns the following character information, for example:

[1265] Character Name: Anshin-kun

[1266] Character description: A safety management expert who relieves everyone's worries

[1267] Image URL: https: / / example-ai-service.com / images / Anshinkun.png

[1268] The user's smart glasses will display this character information, allowing the user to learn new procedures with confidence.

[1269] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1270] Step 1:

[1271] The user puts on the smart glasses and begins work. The user uses the smart glasses' input means to input department information. This input includes the department name, role, and information to be disseminated. The input data is temporarily stored in the smart glasses' memory.

[1272] Step 2:

[1273] The device captures the user's facial expressions and voice. The smart glasses' built-in camera and microphone are used to collect biometric data, which is then processed into emotion recognition data. This data is sent in real time to the emotion engine (Amazon Rekognition).

[1274] Step 3:

[1275] The emotion engine analyzes the user's facial expressions and voice data to recognize the user's emotions. The analyzed emotion information (e.g., "anxiety" or "impatience") is generated and sent to the server. This emotion information is serialized in JSON format.

[1276] Step 4:

[1277] The server receives the user's input information and the recognized emotion information. Specifically, this includes the department name, role, desired message, and emotion information. Based on the received data, the server creates a character generation request for the generative AI. The request is generated in the following format:

[1278] Text format:

[1279] "Department name: Safety Management Department, Procedure: I am concerned about the application of new safety rules."

[1280] The server sends this request to the API of the generative artificial intelligence (OpenAI GPT-4).

[1281] Step 5:

[1282] The generative AI receives the request and generates a character based on the department information and emotion information. The generated character information (character name, character description, image URL) is sent back to the server. In this process, the character design is adapted to the user's emotion.

[1283] Step 6:

[1284] The server transmits the received character generation results to the user's smart glasses. The transmitted data includes the generated character name, character description, and image URL. The data is sent to the user's terminal using a transmission means.

[1285] Step 7:

[1286] The device (smart glasses) receives the character generation results and visually displays them. The user then creates a message based on the displayed character information. Specifically, the user can insert the character name, description, and image URL into the message, making it possible to convey information in a visually appealing way.

[1287] Specific working example:

[1288] 1. The user inputs a "new safety rule" in the "Safety Management Department," and the emotion of "anxiety" is recognized.

[1289] 2. The server sends a request to the generative AI saying, "I am concerned about the application of the Safety Management Department's new safety rules."

[1290] 3. Information about the generated character, "Anshin-kun," is sent back to the server and displayed on the smart glasses.

[1291] 4. Users create announcements that include descriptions and images of Anshin-kun, and communicate them to other employees in a visually appealing way.

[1292] 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.

[1293] 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.

[1294] 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.

[1295] [Fourth embodiment]

[1296] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1297] 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.

[1298] 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).

[1299] 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.

[1300] 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.

[1301] 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).

[1302] 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.

[1303] 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.

[1304] 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.

[1305] 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.

[1306] 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.

[1307] 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.

[1308] 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."

[1309] The present invention is a system in which a user inputs information about a department, generates an original character based on that information using generative artificial intelligence, and creates a message using the generated character. Specific embodiments of the present invention are described below.

[1310] System Overview

[1311] First, the user uses a terminal to input basic information about the department, such as the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[1312] The server receives the information sent from the device and sends it to the generative AI as a character generation request. The generative AI generates an original character based on the received information and returns the generated results, such as the character name, character description, and character image URL, to the server.

[1313] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[1314] Program processing details

[1315] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[1316] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[1317] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[1318] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[1319] Specific examples

[1320] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[1321] Department name: IT department

[1322] Department role: System operation and maintenance

[1323] What we want to announce: Introducing new security rules

[1324] The server sends this information to the generative AI and receives the following as examples of generated characters:

[1325] Character Name: Security-kun

[1326] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[1327] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[1328] Based on the results, the user creates a message like this:

[1329] Hello everyone!

[1330] This is Security-kun.

[1331] Today I would like to inform you about the activities of our department.

[1332] A security expert working in the IT department, always providing the latest security information to everyone

[1333] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[1334] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[1335] Through such specific embodiments, the present invention improves communication between departments within a company and makes it possible to disseminate information more effectively.

[1336] The processing flow will be explained below.

[1337] Step 1:

[1338] The user enters information about the department (e.g., department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[1339] Step 2:

[1340] The terminal serializes the information entered by the user into an appropriate format and sends an HTTP request to the server, which includes information about the department entered by the user.

[1341] Step 3:

[1342] The server receives the request sent from the device. The server analyzes the received data and checks its contents. After checking the validity of the data, it prepares to send a character generation request to the generative AI.

[1343] Step 4:

[1344] The server calls the generative AI API and sends a character generation request that includes information about the department, such as the department name, role, and desired publicity.

[1345] Step 5:

[1346] The generative AI receives and analyzes the character generation request. Based on the input information, it starts the process of generating an appropriate original character. The generation process includes the character name, character description, and character image URL.

[1347] Step 6:

[1348] The generative AI returns the generated character results to the server. The results include the character name, character description, and the URL of the character image. The server receives the generated results.

[1349] Step 7:

[1350] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[1351] Step 8:

[1352] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[1353] Step 9:

[1354] The user's device receives the generated results from the server and displays them on the screen. The user then creates a message based on this information. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[1355] Step 10:

[1356] Users can send the announcements they create to other departments within the company, thereby enabling effective information sharing using the generated characters.

