system

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving information entered in a different language; means for translating the received information into another language using a translating API; means for distributing the translated information to other user terminals; means for receiving additional information from a plurality of users based on the translated information; means for aggregating the received information and generating a summary using a generating AI; and means for distributing the generated summary to a plurality of user terminals.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] Create a document that describes the "problem the invention aims to solve" and the "means for solving the problem."

[0005] ---

[0006] In today's multinational corporations, language barriers and cultural differences pose major obstacles when employees with different languages ​​and cultures collaborate to gather and share information. As a result, it becomes difficult to effectively summarize business issues and explain and convince management. This can slow down the speed and quality of decision-making, potentially undermining a company's competitiveness. Therefore, to solve this problem, a system that supports multiple languages ​​and enables smooth communication and information gathering between employees who speak different languages ​​is needed. [Means for solving the problem]

[0007] In order to solve the above problems, the present invention provides the following means. This system first includes a means for receiving information entered in different languages. Next, a means for translating the received information into another language using a translation API is provided. Furthermore, a means for distributing the translated information to other user terminals is provided. A means for receiving additional information from multiple users based on this pre-translated information is provided. Next, a means for aggregating the received information and generating a summary using a generation AI is provided. Finally, a means for distributing the generated summary to multiple user terminals is provided. This series of means facilitates information sharing among employees with different languages ​​and cultures, making it easier to explain and persuade management about issues.

[0008] ---

[0009] In this format, the patent specification describes the "problem that the invention aims to solve" and the "means for solving the problem."

[0010] Okay, now we'll create definitions for each of the key words in the claims.

[0011] ---

[0012] "Different languages" refers to multiple languages ​​used in different countries or regions, including, for example, Japanese, English, Chinese, Spanish, etc.

[0013] The "means for receiving information" is a system component that allows the server to receive data sent from a user terminal.

[0014] A "translation API" is a software service that automatically translates input text into other languages ​​through a specific program interface.

[0015] "Means for distributing to other user terminals" refers to a mechanism for transmitting information received or translated by the server to other users' devices via the Internet or other communication means.

[0016] The "means for receiving additional information" is a system function that allows the server to receive further opinions and feedback from other users.

[0017] "Information aggregation" is the process of combining and organizing data collected from multiple users into one place.

[0018] "Generative AI" is artificial intelligence that can automatically extract useful information and patterns from large amounts of data and perform tasks such as summarization.

[0019] A "means for generating summaries" is a system function that extracts key points from collected data and summarizes them in a concise format.

[0020] "Management" refers to the senior executives who make decisions in a company or organization, including, for example, the CEO and directors.

[0021] ---

[0022] The above are definitions of important words included in the scope of patent claims. [Brief explanation of the drawings]

[0023] [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

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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."

[0044] Okay, so let's create a "Description of the Invention" based on the claims. We won't list the processing steps here because we'll ask about them later.

[0045] ---

[0046] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary.

[0047] The whole system mainly consists of a server, a user terminal, and the user itself. The roles and functions of each are explained in detail below.

[0048] 1. Server

[0049] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0050] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[0051] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[0052] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[0053] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[0054] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[0055] Summary distribution function: The generated summary is distributed to all relevant users and management.

[0056] 2. User Device

[0057] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0058] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[0059] Information display function: Provides the function to display translation information and summaries delivered from the server.

[0060] 3. Users

[0061] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0062] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[0063] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[0064] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[0065] Specific examples

[0066] Specific usage examples are shown below.

[0067] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0068] The terminal sends this information to the server.

[0069] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[0070] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0071] Each user can view the translated information, add their own comments and resubmit it.

[0072] The server aggregates all the information and generates a summary using generative AI.

[0073] The generated summary is distributed to all users and management.

[0074] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0075] In this way, the use of this system makes it easier to share information among employees with different languages ​​and cultures, and makes it easier to explain and persuade management about issues.

[0076] ---

[0077] The above is a detailed explanation of the "Form for implementing the invention."

[0078] The processing flow will be explained below.

[0079] I understand. Now, I will explain the program's processing flow in detail in the following format.

[0080] ---

[0081] Step 1:

[0082] A user accesses the application through a terminal and logs in with their account.

[0083] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[0084] Step 2:

[0085] The terminal transmits the login information to the server.

[0086] Specific operation: The terminal sends the authentication information entered by user A to the server.

[0087] Step 3:

[0088] The server validates the authentication information and starts a session if the login is successful.

[0089] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[0090] Step 4:

[0091] The user enters business issues and opinions into the application's input form.

[0092] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[0093] Step 5:

[0094] The terminal transmits the user's input information to the server.

[0095] Specific operation: The terminal sends the text data entered by user A to the server.

[0096] Step 6:

[0097] The server sends the received information to a translation API to translate it into other languages.

[0098] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[0099] Step 7:

[0100] The translation API returns the translation results to the server.

[0101] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[0102] Step 8:

[0103] The server distributes the translated information to other user terminals.

[0104] Specific operation: The server sends the translation results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[0105] Step 9:

[0106] The terminal displays the received translation information to the user.

[0107] Specific operation: The devices of users B, C, and D present the opinions displayed in their respective languages ​​to the users.

[0108] Step 10:

[0109] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[0110] Specific operation: User B inputs his opinion in English, and Chinese-speaking User C inputs his opinion in Chinese.

[0111] Step 11:

[0112] The terminal transmits the input information of the other users to the server.

[0113] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[0114] Step 12:

[0115] The server aggregates all the information and creates a summary using generative AI.

[0116] Specific operation: The server retrieves all user opinions from the database and generates a summary using generation AI.

[0117] Step 13:

[0118] The server distributes the generated summary to all users and management.

[0119] Specific operation: The server sends the multilingual summaries to all users and management's terminals.

[0120] Step 14:

[0121] Management reviews the summary through a terminal and decides on the necessary actions.

[0122] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[0123] ---

[0124] This concludes the detailed explanation of the program's processing flow.

[0125] Example 1

[0126] 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."

[0127] The aim is to solve the problem of difficulty in smooth communication and information sharing among employees with different languages ​​and cultures. In particular, there is a need to quickly and accurately translate information entered in different languages ​​and make efficient decisions based on that translation.

[0128] 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.

[0129] In this invention, the server includes means for receiving information entered in different languages, means for translating the information into other languages ​​using a translation API, means for distributing the translated information to other user terminals, means for receiving information added by multiple users, means for aggregating the received information and generating summaries using a generative AI model, means for distributing the generated summaries to multiple user terminals, means for displaying the translated information and summaries, and means for users who receive the summaries to add their opinions. This facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[0130] "Different languages" refers to multiple natural languages ​​spoken by users in different regions or cultures.

[0131] "Information" refers to data such as opinions, challenges, and feedback that users input or submit to the system.

[0132] "Receiving" refers to the server acquiring information sent from a user terminal.

[0133] "Translation API" refers to an application program interface used to translate text between different languages.

[0134] "Delivery" refers to the server sending the translated information and generated summaries to the user terminal.

[0135] "User terminal" refers to a device, such as a PC, smartphone, or tablet, that a user uses to input and receive information.

[0136] "Added information" refers to new opinions and feedback provided based on translated information from other users.

[0137] "Aggregation" refers to combining multiple pieces of received information into a single data set.

[0138] "Generative AI model" refers to an artificial intelligence model used to perform summarization or other processing on aggregated information.

[0139] A "summary" is a concise summary of the important points of aggregated information.

[0140] "Management" refers to the management layer responsible for decision-making in a company or organization.

[0141] This invention relates to a multilingual issue aggregation system that enables employees with different languages ​​and cultures to share information and make efficient decisions. The entire system is mainly composed of a server, user terminals, and users, each of which plays a specific role. The details of this system are described below.

[0142] server

[0143] The server is the core of this system and has the following main functions:

[0144] 1. Information reception function: The server receives information sent from the user terminal. Information is entered in text format. For example, User A in Japan enters and sends "opinions regarding the marketing strategy for a new product" in Japanese.

[0145] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[0146] 2. Translation function: The server analyzes the received information and translates it into other languages ​​using a translation API (e.g., Google Cloud Translation API). For example, information entered in Japanese can be translated into English, Chinese, or Spanish.

[0147] Example prompt: The server translates Japanese information into English, Chinese, and Spanish.

[0148] 3. Information distribution function: The translated information is distributed to other user terminals, for example, to English-speaking user B, Chinese-speaking user C, and Spanish-speaking user D.

[0149] Example prompt: Send translated information to User B, User C, and User D.

[0150] 4. Information aggregation function: The server receives and aggregates the opinions and feedback sent back by each user, forming an overall data set.

[0151] Example prompt: Collect information from all users and aggregate it into one dataset.

[0152] 5. Summary generation function: The server generates a summary based on the aggregated information using a generative AI model (e.g., OpenAI GPT-3). For example, the server inputs an instruction such as, "Please summarize the important points."

[0153] Example prompt: "Please summarize the key points" is input to the generation AI.

[0154] 6. Summary distribution function: The generated summary is distributed to all users and management, who can then make decisions based on it.

[0155] Example prompt: Send the generated summary to all users and management.

[0156] User terminal

[0157] A user terminal is a device that users use to input and receive information. It includes PCs, smartphones, tablets, etc. Each terminal has the following functions:

[0158] 1. Information input function: Users input their opinions and issues in text format and send them to the server. For example, User A writes his opinion in Japanese.

[0159] Example prompt: Enter "Your opinion on the marketing strategy for a new product" in Japanese and press the submit button.

[0160] 2. Information display function: The terminal displays the translated information and summary delivered from the server. For example, information translated into English is displayed on User B's terminal.

[0161] Example prompt: A Japanese comment is translated into English and displayed on User B's device.

[0162] User

[0163] Users are employees and administrators who use the system and have different languages ​​and cultures. Users have the following roles:

[0164] 1. Information input: Enter your opinions and assignments through the terminal and send them to the server.

[0165] Example prompt: User A enters "Your opinion on the marketing strategy for a new product" and presses the submit button.

[0166] 2. Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, User B adds his opinion in English, saying "This is a good idea," and submits it.

[0167] Example prompt: User B types "That's a good idea" in English and presses the send button.

[0168] 3. Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[0169] Example prompt: Management reviews the generated summary and decides on a new marketing strategy.

[0170] Specific examples

[0171] For example, User A in Japan enters his or her opinion on a new product's marketing strategy, and that information is translated into English, Chinese, and Spanish through the system. Users B, C, and D, who speak each language, receive that information and add their own opinions. The server then uses a generative AI model to generate a summary from the aggregated information, which is finally distributed to all users and management. This process facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[0172] In this way, this multilingual issue aggregation system effectively supports information sharing and decision-making among employees with different languages ​​and cultures.

[0173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0174] I understand. Now, I will explain the program processing flow of this system in detail by dividing it into the following steps.

[0175] Program processing steps

[0176] Step 1: Enter your information

[0177] Subject: Terminal

[0178] Operation: A user uses a terminal to enter opinions or issues in text format into an information input form.

[0179] Input: User opinions and issues (e.g., "Opinions regarding marketing strategies for new products")

[0180] Output: Text data is sent from the terminal to the server.

[0181] Specific operation: User A enters "Opinion on marketing strategy for new product" and clicks the submit button.

[0182] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[0183] Step 2: Receiving information

[0184] Subject: Server

[0185] Operation: The server receives the information sent from the terminal.

[0186] Input: Text data sent from the terminal

[0187] Output: Text data received by the server

[0188] Specific operation: Receive Japanese text data sent from the terminal to the server.

[0189] Example prompt: Receive text data for "Your opinion on the marketing strategy for a new product."

[0190] Step 3: Information Translation

[0191] Subject: Server

[0192] How it works: The server parses the information it receives and uses the translation API to translate it into different languages.

[0193] Input: Text data received by the server

[0194] Output: Translated text data (e.g., English, Chinese, Spanish)

[0195] Specific operation: The server translates Japanese information into English, Chinese, and Spanish.

[0196] Example prompt: Translate information submitted in Japanese into English, Chinese, and Spanish.

[0197] Step 4: Information distribution

[0198] Subject: Server

[0199] Operation: The server distributes the translated information to other user terminals.

[0200] Input: Translated text data

[0201] Output: Translated text data delivered to the user's device

[0202] Specific operation: The server sends the translated information to User B, User C, and User D.

[0203] Example prompt: Send translated information to User B, User C, and User D.

[0204] Step 5: Add information

[0205] Subject: User

[0206] What it does: Other users see the translated information, add their comments and resubmit.

[0207] Input: Translated information and user's additional comments

[0208] Output: Additional comments sent to the server

[0209] Specific action: User B adds an opinion in English saying "This is a good idea" and submits it.

[0210] Example prompt: "This is a good idea," add your opinion, and submit.

[0211] Step 6: Information aggregation

[0212] Subject: Server

[0213] How it works: The server collects the information returned by all users and aggregates it into a single data set.

[0214] Input: Additional comments submitted by multiple users

[0215] Output: Aggregated dataset

[0216] Specific operation: Collect information from all users and compile it into a single dataset.

[0217] Example prompt: Collect information from all users and aggregate it into one dataset.

[0218] Step 7: Summary generation

[0219] Subject: Server

[0220] How it works: The server generates a summary based on the aggregated information using a generative AI model.

[0221] Input: Aggregated dataset

[0222] Output: Generated summary

[0223] Specific operation: The generative AI model is given the prompt "Please summarize the key points in a summary" and a summary is generated.

[0224] Example prompt: "Please summarize the key points" is input to the generation AI.

[0225] Step 8: Summary Delivery

[0226] Subject: Server

[0227] Operation: The server distributes the generated summary to all users and management.

[0228] Input: Generated summary

[0229] Output: A summary is delivered to user terminals and management

[0230] Actions to be taken: Send a summary to all users and management for further decision-making.

[0231] Example prompt: Send the generated summary to all users and management.

[0232] This provides a detailed explanation of the processing procedures of the system's program, clarifying the inputs, outputs, and specific operations for each step.

[0233] (Application example 1)

[0234] 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."

[0235] In autonomous vehicle development projects, efficient information sharing and decision-making among researchers and engineers with different languages ​​and cultures is a challenge. Conventional methods require time and effort to support multiple languages ​​and consolidate and summarize information, which can cause delays and obstacles to the progress of the project.

[0236] 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.

[0237] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, means for distributing the translated information to other user terminals, means for receiving additional information from multiple users based on the translated information, means for aggregating the received information and generating a summary using a generation AI, means for distributing the generated summary to multiple user terminals, means for notifying management or administrators of the summary, and means for translating the information in real time to streamline information distribution and summary generation, thereby enabling efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[0238] The "means for receiving information entered in different languages" is a function that allows the server to receive data on issues and opinions entered by users in various languages.

[0239] "Means of translating into other languages ​​using a translation API" is a function that converts received information into other languages ​​in real time using an automatic translation service.

[0240] The "means for distributing translated information to other user terminals" is a function for transmitting translated data to other user devices.

[0241] The "means for receiving information added by multiple users based on translated information" is a function that allows the server to receive again the information added by each user based on the translated data.

[0242] "Means of aggregating received information and generating a summary using generative AI" refers to a function that brings together collected data and uses artificial intelligence to organize it into a summary format.

[0243] The "means for distributing the generated summary to a plurality of user terminals" is a function for transmitting the data of the generated summary to all user devices.

[0244] The "means of notifying the executives and managers of the summary" is a function for notifying the leaders and managers of the organization of the generated summary information.

[0245] "A means of translating information in real time and streamlining the distribution of information and the generation of summaries" is a function that translates input information on the spot, quickly shares that information, and creates summaries, thereby streamlining the entire process.

[0246] MODE FOR CARRYING OUT THE INVENTION

[0247] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary. It is primarily designed for autonomous vehicle development projects.

[0248] 1. Server

[0249] The server is the central part of the system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0250] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[0251] Translation function: Works with translation APIs to translate received information into other languages, for example, using Google Translate API or Microsoft Translator API.

[0252] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[0253] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[0254] Summary generation: Uses generative AI to create summaries from aggregated information, specifically using OpenAI's GPT-4 model.

[0255] Summary distribution function: The generated summary is distributed to all relevant users and management.

[0256] Notification function: Notify management and administrators of generated summaries and important information.

[0257] 2. User Device

[0258] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0259] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[0260] Information display function: Provides the function to display translation information and summaries delivered from the server.

[0261] 3. Users

[0262] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0263] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[0264] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[0265] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[0266] Specific examples

[0267] Process Flow

[0268] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0269] The terminal sends this information to the server.

[0270] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[0271] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0272] Each user can view the translated information, add their own comments and resubmit it.

[0273] The server aggregates all the information and generates a summary using OpenAI's GPT-4.

[0274] The generated summary is distributed to all users and management.

[0275] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0276] Prompt Sentence Examples

[0277] Example prompts for generative AI models:

[0278] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[0279] In this way, the use of this system facilitates information sharing among employees with different languages ​​and cultures, thereby improving the efficiency of autonomous vehicle development projects and supporting decision-making.

[0280] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0281] Step 1:

[0282] The user inputs and sends information from the terminal. The user inputs the task or opinion in text format in their own language and clicks the send button. The input includes the text information entered by the user. This information is sent to the server and received by the server.

[0283] Step 2:

[0284] The server translates the received information into other languages ​​using a translation API. Specifically, the input information is translated into all required languages ​​using the Google Translate API, Microsoft Translator API, etc. The input is the information received in step 1, and the output is the translated text information. In this process, the API is called to perform the translation work in real time and obtain the results.

[0285] Step 3:

[0286] The server distributes the translated information to other user terminals. Specifically, it sends the translated information to each user's terminal. The input is the translated information, and the output is the user terminal that received the information. In this process, the server generates a distribution request to each terminal and sends it to ensure that the information arrives correctly.

[0287] Step 4:

[0288] The user receives the translated information and adds their own opinion. The user's device displays the translated information delivered from the server, and the user inputs a new opinion in text format based on it and sends it. The input is the delivered information, and the output is the added opinion information. In this process, the user edits the information, generates new data, and sends it to the server.

[0289] Step 5:

[0290] The server collects and aggregates the added information. All new information submitted by multiple users is compiled into a single dataset. The input is the added opinion information, and the output is the aggregated dataset. In this process, the server centrally manages all new data and organizes the aggregated data.

