system

Abstract

We provide the system. [Solution] A means of inputting information such as the purpose, goals, participants, and time allocation of the meeting, A means of analyzing the audio of the discussion during the meeting based on the input information and correcting the course of the discussion, A means to automatically generate meeting minutes based on the meeting results, and to automatically assign and share tasks for the next steps, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In conventional meetings, there was a problem that the efficiency of the meeting fluctuated greatly depending on the skills of the facilitator. As a result, there was a problem that the working hours of all meeting participants were affected and the productivity of the entire organization decreased. 【Means for Solving the Problems】 【0005】 This invention provides a means for inputting information such as the purpose, goals, participants, and time allocation of a meeting, thereby allowing for pre-planning of the meeting's progress. Furthermore, it includes a means for analyzing the discussion during the meeting based on the input information and suggesting corrections if the progress deviates from the planned course, thereby improving the efficiency of the meeting. In addition, it provides a means for automatically generating meeting minutes based on the meeting results and automatically assigning and sharing tasks for the next steps, thereby improving the productivity of the meeting. 【0006】 A "meeting" is a place where multiple people gather to share information and discuss topics based on a specific purpose or agenda. 【0007】 "Purpose" refers to the goals or intended outcomes that are to be achieved in a meeting or activity. 【0008】 "Goal" refers to the specific outcome or objective that is expected to be achieved at the end of the meeting. 【0009】 "Participants" refer to people who attend a meeting and are involved in discussions and decision-making. 【0010】 "Time allocation" refers to the plan of how much time is allocated to each agenda item or activity in a meeting. 【0011】 "Means of inputting information" refers to methods or devices for inputting data such as the purpose, goals, participants, and time allocation of a meeting into a system. 【0012】 "Voice analysis" refers to the technology that digitally processes voice data to identify the content of speech, the speaker, and other relevant information. 【0013】 "Means of correcting progress" refers to functions or methods for proposing to return a meeting to its original direction when it deviates from its pre-set objectives or flow. 【0014】 "Meeting minutes" refers to a written report that records the discussions and decisions made during a meeting. 【0015】 "Automatic generation" refers to the creation of necessary data and documents by programs or machines without human intervention. 【0016】 "Automatic task assignment" refers to the process in which the system automatically allocates the action items determined in a meeting to the appropriate responsible persons. 【0017】 "Means of sharing" refers to the method for distributing the generated meeting minutes and task assignment information to all relevant parties to transmit the information. 【Brief Description of Drawings】 【0018】 [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined. 【Mode for Carrying Out the Invention】 【0019】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0020】 First, the terms used in the following description will be explained. 【0021】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc. 【0022】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0023】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0024】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0025】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0026】 [First Embodiment] 【0027】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0028】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0029】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0030】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0031】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0032】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0033】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0034】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0035】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0036】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0037】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0038】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0039】 This invention provides an AI-powered meeting management system for effectively conducting meetings. This system consists of three main components: a server, terminals, and users. 【0040】 Server Functions 【0041】 The server provides an interface for receiving and storing meeting information. It stores data such as the purpose, goals, participants, and time allocation of meetings entered by users, and uses this information to support the progress of the meeting. 【0042】 Furthermore, the server has an audio analysis function that processes audio data transmitted from terminals during meetings in real time. This analysis helps understand the content of the discussion and suggests adjustments to the progress based on the set goals. For example, if the discussion deviates from the agenda, it identifies the next topic to move on to and makes a suggestion through the terminal. 【0043】 The server also has the capability to record meeting discussions and automatically create meeting minutes. Furthermore, it analyzes the action items decided in the meeting, automatically assigns tasks to the appropriate personnel, and generates related documents. 【0044】 Device functions 【0045】 The terminal is a device that receives instructions from the server and notifies meeting participants of suggestions and modifications to the meeting's progress. This allows the terminal to support the meeting's progress in real time, enabling participants to make decisions efficiently. 【0046】 Furthermore, the terminal functions as a means of communication for distributing generated meeting minutes and task information to all participants. The information sent through the terminal enables stakeholders to quickly take necessary actions after the meeting. 【0047】 User actions 【0048】 The user first enters meeting information into the system. This allows the server to understand the purpose and flow of the meeting and prepare to provide the necessary support. During the meeting, the user is also responsible for deciding whether to accept any proposed revisions to the meeting's progress based on the results of the audio analysis. After the meeting, the user reviews the automatically generated minutes and task assignments and makes any necessary corrections. 【0049】 As a concrete example, suppose a user sets up a project progress meeting. In this case, the server supports the progress based on project-related data received in advance, making appropriate corrections and suggestions as needed. After the meeting, the user can review the automatically generated materials and effectively share information about the next steps with the participants. 【0050】 Thus, the system of the present invention enables meetings to proceed smoothly, allowing all participants to share information and act with maximum efficiency. 【0051】 The following describes the processing flow. 【0052】 Step 1: 【0053】 The user enters necessary information, including the meeting's purpose, goals, participants, and time allocation, into the system interface. The server receives this input information and stores it in a database. 【0054】 Step 2: 【0055】 The server checks the meeting schedule based on the received information and verifies that the data is accurate. The terminal sends a confirmation message to the meeting participants, prompting them to confirm the appointment. 【0056】 Step 3: 【0057】 Once the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server uses AI to analyze this audio and identify the topics being discussed and the speakers. 【0058】 Step 4: 【0059】 The server compares the analysis results with the set meeting goals and generates correction suggestions if the progress has deviated. The terminal notifies meeting participants of these suggestions and prompts them to adjust the progress as needed. 【0060】 Step 5: 【0061】 After the meeting ends, the server extracts key points from the audio data and automatically generates meeting minutes. The server then analyzes the next steps and automatically assigns them to the appropriate participants. 【0062】 Step 6: 【0063】 The terminal distributes the generated meeting minutes and task assignment information to all meeting participants, sharing information about the next steps. Users receive this information, review it, and make adjustments as needed. 【0064】 (Example 1) 【0065】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0066】 In today's work environment, meetings are frequent but often inefficient. Participants may engage in discussions that deviate from the meeting's purpose and objectives, or the necessary actions and responsibilities after the meeting may be unclear. This leads to problems with meeting productivity and subsequent actions. 【0067】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0068】 In this invention, the server includes means for inputting data such as the purpose, objectives, participants, and time allocation of a meeting; means for performing voice analysis of the dialogue during communication based on the input data and correcting the course of the meeting; and means for processing the voice data in real time using a generative machine learning model. This makes it possible to manage the progress of the meeting in accordance with its purpose and objectives at all times, and to clarify the actions and responsibilities required after the meeting. 【0069】 The "purpose of a meeting" refers to the ultimate outcome or result that is intended to be achieved through the meeting. 【0070】 "Goals" refer to the specific tasks or topics that should be achieved during the meeting. 【0071】 "Participants" refers to the people or organizations that attend the meeting. 【0072】 "Time allocation" refers to the amount of time that is assigned to each agenda item or session in a meeting. 【0073】 "Means of inputting data" refers to methods or devices used to bring information into a system. 【0074】 "Dialogue during communication" refers to the exchange of information, whether verbal or written, that takes place during a meeting. 【0075】 "Speech analysis" refers to the technology and process of analyzing audio data and deciphering or evaluating its content. 【0076】 "Means of correcting the course of progress" refers to methods or devices for guiding discussions that have strayed from the purpose of a meeting back to their original objective. 【0077】 A "generative machine learning model" is an algorithm or framework that learns from data and performs predictions and classifications. 【0078】 "Means for processing audio data in real time" refers to technologies and devices that instantly analyze audio information and make the results available in real time. 【0079】 This meeting management system is implemented using three main components: servers, terminals, and users. 【0080】 Server Functions 【0081】 The server plays a central role in receiving and storing user-entered data on meeting purpose, objectives, participants, and time allocation. The server uses a generative AI model to process audio data in real time and analyze the dialogue during the meeting. This generative AI model employs advanced analysis software, such as speech analysis systems and natural language processing algorithms. The analyzed data is used to determine whether course corrections are needed to the meeting. 【0082】 Device functions 【0083】 The terminal is a device that receives information transmitted from the server and notifies meeting participants. The terminal uses a microphone and speaker to transmit audio data to the server and also receives feedback from the server. This device can be an existing communication device, such as a tablet or smartphone. 【0084】 User actions 【0085】 As part of the initial setup for the meeting, the user enters data into their terminal. This data is sent to the server, and the system begins operation. During the meeting, the user reviews the progress suggestions from the server and makes decisions as needed. After the meeting ends, the user reviews the automatically generated record and task assignments and makes corrections as necessary. 【0086】 As a concrete example, let's assume a user is setting up a meeting to plan the launch of a new product. The user inputs all the relevant information, and the server uses this to support the progress of the session. An example of a prompt might be, "What are the goals to be achieved in this project meeting? Are there any specific agenda items or action items?" 【0087】 In this way, the system efficiently manages meetings and enables all participants to discuss and make decisions in accordance with the meeting's purpose and objectives. 【0088】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0089】 Step 1: 【0090】 The user enters data such as the meeting's purpose, objectives, participants, and time allocation into the terminal. The entered data is then sent from the terminal to the server. The server receives the specific meeting settings and prepares for the next processing step. 【0091】 Step 2: 【0092】 The server stores the received meeting information in a database. Based on this data, the server prepares to analyze the next audio data using a generative AI model. The stored information forms the basis for real-time progress management. 【0093】 Step 3: 【0094】 As soon as the meeting begins, the terminal captures audio data through the microphone and sends it to the server. The transmitted audio data is received and analyzed by the server. This allows the server to check in real time whether the current discussion is aligned with the meeting's purpose and objectives. 【0095】 Step 4: 【0096】 The server uses a generative AI model to analyze received audio data in real time. The input for the analysis is the audio data sent from the terminal, and the output is a judgment on whether suggestions for progress or corrections regarding the agenda are necessary. Specifically, if the discussion deviates from the topic, a suggestion such as "The next agenda item to discuss is XX" is generated. 【0097】 Step 5: 【0098】 The terminal receives progress suggestions and correction information from the server. The terminal notifies meeting participants of this information via display and audio. This allows participants to appropriately adjust the direction of the meeting. 【0099】 Step 6: 【0100】 After the meeting ends, the server automatically generates meeting minutes based on the analysis results, assigns the next tasks to each participant, and distributes relevant information. Users review the generated minutes, check for accuracy, and make corrections as needed. 【0101】 This process allows the system to maximize meeting efficiency, ensure all participants share information accurately, and facilitate smooth progress to the next steps. 【0102】 (Application Example 1) 【0103】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0104】 In information-sharing settings such as meetings and staff meetings, effective progress management is required to ensure that all participants efficiently communicate information and advance discussions. However, deviations from the agenda and unclear sharing of decisions often occur, making effective information transmission difficult. In particular, the lack of means for real-time progress management and prompt instructions for action after the meeting has ended is a problem. 