System

Abstract

A system is provided.SOLUTION: A system, comprising: means for suggesting topics; means for generating questions; means for organizing opinions; means for setting directions of discussion; and means for managing time.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In traditional group discussions and workshops, a human facilitator is required to manage the direction of the discussion, manage time, and summarize opinions, which places a heavy burden on the facilitator. Furthermore, because the quality and efficiency of the discussion depend on the facilitator's skills, the quality and efficiency of the discussion can be inconsistent. To solve these issues, a system that utilizes AI to efficiently support discussions was needed. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of a discussion, and a means for managing time, thereby achieving the following effects in various discussions:

[0006] 1. The topic suggestion method generates related topics based on the theme entered by the user and displays them on the device. This provides appropriate topics at the beginning of the discussion, helping to ensure smooth progress.

[0007] 2. The question generation means displays questions generated based on the topic selected by the user on the terminal, thereby promoting deeper and more specific discussions.

[0008] 3. The method for summarizing opinions analyzes the comments entered during the discussion and displays the main points and summaries on the device. This allows you to summarize opinions efficiently without missing any important opinions or key points.

[0009] 4. The means for setting the direction of the discussion monitors the flow of the discussion and displays suggestions on the device along the pre-defined direction, preventing derailment and ensuring that the discussion moves consistently towards the goal.

[0010] 5. The time management method monitors the progress of the meeting and generates time alerts before the scheduled time and displays them on the terminal, thereby ensuring that the discussion proceeds efficiently within the time limit.

[0011] As described above, the present invention provides a system that can reduce the burden on the facilitator and improve the quality and efficiency of discussions.

[0012] The "means for suggesting topics" is a function that generates related topics based on a theme input by the user and displays them on the terminal.

[0013] The "means for generating questions" is a function that generates appropriate questions based on the topic selected by the user and displays them on the terminal.

[0014] "Means for summarizing opinions" is a function that analyzes the comments entered during a discussion, extracts the main points and summaries, and displays them on the device.

[0015] "Means for setting the direction of the discussion" is a function that monitors the flow of the discussion, makes suggestions in line with the pre-set direction, and displays them on the device.

[0016] "Time management means" is a function that monitors the progress of a meeting and generates a time alert before the scheduled time and displays it on the terminal. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The discussion facilitator AI of the present invention is a system that proposes topics, generates questions, summarizes opinions, sets the direction of the discussion, and manages time. Specific embodiments will be described below.

[0039] 1. Topic Suggestion

[0040] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific related topics. The server then returns the generated topic list to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server will generate related topics such as "market research," "prototype design," and "competitive analysis" and display them on the device.

[0041] 2. Question Generation

[0042] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[0043] 3. Summary of opinions

[0044] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[0045] 4. Setting the direction of the discussion

[0046] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[0047] 5. Time management

[0048] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[0049] With these functions, the discussion facilitator AI of the present invention supports efficient and smooth discussion progress, reduces the burden on the facilitator, and improves the quality and efficiency of discussions.

[0050] The processing flow will be explained below.

[0051] Topic Suggestion

[0052] 1. Step 1:

[0053] The user inputs the topic of the discussion into the terminal.

[0054] 2. Step 2:

[0055] The terminal transmits the input theme to the server.

[0056] 3. Step 3:

[0057] The server receives the theme and generates related topics using an AI model.

[0058] 4. Step 4:

[0059] The server transmits the generated topic list to the terminal.

[0060] 5. Step 5:

[0061] The terminal displays the topic candidates to the user.

[0062] Question Generation

[0063] 1. Step 1:

[0064] The user selects one of the topic candidates presented on the terminal.

[0065] 2. Step 2:

[0066] The terminal sends the selected topic to the server.

[0067] 3. Step 3:

[0068] The server receives the topic and generates related questions using an AI model.

[0069] 4. Step 4:

[0070] The server transmits the generated question list to the terminal.

[0071] 5. Step 5:

[0072] The terminal displays the generated question to the user.

[0073] Summary of opinions

[0074] 1. Step 1:

[0075] The user inputs the content of the discussion into the terminal.

[0076] 2. Step 2:

[0077] The terminal transmits the inputted speech content to the server.

[0078] 3. Step 3:

[0079] The server analyzes what is said and generates key points and summaries.

[0080] 4. Step 4:

[0081] The server sends the generated gist to the device.

[0082] 5. Step 5:

[0083] The device displays a summary of the key points to the user.

[0084] Setting the direction of the discussion

[0085] 1. Step 1:

[0086] The server monitors the progress of the discussion in real time.

[0087] 2. Step 2:

[0088] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[0089] 3. Step 3:

[0090] The server sends the generated proposal to the terminal.

[0091] 4. Step 4:

[0092] The device displays the suggestions to the user.

[0093] time management

[0094] 1. Step 1:

[0095] The user inputs the start time and scheduled time of the discussion into the terminal.

[0096] 2. Step 2:

[0097] The terminal transmits the input time information to the server.

[0098] 3. Step 3:

[0099] The server monitors the progress and elapsed time in real time.

[0100] 4. Step 4:

[0101] The server generates a time alert when the scheduled time is about to expire.

[0102] 5. Step 5:

[0103] The server sends the generated time alert to the terminal.

[0104] 6. Step 6:

[0105] The device displays a time alert to the user, informing them of the time remaining.

[0106] Through the above steps, the discussion facilitator AI of the present invention functions as a system that supports the efficient and smooth progress of discussions.

[0107] Example 1

[0108] 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."

[0109] With conventional discussion systems, it was difficult to efficiently manage the entire discussion, including proposing topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time. Furthermore, since the facilitator had to take on all of these tasks, it placed a heavy burden on them, and there was a risk that the quality and efficiency of the discussion would decline.

[0110] 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.

[0111] In this invention, the server includes means for receiving a theme input by a user and generating related topics, means for generating questions based on the topic selected by the user, means for summarizing comments made during the discussion, means for monitoring the progress of the discussion and suggesting a direction, and means for managing the time of the discussion, thereby enabling the discussion to proceed efficiently and smoothly.

[0112] The "topic entered by the user" is information that the user enters into the terminal as the subject or topic of the discussion.

[0113] The "means for generating relevant topics" refers to a method and apparatus that uses a generative AI model to create specific topics useful for discussion based on a theme entered by a user.

[0114] A "means for generating questions" is a method and apparatus that uses a generative AI model to create relevant questions based on a user-selected topic.

[0115] The "means for summarizing speech content" refers to a method and device for analyzing speech content entered by users during a discussion, extracting the main points and important matters, and summarizing them in a concise manner.

[0116] "Means for monitoring the progress of the discussion and suggesting the direction" refers to a method and device that constantly monitors the current state of the discussion and appropriately suggests the next step or new topic based on the set direction of the discussion.

[0117] The "means for managing the discussion time" refers to a method and device for monitoring the progress of a discussion in real time based on the start time and scheduled time set by the user, and generating appropriate time alerts to notify the user.

[0118] The discussion facilitator AI of the present invention is a system that supports the highly efficient and smooth progress of discussions. An embodiment of this system will be specifically described below.

[0119] 1. Receive a topic entered by the user and generate related topics

[0120] The user inputs a discussion topic (e.g., "new product development") into the device. The device then sends this topic to the server, which uses a generative AI model (e.g., OpenAI GPT-3) to analyze the topic and generate specific related topics (e.g., "market research," "prototype design," "competitive analysis").

[0121] 2. Generate questions based on user-selected topics

[0122] When a user selects one of the generated topics (e.g., "Target Market Analysis"), the device sends the selected topic to the server, which uses the generative AI model to generate questions related to the selected topic (e.g., "What are the major consumer groups?", "What is the market share by region?").

[0123] 3. Summarize what was said during the discussion

[0124] During a discussion, users input their comments into their device. The device then sends the comments to the server. The server uses a generative AI model to analyze the comments and extract key points and summaries. The device then displays the summarized points to the user (e.g., "Factors that determine target market: price, quality").

[0125] 4. Monitor the progress of the discussion and suggest direction.

[0126] The server monitors the progress of the discussion in real time and, if the discussion deviates from the set direction, suggests next steps or new topics (e.g., "Next steps to advance market research"). The server sends the suggestions to the device and displays them to the user.

[0127] 5. Manage the discussion time

[0128] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert (e.g., "10 minutes remaining") 10 minutes before the planned end time and sends it to the terminal. The terminal displays this time alert to the user.

[0129] Examples of specific examples and prompts

[0130] 1. Receive a topic entered by the user and generate related topics

[0131] User Input: "New Product Development"

[0132] Example prompt: "Please suggest some specific topics related to new product development."

[0133] 2. Generate questions based on user-selected topics

[0134] User Input: "Target Market Analysis"

[0135] Example prompt: "Generate questions related to target market analysis."

[0136] 3. Summarize what was said during the discussion

[0137] User Input: "Price and quality are key factors in determining the target market for a new product."

[0138] Example prompt: "Summarize the main points from this statement."

[0139] 4. Suggest a direction for the discussion

[0140] Surveillance Systems: "The discussion has gone off track"

[0141] Example prompt: "Please suggest next steps to further your market research."

[0142] 5. Manage the discussion time

[0143] User input: "Discussion start time: 10:00, scheduled duration: 60 minutes"

[0144] Example prompt: "Generate a notification 10 minutes before the time is up."

[0145] These embodiments enable the present invention to improve the efficiency and quality of discussions.

[0146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0147] Step 1:

[0148] Enter and submit your theme

[0149] The user inputs the topic of the discussion (e.g., "new product development") into the terminal. The input topic is sent from the terminal to the server. The input is the text data of the topic by the user, and the output is the transmission of the text data of the topic from the terminal to the server.

[0150] Step 2:

[0151] Theme analysis and topic generation

[0152] The server analyzes the received thematic text data using a generative AI model (e.g., OpenAI GPT-3) and generates related topics (e.g., "market research," "prototype design," and "competitive analysis"). The input is thematic text data, and the output is a list of generated topics. The server sends this list back to the device.

[0153] Step 3:

[0154] View topics

[0155] The terminal displays the list of topics received from the server to the user. The input is the topic list data from the server, and the output is the topic list displayed on the terminal screen.

[0156] Step 4:

[0157] Select a topic and post

[0158] The user selects one topic from the displayed list (e.g., "Target Market Analysis"), and the terminal sends the data to the server. The input is the topic data selected by the user, and the output is the transmission of the selected topic data from the terminal to the server.

[0159] Step 5:

[0160] Question Generation

[0161] The server analyzes the received topic data using a generative AI model and generates relevant questions (e.g., "What are the major consumer groups?", "What is the market share by region?"). The input is the selected topic data, and the output is a list of generated questions. The server sends this list back to the device.

[0162] Step 6:

[0163] Show Questions

[0164] The terminal displays the list of questions received from the server to the user. The input is the question list data from the server, and the output is the question list displayed on the terminal screen.

[0165] Step 7:

[0166] Enter and send your message

[0167] During a discussion, a user inputs a statement into a terminal. The input statement is sent from the terminal to the server. The input is text data of the statement made by the user, and the output is the transmission of the text data from the terminal to the server.

[0168] Step 8:

[0169] Analysis and summary of speech content

[0170] The server analyzes the received speech using a generative AI model to extract key points and summaries. The input is the speech text data, and the output is summarized speech point data. The server then returns this summary data to the terminal.

[0171] Step 9:

[0172] View Summary

[0173] The terminal displays the summarized data received from the server to the user. The input is the summarized data from the server, and the output is the summarized data displayed on the screen of the terminal.

[0174] Step 10:

[0175] Monitor the progress of the discussion

[0176] The server monitors the progress of the discussion in real time and suggests next steps or new topics if the discussion strays from the set direction. The input is the current discussion status data, and the output is the proposed next steps or topic data. The server sends this data to the terminal.

[0177] Step 11:

[0178] View Suggestions

[0179] The terminal displays the proposed data received from the server to the user. The input is the proposed data from the server, and the output is the proposed data displayed on the screen of the terminal.

[0180] Step 12:

[0181] Time Management Settings

[0182] The user inputs the start time and scheduled time of the discussion into the terminal. The input time information is sent from the terminal to the server. The input is the start time and scheduled time data set by the user, and the output is the transmission of time information from the terminal to the server.

[0183] Step 13:

[0184] Time Management Practices

[0185] The server monitors the progress of the discussion in real time based on the time information received, and generates a time alert when the scheduled end time approaches. The input is the start time and scheduled time data, and the output is the generated time alert data. The server sends this time alert to the terminal.

[0186] Step 14:

[0187] Displaying time alerts

[0188] The terminal displays the time alert received from the server to the user. The input is the time alert data from the server, and the output is the time alert displayed on the terminal screen.

[0189] These processing steps enable the discussion facilitator AI to conduct discussions efficiently and smoothly.

[0190] (Application example 1)

[0191] 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."

[0192] Conventional discussions place a heavy burden on the facilitator, requiring a great deal of effort to progress and manage the discussion. Furthermore, discussions often go off track and time management is inadequate, making it difficult to hold efficient, high-quality discussions. In particular, in factories, efficiency and precision are required in discussions about production processes, quality control, and solving technical problems, but achieving this has been difficult. The present invention aims to solve these problems and provide a system that supports efficient and smooth discussions.

[0193] 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.

[0194] In this invention, the server includes a means for generating specific topics related to the theme of the discussion, a means for generating questions related to the generated topics, and a means for analyzing comments made during the discussion in real time and presenting summaries, thereby smoothing the progress of the discussion, reducing the burden on the facilitator, and enabling efficient, high-quality discussions.

[0195] A "topic" is a specific theme or subject that is brought up in a discussion or debate.

[0196] A "question" is a specific question related to the topic of discussion that is posed to deepen the discussion.

[0197] "Opinions" are the thoughts and opinions expressed by participants during a discussion.

[0198] The "direction of the discussion" indicates the overall guidelines and way forward for the discussion.

[0199] "Time management" refers to monitoring the start time, progress, and planned end time of a discussion and making appropriate adjustments.

[0200] "Generated Topics" are lists of related topics that are automatically generated based on the topic of the discussion.

[0201] "Related Questions" are a set of automatically generated questions related to the selected topic.

[0202] "Speech content" refers to what participants said during the discussion.

[0203] A "summary" is a summary of the main points or important information extracted from what was said during the discussion.

[0204] "Real-time analysis" refers to processing and analyzing data instantly while the discussion is taking place.

[0205] "Appropriate next steps" are specific actions or topics that should be taken next in the discussion.

[0206] "Time Alert" is a time warning that occurs based on the scheduled time of the discussion.

[0207] This invention is a system that uses a discussion facilitator AI to facilitate smooth discussion progress and reduce the burden on the facilitator. Specific embodiments will be described below.

[0208] The system mainly consists of three main components: a server, a terminal, and a user.

[0209] Hardware and Software

[0210] Hardware:

[0211] tablet device

[0212] Smart Glasses

[0213] software:

[0214] Cloud AI services (e.g., Google Cloud AI and AWS AI services)

[0215] Real-time Data Management System

[0216] Program processing

[0217] Users input the topic of discussion using a tablet or smart glasses. This topic is sent to the server via the device. The server uses a cloud AI service to analyze the topic and generate specific related topics. The generated topic list is then displayed on the device and presented to the user.

[0218] When the user selects one of the displayed topics, the device sends the selected topic to the server, which then uses the cloud AI service to generate a related question and returns it to the device, where it is displayed and presented to the user.

[0219] During the discussion, users input their comments via their devices. The inputted comments are sent to the server in real time, where cloud AI analyzes them and extracts key points and summaries. These summaries are displayed on the device and presented to the user. The server also constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to prevent the discussion from going off track. This information is also displayed on the device and presented to the user.

[0220] Users input the start time and expected duration of the discussion into their terminal. This is also sent to the server, which monitors the progress of the discussion in real time. Before the scheduled end time, a time alert is generated and sent to the terminal to notify the remaining time.

[0221] Specific examples

[0222] For example, if the topic "new product development" is entered, the following topics and questions will be generated:

[0223] Example of a topic-generating prompt:

[0224] Generate topics related to the theme "New Product Development".

[0225] This generates topics such as "market research," "prototype design," and "competitive analysis."

[0226] Example of a question-generating prompt:

[0227] Generate questions related to the topic "Market Research".

[0228] This generates questions such as, "What are the major consumer groups?" and "What is the market share by region?"

[0229] In this way, this system supports the progress of discussions, reduces the burden on facilitators, and enables efficient, high-quality discussions.

[0230] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0231] Step 1:

[0232] The user inputs the topic of discussion into a tablet device or smart glasses.

[0233] The input theme is sent from the terminal to the server. At this time, the theme is sent to the server as input data.

[0234] Step 2:

[0235] The server uses cloud AI services to analyze the received themes and generate specific related topics.

[0236] The generated topic list is returned from the server to the terminal.

[0237] Here, data processing involves extracting related topics from the theme, and generating a topic list as the output.

[0238] Step 3:

[0239] The user selects one topic from the topic list displayed on the terminal.

[0240] The selected topic is again sent from the terminal to the server, this time as selection data.

[0241] Step 4:

[0242] The server uses a cloud AI service to generate questions related to the received topic.

[0243] The generated question list is returned from the server to the terminal.

[0244] Here, data processing involves generating related questions from topics, and generating a question list as the output.

[0245] Step 5:

[0246] During the discussion, the user inputs each statement into the terminal.

[0247] The inputted remarks are sent to the server in real time.

[0248] At this time, the content of the statement is sent to the server as input data.

[0249] Step 6:

[0250] The server uses cloud AI to analyze the received comments in real time and extract key points and summaries.

[0251] The extracted gist is returned from the server to the terminal.

[0252] Here, data processing involves analyzing the content of the comments and generating a summary, and the main points are generated as the output.

[0253] Step 7:

[0254] The server constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to keep the discussion from going off track.

[0255] The content of the proposal is transmitted from the server to the terminal.

[0256] Here, data calculations are performed to monitor progress and propose next steps, and the proposals are generated as output.

[0257] Step 8:

[0258] The user inputs the start time and scheduled time of the discussion into the terminal.

[0259] Based on this, the server monitors the progress of the discussion in real time.

[0260] A time alert is generated before the scheduled end time and sent to the terminal.

[0261] Here, data calculations involve time management and alert generation, and a time alert is generated as the output.

[0262] 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.

[0263] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time, as well as recognizing the user's emotions. Specific embodiments are described below.

[0264] 1. Topic Suggestion

[0265] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific topics related to it. The generated topic list is sent to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server generates related topics such as "market research," "prototype design," and "competitive analysis," and displays them on the device.

[0266] 2. Question Generation

[0267] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[0268] 3. Summary of opinions

[0269] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[0270] 4. Setting the direction of the discussion

[0271] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[0272] 5. Time management

[0273] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[0274] 6. Emotion Engine

[0275] The emotion engine has the ability to analyze the user's voice and text input and determine emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[0276] With these functions, the discussion facilitator AI system of the present invention not only supports efficient and smooth discussion progress, but also flexibly responds to the user's emotional state, reducing the burden on the facilitator and improving the quality and efficiency of discussions.