[1357] Example 1

[1358] 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."

[1359] With conventional information sharing systems, communication between departments was complicated and it took a long time to create announcements. In addition, there was a lack of visually appealing means of communicating information, which made the impact on the recipient weak and sometimes led to ineffective communication of information.

[1360] 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.

[1361] In this invention, the server includes an information receiving means, an AI calling means, a generation result receiving means, a result sending means, and a display means, which allows a character to be generated by the generative AI based on the department information entered by the user, and a message to be created based on the character information.

[1362] "Information input means" refers to an input device or interface that a user uses to input information about a department.

[1363] The "information receiving means" is a function or module that allows the server to receive department information sent from the information input means.

[1364] "Artificial intelligence calling means" is a function or module for calling a generative artificial intelligence using information received by the server and sending a character generation request.

[1365] The "generation result receiving means" is a function or module that allows the server to receive character generation results from the generative artificial intelligence.

[1366] The "result transmission means" is a function or module that transmits the character generation results received by the server via the generation result receiving means to the user's terminal.

[1367] "Display means" is a function or module that allows the terminal to serialize the character generation results and display them to the user.

[1368] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[1369] The "document creation means" is a function or interface that allows the user to create a notice about the department using the character generation results.

[1370] This invention is a system in which a user inputs information about a department, an original character is generated based on that information using generative artificial intelligence, and a notice is created using the generated character.

[1371] System Overview

[1372] First, the user uses a terminal to input basic information about the department, including the department name, department role, and information to be disseminated. The terminal then sends this information to the server.

[1373] The server receives the information sent from the device and sends it to the generative AI as a character generation request. At this time, the server creates a prompt and calls the generative AI's API. The generative AI generates an original character based on the received information and returns the generation results, such as the character name, character description, and character image URL, to the server.

[1374] The server receives the generated results and sends them back to the terminal. The user then uses the character generated results displayed on the terminal to create a message about their department. This message includes the name, description, and image URL of the generated character, allowing for visually appealing communication to other departments within the company.

[1375] Program processing details

[1376] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields, such as text boxes and drop-down lists, which the user uses to enter the required information. Once the input is complete, the terminal serializes the information into an appropriate format and sends it to the server.

[1377] The server calls the API of the generative AI based on the received information. This call includes request information to the generative AI, such as the department name, role, and information to be disseminated. The generative AI analyzes the received information and begins the process of generating an original character.

[1378] The generative AI generates a character name, a character description, and a character image URL as a character generation result, and sends them back to the server. The server receives the generation result and then sends it to the terminal.

[1379] The generated character information is displayed to the user on the device. The user can then create a message based on this information. For example, the user can add the character's name, description, and image URL to the message to create a visually appealing message. The completed message can then be sent to other departments within the company, achieving effective information sharing.

[1380] Specific examples

[1381] As a concrete example, consider the case where the IT department announces new security rules. The user enters the following information:

[1382] Department name: IT department

[1383] Department role: System operation and maintenance

[1384] What we want to announce: Introducing new security rules

[1385] The server sends this information to the generative AI and receives the following as examples of generated characters:

[1386] Character Name: Security-kun

[1387] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[1388] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[1389] Based on the results, the user creates a message like this:

[1390] Hello everyone!

[1391] This is Security-kun.

[1392] Today I would like to inform you about the activities of our department.

[1393] A security expert working in the IT department, always providing the latest security information to everyone

[1394] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[1395] In this way, character generation using generative artificial intelligence and the creation of announcements are linked, enabling effective information sharing.

[1396] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1397] Step 1:

[1398] User enters department information

[1399] The user launches a browser on their device and accesses a web form for entering department information. This form has input fields for the department name, department role, and information to be disseminated. The user enters the necessary information into each field and presses the "Submit" button. This loads the entered information into the device. Specifically, the user launches a browser, accesses the specified URL, enters the department information, and then clicks the "Submit" button.

[1400] Input: Department name, department role, information to be disseminated

[1401] Output: Department information entry completion status on the terminal

[1402] Step 2:

[1403] The device sends the input information to the server

[1404] The device serializes the department information entered by the user into JSON format and creates an HTTP POST request. This request is sent to the server. The sent information includes the department name, department role, and the information to be disseminated. This allows data to be securely transferred from the device to the server. Specifically, the device converts the department information into JSON format and sends it to the server as an HTTP POST request.

[1405] Input: Department information entered by the user

[1406] Output: Department information sent to the server in JSON format

[1407] Step 3:

[1408] The server calls the AI ​​model to generate the character.

[1409] Based on the received department information, the server creates a prompt to call the generative AI's API. The prompt includes the department name, role, and information to be communicated. Using the created prompt, the server sends a character generation request to the generative AI. The generative AI analyzes the received information and generates an original character. Specifically, the server creates a prompt, calls the generative AI's API, and sends a character generation request.

[1410] Input: Department information received by the server

[1411] Output: A character generation request to the generative artificial intelligence

[1412] Step 4:

[1413] The server receives the generated results and sends them to the terminal.