[0291] Step 6:

[0292] The server generates a summary using generative AI. A summary is created from the aggregated information using OpenAI's GPT-4 model. The input is the aggregated dataset, and the output is the generated summary. In this process, a prompt sentence is used to input summarization instructions to the AI ​​model, and the results are obtained.

[0293] Step 7:

[0294] The server distributes the generated summary to multiple user terminals and management. Specifically, it sends the generated summary data to all relevant user and manager terminals. The input is the generated summary, and the output is the user terminal that received the summary. In this process, the server uses a distribution list to deliver the summary to each terminal.

[0295] Step 8:

[0296] Management reviews the summary and uses it to inform decision-making. Management then takes specific actions and makes decisions based on the summarized information. The input is the delivered summary information, and the output is a decision. This process evaluates the received information and determines the next steps for the project based on the results.

[0297] For example, here's a prompt:

[0298] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[0299] This will enable efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[0300] 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.

[0301] Okay, so let's create a "Description of the Invention" for the invention that combines the emotion engine based on the scope of the patent claims.

[0302] ---

[0303] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[0304] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[0305] 1. Server

[0306] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0307] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[0308] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[0309] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[0310] Emotion Recognition: Using an emotion engine, the emotion of the received information is analyzed, for example, to recognize positive, negative, and neutral emotions.

[0311] Emotion information distribution function: Distributes recognized emotion information to other users.

[0312] Information aggregation function: After translation and emotion recognition, the received information is collected again and aggregated into a single data set.

[0313] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[0314] Emotion-reflecting summary generation function: The generated summary reflects the user's emotional information.

[0315] Summary distribution function: The generated summary is distributed to all relevant users and management.

[0316] 2. User Device

[0317] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0318] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[0319] Information display function: Provides a function to display translation information, summaries, and emotional information delivered from the server.

[0320] 3. Users

[0321] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0322] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[0323] Information evaluation and addition: Receive translated information and sentiment information from other users and add your own opinion. For example, American user B sees the translated information and comments in English, saying, "This is a good idea."

[0324] Summary review and decision support: Management and others review the generated summary and sentiment information and make decisions based on it.

[0325] Specific examples

[0326] Specific usage examples are shown below.

[0327] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0328] The terminal sends this information to the server.

[0329] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[0330] The server uses an emotion engine to recognize negative emotions from the information of user A.

[0331] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0332] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[0333] The server aggregates all the information and uses generative AI to generate a summary, which also takes into account emotional information.

[0334] The generated summary is distributed to all users and management.

[0335] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0336] In this way, this system facilitates information sharing among employees with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[0337] ---

[0338] The above is a detailed explanation of the "Form for implementing the invention."

[0339] The processing flow will be explained below.

[0340] Okay, so let me explain the process step by step.

[0341] ---

[0342] Step 1:

[0343] A user accesses the application through a terminal and logs in with their account.

[0344] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[0345] Step 2:

[0346] The terminal transmits the login information to the server.

[0347] Specific operation: The terminal sends the authentication information entered by user A to the server.

[0348] Step 3:

[0349] The server validates the authentication information and starts a session if the login is successful.

[0350] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[0351] Step 4:

[0352] The user enters business issues and opinions into the application's input form.

[0353] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[0354] Step 5:

[0355] The terminal transmits the user's input information to the server.

[0356] Specific operation: The terminal sends the text data entered by user A to the server.

[0357] Step 6:

[0358] The server sends the received information to a translation API to translate it into other languages.

[0359] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[0360] Step 7:

[0361] The translation API returns the translation results to the server.

[0362] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[0363] Step 8:

[0364] The server sends the received information to an emotion engine to analyze the emotion.

[0365] Specific operation: The server calls the emotion engine and recognizes positive, negative, and neutral emotions from the input text of user A.

[0366] Step 9:

[0367] The emotion engine returns the emotion analysis results to the server.

[0368] Specific operation: The emotion engine returns the emotion analysis result (e.g., negative) to the server.

[0369] Step 10:

[0370] The server distributes the translated information and emotion analysis results to other user terminals.

[0371] Specific operation: The server sends the translation results and sentiment analysis results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[0372] Step 11:

[0373] The terminal displays the received translation information and emotion information to the user.

[0374] Specific operation: The devices of users B, C, and D present the opinions and emotion information displayed in their respective languages ​​to the users.

[0375] Step 12:

[0376] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[0377] Specific operation: User B inputs his / her opinion in English, and User C inputs his / her opinion in Chinese.

[0378] Step 13:

[0379] The terminal transmits the input information of the other users to the server.

[0380] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[0381] Step 14:

[0382] The server aggregates all the information and creates a summary using generative AI.

[0383] Specific operation: The server retrieves the opinions and emotional information of all users from the database and uses the generation AI to generate a summary, which also reflects the emotional information.

[0384] Step 15:

[0385] The server distributes the generated summary to all users and management.

[0386] Specific operation: The server sends the generated multilingual summaries and sentiment information to all users and management's terminals.

[0387] Step 16:

[0388] Management reviews the summary through a terminal and decides on the necessary actions.

[0389] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[0390] ---

[0391] The above is a detailed explanation of the processing flow of a system that includes an emotion engine.

[0392] Example 2

[0393] 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."

[0394] Conventional information sharing systems have made it difficult for employees with different languages ​​and cultures to share information smoothly, which can hinder effective decision-making. Furthermore, they are unable to take into account users' emotional information, which can lead to important emotional factors being overlooked in decision-making. This invention solves these problems and realizes efficient information sharing and decision-making support that supports multiple languages ​​and takes into account emotional information.

[0395] 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.

[0396] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation means, means for distributing the translated information to other information processing terminals, means for receiving information added to the distributed information from multiple users, means for aggregating the received information and the added information, means for generating a summary based on the aggregated information using a generative model, means for distributing the generated summary to multiple information processing terminals, means for analyzing emotions in the received information, and means for generating a summary using the results of the emotion analysis. This facilitates information sharing between users who speak different languages ​​and enables decision-making that takes emotional information into consideration.

[0397] Okay, now let's create definitions for each of the important words included in the rewritten claims.

[0398] "Different languages" refers to multiple natural languages ​​used as means of communication in different regions and cultures.

[0399] "Means for receiving" refers to devices or software that have the function of acquiring data sent from users and importing it into a server.

[0400] "Translation means" refers to a system or software, such as a translation API, that converts input information into another language.

[0401] "Other information processing terminals" refers to devices used by users, such as computers, smartphones, and tablets.

[0402] "Delivery means" refers to devices or software that have the functionality to allow the server to deliver translated information or summaries to other information processing terminals.

[0403] "Added information" refers to new opinions or data provided by the user in response to the received translation information.

[0404] "Aggregation means" refers to a system for organizing and integrating information received from multiple users into a single data set.

[0405] A "generative model" refers to an artificial intelligence algorithm that analyzes given data and generates summaries or new data.

[0406] A "means for generating a summary" refers to a device or software that uses a generative model to extract key points from aggregated information and summarize them in a concise form.

[0407] "Means for analyzing emotions" refers to an emotion recognition engine or software for identifying a user's emotional state from received information.

[0408] "Means for generating summaries using the results of emotion analysis" refers to a system that takes into account the results of emotion analysis and has the function of reflecting emotional information in the generated summary.

[0409] Understood. Now, let's write the "Form for carrying out the invention."

[0410] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[0411] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[0412] 1. Server

[0413] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0414] Information reception function

[0415] The server receives issues and opinions submitted by users. This information can be entered in different languages. The server uses the HTTP / HTTPS protocol to receive the information.

[0416] Translation feature

[0417] The server works with a translation API (e.g., Google Translate API) to translate the received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[0418] Information distribution function

[0419] The server then distributes the translated information to other users, potentially using real-time communication technologies (e.g., WebSockets) so that the same content can be understood by users who speak different languages.

[0420] Emotion recognition function

[0421] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion of the received information, for example, recognizing positive, negative, and neutral emotions.

[0422] Emotional information distribution function

[0423] The server distributes the recognized emotion information to other users, allowing them to understand the emotional state of other users.

[0424] Information aggregation function

[0425] The server collects the received information again after translation and emotion recognition and aggregates it into a single data set. This aggregation process uses a database to properly organize and store the information.

[0426] Summary generation function

[0427] The server uses generative AI (e.g., OpenAI's GPT-3) to create a summary from the aggregated information, which is a short, concise summary that extracts the key points.

[0428] Emotional summary generation function

[0429] The server reflects the user's emotional information in the generated summary, so that the summary is provided in a form that includes emotional elements.

[0430] Summary delivery function

[0431] The server distributes the generated summaries to all relevant users and decision makers via email, push notifications, and other methods.

[0432] 2. User Device

[0433] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0434] Information input function

[0435] The terminal allows users to input their assignments and opinions in text format and send them to a server using a dedicated application or web interface.

[0436] Information display function

[0437] The terminal provides the functionality to display translation information, summaries, and emotional information delivered from the server, sometimes using real-time update technology (e.g., AJAX).

[0438] 3. Users

[0439] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0440] Enter information

[0441] Users input and submit their opinions and issues through the terminal. For example, User A in Japan inputs and submits "opinions about the marketing strategy for a new product" in Japanese.

[0442] Information evaluation and addition

[0443] Users receive translated information and sentiment information from other users and add their own opinions. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[0444] Summary review and decision support

[0445] The decision maker reviews the generated summary and sentiment information and makes a decision based on it.

[0446] Specific examples

[0447] Specific usage examples are shown below.

[0448] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0449] The terminal sends this information to the server.

[0450] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[0451] The server uses IBM Watson's emotion analysis API to recognize negative emotions from User A's information.

[0452] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0453] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[0454] The server aggregates all the information and generates a summary using OpenAI's GPT-3, which also incorporates sentiment information.

[0455] The generated summary is distributed to all users and decision makers.

[0456] The decision maker reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0457] In this way, this system facilitates information sharing between users with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[0458] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0459] Processing Steps

[0460] Step 1: Enter your information

[0461] Users use their devices to input their opinions and issues in text format. For example, User A inputs "Opinions about the marketing strategy for a new product" in Japanese and clicks the send button.

[0462] Input: User opinions and issues (text data)

[0463] Output: Text data entered into the terminal

[0464] Step 2: Submit your information

[0465] The terminal sends the input information to the server. At this time, the data is encrypted before being sent, ensuring security.

[0466] Input: Text data entered by the user

[0467] Output: Encrypted data to the server based on the HTTPS protocol

[0468] Step 3: Receiving information

[0469] The server receives the information sent from the device, at which point it is stored in a database.

[0470] Input: Encrypted data sent from the device

[0471] Output: Decoded text data (user opinions and issues)

[0472] Step 4: Translate the information

[0473] The server passes the received information to a translation means (e.g., Google Translate API) to translate it into other languages. For example, user A's Japanese opinion is translated into English, Chinese, and Spanish.

[0474] Input: Decrypted text data

[0475] Output: Translated text data (multiple languages)

[0476] Step 5: Emotion Recognition

[0477] The server passes the translated information to an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion. For example, it recognizes negative emotions from User A's opinion.

[0478] Input: Translated text data

[0479] Output: Sentiment analysis results (positive, negative, neutral, etc.)

[0480] Step 6: Delivering translation and emotion information

[0481] The server distributes the translated information and emotion information to the terminals of other users.

[0482] Input: translated text data, sentiment analysis results

[0483] Output: Data delivered to user device (text and emotional information)

[0484] Step 7: Evaluate and add information

[0485] The user can then check the translation and emotion information delivered to their device and add their own opinion. For example, User B can type "This is a good idea" in English and resubmit.

[0486] Input: Delivered text data and emotional information

[0487] Output: Added opinions (text data)

[0488] Step 8: Submit additional information

[0489] The terminal transmits the added information to the server again.

[0490] Input: Added opinion (text data)

[0491] Output: Encrypted data to the server based on the HTTPS protocol

[0492] Step 9: Aggregating information

[0493] The server receives the added information and stores and aggregates all user submitted information in a database, filtering out duplicate and irrelevant information.

[0494] Input: Additional comments from users (text data)

[0495] Output: Aggregated text dataset

[0496] Step 10: Summary generation

[0497] The server passes the aggregated information to a generative AI (e.g., OpenAI's GPT-3) to generate a summary, which extracts the key points and summarizes them in a short, concise manner.

[0498] Input: Aggregated text dataset

[0499] Output: Generated summary (text data)

[0500] Step 11: Emotion-reflecting summary generation

[0501] The server reflects the user's emotional information in the generated summary, thereby providing the summary in a form that includes emotional information.

[0502] Input: Generated summary, sentiment analysis results

[0503] Output: Summary (text data) reflecting emotional information

[0504] Step 12: Deliver the summary

[0505] The server distributes the generated summaries to all users and decision makers via email, push notifications, and other methods.

[0506] Input: A summary that reflects emotional information

[0507] Output: Data delivered to users and decision makers (text data)

[0508] In this way, the system realizes a series of processes: sharing users' opinions and issues in multiple languages, generating summaries taking into account emotional information, and providing information that contributes to decision-making.

[0509] (Application example 2)

[0510] 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."

[0511] In modern logistics centers, it is common for employees with different languages ​​and cultures to work together. However, if information is not shared smoothly across multiple languages, there is a risk of reduced productivity and mistakes due to misunderstandings. Furthermore, if the psychological state and emotions of employees are not understood, it can be difficult to improve the working environment and make efficient decisions. A system that can solve these issues is needed.

[0512] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, and means for receiving information added by multiple users based on the translated information and emotion information. This enables efficient information sharing across multiple languages ​​and appropriate management based on employee emotion information.

[0513] Okay, so let's create definitions for the important words included in the patent claims according to the application example.

[0514] "Information entered in different languages" refers to text data such as opinions and feedback entered by multiple users who use different languages.

[0515] A "translation API" is an application programming interface for automatically translating text between different languages.

[0516] An "emotion recognition engine" is software for analyzing and identifying a user's emotional state from text data.

[0517] "Generative AI" is an artificial intelligence technology that generates summaries and organizes information based on multiple collected text data.

[0518] "User Terminal" means an electronic device connected to the System that allows a User to input and receive information. Examples include smartphones, tablets, and PCs.

[0519] The "information receiving means" is a function that receives information sent from a user terminal and imports it into the server.

[0520] The "information distribution means" is a function that transmits information collected in the server to an appropriate user terminal.

[0521] The "information aggregation means" is a function that aggregates information received from multiple users into one piece of data.

[0522] "Summary generation means" is a function that uses generative AI to extract key points from aggregated information and create a concise summary.

[0523] The "emotion information distribution means" is a function that distributes analyzed emotion information to other users and the administrator.

[0524] A "manager" is someone whose job is to oversee the entire system and make decisions based on employee behavior and sentiment information.

[0525] "Multilingual support" refers to the ability to support multiple different languages ​​and enable smooth communication between these languages.

[0526] The above definitions clearly indicate the meaning of important terms contained in the claims.

[0527] This invention combines a multilingual issue aggregation system with an emotion recognition engine for use in logistics centers where employees with different languages ​​and cultures work together. The system efficiently translates information entered in different languages, shares it among employees, consolidates the information, and generates summaries. It also analyzes each employee's emotional information, allowing managers to respond appropriately.

[0528] 1. Server

[0529] The server is the core of this system and has the following functions:

[0530] Information receiving means: receives information in different languages ​​sent from the user terminal. This information is input in different languages, such as Japanese, English, Spanish, etc.

[0531] Translation method: Using a translation API, the received information is translated into another language. For example, information entered by a user in Japanese is translated into English or Chinese.

[0532] Information distribution means: Translated information is distributed to each user's device, allowing users who speak different languages ​​to understand the information.

[0533] Emotion recognition means: An emotion recognition engine is used to analyze the user's emotions from the received information. The analysis results include positive, negative, neutral, etc.

[0534] Information aggregation method: Aggregate information after translation and emotion recognition and compile the whole into a single data set.

[0535] Summary generator: A generative AI model is used to generate a summary from the aggregated information, which extracts key points and summarizes them succinctly.

[0536] Emotional information distribution method: Emotional information is reflected in the generated summary and distributed to all parties involved.

[0537] 2. User Device

[0538] User terminals are devices that employees use to input and receive information, including smart glasses, smartphones, and tablets.

[0539] Information input means: Provides a means for users to input their opinions and issues in text format and send them to the server.

[0540] Information display means: Provides a means to display translation information, summaries, and emotional information delivered from the server.

[0541] 3. Users

[0542] Users are employees and administrators who use the system, and it is assumed that they have different languages ​​and cultures.

[0543] Information input: Users input their opinions and issues through the terminal and send them. For example, a Japanese user inputs and sends a "proposal for improving the packaging of a new product" in Japanese.

[0544] Information evaluation and addition: Receive translated information and sentiment information from other users, add your own opinion to it, and resubmit it. For example, an English-speaking user may send feedback such as "This is a good idea."

[0545] Reviewing the summary and making decisions: The manager reviews the generated summary and sentiment information and makes decisions based on it, for example, setting up a meeting to decide on a new marketing strategy.

[0546] Specific examples

[0547] For example, in a discussion about packaging methods at a logistics center, opinions entered in different languages ​​can be translated, sentiment analyzed, and a summary generated based on the results. Using this system, employee A can enter "I propose a new packaging method" in Japanese, which is translated into English and perceived by the manager as "positive feedback." Employee B can also enter "I think this new packaging is great" in English, which is translated into Japanese and recognized as "positive" through sentiment analysis.

[0548] An example of a prompt is:

[0549] plaintext

[0550] "Translate comments entered in different languages ​​about a discussion about packaging methods at a distribution center, perform sentiment analysis, and generate summaries based on that."

[0551] is input into the generative AI model.

[0552] By using this system, it becomes possible to efficiently share information across multiple languages ​​and to appropriately manage employees based on their emotional state.

[0553] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0554] (Processing flow)

[0555] Step 1:

[0556] This is the stage where the user terminal receives information. The user enters text information in their own language and sends this information to the server via the terminal. The entered text information is sent to the server in its original format. For example, Japanese user A enters "I would like to propose a new packaging method" and clicks the send button. This entered text is sent to the server, and the server receives this information.

[0557] Step 2:

[0558] The server passes the received information to a translation API, which translates it into multiple languages. In this case, translation is from Japanese to English, Chinese, etc. The translation API analyzes the received text information and converts it into the specified target language. For example, it translates "I propose a new packaging method." into "I propose a new packaging method." The translation result is returned to the server.