【0105】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0106】 In this invention, the server includes means for analyzing the content of conversations in real time and correcting the progress, means for automatically generating information based on the meeting results and automatically assigning and sharing the next steps, and means for distributing the generated information to relevant parties. This enables efficient information transmission and effective management of meeting progress. 【0107】 "Meeting information" refers to basic data necessary for the smooth running of a meeting, such as participants, objectives, and time allocation. 【0108】 "Voice analysis" is a technology that acquires the content spoken during a meeting as digital audio data and converts it into text information. 【0109】 "Correcting the course of the meeting" is a means of suggesting an appropriate direction for discussion and returning to the original course when the meeting has deviated from its set objectives or goals. 【0110】 "Automatic information generation" refers to the process where AI independently creates meeting minutes, next-step tasks, and other information based on the content discussed in a meeting. 【0111】 The "means of making suggestions" refers to a function that uses data extracted through voice analysis to show meeting participants the direction of the discussion and the next steps to take in real time. 【0112】 The server plays a central role in effectively managing meetings. It receives meeting information in advance, detects conversation content in real time through speech analysis, and automatically generates meeting minutes and tasks. The hardware required is a server computer with high data processing capabilities. The software uses Google® Cloud Speech-to-Text API to analyze speech data and leverages OpenAI® APIs to suggest and automatically generate meeting progress. 【0113】 The terminal is a device that delivers instructions from the server to users participating in a meeting in real time. Users can receive suggestions regarding the meeting's progress and information on task assignments after the meeting via their smartphones or tablets. The application on the terminal is developed using React Native and operates across platforms. 【0114】 As a concrete example, in a new product presentation at a store, the server receives product information in advance and supports the meeting's progress with prompts. Prompts such as, "The agenda for the next meeting is the introduction of the new product. Please discuss the main target audience and store placement strategy, and decide who will be in charge," are used to guide the discussion smoothly. 【0115】 This allows all participants to efficiently acquire information and take action after the meeting with a clear understanding of their tasks. 【0116】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0117】 Step 1: 【0118】 Users enter initial meeting information into a terminal. This information includes the meeting's purpose, participants, and time allocation. This information is sent to the server and stored in a database. This allows the server to understand the overall flow of the meeting and prepare accordingly. 【0119】 Step 2: 【0120】 During the meeting, the terminal sends audio data to the server. The server converts the audio data into text data using the Google Cloud Speech-to-Text API. The converted text data is analyzed by a generating AI model to determine if the discussion has deviated from its purpose or goals. If a deviation is detected, the server generates correction suggestions and sends them to the terminal. 【0121】 Step 3: 【0122】 The server uses a generative AI model to summarize the conversation based on the speech analysis results. It generates prompt sentences to present to the user. Through these prompt sentences, it sends instructions to the terminal indicating the next steps to take, thereby supporting the progress of the meeting. 【0123】 Step 4: 【0124】 After the meeting ends, the server automatically generates meeting minutes based on the audio data and analysis results. It also analyzes the tasks decided during the meeting and creates a task list automatically assigned to each person responsible. This information is sent to the terminal and notified to the user. 【0125】 Step 5: 【0126】 The terminal provides an interface for users to modify meeting minutes and task lists sent from the server if necessary. After the user makes the modifications, the information is uploaded back to the server, and the final result is shared with all participants. 【0127】 This ensures that the entire meeting proceeds smoothly and allows participants to quickly move on to the next action. 【0128】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0129】 This invention is a system that supports the effective management of meetings, and in particular offers a novel approach that takes participants' emotions into consideration. The system consists of a server, terminals, users, and an emotion engine. 【0130】 Server Functions 【0131】 The server receives meeting information input and provides an interface for storing that information. It stores the meeting's purpose, goals, participants, and time allocation entered by the user in a database and maintains the functionality to support the progress of the meeting based on this information. 【0132】 The server also utilizes voice analysis technology to analyze the voice data transmitted from the terminal in real time. This analysis helps to understand the content of the discussion and suggests course corrections if it deviates from the set objectives. 【0133】 Furthermore, the server extracts emotional data from the facial expressions and tone of voice of meeting participants via an emotion engine. This data is dynamically analyzed during the meeting and used to adjust its progress. 【0134】 The server ultimately automatically generates meeting minutes based on the key points of the meeting and assigns tasks that take sentiment data into account. This includes suggesting communication strategies that consider the emotional state of each participant. 【0135】 Device functions 【0136】 The terminal receives progress corrections and sentiment-based suggestions from the server and notifies meeting participants in real time. This allows participants to participate in the discussion while being aware of their own emotional state and the progress of the meeting. 【0137】 Feedback based on sentiment data provided through the device enables participants to engage in more meaningful discussions. Furthermore, the device distributes generated meeting minutes and task information to participants after the meeting, facilitating subsequent actions. 【0138】 User actions 【0139】 The user first enters basic meeting information into the system. During the meeting, the terminal displays feedback from an emotion engine, allowing the user to adjust their comments and participation in the discussion. After the meeting, the user reviews the automatically generated minutes and tasks, making manual adjustments as needed. 【0140】 For example, if a user holds a meeting to get feedback on a presentation, the server analyzes the presenter's and audience's sentiment data and suggests adjustments to the presentation based on the audience's reactions. This information is shared with the presenter in real time via their device, providing valuable insights to improve the quality of the presentation. 【0141】 This system dynamically captures emotions during meetings and enables efficient progress, providing an advanced and effective solution to traditional meeting management. 【0142】 The following describes the processing flow. 【0143】 Step 1: 【0144】 The user enters the meeting's purpose, goals, participants, and time allocation into the interface. The server receives this information and stores it in a database. 【0145】 Step 2: 【0146】 The server retrieves data regarding the meeting schedule and structure, and checks the participant list. The terminal sends meeting notifications to participants, prompting them to prepare. 【0147】 Step 3: 【0148】 As soon as the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server performs audio analysis to understand the content and progress of the discussion. 【0149】 Step 4: 【0150】 The server uses an emotion engine to analyze the tone of voice and facial expression data of meeting participants and obtain their emotional state. The emotional data is dynamically analyzed in conjunction with the progress of the meeting. 【0151】 Step 5: 【0152】 Based on the analysis results, the server detects deviations from the set objectives and goals and, if necessary, proposes course corrections that take sentiment data into consideration. The terminal then notifies the meeting participants of these suggestions. 【0153】 Step 6: 【0154】 After the meeting ends, the server automatically generates meeting minutes and assigns tasks considering emotional data. Specifically, it formulates task priorities and communication strategies based on each participant's emotional state. 【0155】 Step 7: 【0156】 The terminal distributes the generated meeting minutes and task information to participants, clarifying the next steps. Users review this information and make necessary corrections or additions to utilize the meeting results. 【0157】 (Example 2) 【0158】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0159】 Traditional meeting management systems failed to dynamically grasp participants' emotions and the progress of the meeting, and to adequately adjust the meeting's flow based on that information. This sometimes led to discussions deviating from the set objectives and goals, resulting in inefficient meetings. Furthermore, the lack of efficient means to summarize meeting results and appropriately translate them into subsequent actions sometimes hindered the smooth execution of post-meeting tasks. 【0160】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0161】 In this invention, the server includes a function for inputting information such as the purpose, goals, participants, and time allocation of a meeting; a function for processing the dialogue during the meeting based on the input information and adjusting the direction of the meeting; and a function for extracting and analyzing participants' emotional data in real time during the meeting and dynamically optimizing the progress. This not only enables effective management of the meeting progress and dynamic adjustments based on participants' emotions, but also allows for quick and accurate translation of meeting results into subsequent actions. 【0162】 The "objective of the meeting" refers to the ultimate goal of the meeting, and the specific results or conclusions that should be achieved when the meeting concludes. 【0163】 A "goal" refers to a specific objective that should be achieved in the short or long term during a meeting, and serves as a guide for the progress of the meeting. 【0164】 "Participants" refer to those who attend a meeting, engage in discussions and exchange opinions, and are the main actors in decision-making and information sharing. 【0165】 "Time allocation" refers to the distribution of time to each item or agenda item that makes up a meeting, and is a standard for conducting a meeting efficiently. 【0166】 "Speech processing" refers to the technology of analyzing audio data collected during a meeting, converting it into text, or extracting distinctive audio features. 【0167】 The "ability to adjust the direction of progress" refers to the ability to propose course corrections when discussions or dialogues during a meeting deviate from the set objectives or goals. 【0168】 "Emotional data" refers to information that quantifies or categorizes the feelings and attitudes extracted from participants' facial expressions, tone of voice, and word choice. 【0169】 The "dynamic optimization function" refers to the ability to perform optimal progress and adjustments on the spot based on data acquired in real time during a meeting. 【0170】 This invention is a system that innovatively supports meeting management, and aims to improve the efficiency and outcome of meetings, particularly by utilizing participant emotional data. The system consists of a server, terminals, users, and an emotional engine. 【0171】 Server Role 【0172】 The server first receives information from the user, such as the purpose, goals, participants, and time allocation of the meeting. This information is stored in a database and forms the foundation for supporting the overall progress of the meeting. For speech processing technology, cloud services such as the Google Cloud Speech-to-Text API are used to transcribe the audio data during the meeting in real time and determine whether the discussion content deviates from the set goals. In addition, sentiment analysis tools such as the Microsoft® Azure® Emotion API are used to analyze emotional data from the tone of participants' voices and facial expressions. 【0173】 Terminal role 【0174】 The terminal receives real-time updates from the server during the meeting, including proposed revisions and sentiment-based suggestions, and notifies participants. This allows participants to adjust their comments and discussions on the spot. After the meeting ends, the terminal distributes meeting minutes and tasks automatically generated by the server to participants, supporting them in carrying out their next actions. 【0175】 User interaction 【0176】 Users establish a foundation for meeting management by inputting basic meeting information into the system. During the meeting, users can adjust the direction of the discussion by referring to the feedback provided by the terminal. After the meeting, users can review the generated minutes and tasks and make manual adjustments as needed. 【0177】 Specific example 【0178】 A concrete example is a case where users hold a meeting to gather feedback for product development. In this case, the server analyzes participants' sentiment data in real time and suggests course corrections to the discussion based on how each comment is received. This information is immediately shared with the user via their terminal, providing insights to make the discussion more effective. 【0179】 Example of a prompt 【0180】 "Please describe a system that analyzes participants' emotions during product development feedback meetings, measures their reactions, and suggests adjustments to the process." 【0181】 Thus, the present invention enables meeting management that takes participants' emotions into consideration, and is a system that yields superior results compared to conventional management methods. 【0182】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0183】 Step 1: 【0184】 Users input basic information into the system, such as the purpose, goals, participants, and time allocation of the meeting. This information is sent to the server and stored in the database. The entered information is processed as initial setup data to support the progress of the meeting. 【0185】 Step 2: 【0186】 The terminal sends the audio data collected during the meeting to the server. The server converts this data into text using speech analysis technology. Specifically, it processes the audio data using the Google Cloud Speech-to-Text API and generates the result as text output. This makes it possible to monitor the content of the discussion. 【0187】 Step 3: 【0188】 The server analyzes the converted text data in real time to determine whether the meeting is deviating from its set objectives and goals. This analysis uses natural language processing techniques, making decisions by analyzing keywords and context. As output, suggested revisions to the meeting's progress are generated as needed. 【0189】 Step 4: 【0190】 The server uses an emotion engine to extract participant emotion data. Audio and video data from the meeting are used as input, and emotion analysis tools such as the Microsoft Azure Emotion API categorize and quantify participants' emotions. This information becomes output data used to adjust the meeting's progress. 