[0277] The processing flow will be explained below.

[0278] Topic Suggestion

[0279] 1. Step 1:

[0280] The user inputs the topic of the discussion into the terminal.

[0281] 2. Step 2:

[0282] The terminal transmits the input theme to the server.

[0283] 3. Step 3:

[0284] The server receives the theme and generates related topics using an AI model.

[0285] 4. Step 4:

[0286] The server transmits the generated topic list to the terminal.

[0287] 5. Step 5:

[0288] The terminal displays the topic candidates to the user.

[0289] Question Generation

[0290] 1. Step 1:

[0291] The user selects one of the topic candidates presented on the terminal.

[0292] 2. Step 2:

[0293] The terminal sends the selected topic to the server.

[0294] 3. Step 3:

[0295] The server receives the topic and generates related questions using an AI model.

[0296] 4. Step 4:

[0297] The server transmits the generated question list to the terminal.

[0298] 5. Step 5:

[0299] The terminal displays the generated question to the user.

[0300] Summary of opinions

[0301] 1. Step 1:

[0302] The user inputs the content of the discussion into the terminal.

[0303] 2. Step 2:

[0304] The terminal transmits the inputted speech content to the server.

[0305] 3. Step 3:

[0306] The server analyzes what is said and generates key points and summaries.

[0307] 4. Step 4:

[0308] The server sends the generated gist to the device.

[0309] 5. Step 5:

[0310] The device displays a summary of the key points to the user.

[0311] Setting the direction of the discussion

[0312] 1. Step 1:

[0313] The server monitors the progress of the discussion in real time.

[0314] 2. Step 2:

[0315] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[0316] 3. Step 3:

[0317] The server sends the generated proposal to the terminal.

[0318] 4. Step 4:

[0319] The device displays the suggestions to the user.

[0320] time management

[0321] 1. Step 1:

[0322] The user inputs the start time and scheduled time of the discussion into the terminal.

[0323] 2. Step 2:

[0324] The terminal transmits the input time information to the server.

[0325] 3. Step 3:

[0326] The server monitors the progress and elapsed time in real time.

[0327] 4. Step 4:

[0328] The server generates a time alert when the scheduled time is about to expire.

[0329] 5. Step 5:

[0330] The server sends the generated time alert to the terminal.

[0331] 6. Step 6:

[0332] The device displays a time alert to the user, informing them of the time remaining.

[0333] Use of emotion engine

[0334] 1. Step 1:

[0335] During the discussion, the user inputs what is being said into the terminal by voice or text.

[0336] 2. Step 2:

[0337] The device sends the input voice and text data to the server.

[0338] 3. Step 3:

[0339] The server's emotion engine analyzes voice and text data to determine the user's emotions.

[0340] 4. Step 4:

[0341] The server generates appropriate feedback and suggestions based on the emotions determined by the emotion engine.

[0342] 5. Step 5:

[0343] Send server-generated feedback and suggestions to the device.

[0344] 6. Step 6:

[0345] The device displays feedback and suggestions to the user. For example, if the user shows signs of frustration, the server provides advice on how to stay calm and displays it on the device.

[0346] Through the above steps, the discussion facilitator AI system of the present invention, which is combined with an emotion engine, functions as a system that supports the progress of discussions efficiently and with consideration for emotional aspects.

[0347] Example 2

[0348] 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."

[0349] In modern discussions, differences of opinion among participants, deviations in the direction of the discussion, and poor time management are often problems. Furthermore, it is difficult to grasp the emotional state of participants and respond appropriately accordingly. A system that can solve these issues and enable efficient and smooth discussions is needed.

[0350] 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.

[0351] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing the user's emotions. This allows for efficient and smooth progress of the discussion. It also enables flexible responses according to the user's emotions, improving the quality and efficiency of the discussion.

[0352] The "means for suggesting topics" is a function that generates related topics based on a theme input by the user and displays them on the terminal.

[0353] The "means for generating questions" is a function for generating related questions based on a topic selected by the user and displaying them on the terminal.

[0354] "Means for summarizing opinions" is a function that analyzes the comments entered by users during a discussion, extracts the main points and summaries, and displays them on the device.

[0355] "A means of setting the direction of the discussion" is a function that monitors the progress of the discussion and suggests next steps or new topics to prevent the discussion from going off track.

[0356] The "means for managing time" is a function for managing the start time and scheduled time of a discussion, and generating a time alert before the scheduled time and displaying it on the terminal.

[0357] The "means for recognizing user emotions" is a function that analyzes the user's voice and text input, determines their emotions, and responds accordingly.

[0358] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, time management, and recognizing the user's emotions. Specific embodiments of the system are described below.

[0359] Topic Suggestion

[0360] The user inputs a discussion topic into the device. For example, they might input "new product development." The device sends this topic to the server, which analyzes the topic using a generative AI model. Based on the analysis results, it generates specific related topics. The generated topic list is sent to the device, which presents it to the user. For example, generated topics might include "market research," "prototype design," and "competitive analysis."

[0361] Example prompt sentence:

[0362] "I'd like to hold a discussion about new product development. Please suggest specific topics that are relevant."

[0363] Question Generation

[0364] The user selects one of the presented topics. For example, they may select "target market analysis." The selected topic is sent from the device to the server. The server uses a generative AI model to generate questions related to the selected topic. The generated list of questions is sent to the device, which then presents them to the user. For example, generated questions include "What are the major consumer groups?" and "What is the market share by region?"

[0365] Example prompt sentence:

[0366] "Generate relevant questions to drive the discussion about your target market analysis."

[0367] Summary of opinions

[0368] As the discussion progresses, users input their comments into their devices. These comments are then sent from the devices to the server. The server then uses a generative AI model to analyze the comments and extract key points and summaries. The extracted summaries are then sent to the devices, which then display them to the user. For example, if someone says, "Price and quality are the key factors in determining the target market for a new product," the summary will be "Factors in determining the target market: price, quality."

[0369] Setting the direction of the discussion

[0370] The server monitors the progress of the discussion in real time. To prevent the discussion from going off track, it suggests next steps or new topics based on the set direction. The suggestions are sent to the device, which then displays them to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[0371] time management

[0372] The user enters the start time and planned duration of the discussion into the terminal. For example, the start time is 10:00 and the planned duration is 60 minutes. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. For example, a time alert such as "10 minutes remaining" is generated 10 minutes before the planned end time. The terminal displays this alert to the user to inform them of the remaining time.

[0373] Emotion Engine

[0374] The emotion engine is a function that analyzes the user's voice and text input and determines emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[0375] As a result, the discussion facilitator AI system can support efficient and smooth discussions and respond flexibly to the user's emotional state. It functions as a system that reduces the burden on the facilitator and improves the quality and efficiency of discussions.

[0376] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0377] Step 1:

[0378] The user inputs the topic of discussion into the terminal. For example, they input "new product development." The terminal receives this input as data and sends it to the server. The input data is in text format.

[0379] Step 2:

[0380] The server analyzes the received theme data. The server uses a generative AI model to analyze the input theme and generate specific topics related to the theme. The generated topic list is formed as data. The generative AI model extracts topics using natural language processing technology.

[0381] Step 3:

[0382] The server sends the generated topic list to the terminal. The terminal receives this topic list as data and displays it to the user. The user selects one of the presented topics. By selecting the topic, topic data is generated.

[0383] Step 4:

[0384] The selected topic data is sent from the device to the server. The server then uses the generative AI model to generate questions based on the received topic data. The generated list of questions is then formed into data. For example, questions such as "What are the main consumer groups?" are generated from "target market analysis."

[0385] Step 5:

[0386] The server sends the generated question list to the terminal, which displays the question list to the user. To advance the discussion, the user expresses their opinions and thoughts based on the questions and inputs them as text into the terminal.

[0387] Step 6:

[0388] The device sends the user's speech as data to the server, which then analyzes the received speech using a generative AI model. The analysis extracts key points and summaries. Text mining technology is used to process the data.

[0389] Step 7:

[0390] The server sends the extracted summary data to the terminal, which then displays the received summary to the user, allowing the user to grasp the progress of the discussion.

[0391] Step 8:

[0392] The server monitors the progress of the discussion in real time. If the discussion goes off track, the server uses a generative AI model to suggest next steps or new topics. The suggestions are generated as data and sent to the device.

[0393] Step 9:

[0394] The device displays the suggestions received from the server to the user, helping to guide the discussion in the right direction.

[0395] Step 10:

[0396] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this input data to the server. The server monitors the progress of the discussion based on the received time data.

[0397] Step 11:

[0398] The server generates time alert data when the scheduled time approaches and sends it to the terminal. For example, an alert saying "10 minutes remaining" is generated 10 minutes before the scheduled end time.

[0399] Step 12:

[0400] The device displays the received time alert data to the user, allowing the user to grasp the remaining time and make appropriate progress.

[0401] Step 13:

[0402] The emotion engine collects the user's voice and text input as data and sends it from the device to the server, which then analyzes the received emotion data and determines the user's emotion.

[0403] Step 14:

[0404] The server then adjusts the discussion and suggestions based on the emotion data it has determined. For example, if a user shows signs of fatigue, it suggests taking a break.

[0405] Step 15:

[0406] The server sends the adjusted proposal to the device, which displays it to the user, allowing the user to take appropriate action.

[0407] (Application example 2)

[0408] 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."

[0409] In modern manufacturing sites, discussions are frequently held to address a variety of issues, including process efficiency, quality improvement, and safety management. However, factors that significantly reduce the efficiency of discussions include distraction, poor time management, and emotional changes among participants. There is a growing need for a system that can adequately resolve these issues and support efficient discussions.

[0410] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0411] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing users' emotions and adjusting the progress of the discussion and the content of suggestions. This prevents discussions from going off track, ensures appropriate time management, and enables smooth discussion management in accordance with the emotions of participants.

[0412] "Topic suggestions" are a way to start a discussion by generating specific, related topics based on a theme entered by the user.

[0413] "Question generation" is a means for users to generate specific questions related to a topic they have selected and deepen the discussion.

[0414] A "summary" is a method of summarizing each statement made during a discussion and extracting and presenting the main points and summaries.

[0415] "Setting the direction of the discussion" is a way to constantly monitor the progress of the discussion and suggest next steps or new topics based on the set direction to prevent the discussion from going off track.

[0416] "Time management" is a means of managing the start time and scheduled time of a discussion and providing appropriate time alerts by monitoring the progress in real time.

[0417] "Emotion recognition" is a means of analyzing a user's voice and text input, determining the user's emotional state, and adjusting the discussion progress and proposal content accordingly.

[0418] This invention is a system for supporting discussions in manufacturing sites, which proposes topics, generates questions, summarizes opinions, sets the direction of discussions, manages time, and recognizes emotions through communication between servers, terminals, and users.

[0419] 1. Topic Suggestion

[0420] First, the user inputs the topic of the discussion through the device, which then sends it to the server, which then uses a generative AI model (e.g., OpenAI's GPT-3 or GPT-4) to analyze the topic and generate specific related topics based on it. The generated topics are then sent to the device and presented to the user.

[0421] Examples:

[0422] When a user inputs the topic "process improvement," the server generates topics such as "quality improvement," "cost reduction," and "safety management," and displays them on the terminal.

[0423] Example prompt sentence:

[0424] "Please suggest suitable topics for discussion based on the theme 'Process Improvement'."

[0425] 2. Question Generation

[0426] When a user operates their device to select one of the generated topics, that topic is sent to the server, which uses the generative AI model to generate a question related to that topic and returns it to the device, which then presents the question to the user.

[0427] Examples:

[0428] If the user selects "Improve Quality," the server generates questions such as "In which process are quality problems occurring?" and "How can existing quality control methods be improved?" and displays them on the terminal.

[0429] Example prompt sentence:

[0430] "Generate questions related to the topic 'Quality Improvement'."

[0431] 3. Summary of opinions

[0432] During a discussion, users input their comments into their device. The device sends these comments to the server, which analyzes them using a generative AI model. The server extracts key points and summaries and returns them to the device, which then displays the summarized key points to the user.

[0433] Examples:

[0434] If someone says, "Automation of process 1 is necessary," or "The inspection system for process 3 should be strengthened," the server summarizes this as "Automation of process 1, strengthening of inspection system for process 3," and sends this to the terminal.

[0435] Example prompt sentence:

[0436] "Please summarize the main points of the following statement:..."

[0437] 4. Setting the direction of the discussion

[0438] The server constantly monitors the progress of the discussion and suggests next steps or new topics depending on the direction of the discussion, ensuring that the discussion proceeds smoothly without going off track. The suggested information is sent to the terminal and presented to the user.

[0439] Examples:

[0440] If the discussion on "quality improvement" veers off into "technical issues," the server will propose "next steps to improve quality" and display them on the terminal.

[0441] 5. Time management

[0442] When a user enters the start time and planned duration of a discussion into their device, this information is sent to the server. The server monitors the progress of the discussion in real time and generates a time alert and sends it to the device, for example, 10 minutes before the planned end time. The device then displays this time alert to the user, informing them of the remaining time.

[0443] Examples:

[0444] If the start time of the discussion is 10:00 and the scheduled duration is 60 minutes, the server will generate a time alert saying "10 minutes remaining" and display it on the terminal 10 minutes before the scheduled end time.

[0445] 6. Emotional Recognition

[0446] The emotion recognition engine analyzes the user's voice and text input to determine their emotions. Based on this information, the server adjusts the discussion progress and suggestions. If the user shows signs of frustration or fatigue, the server will suggest a break or adjust the pace of the discussion.

[0447] Examples:

[0448] If the user appears tired or irritated, the server will make suggestions such as "Take a 5-minute break."

[0449] This system supports efficient and smooth progress in process improvement discussions at manufacturing sites, and enables flexible responses based on the emotions of participants.

[0450] Hardware and software used:

[0451] AI model: OpenAI's GPT-3 or GPT-4

[0452] Server: High-performance server (e.g. AWS EC2, Google Cloud Compute Engine)

[0453] Device: Smartphone or tablet

[0454] This will significantly improve the quality and efficiency of discussions on the manufacturing floor.

[0455] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0456] Step 1:

[0457] A user inputs a topic for discussion into a terminal, and the terminal transmits this topic to a server.

[0458] Input: Theme (e.g. "Process Improvement")

[0459] Output: Theme data

[0460] Specific operation: Sends text entered by the user on the terminal to the server.

[0461] Step 2:

[0462] The server uses a generative AI model to analyze the input topic and generate specific related topics.

[0463] Input: Theme data

[0464] Output: Topic list

[0465] Specific operation: The topic is input into the generation AI model, and a topic is generated using the prompt, "Please suggest a suitable topic for discussion based on the topic 'Process Improvement'."

[0466] Step 3:

[0467] The server sends the generated topic list to the terminal, which then presents it to the user.

[0468] Input: Topic list

[0469] Output: A list of topics as they appear in the user interface

[0470] Specific operation: Receives a topic list from the server and displays it on the device screen.

[0471] Step 4:

[0472] The user selects one from a list of presented topics, and the terminal transmits the selection to the server.

[0473] Input: Selected Topic

[0474] Output: Selected topic data

[0475] What it does: Captures the user's selections and sends that information to the server.

[0476] Step 5:

[0477] The server generates a question based on the selected topic and returns the generated question to the terminal.

[0478] Input: Selected topic data

[0479] Output: Question list

[0480] Specific operation: The selected topic is input into the generative AI model, and questions are generated using the prompt, "Generate questions related to the topic 'Quality Improvement'."

[0481] Step 6:

[0482] The terminal presents the generated list of questions to the user.

[0483] Input: Question List

[0484] Output: A list of questions displayed in the user interface

[0485] Specific operation: Display a list of questions on the device screen.

[0486] Step 7:

[0487] During the discussion, users input comments into their terminals, and the terminals transmit these comments to the server.

[0488] Input: What you say

[0489] Output: Speech data

[0490] Specific operation: Captures the user's spoken text and sends it to the server.

[0491] Step 8:

[0492] The server analyzes the speech data, extracts the main points and summaries, and sends them to the terminal.

[0493] Input: Speech data

[0494] Output: Summary data

[0495] Specific operation: Speech data is input into a generative AI model, and a summary is generated using the prompt, "Please summarize the main points of the following utterance:..."

[0496] Step 9:

[0497] The terminal displays the summary data to the user.

[0498] Input: Summary data

[0499] Output: A summary that is displayed in the user interface

[0500] Specific behavior: Display a summary on the device screen.

[0501] Step 10:

[0502] The server monitors the progress of the discussion and suggests next steps or new topics when things go off track.

[0503] Input: Discussion progress data

[0504] Output: Suggested next steps and new topics

[0505] Specific behavior: Analyzes the progress, generates appropriate suggestions and sends them to the device.

[0506] Step 11:

[0507] The terminal presents the suggested information to the user.

[0508] Input: Suggest next steps or new topics

[0509] Output: Proposal displayed in the user interface

[0510] Specific behavior: Display suggestions on the device screen.

[0511] Step 12:

[0512] The user inputs the start time and scheduled time of the discussion into the terminal, which then transmits this to the server.

[0513] Input: Start time and Scheduled time

[0514] Output: Time data

[0515] Specific operation: The time information entered on the terminal is sent to the server.

[0516] Step 13:

[0517] The server monitors the progress in real time and generates a time alert before the scheduled time and sends it to the terminal.

[0518] Input: Time and progress data

[0519] Output: Time alert

[0520] Specific operation: Compare the progress with the scheduled time, and generate an alert saying "10 minutes remaining" 10 minutes before the scheduled end time and send it to the device.

[0521] Step 14:

[0522] The terminal displays a time alert to the user.

[0523] Input: Time Alert

[0524] Output: Time alert displayed in the user interface

[0525] Specific operation: Display a time alert on the device screen.

[0526] Step 15:

[0527] The emotion recognition engine analyzes the user's voice and text input to determine their emotions.

[0528] Input: Audio or text data

[0529] Output: Emotion data

[0530] Specific behavior: Analyzes the user's voice tone and text content to determine their emotional status.

[0531] Step 16:

[0532] The server adjusts the progress of the discussion and the content of proposals based on the emotional data and sends them to the terminal.

[0533] Input: Emotion data

[0534] Output: Coordinated progress or proposal

[0535] Specific operation: Analyzes emotional data and generates an adjustment, such as "Take a 5-minute break," and sends it to the device.

[0536] Step 17:

[0537] The terminal displays the adjusted progress and suggestions to the user.

[0538] Input: Adjusted progress or proposal

[0539] Output: The adjusted progress or suggestions displayed in the user interface

[0540] Specific behavior: Display adjusted progress or suggestions on the device screen.

[0541] 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.

[0542] 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.

[0543] 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.

[0544] [Second embodiment]

[0545] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0546] 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.

[0547] 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).

[0548] 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.

[0549] 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.

[0550] 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).

[0551] 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.

[0552] 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.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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."

[0557] The discussion facilitator AI of the present invention is a system that proposes topics, generates questions, summarizes opinions, sets the direction of the discussion, and manages time. Specific embodiments will be described below.