[1414] The generative AI generates a character name, character description, and character image URL as the character generation result and sends them back to the server. The server encodes the generation result into JSON format and sends it to the terminal as an HTTP response. Specifically, the server receives the generation result, converts it into JSON format, and sends it to the terminal as an HTTP response.

[1415] Input: Character generation results returned from generative artificial intelligence

[1416] Output: JSON format character generation results sent to the terminal

[1417] Step 5:

[1418] The user creates a message based on the character information.

[1419] The user views the generated character information in the browser on the device. This information includes the character name, character description, and character image URL. The user creates a message based on this information. Specifically, the user checks the character information on the device, creates a message, and sends the content to other departments within the company via email or the internal bulletin board.

[1420] Input: Character generation results displayed on the terminal

[1421] Output: The created announcement

[1422] (Application example 1)

[1423] 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."

[1424] Traditionally, information sharing between departments within a company has been done through documents and emails, but these lacked visual appeal and often did not effectively communicate the information to the recipient. Similarly, there were limited ways to effectively inform customers about the introduction of new products and services. This resulted in problems such as it taking time for recipients to understand the content, or the intended information not being conveyed accurately.

[1425] 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.

[1426] In this invention, the server includes an input means for a user to input information about the department, a receiving means for the server to receive the information input from the input means, a calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, a receiving means for the server to receive a character generation result from the generative artificial intelligence, a sending means for the server to send the character generation result to the user's device, a push notification means for the server to create a message using the character generation result and send a push notification to the smartphone device, and a display means for receiving the push notification on the smartphone device and interactively displaying detailed information. This enables efficient and effective sharing of information within and outside the department using a visually appealing means.

[1427] A "user" is a person or organization that uses the system to input information about a department and to use the generated characters and announcements.

[1428] "Information about the department" is basic information about a specific department, such as its name, role, and the details you want to make known.

[1429] "Input means" refers to a device or software that has an interface for users to input information about departments.

[1430] A "server" is a computer system that calls a generative artificial intelligence based on received information and generates a character.

[1431] The "receiving means" is a function that allows the server to receive information sent from the input means.

[1432] The "calling means" is a function for the server to call the generative artificial intelligence based on the information received by the receiving means and send a character generation request.

[1433] "Generative AI" is an AI technology that generates original characters based on input information.

[1434] "Character generation results" refers to information including the character name, character description, and character image URL generated by generative artificial intelligence.

[1435] The "transmission means" is a function for the server to transmit the character generation results to the user's terminal.

[1436] The "push notification means" is a function that sends a notification message including the character generation results generated by the server to the smartphone terminal to notify the user.

[1437] "Display means" refers to a function that allows a smartphone device to receive push notifications and interactively display detailed information.

[1438] The present invention is a system for visually and effectively sharing information between departments within a company. This system allows a user to input information about their department, and uses generative artificial intelligence to generate original characters based on that information, and then creates announcements using the generated characters. Specific embodiments of the system are described below.

[1439] First, the user uses a device (e.g., a smartphone or PC) to enter basic information about the department. This information includes, for example, the name of the department, its role, and the information to be disseminated. Input methods include text boxes and drop-down lists. Once input is complete, the device serializes the information into an appropriate format and sends it to the server.

[1440] Next, the server receives the information sent from the user's terminal using the receiving means.The server then uses the calling means to call a generative artificial intelligence (specifically, a generative AI model) based on the received information and sends a character generation request.The generative artificial intelligence generates an original character based on the received information and generates a character name, character description, and character image URL.

[1441] The server receives the generated character generation results using a receiving means and transmits them again to the user's device using a transmitting means. The user creates a message about the department based on the character generation results displayed on the device. This allows for visually appealing information communication. The message includes the name and description of the generated character, an image URL, etc. The server then transmits the created message to the smartphone device via a push notification means.

[1442] Users who receive a push notification on their smartphone can tap the notification to interactively display detailed information, making it easy to check the announcement and enabling efficient information sharing.

[1443] Hardware and software used

[1444] Hardware: Servers, smartphones, PCs

[1445] Software: Flask (Python framework), API for generative AI models

[1446] Specific examples

[1447] For example, if the New Product Development department wants to announce the introduction of a new security product, they might enter the following information:

[1448] Department name: New Product Development Department

[1449] Department Role: Developing and introducing new products and services

[1450] Just wanted to let you know: The latest electronic security gadgets have arrived!

[1451] The server sends this information to the generative AI and receives the following character generation results:

[1452] Character Name: Security Master

[1453] Character description: A master of the latest security products, providing customers with a safer life.

[1454] Character image URL: https: / / example-ai-service.com / images / securitymaster.png

[1455] Users can create a message based on the results, which will be pushed to their smartphone. For example:

[1456] "Hello everyone! This is Security Master. Today I'll be introducing the latest electronic security gadgets. For more details, please see this illustration: https: / / example-ai-service.com / images / SecurityMaster.png"

[1457] In this way, the system allows for effective dissemination of information both within and outside the department, and allows for information sharing using visually appealing means.

[1458] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1459] Step 1:

[1460] The user enters basic information about the department.

[1461] Input: Department name, department role, information to be disseminated

[1462] Users use a device (smartphone or PC) to enter the department name, department role, and information they want to share into text boxes and drop-down lists on a specific screen. Once the input is complete, the device serializes this information into an appropriate data format such as JSON.