[0559] Step 3:

[0560] The server uses the translated information to pass the data to an emotion recognition engine for sentiment analysis. The emotion recognition engine identifies the user's emotional state based on the received text data and returns the result to the server. For example, the text "I propose a new packaging method." is recognized as "positive."

[0561] Step 4:

[0562] The server delivers the translation results and sentiment information to the user's device, where it can be displayed and confirmed by other users. For example, English-speaking user B receives the message "I propose a new packaging method." and confirms the positive feedback.

[0563] Step 5:

[0564] Other users receive the information and add their own opinions. This information is then sent back to the server, where it is further analyzed. For example, user B adds his opinion, "This is a great idea," and sends it back. The server receives the information again and performs translation and sentiment analysis.

[0565] Step 6:

[0566] The server passes the aggregated information to a generative AI model, which then generates an overall summary. The generative AI model analyzes various text data, extracts key points, and generates a summary. For example, it creates a summary such as "The new packaging method has received positive reviews" based on multiple opinions and feedback.

[0567] Step 7:

[0568] The server distributes the generated summary and sentiment information to the administrator and other interested parties. The administrator can make decisions based on the summary. For example, the administrator can decide whether to adopt a new packaging method after viewing the summary and sentiment information.

[0569] The above is a detailed description of the steps involved in implementing the present invention, which enables efficient information sharing across multiple languages ​​and appropriate management based on employee emotional information.

[0570] 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.

[0571] 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.

[0572] 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.

[0573] [Second embodiment]

[0574] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0575] 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.

[0576] 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).

[0577] 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.

[0578] 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.

[0579] 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).

[0580] 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.

[0581] 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.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] 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."

[0586] Okay, so let's create a "Description of the Invention" based on the claims. We won't list the processing steps here because we'll ask about them later.

[0587] ---

[0588] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary.

[0589] The whole system mainly consists of a server, a user terminal, and the user itself. The roles and functions of each are explained in detail below.

[0590] 1. Server

[0591] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0592] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[0593] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[0594] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[0595] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[0596] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[0597] Summary distribution function: The generated summary is distributed to all relevant users and management.

[0598] 2. User Device

[0599] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0600] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[0601] Information display function: Provides the function to display translation information and summaries delivered from the server.

[0602] 3. Users

[0603] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0604] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[0605] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[0606] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[0607] Specific examples

[0608] Specific usage examples are shown below.

[0609] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0610] The terminal sends this information to the server.

[0611] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[0612] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0613] Each user can view the translated information, add their own comments and resubmit it.

[0614] The server aggregates all the information and generates a summary using generative AI.

[0615] The generated summary is distributed to all users and management.

[0616] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0617] In this way, the use of this system makes it easier to share information among employees with different languages ​​and cultures, and makes it easier to explain and persuade management about issues.

[0618] ---

[0619] The above is a detailed explanation of the "Form for implementing the invention."

[0620] The processing flow will be explained below.

[0621] I understand. Now, I will explain the program's processing flow in detail in the following format.

[0622] ---

[0623] Step 1:

[0624] A user accesses the application through a terminal and logs in with their account.

[0625] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[0626] Step 2:

[0627] The terminal transmits the login information to the server.

[0628] Specific operation: The terminal sends the authentication information entered by user A to the server.

[0629] Step 3:

[0630] The server validates the authentication information and starts a session if the login is successful.

[0631] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[0632] Step 4:

[0633] The user enters business issues and opinions into the application's input form.

[0634] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[0635] Step 5:

[0636] The terminal transmits the user's input information to the server.

[0637] Specific operation: The terminal sends the text data entered by user A to the server.

[0638] Step 6:

[0639] The server sends the received information to a translation API to translate it into other languages.

[0640] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[0641] Step 7:

[0642] The translation API returns the translation results to the server.

[0643] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[0644] Step 8:

[0645] The server distributes the translated information to other user terminals.

[0646] Specific operation: The server sends the translation results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[0647] Step 9:

[0648] The terminal displays the received translation information to the user.

[0649] Specific operation: The devices of users B, C, and D present the opinions displayed in their respective languages ​​to the users.

[0650] Step 10:

[0651] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[0652] Specific operation: User B inputs his opinion in English, and Chinese-speaking User C inputs his opinion in Chinese.

[0653] Step 11:

[0654] The terminal transmits the input information of the other users to the server.

[0655] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[0656] Step 12:

[0657] The server aggregates all the information and creates a summary using generative AI.

[0658] Specific operation: The server retrieves all user opinions from the database and generates a summary using generation AI.

[0659] Step 13:

[0660] The server distributes the generated summary to all users and management.

[0661] Specific operation: The server sends the multilingual summaries to all users and management's terminals.

[0662] Step 14:

[0663] Management reviews the summary through a terminal and decides on the necessary actions.

[0664] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[0665] ---

[0666] This concludes the detailed explanation of the program's processing flow.

[0667] Example 1

[0668] 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."

[0669] The aim is to solve the problem of difficulty in smooth communication and information sharing among employees with different languages ​​and cultures. In particular, there is a need to quickly and accurately translate information entered in different languages ​​and make efficient decisions based on that translation.

[0670] 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.

[0671] In this invention, the server includes means for receiving information entered in different languages, means for translating the information into other languages ​​using a translation API, means for distributing the translated information to other user terminals, means for receiving information added by multiple users, means for aggregating the received information and generating summaries using a generative AI model, means for distributing the generated summaries to multiple user terminals, means for displaying the translated information and summaries, and means for users who receive the summaries to add their opinions. This facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[0672] "Different languages" refers to multiple natural languages ​​spoken by users in different regions or cultures.

[0673] "Information" refers to data such as opinions, challenges, and feedback that users input or submit to the system.

[0674] "Receiving" refers to the server acquiring information sent from a user terminal.

[0675] "Translation API" refers to an application program interface used to translate text between different languages.

[0676] "Delivery" refers to the server sending the translated information and generated summaries to the user terminal.

[0677] "User terminal" refers to a device, such as a PC, smartphone, or tablet, that a user uses to input and receive information.

[0678] "Added information" refers to new opinions and feedback provided based on translated information from other users.

[0679] "Aggregation" refers to combining multiple pieces of received information into a single data set.

[0680] "Generative AI model" refers to an artificial intelligence model used to perform summarization or other processing on aggregated information.

[0681] A "summary" is a concise summary of the important points of aggregated information.

[0682] "Management" refers to the management layer responsible for decision-making in a company or organization.

[0683] This invention relates to a multilingual issue aggregation system that enables employees with different languages ​​and cultures to share information and make efficient decisions. The entire system is mainly composed of a server, user terminals, and users, each of which plays a specific role. The details of this system are described below.

[0684] server

[0685] The server is the core of this system and has the following main functions:

[0686] 1. Information reception function: The server receives information sent from the user terminal. Information is entered in text format. For example, User A in Japan enters and sends "opinions regarding the marketing strategy for a new product" in Japanese.

[0687] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[0688] 2. Translation function: The server analyzes the received information and translates it into other languages ​​using a translation API (e.g., Google Cloud Translation API). For example, information entered in Japanese can be translated into English, Chinese, or Spanish.

[0689] Example prompt: The server translates Japanese information into English, Chinese, and Spanish.

[0690] 3. Information distribution function: The translated information is distributed to other user terminals, for example, to English-speaking user B, Chinese-speaking user C, and Spanish-speaking user D.

[0691] Example prompt: Send translated information to User B, User C, and User D.

[0692] 4. Information aggregation function: The server receives and aggregates the opinions and feedback sent back by each user, forming an overall data set.

[0693] Example prompt: Collect information from all users and aggregate it into one dataset.

[0694] 5. Summary generation function: The server generates a summary based on the aggregated information using a generative AI model (e.g., OpenAI GPT-3). For example, the server inputs an instruction such as, "Please summarize the important points."

[0695] Example prompt: "Please summarize the key points" is input to the generation AI.

[0696] 6. Summary distribution function: The generated summary is distributed to all users and management, who can then make decisions based on it.

[0697] Example prompt: Send the generated summary to all users and management.

[0698] User terminal

[0699] A user terminal is a device that users use to input and receive information. It includes PCs, smartphones, tablets, etc. Each terminal has the following functions:

[0700] 1. Information input function: Users input their opinions and issues in text format and send them to the server. For example, User A writes his opinion in Japanese.

[0701] Example prompt: Enter "Your opinion on the marketing strategy for a new product" in Japanese and press the submit button.

[0702] 2. Information display function: The terminal displays the translated information and summary delivered from the server. For example, information translated into English is displayed on User B's terminal.

[0703] Example prompt: A Japanese comment is translated into English and displayed on User B's device.

[0704] User

[0705] Users are employees and administrators who use the system and have different languages ​​and cultures. Users have the following roles:

[0706] 1. Information input: Enter your opinions and assignments through the terminal and send them to the server.

[0707] Example prompt: User A enters "Your opinion on the marketing strategy for a new product" and presses the submit button.

[0708] 2. Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, User B adds his opinion in English, saying "This is a good idea," and submits it.

[0709] Example prompt: User B types "That's a good idea" in English and presses the send button.

[0710] 3. Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[0711] Example prompt: Management reviews the generated summary and decides on a new marketing strategy.

[0712] Specific examples

[0713] For example, User A in Japan enters his or her opinion on a new product's marketing strategy, and that information is translated into English, Chinese, and Spanish through the system. Users B, C, and D, who speak each language, receive that information and add their own opinions. The server then uses a generative AI model to generate a summary from the aggregated information, which is finally distributed to all users and management. This process facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[0714] In this way, this multilingual issue aggregation system effectively supports information sharing and decision-making among employees with different languages ​​and cultures.

[0715] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0716] I understand. Now, I will explain the program processing flow of this system in detail by dividing it into the following steps.

[0717] Program processing steps

[0718] Step 1: Enter your information

[0719] Subject: Terminal

[0720] Operation: A user uses a terminal to enter opinions or issues in text format into an information input form.

[0721] Input: User opinions and issues (e.g., "Opinions regarding marketing strategies for new products")

[0722] Output: Text data is sent from the terminal to the server.

[0723] Specific operation: User A enters "Opinion on marketing strategy for new product" and clicks the submit button.

[0724] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[0725] Step 2: Receiving information

[0726] Subject: Server

[0727] Operation: The server receives the information sent from the terminal.

[0728] Input: Text data sent from the terminal

[0729] Output: Text data received by the server

[0730] Specific operation: Receive Japanese text data sent from the terminal to the server.

[0731] Example prompt: Receive text data for "Your opinion on the marketing strategy for a new product."

[0732] Step 3: Information Translation

[0733] Subject: Server

[0734] How it works: The server parses the information it receives and uses the translation API to translate it into different languages.

[0735] Input: Text data received by the server

[0736] Output: Translated text data (e.g., English, Chinese, Spanish)

[0737] Specific operation: The server translates Japanese information into English, Chinese, and Spanish.

[0738] Example prompt: Translate information submitted in Japanese into English, Chinese, and Spanish.

[0739] Step 4: Information distribution

[0740] Subject: Server

[0741] Operation: The server distributes the translated information to other user terminals.

[0742] Input: Translated text data

[0743] Output: Translated text data delivered to the user's device

[0744] Specific operation: The server sends the translated information to User B, User C, and User D.

[0745] Example prompt: Send translated information to User B, User C, and User D.

[0746] Step 5: Add information

[0747] Subject: User

[0748] What it does: Other users see the translated information, add their comments and resubmit.

[0749] Input: Translated information and user's additional comments

[0750] Output: Additional comments sent to the server

[0751] Specific action: User B adds an opinion in English saying "This is a good idea" and submits it.

[0752] Example prompt: "This is a good idea," add your opinion, and submit.

[0753] Step 6: Information aggregation

[0754] Subject: Server

[0755] How it works: The server collects the information returned by all users and aggregates it into a single data set.

[0756] Input: Additional comments submitted by multiple users

[0757] Output: Aggregated dataset

[0758] Specific operation: Collect information from all users and compile it into a single dataset.

[0759] Example prompt: Collect information from all users and aggregate it into one dataset.

[0760] Step 7: Summary generation

[0761] Subject: Server

[0762] How it works: The server generates a summary based on the aggregated information using a generative AI model.

[0763] Input: Aggregated dataset

[0764] Output: Generated summary

[0765] Specific operation: The generative AI model is given the prompt "Please summarize the key points in a summary" and a summary is generated.

[0766] Example prompt: "Please summarize the key points" is input to the generation AI.

[0767] Step 8: Summary Delivery

[0768] Subject: Server

[0769] Operation: The server distributes the generated summary to all users and management.

[0770] Input: Generated summary

[0771] Output: A summary is delivered to user terminals and management

[0772] Actions to be taken: Send a summary to all users and management for further decision-making.

[0773] Example prompt: Send the generated summary to all users and management.

[0774] This provides a detailed explanation of the processing procedures of the system's program, clarifying the inputs, outputs, and specific operations for each step.

[0775] (Application example 1)

[0776] 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."

[0777] In autonomous vehicle development projects, efficient information sharing and decision-making among researchers and engineers with different languages ​​and cultures is a challenge. Conventional methods require time and effort to support multiple languages ​​and consolidate and summarize information, which can cause delays and obstacles to the progress of the project.

[0778] 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.

[0779] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, means for distributing the translated information to other user terminals, means for receiving additional information from multiple users based on the translated information, means for aggregating the received information and generating a summary using a generation AI, means for distributing the generated summary to multiple user terminals, means for notifying management or administrators of the summary, and means for translating the information in real time to streamline information distribution and summary generation, thereby enabling efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[0780] The "means for receiving information entered in different languages" is a function that allows the server to receive data on issues and opinions entered by users in various languages.

[0781] "Means of translating into other languages ​​using a translation API" is a function that converts received information into other languages ​​in real time using an automatic translation service.

[0782] The "means for distributing translated information to other user terminals" is a function for transmitting translated data to other user devices.

[0783] The "means for receiving information added by multiple users based on translated information" is a function that allows the server to receive again the information added by each user based on the translated data.

[0784] "Means of aggregating received information and generating a summary using generative AI" refers to a function that brings together collected data and uses artificial intelligence to organize it into a summary format.

[0785] The "means for distributing the generated summary to a plurality of user terminals" is a function for transmitting the data of the generated summary to all user devices.

[0786] The "means of notifying the executives and managers of the summary" is a function for notifying the leaders and managers of the organization of the generated summary information.

[0787] "A means of translating information in real time and streamlining the distribution of information and the generation of summaries" is a function that translates input information on the spot, quickly shares that information, and creates summaries, thereby streamlining the entire process.

[0788] MODE FOR CARRYING OUT THE INVENTION

[0789] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary. It is primarily designed for autonomous vehicle development projects.

[0790] 1. Server

[0791] The server is the central part of the system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0792] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[0793] Translation function: Works with translation APIs to translate received information into other languages, for example, using Google Translate API or Microsoft Translator API.

[0794] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[0795] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[0796] Summary generation: Uses generative AI to create summaries from aggregated information, specifically using OpenAI's GPT-4 model.

[0797] Summary distribution function: The generated summary is distributed to all relevant users and management.

[0798] Notification function: Notify management and administrators of generated summaries and important information.

[0799] 2. User Device

[0800] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0801] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[0802] Information display function: Provides the function to display translation information and summaries delivered from the server.

[0803] 3. Users

[0804] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0805] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[0806] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[0807] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[0808] Specific examples

[0809] Process Flow

[0810] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0811] The terminal sends this information to the server.

[0812] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[0813] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0814] Each user can view the translated information, add their own comments and resubmit it.

[0815] The server aggregates all the information and generates a summary using OpenAI's GPT-4.

[0816] The generated summary is distributed to all users and management.

[0817] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0818] Prompt Sentence Examples

[0819] Example prompts for generative AI models:

[0820] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[0821] In this way, the use of this system facilitates information sharing among employees with different languages ​​and cultures, thereby improving the efficiency of autonomous vehicle development projects and supporting decision-making.

[0822] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0823] Step 1:

[0824] The user inputs and sends information from the terminal. The user inputs the task or opinion in text format in their own language and clicks the send button. The input includes the text information entered by the user. This information is sent to the server and received by the server.

[0825] Step 2:

[0826] The server translates the received information into other languages ​​using a translation API. Specifically, the input information is translated into all required languages ​​using the Google Translate API, Microsoft Translator API, etc. The input is the information received in step 1, and the output is the translated text information. In this process, the API is called to perform the translation work in real time and obtain the results.

[0827] Step 3:

[0828] The server distributes the translated information to other user terminals. Specifically, it sends the translated information to each user's terminal. The input is the translated information, and the output is the user terminal that received the information. In this process, the server generates a distribution request to each terminal and sends it to ensure that the information arrives correctly.

[0829] Step 4:

[0830] The user receives the translated information and adds their own opinion. The user's device displays the translated information delivered from the server, and the user inputs a new opinion in text format based on it and sends it. The input is the delivered information, and the output is the added opinion information. In this process, the user edits the information, generates new data, and sends it to the server.

[0831] Step 5:

[0832] The server collects and aggregates the added information. All new information submitted by multiple users is compiled into a single dataset. The input is the added opinion information, and the output is the aggregated dataset. In this process, the server centrally manages all new data and organizes the aggregated data.

[0833] Step 6:

[0834] The server generates a summary using generative AI. A summary is created from the aggregated information using OpenAI's GPT-4 model. The input is the aggregated dataset, and the output is the generated summary. In this process, a prompt sentence is used to input summarization instructions to the AI ​​model, and the results are obtained.

[0835] Step 7:

[0836] The server distributes the generated summary to multiple user terminals and management. Specifically, it sends the generated summary data to all relevant user and manager terminals. The input is the generated summary, and the output is the user terminal that received the summary. In this process, the server uses a distribution list to deliver the summary to each terminal.

[0837] Step 8:

[0838] Management reviews the summary and uses it to inform decision-making. Management then takes specific actions and makes decisions based on the summarized information. The input is the delivered summary information, and the output is a decision. This process evaluates the received information and determines the next steps for the project based on the results.

[0839] For example, here's a prompt:

[0840] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[0841] This will enable efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[0842] 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.

[0843] Okay, so let's create a "Description of the Invention" for the invention that combines the emotion engine based on the scope of the patent claims.

[0844] ---

[0845] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[0846] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[0847] 1. Server

[0848] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0849] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[0850] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[0851] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[0852] Emotion Recognition: Using an emotion engine, the emotion of the received information is analyzed, for example, to recognize positive, negative, and neutral emotions.