[0558] 1. Topic Suggestion

[0559] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific related topics. The server then returns the generated topic list to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server will generate related topics such as "market research," "prototype design," and "competitive analysis" and display them on the device.

[0560] 2. Question Generation

[0561] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[0562] 3. Summary of opinions

[0563] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[0564] 4. Setting the direction of the discussion

[0565] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[0566] 5. Time management

[0567] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[0568] With these functions, the discussion facilitator AI of the present invention supports efficient and smooth discussion progress, reduces the burden on the facilitator, and improves the quality and efficiency of discussions.

[0569] The processing flow will be explained below.

[0570] Topic Suggestion

[0571] 1. Step 1:

[0572] The user inputs the topic of the discussion into the terminal.

[0573] 2. Step 2:

[0574] The terminal transmits the input theme to the server.

[0575] 3. Step 3:

[0576] The server receives the theme and generates related topics using an AI model.

[0577] 4. Step 4:

[0578] The server transmits the generated topic list to the terminal.

[0579] 5. Step 5:

[0580] The terminal displays the topic candidates to the user.

[0581] Question Generation

[0582] 1. Step 1:

[0583] The user selects one of the topic candidates presented on the terminal.

[0584] 2. Step 2:

[0585] The terminal sends the selected topic to the server.

[0586] 3. Step 3:

[0587] The server receives the topic and generates relevant questions using an AI model.

[0588] 4. Step 4:

[0589] The server transmits the generated question list to the terminal.

[0590] 5. Step 5:

[0591] The terminal displays the generated question to the user.

[0592] Summary of opinions

[0593] 1. Step 1:

[0594] The user inputs the content of the discussion into the terminal.

[0595] 2. Step 2:

[0596] The terminal transmits the inputted speech content to the server.

[0597] 3. Step 3:

[0598] The server analyzes what is said and generates key points and summaries.

[0599] 4. Step 4:

[0600] The server sends the generated gist to the device.

[0601] 5. Step 5:

[0602] The device displays a summary of the key points to the user.

[0603] Setting the direction of the discussion

[0604] 1. Step 1:

[0605] The server monitors the progress of the discussion in real time.

[0606] 2. Step 2:

[0607] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[0608] 3. Step 3:

[0609] The server sends the generated proposal to the terminal.

[0610] 4. Step 4:

[0611] The device displays the suggestions to the user.

[0612] time management

[0613] 1. Step 1:

[0614] The user inputs the start time and scheduled time of the discussion into the terminal.

[0615] 2. Step 2:

[0616] The terminal transmits the input time information to the server.

[0617] 3. Step 3:

[0618] The server monitors the progress and elapsed time in real time.

[0619] 4. Step 4:

[0620] The server generates a time alert when the scheduled time is about to expire.

[0621] 5. Step 5:

[0622] The server sends the generated time alert to the terminal.

[0623] 6. Step 6:

[0624] The device displays a time alert to the user, informing them of the time remaining.

[0625] Through the above steps, the discussion facilitator AI of the present invention functions as a system that supports the efficient and smooth progress of discussions.

[0626] Example 1

[0627] 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."

[0628] With conventional discussion systems, it was difficult to efficiently manage the entire discussion, including proposing topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time. Furthermore, since the facilitator had to take on all of these tasks, it placed a heavy burden on them, and there was a risk that the quality and efficiency of the discussion would decline.

[0629] 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.

[0630] In this invention, the server includes means for receiving a theme input by a user and generating related topics, means for generating questions based on the topic selected by the user, means for summarizing comments made during the discussion, means for monitoring the progress of the discussion and suggesting a direction, and means for managing the time of the discussion, thereby enabling the discussion to proceed efficiently and smoothly.

[0631] The "topic entered by the user" is information that the user enters into the terminal as the subject or topic of the discussion.

[0632] The "means for generating relevant topics" refers to a method and apparatus that uses a generative AI model to create specific topics useful for discussion based on a theme entered by a user.

[0633] A "means for generating questions" is a method and apparatus that uses a generative AI model to create relevant questions based on a user-selected topic.

[0634] The "means for summarizing speech content" refers to a method and device for analyzing speech content entered by users during a discussion, extracting the main points and important matters, and summarizing them in a concise manner.

[0635] "Means for monitoring the progress of the discussion and suggesting the direction" refers to a method and device that constantly monitors the current state of the discussion and appropriately suggests the next step or new topic based on the set direction of the discussion.

[0636] The "means for managing the discussion time" refers to a method and device for monitoring the progress of a discussion in real time based on the start time and scheduled time set by the user, and generating appropriate time alerts to notify the user.

[0637] The discussion facilitator AI of the present invention is a system that supports the highly efficient and smooth progress of discussions. An embodiment of this system will be specifically described below.

[0638] 1. Receive a topic entered by the user and generate related topics

[0639] The user inputs a discussion topic (e.g., "new product development") into the device. The device then sends this topic to the server, which uses a generative AI model (e.g., OpenAI GPT-3) to analyze the topic and generate specific related topics (e.g., "market research," "prototype design," "competitive analysis").

[0640] 2. Generate questions based on user-selected topics

[0641] When a user selects one of the generated topics (e.g., "Target Market Analysis"), the device sends the selected topic to the server, which uses the generative AI model to generate questions related to the selected topic (e.g., "What are the major consumer groups?", "What is the market share by region?").

[0642] 3. Summarize what was said during the discussion

[0643] During a discussion, users input their comments into their device. The device then sends the comments to the server. The server uses a generative AI model to analyze the comments and extract key points and summaries. The device then displays the summarized points to the user (e.g., "Factors that determine target market: price, quality").

[0644] 4. Monitor the progress of the discussion and suggest direction.

[0645] The server monitors the progress of the discussion in real time and, if the discussion deviates from the set direction, suggests next steps or new topics (e.g., "Next steps to advance market research"). The server sends the suggestions to the device and displays them to the user.

[0646] 5. Manage the discussion time

[0647] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert (e.g., "10 minutes remaining") 10 minutes before the planned end time and sends it to the terminal. The terminal displays this time alert to the user.

[0648] Examples of concrete examples and prompts

[0649] 1. Receive a topic entered by the user and generate related topics

[0650] User Input: "New Product Development"

[0651] Example prompt: "Please suggest some specific topics related to new product development."

[0652] 2. Generate questions based on user-selected topics

[0653] User Input: "Target Market Analysis"

[0654] Example prompt: "Generate questions related to target market analysis."

[0655] 3. Summarize what was said during the discussion

[0656] User Input: "Price and quality are key factors in determining the target market for a new product."

[0657] Example prompt: "Summarize the main points from this statement."

[0658] 4. Suggest a direction for the discussion

[0659] Surveillance Systems: "The discussion has gone off track"

[0660] Example prompt: "Please suggest next steps to further your market research."

[0661] 5. Manage the discussion time

[0662] User input: "Discussion start time: 10:00, scheduled duration: 60 minutes"

[0663] Example prompt: "Generate a notification 10 minutes before the time is up."

[0664] These embodiments enable the present invention to improve the efficiency and quality of discussions.

[0665] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0666] Step 1:

[0667] Enter and submit your theme

[0668] The user inputs the topic of the discussion (e.g., "new product development") into the terminal. The input topic is sent from the terminal to the server. The input is the text data of the topic by the user, and the output is the transmission of the text data of the topic from the terminal to the server.

[0669] Step 2:

[0670] Theme analysis and topic generation

[0671] The server analyzes the received thematic text data using a generative AI model (e.g., OpenAI GPT-3) and generates related topics (e.g., "market research," "prototype design," and "competitive analysis"). The input is thematic text data, and the output is a list of generated topics. The server sends this list back to the device.

[0672] Step 3:

[0673] View topics

[0674] The terminal displays the list of topics received from the server to the user. The input is the topic list data from the server, and the output is the topic list displayed on the terminal screen.

[0675] Step 4:

[0676] Select a topic and post

[0677] The user selects one topic from the displayed list (e.g., "Target Market Analysis"), and the terminal sends the data to the server. The input is the topic data selected by the user, and the output is the transmission of the selected topic data from the terminal to the server.

[0678] Step 5:

[0679] Question Generation

[0680] The server analyzes the received topic data using a generative AI model and generates relevant questions (e.g., "What are the major consumer groups?", "What is the market share by region?"). The input is the selected topic data, and the output is a list of generated questions. The server sends this list back to the device.

[0681] Step 6:

[0682] Show Questions

[0683] The terminal displays the list of questions received from the server to the user. The input is the question list data from the server, and the output is the question list displayed on the terminal screen.

[0684] Step 7:

[0685] Enter and send your message

[0686] During a discussion, a user inputs a statement into a terminal. The input statement is sent from the terminal to the server. The input is text data of the statement made by the user, and the output is the transmission of the text data from the terminal to the server.

[0687] Step 8:

[0688] Analysis and summary of speech content

[0689] The server analyzes the received speech using a generative AI model to extract key points and summaries. The input is the speech text data, and the output is summarized speech point data. The server then returns this summary data to the terminal.

[0690] Step 9:

[0691] View Summary

[0692] The terminal displays the summarized data received from the server to the user. The input is the summarized data from the server, and the output is the summarized data displayed on the screen of the terminal.

[0693] Step 10:

[0694] Monitor the progress of the discussion

[0695] The server monitors the progress of the discussion in real time and suggests next steps or new topics if the discussion strays from the set direction. The input is the current discussion status data, and the output is the proposed next steps or topic data. The server sends this data to the terminal.

[0696] Step 11:

[0697] View Suggestions

[0698] The terminal displays the proposed data received from the server to the user. The input is the proposed data from the server, and the output is the proposed data displayed on the screen of the terminal.

[0699] Step 12:

[0700] Time Management Settings

[0701] The user inputs the start time and scheduled time of the discussion into the terminal. The input time information is sent from the terminal to the server. The input is the start time and scheduled time data set by the user, and the output is the transmission of time information from the terminal to the server.

[0702] Step 13:

[0703] Time Management Practices

[0704] The server monitors the progress of the discussion in real time based on the time information received, and generates a time alert when the scheduled end time approaches. The input is the start time and scheduled time data, and the output is the generated time alert data. The server sends this time alert to the terminal.

[0705] Step 14:

[0706] Displaying time alerts

[0707] The terminal displays the time alert received from the server to the user. The input is the time alert data from the server, and the output is the time alert displayed on the terminal screen.

[0708] These processing steps enable the discussion facilitator AI to conduct discussions efficiently and smoothly.

[0709] (Application example 1)

[0710] 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."

[0711] Conventional discussions place a heavy burden on the facilitator, requiring a great deal of effort to progress and manage the discussion. Furthermore, discussions often go off track and time management is inadequate, making it difficult to hold efficient, high-quality discussions. In particular, in factories, efficiency and precision are required in discussions about production processes, quality control, and solving technical problems, but achieving this has been difficult. The present invention aims to solve these problems and provide a system that supports efficient and smooth discussions.

[0712] 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.

[0713] In this invention, the server includes a means for generating specific topics related to the theme of the discussion, a means for generating questions related to the generated topics, and a means for analyzing comments made during the discussion in real time and presenting summaries, thereby smoothing the progress of the discussion, reducing the burden on the facilitator, and enabling efficient, high-quality discussions.

[0714] A "topic" is a specific theme or subject that is brought up in a discussion or debate.

[0715] A "question" is a specific question related to the topic of discussion that is posed to deepen the discussion.

[0716] "Opinions" are the thoughts and opinions expressed by participants during a discussion.

[0717] The "direction of the discussion" indicates the overall guidelines and way forward for the discussion.

[0718] "Time management" refers to monitoring the start time, progress, and planned end time of a discussion and making appropriate adjustments.

[0719] "Generated Topics" are lists of related topics that are automatically generated based on the topic of the discussion.

[0720] "Related Questions" are a set of automatically generated questions related to the selected topic.

[0721] "Speech content" refers to what participants said during the discussion.

[0722] A "summary" is a summary of the main points or important information extracted from what was said during the discussion.

[0723] "Real-time analysis" refers to processing and analyzing data instantly while the discussion is taking place.

[0724] "Appropriate next steps" are specific actions or topics that should be taken next in the discussion.

[0725] "Time Alert" is a time warning that occurs based on the scheduled time of the discussion.

[0726] This invention is a system that uses a discussion facilitator AI to facilitate smooth discussion progress and reduce the burden on the facilitator. Specific embodiments will be described below.

[0727] The system mainly consists of three main components: a server, a terminal, and a user.

[0728] Hardware and Software

[0729] Hardware:

[0730] tablet device

[0731] Smart Glasses

[0732] software:

[0733] Cloud AI services (e.g., Google Cloud AI and AWS AI services)

[0734] Real-time Data Management System

[0735] Program processing

[0736] Users input the topic of discussion using a tablet or smart glasses. This topic is sent to the server via the device. The server uses a cloud AI service to analyze the topic and generate specific related topics. The generated topic list is then displayed on the device and presented to the user.

[0737] When the user selects one of the displayed topics, the device sends the selected topic to the server, which then uses the cloud AI service to generate a related question and returns it to the device, where it is displayed and presented to the user.

[0738] During the discussion, users input their comments via their devices. The inputted comments are sent to the server in real time, where cloud AI analyzes them and extracts key points and summaries. These summaries are displayed on the device and presented to the user. The server also constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to prevent the discussion from going off track. This information is also displayed on the device and presented to the user.

[0739] Users input the start time and expected duration of the discussion into their terminal. This is also sent to the server, which monitors the progress of the discussion in real time. Before the scheduled end time, a time alert is generated and sent to the terminal to notify the remaining time.

[0740] Specific examples

[0741] For example, if the topic "new product development" is entered, the following topics and questions will be generated:

[0742] Example of a topic-generating prompt:

[0743] Generate topics related to the theme "New Product Development".

[0744] This generates topics such as "market research," "prototype design," and "competitive analysis."

[0745] Example of a question-generating prompt:

[0746] Generate questions related to the topic "Market Research".

[0747] This generates questions such as, "What are the major consumer groups?" and "What is the market share by region?"

[0748] In this way, this system supports the progress of discussions, reduces the burden on facilitators, and enables efficient, high-quality discussions.

[0749] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0750] Step 1:

[0751] The user inputs the topic of discussion into a tablet device or smart glasses.

[0752] The input theme is sent from the terminal to the server. At this time, the theme is sent to the server as input data.

[0753] Step 2:

[0754] The server uses cloud AI services to analyze the received themes and generate specific related topics.

[0755] The generated topic list is returned from the server to the terminal.

[0756] Here, data processing involves extracting related topics from the theme, and generating a topic list as the output.

[0757] Step 3:

[0758] The user selects one topic from the topic list displayed on the terminal.

[0759] The selected topic is again sent from the terminal to the server, this time as selection data.

[0760] Step 4:

[0761] The server uses a cloud AI service to generate questions related to the received topic.

[0762] The generated question list is returned from the server to the terminal.

[0763] Here, data processing involves generating related questions from topics, and generating a question list as the output.

[0764] Step 5:

[0765] During the discussion, the user inputs each statement into the terminal.

[0766] The inputted remarks are sent to the server in real time.

[0767] At this time, the content of the statement is sent to the server as input data.

[0768] Step 6:

[0769] The server uses cloud AI to analyze the received comments in real time and extract key points and summaries.

[0770] The extracted gist is returned from the server to the terminal.

[0771] Here, data processing involves analyzing the content of the comments and generating a summary, and the main points are generated as the output.

[0772] Step 7:

[0773] The server constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to keep the discussion from going off track.

[0774] The content of the proposal is transmitted from the server to the terminal.

[0775] Here, data calculations are performed to monitor progress and propose next steps, and the proposals are generated as output.

[0776] Step 8:

[0777] The user inputs the start time and scheduled time of the discussion into the terminal.

[0778] Based on this, the server monitors the progress of the discussion in real time.

[0779] A time alert is generated before the scheduled end time and sent to the terminal.

[0780] Here, data calculations involve time management and alert generation, and a time alert is generated as the output.

[0781] 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.

[0782] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time, as well as recognizing the user's emotions. Specific embodiments are described below.

[0783] 1. Topic Suggestion

[0784] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific topics related to it. The generated topic list is sent to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server generates related topics such as "market research," "prototype design," and "competitive analysis," and displays them on the device.

[0785] 2. Question Generation

[0786] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[0787] 3. Summary of opinions

[0788] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[0789] 4. Setting the direction of the discussion

[0790] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[0791] 5. Time management

[0792] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[0793] 6. Emotion Engine

[0794] The emotion engine has the ability to analyze the user's voice and text input and determine emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[0795] With these functions, the discussion facilitator AI system of the present invention not only supports efficient and smooth discussion progress, but also flexibly responds to the user's emotional state, reducing the burden on the facilitator and improving the quality and efficiency of discussions.

[0796] The processing flow will be explained below.

[0797] Topic Suggestion

[0798] 1. Step 1:

[0799] The user inputs the topic of the discussion into the terminal.

[0800] 2. Step 2:

[0801] The terminal transmits the input theme to the server.

[0802] 3. Step 3:

[0803] The server receives the theme and generates related topics using an AI model.

[0804] 4. Step 4:

[0805] The server transmits the generated topic list to the terminal.

[0806] 5. Step 5:

[0807] The terminal displays the topic candidates to the user.

[0808] Question Generation

[0809] 1. Step 1:

[0810] The user selects one of the topic candidates presented on the terminal.

[0811] 2. Step 2:

[0812] The terminal sends the selected topic to the server.

[0813] 3. Step 3:

[0814] The server receives the topic and generates relevant questions using an AI model.

[0815] 4. Step 4:

[0816] The server transmits the generated question list to the terminal.

[0817] 5. Step 5:

[0818] The terminal displays the generated question to the user.

[0819] Summary of opinions

[0820] 1. Step 1:

[0821] The user inputs the content of the discussion into the terminal.

[0822] 2. Step 2:

[0823] The terminal transmits the inputted speech content to the server.

[0824] 3. Step 3:

[0825] The server analyzes what is said and generates key points and summaries.

[0826] 4. Step 4:

[0827] The server sends the generated gist to the device.

[0828] 5. Step 5:

[0829] The device displays a summary of the key points to the user.

[0830] Setting the direction of the discussion

[0831] 1. Step 1:

[0832] The server monitors the progress of the discussion in real time.

[0833] 2. Step 2:

[0834] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[0835] 3. Step 3:

[0836] The server sends the generated proposal to the terminal.

[0837] 4. Step 4:

[0838] The device displays the suggestions to the user.

[0839] time management

[0840] 1. Step 1:

[0841] The user inputs the start time and scheduled time of the discussion into the terminal.

[0842] 2. Step 2:

[0843] The terminal transmits the input time information to the server.

[0844] 3. Step 3:

[0845] The server monitors the progress and elapsed time in real time.

[0846] 4. Step 4:

[0847] The server generates a time alert when the scheduled time is about to expire.

[0848] 5. Step 5:

[0849] The server sends the generated time alert to the terminal.

[0850] 6. Step 6:

[0851] The device displays a time alert to the user, informing them of the time remaining.