[1463] Step 2:

[1464] The terminal transmits the input information to the server.

[1465] Output: Serialized department information

[1466] The terminal sends the serialized department information to the server as an HTTP POST request. The receiving server has a receiving means implemented, and receives this request.

[1467] Step 3:

[1468] The server calls a generative artificial intelligence based on the information received.

[1469] Input: Serialized department information

[1470] The server analyzes the received department information and sends a character generation request to the generative AI API based on that data. Specifically, it uses a calling method to send the department name, department role, and announcements to the API.

[1471] Step 4:

[1472] The generative artificial intelligence generates a character based on the character generation request and returns the result.

[1473] Output: Character generation result (character name, description, image URL)

[1474] The generative AI model analyzes the received information and generates an original character. Information about the generated character (character name, description, image URL) is sent back to the server.

[1475] Step 5:

[1476] The server receives the character generation results and sends them to the user's terminal.

[1477] Input: Character generation result

[1478] The server transmits the character generation results received from the generative AI back to the user's terminal, using the transmission means to transmit the result data as an HTTP response.

[1479] Step 6:

[1480] The user receives the character generation results on the terminal and they are displayed.

[1481] Output: Character information displayed on the screen (character name, description, image URL)

[1482] The user's device displays the character generation results received from the server, and the user checks the displayed character information.

[1483] Step 7:

[1484] The user creates a message based on the character generation results.

[1485] Input: Character generation results, information

[1486] Users create visually appealing announcements based on the displayed character names, descriptions, and image URLs. The completed announcements are saved on the device.

[1487] Step 8:

[1488] The server will push the created notice to the smartphone device.

[1489] Input: Created announcement

[1490] The server sends the message created by the user to other smartphone terminals using push notification means. Specifically, the notification content is sent through a push notification server.

[1491] Step 9:

[1492] The smartphone device receives a push notification, and the user taps the notification to display detailed information.

[1493] Output: Push notification, display of detailed information

[1494] When a push notification is received, it will be displayed on the smartphone. When the user taps on the notification, detailed information will be displayed interactively on the screen, allowing the user to check the information.

[1495] This series of steps enables effective visual information sharing both within and outside the company.

[1496] 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.

[1497] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on the information using generative artificial intelligence, and the generated character is used to create announcements. Specific embodiments of the present invention are described in detail below.

[1498] System Overview

[1499] First, a user uses a device to enter basic information about their department, such as the department's name, its role, and any information they want to share. The device then collects this information and activates an emotion engine that analyzes the user's input, typing speed, and possibly facial expressions and voice.

[1500] The emotion engine analyzes the user's input operations and real-time biometric data to recognize the user's emotions. For example, if the user is typing quickly, it can detect emotions such as "impatience" or "tension."

[1501] The recognized emotion information and department information are sent from the device to the server. Based on the received information, the server sends a character generation request to the generative AI. The generative AI adjusts the character's attributes taking the user's emotions into account and generates the character. For example, if the user is "nervous," the generated character can have a more relaxed atmosphere.

[1502] The generative AI returns the generated results, including the character name, character description, and character image URL, to the server. The server receives the generated results and sends them back to the terminal. The user uses the character generation results displayed on the terminal to create a notice for the department. This notice includes the generated character's name, description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[1503] Program processing details

[1504] On the terminal, the user accesses a screen for entering basic information about the department. This screen contains input fields such as text boxes and drop-down lists, which the user uses to enter the necessary information. When the user begins to enter information, the emotion engine is activated and begins analyzing the input content, the facial expressions of the user in front of the screen, and the voice.

[1505] The emotion engine recognizes a user's emotions in real time using multiple data points, including analysis of input content, keyboard typing speed, and the user's facial expressions and voice. For example, if a user types quickly, their emotion may be determined to be "impatience."

[1506] The emotion information and department information recognized by the emotion engine are serialized into an appropriate format and sent to the server. The server analyzes the received data and calls the generative artificial intelligence API. This request includes the department name, role, message content, and recognized emotion information.

[1507] The generative AI analyzes the received information and adjusts the character's attributes to match the user's emotions. For example, if the user is "worried," the generated character may be changed to a design that gives a sense of security. The generated character name, character description, and image URL are then sent back to the server as the generation result.

[1508] The server receives the generated results and sends them back to the user's device. The generated character information is displayed on the user's device, and the user can use this information to create a message. Using the character name, description, and image URL, users can create a more visually appealing message and effectively communicate information to other departments within the company.

[1509] Specific examples

[1510] For example, suppose the IT department wants to announce a new security rule. The user enters the following information:

[1511] Department name: IT department

[1512] Department role: System operation and maintenance

[1513] What we want to announce: Introducing new security rules

[1514] If the user is typing in a hurry, the emotion engine will recognize this "impatience." The server sends this information to the generative AI, which then generates a relaxed character that alleviates the "impatience."

[1515] An example of a generated character would be:

[1516] Character Name: Security-kun

[1517] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[1518] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[1519] Based on the results, the user creates a message like this:

[1520] Hello everyone!

[1521] This is Security-kun.

[1522] Today I would like to inform you about the activities of our department.

[1523] A security expert working in the IT department, always providing the latest security information to everyone

[1524] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[1525] In this way, by using a system that combines an emotion engine and generative artificial intelligence, effective information sharing can be achieved by taking into account the user's emotions and using visually appealing characters.