[0853] Emotion information distribution function: Distributes recognized emotion information to other users.

[0854] Information aggregation function: After translation and emotion recognition, the received information is collected again and aggregated into a single data set.

[0855] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[0856] Emotion-reflecting summary generation function: The generated summary reflects the user's emotional information.

[0857] Summary distribution function: The generated summary is distributed to all relevant users and management.

[0858] 2. User Device

[0859] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0860] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[0861] Information display function: Provides a function to display translation information, summaries, and emotional information delivered from the server.

[0862] 3. Users

[0863] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0864] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[0865] Information evaluation and addition: Receive translated information and sentiment information from other users and add your own opinion. For example, American user B sees the translated information and comments in English, saying, "This is a good idea."

[0866] Summary review and decision support: Management and others review the generated summary and sentiment information and make decisions based on it.

[0867] Specific examples

[0868] Specific usage examples are shown below.

[0869] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0870] The terminal sends this information to the server.

[0871] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[0872] The server uses an emotion engine to recognize negative emotions from the information of user A.

[0873] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0874] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[0875] The server aggregates all the information and uses generative AI to generate a summary, which also takes into account emotional information.

[0876] The generated summary is distributed to all users and management.

[0877] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0878] In this way, this system facilitates information sharing among employees with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[0879] ---

[0880] The above is a detailed explanation of the "Form for implementing the invention."

[0881] The processing flow will be explained below.

[0882] Okay, so let me explain the process step by step.

[0883] ---

[0884] Step 1:

[0885] A user accesses the application through a terminal and logs in with their account.

[0886] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[0887] Step 2:

[0888] The terminal transmits the login information to the server.

[0889] Specific operation: The terminal sends the authentication information entered by user A to the server.

[0890] Step 3:

[0891] The server validates the authentication information and starts a session if the login is successful.

[0892] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[0893] Step 4:

[0894] The user enters business issues and opinions into the application's input form.

[0895] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[0896] Step 5:

[0897] The terminal transmits the user's input information to the server.

[0898] Specific operation: The terminal sends the text data entered by user A to the server.

[0899] Step 6:

[0900] The server sends the received information to a translation API to translate it into other languages.

[0901] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[0902] Step 7:

[0903] The translation API returns the translation results to the server.

[0904] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[0905] Step 8:

[0906] The server sends the received information to an emotion engine to analyze the emotion.

[0907] Specific operation: The server calls the emotion engine and recognizes positive, negative, and neutral emotions from the input text of user A.

[0908] Step 9:

[0909] The emotion engine returns the emotion analysis results to the server.

[0910] Specific operation: The emotion engine returns the emotion analysis result (e.g., negative) to the server.

[0911] Step 10:

[0912] The server distributes the translated information and emotion analysis results to other user terminals.

[0913] Specific operation: The server sends the translation results and sentiment analysis results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[0914] Step 11:

[0915] The terminal displays the received translation information and emotion information to the user.

[0916] Specific operation: The devices of users B, C, and D present the opinions and emotion information displayed in their respective languages ​​to the users.

[0917] Step 12:

[0918] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[0919] Specific operation: User B inputs his / her opinion in English, and User C inputs his / her opinion in Chinese.

[0920] Step 13:

[0921] The terminal transmits the input information of the other users to the server.

[0922] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[0923] Step 14:

[0924] The server aggregates all the information and creates a summary using generative AI.

[0925] Specific operation: The server retrieves the opinions and emotional information of all users from the database and uses the generation AI to generate a summary, which also reflects the emotional information.

[0926] Step 15:

[0927] The server distributes the generated summary to all users and management.

[0928] Specific operation: The server sends the generated multilingual summaries and sentiment information to all users and management's terminals.

[0929] Step 16:

[0930] Management reviews the summary through a terminal and decides on the necessary actions.

[0931] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[0932] ---

[0933] The above is a detailed explanation of the processing flow of a system that includes an emotion engine.

[0934] Example 2

[0935] 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."

[0936] Conventional information sharing systems have made it difficult for employees with different languages ​​and cultures to share information smoothly, which can hinder effective decision-making. Furthermore, they are unable to take into account users' emotional information, which can lead to important emotional factors being overlooked in decision-making. This invention solves these problems and realizes efficient information sharing and decision-making support that supports multiple languages ​​and takes into account emotional information.

[0937] 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.

[0938] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation means, means for distributing the translated information to other information processing terminals, means for receiving information added to the distributed information from multiple users, means for aggregating the received information and the added information, means for generating a summary based on the aggregated information using a generative model, means for distributing the generated summary to multiple information processing terminals, means for analyzing emotions in the received information, and means for generating a summary using the results of the emotion analysis. This facilitates information sharing between users who speak different languages ​​and enables decision-making that takes emotional information into consideration.

[0939] Okay, now let's create definitions for each of the important words included in the rewritten claims.

[0940] "Different languages" refers to multiple natural languages ​​used as means of communication in different regions and cultures.

[0941] "Means for receiving" refers to devices or software that have the function of acquiring data sent from users and importing it into a server.

[0942] "Translation means" refers to a system or software, such as a translation API, that converts input information into another language.

[0943] "Other information processing terminals" refers to devices used by users, such as computers, smartphones, and tablets.

[0944] "Delivery means" refers to devices or software that have the functionality to allow the server to deliver translated information or summaries to other information processing terminals.

[0945] "Added information" refers to new opinions or data provided by the user in response to the received translation information.

[0946] "Aggregation means" refers to a system for organizing and integrating information received from multiple users into a single data set.

[0947] A "generative model" refers to an artificial intelligence algorithm that analyzes given data and generates summaries or new data.

[0948] A "means for generating a summary" refers to a device or software that uses a generative model to extract key points from aggregated information and summarize them in a concise form.

[0949] "Means for analyzing emotions" refers to an emotion recognition engine or software for identifying a user's emotional state from received information.

[0950] "Means for generating summaries using the results of emotion analysis" refers to a system that takes into account the results of emotion analysis and has the function of reflecting emotional information in the generated summary.

[0951] Understood. Now, let's write the "Form for carrying out the invention."

[0952] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[0953] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[0954] 1. Server

[0955] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[0956] Information reception function

[0957] The server receives issues and opinions submitted by users. This information can be entered in different languages. The server uses the HTTP / HTTPS protocol to receive the information.

[0958] Translation feature

[0959] The server works with a translation API (e.g., Google Translate API) to translate the received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[0960] Information distribution function

[0961] The server then distributes the translated information to other users, potentially using real-time communication technologies (e.g., WebSockets) so that the same content can be understood by users who speak different languages.

[0962] Emotion recognition function

[0963] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion of the received information, for example, recognizing positive, negative, and neutral emotions.

[0964] Emotional information distribution function

[0965] The server distributes the recognized emotion information to other users, allowing them to understand the emotional state of other users.

[0966] Information aggregation function

[0967] The server collects the received information again after translation and emotion recognition and aggregates it into a single data set. This aggregation process uses a database to properly organize and store the information.

[0968] Summary generation function

[0969] The server uses generative AI (e.g., OpenAI's GPT-3) to create a summary from the aggregated information, which is a short, concise summary that extracts the key points.

[0970] Emotional summary generation function

[0971] The server reflects the user's emotional information in the generated summary, so that the summary is provided in a form that includes emotional elements.

[0972] Summary delivery function

[0973] The server distributes the generated summaries to all relevant users and decision makers via email, push notifications, and other methods.

[0974] 2. User Device

[0975] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[0976] Information input function

[0977] The terminal allows users to input their assignments and opinions in text format and send them to a server using a dedicated application or web interface.

[0978] Information display function

[0979] The terminal provides the functionality to display translation information, summaries, and emotional information delivered from the server, sometimes using real-time update technology (e.g., AJAX).

[0980] 3. Users

[0981] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[0982] Enter information

[0983] Users input and submit their opinions and issues through the terminal. For example, User A in Japan inputs and submits "opinions about the marketing strategy for a new product" in Japanese.

[0984] Information evaluation and addition

[0985] Users receive translated information and sentiment information from other users and add their own opinions. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[0986] Summary review and decision support

[0987] The decision maker reviews the generated summary and sentiment information and makes a decision based on it.

[0988] Specific examples

[0989] Specific usage examples are shown below.

[0990] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[0991] The terminal sends this information to the server.

[0992] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[0993] The server uses IBM Watson's emotion analysis API to recognize negative emotions from User A's information.

[0994] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[0995] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[0996] The server aggregates all the information and generates a summary using OpenAI's GPT-3, which also incorporates sentiment information.

[0997] The generated summary is distributed to all users and decision makers.

[0998] The decision maker reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[0999] In this way, this system facilitates information sharing between users with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[1000] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1001] Processing Steps

[1002] Step 1: Enter your information

[1003] Users use their devices to input their opinions and issues in text format. For example, User A inputs "Opinions about the marketing strategy for a new product" in Japanese and clicks the send button.

[1004] Input: User opinions and issues (text data)

[1005] Output: Text data entered into the terminal

[1006] Step 2: Submit your information

[1007] The terminal sends the input information to the server. At this time, the data is encrypted before being sent, ensuring security.

[1008] Input: Text data entered by the user

[1009] Output: Encrypted data to the server based on the HTTPS protocol

[1010] Step 3: Receiving information

[1011] The server receives the information sent from the device, at which point it is stored in a database.

[1012] Input: Encrypted data sent from the device

[1013] Output: Decoded text data (user opinions and issues)

[1014] Step 4: Translate the information

[1015] The server passes the received information to a translation means (e.g., Google Translate API) to translate it into other languages. For example, user A's Japanese opinion is translated into English, Chinese, and Spanish.

[1016] Input: Decrypted text data

[1017] Output: Translated text data (multiple languages)

[1018] Step 5: Emotion Recognition

[1019] The server passes the translated information to an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion. For example, it recognizes negative emotions from User A's opinion.

[1020] Input: Translated text data

[1021] Output: Sentiment analysis results (positive, negative, neutral, etc.)

[1022] Step 6: Delivering translation and emotion information

[1023] The server distributes the translated information and emotion information to the terminals of other users.

[1024] Input: translated text data, sentiment analysis results

[1025] Output: Data delivered to user device (text and emotional information)

[1026] Step 7: Evaluate and add information

[1027] The user can then check the translation and emotion information delivered to their device and add their own opinion. For example, User B can type "This is a good idea" in English and resubmit.

[1028] Input: Delivered text data and emotional information

[1029] Output: Added opinions (text data)

[1030] Step 8: Submit additional information

[1031] The terminal transmits the added information to the server again.

[1032] Input: Added opinion (text data)

[1033] Output: Encrypted data to the server based on the HTTPS protocol

[1034] Step 9: Aggregating information

[1035] The server receives the added information and stores and aggregates all user submitted information in a database, filtering out duplicate and irrelevant information.

[1036] Input: Additional comments from users (text data)

[1037] Output: Aggregated text dataset

[1038] Step 10: Summary generation

[1039] The server passes the aggregated information to a generative AI (e.g., OpenAI's GPT-3) to generate a summary, which extracts the key points and summarizes them in a short, concise manner.

[1040] Input: Aggregated text dataset

[1041] Output: Generated summary (text data)

[1042] Step 11: Emotion-reflecting summary generation

[1043] The server reflects the user's emotional information in the generated summary, thereby providing the summary in a form that includes emotional information.

[1044] Input: Generated summary, sentiment analysis results

[1045] Output: Summary (text data) reflecting emotional information

[1046] Step 12: Deliver the summary

[1047] The server distributes the generated summaries to all users and decision makers via email, push notifications, and other methods.

[1048] Input: A summary that reflects emotional information

[1049] Output: Data delivered to users and decision makers (text data)

[1050] In this way, the system realizes a series of processes: sharing users' opinions and issues in multiple languages, generating summaries taking into account emotional information, and providing information that contributes to decision-making.

[1051] (Application example 2)

[1052] 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."

[1053] In modern logistics centers, it is common for employees with different languages ​​and cultures to work together. However, if information is not shared smoothly across multiple languages, there is a risk of reduced productivity and mistakes due to misunderstandings. Furthermore, if the psychological state and emotions of employees are not understood, it can be difficult to improve the working environment and make efficient decisions. A system that can solve these issues is needed.

[1054] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, and means for receiving information added by multiple users based on the translated information and emotion information. This enables efficient information sharing across multiple languages ​​and appropriate management based on employee emotion information.

[1055] Okay, so let's create definitions for the important words included in the patent claims according to the application example.

[1056] "Information entered in different languages" refers to text data such as opinions and feedback entered by multiple users who use different languages.

[1057] A "translation API" is an application programming interface for automatically translating text between different languages.

[1058] An "emotion recognition engine" is software for analyzing and identifying a user's emotional state from text data.

[1059] "Generative AI" is an artificial intelligence technology that generates summaries and organizes information based on multiple collected text data.

[1060] "User Terminal" means an electronic device connected to the System that allows a User to input and receive information. Examples include smartphones, tablets, and PCs.

[1061] The "information receiving means" is a function that receives information sent from a user terminal and imports it into the server.

[1062] The "information distribution means" is a function that transmits information collected in the server to an appropriate user terminal.

[1063] The "information aggregation means" is a function that aggregates information received from multiple users into one piece of data.

[1064] "Summary generation means" is a function that uses generative AI to extract key points from aggregated information and create a concise summary.

[1065] The "emotion information distribution means" is a function that distributes analyzed emotion information to other users and the administrator.

[1066] A "manager" is someone whose job is to oversee the entire system and make decisions based on employee behavior and sentiment information.

[1067] "Multilingual support" refers to the ability to support multiple different languages ​​and enable smooth communication between these languages.

[1068] The above definitions clearly indicate the meaning of important terms contained in the claims.

[1069] This invention combines a multilingual issue aggregation system with an emotion recognition engine for use in logistics centers where employees with different languages ​​and cultures work together. The system efficiently translates information entered in different languages, shares it among employees, consolidates the information, and generates summaries. It also analyzes each employee's emotional information, allowing managers to respond appropriately.

[1070] 1. Server

[1071] The server is the core of this system and has the following functions:

[1072] Information receiving means: receives information in different languages ​​sent from the user terminal. This information is input in different languages, such as Japanese, English, Spanish, etc.

[1073] Translation method: Using a translation API, the received information is translated into another language. For example, information entered by a user in Japanese is translated into English or Chinese.

[1074] Information distribution means: Translated information is distributed to each user's device, allowing users who speak different languages ​​to understand the information.

[1075] Emotion recognition means: An emotion recognition engine is used to analyze the user's emotions from the received information. The analysis results include positive, negative, neutral, etc.

[1076] Information aggregation method: Aggregate information after translation and emotion recognition and compile the whole into a single data set.

[1077] Summary generator: A generative AI model is used to generate a summary from the aggregated information, which extracts key points and summarizes them succinctly.

[1078] Emotional information distribution method: Emotional information is reflected in the generated summary and distributed to all parties involved.

[1079] 2. User Device

[1080] User terminals are devices that employees use to input and receive information, including smart glasses, smartphones, and tablets.

[1081] Information input means: Provides a means for users to input their opinions and issues in text format and send them to the server.

[1082] Information display means: Provides a means to display translation information, summaries, and emotional information delivered from the server.

[1083] 3. Users

[1084] Users are employees and administrators who use the system, and it is assumed that they have different languages ​​and cultures.

[1085] Information input: Users input their opinions and issues through the terminal and send them. For example, a Japanese user inputs and sends a "proposal for improving the packaging of a new product" in Japanese.

[1086] Information evaluation and addition: Receive translated information and sentiment information from other users, add your own opinion to it, and resubmit it. For example, an English-speaking user may send feedback such as "This is a good idea."

[1087] Reviewing the summary and making decisions: The manager reviews the generated summary and sentiment information and makes decisions based on it, for example, setting up a meeting to decide on a new marketing strategy.

[1088] Specific examples

[1089] For example, in a discussion about packaging methods at a logistics center, opinions entered in different languages ​​can be translated, sentiment analyzed, and a summary generated based on the results. Using this system, employee A can enter "I propose a new packaging method" in Japanese, which is translated into English and perceived by the manager as "positive feedback." Employee B can also enter "I think this new packaging is great" in English, which is translated into Japanese and recognized as "positive" through sentiment analysis.

[1090] An example of a prompt is:

[1091] plaintext

[1092] "Translate comments entered in different languages ​​about a discussion about packaging methods at a distribution center, perform sentiment analysis, and generate summaries based on that."

[1093] is input into the generative AI model.

[1094] By using this system, it becomes possible to efficiently share information across multiple languages ​​and to appropriately manage employees based on their emotional state.

[1095] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1096] (Processing flow)

[1097] Step 1:

[1098] This is the stage where the user terminal receives information. The user enters text information in their own language and sends this information to the server via the terminal. The entered text information is sent to the server in its original format. For example, Japanese user A enters "I would like to propose a new packaging method" and clicks the send button. This entered text is sent to the server, and the server receives this information.

[1099] Step 2:

[1100] The server passes the received information to a translation API, which translates it into multiple languages. In this case, translation is from Japanese to English, Chinese, etc. The translation API analyzes the received text information and converts it into the specified target language. For example, it translates "I propose a new packaging method." into "I propose a new packaging method." The translation result is returned to the server.

[1101] Step 3:

[1102] The server uses the translated information to pass the data to an emotion recognition engine for sentiment analysis. The emotion recognition engine identifies the user's emotional state based on the received text data and returns the result to the server. For example, the text "I propose a new packaging method." is recognized as "positive."

[1103] Step 4:

[1104] The server delivers the translation results and sentiment information to the user's device, where it can be displayed and confirmed by other users. For example, English-speaking user B receives the message "I propose a new packaging method." and confirms the positive feedback.

[1105] Step 5:

[1106] Other users receive the information and add their own opinions. This information is then sent back to the server, where it is further analyzed. For example, user B adds his opinion, "This is a great idea," and sends it back. The server receives the information again and performs translation and sentiment analysis.

[1107] Step 6:

[1108] The server passes the aggregated information to a generative AI model, which then generates an overall summary. The generative AI model analyzes various text data, extracts key points, and generates a summary. For example, it creates a summary such as "The new packaging method has received positive reviews" based on multiple opinions and feedback.