[0852] Use of emotion engine

[0853] 1. Step 1:

[0854] During the discussion, the user inputs what is being said into the terminal by voice or text.

[0855] 2. Step 2:

[0856] The device sends the input voice and text data to the server.

[0857] 3. Step 3:

[0858] The server's emotion engine analyzes voice and text data to determine the user's emotions.

[0859] 4. Step 4:

[0860] The server generates appropriate feedback and suggestions based on the emotions determined by the emotion engine.

[0861] 5. Step 5:

[0862] Send server-generated feedback and suggestions to the device.

[0863] 6. Step 6:

[0864] The device displays feedback and suggestions to the user. For example, if the user shows signs of frustration, the server provides advice on how to stay calm and displays it on the device.

[0865] Through the above steps, the discussion facilitator AI system of the present invention, which is combined with an emotion engine, functions as a system that supports the progress of discussions efficiently and with consideration for emotional aspects.

[0866] Example 2

[0867] 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."

[0868] In modern discussions, differences of opinion among participants, deviations in the direction of the discussion, and poor time management are often problems. Furthermore, it is difficult to grasp the emotional state of participants and respond appropriately accordingly. A system that can solve these issues and enable efficient and smooth discussions is needed.

[0869] 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.

[0870] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing the user's emotions. This allows for efficient and smooth progress of the discussion. It also enables flexible responses according to the user's emotions, improving the quality and efficiency of the discussion.

[0871] The "means for suggesting topics" is a function that generates related topics based on a theme input by the user and displays them on the terminal.

[0872] The "means for generating questions" is a function for generating related questions based on a topic selected by the user and displaying them on the terminal.

[0873] "Means for summarizing opinions" is a function that analyzes the comments entered by users during a discussion, extracts the main points and summaries, and displays them on the device.

[0874] "A means of setting the direction of the discussion" is a function that monitors the progress of the discussion and suggests next steps or new topics to prevent the discussion from going off track.

[0875] The "means for managing time" is a function for managing the start time and scheduled time of a discussion, and generating a time alert before the scheduled time and displaying it on the terminal.

[0876] The "means for recognizing user emotions" is a function that analyzes the user's voice and text input, determines their emotions, and responds accordingly.

[0877] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, time management, and recognizing the user's emotions. Specific embodiments of the system are described below.

[0878] Topic Suggestion

[0879] The user inputs a discussion topic into the device. For example, they might input "new product development." The device sends this topic to the server, which analyzes the topic using a generative AI model. Based on the analysis results, it generates specific related topics. The generated topic list is sent to the device, which presents it to the user. For example, generated topics might include "market research," "prototype design," and "competitive analysis."

[0880] Example prompt sentence:

[0881] "I'd like to hold a discussion about new product development. Please suggest specific topics that are relevant."

[0882] Question Generation

[0883] The user selects one of the presented topics. For example, they may select "target market analysis." The selected topic is sent from the device to the server. The server uses a generative AI model to generate questions related to the selected topic. The generated list of questions is sent to the device, which then presents them to the user. For example, generated questions include "What are the major consumer groups?" and "What is the market share by region?"

[0884] Example prompt sentence:

[0885] "Generate relevant questions to drive the discussion about your target market analysis."

[0886] Summary of opinions

[0887] As the discussion progresses, users input their comments into their devices. These comments are then sent from the devices to the server. The server then uses a generative AI model to analyze the comments and extract key points and summaries. The extracted summaries are then sent to the devices, which then display them to the user. For example, if someone says, "Price and quality are the key factors in determining the target market for a new product," the summary will be "Factors in determining the target market: price, quality."

[0888] Setting the direction of the discussion

[0889] The server monitors the progress of the discussion in real time. To prevent the discussion from going off track, it suggests next steps or new topics based on the set direction. The suggestions are sent to the device, which then displays them to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[0890] time management

[0891] The user enters the start time and planned duration of the discussion into the terminal. For example, the start time is 10:00 and the planned duration is 60 minutes. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. For example, a time alert such as "10 minutes remaining" is generated 10 minutes before the planned end time. The terminal displays this alert to the user to inform them of the remaining time.

[0892] Emotion Engine

[0893] The emotion engine is a function that analyzes the user's voice and text input and determines emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[0894] As a result, the discussion facilitator AI system can support efficient and smooth discussions and respond flexibly to the user's emotional state. It functions as a system that reduces the burden on the facilitator and improves the quality and efficiency of discussions.

[0895] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0896] Step 1:

[0897] The user inputs the topic of discussion into the terminal. For example, they input "new product development." The terminal receives this input as data and sends it to the server. The input data is in text format.

[0898] Step 2:

[0899] The server analyzes the received theme data. The server uses a generative AI model to analyze the input theme and generate specific topics related to the theme. The generated topic list is formed as data. The generative AI model extracts topics using natural language processing technology.

[0900] Step 3:

[0901] The server sends the generated topic list to the terminal. The terminal receives this topic list as data and displays it to the user. The user selects one of the presented topics. Topic data is generated by selecting it.

[0902] Step 4:

[0903] The selected topic data is sent from the device to the server. The server then uses the generative AI model to generate questions based on the received topic data. The generated list of questions is then formed into data. For example, questions such as "What are the main consumer groups?" are generated from "target market analysis."

[0904] Step 5:

[0905] The server sends the generated question list to the terminal, which displays the question list to the user. To advance the discussion, the user expresses their opinions and thoughts based on the questions and inputs them as text into the terminal.

[0906] Step 6:

[0907] The device sends the user's speech as data to the server, which then analyzes the received speech using a generative AI model. Through this analysis, key points and summaries are extracted. Text mining technology is used to process the data.

[0908] Step 7:

[0909] The server sends the extracted summary data to the terminal, which then displays the received summary to the user, allowing the user to grasp the progress of the discussion.

[0910] Step 8:

[0911] The server monitors the progress of the discussion in real time. If the discussion goes off track, the server uses a generative AI model to suggest next steps or new topics. The suggestions are generated as data and sent to the device.

[0912] Step 9:

[0913] The device displays the suggestions received from the server to the user, helping to guide the discussion in the right direction.

[0914] Step 10:

[0915] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this input data to the server. The server monitors the progress of the discussion based on the received time data.

[0916] Step 11:

[0917] The server generates time alert data when the scheduled time approaches and sends it to the terminal. For example, an alert saying "10 minutes remaining" is generated 10 minutes before the scheduled end time.

[0918] Step 12:

[0919] The device displays the received time alert data to the user, allowing the user to grasp the remaining time and make appropriate progress.

[0920] Step 13:

[0921] The emotion engine collects the user's voice and text input as data and sends it from the device to the server, which then analyzes the received emotion data and determines the user's emotion.

[0922] Step 14:

[0923] The server then adjusts the discussion and suggestions based on the emotion data it has determined. For example, if a user shows signs of fatigue, it suggests taking a break.

[0924] Step 15:

[0925] The server sends the adjusted proposal to the device, which displays it to the user, allowing the user to take appropriate action.

[0926] (Application example 2)

[0927] 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."

[0928] In modern manufacturing sites, discussions are frequently held to address a variety of issues, including process efficiency, quality improvement, and safety management. However, factors that significantly reduce the efficiency of discussions include distraction, poor time management, and emotional changes among participants. There is a growing need for a system that can adequately resolve these issues and support efficient discussions.

[0929] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0930] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing users' emotions and adjusting the progress of the discussion and the content of suggestions. This prevents discussions from going off track, ensures appropriate time management, and enables smooth discussion management in accordance with the emotions of participants.

[0931] "Topic suggestions" are a way to start a discussion by generating specific, related topics based on a theme entered by the user.

[0932] "Question generation" is a means for users to generate specific questions related to a topic they have selected and deepen the discussion.

[0933] A "summary" is a method of summarizing each statement made during a discussion and extracting and presenting the main points and summaries.

[0934] "Setting the direction of the discussion" is a way to constantly monitor the progress of the discussion and suggest next steps or new topics based on the set direction to prevent the discussion from going off track.

[0935] "Time management" is a means of managing the start and scheduled time of a discussion and providing appropriate time alerts by monitoring progress in real time.

[0936] "Emotion recognition" is a means of analyzing a user's voice and text input, determining the user's emotional state, and adjusting the discussion progress and proposal content accordingly.

[0937] This invention is a system for supporting discussions in manufacturing sites, which proposes topics, generates questions, summarizes opinions, sets the direction of discussions, manages time, and recognizes emotions through communication between servers, terminals, and users.

[0938] 1. Topic Suggestion

[0939] First, the user inputs the topic of the discussion through the device, which then sends it to the server, which then uses a generative AI model (e.g., OpenAI's GPT-3 or GPT-4) to analyze the topic and generate specific related topics based on it. The generated topics are then sent to the device and presented to the user.

[0940] Examples:

[0941] When a user inputs the topic "process improvement," the server generates topics such as "quality improvement," "cost reduction," and "safety management," and displays them on the terminal.

[0942] Example prompt sentence:

[0943] "Please suggest suitable topics for discussion based on the theme 'Process Improvement'."

[0944] 2. Question Generation

[0945] When a user operates their device to select one of the generated topics, that topic is sent to the server, which uses the generative AI model to generate a question related to that topic and returns it to the device, which then presents the question to the user.

[0946] Examples:

[0947] If the user selects "Improve Quality," the server generates questions such as "In which process are quality problems occurring?" and "How can existing quality control methods be improved?" and displays them on the terminal.

[0948] Example prompt sentence:

[0949] "Generate questions related to the topic 'Quality Improvement'."

[0950] 3. Summary of opinions

[0951] During a discussion, users input their comments into their device. The device sends these comments to the server, which analyzes them using a generative AI model. The server extracts key points and summaries and returns them to the device, which then displays the summarized key points to the user.

[0952] Examples:

[0953] If someone says, "Automation of process 1 is necessary," or "The inspection system for process 3 should be strengthened," the server summarizes this as "Automation of process 1, strengthening of inspection system for process 3," and sends this to the terminal.

[0954] Example prompt sentence:

[0955] "Please summarize the main points of the following statement:..."

[0956] 4. Setting the direction of the discussion

[0957] The server constantly monitors the progress of the discussion and suggests next steps or new topics depending on the direction of the discussion, ensuring that the discussion proceeds smoothly without going off track. The suggested information is sent to the terminal and presented to the user.

[0958] Examples:

[0959] If the discussion on "quality improvement" veers off into "technical issues," the server will propose "next steps to improve quality" and display them on the terminal.

[0960] 5. Time management

[0961] When a user enters the start time and planned duration of a discussion into their device, this information is sent to the server. The server monitors the progress of the discussion in real time and generates a time alert and sends it to the device, for example, 10 minutes before the planned end time. The device then displays this time alert to the user, informing them of the remaining time.

[0962] Examples:

[0963] If the start time of the discussion is 10:00 and the scheduled duration is 60 minutes, the server will generate a time alert saying "10 minutes remaining" and display it on the terminal 10 minutes before the scheduled end time.

[0964] 6. Emotional Recognition

[0965] The emotion recognition engine analyzes the user's voice and text input to determine their emotions. Based on this information, the server adjusts the discussion progress and suggestions. If the user shows signs of frustration or fatigue, the server will suggest a break or adjust the pace of the discussion.

[0966] Examples:

[0967] If the user appears tired or irritated, the server will make suggestions such as "Take a 5-minute break."

[0968] This system supports efficient and smooth progress in process improvement discussions at manufacturing sites, and enables flexible responses based on the emotions of participants.

[0969] Hardware and software used:

[0970] AI model: OpenAI's GPT-3 or GPT-4

[0971] Server: High-performance server (e.g. AWS EC2, Google Cloud Compute Engine)

[0972] Device: Smartphone or tablet

[0973] This will significantly improve the quality and efficiency of discussions on the manufacturing floor.

[0974] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0975] Step 1:

[0976] A user inputs a topic for discussion into a terminal, and the terminal transmits this topic to a server.

[0977] Input: Theme (e.g. "Process Improvement")

[0978] Output: Theme data

[0979] Specific operation: Sends text entered by the user on the terminal to the server.

[0980] Step 2:

[0981] The server uses a generative AI model to analyze the input topic and generate specific related topics.

[0982] Input: Theme data

[0983] Output: Topic list

[0984] Specific operation: The topic is input into the generation AI model, and a topic is generated using the prompt, "Please suggest a suitable topic for discussion based on the topic 'Process Improvement'."

[0985] Step 3:

[0986] The server sends the generated topic list to the terminal, which then presents it to the user.

[0987] Input: Topic list

[0988] Output: A list of topics as they appear in the user interface

[0989] Specific operation: Receives a topic list from the server and displays it on the device screen.

[0990] Step 4:

[0991] The user selects one from a list of presented topics, and the terminal transmits the selection to the server.

[0992] Input: Selected Topic

[0993] Output: Selected topic data

[0994] What it does: Captures the user's selections and sends that information to the server.

[0995] Step 5:

[0996] The server generates a question based on the selected topic and returns the generated question to the terminal.

[0997] Input: Selected topic data

[0998] Output: Question list

[0999] Specific operation: The selected topic is input into the generative AI model, and questions are generated using the prompt, "Generate questions related to the topic 'Quality Improvement'."

[1000] Step 6:

[1001] The terminal presents the generated list of questions to the user.

[1002] Input: Question List

[1003] Output: A list of questions displayed in the user interface

[1004] Specific operation: Display a list of questions on the device screen.

[1005] Step 7:

[1006] During the discussion, users input comments into their terminals, and the terminals transmit these comments to the server.

[1007] Input: What you say

[1008] Output: Speech data

[1009] Specific operation: Captures the user's spoken text and sends it to the server.

[1010] Step 8:

[1011] The server analyzes the speech data, extracts the main points and summaries, and sends them to the terminal.

[1012] Input: Speech data

[1013] Output: Summary data

[1014] Specific operation: Speech data is input into a generative AI model, and a summary is generated using the prompt, "Please summarize the main points of the following utterance:..."

[1015] Step 9:

[1016] The terminal displays the summary data to the user.

[1017] Input: Summary data

[1018] Output: A summary that is displayed in the user interface

[1019] Specific behavior: Display a summary on the device screen.

[1020] Step 10:

[1021] The server monitors the progress of the discussion and suggests next steps or new topics when things go off track.

[1022] Input: Discussion progress data

[1023] Output: Suggested next steps and new topics

[1024] Specific behavior: Analyzes the progress, generates appropriate suggestions and sends them to the device.

[1025] Step 11:

[1026] The terminal presents the suggested information to the user.

[1027] Input: Suggest next steps or new topics

[1028] Output: Proposal displayed in the user interface

[1029] Specific behavior: Display suggestions on the device screen.

[1030] Step 12:

[1031] The user inputs the start time and scheduled time of the discussion into the terminal, which then transmits this to the server.

[1032] Input: Start time and Scheduled time

[1033] Output: Time data

[1034] Specific operation: The time information entered on the terminal is sent to the server.

[1035] Step 13:

[1036] The server monitors the progress in real time and generates a time alert before the scheduled time and sends it to the terminal.

[1037] Input: Time and progress data

[1038] Output: Time alert

[1039] Specific operation: Compare the progress with the scheduled time, and generate an alert saying "10 minutes remaining" 10 minutes before the scheduled end time and send it to the device.

[1040] Step 14:

[1041] The terminal displays a time alert to the user.

[1042] Input: Time Alert

[1043] Output: Time alert displayed in the user interface

[1044] Specific operation: Display a time alert on the device screen.

[1045] Step 15:

[1046] The emotion recognition engine analyzes the user's voice and text input to determine their emotions.

[1047] Input: Audio or text data

[1048] Output: Emotion data

[1049] Specific behavior: Analyzes the user's voice tone and text content to determine their emotional status.

[1050] Step 16:

[1051] The server adjusts the progress of the discussion and the content of proposals based on the emotional data and sends them to the terminal.

[1052] Input: Emotion data

[1053] Output: Coordinated progress or proposal

[1054] Specific operation: Analyzes emotional data and generates an adjustment, such as "Take a 5-minute break," and sends it to the device.

[1055] Step 17:

[1056] The terminal displays the adjusted progress and suggestions to the user.

[1057] Input: Adjusted progress or proposal

[1058] Output: The adjusted progress or suggestions displayed in the user interface

[1059] Specific behavior: Display adjusted progress or suggestions on the device screen.

[1060] 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.

[1061] 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.

[1062] 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.

[1063] [Third embodiment]

[1064] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1065] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1066] 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).

[1067] 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.

[1068] 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.

[1069] 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).

[1070] 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.

[1071] 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.

[1072] 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.

[1073] 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.

[1074] 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.

[1075] 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."

[1076] The discussion facilitator AI of the present invention is a system that proposes topics, generates questions, summarizes opinions, sets the direction of the discussion, and manages time. Specific embodiments will be described below.

[1077] 1. Topic Suggestion

[1078] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific related topics. The server then returns the generated topic list to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server will generate related topics such as "market research," "prototype design," and "competitive analysis" and display them on the device.

[1079] 2. Question Generation

[1080] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[1081] 3. Summary of opinions

[1082] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[1083] 4. Setting the direction of the discussion

[1084] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[1085] 5. Time management

[1086] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[1087] With these functions, the discussion facilitator AI of the present invention supports efficient and smooth discussion progress, reduces the burden on the facilitator, and improves the quality and efficiency of discussions.

[1088] The processing flow will be explained below.

[1089] Topic Suggestion

[1090] 1. Step 1:

[1091] The user inputs the topic of the discussion into the terminal.

[1092] 2. Step 2:

[1093] The terminal transmits the input theme to the server.

[1094] 3. Step 3:

[1095] The server receives the theme and generates related topics using an AI model.

[1096] 4. Step 4:

[1097] The server transmits the generated topic list to the terminal.

[1098] 5. Step 5:

[1099] The terminal displays the topic candidates to the user.

[1100] Question Generation

[1101] 1. Step 1:

[1102] The user selects one of the topic candidates presented on the terminal.

[1103] 2. Step 2:

[1104] The terminal sends the selected topic to the server.

[1105] 3. Step 3:

[1106] The server receives the topic and generates relevant questions using an AI model.

[1107] 4. Step 4:

[1108] The server transmits the generated question list to the terminal.

[1109] 5. Step 5:

[1110] The terminal displays the generated question to the user.

[1111] Summary of opinions

[1112] 1. Step 1:

[1113] The user inputs the content of the discussion into the terminal.

[1114] 2. Step 2:

[1115] The terminal transmits the inputted speech content to the server.

[1116] 3. Step 3:

[1117] The server analyzes what is said and generates key points and summaries.

[1118] 4. Step 4:

[1119] The server sends the generated gist to the device.

[1120] 5. Step 5:

[1121] The device displays a summary of the key points to the user.

[1122] Setting the direction of the discussion

[1123] 1. Step 1:

[1124] The server monitors the progress of the discussion in real time.

[1125] 2. Step 2:

[1126] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[1127] 3. Step 3:

[1128] The server sends the generated proposal to the terminal.

[1129] 4. Step 4:

[1130] The device displays the suggestions to the user.

[1131] time management

[1132] 1. Step 1:

[1133] The user inputs the start time and scheduled time of the discussion into the terminal.