【0191】 Step 5: 【0192】 The server generates proposed revisions and sentiment-based suggestions based on the meeting's progress and sentiment data, and sends them to the terminal. The terminal notifies participants in real time, helping users adjust their comments and discussions on the spot. 【0193】 Step 6: 【0194】 Once the meeting concludes, the server automatically generates meeting minutes based on the audio analysis results and the recorded proceedings. This process extracts key points and decisions made during the meeting and outputs them in a structured document format. The generated minutes are then shared with the participants. 【0195】 Step 7: 【0196】 Ultimately, the server assigns tasks to each participant, taking emotional data into consideration, and proposes the optimal communication strategy. The output tasks, which take each participant's emotional state into account, are synchronized to the communication application via the terminal to support the next action. 【0197】 (Application Example 2) 【0198】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0199】 Modern family communication presents a challenge in preventing conflicts arising from emotional misunderstandings. In particular, family dialogue requires flexible responses to changing emotions, but appropriate real-time feedback is often lacking. This can hinder smooth and meaningful communication. 【0200】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0201】 In this invention, the server includes means for inputting information such as the purpose, goals, participants, and time allocation of a meeting; means for performing voice analysis of the discussion during the meeting based on the input information and correcting the course of progress; and means for observing conversations within the home, analyzing the emotions of the participants, and suggesting ways to proceed. This makes it possible to analyze emotions during conversations within the home, enabling more constructive and smoother communication. 【0202】 A "meeting" is a place where multiple participants gather to share information and discuss in order to achieve a specific purpose or goal. 【0203】 "Purpose" refers to the specific main theme or goal that should be achieved during the process of a meeting or discussion. 【0204】 "Participants" refer to individuals who gather in a meeting or discussion to exchange opinions and share information. 【0205】 "Time allocation" refers to the distribution of time allocated to each topic throughout a meeting or discussion. 【0206】 "Voice analysis" is a technology that analyzes participants' statements in order to understand the content of a discussion. 【0207】 "Correcting the course of progress" means appropriately adjusting the content and flow of a meeting or discussion so that it does not deviate from its set objectives. 【0208】 "Emotional analysis" is a technique that analyzes participants' emotions from their tone of voice and facial expressions during conversations. 【0209】 A "proposal" is the act of presenting specific policies or action plans to improve the process or dialogue. 【0210】 "Automatically generating records" means that the system automatically transcribes important information from conversations and dialogues into written form. 【0211】 "Next steps" refer to the specific actions each participant should take based on the outcome of the conversation. 【0212】 To implement this invention, it is necessary to construct a system using a server, a terminal, and an emotion analysis engine. The server includes a database for managing information such as the purpose, goals, participants, and time allocation related to meetings and conversations within the home. The server uses speech analysis technology to analyze the content of discussions and conversations in real time and suggests corrections to the process if it deviates from the set goals. 【0213】 Furthermore, the server extracts emotional data from participants' facial expressions and tone of voice via an emotion analysis engine. This extracted emotional data is used to adjust the flow of the conversation, allowing the server to make appropriate suggestions in real time. Specifically, for example, if an emotional conflict arises during a conversation, the server can suggest a reconciliation or a change of topic. 【0214】 The terminal notifies participants in meetings and discussions in real time of proposed revisions and feedback based on sentiment analysis sent from the server. Based on this information, participants can adjust their statements and achieve more meaningful communication. 【0215】 The user inputs basic conversation information into the server through the interface and receives emotional feedback via their device. This allows for dynamic adjustments to the conversation's progression, and ultimately, the automatically generated record can be reviewed and edited as needed. An example of a prompt for the generating AI model is, "Scenario where a family conversation has started to become confrontational: Please suggest something for when Mom is feeling frustrated." 【0216】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0217】 Step 1: 【0218】 The user enters basic information about the meeting or home conversation (purpose, goals, participants, time allocation) into the device. The entered information is sent to the server and stored in the database. Based on this information, the system is ready for subsequent voice analysis and sentiment analysis. 【0219】 Step 2: 【0220】 The server receives audio data transmitted from terminals in real time. It uses a speech analysis engine to analyze the content of discussions and conversations. The input is audio data, and the output is a textualized transcript of the discussion and identification of topics. This analysis allows for an evaluation of progress toward the set objectives and goals. 【0221】 Step 3: 【0222】 The server uses an emotion analysis engine to extract emotional data from participants' audio and camera footage. The inputs are audio and video data, and the output is the analysis of their emotional state. For example, it assesses levels of joy, anger, and stress based on voice tone and facial expression changes. This information can then be used to adjust the program's progress. 【0223】 Step 4: 【0224】 The server integrates the results of speech analysis and sentiment analysis to generate suggested course corrections and emotion-based recommendations. The input is the speech analysis results and sentiment analysis results, and the output is a suggested message. Specifically, it provides concrete actions to correct the course of the conversation and emotionally conscious directions for the discussion. 【0225】 Step 5: 【0226】 The terminal notifies participants in real time of suggestion messages received from the server. The output is visual or auditory suggestion information provided to participants. This allows participants to immediately adjust the flow of the conversation and achieve emotionally resonant communication. 【0227】 Step 6: 【0228】 After the conversation ends, the server automatically generates a summary of the conversation's key points and assigns tasks to each participant. The input is the audio data of the entire conversation and the analysis results, while the output is a text-based record and task assignments. This automatically generated record is provided to the user via their terminal, allowing for editing and additions as needed. 【0229】 The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data. 【0230】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0231】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0232】 [Second Embodiment] 【0233】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0234】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0235】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0236】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0237】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0238】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0239】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0240】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0241】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0242】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0243】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0244】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0245】 This invention provides an AI-powered meeting management system for effectively conducting meetings. This system consists of three main components: a server, terminals, and users. 【0246】 Server Functions 【0247】 The server provides an interface for receiving and storing meeting information. It stores data such as the purpose, goals, participants, and time allocation of meetings entered by users, and uses this information to support the progress of the meeting. 【0248】 Furthermore, the server has an audio analysis function that processes audio data transmitted from terminals during meetings in real time. This analysis helps understand the content of the discussion and suggests adjustments to the progress based on the set goals. For example, if the discussion deviates from the agenda, it identifies the next topic to move on to and makes a suggestion through the terminal. 【0249】 The server also has the capability to record meeting discussions and automatically create meeting minutes. Furthermore, it analyzes the action items decided in the meeting, automatically assigns tasks to the appropriate personnel, and generates related documents. 【0250】 Device functions 【0251】 The terminal is a device that receives instructions from the server and notifies meeting participants of suggestions and modifications to the meeting's progress. This allows the terminal to support the meeting's progress in real time, enabling participants to make decisions efficiently. 【0252】 Furthermore, the terminal functions as a means of communication for distributing generated meeting minutes and task information to all participants. The information sent through the terminal enables stakeholders to quickly take necessary actions after the meeting. 【0253】 User actions 【0254】 The user first enters meeting information into the system. This allows the server to understand the purpose and flow of the meeting and prepare to provide the necessary support. During the meeting, the user is also responsible for deciding whether to accept any proposed revisions to the meeting's progress based on the results of the audio analysis. After the meeting, the user reviews the automatically generated minutes and task assignments and makes any necessary corrections. 【0255】 As a concrete example, suppose a user sets up a project progress meeting. In this case, the server supports the progress based on project-related data received in advance, making appropriate corrections and suggestions as needed. After the meeting, the user can review the automatically generated materials and effectively share information about the next steps with the participants. 【0256】 Thus, the system of the present invention enables meetings to proceed smoothly, allowing all participants to share information and act with maximum efficiency. 【0257】 The following describes the processing flow. 【0258】 Step 1: 【0259】 The user enters necessary information, including the meeting's purpose, goals, participants, and time allocation, into the system interface. The server receives this input information and stores it in a database. 【0260】 Step 2: 【0261】 The server checks the meeting schedule based on the received information and verifies that the data is accurate. The terminal sends a confirmation message to the meeting participants, prompting them to confirm the appointment. 【0262】 Step 3: 【0263】 Once the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server uses AI to analyze this audio and identify the topics being discussed and the speakers. 【0264】 Step 4: 【0265】 The server compares the analysis results with the set meeting goals and generates correction suggestions if the progress has deviated. The terminal notifies meeting participants of these suggestions and prompts them to adjust the progress as needed. 【0266】 Step 5: 【0267】 After the meeting ends, the server extracts key points from the audio data and automatically generates meeting minutes. The server then analyzes the next steps and automatically assigns them to the appropriate participants. 【0268】 Step 6: 【0269】 The terminal distributes the generated meeting minutes and task assignment information to all meeting participants, sharing information about the next steps. Users receive this information, review it, and make adjustments as needed. 【0270】 (Example 1) 【0271】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0272】 In today's work environment, meetings are frequent but often inefficient. Participants may engage in discussions that deviate from the meeting's purpose and objectives, or the necessary actions and responsibilities after the meeting may be unclear. This leads to problems with meeting productivity and subsequent actions. 【0273】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0274】 In this invention, the server includes means for inputting data such as the purpose, objectives, participants, and time allocation of a meeting; means for performing voice analysis of the dialogue during communication based on the input data and correcting the course of the meeting; and means for processing the voice data in real time using a generative machine learning model. This makes it possible to manage the progress of the meeting in accordance with its purpose and objectives at all times, and to clarify the actions and responsibilities required after the meeting. 【0275】 The "purpose of a meeting" refers to the ultimate outcome or result that is intended to be achieved through the meeting. 【0276】 "Goals" refer to the specific tasks or topics that should be achieved during the meeting. 【0277】 "Participants" refers to the people or organizations that attend the meeting. 【0278】 "Time allocation" refers to the time assigned to each topic or session of a meeting. 【0279】 "Means for inputting data" refers to methods or devices for importing information into a system. 【0280】 "Dialogue during communication" refers to the oral or written information exchange that takes place during a meeting. 【0281】 "Voice analysis" refers to technologies or processes for analyzing voice data to interpret or evaluate its content. 【0282】 "Means for correcting the progress trajectory" refers to methods or devices for returning discussions that deviate from the purpose of a meeting to the original purpose. 【0283】 "Generative machine learning model" refers to algorithms or frameworks that learn based on data and perform predictions or classifications. 【0284】 "Means for processing voice data in real time" refers to technologies or devices that immediately analyze voice information and make the results available in real time. 【0285】 This meeting management system is implemented by three main components: a server, a terminal, and a user. 【0286】 Functions of the server 【0287】 The server plays a central role in receiving data on the purpose, goals, participants, and time allocation of a meeting entered by the user and storing it in the system. The server uses a generative AI model to process voice data in real time and analyze the dialogue during the meeting. The generative AI model uses advanced analysis software such as, for example, a voice analysis system or natural language processing algorithms. The analyzed data is used to determine whether a correction of the progress trajectory is necessary. 【0288】 Functions of the terminal 【0289】 The terminal is a device that receives information transmitted from the server and notifies meeting participants. The terminal uses a microphone and speaker to transmit audio data to the server and also receives feedback from the server. This device can be an existing communication device, such as a tablet or smartphone. 