[1109] Step 7:

[1110] The server distributes the generated summary and sentiment information to the administrator and other interested parties. The administrator can make decisions based on the summary. For example, the administrator can decide whether to adopt a new packaging method after viewing the summary and sentiment information.

[1111] The above is a detailed description of the steps involved in implementing the present invention, which enables efficient information sharing across multiple languages ​​and appropriate management based on employee emotional information.

[1112] 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.

[1113] 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.

[1114] 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.

[1115] [Third embodiment]

[1116] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1117] 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.

[1118] 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).

[1119] 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.

[1120] 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.

[1121] 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).

[1122] 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.

[1123] 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.

[1124] 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.

[1125] 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.

[1126] 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.

[1127] 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."

[1128] Okay, so let's create a "Description of the Invention" based on the claims. We won't list the processing steps here because we'll ask about them later.

[1129] ---

[1130] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary.

[1131] The whole system mainly consists of a server, a user terminal, and the user itself. The roles and functions of each are explained in detail below.

[1132] 1. Server

[1133] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[1134] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[1135] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[1136] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[1137] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[1138] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[1139] Summary distribution function: The generated summary is distributed to all relevant users and management.

[1140] 2. User Device

[1141] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[1142] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[1143] Information display function: Provides the function to display translation information and summaries delivered from the server.

[1144] 3. Users

[1145] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[1146] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[1147] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[1148] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[1149] Specific examples

[1150] Specific usage examples are shown below.

[1151] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[1152] The terminal sends this information to the server.

[1153] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[1154] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[1155] Each user can view the translated information, add their own comments and resubmit it.

[1156] The server aggregates all the information and generates a summary using generative AI.

[1157] The generated summary is distributed to all users and management.

[1158] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[1159] In this way, the use of this system makes it easier to share information among employees with different languages ​​and cultures, and makes it easier to explain and persuade management about issues.

[1160] ---

[1161] The above is a detailed explanation of the "Form for implementing the invention."

[1162] The processing flow will be explained below.

[1163] I understand. Now, I will explain the program's processing flow in detail in the following format.

[1164] ---

[1165] Step 1:

[1166] A user accesses the application through a terminal and logs in with their account.

[1167] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[1168] Step 2:

[1169] The terminal transmits the login information to the server.

[1170] Specific operation: The terminal sends the authentication information entered by user A to the server.

[1171] Step 3:

[1172] The server validates the authentication information and starts a session if the login is successful.

[1173] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[1174] Step 4:

[1175] The user enters business issues and opinions into the application's input form.

[1176] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[1177] Step 5:

[1178] The terminal transmits the user's input information to the server.

[1179] Specific operation: The terminal sends the text data entered by user A to the server.

[1180] Step 6:

[1181] The server sends the received information to a translation API to translate it into other languages.

[1182] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[1183] Step 7:

[1184] The translation API returns the translation results to the server.

[1185] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[1186] Step 8:

[1187] The server distributes the translated information to other user terminals.

[1188] Specific operation: The server sends the translation results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[1189] Step 9:

[1190] The terminal displays the received translation information to the user.

[1191] Specific operation: The devices of users B, C, and D present the opinions displayed in their respective languages ​​to the users.

[1192] Step 10:

[1193] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[1194] Specific operation: User B inputs his opinion in English, and Chinese-speaking User C inputs his opinion in Chinese.

[1195] Step 11:

[1196] The terminal transmits the input information of the other users to the server.

[1197] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[1198] Step 12:

[1199] The server aggregates all the information and creates a summary using generative AI.

[1200] Specific operation: The server retrieves all user opinions from the database and generates a summary using generation AI.

[1201] Step 13:

[1202] The server distributes the generated summary to all users and management.

[1203] Specific operation: The server sends the multilingual summaries to all users and management's terminals.

[1204] Step 14:

[1205] Management reviews the summary through a terminal and decides on the necessary actions.

[1206] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[1207] ---

[1208] This concludes the detailed explanation of the program's processing flow.

[1209] Example 1

[1210] 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."

[1211] The aim is to solve the problem of difficulty in smooth communication and information sharing among employees with different languages ​​and cultures. In particular, there is a need to quickly and accurately translate information entered in different languages ​​and make efficient decisions based on that translation.

[1212] 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.

[1213] In this invention, the server includes means for receiving information entered in different languages, means for translating the information into other languages ​​using a translation API, means for distributing the translated information to other user terminals, means for receiving information added by multiple users, means for aggregating the received information and generating summaries using a generative AI model, means for distributing the generated summaries to multiple user terminals, means for displaying the translated information and summaries, and means for users who receive the summaries to add their opinions. This facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[1214] "Different languages" refers to multiple natural languages ​​spoken by users in different regions or cultures.

[1215] "Information" refers to data such as opinions, challenges, and feedback that users input or submit to the system.

[1216] "Receiving" refers to the server acquiring information sent from a user terminal.

[1217] "Translation API" refers to an application program interface used to translate text between different languages.

[1218] "Delivery" refers to the server sending the translated information and generated summaries to the user terminal.

[1219] "User terminal" refers to a device, such as a PC, smartphone, or tablet, that a user uses to input and receive information.

[1220] "Added information" refers to new opinions and feedback provided based on translated information from other users.

[1221] "Aggregation" refers to combining multiple pieces of received information into a single data set.

[1222] "Generative AI model" refers to an artificial intelligence model used to perform summarization or other processing on aggregated information.

[1223] A "summary" is a concise summary of the important points of aggregated information.

[1224] "Management" refers to the management layer responsible for decision-making in a company or organization.

[1225] This invention relates to a multilingual issue aggregation system that enables employees with different languages ​​and cultures to share information and make efficient decisions. The entire system is mainly composed of a server, user terminals, and users, each of which plays a specific role. The details of this system are described below.

[1226] server

[1227] The server is the core of this system and has the following main functions:

[1228] 1. Information reception function: The server receives information sent from the user terminal. Information is entered in text format. For example, User A in Japan enters and sends "opinions regarding the marketing strategy for a new product" in Japanese.

[1229] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[1230] 2. Translation function: The server analyzes the received information and translates it into other languages ​​using a translation API (e.g., Google Cloud Translation API). For example, information entered in Japanese can be translated into English, Chinese, or Spanish.

[1231] Example prompt: The server translates Japanese information into English, Chinese, and Spanish.

[1232] 3. Information distribution function: The translated information is distributed to other user terminals, for example, to English-speaking user B, Chinese-speaking user C, and Spanish-speaking user D.

[1233] Example prompt: Send translated information to User B, User C, and User D.

[1234] 4. Information aggregation function: The server receives and aggregates the opinions and feedback sent back by each user, forming an overall data set.

[1235] Example prompt: Collect information from all users and aggregate it into one dataset.

[1236] 5. Summary generation function: The server generates a summary based on the aggregated information using a generative AI model (e.g., OpenAI GPT-3). For example, the server inputs an instruction such as, "Please summarize the important points."

[1237] Example prompt: "Please summarize the key points" is input to the generation AI.

[1238] 6. Summary distribution function: The generated summary is distributed to all users and management, who can then make decisions based on it.

[1239] Example prompt: Send the generated summary to all users and management.

[1240] User terminal

[1241] A user terminal is a device that users use to input and receive information. It includes PCs, smartphones, tablets, etc. Each terminal has the following functions:

[1242] 1. Information input function: Users input their opinions and issues in text format and send them to the server. For example, User A writes his opinion in Japanese.

[1243] Example prompt: Enter "Your opinion on the marketing strategy for a new product" in Japanese and press the submit button.

[1244] 2. Information display function: The terminal displays the translated information and summary delivered from the server. For example, information translated into English is displayed on User B's terminal.

[1245] Example prompt: A Japanese comment is translated into English and displayed on User B's device.

[1246] User

[1247] Users are employees and administrators who use the system and have different languages ​​and cultures. Users have the following roles:

[1248] 1. Information input: Enter your opinions and assignments through the terminal and send them to the server.

[1249] Example prompt: User A enters "Your opinion on the marketing strategy for a new product" and presses the submit button.

[1250] 2. Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, User B adds his opinion in English, saying "This is a good idea," and submits it.

[1251] Example prompt: User B types "That's a good idea" in English and presses the send button.

[1252] 3. Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[1253] Example prompt: Management reviews the generated summary and decides on a new marketing strategy.

[1254] Specific examples

[1255] For example, User A in Japan enters his or her opinion on a new product's marketing strategy, and that information is translated into English, Chinese, and Spanish through the system. Users B, C, and D, who speak each language, receive that information and add their own opinions. The server then uses a generative AI model to generate a summary from the aggregated information, which is finally distributed to all users and management. This process facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[1256] In this way, this multilingual issue aggregation system effectively supports information sharing and decision-making among employees with different languages ​​and cultures.

[1257] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1258] I understand. Now, I will explain the program processing flow of this system in detail by dividing it into the following steps.

[1259] Program processing steps

[1260] Step 1: Enter your information

[1261] Subject: Terminal

[1262] Operation: A user uses a terminal to enter opinions or issues in text format into an information input form.

[1263] Input: User opinions and issues (e.g., "Opinions regarding marketing strategies for new products")

[1264] Output: Text data is sent from the terminal to the server.

[1265] Specific operation: User A enters "Opinion on marketing strategy for new product" and clicks the submit button.

[1266] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[1267] Step 2: Receiving information

[1268] Subject: Server

[1269] Operation: The server receives the information sent from the terminal.

[1270] Input: Text data sent from the terminal

[1271] Output: Text data received by the server

[1272] Specific operation: Receive Japanese text data sent from the terminal to the server.

[1273] Example prompt: Receive text data for "Your opinion on the marketing strategy for a new product."

[1274] Step 3: Information Translation

[1275] Subject: Server

[1276] How it works: The server parses the information it receives and uses the translation API to translate it into different languages.

[1277] Input: Text data received by the server

[1278] Output: Translated text data (e.g., English, Chinese, Spanish)

[1279] Specific operation: The server translates Japanese information into English, Chinese, and Spanish.

[1280] Example prompt: Translate information submitted in Japanese into English, Chinese, and Spanish.

[1281] Step 4: Information distribution

[1282] Subject: Server

[1283] Operation: The server distributes the translated information to other user terminals.

[1284] Input: Translated text data

[1285] Output: Translated text data delivered to the user's device

[1286] Specific operation: The server sends the translated information to User B, User C, and User D.

[1287] Example prompt: Send translated information to User B, User C, and User D.

[1288] Step 5: Add information

[1289] Subject: User

[1290] What it does: Other users see the translated information, add their comments and resubmit.

[1291] Input: Translated information and user's additional comments

[1292] Output: Additional comments sent to the server

[1293] Specific action: User B adds an opinion in English saying "This is a good idea" and submits it.

[1294] Example prompt: "This is a good idea," add your opinion, and submit.

[1295] Step 6: Information aggregation

[1296] Subject: Server

[1297] How it works: The server collects the information returned by all users and aggregates it into a single data set.

[1298] Input: Additional comments submitted by multiple users

[1299] Output: Aggregated dataset

[1300] Specific operation: Collect information from all users and compile it into a single dataset.

[1301] Example prompt: Collect information from all users and aggregate it into one dataset.

[1302] Step 7: Summary generation

[1303] Subject: Server

[1304] How it works: The server generates a summary based on the aggregated information using a generative AI model.

[1305] Input: Aggregated dataset

[1306] Output: Generated summary

[1307] Specific operation: The generative AI model is given the prompt "Please summarize the key points in a summary" and a summary is generated.

[1308] Example prompt: "Please summarize the key points" is input to the generation AI.

[1309] Step 8: Summary Delivery

[1310] Subject: Server

[1311] Operation: The server distributes the generated summary to all users and management.

[1312] Input: Generated summary

[1313] Output: A summary is delivered to user terminals and management

[1314] Actions to be taken: Send a summary to all users and management for further decision-making.

[1315] Example prompt: Send the generated summary to all users and management.

[1316] This provides a detailed explanation of the processing procedures of the system's program, clarifying the inputs, outputs, and specific operations for each step.

[1317] (Application example 1)

[1318] 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."

[1319] In autonomous vehicle development projects, efficient information sharing and decision-making among researchers and engineers with different languages ​​and cultures is a challenge. Conventional methods require time and effort to support multiple languages ​​and consolidate and summarize information, which can cause delays and obstacles to the progress of the project.

[1320] 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.

[1321] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, means for distributing the translated information to other user terminals, means for receiving additional information from multiple users based on the translated information, means for aggregating the received information and generating a summary using a generation AI, means for distributing the generated summary to multiple user terminals, means for notifying management or administrators of the summary, and means for translating the information in real time to streamline information distribution and summary generation, thereby enabling efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[1322] The "means for receiving information entered in different languages" is a function that allows the server to receive data on issues and opinions entered by users in various languages.

[1323] "Means of translating into other languages ​​using a translation API" is a function that converts received information into other languages ​​in real time using an automatic translation service.

[1324] The "means for distributing translated information to other user terminals" is a function for transmitting translated data to other user devices.

[1325] The "means for receiving information added by multiple users based on translated information" is a function that allows the server to receive again the information added by each user based on the translated data.

[1326] "Means of aggregating received information and generating a summary using generative AI" refers to a function that brings together collected data and uses artificial intelligence to organize it into a summary format.

[1327] The "means for distributing the generated summary to a plurality of user terminals" is a function for transmitting the data of the generated summary to all user devices.

[1328] The "means of notifying the executives and managers of the summary" is a function for notifying the leaders and managers of the organization of the generated summary information.

[1329] "A means of translating information in real time and streamlining the distribution of information and the generation of summaries" is a function that translates input information on the spot, quickly shares that information, and creates summaries, thereby streamlining the entire process.

[1330] MODE FOR CARRYING OUT THE INVENTION

[1331] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary. It is primarily designed for autonomous vehicle development projects.

[1332] 1. Server

[1333] The server is the central part of the system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[1334] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[1335] Translation function: Works with translation APIs to translate received information into other languages, for example, using Google Translate API or Microsoft Translator API.

[1336] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[1337] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[1338] Summary generation: Uses generative AI to create summaries from aggregated information, specifically using OpenAI's GPT-4 model.

[1339] Summary distribution function: The generated summary is distributed to all relevant users and management.

[1340] Notification function: Notify management and administrators of generated summaries and important information.

[1341] 2. User Device

[1342] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[1343] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[1344] Information display function: Provides the function to display translation information and summaries delivered from the server.

[1345] 3. Users

[1346] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[1347] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[1348] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[1349] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[1350] Specific examples

[1351] Process Flow

[1352] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[1353] The terminal sends this information to the server.

[1354] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[1355] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[1356] Each user can view the translated information, add their own comments and resubmit it.

[1357] The server aggregates all the information and generates a summary using OpenAI's GPT-4.

[1358] The generated summary is distributed to all users and management.

[1359] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[1360] Prompt Sentence Examples

[1361] Example prompts for generative AI models:

[1362] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[1363] In this way, the use of this system facilitates information sharing among employees with different languages ​​and cultures, thereby improving the efficiency of autonomous vehicle development projects and supporting decision-making.

[1364] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1365] Step 1:

[1366] The user inputs and sends information from the terminal. The user inputs the task or opinion in text format in their own language and clicks the send button. The input includes the text information entered by the user. This information is sent to the server and received by the server.

[1367] Step 2:

[1368] The server translates the received information into other languages ​​using a translation API. Specifically, the input information is translated into all required languages ​​using the Google Translate API, Microsoft Translator API, etc. The input is the information received in step 1, and the output is the translated text information. In this process, the API is called to perform the translation work in real time and obtain the results.

[1369] Step 3:

[1370] The server distributes the translated information to other user terminals. Specifically, it sends the translated information to each user's terminal. The input is the translated information, and the output is the user terminal that received the information. In this process, the server generates a distribution request to each terminal and sends it to ensure that the information arrives correctly.

[1371] Step 4:

[1372] The user receives the translated information and adds their own opinion. The user's device displays the translated information delivered from the server, and the user inputs a new opinion in text format based on it and sends it. The input is the delivered information, and the output is the added opinion information. In this process, the user edits the information, generates new data, and sends it to the server.

[1373] Step 5:

[1374] The server collects and aggregates the added information. All new information submitted by multiple users is compiled into a single dataset. The input is the added opinion information, and the output is the aggregated dataset. In this process, the server centrally manages all new data and organizes the aggregated data.

[1375] Step 6:

[1376] The server generates a summary using generative AI. A summary is created from the aggregated information using OpenAI's GPT-4 model. The input is the aggregated dataset, and the output is the generated summary. In this process, a prompt sentence is used to input summarization instructions to the AI ​​model, and the results are obtained.

[1377] Step 7:

[1378] The server distributes the generated summary to multiple user terminals and management. Specifically, it sends the generated summary data to all relevant user and manager terminals. The input is the generated summary, and the output is the user terminal that received the summary. In this process, the server uses a distribution list to deliver the summary to each terminal.

[1379] Step 8:

[1380] Management reviews the summary and uses it to inform decision-making. Management then takes specific actions and makes decisions based on the summarized information. The input is the delivered summary information, and the output is a decision. This process evaluates the received information and determines the next steps for the project based on the results.

[1381] For example, here's a prompt:

[1382] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[1383] This will enable efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[1384] 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.

[1385] Okay, so let's create a "Description of the Invention" for the invention that combines the emotion engine based on the scope of the patent claims.

[1386] ---

[1387] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[1388] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[1389] 1. Server

[1390] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[1391] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[1392] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[1393] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[1394] Emotion Recognition: Using an emotion engine, the emotion of the received information is analyzed, for example, to recognize positive, negative, and neutral emotions.

[1395] Emotion information distribution function: Distributes recognized emotion information to other users.

[1396] Information aggregation function: After translation and emotion recognition, the received information is collected again and aggregated into a single data set.

[1397] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[1398] Emotion-reflecting summary generation function: The generated summary reflects the user's emotional information.

[1399] Summary distribution function: The generated summary is distributed to all relevant users and management.

[1400] 2. User Device

[1401] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[1402] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[1403] Information display function: Provides a function to display translation information, summaries, and emotional information delivered from the server.

[1404] 3. Users

[1405] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[1406] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[1407] Information evaluation and addition: Receive translated information and sentiment information from other users and add your own opinion. For example, American user B sees the translated information and comments in English, saying, "This is a good idea."

[1408] Summary review and decision support: Management and others review the generated summary and sentiment information and make decisions based on it.

[1409] Specific examples

[1410] Specific usage examples are shown below.