[1134] 2. Step 2:

[1135] The terminal transmits the input time information to the server.

[1136] 3. Step 3:

[1137] The server monitors the progress and elapsed time in real time.

[1138] 4. Step 4:

[1139] The server generates a time alert when the scheduled time is about to expire.

[1140] 5. Step 5:

[1141] The server sends the generated time alert to the terminal.

[1142] 6. Step 6:

[1143] The device displays a time alert to the user, informing them of the time remaining.

[1144] Through the above steps, the discussion facilitator AI of the present invention functions as a system that supports the efficient and smooth progress of discussions.

[1145] Example 1

[1146] 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."

[1147] With conventional discussion systems, it was difficult to efficiently manage the entire discussion, including proposing topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time. Furthermore, since the facilitator had to take on all of these tasks, it placed a heavy burden on them, and there was a risk that the quality and efficiency of the discussion would decline.

[1148] 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.

[1149] In this invention, the server includes means for receiving a theme input by a user and generating related topics, means for generating questions based on the topic selected by the user, means for summarizing comments made during the discussion, means for monitoring the progress of the discussion and suggesting a direction, and means for managing the time of the discussion, thereby enabling the discussion to proceed efficiently and smoothly.

[1150] The "topic entered by the user" is information that the user enters into the terminal as the subject or topic of the discussion.

[1151] The "means for generating relevant topics" refers to a method and apparatus that uses a generative AI model to create specific topics useful for discussion based on a theme entered by a user.

[1152] A "means for generating questions" is a method and apparatus that uses a generative AI model to create relevant questions based on a user-selected topic.

[1153] The "means for summarizing speech content" refers to a method and device for analyzing speech content entered by users during a discussion, extracting the main points and important matters, and summarizing them in a concise manner.

[1154] "Means for monitoring the progress of the discussion and suggesting the direction" refers to a method and device that constantly monitors the current state of the discussion and appropriately suggests the next step or new topic based on the set direction of the discussion.

[1155] The "means for managing the discussion time" refers to a method and device for monitoring the progress of a discussion in real time based on the start time and scheduled time set by the user, and generating appropriate time alerts to notify the user.

[1156] The discussion facilitator AI of the present invention is a system that supports the highly efficient and smooth progress of discussions. An embodiment of this system will be specifically described below.

[1157] 1. Receive a topic entered by the user and generate related topics

[1158] The user inputs a discussion topic (e.g., "new product development") into the device. The device then sends this topic to the server, which uses a generative AI model (e.g., OpenAI GPT-3) to analyze the topic and generate specific related topics (e.g., "market research," "prototype design," "competitive analysis").

[1159] 2. Generate questions based on user-selected topics

[1160] When a user selects one of the generated topics (e.g., "Target Market Analysis"), the device sends the selected topic to the server, which uses the generative AI model to generate questions related to the selected topic (e.g., "What are the major consumer groups?", "What is the market share by region?").

[1161] 3. Summarize what was said during the discussion

[1162] During a discussion, users input their comments into their device. The device then sends the comments to the server. The server uses a generative AI model to analyze the comments and extract key points and summaries. The device then displays the summarized points to the user (e.g., "Factors that determine target market: price, quality").

[1163] 4. Monitor the progress of the discussion and suggest direction.

[1164] The server monitors the progress of the discussion in real time and, if the discussion deviates from the set direction, suggests next steps or new topics (e.g., "Next steps to advance market research"). The server sends the suggestions to the device and displays them to the user.

[1165] 5. Manage the discussion time

[1166] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert (e.g., "10 minutes remaining") 10 minutes before the planned end time and sends it to the terminal. The terminal displays this time alert to the user.

[1167] Examples of concrete examples and prompts

[1168] 1. Receive a topic entered by the user and generate related topics

[1169] User Input: "New Product Development"

[1170] Example prompt: "Please suggest some specific topics related to new product development."

[1171] 2. Generate questions based on user-selected topics

[1172] User Input: "Target Market Analysis"

[1173] Example prompt: "Generate questions related to target market analysis."

[1174] 3. Summarize what was said during the discussion

[1175] User Input: "Price and quality are key factors in determining the target market for a new product."

[1176] Example prompt: "Summarize the main points from this statement."

[1177] 4. Suggest a direction for the discussion

[1178] Surveillance Systems: "The discussion has gone off track"

[1179] Example prompt: "Please suggest next steps to further your market research."

[1180] 5. Manage the discussion time

[1181] User input: "Discussion start time: 10:00, scheduled duration: 60 minutes"

[1182] Example prompt: "Generate a notification 10 minutes before the time is up."

[1183] These embodiments enable the present invention to improve the efficiency and quality of discussions.

[1184] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1185] Step 1:

[1186] Enter and submit your theme

[1187] The user inputs the topic of the discussion (e.g., "new product development") into the terminal. The input topic is sent from the terminal to the server. The input is the text data of the topic by the user, and the output is the transmission of the text data of the topic from the terminal to the server.

[1188] Step 2:

[1189] Theme analysis and topic generation

[1190] The server analyzes the received thematic text data using a generative AI model (e.g., OpenAI GPT-3) and generates related topics (e.g., "market research," "prototype design," and "competitive analysis"). The input is thematic text data, and the output is a list of generated topics. The server sends this list back to the device.

[1191] Step 3:

[1192] View topics

[1193] The terminal displays the list of topics received from the server to the user. The input is the topic list data from the server, and the output is the topic list displayed on the terminal screen.

[1194] Step 4:

[1195] Select a topic and post

[1196] The user selects one topic from the displayed list (e.g., "Target Market Analysis"), and the terminal sends the data to the server. The input is the topic data selected by the user, and the output is the transmission of the selected topic data from the terminal to the server.

[1197] Step 5:

[1198] Question Generation

[1199] The server analyzes the received topic data using a generative AI model and generates relevant questions (e.g., "What are the major consumer groups?", "What is the market share by region?"). The input is the selected topic data, and the output is a list of generated questions. The server sends this list back to the device.

[1200] Step 6:

[1201] Show Questions

[1202] The terminal displays the list of questions received from the server to the user. The input is the question list data from the server, and the output is the question list displayed on the terminal screen.

[1203] Step 7:

[1204] Enter and send your message

[1205] During a discussion, a user inputs a statement into a terminal. The input statement is sent from the terminal to the server. The input is text data of the statement made by the user, and the output is the transmission of the text data from the terminal to the server.

[1206] Step 8:

[1207] Analysis and summary of speech content

[1208] The server analyzes the received speech using a generative AI model to extract key points and summaries. The input is the speech text data, and the output is summarized speech point data. The server then returns this summary data to the terminal.

[1209] Step 9:

[1210] View Summary

[1211] The terminal displays the summarized data received from the server to the user. The input is the summarized data from the server, and the output is the summarized data displayed on the screen of the terminal.

[1212] Step 10:

[1213] Monitor the progress of the discussion

[1214] The server monitors the progress of the discussion in real time and suggests next steps or new topics if the discussion strays from the set direction. The input is the current discussion status data, and the output is the proposed next steps or topic data. The server sends this data to the terminal.

[1215] Step 11:

[1216] View Suggestions

[1217] The terminal displays the proposed data received from the server to the user. The input is the proposed data from the server, and the output is the proposed data displayed on the screen of the terminal.

[1218] Step 12:

[1219] Time Management Settings

[1220] The user inputs the start time and scheduled time of the discussion into the terminal. The input time information is sent from the terminal to the server. The input is the start time and scheduled time data set by the user, and the output is the transmission of time information from the terminal to the server.

[1221] Step 13:

[1222] Time Management Practices

[1223] The server monitors the progress of the discussion in real time based on the time information received, and generates a time alert when the scheduled end time approaches. The input is the start time and scheduled time data, and the output is the generated time alert data. The server sends this time alert to the terminal.

[1224] Step 14:

[1225] Displaying time alerts

[1226] The terminal displays the time alert received from the server to the user. The input is the time alert data from the server, and the output is the time alert displayed on the terminal screen.

[1227] These processing steps enable the discussion facilitator AI to conduct discussions efficiently and smoothly.

[1228] (Application example 1)

[1229] 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."

[1230] Conventional discussions place a heavy burden on the facilitator, requiring a great deal of effort to progress and manage the discussion. Furthermore, discussions often go off track and time management is inadequate, making it difficult to hold efficient, high-quality discussions. In particular, in factories, efficiency and precision are required in discussions about production processes, quality control, and solving technical problems, but achieving this has been difficult. The present invention aims to solve these problems and provide a system that supports efficient and smooth discussions.

[1231] 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.

[1232] In this invention, the server includes a means for generating specific topics related to the theme of the discussion, a means for generating questions related to the generated topics, and a means for analyzing comments made during the discussion in real time and presenting summaries, thereby smoothing the progress of the discussion, reducing the burden on the facilitator, and enabling efficient, high-quality discussions.

[1233] A "topic" is a specific theme or subject that is brought up in a discussion or debate.

[1234] A "question" is a specific question related to the topic of discussion that is posed to deepen the discussion.

[1235] "Opinions" are the thoughts and opinions expressed by participants during a discussion.

[1236] The "direction of the discussion" indicates the overall guidelines and way forward for the discussion.

[1237] "Time management" refers to monitoring the start time, progress, and planned end time of a discussion and making appropriate adjustments.

[1238] "Generated Topics" are lists of related topics that are automatically generated based on the topic of the discussion.

[1239] "Related Questions" are a set of automatically generated questions related to the selected topic.

[1240] "Speech content" refers to what participants said during the discussion.

[1241] A "summary" is a summary of the main points or important information extracted from what was said during the discussion.

[1242] "Real-time analysis" refers to processing and analyzing data instantly while the discussion is taking place.

[1243] "Appropriate next steps" are specific actions or topics that should be taken next in the discussion.

[1244] "Time Alert" is a time warning that occurs based on the scheduled time of the discussion.

[1245] This invention is a system that uses a discussion facilitator AI to facilitate smooth discussion progress and reduce the burden on the facilitator. Specific embodiments will be described below.

[1246] The system mainly consists of three main components: a server, a terminal, and a user.

[1247] Hardware and Software

[1248] Hardware:

[1249] tablet device

[1250] Smart Glasses

[1251] software:

[1252] Cloud AI services (e.g., Google Cloud AI and AWS AI services)

[1253] Real-time Data Management System

[1254] Program processing

[1255] Users input the topic of discussion using a tablet or smart glasses. This topic is sent to the server via the device. The server uses a cloud AI service to analyze the topic and generate specific related topics. The generated topic list is then displayed on the device and presented to the user.

[1256] When the user selects one of the displayed topics, the device sends the selected topic to the server, which then uses the cloud AI service to generate a related question and returns it to the device, where it is displayed and presented to the user.

[1257] During the discussion, users input their comments via their devices. The inputted comments are sent to the server in real time, where cloud AI analyzes them and extracts key points and summaries. These summaries are displayed on the device and presented to the user. The server also constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to prevent the discussion from going off track. This information is also displayed on the device and presented to the user.

[1258] Users input the start time and expected duration of the discussion into their terminal. This is also sent to the server, which monitors the progress of the discussion in real time. Before the scheduled end time, a time alert is generated and sent to the terminal to notify the remaining time.

[1259] Specific examples

[1260] For example, if the topic "new product development" is entered, the following topics and questions will be generated:

[1261] Example of a topic-generating prompt:

[1262] Generate topics related to the theme "New Product Development".

[1263] This generates topics such as "market research," "prototype design," and "competitive analysis."

[1264] Example of a question-generating prompt:

[1265] Generate questions related to the topic "Market Research".

[1266] This generates questions such as, "What are the major consumer groups?" and "What is the market share by region?"

[1267] In this way, this system supports the progress of discussions, reduces the burden on facilitators, and enables efficient, high-quality discussions.

[1268] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1269] Step 1:

[1270] The user inputs the topic of discussion into a tablet device or smart glasses.

[1271] The input theme is sent from the terminal to the server. At this time, the theme is sent to the server as input data.

[1272] Step 2:

[1273] The server uses cloud AI services to analyze the received themes and generate specific related topics.

[1274] The generated topic list is returned from the server to the terminal.

[1275] Here, data processing involves extracting related topics from the theme, and generating a topic list as the output.

[1276] Step 3:

[1277] The user selects one topic from the topic list displayed on the terminal.

[1278] The selected topic is again sent from the terminal to the server, this time as selection data.

[1279] Step 4:

[1280] The server uses a cloud AI service to generate questions related to the received topic.

[1281] The generated question list is returned from the server to the terminal.

[1282] Here, data processing involves generating related questions from topics, and generating a question list as the output.

[1283] Step 5:

[1284] During the discussion, the user inputs each statement into the terminal.

[1285] The inputted remarks are sent to the server in real time.

[1286] At this time, the content of the statement is sent to the server as input data.

[1287] Step 6:

[1288] The server uses cloud AI to analyze the received comments in real time and extract key points and summaries.

[1289] The extracted gist is returned from the server to the terminal.

[1290] Here, data processing involves analyzing the content of the comments and generating a summary, and the main points are generated as the output.

[1291] Step 7:

[1292] The server constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to keep the discussion from going off track.

[1293] The content of the proposal is transmitted from the server to the terminal.

[1294] Here, data calculations are performed to monitor progress and propose next steps, and the proposals are generated as output.

[1295] Step 8:

[1296] The user inputs the start time and scheduled time of the discussion into the terminal.

[1297] Based on this, the server monitors the progress of the discussion in real time.

[1298] A time alert is generated before the scheduled end time and sent to the terminal.

[1299] Here, data calculations involve time management and alert generation, and a time alert is generated as the output.

[1300] 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.

[1301] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time, as well as recognizing the user's emotions. Specific embodiments are described below.

[1302] 1. Topic Suggestion

[1303] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific topics related to it. The generated topic list is sent to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server generates related topics such as "market research," "prototype design," and "competitive analysis," and displays them on the device.

[1304] 2. Question Generation

[1305] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[1306] 3. Summary of opinions

[1307] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[1308] 4. Setting the direction of the discussion

[1309] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[1310] 5. Time management

[1311] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[1312] 6. Emotion Engine

[1313] The emotion engine has the ability to analyze the user's voice and text input and determine emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[1314] With these functions, the discussion facilitator AI system of the present invention not only supports efficient and smooth discussion progress, but also flexibly responds to the user's emotional state, reducing the burden on the facilitator and improving the quality and efficiency of discussions.

[1315] The processing flow will be explained below.

[1316] Topic Suggestion

[1317] 1. Step 1:

[1318] The user inputs the topic of the discussion into the terminal.

[1319] 2. Step 2:

[1320] The terminal transmits the input theme to the server.

[1321] 3. Step 3:

[1322] The server receives the theme and generates related topics using an AI model.

[1323] 4. Step 4:

[1324] The server transmits the generated topic list to the terminal.

[1325] 5. Step 5:

[1326] The terminal displays the topic candidates to the user.

[1327] Question Generation

[1328] 1. Step 1:

[1329] The user selects one of the topic candidates presented on the terminal.

[1330] 2. Step 2:

[1331] The terminal sends the selected topic to the server.

[1332] 3. Step 3:

[1333] The server receives the topic and generates relevant questions using an AI model.

[1334] 4. Step 4:

[1335] The server transmits the generated question list to the terminal.

[1336] 5. Step 5:

[1337] The terminal displays the generated question to the user.

[1338] Summary of opinions

[1339] 1. Step 1:

[1340] The user inputs the content of the discussion into the terminal.

[1341] 2. Step 2:

[1342] The terminal transmits the inputted speech content to the server.

[1343] 3. Step 3:

[1344] The server analyzes what is said and generates key points and summaries.

[1345] 4. Step 4:

[1346] The server sends the generated gist to the device.

[1347] 5. Step 5:

[1348] The device displays a summary of the key points to the user.

[1349] Setting the direction of the discussion

[1350] 1. Step 1:

[1351] The server monitors the progress of the discussion in real time.

[1352] 2. Step 2:

[1353] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[1354] 3. Step 3:

[1355] The server sends the generated proposal to the terminal.

[1356] 4. Step 4:

[1357] The device displays the suggestions to the user.

[1358] time management

[1359] 1. Step 1:

[1360] The user inputs the start time and scheduled time of the discussion into the terminal.

[1361] 2. Step 2:

[1362] The terminal transmits the input time information to the server.

[1363] 3. Step 3:

[1364] The server monitors the progress and elapsed time in real time.

[1365] 4. Step 4:

[1366] The server generates a time alert when the scheduled time is about to expire.

[1367] 5. Step 5:

[1368] The server sends the generated time alert to the terminal.

[1369] 6. Step 6:

[1370] The device displays a time alert to the user, informing them of the time remaining.

[1371] Use of emotion engine

[1372] 1. Step 1:

[1373] During the discussion, the user inputs what is being said into the terminal by voice or text.

[1374] 2. Step 2:

[1375] The device sends the input voice and text data to the server.

[1376] 3. Step 3:

[1377] The server's emotion engine analyzes voice and text data to determine the user's emotions.

[1378] 4. Step 4:

[1379] The server generates appropriate feedback and suggestions based on the emotions determined by the emotion engine.

[1380] 5. Step 5:

[1381] Send server-generated feedback and suggestions to the device.

[1382] 6. Step 6:

[1383] The device displays feedback and suggestions to the user. For example, if the user shows signs of frustration, the server provides advice on how to stay calm and displays it on the device.

[1384] Through the above steps, the discussion facilitator AI system of the present invention, which is combined with an emotion engine, functions as a system that supports the progress of discussions efficiently and with consideration for emotional aspects.

[1385] Example 2

[1386] 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."

[1387] In modern discussions, differences of opinion among participants, deviations in the direction of the discussion, and poor time management are often problems. Furthermore, it is difficult to grasp the emotional state of participants and respond appropriately accordingly. A system that can solve these issues and enable efficient and smooth discussions is needed.

[1388] 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.

[1389] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing the user's emotions. This allows for efficient and smooth progress of the discussion. It also enables flexible responses according to the user's emotions, improving the quality and efficiency of the discussion.

[1390] The "means for suggesting topics" is a function that generates related topics based on a theme input by the user and displays them on the terminal.

[1391] The "means for generating questions" is a function for generating related questions based on a topic selected by the user and displaying them on the terminal.

[1392] "Means for summarizing opinions" is a function that analyzes the comments entered by users during a discussion, extracts the main points and summaries, and displays them on the device.

[1393] "A means of setting the direction of the discussion" is a function that monitors the progress of the discussion and suggests next steps or new topics to prevent the discussion from going off track.

[1394] The "means for managing time" is a function for managing the start time and scheduled time of a discussion, and generating a time alert before the scheduled time and displaying it on the terminal.

[1395] The "means for recognizing user emotions" is a function that analyzes the user's voice and text input, determines their emotions, and responds accordingly.

[1396] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, time management, and recognizing the user's emotions. Specific embodiments of the system are described below.