【0290】 User actions 【0291】 As part of the initial setup for the meeting, the user enters data into their terminal. This data is sent to the server, and the system begins operation. During the meeting, the user reviews the progress suggestions from the server and makes decisions as needed. After the meeting ends, the user reviews the automatically generated record and task assignments and makes corrections as necessary. 【0292】 As a concrete example, let's assume a user is setting up a meeting to plan the launch of a new product. The user inputs all the relevant information, and the server uses this to support the progress of the session. An example of a prompt might be, "What are the goals to be achieved in this project meeting? Are there any specific agenda items or action items?" 【0293】 In this way, the system efficiently manages meetings and enables all participants to discuss and make decisions in accordance with the meeting's purpose and objectives. 【0294】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0295】 Step 1: 【0296】 The user enters data such as the meeting's purpose, objectives, participants, and time allocation into the terminal. The entered data is then sent from the terminal to the server. The server receives the specific meeting settings and prepares for the next processing step. 【0297】 Step 2: 【0298】 The server stores the received meeting information in a database. Based on this data, the server prepares to analyze the next audio data using a generative AI model. The stored information forms the basis for real-time progress management. 【0299】 Step 3: 【0300】 As soon as the meeting begins, the terminal captures audio data through the microphone and sends it to the server. The transmitted audio data is received and analyzed by the server. This allows the server to check in real time whether the current discussion is aligned with the meeting's purpose and objectives. 【0301】 Step 4: 【0302】 The server uses a generative AI model to analyze received audio data in real time. The input for the analysis is the audio data sent from the terminal, and the output is a judgment on whether suggestions for progress or corrections regarding the agenda are necessary. Specifically, if the discussion deviates from the topic, a suggestion such as "The next agenda item to discuss is XX" is generated. 【0303】 Step 5: 【0304】 The terminal receives progress suggestions and correction information from the server. The terminal notifies meeting participants of this information via display and audio. This allows participants to appropriately adjust the direction of the meeting. 【0305】 Step 6: 【0306】 After the meeting ends, the server automatically generates meeting minutes based on the analysis results, assigns the next tasks to each participant, and distributes relevant information. Users review the generated minutes, check for accuracy, and make corrections as needed. 【0307】 With this process, the system can maximize the efficiency of the meeting, ensure that all participants accurately share information, and smoothly proceed with actions in the next step. 【0308】 (Application Example 1) 【0309】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0310】 In information-sharing scenarios such as meetings and staff meetings, effective progress management is required for all participants to efficiently transmit information and conduct discussions. However, there are often issues such as deviating from the topic and unclear sharing of decisions, making it difficult to effectively transmit information. In particular, there is a problem with the lack of means for real-time progress management and instructions for rapid actions after the meeting. 【0311】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0312】 In this invention, the server includes means for real-time voice analysis of the conversation content to correct the progress, means for automatically generating information based on the meeting results and automatically allocating and sharing the next steps, and means for distributing the generated information to relevant parties. This enables efficient transmission of information and effective management of the meeting progress. 【0313】 "Meeting information" refers to basic data necessary for the progress of the meeting, such as participants, purpose, and time allocation. 【0314】 "Voice analysis" is a technology that acquires the content spoken during the meeting as digital voice data and converts it into character information. 【0315】 "Correction of the progress track" is a means of proposing an appropriate direction for discussion and returning to the original progress when the meeting deviates from the set purpose or goal. 【0316】 "Automatic information generation" refers to the process where AI independently creates meeting minutes, next-step tasks, and other information based on the content discussed in a meeting. 【0317】 The "means of making suggestions" refers to a function that uses data extracted through voice analysis to show meeting participants the direction of the discussion and the next steps to take in real time. 【0318】 The server plays a central role in effectively managing meetings. It receives meeting information in advance, detects conversation content in real time through speech analysis, and automatically generates meeting minutes and tasks. The hardware required is a server computer with high data processing capabilities. The software uses the Google Cloud Speech-to-Text API to analyze speech data and leverages the OpenAI API to suggest and automatically generate meeting progress. 【0319】 The terminal is a device that delivers instructions from the server to users participating in a meeting in real time. Users can receive suggestions regarding the meeting's progress and information on task assignments after the meeting via their smartphones or tablets. The application on the terminal is developed using React Native and operates across platforms. 【0320】 As a concrete example, in a new product presentation at a store, the server receives product information in advance and supports the meeting's progress with prompts. Prompts such as, "The agenda for the next meeting is the introduction of the new product. Please discuss the main target audience and store placement strategy, and decide who will be in charge," are used to guide the discussion smoothly. 【0321】 This allows all participants to efficiently acquire information and take action after the meeting with a clear understanding of their tasks. 【0322】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0323】 Step 1: 【0324】 Users enter initial meeting information into a terminal. This information includes the meeting's purpose, participants, and time allocation. This information is sent to the server and stored in a database. This allows the server to understand the overall flow of the meeting and prepare accordingly. 【0325】 Step 2: 【0326】 During the meeting, the terminal sends audio data to the server. The server converts the audio data into text data using the Google Cloud Speech-to-Text API. The converted text data is analyzed by a generating AI model to determine if the discussion has deviated from its purpose or goals. If a deviation is detected, the server generates correction suggestions and sends them to the terminal. 【0327】 Step 3: 【0328】 The server uses a generative AI model to summarize the conversation based on the speech analysis results. It generates prompt sentences to present to the user. Through these prompt sentences, it sends instructions to the terminal indicating the next steps to take, thereby supporting the progress of the meeting. 【0329】 Step 4: 【0330】 After the meeting ends, the server automatically generates meeting minutes based on the audio data and analysis results. It also analyzes the tasks decided during the meeting and creates a task list automatically assigned to each person responsible. This information is sent to the terminal and notified to the user. 【0331】 Step 5: 【0332】 The terminal provides an interface for users to modify meeting minutes and task lists sent from the server if necessary. After the user makes the modifications, the information is uploaded back to the server, and the final result is shared with all participants. 【0333】 This ensures that the entire meeting proceeds smoothly and allows participants to quickly move on to the next action. 【0334】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0335】 This invention is a system that supports the effective management of meetings, and in particular offers a novel approach that takes participants' emotions into consideration. The system consists of a server, terminals, users, and an emotion engine. 【0336】 Server Functions 【0337】 The server receives meeting information input and provides an interface for storing that information. It stores the meeting's purpose, goals, participants, and time allocation entered by the user in a database and maintains the functionality to support the progress of the meeting based on this information. 【0338】 The server also utilizes voice analysis technology to analyze the voice data transmitted from the terminal in real time. This analysis helps to understand the content of the discussion and suggests course corrections if it deviates from the set objectives. 【0339】 Furthermore, the server extracts emotional data from the facial expressions and tone of voice of meeting participants via an emotion engine. This data is dynamically analyzed during the meeting and used to adjust its progress. 【0340】 The server ultimately automatically generates meeting minutes based on the key points of the meeting and assigns tasks that take sentiment data into account. This includes suggesting communication strategies that consider the emotional state of each participant. 【0341】 Device functions 【0342】 The terminal receives progress corrections and sentiment-based suggestions from the server and notifies meeting participants in real time. This allows participants to participate in the discussion while being aware of their own emotional state and the progress of the meeting. 【0343】 Feedback based on sentiment data provided through the device enables participants to engage in more meaningful discussions. Furthermore, the device distributes generated meeting minutes and task information to participants after the meeting, facilitating subsequent actions. 【0344】 User actions 【0345】 The user first enters basic meeting information into the system. During the meeting, the terminal displays feedback from an emotion engine, allowing the user to adjust their comments and participation in the discussion. After the meeting, the user reviews the automatically generated minutes and tasks, making manual adjustments as needed. 【0346】 For example, if a user holds a meeting to get feedback on a presentation, the server analyzes the presenter's and audience's sentiment data and suggests adjustments to the presentation based on the audience's reactions. This information is shared with the presenter in real time via their device, providing valuable insights to improve the quality of the presentation. 【0347】 This system dynamically captures emotions during meetings and enables efficient progress, providing an advanced and effective solution to traditional meeting management. 【0348】 The following describes the processing flow. 【0349】 Step 1: 【0350】 The user enters the meeting's purpose, goals, participants, and time allocation into the interface. The server receives this information and stores it in a database. 【0351】 Step 2: 【0352】 The server retrieves data regarding the meeting schedule and structure, and checks the participant list. The terminal sends meeting notifications to participants, prompting them to prepare. 【0353】 Step 3: 【0354】 As soon as the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server performs audio analysis to understand the content and progress of the discussion. 【0355】 Step 4: 【0356】 The server uses an emotion engine to analyze the tone of voice and facial expression data of meeting participants and obtain their emotional state. The emotional data is dynamically analyzed in conjunction with the progress of the meeting. 【0357】 Step 5: 【0358】 Based on the analysis results, the server detects deviations from the set objectives and goals and, if necessary, proposes course corrections that take sentiment data into consideration. The terminal then notifies the meeting participants of these suggestions. 【0359】 Step 6: 【0360】 After the meeting ends, the server automatically generates meeting minutes and assigns tasks considering emotional data. Specifically, it formulates task priorities and communication strategies based on each participant's emotional state. 【0361】 Step 7: 【0362】 The terminal distributes the generated meeting minutes and task information to participants, clarifying the next steps. Users review this information and make necessary corrections or additions to utilize the meeting results. 【0363】 (Example 2) 【0364】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0365】 Traditional meeting management systems failed to dynamically grasp participants' emotions and the progress of the meeting, and to adequately adjust the meeting's flow based on that information. This sometimes led to discussions deviating from the set objectives and goals, resulting in inefficient meetings. Furthermore, the lack of efficient means to summarize meeting results and appropriately translate them into subsequent actions sometimes hindered the smooth execution of post-meeting tasks. 【0366】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0367】 In this invention, the server includes a function for inputting information such as the purpose, goals, participants, and time allocation of a meeting; a function for processing the dialogue during the meeting based on the input information and adjusting the direction of the meeting; and a function for extracting and analyzing participants' emotional data in real time during the meeting and dynamically optimizing the progress. This not only enables effective management of the meeting progress and dynamic adjustments based on participants' emotions, but also allows for quick and accurate translation of meeting results into subsequent actions. 【0368】 The "objective of the meeting" refers to the ultimate goal of the meeting, and the specific results or conclusions that should be achieved when the meeting concludes. 【0369】 A "goal" refers to a specific objective that should be achieved in the short or long term during a meeting, and serves as a guide for the progress of the meeting. 【0370】 "Participants" refer to those who attend a meeting, engage in discussions and exchange opinions, and are the main actors in decision-making and information sharing. 【0371】 "Time allocation" refers to the distribution of time to each item or agenda item that makes up a meeting, and is a standard for conducting a meeting efficiently. 【0372】 "Speech processing" refers to the technology of analyzing audio data collected during a meeting, converting it into text, or extracting distinctive audio features. 【0373】 The "ability to adjust the direction of progress" refers to the ability to propose course corrections when discussions or dialogues during a meeting deviate from the set objectives or goals. 【0374】 "Emotional data" refers to information that quantifies or categorizes the feelings and attitudes extracted from participants' facial expressions, tone of voice, and word choice. 【0375】 The "dynamic optimization function" refers to the ability to perform optimal progress and adjustments on the spot based on data acquired in real time during a meeting. 【0376】 This invention is a system that innovatively supports meeting management, and aims to improve the efficiency and outcome of meetings, particularly by utilizing participant emotional data. The system consists of a server, terminals, users, and an emotional engine. 