[1526] The processing flow will be explained below.

[1527] Step 1:

[1528] The user enters information about the department (department name, department role, and information to be disseminated). The input screen displayed on the terminal contains text boxes and drop-down lists for entering this information. The user enters the necessary information and presses the send button.

[1529] Step 2:

[1530] The device activates its emotion engine and begins analyzing the user's input operations, input content, and keyboard typing speed. It also uses a camera and microphone to capture the user's facial expressions and voice, and comprehensively recognizes emotions.

[1531] Step 3:

[1532] The emotion engine analyzes the user's emotion (e.g., "tension" or "impatience") and sends the emotion information along with the department information to the server. The device serializes this data into an appropriate format and sends it to the server as an HTTP request.

[1533] Step 4:

[1534] The server receives the request sent from the device. The server analyzes the received data and checks its validity. Then, it calls the generative AI API and prepares to send a character generation request.

[1535] Step 5:

[1536] The server calls the generative AI API and sends department information including emotion information. This request includes details of the department name, department role, desired message, and emotion information.

[1537] Step 6:

[1538] The generative AI receives and analyzes the character generation request. The generative AI adjusts the character's attributes taking into account the user's emotional information and generates an original character. For example, if the user's emotion is "tension," the character will have a relaxed atmosphere.

[1539] Step 7:

[1540] The generative AI returns the generated character results to the server, which include the character name, character description, and character image URL.

[1541] Step 8:

[1542] The server receives the generated results, checks their contents, and then prepares them for transmission to the user's terminal. The resulting data is formatted in a format that is easily usable by the user.

[1543] Step 9:

[1544] The server sends the generated results to the device. The sent data includes the generated character name, description, and image URL.

[1545] Step 10:

[1546] The user's device receives the generated results from the server and displays them on the screen. The user then uses this information to create a message. For example, the user can incorporate the character name, description, and image URL into the message to create a visually appealing message.

[1547] Step 11:

[1548] Users can send announcements they create to other departments within the company. By using characters that reflect emotional information and detailed announcements, information can be conveyed to other departments effectively.

[1549] Example 2

[1550] 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."

[1551] Conventional information dissemination systems generate uniform characters and messages without considering the user's emotions, which can result in a lack of appeal and familiarity to the recipient. In particular, when the user is in a hurry or under stress, the messages created often lack an appropriate response to the situation. This makes it difficult to communicate information effectively.

[1552] 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.

[1553] In this invention, the server includes input means for a user to input information about the department, emotion recognition means for activating an emotion engine in the terminal when the user starts inputting information and recognizing the user's emotion, receiving means for the server to receive the information input from the input means and the emotion information recognized by the emotion recognition means, calling means for the server to call a generation AI model using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generation AI model, and sending means for the server to send the character generation result to the user's terminal. This enables character generation and message creation that take the user's emotions into consideration, improving appeal and familiarity to recipients and realizing effective information communication.

[1554] "User" refers to the person who operates this system and inputs department information.

[1555] "Department information" refers to basic information about a specific department, such as the department name, department role, and information you want to share.

[1556] A "terminal" is a device that a user uses to access the system and input information, and includes PCs, smartphones, tablets, etc.

[1557] An "emotion engine" refers to a piece of software or hardware that analyzes the user's input, typing speed, facial expressions, voice, etc., and recognizes the user's emotions.

[1558] "Emotion recognition means" refers to a function that identifies the user's emotions using an emotion engine.

[1559] "Serialization" refers to the process of converting data into a format that can be stored or transmitted.

[1560] "Server" refers to a device or system that receives and analyzes data sent from a user's device and sends a character generation request to a generative AI model.

[1561] "Generative AI model" refers to an artificial intelligence model that generates characters based on received information.

[1562] A "character generation request" is a request that instructs a generative AI model to generate a character using data that includes department information and emotional information.

[1563] "Character generation results" refers to information about the character generated by the generative AI model, including the character name, character description, and character image URL.

[1564] "Receiving means" refers to the function by which a terminal or server receives data.

[1565] "Transmission means" refers to the function of sending data from the server to the user's terminal.

[1566] The "creation means" refers to a function that allows a user to create a message using the character generation results.

[1567] The present invention is a system in which a user inputs information about their department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using a generative AI model, and the generated character is used to create announcements.

[1568] The user first uses a terminal to input basic information about the department. This basic information includes the department name, department role, and information to be disseminated. As soon as the user starts inputting, the terminal starts the emotion engine. The emotion engine analyzes the input content, keyboard typing speed, and in some cases the user's facial expressions and voice to recognize the user's emotions. The recognized emotion information and department information are sent from the terminal to the server.

[1569] The server analyzes the received information and calls the API of the generative AI model. The API request includes the department name, department role, information to be communicated, and recognized emotion information. The generative AI model adjusts the character's attributes based on the received data and generates an original character that reflects the user's emotions. For example, if the user is "nervous," it can generate a character with a relaxed atmosphere.

[1570] The generative AI model returns the generated character information (character name, character description, character image URL) to the server. The server receives this information and sends it back to the device. The device displays the generated character information to the user. The user creates a message based on the displayed character information. This message includes the character name, character description, image URL, etc., making it possible to communicate information to other departments within the company in a visually appealing way.