[1411] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[1412] The terminal sends this information to the server.

[1413] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[1414] The server uses an emotion engine to recognize negative emotions from the information of user A.

[1415] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[1416] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[1417] The server aggregates all the information and uses generative AI to generate a summary, which also takes into account emotional information.

[1418] The generated summary is distributed to all users and management.

[1419] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[1420] In this way, this system facilitates information sharing among employees with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[1421] ---

[1422] The above is a detailed explanation of the "Form for implementing the invention."

[1423] The processing flow will be explained below.

[1424] Okay, so let me explain the process step by step.

[1425] ---

[1426] Step 1:

[1427] A user accesses the application through a terminal and logs in with their account.

[1428] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[1429] Step 2:

[1430] The terminal transmits the login information to the server.

[1431] Specific operation: The terminal sends the authentication information entered by user A to the server.

[1432] Step 3:

[1433] The server validates the authentication information and starts a session if the login is successful.

[1434] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[1435] Step 4:

[1436] The user enters business issues and opinions into the application's input form.

[1437] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[1438] Step 5:

[1439] The terminal transmits the user's input information to the server.

[1440] Specific operation: The terminal sends the text data entered by user A to the server.

[1441] Step 6:

[1442] The server sends the received information to a translation API to translate it into other languages.

[1443] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[1444] Step 7:

[1445] The translation API returns the translation results to the server.

[1446] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[1447] Step 8:

[1448] The server sends the received information to an emotion engine to analyze the emotion.

[1449] Specific operation: The server calls the emotion engine and recognizes positive, negative, and neutral emotions from the input text of user A.

[1450] Step 9:

[1451] The emotion engine returns the emotion analysis results to the server.

[1452] Specific operation: The emotion engine returns the emotion analysis result (e.g., negative) to the server.

[1453] Step 10:

[1454] The server distributes the translated information and emotion analysis results to other user terminals.

[1455] Specific operation: The server sends the translation results and sentiment analysis results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[1456] Step 11:

[1457] The terminal displays the received translation information and emotion information to the user.

[1458] Specific operation: The devices of users B, C, and D present the opinions and emotion information displayed in their respective languages ​​to the users.

[1459] Step 12:

[1460] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[1461] Specific operation: User B inputs his / her opinion in English, and User C inputs his / her opinion in Chinese.

[1462] Step 13:

[1463] The terminal transmits the input information of the other users to the server.

[1464] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[1465] Step 14:

[1466] The server aggregates all the information and creates a summary using generative AI.

[1467] Specific operation: The server retrieves the opinions and emotional information of all users from the database and uses the generation AI to generate a summary, which also reflects the emotional information.

[1468] Step 15:

[1469] The server distributes the generated summary to all users and management.

[1470] Specific operation: The server sends the generated multilingual summaries and sentiment information to all users and management's terminals.

[1471] Step 16:

[1472] Management reviews the summary through a terminal and decides on the necessary actions.

[1473] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[1474] ---

[1475] The above is a detailed explanation of the processing flow of a system that includes an emotion engine.

[1476] Example 2

[1477] 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."

[1478] Conventional information sharing systems have made it difficult for employees with different languages ​​and cultures to share information smoothly, which can hinder effective decision-making. Furthermore, they are unable to take into account users' emotional information, which can lead to important emotional factors being overlooked in decision-making. This invention solves these problems and realizes efficient information sharing and decision-making support that supports multiple languages ​​and takes into account emotional information.

[1479] 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.

[1480] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation means, means for distributing the translated information to other information processing terminals, means for receiving information added to the distributed information from multiple users, means for aggregating the received information and the added information, means for generating a summary based on the aggregated information using a generative model, means for distributing the generated summary to multiple information processing terminals, means for analyzing emotions in the received information, and means for generating a summary using the results of the emotion analysis. This facilitates information sharing between users who speak different languages ​​and enables decision-making that takes emotional information into consideration.

[1481] Okay, now let's create definitions for each of the important words included in the rewritten claims.

[1482] "Different languages" refers to multiple natural languages ​​used as means of communication in different regions and cultures.

[1483] "Means for receiving" refers to devices or software that have the function of acquiring data sent from users and importing it into a server.

[1484] "Translation means" refers to a system or software, such as a translation API, that converts input information into another language.

[1485] "Other information processing terminals" refers to devices used by users, such as computers, smartphones, and tablets.

[1486] "Delivery means" refers to devices or software that have the functionality to allow the server to deliver translated information or summaries to other information processing terminals.

[1487] "Added information" refers to new opinions or data provided by the user in response to the received translation information.

[1488] "Aggregation means" refers to a system for organizing and integrating information received from multiple users into a single data set.

[1489] A "generative model" refers to an artificial intelligence algorithm that analyzes given data and generates summaries or new data.

[1490] A "means for generating a summary" refers to a device or software that uses a generative model to extract key points from aggregated information and summarize them in a concise form.

[1491] "Means for analyzing emotions" refers to an emotion recognition engine or software for identifying a user's emotional state from received information.

[1492] "Means for generating summaries using the results of emotion analysis" refers to a system that takes into account the results of emotion analysis and has the function of reflecting emotional information in the generated summary.

[1493] Understood. Now, let's write the "Form for carrying out the invention."

[1494] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[1495] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[1496] 1. Server

[1497] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[1498] Information reception function

[1499] The server receives issues and opinions submitted by users. This information can be entered in different languages. The server uses the HTTP / HTTPS protocol to receive the information.

[1500] Translation feature

[1501] The server works with a translation API (e.g., Google Translate API) to translate the received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[1502] Information distribution function

[1503] The server then distributes the translated information to other users, potentially using real-time communication technologies (e.g., WebSockets) so that the same content can be understood by users who speak different languages.

[1504] Emotion recognition function

[1505] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion of the received information, for example, recognizing positive, negative, and neutral emotions.

[1506] Emotional information distribution function

[1507] The server distributes the recognized emotion information to other users, allowing them to understand the emotional state of other users.

[1508] Information aggregation function

[1509] The server collects the received information again after translation and emotion recognition and aggregates it into a single data set. This aggregation process uses a database to properly organize and store the information.

[1510] Summary generation function

[1511] The server uses generative AI (e.g., OpenAI's GPT-3) to create a summary from the aggregated information, which is a short, concise summary that extracts the key points.

[1512] Emotional summary generation function

[1513] The server reflects the user's emotional information in the generated summary, so that the summary is provided in a form that includes emotional elements.

[1514] Summary delivery function

[1515] The server distributes the generated summaries to all relevant users and decision makers via email, push notifications, and other methods.

[1516] 2. User Device

[1517] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[1518] Information input function

[1519] The terminal allows users to input their assignments and opinions in text format and send them to a server using a dedicated application or web interface.

[1520] Information display function

[1521] The terminal provides the functionality to display translation information, summaries, and emotional information delivered from the server, sometimes using real-time update technology (e.g., AJAX).

[1522] 3. Users

[1523] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[1524] Enter information

[1525] Users input and submit their opinions and issues through the terminal. For example, User A in Japan inputs and submits "opinions about the marketing strategy for a new product" in Japanese.

[1526] Information evaluation and addition

[1527] Users receive translated information and sentiment information from other users and add their own opinions. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[1528] Summary review and decision support

[1529] The decision maker reviews the generated summary and sentiment information and makes a decision based on it.

[1530] Specific examples

[1531] Specific usage examples are shown below.

[1532] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[1533] The terminal sends this information to the server.

[1534] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[1535] The server uses IBM Watson's emotion analysis API to recognize negative emotions from User A's information.

[1536] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[1537] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[1538] The server aggregates all the information and generates a summary using OpenAI's GPT-3, which also incorporates sentiment information.

[1539] The generated summary is distributed to all users and decision makers.

[1540] The decision maker reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[1541] In this way, this system facilitates information sharing between users with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[1542] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1543] Processing Steps

[1544] Step 1: Enter your information

[1545] Users use their devices to input their opinions and issues in text format. For example, User A inputs "Opinions about the marketing strategy for a new product" in Japanese and clicks the send button.

[1546] Input: User opinions and issues (text data)

[1547] Output: Text data entered into the terminal

[1548] Step 2: Submit your information

[1549] The terminal sends the input information to the server. At this time, the data is encrypted before being sent, ensuring security.

[1550] Input: Text data entered by the user

[1551] Output: Encrypted data to the server based on the HTTPS protocol

[1552] Step 3: Receiving information

[1553] The server receives the information sent from the device, at which point it is stored in a database.

[1554] Input: Encrypted data sent from the device

[1555] Output: Decoded text data (user opinions and issues)

[1556] Step 4: Translate the information

[1557] The server passes the received information to a translation means (e.g., Google Translate API) to translate it into other languages. For example, user A's Japanese opinion is translated into English, Chinese, and Spanish.

[1558] Input: Decrypted text data

[1559] Output: Translated text data (multiple languages)

[1560] Step 5: Emotion Recognition

[1561] The server passes the translated information to an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion. For example, it recognizes negative emotions from User A's opinion.

[1562] Input: Translated text data

[1563] Output: Sentiment analysis results (positive, negative, neutral, etc.)

[1564] Step 6: Delivering translation and emotion information

[1565] The server distributes the translated information and emotion information to the terminals of other users.

[1566] Input: translated text data, sentiment analysis results

[1567] Output: Data delivered to user device (text and emotional information)

[1568] Step 7: Evaluate and add information

[1569] The user can then check the translation and emotion information delivered to their device and add their own opinion. For example, User B can type "This is a good idea" in English and resubmit.

[1570] Input: Delivered text data and emotional information

[1571] Output: Added opinions (text data)

[1572] Step 8: Submit additional information

[1573] The terminal transmits the added information to the server again.

[1574] Input: Added opinion (text data)

[1575] Output: Encrypted data to the server based on the HTTPS protocol

[1576] Step 9: Aggregating information

[1577] The server receives the added information and stores and aggregates all user submitted information in a database, filtering out duplicate and irrelevant information.

[1578] Input: Additional comments from users (text data)

[1579] Output: Aggregated text dataset

[1580] Step 10: Summary generation

[1581] The server passes the aggregated information to a generative AI (e.g., OpenAI's GPT-3) to generate a summary, which extracts the key points and summarizes them in a short, concise manner.

[1582] Input: Aggregated text dataset

[1583] Output: Generated summary (text data)

[1584] Step 11: Emotion-reflecting summary generation

[1585] The server reflects the user's emotional information in the generated summary, thereby providing the summary in a form that includes emotional information.

[1586] Input: Generated summary, sentiment analysis results

[1587] Output: Summary (text data) reflecting emotional information

[1588] Step 12: Deliver the summary

[1589] The server distributes the generated summaries to all users and decision makers via email, push notifications, and other methods.

[1590] Input: A summary that reflects emotional information

[1591] Output: Data delivered to users and decision makers (text data)

[1592] In this way, the system realizes a series of processes: sharing users' opinions and issues in multiple languages, generating summaries taking into account emotional information, and providing information that contributes to decision-making.

[1593] (Application example 2)

[1594] 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."

[1595] In modern logistics centers, it is common for employees with different languages ​​and cultures to work together. However, if information is not shared smoothly across multiple languages, there is a risk of reduced productivity and mistakes due to misunderstandings. Furthermore, if the psychological state and emotions of employees are not understood, it can be difficult to improve the working environment and make efficient decisions. A system that can solve these issues is needed.

[1596] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, and means for receiving information added by multiple users based on the translated information and emotion information. This enables efficient information sharing across multiple languages ​​and appropriate management based on employee emotion information.

[1597] Okay, so let's create definitions for the important words included in the patent claims according to the application example.

[1598] "Information entered in different languages" refers to text data such as opinions and feedback entered by multiple users who use different languages.

[1599] A "translation API" is an application programming interface for automatically translating text between different languages.

[1600] An "emotion recognition engine" is software for analyzing and identifying a user's emotional state from text data.

[1601] "Generative AI" is an artificial intelligence technology that generates summaries and organizes information based on multiple collected text data.

[1602] "User Terminal" means an electronic device connected to the System that allows a User to input and receive information. Examples include smartphones, tablets, and PCs.

[1603] The "information receiving means" is a function that receives information sent from a user terminal and imports it into the server.

[1604] The "information distribution means" is a function that transmits information collected in the server to an appropriate user terminal.

[1605] The "information aggregation means" is a function that aggregates information received from multiple users into one piece of data.

[1606] "Summary generation means" is a function that uses generative AI to extract key points from aggregated information and create a concise summary.

[1607] The "emotion information distribution means" is a function that distributes analyzed emotion information to other users and the administrator.

[1608] A "manager" is someone whose job is to oversee the entire system and make decisions based on employee behavior and sentiment information.

[1609] "Multilingual support" refers to the ability to support multiple different languages ​​and enable smooth communication between these languages.

[1610] The above definitions clearly indicate the meaning of important terms contained in the claims.

[1611] This invention combines a multilingual issue aggregation system with an emotion recognition engine for use in logistics centers where employees with different languages ​​and cultures work together. The system efficiently translates information entered in different languages, shares it among employees, consolidates the information, and generates summaries. It also analyzes each employee's emotional information, allowing managers to respond appropriately.

[1612] 1. Server

[1613] The server is the core of this system and has the following functions:

[1614] Information receiving means: receives information in different languages ​​sent from the user terminal. This information is input in different languages, such as Japanese, English, Spanish, etc.

[1615] Translation method: Using a translation API, the received information is translated into another language. For example, information entered by a user in Japanese is translated into English or Chinese.

[1616] Information distribution means: Translated information is distributed to each user's device, allowing users who speak different languages ​​to understand the information.

[1617] Emotion recognition means: An emotion recognition engine is used to analyze the user's emotions from the received information. The analysis results include positive, negative, neutral, etc.

[1618] Information aggregation method: Aggregate information after translation and emotion recognition and compile the whole into a single data set.

[1619] Summary generator: A generative AI model is used to generate a summary from the aggregated information, which extracts key points and summarizes them succinctly.

[1620] Emotional information distribution method: Emotional information is reflected in the generated summary and distributed to all parties involved.

[1621] 2. User Device

[1622] User terminals are devices that employees use to input and receive information, including smart glasses, smartphones, and tablets.

[1623] Information input means: Provides a means for users to input their opinions and issues in text format and send them to the server.

[1624] Information display means: Provides a means to display translation information, summaries, and emotional information delivered from the server.

[1625] 3. Users

[1626] Users are employees and administrators who use the system, and it is assumed that they have different languages ​​and cultures.

[1627] Information input: Users input their opinions and issues through the terminal and send them. For example, a Japanese user inputs and sends a "proposal for improving the packaging of a new product" in Japanese.

[1628] Information evaluation and addition: Receive translated information and sentiment information from other users, add your own opinion to it, and resubmit it. For example, an English-speaking user may send feedback such as "This is a good idea."

[1629] Reviewing the summary and making decisions: The manager reviews the generated summary and sentiment information and makes decisions based on it, for example, setting up a meeting to decide on a new marketing strategy.

[1630] Specific examples

[1631] For example, in a discussion about packaging methods at a logistics center, opinions entered in different languages ​​can be translated, sentiment analyzed, and a summary generated based on the results. Using this system, employee A can enter "I propose a new packaging method" in Japanese, which is translated into English and perceived by the manager as "positive feedback." Employee B can also enter "I think this new packaging is great" in English, which is translated into Japanese and recognized as "positive" through sentiment analysis.

[1632] An example of a prompt is:

[1633] plaintext

[1634] "Translate comments entered in different languages ​​about a discussion about packaging methods at a distribution center, perform sentiment analysis, and generate summaries based on that."

[1635] is input into the generative AI model.

[1636] By using this system, it becomes possible to efficiently share information across multiple languages ​​and to appropriately manage employees based on their emotional state.

[1637] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1638] (Processing flow)

[1639] Step 1:

[1640] This is the stage where the user terminal receives information. The user enters text information in their own language and sends this information to the server via the terminal. The entered text information is sent to the server in its original format. For example, Japanese user A enters "I would like to propose a new packaging method" and clicks the send button. This entered text is sent to the server, and the server receives this information.

[1641] Step 2:

[1642] The server passes the received information to a translation API, which translates it into multiple languages. In this case, translation is from Japanese to English, Chinese, etc. The translation API analyzes the received text information and converts it into the specified target language. For example, it translates "I propose a new packaging method." into "I propose a new packaging method." The translation result is returned to the server.

[1643] Step 3:

[1644] The server uses the translated information to pass the data to an emotion recognition engine for sentiment analysis. The emotion recognition engine identifies the user's emotional state based on the received text data and returns the result to the server. For example, the text "I propose a new packaging method." is recognized as "positive."

[1645] Step 4:

[1646] The server delivers the translation results and sentiment information to the user's device, where it can be displayed and confirmed by other users. For example, English-speaking user B receives the message "I propose a new packaging method." and confirms the positive feedback.

[1647] Step 5:

[1648] Other users receive the information and add their own opinions. This information is then sent back to the server, where it is further analyzed. For example, user B adds his opinion, "This is a great idea," and sends it back. The server receives the information again and performs translation and sentiment analysis.

[1649] Step 6:

[1650] The server passes the aggregated information to a generative AI model, which then generates an overall summary. The generative AI model analyzes various text data, extracts key points, and generates a summary. For example, it creates a summary such as "The new packaging method has received positive reviews" based on multiple opinions and feedback.

[1651] Step 7:

[1652] The server distributes the generated summary and sentiment information to the administrator and other interested parties. The administrator can make decisions based on the summary. For example, the administrator can decide whether to adopt a new packaging method after viewing the summary and sentiment information.

[1653] The above is a detailed description of the steps involved in implementing the present invention, which enables efficient information sharing across multiple languages ​​and appropriate management based on employee emotional information.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] [Fourth embodiment]

[1658] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1659] 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.

[1660] 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).

[1661] 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.

[1662] 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.

[1663] 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).

[1664] 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.

[1665] 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.

[1666] 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.

[1667] 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.

[1668] 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.

[1669] 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.

[1670] 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."

[1671] Okay, so let's create a "Description of the Invention" based on the claims. We won't list the processing steps here because we'll ask about them later.

[1672] ---

[1673] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary.

[1674] The whole system mainly consists of a server, a user terminal, and the user itself. The roles and functions of each are explained in detail below.

[1675] 1. Server

[1676] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[1677] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[1678] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[1679] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[1680] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[1681] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[1682] Summary distribution function: The generated summary is distributed to all relevant users and management.