【0377】 Server Role 【0378】 The server first receives information from the user, such as the purpose, goals, participants, and time allocation of the meeting. This information is stored in a database and forms the foundation for supporting the overall progress of the meeting. For speech processing technology, cloud services such as the Google Cloud Speech-to-Text API are used to transcribe the audio data during the meeting in real time and determine whether the discussion content deviates from the set goals. In addition, sentiment analysis tools such as the Microsoft Azure Emotion API are used to analyze emotional data from the tone of voice and facial expressions of the participants. 【0379】 Terminal role 【0380】 The terminal receives real-time updates from the server during the meeting, including proposed revisions and sentiment-based suggestions, and notifies participants. This allows participants to adjust their comments and discussions on the spot. After the meeting ends, the terminal distributes meeting minutes and tasks automatically generated by the server to participants, supporting them in carrying out their next actions. 【0381】 User interaction 【0382】 Users establish a foundation for meeting management by inputting basic meeting information into the system. During the meeting, users can adjust the direction of the discussion by referring to the feedback provided by the terminal. After the meeting, users can review the generated minutes and tasks and make manual adjustments as needed. 【0383】 Specific example 【0384】 A concrete example is a case where users hold a meeting to gather feedback for product development. In this case, the server analyzes participants' sentiment data in real time and suggests course corrections to the discussion based on how each comment is received. This information is immediately shared with the user via their terminal, providing insights to make the discussion more effective. 【0385】 Example of a prompt 【0386】 "Please describe a system that analyzes participants' emotions during product development feedback meetings, measures their reactions, and suggests adjustments to the process." 【0387】 Thus, the present invention enables meeting management that takes participants' emotions into consideration, and is a system that yields superior results compared to conventional management methods. 【0388】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0389】 Step 1: 【0390】 Users input basic information into the system, such as the purpose, goals, participants, and time allocation of the meeting. This information is sent to the server and stored in the database. The entered information is processed as initial setup data to support the progress of the meeting. 【0391】 Step 2: 【0392】 The terminal sends the audio data collected during the meeting to the server. The server converts this data into text using speech analysis technology. Specifically, it processes the audio data using the Google Cloud Speech-to-Text API and generates the result as text output. This makes it possible to monitor the content of the discussion. 【0393】 Step 3: 【0394】 The server analyzes the converted text data in real time to determine whether the meeting is deviating from its set objectives and goals. This analysis uses natural language processing techniques, making decisions by analyzing keywords and context. As output, suggested revisions to the meeting's progress are generated as needed. 【0395】 Step 4: 【0396】 The server uses an emotion engine to extract participant emotion data. Audio and video data from the meeting are used as input, and emotion analysis tools such as the Microsoft Azure Emotion API categorize and quantify participants' emotions. This information becomes output data used to adjust the meeting's progress. 【0397】 Step 5: 【0398】 The server generates proposed revisions and sentiment-based suggestions based on the meeting's progress and sentiment data, and sends them to the terminal. The terminal notifies participants in real time, helping users adjust their comments and discussions on the spot. 【0399】 Step 6: 【0400】 Once the meeting concludes, the server automatically generates meeting minutes based on the audio analysis results and the recorded proceedings. This process extracts key points and decisions made during the meeting and outputs them in a structured document format. The generated minutes are then shared with the participants. 【0401】 Step 7: 【0402】 Ultimately, the server assigns tasks to each participant, taking emotional data into consideration, and proposes the optimal communication strategy. The output tasks, which take each participant's emotional state into account, are synchronized to the communication application via the terminal to support the next action. 【0403】 (Application Example 2) 【0404】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0405】 Modern family communication presents a challenge in preventing conflicts arising from emotional misunderstandings. In particular, family dialogue requires flexible responses to changing emotions, but appropriate real-time feedback is often lacking. This can hinder smooth and meaningful communication. 【0406】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0407】 In this invention, the server includes means for inputting information such as the purpose, goals, participants, and time allocation of a meeting; means for performing voice analysis of the discussion during the meeting based on the input information and correcting the course of progress; and means for observing conversations within the home, analyzing the emotions of the participants, and suggesting ways to proceed. This makes it possible to analyze emotions during conversations within the home, enabling more constructive and smoother communication. 【0408】 A "meeting" is a place where multiple participants gather to share information and discuss in order to achieve a specific purpose or goal. 【0409】 "Purpose" refers to the specific main theme or goal that should be achieved during the process of a meeting or discussion. 【0410】 "Participants" refer to individuals who gather in a meeting or discussion to exchange opinions and share information. 【0411】 "Time allocation" refers to the distribution of time allocated to each topic throughout a meeting or discussion. 【0412】 "Voice analysis" is a technology that analyzes participants' statements in order to understand the content of a discussion. 【0413】 "Correcting the course of progress" means appropriately adjusting the content and flow of a meeting or discussion so that it does not deviate from its set objectives. 【0414】 "Emotional analysis" is a technique that analyzes participants' emotions from their tone of voice and facial expressions during conversations. 【0415】 A "proposal" is the act of presenting specific policies or action plans to improve the process or dialogue. 【0416】 "Automatically generating records" means that the system automatically transcribes important information from conversations and dialogues into written form. 【0417】 "Next steps" refer to the specific actions each participant should take based on the outcome of the conversation. 【0418】 To implement this invention, it is necessary to construct a system using a server, a terminal, and an emotion analysis engine. The server includes a database for managing information such as the purpose, goals, participants, and time allocation related to meetings and conversations within the home. The server uses speech analysis technology to analyze the content of discussions and conversations in real time and suggests corrections to the process if it deviates from the set goals. 【0419】 Furthermore, the server extracts emotional data from participants' facial expressions and tone of voice via an emotion analysis engine. This extracted emotional data is used to adjust the flow of the conversation, allowing the server to make appropriate suggestions in real time. Specifically, for example, if an emotional conflict arises during a conversation, the server can suggest a reconciliation or a change of topic. 【0420】 The terminal notifies participants in meetings and discussions in real time of proposed revisions and feedback based on sentiment analysis sent from the server. Based on this information, participants can adjust their statements and achieve more meaningful communication. 【0421】 The user inputs basic conversation information into the server through the interface and receives emotional feedback via their device. This allows for dynamic adjustments to the conversation's progression, and ultimately, the automatically generated record can be reviewed and edited as needed. An example of a prompt for the generating AI model is, "Scenario where a family conversation has started to become confrontational: Please suggest something for when Mom is feeling frustrated." 【0422】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0423】 Step 1: 【0424】 The user enters basic information about the meeting or home conversation (purpose, goals, participants, time allocation) into the device. The entered information is sent to the server and stored in the database. Based on this information, the system is ready for subsequent voice analysis and sentiment analysis. 【0425】 Step 2: 【0426】 The server receives audio data transmitted from terminals in real time. It uses a speech analysis engine to analyze the content of discussions and conversations. The input is audio data, and the output is a textualized transcript of the discussion and identification of topics. This analysis allows for an evaluation of progress toward the set objectives and goals. 【0427】 Step 3: 【0428】 The server uses an emotion analysis engine to extract emotional data from participants' audio and camera footage. The inputs are audio and video data, and the output is the analysis of their emotional state. For example, it assesses levels of joy, anger, and stress based on voice tone and facial expression changes. This information can then be used to adjust the program's progress. 【0429】 Step 4: 【0430】 The server integrates the results of speech analysis and sentiment analysis to generate suggested course corrections and emotion-based recommendations. The input is the speech analysis results and sentiment analysis results, and the output is a suggested message. Specifically, it provides concrete actions to correct the course of the conversation and emotionally conscious directions for the discussion. 【0431】 Step 5: 【0432】 The terminal notifies participants in real time of suggestion messages received from the server. The output is visual or auditory suggestion information provided to participants. This allows participants to immediately adjust the flow of the conversation and achieve emotionally resonant communication. 【0433】 Step 6: 【0434】 After the conversation ends, the server automatically generates a summary of the conversation's key points and assigns tasks to each participant. The input is the audio data of the entire conversation and the analysis results, while the output is a text-based record and task assignments. This automatically generated record is provided to the user via their terminal, allowing for editing and additions as needed. 【0435】 The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0436】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0437】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0438】 [Third Embodiment] 【0439】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0440】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0441】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0442】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0443】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0444】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0445】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0446】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0447】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0448】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0449】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0450】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0451】 This invention provides an AI-powered meeting management system for effectively conducting meetings. This system consists of three main components: a server, terminals, and users. 【0452】 Server Functions 【0453】 The server provides an interface for receiving and storing meeting information. It stores data such as the purpose, goals, participants, and time allocation of meetings entered by users, and uses this information to support the progress of the meeting. 【0454】 Furthermore, the server has an audio analysis function that processes audio data transmitted from terminals during meetings in real time. This analysis helps understand the content of the discussion and suggests adjustments to the progress based on the set goals. For example, if the discussion deviates from the agenda, it identifies the next topic to move on to and makes a suggestion through the terminal. 【0455】 The server also has the capability to record meeting discussions and automatically create meeting minutes. Furthermore, it analyzes the action items decided in the meeting, automatically assigns tasks to the appropriate personnel, and generates related documents. 【0456】 Device functions 【0457】 The terminal is a device that receives instructions from the server and notifies meeting participants of suggestions and modifications to the meeting's progress. This allows the terminal to support the meeting's progress in real time, enabling participants to make decisions efficiently. 【0458】 Furthermore, the terminal functions as a means of communication for distributing generated meeting minutes and task information to all participants. The information sent through the terminal enables stakeholders to quickly take necessary actions after the meeting. 【0459】 User actions 【0460】 The user first enters meeting information into the system. This allows the server to understand the purpose and flow of the meeting and prepare to provide the necessary support. During the meeting, the user is also responsible for deciding whether to accept any proposed revisions to the meeting's progress based on the results of the audio analysis. After the meeting, the user reviews the automatically generated minutes and task assignments and makes any necessary corrections. 【0461】 As a concrete example, suppose a user sets up a project progress meeting. In this case, the server supports the progress based on project-related data received in advance, making appropriate corrections and suggestions as needed. After the meeting, the user can review the automatically generated materials and effectively share information about the next steps with the participants. 【0462】 Thus, the system of the present invention enables meetings to proceed smoothly, allowing all participants to share information and act with maximum efficiency. 【0463】 The following describes the processing flow. 【0464】 Step 1: 【0465】 The user enters necessary information, including the meeting's purpose, goals, participants, and time allocation, into the system interface. The server receives this input information and stores it in a database. 【0466】 Step 2: 【0467】 The server checks the meeting schedule based on the received information and verifies that the data is accurate. The terminal sends a confirmation message to the meeting participants, prompting them to confirm the appointment. 【0468】 Step 3: 【0469】 Once the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server uses AI to analyze this audio and identify the topics being discussed and the speakers. 【0470】 Step 4: 【0471】 The server compares the analysis results with the set meeting goals and generates correction suggestions if the progress has deviated. The terminal notifies meeting participants of these suggestions and prompts them to adjust the progress as needed. 【0472】 Step 5: 【0473】 After the meeting ends, the server extracts key points from the audio data and automatically generates meeting minutes. The server then analyzes the next steps and automatically assigns them to the appropriate participants. 