[1571] For example, when IT announces new security rules, users enter the following information:

[1572] Department name: IT department

[1573] Department role: System operation and maintenance

[1574] What we want to announce: Introducing new security rules

[1575] If the user is typing in a hurry, the emotion engine will recognize the "impatience." The server sends this information to the generative AI model, which then generates a relaxed character that reduces the "impatience." An example of a generated character would be:

[1576] Character Name: Security-kun

[1577] Character description: A security expert who works in the IT department and always keeps everyone up to date with the latest security information.

[1578] Character image URL: https: / / example-ai-service.com / images / security-kun.png

[1579] Based on the results, the user creates a message like this:

[1580] Hello everyone!

[1581] This is Security-kun.

[1582] Today I would like to inform you about the activities of our department.

[1583] A security expert working in the IT department, always providing the latest security information to everyone

[1584] For more details, please see this illustration: https: / / example-ai-service.com / images / security-kun.png

[1585] In this way, a character can be generated taking into consideration the user's emotions, and visually appealing announcements can be created.

[1586] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1587] Step 1:

[1588] (User enters department information and launches emotion engine)

[1589] The user launches a dedicated application on their device and accesses a department information input form. This form contains fields for entering the department name, department role, and information they want to share. As soon as the user starts entering information in these fields, the device starts the emotion engine in the background.

[1590] input:

[1591] Department name

[1592] Roles of the Department

[1593] Information to be made known

[1594] output:

[1595] Emotional Engine Activation

[1596] Operation:

[1597] The device collects user input information in real time and provides it to the emotion engine.

[1598] Step 2:

[1599] (Emotion recognition by emotion engine)

[1600] The emotion engine analyzes input content, keyboard typing speed, the user's facial expressions, and voice to recognize the user's emotions in real time. The analyzed emotion information continues to be updated until the user completes input.

[1601] input:

[1602] User input

[1603] Keyboard typing speed

[1604] User's facial expressions and voice

[1605] output:

[1606] Recognized emotional information

[1607] Operation:

[1608] The emotion engine uses multiple sensors and data analysis techniques to determine the user's emotional state. For example, if the user types quickly, it will detect "impatience."

[1609] Step 3:

[1610] (Transmitting emotional and departmental information)

[1611] When the user completes inputting the department information, the emotion engine determines the final emotion information, and the terminal serializes this emotion information and department information and transmits them to the server.

[1612] input:

[1613] Department information

[1614] Recognized emotional information

[1615] output:

[1616] Sending serialized data

[1617] Operation:

[1618] The device converts the input data and emotional information into an appropriate format and transmits it to a server via a network.

[1619] Step 4:

[1620] (Calling the generated AI model by the server)

[1621] The server analyzes the serialized data received from the device and calls the API of the generative AI model to send a character generation request.

[1622] input:

[1623] Data received from the device

[1624] output:

[1625] Character creation request submission

[1626] Operation:

[1627] The server analyzes the data, extracts the necessary information (department name, department role, announcements, emotional information), and sends it to the API of the generative AI model.

[1628] Step 5:

[1629] (Character generation using generative AI models)

[1630] The generative AI model analyzes the data received from the server and generates a character based on the user's emotions. The generated character information includes the character name, description, and image URL.

[1631] input:

[1632] Data sent from the server

[1633] output:

[1634] Generated character information

[1635] Operation:

[1636] The generative AI model uses data analysis and character synthesis algorithms to create characters that adapt to emotions.

[1637] Step 6:

[1638] (Sending character generation results from the server to the device)

[1639] The server analyzes the character generation results received from the generation AI model and sends them back to the terminal.

[1640] input:

[1641] Character information from generative AI models

[1642] output:

[1643] Transferring character generation results

[1644] Operation:

[1645] The server organizes the generated character information (character name, description, image URL) and sends it to the user's device.

[1646] Step 7:

[1647] (Displaying character information on a device and creating announcements)

[1648] The terminal displays the character generation results to the user, allowing the user to create a message based on the results.

[1649] input:

[1650] Character generation results received from the server

[1651] output:

[1652] Character information displayed to the user

[1653] Operation:

[1654] The terminal displays character information and provides a user interface for the user to create an effective message based on the information. The user uses the displayed character information to write a specific message and confirm its content.

[1655] (Application example 2)

[1656] 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."

[1657] Conventional information transmission systems provide characters and messages uniformly generated without considering the user's emotions, making it difficult to effectively transmit information according to a specific situation or emotional state. Furthermore, because the character generation is not dependent on the user's emotions, the system may lack visual appeal and user acceptance. This results in issues such as time-consuming transmission and understanding of information, reducing efficiency.

[1658] 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.

[1659] In this invention, the server includes input means for a user to input information about the department, receiving means for the server to receive the information input from the input means, calling means for the server to call a generative artificial intelligence using the information received by the receiving means and send a character generation request, receiving means for the server to receive a character generation result from the generative artificial intelligence, sending means for the server to send the character generation result to the user's terminal, emotion recognition means for recognizing the user's emotion, adjustment means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means, and display means for displaying visually attractive notices using the generated character. This makes it possible to generate characters and create messages that take the user's emotions into consideration, thereby realizing visually attractive and easily accepted information transmission.

[1660] The "input means" is a means for a user to input information about a department.