[1683] 2. User Device

[1684] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[1685] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[1686] Information display function: Provides the function to display translation information and summaries delivered from the server.

[1687] 3. Users

[1688] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[1689] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[1690] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[1691] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[1692] Specific examples

[1693] Specific usage examples are shown below.

[1694] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[1695] The terminal sends this information to the server.

[1696] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[1697] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[1698] Each user can view the translated information, add their own comments and resubmit it.

[1699] The server aggregates all the information and generates a summary using generative AI.

[1700] The generated summary is distributed to all users and management.

[1701] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[1702] In this way, the use of this system makes it easier to share information among employees with different languages ​​and cultures, and makes it easier to explain and persuade management about issues.

[1703] ---

[1704] The above is a detailed explanation of the "Form for implementing the invention."

[1705] The processing flow will be explained below.

[1706] I understand. Now, I will explain the program's processing flow in detail in the following format.

[1707] ---

[1708] Step 1:

[1709] A user accesses the application through a terminal and logs in with their account.

[1710] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[1711] Step 2:

[1712] The terminal transmits the login information to the server.

[1713] Specific operation: The terminal sends the authentication information entered by user A to the server.

[1714] Step 3:

[1715] The server validates the authentication information and starts a session if the login is successful.

[1716] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[1717] Step 4:

[1718] The user enters business issues and opinions into the application's input form.

[1719] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[1720] Step 5:

[1721] The terminal transmits the user's input information to the server.

[1722] Specific operation: The terminal sends the text data entered by user A to the server.

[1723] Step 6:

[1724] The server sends the received information to a translation API to translate it into other languages.

[1725] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[1726] Step 7:

[1727] The translation API returns the translation results to the server.

[1728] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[1729] Step 8:

[1730] The server distributes the translated information to other user terminals.

[1731] Specific operation: The server sends the translation results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[1732] Step 9:

[1733] The terminal displays the received translation information to the user.

[1734] Specific operation: The devices of users B, C, and D present the opinions displayed in their respective languages ​​to the users.

[1735] Step 10:

[1736] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[1737] Specific operation: User B inputs his opinion in English, and Chinese-speaking User C inputs his opinion in Chinese.

[1738] Step 11:

[1739] The terminal transmits the input information of the other users to the server.

[1740] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[1741] Step 12:

[1742] The server aggregates all the information and creates a summary using generative AI.

[1743] Specific operation: The server retrieves all user opinions from the database and generates a summary using generation AI.

[1744] Step 13:

[1745] The server distributes the generated summary to all users and management.

[1746] Specific operation: The server sends the multilingual summaries to all users and management's terminals.

[1747] Step 14:

[1748] Management reviews the summary through a terminal and decides on the necessary actions.

[1749] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[1750] ---

[1751] This concludes the detailed explanation of the program's processing flow.

[1752] Example 1

[1753] 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."

[1754] The aim is to solve the problem of difficulty in smooth communication and information sharing among employees with different languages ​​and cultures. In particular, there is a need to quickly and accurately translate information entered in different languages ​​and make efficient decisions based on that translation.

[1755] 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.

[1756] In this invention, the server includes means for receiving information entered in different languages, means for translating the information into other languages ​​using a translation API, means for distributing the translated information to other user terminals, means for receiving information added by multiple users, means for aggregating the received information and generating summaries using a generative AI model, means for distributing the generated summaries to multiple user terminals, means for displaying the translated information and summaries, and means for users who receive the summaries to add their opinions. This facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[1757] "Different languages" refers to multiple natural languages ​​spoken by users in different regions or cultures.

[1758] "Information" refers to data such as opinions, challenges, and feedback that users input or submit to the system.

[1759] "Receiving" refers to the server acquiring information sent from a user terminal.

[1760] "Translation API" refers to an application program interface used to translate text between different languages.

[1761] "Delivery" refers to the server sending the translated information and generated summaries to the user terminal.

[1762] "User terminal" refers to a device, such as a PC, smartphone, or tablet, that a user uses to input and receive information.

[1763] "Added information" refers to new opinions and feedback provided based on translated information from other users.

[1764] "Aggregation" refers to combining multiple pieces of received information into a single data set.

[1765] "Generative AI model" refers to an artificial intelligence model used to perform summarization or other processing on aggregated information.

[1766] A "summary" is a concise summary of the important points of aggregated information.

[1767] "Management" refers to the management layer responsible for decision-making in a company or organization.

[1768] This invention relates to a multilingual issue aggregation system that enables employees with different languages ​​and cultures to share information and make efficient decisions. The entire system is mainly composed of a server, user terminals, and users, each of which plays a specific role. The details of this system are described below.

[1769] server

[1770] The server is the core of this system and has the following main functions:

[1771] 1. Information reception function: The server receives information sent from the user terminal. Information is entered in text format. For example, User A in Japan enters and sends "opinions regarding the marketing strategy for a new product" in Japanese.

[1772] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[1773] 2. Translation function: The server analyzes the received information and translates it into other languages ​​using a translation API (e.g., Google Cloud Translation API). For example, information entered in Japanese can be translated into English, Chinese, or Spanish.

[1774] Example prompt: The server translates Japanese information into English, Chinese, and Spanish.

[1775] 3. Information distribution function: The translated information is distributed to other user terminals, for example, to English-speaking user B, Chinese-speaking user C, and Spanish-speaking user D.

[1776] Example prompt: Send translated information to User B, User C, and User D.

[1777] 4. Information aggregation function: The server receives and aggregates the opinions and feedback sent back by each user, forming an overall data set.

[1778] Example prompt: Collect information from all users and aggregate it into one dataset.

[1779] 5. Summary generation function: The server generates a summary based on the aggregated information using a generative AI model (e.g., OpenAI GPT-3). For example, the server inputs an instruction such as, "Please summarize the important points."

[1780] Example prompt: "Please summarize the key points" is input to the generation AI.

[1781] 6. Summary distribution function: The generated summary is distributed to all users and management, who can then make decisions based on it.

[1782] Example prompt: Send the generated summary to all users and management.

[1783] User terminal

[1784] A user terminal is a device that users use to input and receive information. It includes PCs, smartphones, tablets, etc. Each terminal has the following functions:

[1785] 1. Information input function: Users input their opinions and issues in text format and send them to the server. For example, User A writes his opinion in Japanese.

[1786] Example prompt: Enter "Your opinion on the marketing strategy for a new product" in Japanese and press the submit button.

[1787] 2. Information display function: The terminal displays the translated information and summary delivered from the server. For example, information translated into English is displayed on User B's terminal.

[1788] Example prompt: A Japanese comment is translated into English and displayed on User B's device.

[1789] User

[1790] Users are employees and administrators who use the system and have different languages ​​and cultures. Users have the following roles:

[1791] 1. Information input: Enter your opinions and assignments through the terminal and send them to the server.

[1792] Example prompt: User A enters "Your opinion on the marketing strategy for a new product" and presses the submit button.

[1793] 2. Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, User B adds his opinion in English, saying "This is a good idea," and submits it.

[1794] Example prompt: User B types "That's a good idea" in English and presses the send button.

[1795] 3. Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[1796] Example prompt: Management reviews the generated summary and decides on a new marketing strategy.

[1797] Specific examples

[1798] For example, User A in Japan enters his or her opinion on a new product's marketing strategy, and that information is translated into English, Chinese, and Spanish through the system. Users B, C, and D, who speak each language, receive that information and add their own opinions. The server then uses a generative AI model to generate a summary from the aggregated information, which is finally distributed to all users and management. This process facilitates information sharing among employees with different languages ​​and cultures, enabling fast and efficient decision-making.

[1799] In this way, this multilingual issue aggregation system effectively supports information sharing and decision-making among employees with different languages ​​and cultures.

[1800] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1801] I understand. Now, I will explain the program processing flow of this system in detail by dividing it into the following steps.

[1802] Program processing steps

[1803] Step 1: Enter your information

[1804] Subject: Terminal

[1805] Operation: A user uses a terminal to enter opinions or issues in text format into an information input form.

[1806] Input: User opinions and issues (e.g., "Opinions regarding marketing strategies for new products")

[1807] Output: Text data is sent from the terminal to the server.

[1808] Specific operation: User A enters "Opinion on marketing strategy for new product" and clicks the submit button.

[1809] Example prompt: "Your opinion on the marketing strategy for a new product" is entered into an information entry form.

[1810] Step 2: Receiving information

[1811] Subject: Server

[1812] Operation: The server receives the information sent from the terminal.

[1813] Input: Text data sent from the terminal

[1814] Output: Text data received by the server

[1815] Specific operation: Receive Japanese text data sent from the terminal to the server.

[1816] Example prompt: Receive text data for "Your opinion on the marketing strategy for a new product."

[1817] Step 3: Information Translation

[1818] Subject: Server

[1819] How it works: The server parses the information it receives and uses the translation API to translate it into different languages.

[1820] Input: Text data received by the server

[1821] Output: Translated text data (e.g., English, Chinese, Spanish)

[1822] Specific operation: The server translates Japanese information into English, Chinese, and Spanish.

[1823] Example prompt: Translate information submitted in Japanese into English, Chinese, and Spanish.

[1824] Step 4: Information distribution

[1825] Subject: Server

[1826] Operation: The server distributes the translated information to other user terminals.

[1827] Input: Translated text data

[1828] Output: Translated text data delivered to the user's device

[1829] Specific operation: The server sends the translated information to User B, User C, and User D.

[1830] Example prompt: Send translated information to User B, User C, and User D.

[1831] Step 5: Add information

[1832] Subject: User

[1833] What it does: Other users see the translated information, add their comments and resubmit.

[1834] Input: Translated information and user's additional comments

[1835] Output: Additional comments sent to the server

[1836] Specific action: User B adds an opinion in English saying "This is a good idea" and submits it.

[1837] Example prompt: "This is a good idea," add your opinion, and submit.

[1838] Step 6: Information aggregation

[1839] Subject: Server

[1840] How it works: The server collects the information returned by all users and aggregates it into a single data set.

[1841] Input: Additional comments submitted by multiple users

[1842] Output: Aggregated dataset

[1843] Specific operation: Collect information from all users and compile it into a single dataset.

[1844] Example prompt: Collect information from all users and aggregate it into one dataset.

[1845] Step 7: Summary generation

[1846] Subject: Server

[1847] How it works: The server generates a summary based on the aggregated information using a generative AI model.

[1848] Input: Aggregated dataset

[1849] Output: Generated summary

[1850] Specific operation: The generative AI model is given the prompt "Please summarize the key points in a summary" and a summary is generated.

[1851] Example prompt: "Please summarize the key points" is input to the generation AI.

[1852] Step 8: Summary Delivery

[1853] Subject: Server

[1854] Operation: The server distributes the generated summary to all users and management.

[1855] Input: Generated summary

[1856] Output: A summary is delivered to user terminals and management

[1857] Actions to be taken: Send a summary to all users and management for further decision-making.

[1858] Example prompt: Send the generated summary to all users and management.

[1859] This provides a detailed explanation of the processing procedures of the system's program, clarifying the inputs, outputs, and specific operations for each step.

[1860] (Application example 1)

[1861] 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."

[1862] In autonomous vehicle development projects, efficient information sharing and decision-making among researchers and engineers with different languages ​​and cultures is a challenge. Conventional methods require time and effort to support multiple languages ​​and consolidate and summarize information, which can cause delays and obstacles to the progress of the project.

[1863] 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.

[1864] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, means for distributing the translated information to other user terminals, means for receiving additional information from multiple users based on the translated information, means for aggregating the received information and generating a summary using a generation AI, means for distributing the generated summary to multiple user terminals, means for notifying management or administrators of the summary, and means for translating the information in real time to streamline information distribution and summary generation, thereby enabling efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[1865] The "means for receiving information entered in different languages" is a function that allows the server to receive data on issues and opinions entered by users in various languages.

[1866] "Means of translating into other languages ​​using a translation API" is a function that converts received information into other languages ​​in real time using an automatic translation service.

[1867] The "means for distributing translated information to other user terminals" is a function for transmitting translated data to other user devices.

[1868] The "means for receiving information added by multiple users based on translated information" is a function that allows the server to receive again the information added by each user based on the translated data.

[1869] "Means of aggregating received information and generating a summary using generative AI" refers to a function that brings together collected data and uses artificial intelligence to organize it into a summary format.

[1870] The "means for distributing the generated summary to a plurality of user terminals" is a function for transmitting the data of the generated summary to all user devices.

[1871] The "means of notifying the executives and managers of the summary" is a function for notifying the leaders and managers of the organization of the generated summary information.

[1872] "A means of translating information in real time and streamlining the distribution of information and the generation of summaries" is a function that translates input information on the spot, quickly shares that information, and creates summaries, thereby streamlining the entire process.

[1873] MODE FOR CARRYING OUT THE INVENTION

[1874] This invention relates to a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information. The system receives information entered in different languages, translates it, shares it among multiple users, and finally generates a summary. It is primarily designed for autonomous vehicle development projects.

[1875] 1. Server

[1876] The server is the central part of the system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[1877] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[1878] Translation function: Works with translation APIs to translate received information into other languages, for example, using Google Translate API or Microsoft Translator API.

[1879] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[1880] Information aggregation function: After translation, the received information is collected again and aggregated into a single data set.

[1881] Summary generation: Uses generative AI to create summaries from aggregated information, specifically using OpenAI's GPT-4 model.

[1882] Summary distribution function: The generated summary is distributed to all relevant users and management.

[1883] Notification function: Notify management and administrators of generated summaries and important information.

[1884] 2. User Device

[1885] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[1886] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[1887] Information display function: Provides the function to display translation information and summaries delivered from the server.

[1888] 3. Users

[1889] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[1890] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[1891] Information evaluation and addition: Receive translated information from other users and add your own opinion to it. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[1892] Summary review and decision support: Management and others review the generated summary and make decisions based on it.

[1893] Specific examples

[1894] Process Flow

[1895] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[1896] The terminal sends this information to the server.

[1897] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[1898] The translated information is distributed from the server to the terminals of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[1899] Each user can view the translated information, add their own comments and resubmit it.

[1900] The server aggregates all the information and generates a summary using OpenAI's GPT-4.

[1901] The generated summary is distributed to all users and management.

[1902] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[1903] Prompt Sentence Examples

[1904] Example prompts for generative AI models:

[1905] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[1906] In this way, the use of this system facilitates information sharing among employees with different languages ​​and cultures, thereby improving the efficiency of autonomous vehicle development projects and supporting decision-making.

[1907] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1908] Step 1:

[1909] The user inputs and sends information from the terminal. The user inputs the task or opinion in text format in their own language and clicks the send button. The input includes the text information entered by the user. This information is sent to the server and received by the server.

[1910] Step 2:

[1911] The server translates the received information into other languages ​​using a translation API. Specifically, the input information is translated into all required languages ​​using the Google Translate API, Microsoft Translator API, etc. The input is the information received in step 1, and the output is the translated text information. In this process, the API is called to perform the translation work in real time and obtain the results.

[1912] Step 3:

[1913] The server distributes the translated information to other user terminals. Specifically, it sends the translated information to each user's terminal. The input is the translated information, and the output is the user terminal that received the information. In this process, the server generates a distribution request to each terminal and sends it to ensure that the information arrives correctly.

[1914] Step 4:

[1915] The user receives the translated information and adds their own opinion. The user's device displays the translated information delivered from the server, and the user inputs a new opinion in text format based on it and sends it. The input is the delivered information, and the output is the added opinion information. In this process, the user edits the information, generates new data, and sends it to the server.

[1916] Step 5:

[1917] The server collects and aggregates the added information. All new information submitted by multiple users is compiled into a single dataset. The input is the added opinion information, and the output is the aggregated dataset. In this process, the server centrally manages all new data and organizes the aggregated data.

[1918] Step 6:

[1919] The server generates a summary using generative AI. A summary is created from the aggregated information using OpenAI's GPT-4 model. The input is the aggregated dataset, and the output is the generated summary. In this process, a prompt sentence is used to input summarization instructions to the AI ​​model, and the results are obtained.

[1920] Step 7:

[1921] The server distributes the generated summary to multiple user terminals and management. Specifically, it sends the generated summary data to all relevant user and manager terminals. The input is the generated summary, and the output is the user terminal that received the summary. In this process, the server uses a distribution list to deliver the summary to each terminal.

[1922] Step 8:

[1923] Management reviews the summary and uses it to inform decision-making. Management then takes specific actions and makes decisions based on the summarized information. The input is the delivered summary information, and the output is a decision. This process evaluates the received information and determines the next steps for the project based on the results.

[1924] For example, here's a prompt:

[1925] Summarize the following information: "Review of new sensor technology needed. Additional insights by team members."

[1926] This will enable efficient information sharing and rapid decision-making among researchers and engineers who speak different languages.

[1927] 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.

[1928] Okay, so let's create a "Description of the Invention" for the invention that combines the emotion engine based on the scope of the patent claims.

[1929] ---

[1930] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[1931] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[1932] 1. Server

[1933] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[1934] Information receiving function: Receives issues and opinions sent by users. This information is assumed to be entered in different languages.

[1935] Translation function: Works with the translation API to translate received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[1936] Information distribution function: Distributes translated information to other users, making the same content understandable to users who speak different languages.

[1937] Emotion Recognition: Using an emotion engine, the emotion of the received information is analyzed, for example, to recognize positive, negative, and neutral emotions.

[1938] Emotion information distribution function: Distributes recognized emotion information to other users.

[1939] Information aggregation function: After translation and emotion recognition, the received information is collected again and aggregated into a single data set.

[1940] Summary generation: Uses generative AI to create summaries from aggregated information, distilling key points into a short, concise summary.

[1941] Emotion-reflecting summary generation function: The generated summary reflects the user's emotional information.

[1942] Summary distribution function: The generated summary is distributed to all relevant users and management.

[1943] 2. User Device

[1944] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[1945] Information input function: Provides a function that allows users to input their issues and opinions in text format and send them to the server.

[1946] Information display function: Provides a function to display translation information, summaries, and emotional information delivered from the server.

[1947] 3. Users

[1948] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[1949] Information input: Users input their opinions and issues through the terminal and send them. For example, User A in Japan inputs and sends "opinions about the marketing strategy for a new product" in Japanese.

[1950] Information evaluation and addition: Receive translated information and sentiment information from other users and add your own opinion. For example, American user B sees the translated information and comments in English, saying, "This is a good idea."