【0474】 Step 6: 【0475】 The terminal distributes the generated meeting minutes and task assignment information to all meeting participants, sharing information about the next steps. Users receive this information, review it, and make adjustments as needed. 【0476】 (Example 1) 【0477】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0478】 In today's work environment, meetings are frequent but often inefficient. Participants may engage in discussions that deviate from the meeting's purpose and objectives, or the necessary actions and responsibilities after the meeting may be unclear. This leads to problems with meeting productivity and subsequent actions. 【0479】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0480】 In this invention, the server includes means for inputting data such as the purpose, objectives, participants, and time allocation of a meeting; means for performing voice analysis of the dialogue during communication based on the input data and correcting the course of the meeting; and means for processing the voice data in real time using a generative machine learning model. This makes it possible to manage the progress of the meeting in accordance with its purpose and objectives at all times, and to clarify the actions and responsibilities required after the meeting. 【0481】 The "purpose of a meeting" refers to the ultimate outcome or result that is intended to be achieved through the meeting. 【0482】 "Goals" refer to the specific tasks or topics that should be achieved during the meeting. 【0483】 "Participants" refers to the people or organizations that attend the meeting. 【0484】 "Time allocation" refers to the amount of time that is assigned to each agenda item or session in a meeting. 【0485】 "Means of inputting data" refers to methods or devices used to bring information into a system. 【0486】 "Dialogue during communication" refers to the exchange of information, whether verbal or written, that takes place during a meeting. 【0487】 "Speech analysis" refers to the technology and process of analyzing audio data and deciphering or evaluating its content. 【0488】 "Means of correcting the course of progress" refers to methods or devices for guiding discussions that have strayed from the purpose of a meeting back to their original objective. 【0489】 A "generative machine learning model" is an algorithm or framework that learns from data and performs predictions and classifications. 【0490】 "Means for processing audio data in real time" refers to technologies and devices that instantly analyze audio information and make the results available in real time. 【0491】 This meeting management system is implemented using three main components: servers, terminals, and users. 【0492】 Server Functions 【0493】 The server plays a central role in receiving and storing user-entered data on meeting purpose, objectives, participants, and time allocation. The server uses a generative AI model to process audio data in real time and analyze the dialogue during the meeting. This generative AI model employs advanced analysis software, such as speech analysis systems and natural language processing algorithms. The analyzed data is used to determine whether course corrections are needed to the meeting. 【0494】 Device functions 【0495】 The terminal is a device that receives information transmitted from the server and notifies meeting participants. The terminal uses a microphone and speaker to transmit audio data to the server and also receives feedback from the server. This device can be an existing communication device, such as a tablet or smartphone. 【0496】 User actions 【0497】 As part of the initial setup for the meeting, the user enters data into their terminal. This data is sent to the server, and the system begins operation. During the meeting, the user reviews the progress suggestions from the server and makes decisions as needed. After the meeting ends, the user reviews the automatically generated record and task assignments and makes corrections as necessary. 【0498】 As a concrete example, let's assume a user is setting up a meeting to plan the launch of a new product. The user inputs all the relevant information, and the server uses this to support the progress of the session. An example of a prompt might be, "What are the goals to be achieved in this project meeting? Are there any specific agenda items or action items?" 【0499】 In this way, the system efficiently manages meetings and enables all participants to discuss and make decisions in accordance with the meeting's purpose and objectives. 【0500】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0501】 Step 1: 【0502】 The user enters data such as the meeting's purpose, objectives, participants, and time allocation into the terminal. The entered data is then sent from the terminal to the server. The server receives the specific meeting settings and prepares for the next processing step. 【0503】 Step 2: 【0504】 The server stores the received meeting information in a database. Based on this data, the server prepares to analyze the next audio data using a generative AI model. The stored information forms the basis for real-time progress management. 【0505】 Step 3: 【0506】 As soon as the meeting begins, the terminal captures audio data through the microphone and sends it to the server. The transmitted audio data is received and analyzed by the server. This allows the server to check in real time whether the current discussion is aligned with the meeting's purpose and objectives. 【0507】 Step 4: 【0508】 The server uses a generative AI model to analyze received audio data in real time. The input for the analysis is the audio data sent from the terminal, and the output is a judgment on whether suggestions for progress or corrections regarding the agenda are necessary. Specifically, if the discussion deviates from the topic, a suggestion such as "The next agenda item to discuss is XX" is generated. 【0509】 Step 5: 【0510】 The terminal receives progress suggestions and correction information from the server. The terminal notifies meeting participants of this information via display and audio. This allows participants to appropriately adjust the direction of the meeting. 【0511】 Step 6: 【0512】 After the meeting ends, the server automatically generates meeting minutes based on the analysis results, assigns the next tasks to each participant, and distributes relevant information. Users review the generated minutes, check for accuracy, and make corrections as needed. 【0513】 This process allows the system to maximize meeting efficiency, ensure all participants share information accurately, and facilitate smooth progress to the next steps. 【0514】 (Application Example 1) 【0515】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0516】 In information-sharing settings such as meetings and staff meetings, effective progress management is required to ensure that all participants efficiently communicate information and advance discussions. However, deviations from the agenda and unclear sharing of decisions often occur, making effective information transmission difficult. In particular, the lack of means for real-time progress management and prompt instructions for action after the meeting has ended is a problem. 【0517】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0518】 In this invention, the server includes means for analyzing the content of conversations in real time and correcting the progress, means for automatically generating information based on the meeting results and automatically assigning and sharing the next steps, and means for distributing the generated information to relevant parties. This enables efficient information transmission and effective management of meeting progress. 【0519】 "Meeting information" refers to basic data necessary for the smooth running of a meeting, such as participants, objectives, and time allocation. 【0520】 "Voice analysis" is a technology that acquires the content spoken during a meeting as digital audio data and converts it into text information. 【0521】 "Correcting the course of the meeting" is a means of suggesting an appropriate direction for discussion and returning to the original course when the meeting has deviated from its set objectives or goals. 【0522】 "Automatic information generation" refers to the process where AI independently creates meeting minutes, next-step tasks, and other information based on the content discussed in a meeting. 【0523】 The "means of making suggestions" refers to a function that uses data extracted through voice analysis to show meeting participants the direction of the discussion and the next steps to take in real time. 【0524】 The server plays a central role in effectively managing meetings. It receives meeting information in advance, detects conversation content in real time through speech analysis, and automatically generates meeting minutes and tasks. The hardware required is a server computer with high data processing capabilities. The software uses the Google Cloud Speech-to-Text API to analyze speech data and leverages the OpenAI API to suggest and automatically generate meeting progress. 【0525】 The terminal is a device that delivers instructions from the server to users participating in a meeting in real time. Users can receive suggestions regarding the meeting's progress and information on task assignments after the meeting via their smartphones or tablets. The application on the terminal is developed using React Native and operates across platforms. 【0526】 As a concrete example, in a new product presentation at a store, the server receives product information in advance and supports the meeting's progress with prompts. Prompts such as, "The agenda for the next meeting is the introduction of the new product. Please discuss the main target audience and store placement strategy, and decide who will be in charge," are used to guide the discussion smoothly. 【0527】 This allows all participants to efficiently acquire information and take action after the meeting with a clear understanding of their tasks. 【0528】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0529】 Step 1: 【0530】 Users enter initial meeting information into a terminal. This information includes the meeting's purpose, participants, and time allocation. This information is sent to the server and stored in a database. This allows the server to understand the overall flow of the meeting and prepare accordingly. 【0531】 Step 2: 【0532】 During the meeting, the terminal sends audio data to the server. The server converts the audio data into text data using the Google Cloud Speech-to-Text API. The converted text data is analyzed by a generating AI model to determine if the discussion has deviated from its purpose or goals. If a deviation is detected, the server generates correction suggestions and sends them to the terminal. 【0533】 Step 3: 【0534】 The server uses a generative AI model to summarize the conversation based on the speech analysis results. It generates prompt sentences to present to the user. Through these prompt sentences, it sends instructions to the terminal indicating the next steps to take, thereby supporting the progress of the meeting. 【0535】 Step 4: 【0536】 After the meeting ends, the server automatically generates meeting minutes based on the audio data and analysis results. It also analyzes the tasks decided during the meeting and creates a task list automatically assigned to each person responsible. This information is sent to the terminal and notified to the user. 【0537】 Step 5: 【0538】 The terminal provides an interface for users to modify meeting minutes and task lists sent from the server if necessary. After the user makes the modifications, the information is uploaded back to the server, and the final result is shared with all participants. 【0539】 This ensures that the entire meeting proceeds smoothly and allows participants to quickly move on to the next action. 【0540】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0541】 This invention is a system that supports the effective management of meetings, and in particular offers a novel approach that takes participants' emotions into consideration. The system consists of a server, terminals, users, and an emotion engine. 【0542】 Server Functions 【0543】 The server receives meeting information input and provides an interface for storing that information. It stores the meeting's purpose, goals, participants, and time allocation entered by the user in a database and maintains the functionality to support the progress of the meeting based on this information. 【0544】 The server also utilizes voice analysis technology to analyze the voice data transmitted from the terminal in real time. This analysis helps to understand the content of the discussion and suggests course corrections if it deviates from the set objectives. 【0545】 Furthermore, the server extracts emotional data from the facial expressions and tone of voice of meeting participants via an emotion engine. This data is dynamically analyzed during the meeting and used to adjust its progress. 【0546】 The server ultimately automatically generates meeting minutes based on the key points of the meeting and assigns tasks that take sentiment data into account. This includes suggesting communication strategies that consider the emotional state of each participant. 【0547】 Device functions 【0548】 The terminal receives progress corrections and sentiment-based suggestions from the server and notifies meeting participants in real time. This allows participants to participate in the discussion while being aware of their own emotional state and the progress of the meeting. 【0549】 Feedback based on sentiment data provided through the device enables participants to engage in more meaningful discussions. Furthermore, the device distributes generated meeting minutes and task information to participants after the meeting, facilitating subsequent actions. 【0550】 User actions 【0551】 The user first enters basic meeting information into the system. During the meeting, the terminal displays feedback from an emotion engine, allowing the user to adjust their comments and participation in the discussion. After the meeting, the user reviews the automatically generated minutes and tasks, making manual adjustments as needed. 【0552】 For example, if a user holds a meeting to get feedback on a presentation, the server analyzes the presenter's and audience's sentiment data and suggests adjustments to the presentation based on the audience's reactions. This information is shared with the presenter in real time via their device, providing valuable insights to improve the quality of the presentation. 【0553】 This system dynamically captures emotions during meetings and enables efficient progress, providing an advanced and effective solution to traditional meeting management. 【0554】 The following describes the processing flow. 【0555】 Step 1: 【0556】 The user enters the meeting's purpose, goals, participants, and time allocation into the interface. The server receives this information and stores it in a database. 【0557】 Step 2: 【0558】 The server retrieves data regarding the meeting schedule and structure, and checks the participant list. The terminal sends meeting notifications to participants, prompting them to prepare. 【0559】 Step 3: 【0560】 As soon as the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server performs audio analysis to understand the content and progress of the discussion. 【0561】 Step 4: 【0562】 The server uses an emotion engine to analyze the tone of voice and facial expression data of meeting participants and obtain their emotional state. The emotional data is dynamically analyzed in conjunction with the progress of the meeting. 【0563】 Step 5: 【0564】 Based on the analysis results, the server detects deviations from the set objectives and goals and, if necessary, proposes course corrections that take sentiment data into consideration. The terminal then notifies the meeting participants of these suggestions. 