[1661] The "receiving means" is a means by which the server receives information input from the input means.

[1662] The "calling means" is a means by which the server calls the generative artificial intelligence using the information received by the receiving means and transmits a character generation request.

[1663] "Generative AI" is an AI system that generates characters based on user information.

[1664] "Character generation results" refers to information about a character generated by generative artificial intelligence, including the character name, character description, and character image URL.

[1665] The "transmission means" is a means by which the server transmits the character generation results to the user's terminal.

[1666] The "emotion recognition means" is a means for recognizing the user's emotions.

[1667] The "adjustment means" is a means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means.

[1668] The "display means" is a means for displaying visually appealing notices on a user terminal using the generated characters.

[1669] The present invention is a system in which a user inputs information about a department, an emotion engine is used to recognize the user's emotions, an original character is generated based on that information using generative artificial intelligence, and the generated character is used to create announcements.

[1670] System Overview

[1671] First, the user puts on the smart glasses and begins work. Using the smart glasses' input mechanism, the user enters information about their department, including the department name, role, and any information they wish to share. The smart glasses' built-in camera and microphone capture the user's facial expressions and voice, and analyze their emotions in real time. This emotion recognition is performed using an emotion engine such as Amazon Rekognition.

[1672] Next, the server receives the input information and the recognized emotion information using the receiving means. After that, the calling means calls the generative artificial intelligence (e.g., OpenAI's GPT-4) and sends a character generation request. This request includes the department name, role, content to be communicated, and the recognized emotion information.

[1673] The generative artificial intelligence generates a character based on the received information. The generated character's information (character name, description, image URL) is sent back to the server. The server then sends this information back to the user's smart glasses using a transmission means. The smart glasses then display the character information to the user using a display means. As a result, the user can create visually appealing messages using the generated character.

[1674] The specific hardware and software used

[1675] Smart Glasses: Smart glasses such as Oculus Quest 2

[1676] Sentiment engine: Amazon Rekognition

[1677] Generative artificial intelligence: OpenAI GPT-4

[1678] Server: AWS EC2 instance

[1679] Communication protocol: HTTP / HTTPS

[1680] Data serialization: JSON

[1681] Specific examples

[1682] For example, consider the case where a safety department employee is learning new safety rules.

[1683] The user puts on the smart glasses and enters the following information:

[1684] Department name: Safety Management Department

[1685] Procedure: Applying new safety rules

[1686] If the emotion engine detects that the user is feeling "anxiety" based on their facial expression or voice, the server sends this information to the generative AI, which then sends the following prompt:

[1687] "I'm worried about the application of the Safety Management Department's new safety rules."

[1688] The generative AI generates a character based on this information and returns the following character information, for example:

[1689] Character Name: Anshin-kun

[1690] Character description: A safety management expert who relieves everyone's worries

[1691] Image URL: https: / / example-ai-service.com / images / Anshinkun.png

[1692] The user's smart glasses will display this character information, allowing the user to learn new procedures with confidence.

[1693] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1694] Step 1:

[1695] The user puts on the smart glasses and begins work. The user uses the smart glasses' input means to input department information. This input includes the department name, role, and information to be disseminated. The input data is temporarily stored in the smart glasses' memory.

[1696] Step 2:

[1697] The device captures the user's facial expressions and voice. The smart glasses' built-in camera and microphone are used to collect biometric data, which is then processed into emotion recognition data. This data is sent in real time to the emotion engine (Amazon Rekognition).

[1698] Step 3:

[1699] The emotion engine analyzes the user's facial expressions and voice data to recognize the user's emotions. The analyzed emotion information (e.g., "anxiety" or "impatience") is generated and sent to the server. This emotion information is serialized in JSON format.

[1700] Step 4:

[1701] The server receives the user's input information and the recognized emotion information. Specifically, this includes the department name, role, desired message, and emotion information. Based on the received data, the server creates a character generation request for the generative AI. The request is generated in the following format:

[1702] Text format:

[1703] "Department name: Safety Management Department, Procedure: I am concerned about the application of new safety rules."

[1704] The server sends this request to the API of the generative artificial intelligence (OpenAI GPT-4).

[1705] Step 5:

[1706] The generative AI receives the request and generates a character based on the department information and emotion information. The generated character information (character name, character description, image URL) is sent back to the server. In this process, the character design is adapted to the user's emotion.

[1707] Step 6:

[1708] The server transmits the received character generation results to the user's smart glasses. The transmitted data includes the generated character name, character description, and image URL. The data is sent to the user's terminal using a transmission means.

[1709] Step 7:

[1710] The device (smart glasses) receives the character generation results and visually displays them. The user then creates a message based on the displayed character information. Specifically, the user can insert the character name, description, and image URL into the message, making it possible to convey information in a visually appealing way.

[1711] Specific working example:

[1712] 1. The user inputs a "new safety rule" in the "Safety Management Department," and the emotion of "anxiety" is recognized.

[1713] 2. The server sends a request to the generative AI saying, "I am concerned about the application of the Safety Management Department's new safety rules."

[1714] 3. Information about the generated character, "Anshin-kun," is sent back to the server and displayed on the smart glasses.

[1715] 4. Users create announcements that include descriptions and images of Anshin-kun, and communicate them to other employees in a visually appealing way.

[1716] 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.