[1397] Topic Suggestion

[1398] The user inputs a discussion topic into the device. For example, they might input "new product development." The device sends this topic to the server, which analyzes the topic using a generative AI model. Based on the analysis results, it generates specific related topics. The generated topic list is sent to the device, which presents it to the user. For example, generated topics might include "market research," "prototype design," and "competitive analysis."

[1399] Example prompt sentence:

[1400] "I'd like to hold a discussion about new product development. Please suggest specific topics that are relevant."

[1401] Question Generation

[1402] The user selects one of the presented topics. For example, they may select "target market analysis." The selected topic is sent from the device to the server. The server uses a generative AI model to generate questions related to the selected topic. The generated list of questions is sent to the device, which then presents them to the user. For example, generated questions include "What are the major consumer groups?" and "What is the market share by region?"

[1403] Example prompt sentence:

[1404] "Generate relevant questions to drive the discussion about your target market analysis."

[1405] Summary of opinions

[1406] As the discussion progresses, users input their comments into their devices. These comments are then sent from the devices to the server. The server then uses a generative AI model to analyze the comments and extract key points and summaries. The extracted summaries are then sent to the devices, which then display them to the user. For example, if someone says, "Price and quality are the key factors in determining the target market for a new product," the summary will be "Factors in determining the target market: price, quality."

[1407] Setting the direction of the discussion

[1408] The server monitors the progress of the discussion in real time. To prevent the discussion from going off track, it suggests next steps or new topics based on the set direction. The suggestions are sent to the device, which then displays them to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[1409] time management

[1410] The user enters the start time and planned duration of the discussion into the terminal. For example, the start time is 10:00 and the planned duration is 60 minutes. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. For example, a time alert such as "10 minutes remaining" is generated 10 minutes before the planned end time. The terminal displays this alert to the user to inform them of the remaining time.

[1411] Emotion Engine

[1412] The emotion engine is a function that analyzes the user's voice and text input and determines emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[1413] As a result, the discussion facilitator AI system can support efficient and smooth discussions and respond flexibly to the user's emotional state. It functions as a system that reduces the burden on the facilitator and improves the quality and efficiency of discussions.

[1414] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1415] Step 1:

[1416] The user inputs the topic of discussion into the terminal. For example, they input "new product development." The terminal receives this input as data and sends it to the server. The input data is in text format.

[1417] Step 2:

[1418] The server analyzes the received theme data. The server uses a generative AI model to analyze the input theme and generate specific topics related to the theme. The generated topic list is formed as data. The generative AI model extracts topics using natural language processing technology.

[1419] Step 3:

[1420] The server sends the generated topic list to the terminal. The terminal receives this topic list as data and displays it to the user. The user selects one of the presented topics. Topic data is generated by selecting it.

[1421] Step 4:

[1422] The selected topic data is sent from the device to the server. The server then uses the generative AI model to generate questions based on the received topic data. The generated list of questions is then formed into data. For example, questions such as "What are the main consumer groups?" are generated from "target market analysis."

[1423] Step 5:

[1424] The server sends the generated question list to the terminal, which displays the question list to the user. To advance the discussion, the user expresses their opinions and thoughts based on the questions and inputs them as text into the terminal.

[1425] Step 6:

[1426] The device sends the user's speech as data to the server, which then analyzes the received speech using a generative AI model. Through this analysis, key points and summaries are extracted. Text mining technology is used to process the data.

[1427] Step 7:

[1428] The server sends the extracted summary data to the terminal, which then displays the received summary to the user, allowing the user to grasp the progress of the discussion.

[1429] Step 8:

[1430] The server monitors the progress of the discussion in real time. If the discussion goes off track, the server uses a generative AI model to suggest next steps or new topics. The suggestions are generated as data and sent to the device.

[1431] Step 9:

[1432] The device displays the suggestions received from the server to the user, helping to guide the discussion in the right direction.

[1433] Step 10:

[1434] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this input data to the server. The server monitors the progress of the discussion based on the received time data.

[1435] Step 11:

[1436] The server generates time alert data when the scheduled time approaches and sends it to the terminal. For example, an alert saying "10 minutes remaining" is generated 10 minutes before the scheduled end time.

[1437] Step 12:

[1438] The device displays the received time alert data to the user, allowing the user to grasp the remaining time and make appropriate progress.

[1439] Step 13:

[1440] The emotion engine collects the user's voice and text input as data and sends it from the device to the server, which then analyzes the received emotion data and determines the user's emotion.

[1441] Step 14:

[1442] The server then adjusts the discussion and suggestions based on the emotion data it has determined. For example, if a user shows signs of fatigue, it suggests taking a break.

[1443] Step 15:

[1444] The server sends the adjusted proposal to the device, which displays it to the user, allowing the user to take appropriate action.

[1445] (Application example 2)

[1446] 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."

[1447] In modern manufacturing sites, discussions are frequently held to address a variety of issues, including process efficiency, quality improvement, and safety management. However, factors that significantly reduce the efficiency of discussions include distraction, poor time management, and emotional changes among participants. There is a growing need for a system that can adequately resolve these issues and support efficient discussions.

[1448] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1449] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing users' emotions and adjusting the progress of the discussion and the content of suggestions. This prevents discussions from going off track, ensures appropriate time management, and enables smooth discussion management in accordance with the emotions of participants.

[1450] "Topic suggestions" are a way to start a discussion by generating specific, related topics based on a theme entered by the user.

[1451] "Question generation" is a means for users to generate specific questions related to a topic they have selected and deepen the discussion.

[1452] A "summary" is a method of summarizing each statement made during a discussion and extracting and presenting the main points and summaries.

[1453] "Setting the direction of the discussion" is a way to constantly monitor the progress of the discussion and suggest next steps or new topics based on the set direction to prevent the discussion from going off track.

[1454] "Time management" is a means of managing the start and scheduled time of a discussion and providing appropriate time alerts by monitoring progress in real time.

[1455] "Emotion recognition" is a means of analyzing a user's voice and text input, determining the user's emotional state, and adjusting the discussion progress and proposal content accordingly.

[1456] This invention is a system for supporting discussions in manufacturing sites, which proposes topics, generates questions, summarizes opinions, sets the direction of discussions, manages time, and recognizes emotions through communication between servers, terminals, and users.

[1457] 1. Topic Suggestion

[1458] First, the user inputs the topic of the discussion through the device, which then sends it to the server, which then uses a generative AI model (e.g., OpenAI's GPT-3 or GPT-4) to analyze the topic and generate specific related topics based on it. The generated topics are then sent to the device and presented to the user.

[1459] Examples:

[1460] When a user inputs the topic "process improvement," the server generates topics such as "quality improvement," "cost reduction," and "safety management," and displays them on the terminal.

[1461] Example prompt sentence:

[1462] "Please suggest suitable topics for discussion based on the theme 'Process Improvement'."

[1463] 2. Question Generation

[1464] When a user operates their device to select one of the generated topics, that topic is sent to the server, which uses the generative AI model to generate a question related to that topic and returns it to the device, which then presents the question to the user.

[1465] Examples:

[1466] If the user selects "Improve Quality," the server generates questions such as "In which process are quality problems occurring?" and "How can existing quality control methods be improved?" and displays them on the terminal.

[1467] Example prompt sentence:

[1468] "Generate questions related to the topic 'Quality Improvement'."

[1469] 3. Summary of opinions

[1470] During a discussion, users input their comments into their device. The device sends these comments to the server, which analyzes them using a generative AI model. The server extracts key points and summaries and returns them to the device, which then displays the summarized key points to the user.

[1471] Examples:

[1472] If someone says, "Automation of process 1 is necessary," or "The inspection system for process 3 should be strengthened," the server summarizes this as "Automation of process 1, strengthening of inspection system for process 3," and sends this to the terminal.

[1473] Example prompt sentence:

[1474] "Please summarize the main points of the following statement:..."

[1475] 4. Setting the direction of the discussion

[1476] The server constantly monitors the progress of the discussion and suggests next steps or new topics depending on the direction of the discussion, ensuring that the discussion proceeds smoothly without going off track. The suggested information is sent to the terminal and presented to the user.

[1477] Examples:

[1478] If the discussion on "quality improvement" veers off into "technical issues," the server will propose "next steps to improve quality" and display them on the terminal.

[1479] 5. Time management

[1480] When a user enters the start time and planned duration of a discussion into their device, this information is sent to the server. The server monitors the progress of the discussion in real time and generates a time alert and sends it to the device, for example, 10 minutes before the planned end time. The device then displays this time alert to the user, informing them of the remaining time.

[1481] Examples:

[1482] If the start time of the discussion is 10:00 and the scheduled duration is 60 minutes, the server will generate a time alert saying "10 minutes remaining" and display it on the terminal 10 minutes before the scheduled end time.

[1483] 6. Emotional Recognition

[1484] The emotion recognition engine analyzes the user's voice and text input to determine their emotions. Based on this information, the server adjusts the discussion progress and suggestions. If the user shows signs of frustration or fatigue, the server will suggest a break or adjust the pace of the discussion.

[1485] Examples:

[1486] If the user appears tired or irritated, the server will make suggestions such as "Take a 5-minute break."

[1487] This system supports efficient and smooth progress in process improvement discussions at manufacturing sites, and enables flexible responses based on the emotions of participants.

[1488] Hardware and software used:

[1489] AI model: OpenAI's GPT-3 or GPT-4

[1490] Server: High-performance server (e.g. AWS EC2, Google Cloud Compute Engine)

[1491] Device: Smartphone or tablet

[1492] This will significantly improve the quality and efficiency of discussions on the manufacturing floor.

[1493] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1494] Step 1:

[1495] A user inputs a topic for discussion into a terminal, and the terminal transmits this topic to a server.

[1496] Input: Theme (e.g. "Process Improvement")

[1497] Output: Theme data

[1498] Specific operation: Sends text entered by the user on the terminal to the server.

[1499] Step 2:

[1500] The server uses a generative AI model to analyze the input topic and generate specific related topics.

[1501] Input: Theme data

[1502] Output: Topic list

[1503] Specific operation: The topic is input into the generation AI model, and a topic is generated using the prompt, "Please suggest a suitable topic for discussion based on the topic 'Process Improvement'."

[1504] Step 3:

[1505] The server sends the generated topic list to the terminal, which then presents it to the user.

[1506] Input: Topic list

[1507] Output: A list of topics as they appear in the user interface

[1508] Specific operation: Receives a topic list from the server and displays it on the device screen.

[1509] Step 4:

[1510] The user selects one from a list of presented topics, and the terminal transmits the selection to the server.

[1511] Input: Selected Topic

[1512] Output: Selected topic data

[1513] What it does: Captures the user's selections and sends that information to the server.

[1514] Step 5:

[1515] The server generates a question based on the selected topic and returns the generated question to the terminal.

[1516] Input: Selected topic data

[1517] Output: Question list

[1518] Specific operation: The selected topic is input into the generative AI model, and questions are generated using the prompt, "Generate questions related to the topic 'Quality Improvement'."

[1519] Step 6:

[1520] The terminal presents the generated list of questions to the user.

[1521] Input: Question List

[1522] Output: A list of questions displayed in the user interface

[1523] Specific operation: Display a list of questions on the device screen.

[1524] Step 7:

[1525] During the discussion, users input comments into their terminals, and the terminals transmit these comments to the server.

[1526] Input: What you say

[1527] Output: Speech data

[1528] Specific operation: Captures the user's spoken text and sends it to the server.

[1529] Step 8:

[1530] The server analyzes the speech data, extracts the main points and summaries, and sends them to the terminal.

[1531] Input: Speech data

[1532] Output: Summary data

[1533] Specific operation: Speech data is input into a generative AI model, and a summary is generated using the prompt, "Please summarize the main points of the following utterance:..."

[1534] Step 9:

[1535] The terminal displays the summary data to the user.

[1536] Input: Summary data

[1537] Output: A summary that is displayed in the user interface

[1538] Specific behavior: Display a summary on the device screen.

[1539] Step 10:

[1540] The server monitors the progress of the discussion and suggests next steps or new topics when things go off track.

[1541] Input: Discussion progress data

[1542] Output: Suggested next steps and new topics

[1543] Specific behavior: Analyzes the progress, generates appropriate suggestions and sends them to the device.

[1544] Step 11:

[1545] The terminal presents the suggested information to the user.

[1546] Input: Suggest next steps or new topics

[1547] Output: Proposal displayed in the user interface

[1548] Specific behavior: Display suggestions on the device screen.

[1549] Step 12:

[1550] The user inputs the start time and scheduled time of the discussion into the terminal, which then transmits this to the server.

[1551] Input: Start time and Scheduled time

[1552] Output: Time data

[1553] Specific operation: The time information entered on the terminal is sent to the server.

[1554] Step 13:

[1555] The server monitors the progress in real time and generates a time alert before the scheduled time and sends it to the terminal.

[1556] Input: Time and progress data

[1557] Output: Time alert

[1558] Specific operation: Compare the progress with the scheduled time, and generate an alert saying "10 minutes remaining" 10 minutes before the scheduled end time and send it to the device.

[1559] Step 14:

[1560] The terminal displays a time alert to the user.

[1561] Input: Time Alert

[1562] Output: Time alert displayed in the user interface

[1563] Specific operation: Display a time alert on the device screen.

[1564] Step 15:

[1565] The emotion recognition engine analyzes the user's voice and text input to determine their emotions.

[1566] Input: Audio or text data

[1567] Output: Emotion data

[1568] Specific behavior: Analyzes the user's voice tone and text content to determine their emotional status.

[1569] Step 16:

[1570] The server adjusts the progress of the discussion and the content of proposals based on the emotional data and sends them to the terminal.

[1571] Input: Emotion data

[1572] Output: Coordinated progress or proposal

[1573] Specific operation: Analyzes emotional data and generates an adjustment, such as "Take a 5-minute break," and sends it to the device.

[1574] Step 17:

[1575] The terminal displays the adjusted progress and suggestions to the user.

[1576] Input: Adjusted progress or proposal

[1577] Output: The adjusted progress or suggestions displayed in the user interface

[1578] Specific behavior: Display adjusted progress or suggestions on the device screen.

[1579] 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.

[1580] 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.

[1581] 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.

[1582] [Fourth embodiment]

[1583] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1584] 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.

[1585] 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).

[1586] 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.

[1587] 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.

[1588] 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).

[1589] 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.

[1590] 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.

[1591] 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.

[1592] 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.

[1593] 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.

[1594] 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.

[1595] 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."

[1596] The discussion facilitator AI of the present invention is a system that proposes topics, generates questions, summarizes opinions, sets the direction of the discussion, and manages time. Specific embodiments will be described below.

[1597] 1. Topic Suggestion

[1598] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific related topics. The server then returns the generated topic list to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server will generate related topics such as "market research," "prototype design," and "competitive analysis" and display them on the device.

[1599] 2. Question Generation

[1600] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[1601] 3. Summary of opinions

[1602] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[1603] 4. Setting the direction of the discussion

[1604] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[1605] 5. Time management

[1606] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[1607] With these functions, the discussion facilitator AI of the present invention supports efficient and smooth discussion progress, reduces the burden on the facilitator, and improves the quality and efficiency of discussions.

[1608] The processing flow will be explained below.

[1609] Topic Suggestion

[1610] 1. Step 1:

[1611] The user inputs the topic of the discussion into the terminal.

[1612] 2. Step 2:

[1613] The terminal transmits the input theme to the server.

[1614] 3. Step 3:

[1615] The server receives the theme and generates related topics using an AI model.

[1616] 4. Step 4:

[1617] The server transmits the generated topic list to the terminal.

[1618] 5. Step 5:

[1619] The terminal displays the topic candidates to the user.

[1620] Question Generation

[1621] 1. Step 1:

[1622] The user selects one of the topic candidates presented on the terminal.

[1623] 2. Step 2:

[1624] The terminal sends the selected topic to the server.

[1625] 3. Step 3:

[1626] The server receives the topic and generates relevant questions using an AI model.

[1627] 4. Step 4:

[1628] The server transmits the generated question list to the terminal.

[1629] 5. Step 5:

[1630] The terminal displays the generated question to the user.

[1631] Summary of opinions

[1632] 1. Step 1:

[1633] The user inputs the content of the discussion into the terminal.

[1634] 2. Step 2:

[1635] The terminal transmits the inputted speech content to the server.

[1636] 3. Step 3:

[1637] The server analyzes what is said and generates key points and summaries.

[1638] 4. Step 4:

[1639] The server sends the generated gist to the device.

[1640] 5. Step 5:

[1641] The device displays a summary of the key points to the user.

[1642] Setting the direction of the discussion

[1643] 1. Step 1:

[1644] The server monitors the progress of the discussion in real time.

[1645] 2. Step 2:

[1646] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[1647] 3. Step 3:

[1648] The server sends the generated proposal to the terminal.

[1649] 4. Step 4:

[1650] The device displays the suggestions to the user.

[1651] time management

[1652] 1. Step 1:

[1653] The user inputs the start time and scheduled time of the discussion into the terminal.

[1654] 2. Step 2:

[1655] The terminal transmits the input time information to the server.

[1656] 3. Step 3:

[1657] The server monitors the progress and elapsed time in real time.

[1658] 4. Step 4:

[1659] The server generates a time alert when the scheduled time is about to expire.

[1660] 5. Step 5:

[1661] The server sends the generated time alert to the terminal.

[1662] 6. Step 6:

[1663] The device displays a time alert to the user, informing them of the time remaining.

[1664] Through the above steps, the discussion facilitator AI of the present invention functions as a system that supports the efficient and smooth progress of discussions.

[1665] Example 1

[1666] 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."

[1667] With conventional discussion systems, it was difficult to efficiently manage the entire discussion, including proposing topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time. Furthermore, since the facilitator had to take on all of these tasks, it placed a heavy burden on them, and there was a risk that the quality and efficiency of the discussion would decline.

[1668] 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.

[1669] In this invention, the server includes means for receiving a theme input by a user and generating related topics, means for generating questions based on the topic selected by the user, means for summarizing comments made during the discussion, means for monitoring the progress of the discussion and suggesting a direction, and means for managing the time of the discussion, thereby enabling the discussion to proceed efficiently and smoothly.

[1670] The "topic entered by the user" is information that the user enters into the terminal as the subject or topic of the discussion.

[1671] The "means for generating relevant topics" refers to a method and apparatus that uses a generative AI model to create specific topics useful for discussion based on a theme entered by a user.

[1672] A "means for generating questions" is a method and apparatus that uses a generative AI model to create relevant questions based on a user-selected topic.

[1673] The "means for summarizing speech content" refers to a method and device for analyzing speech content entered by users during a discussion, extracting the main points and important matters, and summarizing them in a concise manner.

[1674] "Means for monitoring the progress of the discussion and suggesting the direction" refers to a method and device that constantly monitors the current state of the discussion and appropriately suggests the next step or new topic based on the set direction of the discussion.

[1675] The "means for managing the discussion time" refers to a method and device for monitoring the progress of a discussion in real time based on the start time and scheduled time set by the user, and generating appropriate time alerts to notify the user.

[1676] The discussion facilitator AI of the present invention is a system that supports the highly efficient and smooth progress of discussions. An embodiment of this system will be specifically described below.