【0565】 Step 6: 【0566】 After the meeting ends, the server automatically generates meeting minutes and assigns tasks considering emotional data. Specifically, it formulates task priorities and communication strategies based on each participant's emotional state. 【0567】 Step 7: 【0568】 The terminal distributes the generated meeting minutes and task information to participants, clarifying the next steps. Users review this information and make necessary corrections or additions to utilize the meeting results. 【0569】 (Example 2) 【0570】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0571】 Traditional meeting management systems failed to dynamically grasp participants' emotions and the progress of the meeting, and to adequately adjust the meeting's flow based on that information. This sometimes led to discussions deviating from the set objectives and goals, resulting in inefficient meetings. Furthermore, the lack of efficient means to summarize meeting results and appropriately translate them into subsequent actions sometimes hindered the smooth execution of post-meeting tasks. 【0572】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0573】 In this invention, the server includes a function for inputting information such as the purpose, goals, participants, and time allocation of a meeting; a function for processing the dialogue during the meeting based on the input information and adjusting the direction of the meeting; and a function for extracting and analyzing participants' emotional data in real time during the meeting and dynamically optimizing the progress. This not only enables effective management of the meeting progress and dynamic adjustments based on participants' emotions, but also allows for quick and accurate translation of meeting results into subsequent actions. 【0574】 The "objective of the meeting" refers to the ultimate goal of the meeting, and the specific results or conclusions that should be achieved when the meeting concludes. 【0575】 A "goal" refers to a specific objective that should be achieved in the short or long term during a meeting, and serves as a guide for the progress of the meeting. 【0576】 "Participants" refer to those who attend a meeting, engage in discussions and exchange opinions, and are the main actors in decision-making and information sharing. 【0577】 "Time allocation" refers to the distribution of time to each item or agenda item that makes up a meeting, and is a standard for conducting a meeting efficiently. 【0578】 "Speech processing" refers to the technology of analyzing audio data collected during a meeting, converting it into text, or extracting distinctive audio features. 【0579】 The "ability to adjust the direction of progress" refers to the ability to propose course corrections when discussions or dialogues during a meeting deviate from the set objectives or goals. 【0580】 "Emotional data" refers to information that quantifies or categorizes the feelings and attitudes extracted from participants' facial expressions, tone of voice, and word choice. 【0581】 The "dynamic optimization function" refers to the ability to perform optimal progress and adjustments on the spot based on data acquired in real time during a meeting. 【0582】 This invention is a system that innovatively supports meeting management, and aims to improve the efficiency and outcome of meetings, particularly by utilizing participant emotional data. The system consists of a server, terminals, users, and an emotional engine. 【0583】 Server Role 【0584】 The server first receives information from the user, such as the purpose, goals, participants, and time allocation of the meeting. This information is stored in a database and forms the foundation for supporting the overall progress of the meeting. For speech processing technology, cloud services such as the Google Cloud Speech-to-Text API are used to transcribe the audio data during the meeting in real time and determine whether the discussion content deviates from the set goals. In addition, sentiment analysis tools such as the Microsoft Azure Emotion API are used to analyze emotional data from the tone of voice and facial expressions of the participants. 【0585】 Terminal role 【0586】 The terminal receives real-time updates from the server during the meeting, including proposed revisions and sentiment-based suggestions, and notifies participants. This allows participants to adjust their comments and discussions on the spot. After the meeting ends, the terminal distributes meeting minutes and tasks automatically generated by the server to participants, supporting them in carrying out their next actions. 【0587】 User interaction 【0588】 Users establish a foundation for meeting management by inputting basic meeting information into the system. During the meeting, users can adjust the direction of the discussion by referring to the feedback provided by the terminal. After the meeting, users can review the generated minutes and tasks and make manual adjustments as needed. 【0589】 Specific example 【0590】 A concrete example is a case where users hold a meeting to gather feedback for product development. In this case, the server analyzes participants' sentiment data in real time and suggests course corrections to the discussion based on how each comment is received. This information is immediately shared with the user via their terminal, providing insights to make the discussion more effective. 【0591】 Example of a prompt 【0592】 "Please describe a system that analyzes participants' emotions during product development feedback meetings, measures their reactions, and suggests adjustments to the process." 【0593】 Thus, the present invention enables meeting management that takes participants' emotions into consideration, and is a system that yields superior results compared to conventional management methods. 【0594】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0595】 Step 1: 【0596】 Users input basic information into the system, such as the purpose, goals, participants, and time allocation of the meeting. This information is sent to the server and stored in the database. The entered information is processed as initial setup data to support the progress of the meeting. 【0597】 Step 2: 【0598】 The terminal sends the audio data collected during the meeting to the server. The server converts this data into text using speech analysis technology. Specifically, it processes the audio data using the Google Cloud Speech-to-Text API and generates the result as text output. This makes it possible to monitor the content of the discussion. 【0599】 Step 3: 【0600】 The server analyzes the converted text data in real time to determine whether the meeting is deviating from its set objectives and goals. This analysis uses natural language processing techniques, making decisions by analyzing keywords and context. As output, suggested revisions to the meeting's progress are generated as needed. 【0601】 Step 4: 【0602】 The server uses an emotion engine to extract participant emotion data. Audio and video data from the meeting are used as input, and emotion analysis tools such as the Microsoft Azure Emotion API categorize and quantify participants' emotions. This information becomes output data used to adjust the meeting's progress. 【0603】 Step 5: 【0604】 The server generates proposed revisions and sentiment-based suggestions based on the meeting's progress and sentiment data, and sends them to the terminal. The terminal notifies participants in real time, helping users adjust their comments and discussions on the spot. 【0605】 Step 6: 【0606】 Once the meeting concludes, the server automatically generates meeting minutes based on the audio analysis results and the recorded proceedings. This process extracts key points and decisions made during the meeting and outputs them in a structured document format. The generated minutes are then shared with the participants. 【0607】 Step 7: 【0608】 Ultimately, the server assigns tasks to each participant, taking emotional data into consideration, and proposes the optimal communication strategy. The output tasks, which take each participant's emotional state into account, are synchronized to the communication application via the terminal to support the next action. 【0609】 (Application Example 2) 【0610】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0611】 Modern family communication presents a challenge in preventing conflicts arising from emotional misunderstandings. In particular, family dialogue requires flexible responses to changing emotions, but appropriate real-time feedback is often lacking. This can hinder smooth and meaningful communication. 【0612】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0613】 In this invention, the server includes means for inputting information such as the purpose, goals, participants, and time allocation of a meeting; means for performing voice analysis of the discussion during the meeting based on the input information and correcting the course of progress; and means for observing conversations within the home, analyzing the emotions of the participants, and suggesting ways to proceed. This makes it possible to analyze emotions during conversations within the home, enabling more constructive and smoother communication. 【0614】 A "meeting" is a place where multiple participants gather to share information and discuss in order to achieve a specific purpose or goal. 【0615】 "Purpose" refers to the specific main theme or goal that should be achieved during the process of a meeting or discussion. 【0616】 "Participants" refer to individuals who gather in a meeting or discussion to exchange opinions and share information. 【0617】 "Time allocation" refers to the distribution of time allocated to each topic throughout a meeting or discussion. 【0618】 "Voice analysis" is a technology that analyzes participants' statements in order to understand the content of a discussion. 【0619】 "Correcting the course of progress" means appropriately adjusting the content and flow of a meeting or discussion so that it does not deviate from its set objectives. 【0620】 "Emotional analysis" is a technique that analyzes participants' emotions from their tone of voice and facial expressions during conversations. 【0621】 A "proposal" is the act of presenting specific policies or action plans to improve the process or dialogue. 【0622】 "Automatically generating records" means that the system automatically transcribes important information from conversations and dialogues into written form. 【0623】 "Next steps" refer to the specific actions each participant should take based on the outcome of the conversation. 【0624】 To implement this invention, it is necessary to construct a system using a server, a terminal, and an emotion analysis engine. The server includes a database for managing information such as the purpose, goals, participants, and time allocation related to meetings and conversations within the home. The server uses speech analysis technology to analyze the content of discussions and conversations in real time and suggests corrections to the process if it deviates from the set goals. 【0625】 Furthermore, the server extracts emotional data from participants' facial expressions and tone of voice via an emotion analysis engine. This extracted emotional data is used to adjust the flow of the conversation, allowing the server to make appropriate suggestions in real time. Specifically, for example, if an emotional conflict arises during a conversation, the server can suggest a reconciliation or a change of topic. 【0626】 The terminal notifies participants in meetings and discussions in real time of proposed revisions and feedback based on sentiment analysis sent from the server. Based on this information, participants can adjust their statements and achieve more meaningful communication. 【0627】 The user inputs basic conversation information into the server through the interface and receives emotional feedback via their device. This allows for dynamic adjustments to the conversation's progression, and ultimately, the automatically generated record can be reviewed and edited as needed. An example of a prompt for the generating AI model is, "Scenario where a family conversation has started to become confrontational: Please suggest something for when Mom is feeling frustrated." 【0628】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0629】 Step 1: 【0630】 The user enters basic information about the meeting or home conversation (purpose, goals, participants, time allocation) into the device. The entered information is sent to the server and stored in the database. Based on this information, the system is ready for subsequent voice analysis and sentiment analysis. 【0631】 Step 2: 【0632】 The server receives audio data transmitted from terminals in real time. It uses a speech analysis engine to analyze the content of discussions and conversations. The input is audio data, and the output is a textualized transcript of the discussion and identification of topics. This analysis allows for an evaluation of progress toward the set objectives and goals. 【0633】 Step 3: 【0634】 The server uses an emotion analysis engine to extract emotional data from participants' audio and camera footage. The inputs are audio and video data, and the output is the analysis of their emotional state. For example, it assesses levels of joy, anger, and stress based on voice tone and facial expression changes. This information can then be used to adjust the program's progress. 【0635】 Step 4: 【0636】 The server integrates the results of speech analysis and sentiment analysis to generate suggested course corrections and emotion-based recommendations. The input is the speech analysis results and sentiment analysis results, and the output is a suggested message. Specifically, it provides concrete actions to correct the course of the conversation and emotionally conscious directions for the discussion. 【0637】 Step 5: 【0638】 The terminal notifies participants in real time of suggestion messages received from the server. The output is visual or auditory suggestion information provided to participants. This allows participants to immediately adjust the flow of the conversation and achieve emotionally resonant communication. 【0639】 Step 6: 【0640】 After the conversation ends, the server automatically generates a summary of the conversation's key points and assigns tasks to each participant. The input is the audio data of the entire conversation and the analysis results, while the output is a text-based record and task assignments. This automatically generated record is provided to the user via their terminal, allowing for editing and additions as needed. 【0641】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0642】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0643】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0644】 [Fourth Embodiment] 【0645】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0646】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0647】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0648】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0649】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0650】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0651】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0652】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0653】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0654】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0655】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0656】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0657】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0658】 This invention provides an AI-powered meeting management system for effectively conducting meetings. This system consists of three main components: a server, terminals, and users. 