[1717] 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.

[1718] 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.

[1719] 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.

[1720] 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.

[1721] 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.

[1722] 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).

[1723] 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.

[1724] 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."

[1725] 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.

[1726] 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).

[1727] 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.

[1728] 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.

[1729] 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.

[1730] 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.

[1731] 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.

[1732] 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.

[1733] 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.

[1734] 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.

[1735] 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.

[1736] 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.

[1737] The following is further disclosed regarding the above embodiment.

[1738] (Claim 1)

[1739] an input means for a user to input information about a department;

[1740] a receiving means for receiving information input by the server from the input means;

[1741] A server uses the information received by the receiving means to call a generative artificial intelligence and transmits a character generation request;

[1742] a receiving means for the server to receive a character generation result from the generative artificial intelligence;

[1743] The system includes a transmission means for the server to transmit the character generation results to the user's terminal.

[1744] (Claim 2)

[1745] The system of claim 1 , wherein the character generation result includes a character name, a character description, and an image URL of the character.

[1746] (Claim 3)

[1747] 2. The system according to claim 1, further comprising a creation means for a user to create a notice about the department using the character creation result.

[1748] "Example 1"

[1749] (Claim 1)

[1750] an information input means for a user to input information about a department;

[1751] an information receiving means for receiving information input by the server from the information input means;

[1752] an artificial intelligence calling means for the server to call a generative artificial intelligence using the information received by the information receiving means and to send a character generation request;

[1753] a generation result receiving means for receiving a character generation result from the generative artificial intelligence;

[1754] a result transmission means for transmitting the character generation results received by the generation result receiving means to the user's terminal;

[1755] The system further includes a display means for the terminal to serialize the character generation result and display it to the user.

[1756] (Claim 2)

[1757] The system of claim 1 , wherein the character generation result includes a character name, a character description, and an image URL of the character.

[1758] (Claim 3)

[1759] 2. The system according to claim 1, further comprising a document creation means for allowing a user to create a notice about the department using the character generation result.

[1760] "Application Example 1"

[1761] (Claim 1)

[1762] an input means for a user to input information about a department;

[1763] a receiving means for receiving information input by the server from the input means;

[1764] A server uses the information received by the receiving means to call a generative artificial intelligence and transmits a character generation request;

[1765] a receiving means for the server to receive a character generation result from the generative artificial intelligence;

[1766] a transmission means for transmitting the character generation result from the server to the user's terminal;

[1767] a push notification means for the server to create a message using the character generation result and send a push notification to the smartphone terminal;

[1768] The system includes a display means for receiving the push notification on a smartphone terminal and interactively displaying detailed information.

[1769] (Claim 2)

[1770] The system of claim 1 , wherein the character generation result includes a character name, a character description, and an image URL of the character.

[1771] (Claim 3)

[1772] 2. The system according to claim 1, further comprising a creation means for a user to create a notice about the department using the character creation result.

[1773] "Example 2: Combining Emotion Engines"

[1774] (Claim 1)

[1775] an input means for a user to input information about a department;

[1776] emotion recognition means for activating an emotion engine in response to a user's start of input and recognizing the user's emotion;

[1777] a receiving means for receiving the information input from the input means and the emotion information recognized by the emotion recognition means;

[1778] A calling means for the server to call a generation AI model using the information received by the receiving means and transmit a character generation request;

[1779] A receiving means for the server to receive a character generation result from the generation AI model;

[1780] The system includes a transmission means for the server to transmit the character generation results to the user's terminal.

[1781] (Claim 2)

[1782] The system of claim 1 , wherein the character generation result includes a character name, a character description, and an image URL of the character.

[1783] (Claim 3)

[1784] 2. The system according to claim 1, further comprising a creation means for a user to create a notice about the department using the character creation result.

[1785] "Application example 2 when combining emotion engines"

[1786] (Claim 1)

[1787] an input means for a user to input information about a department;

[1788] a receiving means for receiving information input by the server from the input means;

[1789] A server uses the information received by the receiving means to call a generative artificial intelligence and transmits a character generation request;

[1790] a receiving means for the server to receive a character generation result from the generative artificial intelligence;

[1791] a transmission means for transmitting the character generation result from the server to the user's terminal;

[1792] emotion recognition means for recognizing an emotion of a user;

[1793] an adjustment means for adjusting the content of the character generation request based on the emotion recognized by the emotion recognition means;

[1794] The system includes a display means for displaying visually appealing announcements using the generated characters.

[1795] (Claim 2)

[1796] The system of claim 1 , wherein the character generation result includes a character name, a character description, and an image URL of the character.

[1797] (Claim 3)

[1798] 2. The system according to claim 1, further comprising a creation means for a user to create a notice about the department using the character creation result. [Explanation of symbols]

[1799] 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. an input means for a user to input information about a department; a receiving means for receiving information input by the server from the input means; A server uses the information received by the receiving means to call a generative artificial intelligence and transmits a character generation request; a receiving means for the server to receive a character generation result from the generative artificial intelligence; The system includes a transmission means for the server to transmit the character generation results to the user's terminal.

2. The system of claim 1 , wherein the character generation result includes a character name, a character description, and an image URL of the character.

3. The system according to claim 1, further comprising a creation means for allowing a user to create a notice about the department using the character creation result.

Images