[1677] 1. Receive a topic entered by the user and generate related topics

[1678] The user inputs a discussion topic (e.g., "new product development") into the device. The device then sends this topic to the server, which uses a generative AI model (e.g., OpenAI GPT-3) to analyze the topic and generate specific related topics (e.g., "market research," "prototype design," "competitive analysis").

[1679] 2. Generate questions based on user-selected topics

[1680] When a user selects one of the generated topics (e.g., "Target Market Analysis"), the device sends the selected topic to the server, which uses the generative AI model to generate questions related to the selected topic (e.g., "What are the major consumer groups?", "What is the market share by region?").

[1681] 3. Summarize what was said during the discussion

[1682] During a discussion, users input their comments into their device. The device then sends the comments to the server. The server uses a generative AI model to analyze the comments and extract key points and summaries. The device then displays the summarized points to the user (e.g., "Factors that determine target market: price, quality").

[1683] 4. Monitor the progress of the discussion and suggest direction.

[1684] The server monitors the progress of the discussion in real time and, if the discussion deviates from the set direction, suggests next steps or new topics (e.g., "Next steps to advance market research"). The server sends the suggestions to the device and displays them to the user.

[1685] 5. Manage the discussion time

[1686] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert (e.g., "10 minutes remaining") 10 minutes before the planned end time and sends it to the terminal. The terminal displays this time alert to the user.

[1687] Examples of concrete examples and prompts

[1688] 1. Receive a topic entered by the user and generate related topics

[1689] User Input: "New Product Development"

[1690] Example prompt: "Please suggest some specific topics related to new product development."

[1691] 2. Generate questions based on user-selected topics

[1692] User Input: "Target Market Analysis"

[1693] Example prompt: "Generate questions related to target market analysis."

[1694] 3. Summarize what was said during the discussion

[1695] User Input: "Price and quality are key factors in determining the target market for a new product."

[1696] Example prompt: "Summarize the main points from this statement."

[1697] 4. Suggest a direction for the discussion

[1698] Surveillance Systems: "The discussion has gone off track"

[1699] Example prompt: "Please suggest next steps to further your market research."

[1700] 5. Manage the discussion time

[1701] User input: "Discussion start time: 10:00, scheduled duration: 60 minutes"

[1702] Example prompt: "Generate a notification 10 minutes before the time is up."

[1703] These embodiments enable the present invention to improve the efficiency and quality of discussions.

[1704] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1705] Step 1:

[1706] Enter and submit your theme

[1707] The user inputs the topic of the discussion (e.g., "new product development") into the terminal. The input topic is sent from the terminal to the server. The input is the text data of the topic by the user, and the output is the transmission of the text data of the topic from the terminal to the server.

[1708] Step 2:

[1709] Theme analysis and topic generation

[1710] The server analyzes the received thematic text data using a generative AI model (e.g., OpenAI GPT-3) and generates related topics (e.g., "market research," "prototype design," and "competitive analysis"). The input is thematic text data, and the output is a list of generated topics. The server sends this list back to the device.

[1711] Step 3:

[1712] View topics

[1713] The terminal displays the list of topics received from the server to the user. The input is the topic list data from the server, and the output is the topic list displayed on the terminal screen.

[1714] Step 4:

[1715] Select a topic and post

[1716] The user selects one topic from the displayed list (e.g., "Target Market Analysis"), and the terminal sends the data to the server. The input is the topic data selected by the user, and the output is the transmission of the selected topic data from the terminal to the server.

[1717] Step 5:

[1718] Question Generation

[1719] The server analyzes the received topic data using a generative AI model and generates relevant questions (e.g., "What are the major consumer groups?", "What is the market share by region?"). The input is the selected topic data, and the output is a list of generated questions. The server sends this list back to the device.

[1720] Step 6:

[1721] Show Questions

[1722] The terminal displays the list of questions received from the server to the user. The input is the question list data from the server, and the output is the question list displayed on the terminal screen.

[1723] Step 7:

[1724] Enter and send your message

[1725] During a discussion, a user inputs a statement into a terminal. The input statement is sent from the terminal to the server. The input is text data of the statement made by the user, and the output is the transmission of the text data from the terminal to the server.

[1726] Step 8:

[1727] Analysis and summary of speech content

[1728] The server analyzes the received speech using a generative AI model to extract key points and summaries. The input is the speech text data, and the output is summarized speech point data. The server then returns this summary data to the terminal.

[1729] Step 9:

[1730] View Summary

[1731] The terminal displays the summarized data received from the server to the user. The input is the summarized data from the server, and the output is the summarized data displayed on the screen of the terminal.

[1732] Step 10:

[1733] Monitor the progress of the discussion

[1734] The server monitors the progress of the discussion in real time and suggests next steps or new topics if the discussion strays from the set direction. The input is the current discussion status data, and the output is the proposed next steps or topic data. The server sends this data to the terminal.

[1735] Step 11:

[1736] View Suggestions

[1737] The terminal displays the proposed data received from the server to the user. The input is the proposed data from the server, and the output is the proposed data displayed on the screen of the terminal.

[1738] Step 12:

[1739] Time Management Settings

[1740] The user inputs the start time and scheduled time of the discussion into the terminal. The input time information is sent from the terminal to the server. The input is the start time and scheduled time data set by the user, and the output is the transmission of time information from the terminal to the server.

[1741] Step 13:

[1742] Time Management Practices

[1743] The server monitors the progress of the discussion in real time based on the time information received, and generates a time alert when the scheduled end time approaches. The input is the start time and scheduled time data, and the output is the generated time alert data. The server sends this time alert to the terminal.

[1744] Step 14:

[1745] Displaying time alerts

[1746] The terminal displays the time alert received from the server to the user. The input is the time alert data from the server, and the output is the time alert displayed on the terminal screen.

[1747] These processing steps enable the discussion facilitator AI to conduct discussions efficiently and smoothly.

[1748] (Application example 1)

[1749] 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."

[1750] Conventional discussions place a heavy burden on the facilitator, requiring a great deal of effort to progress and manage the discussion. Furthermore, discussions often go off track and time management is inadequate, making it difficult to hold efficient, high-quality discussions. In particular, in factories, efficiency and precision are required in discussions about production processes, quality control, and solving technical problems, but achieving this has been difficult. The present invention aims to solve these problems and provide a system that supports efficient and smooth discussions.

[1751] 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.

[1752] In this invention, the server includes a means for generating specific topics related to the theme of the discussion, a means for generating questions related to the generated topics, and a means for analyzing comments made during the discussion in real time and presenting summaries, thereby smoothing the progress of the discussion, reducing the burden on the facilitator, and enabling efficient, high-quality discussions.

[1753] A "topic" is a specific theme or subject that is brought up in a discussion or debate.

[1754] A "question" is a specific question related to the topic of discussion that is posed to deepen the discussion.

[1755] "Opinions" are the thoughts and opinions expressed by participants during a discussion.

[1756] The "direction of the discussion" indicates the overall guidelines and way forward for the discussion.

[1757] "Time management" refers to monitoring the start time, progress, and planned end time of a discussion and making appropriate adjustments.

[1758] "Generated Topics" are lists of related topics that are automatically generated based on the topic of the discussion.

[1759] "Related Questions" are a set of automatically generated questions related to the selected topic.

[1760] "Speech content" refers to what participants said during the discussion.

[1761] A "summary" is a summary of the main points or important information extracted from what was said during the discussion.

[1762] "Real-time analysis" refers to processing and analyzing data instantly while the discussion is taking place.

[1763] "Appropriate next steps" are specific actions or topics that should be taken next in the discussion.

[1764] "Time Alert" is a time warning that occurs based on the scheduled time of the discussion.

[1765] This invention is a system that uses a discussion facilitator AI to facilitate smooth discussion progress and reduce the burden on the facilitator. Specific embodiments will be described below.

[1766] The system mainly consists of three main components: a server, a terminal, and a user.

[1767] Hardware and Software

[1768] Hardware:

[1769] tablet device

[1770] Smart Glasses

[1771] software:

[1772] Cloud AI services (e.g., Google Cloud AI and AWS AI services)

[1773] Real-time Data Management System

[1774] Program processing

[1775] Users input the topic of discussion using a tablet or smart glasses. This topic is sent to the server via the device. The server uses a cloud AI service to analyze the topic and generate specific related topics. The generated topic list is then displayed on the device and presented to the user.

[1776] When the user selects one of the displayed topics, the device sends the selected topic to the server, which then uses the cloud AI service to generate a related question and returns it to the device, where it is displayed and presented to the user.

[1777] During the discussion, users input their comments via their devices. The inputted comments are sent to the server in real time, where cloud AI analyzes them and extracts key points and summaries. These summaries are displayed on the device and presented to the user. The server also constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to prevent the discussion from going off track. This information is also displayed on the device and presented to the user.

[1778] Users input the start time and expected duration of the discussion into their terminal. This is also sent to the server, which monitors the progress of the discussion in real time. Before the scheduled end time, a time alert is generated and sent to the terminal to notify the remaining time.

[1779] Specific examples

[1780] For example, if the topic "new product development" is entered, the following topics and questions will be generated:

[1781] Example of a topic-generating prompt:

[1782] Generate topics related to the theme "New Product Development".

[1783] This generates topics such as "market research," "prototype design," and "competitive analysis."

[1784] Example of a question-generating prompt:

[1785] Generate questions related to the topic "Market Research".

[1786] This generates questions such as, "What are the major consumer groups?" and "What is the market share by region?"

[1787] In this way, this system supports the progress of discussions, reduces the burden on facilitators, and enables efficient, high-quality discussions.

[1788] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1789] Step 1:

[1790] The user inputs the topic of discussion into a tablet device or smart glasses.

[1791] The input theme is sent from the terminal to the server. At this time, the theme is sent to the server as input data.

[1792] Step 2:

[1793] The server uses cloud AI services to analyze the received themes and generate specific related topics.

[1794] The generated topic list is returned from the server to the terminal.

[1795] Here, data processing involves extracting related topics from the theme, and generating a topic list as the output.

[1796] Step 3:

[1797] The user selects one topic from the topic list displayed on the terminal.

[1798] The selected topic is again sent from the terminal to the server, this time as selection data.

[1799] Step 4:

[1800] The server uses a cloud AI service to generate questions related to the received topic.

[1801] The generated question list is returned from the server to the terminal.

[1802] Here, data processing involves generating related questions from topics, and generating a question list as the output.

[1803] Step 5:

[1804] During the discussion, the user inputs each statement into the terminal.

[1805] The inputted remarks are sent to the server in real time.

[1806] At this time, the content of the statement is sent to the server as input data.

[1807] Step 6:

[1808] The server uses cloud AI to analyze the received comments in real time and extract key points and summaries.

[1809] The extracted gist is returned from the server to the terminal.

[1810] Here, data processing involves analyzing the content of the comments and generating a summary, and the main points are generated as the output.

[1811] Step 7:

[1812] The server constantly monitors the progress of the discussion and suggests appropriate next steps or new topics to keep the discussion from going off track.

[1813] The content of the proposal is transmitted from the server to the terminal.

[1814] Here, data calculations are performed to monitor progress and propose next steps, and the proposals are generated as output.

[1815] Step 8:

[1816] The user inputs the start time and scheduled time of the discussion into the terminal.

[1817] Based on this, the server monitors the progress of the discussion in real time.

[1818] A time alert is generated before the scheduled end time and sent to the terminal.

[1819] Here, data calculations involve time management and alert generation, and a time alert is generated as the output.

[1820] 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.

[1821] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, and managing time, as well as recognizing the user's emotions. Specific embodiments are described below.

[1822] 1. Topic Suggestion

[1823] When a user enters a topic for discussion, the device sends the topic to the server. The server uses an AI model to analyze the topic and generate specific topics related to it. The generated topic list is sent to the device, which then presents it to the user. For example, if a user enters the topic "new product development," the server generates related topics such as "market research," "prototype design," and "competitive analysis," and displays them on the device.

[1824] 2. Question Generation

[1825] After the user operates the device to select one of the generated topics, the device sends the selected topic to the server. The server uses an AI model to generate questions related to the topic and returns them to the device. The device then presents the questions to the user. For example, if the user selects the topic "Target Market Analysis," the server generates questions such as "What are the major consumer groups?" and "What is the market share by region?" and displays them on the device.

[1826] 3. Summary of opinions

[1827] During the discussion, users input each statement through their device. The device sends these statements to the server, which analyzes them using an AI model. It extracts key points and summaries and returns them to the device. The device then displays the summarized key points to the user. For example, if one of the discussion points is, "Price and quality are the key factors in determining the target market for a new product," the server summarizes this and sends it to the device. The device then displays, "Factors in determining the target market: Price, quality."

[1828] 4. Setting the direction of the discussion

[1829] The server constantly monitors the progress of the discussion and suggests next steps or new topics based on the set direction to prevent the discussion from going off track. This information is sent to the device, which then displays it to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[1830] 5. Time management

[1831] When a user enters the start time and planned duration of a discussion into a terminal, the terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. The terminal displays the time alert to the user to inform them of the remaining time. For example, if the start time of a discussion is 10:00 and the planned duration is 60 minutes, the server will generate a time alert such as "10 minutes remaining" 10 minutes before the planned end time and display it on the terminal.

[1832] 6. Emotion Engine

[1833] The emotion engine has the ability to analyze the user's voice and text input and determine emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[1834] With these functions, the discussion facilitator AI system of the present invention not only supports efficient and smooth discussion progress, but also flexibly responds to the user's emotional state, reducing the burden on the facilitator and improving the quality and efficiency of discussions.

[1835] The processing flow will be explained below.

[1836] Topic Suggestion

[1837] 1. Step 1:

[1838] The user inputs the topic of the discussion into the terminal.

[1839] 2. Step 2:

[1840] The terminal transmits the input theme to the server.

[1841] 3. Step 3:

[1842] The server receives the theme and generates related topics using an AI model.

[1843] 4. Step 4:

[1844] The server transmits the generated topic list to the terminal.

[1845] 5. Step 5:

[1846] The terminal displays the topic candidates to the user.

[1847] Question Generation

[1848] 1. Step 1:

[1849] The user selects one of the topic candidates presented on the terminal.

[1850] 2. Step 2:

[1851] The terminal sends the selected topic to the server.

[1852] 3. Step 3:

[1853] The server receives the topic and generates relevant questions using an AI model.

[1854] 4. Step 4:

[1855] The server transmits the generated question list to the terminal.

[1856] 5. Step 5:

[1857] The terminal displays the generated question to the user.

[1858] Summary of opinions

[1859] 1. Step 1:

[1860] The user inputs the content of the discussion into the terminal.

[1861] 2. Step 2:

[1862] The terminal transmits the inputted speech content to the server.

[1863] 3. Step 3:

[1864] The server analyzes what is said and generates key points and summaries.

[1865] 4. Step 4:

[1866] The server sends the generated gist to the device.

[1867] 5. Step 5:

[1868] The device displays a summary of the key points to the user.

[1869] Setting the direction of the discussion

[1870] 1. Step 1:

[1871] The server monitors the progress of the discussion in real time.

[1872] 2. Step 2:

[1873] The server generates proposals that fit into pre-defined directions to keep the discussion on track.

[1874] 3. Step 3:

[1875] The server sends the generated proposal to the terminal.

[1876] 4. Step 4:

[1877] The device displays the suggestions to the user.

[1878] time management

[1879] 1. Step 1:

[1880] The user inputs the start time and scheduled time of the discussion into the terminal.

[1881] 2. Step 2:

[1882] The terminal transmits the input time information to the server.

[1883] 3. Step 3:

[1884] The server monitors the progress and elapsed time in real time.

[1885] 4. Step 4:

[1886] The server generates a time alert when the scheduled time is about to expire.

[1887] 5. Step 5:

[1888] The server sends the generated time alert to the terminal.

[1889] 6. Step 6:

[1890] The device displays a time alert to the user, informing them of the time remaining.

[1891] Use of emotion engine

[1892] 1. Step 1:

[1893] During the discussion, the user inputs what is being said into the terminal by voice or text.

[1894] 2. Step 2:

[1895] The device sends the input voice and text data to the server.

[1896] 3. Step 3:

[1897] The server's emotion engine analyzes voice and text data to determine the user's emotions.

[1898] 4. Step 4:

[1899] The server generates appropriate feedback and suggestions based on the emotions determined by the emotion engine.

[1900] 5. Step 5:

[1901] Send server-generated feedback and suggestions to the device.

[1902] 6. Step 6:

[1903] The device displays feedback and suggestions to the user. For example, if the user shows signs of frustration, the server provides advice on how to stay calm and displays it on the device.

[1904] Through the above steps, the discussion facilitator AI system of the present invention, which is combined with an emotion engine, functions as a system that supports the progress of discussions efficiently and with consideration for emotional aspects.

[1905] Example 2

[1906] 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."

[1907] In modern discussions, differences of opinion among participants, deviations in the direction of the discussion, and poor time management are often problems. Furthermore, it is difficult to grasp the emotional state of participants and respond appropriately accordingly. A system that can solve these issues and enable efficient and smooth discussions is needed.

[1908] 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.

[1909] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing the user's emotions. This allows for efficient and smooth progress of the discussion. It also enables flexible responses according to the user's emotions, improving the quality and efficiency of the discussion.

[1910] The "means for suggesting topics" is a function that generates related topics based on a theme input by the user and displays them on the terminal.

[1911] The "means for generating questions" is a function for generating related questions based on a topic selected by the user and displaying them on the terminal.

[1912] "Means for summarizing opinions" is a function that analyzes the comments entered by users during a discussion, extracts the main points and summaries, and displays them on the device.

[1913] "A means of setting the direction of the discussion" is a function that monitors the progress of the discussion and suggests next steps or new topics to prevent the discussion from going off track.

[1914] The "means for managing time" is a function for managing the start time and scheduled time of a discussion, and generating a time alert before the scheduled time and displaying it on the terminal.

[1915] The "means for recognizing user emotions" is a function that analyzes the user's voice and text input, determines their emotions, and responds accordingly.

[1916] The discussion facilitator AI system of the present invention is a system that includes functions for suggesting topics, generating questions, summarizing opinions, setting the direction of the discussion, time management, and recognizing the user's emotions. Specific embodiments of the system are described below.

[1917] Topic Suggestion

[1918] The user inputs a discussion topic into the device. For example, they might input "new product development." The device sends this topic to the server, which analyzes the topic using a generative AI model. Based on the analysis results, it generates specific related topics. The generated topic list is sent to the device, which presents it to the user. For example, generated topics might include "market research," "prototype design," and "competitive analysis."

[1919] Example prompt sentence:

[1920] "I'd like to hold a discussion about new product development. Please suggest specific topics that are relevant."

[1921] Question Generation

[1922] The user selects one of the presented topics. For example, they may select "target market analysis." The selected topic is sent from the device to the server. The server uses a generative AI model to generate questions related to the selected topic. The generated list of questions is sent to the device, which then presents them to the user. For example, generated questions include "What are the major consumer groups?" and "What is the market share by region?"

[1923] Example prompt sentence:

[1924] "Generate relevant questions to drive the discussion about your target market analysis."