[1951] Summary review and decision support: Management and others review the generated summary and sentiment information and make decisions based on it.

[1952] Specific examples

[1953] Specific usage examples are shown below.

[1954] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[1955] The terminal sends this information to the server.

[1956] The server uses a translation API to translate the information into English, Chinese, and Spanish.

[1957] The server uses an emotion engine to recognize negative emotions from the information of user A.

[1958] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[1959] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[1960] The server aggregates all the information and uses generative AI to generate a summary, which also takes into account emotional information.

[1961] The generated summary is distributed to all users and management.

[1962] Management reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[1963] In this way, this system facilitates information sharing among employees with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[1964] ---

[1965] The above is a detailed explanation of the "Form for implementing the invention."

[1966] The processing flow will be explained below.

[1967] Okay, so let me explain the process step by step.

[1968] ---

[1969] Step 1:

[1970] A user accesses the application through a terminal and logs in with their account.

[1971] Specific operation: User A opens the application on his / her PC, enters his / her username and password, and clicks the login button.

[1972] Step 2:

[1973] The terminal transmits the login information to the server.

[1974] Specific operation: The terminal sends the authentication information entered by user A to the server.

[1975] Step 3:

[1976] The server validates the authentication information and starts a session if the login is successful.

[1977] Specific operation: The server checks the information of user A in the database, and if authentication is successful, generates a session ID and returns it to the terminal.

[1978] Step 4:

[1979] The user enters business issues and opinions into the application's input form.

[1980] Specific actions: User A enters "Opinion on the marketing strategy for the new product" in Japanese and clicks the send button.

[1981] Step 5:

[1982] The terminal transmits the user's input information to the server.

[1983] Specific operation: The terminal sends the text data entered by user A to the server.

[1984] Step 6:

[1985] The server sends the received information to a translation API to translate it into other languages.

[1986] Specific operation: The server calls the translation API and translates User A's Japanese comment into English, Chinese, and Spanish.

[1987] Step 7:

[1988] The translation API returns the translation results to the server.

[1989] Specific operation: The translation API returns the translation results (text in English, Chinese, and Spanish) to the server.

[1990] Step 8:

[1991] The server sends the received information to an emotion engine to analyze the emotion.

[1992] Specific operation: The server calls the emotion engine and recognizes positive, negative, and neutral emotions from the input text of user A.

[1993] Step 9:

[1994] The emotion engine returns the emotion analysis results to the server.

[1995] Specific operation: The emotion engine returns the emotion analysis result (e.g., negative) to the server.

[1996] Step 10:

[1997] The server distributes the translated information and emotion analysis results to other user terminals.

[1998] Specific operation: The server sends the translation results and sentiment analysis results to the devices of the target users (e.g., English-speaking user B, Chinese-speaking user C, Spanish-speaking user D).

[1999] Step 11:

[2000] The terminal displays the received translation information and emotion information to the user.

[2001] Specific operation: The devices of users B, C, and D present the opinions and emotion information displayed in their respective languages ​​to the users.

[2002] Step 12:

[2003] Other users can input their own opinions or issues regarding the distributed information and retransmit it via their terminals.

[2004] Specific operation: User B inputs his / her opinion in English, and User C inputs his / her opinion in Chinese.

[2005] Step 13:

[2006] The terminal transmits the input information of the other users to the server.

[2007] Specific operation: The terminal sends the text data entered by user B and user C to the server.

[2008] Step 14:

[2009] The server aggregates all the information and creates a summary using generative AI.

[2010] Specific operation: The server retrieves the opinions and emotional information of all users from the database and uses the generation AI to generate a summary, which also reflects the emotional information.

[2011] Step 15:

[2012] The server distributes the generated summary to all users and management.

[2013] Specific operation: The server sends the generated multilingual summaries and sentiment information to all users and management's terminals.

[2014] Step 16:

[2015] Management reviews the summary through a terminal and decides on the necessary actions.

[2016] What happens: Management reads the summary on their devices and schedules a meeting to decide on a new marketing strategy.

[2017] ---

[2018] The above is a detailed explanation of the processing flow of a system that includes an emotion engine.

[2019] Example 2

[2020] 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."

[2021] Conventional information sharing systems have made it difficult for employees with different languages ​​and cultures to share information smoothly, which can hinder effective decision-making. Furthermore, they are unable to take into account users' emotional information, which can lead to important emotional factors being overlooked in decision-making. This invention solves these problems and realizes efficient information sharing and decision-making support that supports multiple languages ​​and takes into account emotional information.

[2022] 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.

[2023] In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation means, means for distributing the translated information to other information processing terminals, means for receiving information added to the distributed information from multiple users, means for aggregating the received information and the added information, means for generating a summary based on the aggregated information using a generative model, means for distributing the generated summary to multiple information processing terminals, means for analyzing emotions in the received information, and means for generating a summary using the results of the emotion analysis. This facilitates information sharing between users who speak different languages ​​and enables decision-making that takes emotional information into consideration.

[2024] Okay, now let's create definitions for each of the important words included in the rewritten claims.

[2025] "Different languages" refers to multiple natural languages ​​used as means of communication in different regions and cultures.

[2026] "Means for receiving" refers to devices or software that have the function of acquiring data sent from users and importing it into a server.

[2027] "Translation means" refers to a system or software, such as a translation API, that converts input information into another language.

[2028] "Other information processing terminals" refers to devices used by users, such as computers, smartphones, and tablets.

[2029] "Delivery means" refers to devices or software that have the functionality to allow the server to deliver translated information or summaries to other information processing terminals.

[2030] "Added information" refers to new opinions or data provided by the user in response to the received translation information.

[2031] "Aggregation means" refers to a system for organizing and integrating information received from multiple users into a single data set.

[2032] A "generative model" refers to an artificial intelligence algorithm that analyzes given data and generates summaries or new data.

[2033] A "means for generating a summary" refers to a device or software that uses a generative model to extract key points from aggregated information and summarize them in a concise form.

[2034] "Means for analyzing emotions" refers to an emotion recognition engine or software for identifying a user's emotional state from received information.

[2035] "Means for generating summaries using the results of emotion analysis" refers to a system that takes into account the results of emotion analysis and has the function of reflecting emotional information in the generated summary.

[2036] Understood. Now, let's write the "Form for carrying out the invention."

[2037] This invention combines a multilingual task aggregation system that allows employees with different languages ​​and cultures to collaborate and train AI on information, with an emotion engine that recognizes user emotions. This system receives information entered in different languages, translates it, shares it among multiple users, and ultimately generates a summary. Furthermore, the emotion engine is used to analyze user emotions, and the results are utilized throughout the system.

[2038] The entire system consists of a server, a user terminal, and the user itself, and has the following functions:

[2039] 1. Server

[2040] The server is the core of this system, receiving information from multiple users and processing it appropriately. Specifically, it has the following functions:

[2041] Information reception function

[2042] The server receives issues and opinions submitted by users. This information can be entered in different languages. The server uses the HTTP / HTTPS protocol to receive the information.

[2043] Translation feature

[2044] The server works with a translation API (e.g., Google Translate API) to translate the received information into other languages. For example, information entered by a user in Japanese can be translated into English, Chinese, and Spanish.

[2045] Information distribution function

[2046] The server then distributes the translated information to other users, potentially using real-time communication technologies (e.g., WebSockets) so that the same content can be understood by users who speak different languages.

[2047] Emotion recognition function

[2048] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion of the received information, for example, recognizing positive, negative, and neutral emotions.

[2049] Emotional information distribution function

[2050] The server distributes the recognized emotion information to other users, allowing them to understand the emotional state of other users.

[2051] Information aggregation function

[2052] The server collects the received information again after translation and emotion recognition and aggregates it into a single data set. This aggregation process uses a database to properly organize and store the information.

[2053] Summary generation function

[2054] The server uses generative AI (e.g., OpenAI's GPT-3) to create a summary from the aggregated information, which is a short, concise summary that extracts the key points.

[2055] Emotional summary generation function

[2056] The server reflects the user's emotional information in the generated summary, so that the summary is provided in a form that includes emotional elements.

[2057] Summary delivery function

[2058] The server distributes the generated summaries to all relevant users and decision makers via email, push notifications, and other methods.

[2059] 2. User Device

[2060] A user terminal is a device that allows a user to input and receive information. It includes PCs, smartphones, tablets, etc.

[2061] Information input function

[2062] The terminal allows users to input their assignments and opinions in text format and send them to a server using a dedicated application or web interface.

[2063] Information display function

[2064] The terminal provides the functionality to display translation information, summaries, and emotional information delivered from the server, sometimes using real-time update technology (e.g., AJAX).

[2065] 3. Users

[2066] Users are employees and administrators who use the system, and are assumed to have different languages ​​and cultures.

[2067] Enter information

[2068] Users input and submit their opinions and issues through the terminal. For example, User A in Japan inputs and submits "opinions about the marketing strategy for a new product" in Japanese.

[2069] Information evaluation and addition

[2070] Users receive translated information and sentiment information from other users and add their own opinions. For example, American user B sees the translated information and types and submits "This is a good idea" in English.

[2071] Summary review and decision support

[2072] The decision maker reviews the generated summary and sentiment information and makes a decision based on it.

[2073] Specific examples

[2074] Specific usage examples are shown below.

[2075] User A (Japanese speaking) enters "Opinion on marketing strategy for new product" in Japanese and clicks the submit button.

[2076] The terminal sends this information to the server.

[2077] The server uses the Google Translate API to translate the information into English, Chinese, and Spanish.

[2078] The server uses IBM Watson's emotion analysis API to recognize negative emotions from User A's information.

[2079] The translated information and emotion information are delivered from the server to the devices of User B (English speaking), User C (Chinese speaking), and User D (Spanish speaking).

[2080] Each user can view the translated information and sentiment information, add their own opinions and resubmit.

[2081] The server aggregates all the information and generates a summary using OpenAI's GPT-3, which also incorporates sentiment information.

[2082] The generated summary is distributed to all users and decision makers.

[2083] The decision maker reviews the summary, schedules a meeting, and decides on a new marketing strategy.

[2084] In this way, this system facilitates information sharing between users with different languages ​​and cultures, and enables decision-making that takes emotional information into account.

[2085] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2086] Processing Steps

[2087] Step 1: Enter your information

[2088] Users use their devices to input their opinions and issues in text format. For example, User A inputs "Opinions about the marketing strategy for a new product" in Japanese and clicks the send button.

[2089] Input: User opinions and issues (text data)

[2090] Output: Text data entered into the terminal

[2091] Step 2: Submit your information

[2092] The terminal sends the input information to the server. At this time, the data is encrypted before being sent, ensuring security.

[2093] Input: Text data entered by the user

[2094] Output: Encrypted data to the server based on the HTTPS protocol

[2095] Step 3: Receiving information

[2096] The server receives the information sent from the device, at which point it is stored in a database.

[2097] Input: Encrypted data sent from the device

[2098] Output: Decoded text data (user opinions and issues)

[2099] Step 4: Translate the information

[2100] The server passes the received information to a translation means (e.g., Google Translate API) to translate it into other languages. For example, user A's Japanese opinion is translated into English, Chinese, and Spanish.

[2101] Input: Decrypted text data

[2102] Output: Translated text data (multiple languages)

[2103] Step 5: Emotion Recognition

[2104] The server passes the translated information to an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the emotion. For example, it recognizes negative emotions from User A's opinion.

[2105] Input: Translated text data

[2106] Output: Sentiment analysis results (positive, negative, neutral, etc.)

[2107] Step 6: Delivering translation and emotion information

[2108] The server distributes the translated information and emotion information to the terminals of other users.

[2109] Input: translated text data, sentiment analysis results

[2110] Output: Data delivered to user device (text and emotional information)

[2111] Step 7: Evaluate and add information

[2112] The user can then check the translation and emotion information delivered to their device and add their own opinion. For example, User B can type "This is a good idea" in English and resubmit.

[2113] Input: Delivered text data and emotional information

[2114] Output: Added opinions (text data)

[2115] Step 8: Submit additional information

[2116] The terminal transmits the added information to the server again.

[2117] Input: Added opinion (text data)

[2118] Output: Encrypted data to the server based on the HTTPS protocol

[2119] Step 9: Aggregating information

[2120] The server receives the added information and stores and aggregates all user submitted information in a database, filtering out duplicate and irrelevant information.

[2121] Input: Additional comments from users (text data)

[2122] Output: Aggregated text dataset

[2123] Step 10: Summary generation

[2124] The server passes the aggregated information to a generative AI (e.g., OpenAI's GPT-3) to generate a summary, which extracts the key points and summarizes them in a short, concise manner.

[2125] Input: Aggregated text dataset

[2126] Output: Generated summary (text data)

[2127] Step 11: Emotion-reflecting summary generation

[2128] The server reflects the user's emotional information in the generated summary, thereby providing the summary in a form that includes emotional information.

[2129] Input: Generated summary, sentiment analysis results

[2130] Output: Summary (text data) reflecting emotional information

[2131] Step 12: Deliver the summary

[2132] The server distributes the generated summaries to all users and decision makers via email, push notifications, and other methods.

[2133] Input: A summary that reflects emotional information

[2134] Output: Data delivered to users and decision makers (text data)

[2135] In this way, the system realizes a series of processes: sharing users' opinions and issues in multiple languages, generating summaries taking into account emotional information, and providing information that contributes to decision-making.

[2136] (Application example 2)

[2137] 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."

[2138] In modern logistics centers, it is common for employees with different languages ​​and cultures to work together. However, if information is not shared smoothly across multiple languages, there is a risk of reduced productivity and mistakes due to misunderstandings. Furthermore, if the psychological state and emotions of employees are not understood, it can be difficult to improve the working environment and make efficient decisions. A system that can solve these issues is needed.

[2139] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information input in different languages, means for translating the received information into another language using a translation API, and means for receiving information added by multiple users based on the translated information and emotion information. This enables efficient information sharing across multiple languages ​​and appropriate management based on employee emotion information.

[2140] Okay, so let's create definitions for the important words included in the patent claims according to the application example.

[2141] "Information entered in different languages" refers to text data such as opinions and feedback entered by multiple users who use different languages.

[2142] A "translation API" is an application programming interface for automatically translating text between different languages.

[2143] An "emotion recognition engine" is software for analyzing and identifying a user's emotional state from text data.

[2144] "Generative AI" is an artificial intelligence technology that generates summaries and organizes information based on multiple collected text data.

[2145] "User Terminal" means an electronic device connected to the System that allows a User to input and receive information. Examples include smartphones, tablets, and PCs.

[2146] The "information receiving means" is a function that receives information sent from a user terminal and imports it into the server.

[2147] The "information distribution means" is a function that transmits information collected in the server to an appropriate user terminal.

[2148] The "information aggregation means" is a function that aggregates information received from multiple users into one piece of data.

[2149] "Summary generation means" is a function that uses generative AI to extract key points from aggregated information and create a concise summary.

[2150] The "emotion information distribution means" is a function that distributes analyzed emotion information to other users and the administrator.

[2151] A "manager" is someone whose job is to oversee the entire system and make decisions based on employee behavior and sentiment information.

[2152] "Multilingual support" refers to the ability to support multiple different languages ​​and enable smooth communication between these languages.

[2153] The above definitions clearly indicate the meaning of important terms contained in the claims.

[2154] This invention combines a multilingual issue aggregation system with an emotion recognition engine for use in logistics centers where employees with different languages ​​and cultures work together. The system efficiently translates information entered in different languages, shares it among employees, consolidates the information, and generates summaries. It also analyzes each employee's emotional information, allowing managers to respond appropriately.

[2155] 1. Server

[2156] The server is the core of this system and has the following functions:

[2157] Information receiving means: receives information in different languages ​​sent from the user terminal. This information is input in different languages, such as Japanese, English, Spanish, etc.

[2158] Translation method: Using a translation API, the received information is translated into another language. For example, information entered by a user in Japanese is translated into English or Chinese.

[2159] Information distribution means: Translated information is distributed to each user's device, allowing users who speak different languages ​​to understand the information.

[2160] Emotion recognition means: An emotion recognition engine is used to analyze the user's emotions from the received information. The analysis results include positive, negative, neutral, etc.

[2161] Information aggregation method: Aggregate information after translation and emotion recognition and compile the whole into a single data set.

[2162] Summary generator: A generative AI model is used to generate a summary from the aggregated information, which extracts key points and summarizes them succinctly.

[2163] Emotional information distribution method: Emotional information is reflected in the generated summary and distributed to all parties involved.

[2164] 2. User Device

[2165] User terminals are devices that employees use to input and receive information, including smart glasses, smartphones, and tablets.

[2166] Information input means: Provides a means for users to input their opinions and issues in text format and send them to the server.

[2167] Information display means: Provides a means to display translation information, summaries, and emotional information delivered from the server.

[2168] 3. Users

[2169] Users are employees and administrators who use the system, and it is assumed that they have different languages ​​and cultures.

[2170] Information input: Users input their opinions and issues through the terminal and send them. For example, a Japanese user inputs and sends a "proposal for improving the packaging of a new product" in Japanese.

[2171] Information evaluation and addition: Receive translated information and sentiment information from other users, add your own opinion to it, and resubmit it. For example, an English-speaking user may send feedback such as "This is a good idea."

[2172] Reviewing the summary and making decisions: The manager reviews the generated summary and sentiment information and makes decisions based on it, for example, setting up a meeting to decide on a new marketing strategy.

[2173] Specific examples

[2174] For example, in a discussion about packaging methods at a logistics center, opinions entered in different languages ​​can be translated, sentiment analyzed, and a summary generated based on the results. Using this system, employee A can enter "I propose a new packaging method" in Japanese, which is translated into English and perceived by the manager as "positive feedback." Employee B can also enter "I think this new packaging is great" in English, which i...

Claims

1. means for receiving information entered in different languages; means for translating the received information into another language using a translation API; means for distributing the translated information to other user terminals; means for receiving additional information from a plurality of users based on the translated information; means for aggregating the received information and generating a summary using a generation AI; The system includes means for distributing the generated summary to a plurality of user terminals.

2. 10. The system of claim 1, further comprising means for management receiving said summary to make decisions based on said summary.

3. 2. The system of claim 1, wherein the translation API is multilingual and supports at least three or more different languages. --- By doing so, the core of the invention is clarified and the wording used to limit the scope of the claims is included.

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