[1925] Summary of opinions

[1926] As the discussion progresses, users input their comments into their devices. These comments are then sent from the devices to the server. The server then uses a generative AI model to analyze the comments and extract key points and summaries. The extracted summaries are then sent to the devices, which then display them to the user. For example, if someone says, "Price and quality are the key factors in determining the target market for a new product," the summary will be "Factors in determining the target market: price, quality."

[1927] Setting the direction of the discussion

[1928] The server monitors the progress of the discussion in real time. To prevent the discussion from going off track, it suggests next steps or new topics based on the set direction. The suggestions are sent to the device, which then displays them to the user. For example, if the discussion veers from "market research" to "technical challenges," the server will suggest "next steps to advance market research" and display them on the device.

[1929] time management

[1930] The user enters the start time and planned duration of the discussion into the terminal. For example, the start time is 10:00 and the planned duration is 60 minutes. The terminal sends this to the server. The server monitors the progress of the discussion in real time and generates a time alert before the planned duration and sends it to the terminal. For example, a time alert such as "10 minutes remaining" is generated 10 minutes before the planned end time. The terminal displays this alert to the user to inform them of the remaining time.

[1931] Emotion Engine

[1932] The emotion engine is a function that analyzes the user's voice and text input and determines emotions. For example, it can recognize emotions such as "joy," "anger," and "sadness" from the content of the text entered by the user and the tone of the voice. Based on this information, the server can adjust the progress of the discussion and the content of its suggestions. For example, if the user appears tired or irritated, the server can suggest a break or adjust the tempo of the discussion.

[1933] As a result, the discussion facilitator AI system can support efficient and smooth discussions and respond flexibly to the user's emotional state. It functions as a system that reduces the burden on the facilitator and improves the quality and efficiency of discussions.

[1934] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1935] Step 1:

[1936] The user inputs the topic of discussion into the terminal. For example, they input "new product development." The terminal receives this input as data and sends it to the server. The input data is in text format.

[1937] Step 2:

[1938] The server analyzes the received theme data. The server uses a generative AI model to analyze the input theme and generate specific topics related to the theme. The generated topic list is formed as data. The generative AI model extracts topics using natural language processing technology.

[1939] Step 3:

[1940] The server sends the generated topic list to the terminal. The terminal receives this topic list as data and displays it to the user. The user selects one of the presented topics. Topic data is generated by selecting it.

[1941] Step 4:

[1942] The selected topic data is sent from the device to the server. The server then uses the generative AI model to generate questions based on the received topic data. The generated list of questions is then formed into data. For example, questions such as "What are the main consumer groups?" are generated from "target market analysis."

[1943] Step 5:

[1944] The server sends the generated question list to the terminal, which displays the question list to the user. To advance the discussion, the user expresses their opinions and thoughts based on the questions and inputs them as text into the terminal.

[1945] Step 6:

[1946] The device sends the user's speech as data to the server, which then analyzes the received speech using a generative AI model. Through this analysis, key points and summaries are extracted. Text mining technology is used to process the data.

[1947] Step 7:

[1948] The server sends the extracted summary data to the terminal, which then displays the received summary to the user, allowing the user to grasp the progress of the discussion.

[1949] Step 8:

[1950] The server monitors the progress of the discussion in real time. If the discussion goes off track, the server uses a generative AI model to suggest next steps or new topics. The suggestions are generated as data and sent to the device.

[1951] Step 9:

[1952] The device displays the suggestions received from the server to the user, helping to guide the discussion in the right direction.

[1953] Step 10:

[1954] The user inputs the start time and planned duration of the discussion into the terminal. The terminal sends this input data to the server. The server monitors the progress of the discussion based on the received time data.

[1955] Step 11:

[1956] The server generates time alert data when the scheduled time approaches and sends it to the terminal. For example, an alert saying "10 minutes remaining" is generated 10 minutes before the scheduled end time.

[1957] Step 12:

[1958] The device displays the received time alert data to the user, allowing the user to grasp the remaining time and make appropriate progress.

[1959] Step 13:

[1960] The emotion engine collects the user's voice and text input as data and sends it from the device to the server, which then analyzes the received emotion data and determines the user's emotion.

[1961] Step 14:

[1962] The server then adjusts the discussion and suggestions based on the emotion data it has determined. For example, if a user shows signs of fatigue, it suggests taking a break.

[1963] Step 15:

[1964] The server sends the adjusted proposal to the device, which displays it to the user, allowing the user to take appropriate action.

[1965] (Application example 2)

[1966] 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."

[1967] In modern manufacturing sites, discussions are frequently held to address a variety of issues, including process efficiency, quality improvement, and safety management. However, factors that significantly reduce the efficiency of discussions include distraction, poor time management, and emotional changes among participants. There is a growing need for a system that can adequately resolve these issues and support efficient discussions.

[1968] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1969] In this invention, the server includes a means for suggesting topics, a means for generating questions, a means for summarizing opinions, a means for setting the direction of the discussion, a means for managing time, and a means for recognizing users' emotions and adjusting the progress of the discussion and the content of suggestions. This prevents discussions from going off track, ensures appropriate time management, and enables smooth discussion management in accordance with the emotions of participants.

[1970] "Topic suggestions" are a way to start a discussion by generating specific, related topics based on a theme entered by the user.

[1971] "Question generation" is a means for users to generate specific questions related to a topic they have selected and deepen the discussion.

[1972] A "summary" is a method of summarizing each statement made during a discussion and extracting and presenting the main points and summaries.

[1973] "Setting the direction of the discussion" is a way to constantly monitor the progress of the discussion and suggest next steps or new topics based on the set direction to prevent the discussion from going off track.

[1974] "Time management" is a means of managing the start and scheduled time of a discussion and providing appropriate time alerts by monitoring progress in real time.

[1975] "Emotion recognition" is a means of analyzing a user's voice and text input, determining the user's emotional state, and adjusting the discussion progress and proposal content accordingly.

[1976] This invention is a system for supporting discussions in manufacturing sites, which proposes topics, generates questions, summarizes opinions, sets the direction of discussions, manages time, and recognizes emotions through communication between servers, terminals, and users.

[1977] 1. Topic Suggestion

[1978] First, the user inputs the topic of the discussion through the device, which then sends it to the server, which then uses a generative AI model (e.g., OpenAI's GPT-3 or GPT-4) to analyze the topic and generate specific related topics based on it. The generated topics are then sent to the device and presented to the user.

[1979] Examples:

[1980] When a user inputs the topic "process improvement," the server generates topics such as "quality improvement," "cost reduction," and "safety management," and displays them on the terminal.

[1981] Example prompt sentence:

[1982] "Please suggest suitable topics for discussion based on the theme 'Process Improvement'."

[1983] 2. Question Generation

[1984] When a user operates their device to select one of the generated topics, that topic is sent to the server, which uses the generative AI model to generate a question related to that topic and returns it to the device, which then presents the question to the user.

[1985] Examples:

[1986] If the user selects "Improve Quality," the server generates questions such as "In which process are quality problems occurring?" and "How can existing quality control methods be improved?" and displays them on the terminal.

[1987] Example prompt sentence:

[1988] "Generate questions related to the topic 'Quality Improvement'."

[1989] 3. Summary of opinions

[1990] During a discussion, users input their comments into their device. The device sends these comments to the server, which analyzes them using a generative AI model. The server extracts key points and summaries and returns them to the device, which then displays the summarized key points to the user.

[1991] Examples:

[1992] If someone says, "Automation of process 1 is necessary," or "The inspection system for process 3 should be strengthened," the server summarizes this as "Automation of process 1, strengthening of inspection system for process 3," and sends this to the terminal.

[1993] Example prompt sentence:

[1994] "Please summarize the main points of the following statement:..."

[1995] 4. Setting the direction of the discussion

[1996] The server constantly monitors the progress of the discussion and suggests next steps or new topics depending on the direction of the discussion, ensuring that the discussion proceeds smoothly without going off track. The suggested information is sent to the terminal and presented to the user.

[1997] Examples:

[1998] If the discussion on "quality improvement" veers off into "technical issues," the server will propose "next steps to improve quality" and display them on the terminal.

[1999] 5. Time management

[2000] When a user enters the start time and planned duration of a discussion into their device, this information is sent to the server. The server monitors the progress of the discussion in real time and generates a time alert and sends it to the device, for example, 10 minutes before the planned end time. The device then displays this time alert to the user, informing them of the remaining time.

[2001] Examples:

[2002] If the start time of the discussion is 10:00 and the scheduled duration is 60 minutes, the server will generate a time alert saying "10 minutes remaining" and display it on the terminal 10 minutes before the scheduled end time.

[2003] 6. Emotional Recognition

[2004] The emotion recognition engine analyzes the user's voice and text input to determine their emotions. Based on this information, the server adjusts the discussion progress and suggestions. If the user shows signs of frustration or fatigue, the server will suggest a break or adjust the pace of the discussion.

[2005] Examples:

[2006] If the user appears tired or irritated, the server will make suggestions such as "Take a 5-minute break."

[2007] This system supports efficient and smooth progress in process improvement discussions at manufacturing sites, and enables flexible responses based on the emotions of participants.

[2008] Hardware and software used:

[2009] AI model: OpenAI's GPT-3 or GPT-4

[2010] Server: High-performance server (e.g. AWS EC2, Google Cloud Compute Engine)

[2011] Device: Smartphone or tablet

[2012] This will significantly improve the quality and efficiency of discussions on the manufacturing floor.

[2013] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2014] Step 1:

[2015] A user inputs a topic for discussion into a terminal, and the terminal transmits this topic to a server.

[2016] Input: Theme (e.g. "Process Improvement")

[2017] Output: Theme data

[2018] Specific operation: Sends text entered by the user on the terminal to the server.

[2019] Step 2:

[2020] The server uses a generative AI model to analyze the input topic and generate specific related topics.

[2021] Input: Theme data

[2022] Output: Topic list

[2023] Specific operation: The topic is input into the generation AI model, and a topic is generated using the prompt, "Please suggest a suitable topic for discussion based on the topic 'Process Improvement'."

[2024] Step 3:

[2025] The server sends the generated topic list to the terminal, which then presents it to the user.

[2026] Input: Topic list

[2027] Output: A list of topics as they appear in the user interface

[2028] Specific operation: Receives a topic list from the server and displays it on the device screen.

[2029] Step 4:

[2030] The user selects one from a list of presented topics, and the terminal transmits the selection to the server.

[2031] Input: Selected Topic

[2032] Output: Selected topic data

[2033] What it does: Captures the user's selections and sends that information to the server.

[2034] Step 5:

[2035] The server generates a question based on the selected topic and returns the generated question to the terminal.

[2036] Input: Selected topic data

[2037] Output: Question list

[2038] Specific operation: The selected topic is input into the generative AI model, and questions are generated using the prompt, "Generate questions related to the topic 'Quality Improvement'."

[2039] Step 6:

[2040] The terminal presents the generated list of questions to the user.

[2041] Input: Question List

[2042] Output: A list of questions displayed in the user interface

[2043] Specific operation: Display a list of questions on the device screen.

[2044] Step 7:

[2045] During the discussion, users input comments into their terminals, and the terminals transmit these comments to the server.

[2046] Input: What you say

[2047] Output: Speech data

[2048] Specific operation: Captures the user's spoken text and sends it to the server.

[2049] Step 8:

[2050] The server analyzes the speech data, extracts the main points and summaries, and sends them to the terminal.

[2051] Input: Speech data

[2052] Output: Summary data

[2053] Specific operation: Speech data is input into a generative AI model, and a summary is generated using the prompt, "Please summarize the main points of the following utterance:..."

[2054] Step 9:

[2055] The terminal displays the summary data to the user.

[2056] Input: Summary data

[2057] Output: A summary that is displayed in the user interface

[2058] Specific behavior: Display a summary on the device screen.

[2059] Step 10:

[2060] The server monitors the progress of the discussion and suggests next steps or new topics when things go off track.

[2061] Input: Discussion progress data

[2062] Output: Suggested next steps and new topics

[2063] Specific behavior: Analyzes the progress, generates appropriate suggestions and sends them to the device.

[2064] Step 11:

[2065] The terminal presents the suggested information to the user.

[2066] Input: Suggest next steps or new topics

[2067] Output: Proposal displayed in the user interface

[2068] Specific behavior: Display suggestions on the device screen.

[2069] Step 12:

[2070] The user inputs the start time and scheduled time of the discussion into the terminal, which then transmits this to the server.

[2071] Input: Start time and Scheduled time

[2072] Output: Time data

[2073] Specific operation: The time information entered on the terminal is sent to the server.

[2074] Step 13:

[2075] The server monitors the progress in real time and generates a time alert before the scheduled time and sends it to the terminal.

[2076] Input: Time and progress data

[2077] Output: Time alert

[2078] Specific operation: Compare the progress with the scheduled time, and generate an alert saying "10 minutes remaining" 10 minutes before the scheduled end time and send it to the device.

[2079] Step 14:

[2080] The terminal displays a time alert to the user.

[2081] Input: Time Alert

[2082] Output: Time alert displayed in the user interface

[2083] Specific operation: Display a time alert on the device screen.

[2084] Step 15:

[2085] The emotion recognition engine analyzes the user's voice and text input to determine their emotions.

[2086] Input: Audio or text data

[2087] Output: Emotion data

[2088] Specific behavior: Analyzes the user's voice tone and text content to determine their emotional status.

[2089] Step 16:

[2090] The server adjusts the progress of the discussion and the content of proposals based on the emotional data and sends them to the terminal.

[2091] Input: Emotion data

[2092] Output: Coordinated progress or proposal

[2093] Specific operation: Analyzes emotional data and generates an adjustment, such as "Take a 5-minute break," and sends it to the device.

[2094] Step 17:

[2095] The terminal displays the adjusted progress and suggestions to the user.

[2096] Input: Adjusted progress or proposal

[2097] Output: The adjusted progress or suggestions displayed in the user interface

[2098] Specific behavior: Display adjusted progress or suggestions on the device screen.

[2099] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2100] 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.

[2101] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2102] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2103] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2104] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2105] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2106] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2107] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2108] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2109] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2110] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2111] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2112] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2113] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2114] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2115] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2116] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2117] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2118] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2119] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2120] The following is further disclosed regarding the above embodiment.

[2121] (Claim 1)

[2122] a means of suggesting topics;

[2123] a means for generating a question;

[2124] A means of gathering opinions and

[2125] a means of setting the direction of the discussion;

[2126] A way to manage time,

[2127] A system including:

[2128] (Claim 2)

[2129] 2. The system according to claim 1, wherein the means for suggesting a topic generates related topics based on a theme input by the user and displays them on the terminal.

[2130] (Claim 3)

[2131] 2. The system according to claim 1, wherein the means for generating a question displays, on the terminal, a question generated based on a topic selected by the user.

[2132] (Claim 4)

[2133] 2. The system according to claim 1, wherein the means for summarizing opinions analyzes the content of comments entered during the discussion and displays the main points and summaries on the terminal.

[2134] (Claim 5)

[2135] 2. The system according to claim 1, wherein the means for setting the direction of the discussion monitors the flow of the discussion and displays on the terminal suggestions that are in line with the direction that has been set in advance.

[2136] (Claim 6)

[2137] 2. The system according to claim 1, wherein the time management means monitors the progress of the meeting, generates a time alert before the scheduled time, and displays it on the terminal.

[2138] "Example 1"

[2139] (Claim 1)

[2140] means for receiving a theme input by a user and generating related topics;

[2141] means for generating questions based on user-selected topics;

[2142] A means of summarizing what was said during the discussion;

[2143] a means of monitoring the progress of the discussion and suggesting direction;

[2144] A means of managing the time of the discussion;

[2145] A system including:

[2146] (Claim 2)

[2147] The system of claim 1 uses a generative AI model to generate related topics based on a theme entered by a user and displays them on the terminal.

[2148] (Claim 3)

[2149] The system of claim 1, wherein questions generated using a generative AI model are displayed on a terminal based on a topic selected by a user.

[2150] "Application Example 1"

[2151] (Claim 1)

[2152] a means of suggesting topics;

[2153] a means for generating a question;

[2154] A means of gathering opinions and

[2155] a means of setting the direction of the discussion;

[2156] A way to manage time,

[2157] A means of generating relevant, specific topics based on the discussion topic;

[2158] means for generating questions related to the generated topics;

[2159] A means of analyzing comments made during discussions in real time and presenting summaries,

[2160] A means to monitor the progress of the discussion and suggest next steps or appropriate topics;

[2161] a means of monitoring the duration of discussions and generating time alerts;

[2162] A system including:

[2163] (Claim 2)

[2164] 2. The system according to claim 1, wherein related specific topics are generated based on the theme of the discussion and displayed on the terminal.

[2165] (Claim 3)

[2166] 10. The system of claim 1, wherein questions related to the topic are generated and displayed on the terminal.

[2167] "Example 2: Combining Emotion Engines"

[2168] (Claim 1)

[2169] a means of suggesting topics;

[2170] a means for generating a question;

[2171] A means of gathering opinions and

[2172] a means of setting the direction of the discussion;

[2173] A way to manage time,

[2174] means for recognizing a user's emotion;

[2175] A system including:

[2176] (Claim 2)

[2177] 2. The system according to claim 1, further comprising means for generating related topics based on a theme input by a user and proposing topics to be displayed on the terminal.

[2178] (Claim 3)

[2179] 2. The system according to claim 1, further comprising a means for generating a question, the means for generating a question based on a topic selected by a user, and displaying the question on a terminal.

[2180] "Application example 2 when combining emotion engines"

[2181] (Claim 1)

[2182] a means of suggesting topics;

[2183] a means for generating a question;

[2184] A means of gathering opinions and

[2185] a means of setting the direction of the discussion;

[2186] A way to manage time,

[2187] A system that recognizes users' emotions and includes a means to adjust the progress of discussions and the content of proposals.

[2188] (Claim 2)

[2189] 2. The system according to claim 1, wherein the means for suggesting a topic generates related topics based on a theme input by the user and displays them on the terminal.

[2190] (Claim 3)

[2191] 2. The system according to claim 1, wherein the means for generating a question displays, on the terminal, a question generated based on a topic selected by the user. [Explanation of symbols]

[2192] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means of suggesting topics; a means for generating a question; A means of gathering opinions and a means of setting the direction of the discussion; A way to manage time, A system including:

2. 2. The system according to claim 1, wherein the topic suggesting means generates related topics based on a theme input by the user and displays them on the terminal.

3. 2. The system according to claim 1, wherein the means for generating a question displays a question generated based on a topic selected by the user on the terminal.

4. 2. The system according to claim 1, wherein the means for summarizing opinions analyzes the content of comments entered during the discussion and displays the main points and summaries on the terminal.

5. 2. The system according to claim 1, wherein the means for setting the direction of the discussion monitors the flow of the discussion and displays on the terminal a proposal that is in line with the direction that has been set in advance.

6. 2. The system according to claim 1, wherein the time management means monitors the progress of the meeting, generates a time alert before the scheduled time, and displays it on the terminal.

Images