【0659】 Server Functions 【0660】 The server provides an interface for receiving and storing meeting information. It stores data such as the purpose, goals, participants, and time allocation of meetings entered by users, and uses this information to support the progress of the meeting. 【0661】 Furthermore, the server has an audio analysis function that processes audio data transmitted from terminals during meetings in real time. This analysis helps understand the content of the discussion and suggests adjustments to the progress based on the set goals. For example, if the discussion deviates from the agenda, it identifies the next topic to move on to and makes a suggestion through the terminal. 【0662】 The server also has the capability to record meeting discussions and automatically create meeting minutes. Furthermore, it analyzes the action items decided in the meeting, automatically assigns tasks to the appropriate personnel, and generates related documents. 【0663】 Device functions 【0664】 The terminal is a device that receives instructions from the server and notifies meeting participants of suggestions and modifications to the meeting's progress. This allows the terminal to support the meeting's progress in real time, enabling participants to make decisions efficiently. 【0665】 Furthermore, the terminal functions as a means of communication for distributing generated meeting minutes and task information to all participants. The information sent through the terminal enables stakeholders to quickly take necessary actions after the meeting. 【0666】 User actions 【0667】 The user first enters meeting information into the system. This allows the server to understand the purpose and flow of the meeting and prepare to provide the necessary support. During the meeting, the user is also responsible for deciding whether to accept any proposed revisions to the meeting's progress based on the results of the audio analysis. After the meeting, the user reviews the automatically generated minutes and task assignments and makes any necessary corrections. 【0668】 As a concrete example, suppose a user sets up a project progress meeting. In this case, the server supports the progress based on project-related data received in advance, making appropriate corrections and suggestions as needed. After the meeting, the user can review the automatically generated materials and effectively share information about the next steps with the participants. 【0669】 Thus, the system of the present invention enables meetings to proceed smoothly, allowing all participants to share information and act with maximum efficiency. 【0670】 The following describes the processing flow. 【0671】 Step 1: 【0672】 The user enters necessary information, including the meeting's purpose, goals, participants, and time allocation, into the system interface. The server receives this input information and stores it in a database. 【0673】 Step 2: 【0674】 The server checks the meeting schedule based on the received information and verifies that the data is accurate. The terminal sends a confirmation message to the meeting participants, prompting them to confirm the appointment. 【0675】 Step 3: 【0676】 Once the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server uses AI to analyze this audio and identify the topics being discussed and the speakers. 【0677】 Step 4: 【0678】 The server compares the analysis results with the set meeting goals and generates correction suggestions if the progress has deviated. The terminal notifies meeting participants of these suggestions and prompts them to adjust the progress as needed. 【0679】 Step 5: 【0680】 After the meeting ends, the server extracts key points from the audio data and automatically generates meeting minutes. The server then analyzes the next steps and automatically assigns them to the appropriate participants. 【0681】 Step 6: 【0682】 The terminal distributes the generated meeting minutes and task assignment information to all meeting participants, sharing information about the next steps. Users receive this information, review it, and make adjustments as needed. 【0683】 (Example 1) 【0684】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0685】 In today's work environment, meetings are frequent but often inefficient. Participants may engage in discussions that deviate from the meeting's purpose and objectives, or the necessary actions and responsibilities after the meeting may be unclear. This leads to problems with meeting productivity and subsequent actions. 【0686】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0687】 In this invention, the server includes means for inputting data such as the purpose, objectives, participants, and time allocation of a meeting; means for performing voice analysis of the dialogue during communication based on the input data and correcting the course of the meeting; and means for processing the voice data in real time using a generative machine learning model. This makes it possible to manage the progress of the meeting in accordance with its purpose and objectives at all times, and to clarify the actions and responsibilities required after the meeting. 【0688】 The "purpose of a meeting" refers to the ultimate outcome or result that is intended to be achieved through the meeting. 【0689】 "Goals" refer to the specific tasks or topics that should be achieved during the meeting. 【0690】 "Participants" refers to the people or organizations that attend the meeting. 【0691】 "Time allocation" refers to the amount of time that is assigned to each agenda item or session in a meeting. 【0692】 "Means of inputting data" refers to methods or devices used to bring information into a system. 【0693】 "Dialogue during communication" refers to the exchange of information, whether verbal or written, that takes place during a meeting. 【0694】 "Speech analysis" refers to the technology and process of analyzing audio data and deciphering or evaluating its content. 【0695】 "Means of correcting the course of progress" refers to methods or devices for guiding discussions that have strayed from the purpose of a meeting back to their original objective. 【0696】 A "generative machine learning model" is an algorithm or framework that learns from data and performs predictions and classifications. 【0697】 "Means for processing audio data in real time" refers to technologies and devices that instantly analyze audio information and make the results available in real time. 【0698】 This meeting management system is implemented using three main components: servers, terminals, and users. 【0699】 Server Functions 【0700】 The server plays a central role in receiving and storing user-entered data on meeting purpose, objectives, participants, and time allocation. The server uses a generative AI model to process audio data in real time and analyze the dialogue during the meeting. This generative AI model employs advanced analysis software, such as speech analysis systems and natural language processing algorithms. The analyzed data is used to determine whether course corrections are needed to the meeting. 【0701】 Device functions 【0702】 The terminal is a device that receives information transmitted from the server and notifies meeting participants. The terminal uses a microphone and speaker to transmit audio data to the server and also receives feedback from the server. This device can be an existing communication device, such as a tablet or smartphone. 【0703】 User actions 【0704】 As part of the initial setup for the meeting, the user enters data into their terminal. This data is sent to the server, and the system begins operation. During the meeting, the user reviews the progress suggestions from the server and makes decisions as needed. After the meeting ends, the user reviews the automatically generated record and task assignments and makes corrections as necessary. 【0705】 As a concrete example, let's assume a user is setting up a meeting to plan the launch of a new product. The user inputs all the relevant information, and the server uses this to support the progress of the session. An example of a prompt might be, "What are the goals to be achieved in this project meeting? Are there any specific agenda items or action items?" 【0706】 In this way, the system efficiently manages meetings and enables all participants to discuss and make decisions in accordance with the meeting's purpose and objectives. 【0707】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0708】 Step 1: 【0709】 The user enters data such as the meeting's purpose, objectives, participants, and time allocation into the terminal. The entered data is then sent from the terminal to the server. The server receives the specific meeting settings and prepares for the next processing step. 【0710】 Step 2: 【0711】 The server stores the received meeting information in a database. Based on this data, the server prepares to analyze the next audio data using a generative AI model. The stored information forms the basis for real-time progress management. 【0712】 Step 3: 【0713】 As soon as the meeting begins, the terminal captures audio data through the microphone and sends it to the server. The transmitted audio data is received and analyzed by the server. This allows the server to check in real time whether the current discussion is aligned with the meeting's purpose and objectives. 【0714】 Step 4: 【0715】 The server uses a generative AI model to analyze received audio data in real time. The input for the analysis is the audio data sent from the terminal, and the output is a judgment on whether suggestions for progress or corrections regarding the agenda are necessary. Specifically, if the discussion deviates from the topic, a suggestion such as "The next agenda item to discuss is XX" is generated. 【0716】 Step 5: 【0717】 The terminal receives progress suggestions and correction information from the server. The terminal notifies meeting participants of this information via display and audio. This allows participants to appropriately adjust the direction of the meeting. 【0718】 Step 6: 【0719】 After the meeting ends, the server automatically generates meeting minutes based on the analysis results, assigns the next tasks to each participant, and distributes relevant information. Users review the generated minutes, check for accuracy, and make corrections as needed. 【0720】 This process allows the system to maximize meeting efficiency, ensure all participants share information accurately, and facilitate smooth progress to the next steps. 【0721】 (Application Example 1) 【0722】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0723】 In information-sharing settings such as meetings and staff meetings, effective progress management is required to ensure that all participants efficiently communicate information and advance discussions. However, deviations from the agenda and unclear sharing of decisions often occur, making effective information transmission difficult. In particular, the lack of means for real-time progress management and prompt instructions for action after the meeting has ended is a problem. 【0724】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0725】 In this invention, the server includes means for analyzing the content of conversations in real time and correcting the progress, means for automatically generating information based on the meeting results and automatically assigning and sharing the next steps, and means for distributing the generated information to relevant parties. This enables efficient information transmission and effective management of meeting progress. 【0726】 "Meeting information" refers to basic data necessary for the smooth running of a meeting, such as participants, objectives, and time allocation. 【0727】 "Voice analysis" is a technology that acquires the content spoken during a meeting as digital audio data and converts it into text information. 【0728】 "Correcting the course of the meeting" is a means of suggesting an appropriate direction for discussion and returning to the original course when the meeting has deviated from its set objectives or goals. 【0729】 "Automatic information generation" refers to the process where AI independently creates meeting minutes, next-step tasks, and other information based on the content discussed in a meeting. 【0730】 The "means of making suggestions" refers to a function that uses data extracted through voice analysis to show meeting participants the direction of the discussion and the next steps to take in real time. 【0731】 The server plays a central role in effectively managing meetings. It receives meeting information in advance, detects conversation content in real time through speech analysis, and automatically generates meeting minutes and tasks. The hardware required is a server computer with high data processing capabilities. The software uses the Google Cloud Speech-to-Text API to analyze speech data and leverages the OpenAI API to suggest and automatically generate meeting progress. 【0732】 The terminal is a device that delivers instructions from the server to users participating in a meeting in real time. Users can receive suggestions regarding the meeting's progress and information on task assignments after the meeting via their smartphones or tablets. The application on the terminal is developed using React Native and operates across platforms. 【0733】 As a concrete example, in a new product presentation at a store, the server receives product information in advance and supports the meeting's progress with prompts. Prompts such as, "The agenda for the next meeting is the introduction of the new product. Please discuss the main target audience and store placement strategy, and decide who will be in charge," are used to guide the discussion smoothly. 【0734】 This allows all participants to efficiently acquire information and take action after the meeting with a clear understanding of their tasks. 【0735】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0736】 Step 1: 【0737】 Users enter initial meeting information into a terminal. This information includes the meeting's purpose, participants, and time allocation. This information is sent to the server and stored in a database. This allows the server to understand the overall flow of the meeting and prepare accordingly. 【0738】 Step 2: 【0739】 During the meeting, the terminal sends audio data to the server. The server converts the audio data into text data using the Google Cloud Speech-to-Text API. The converted text data is analyzed by a generating AI model to determine if the discussion has deviated from its purpose or goals. If a deviation is detected, the server generates correction suggestions and sends them to the terminal. 【0740】 Step 3: 【0741】 The server uses a generative AI model to summarize the conversation based on the speech analysis results. It generates prompt sentences to present to the user. Through these prompt sentences, it sends instructions to the terminal indicating the next steps to take, thereby supporting the progress of the meeting. 【0742】 Step 4: 【0743】 After the meeting ends, the server automatically generates meeting minutes based on the audio data and analysis results. It also analyzes the tasks decided during the meeting and creates a task list automatically assigned to each person responsible. This information is sent to the terminal and notified to the user. 【0744】 Step 5: 【0745】 The terminal provides an interface for users to modify meeting minutes and task lists sent from the server if necessary. After the user makes the modifications, the information is uploaded back to the server, and the final result is shared with all participants. 【0746】 This ensures that the entire meeting proceeds smoothly and allows participants to quickly move on to the next action. 【0747】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0748】 This invention is a system that supports the effective management of meetings, and in particular offers a novel approach that takes participants' emotions into consideration. The system consists of a server, terminals, users, and an emotion engine. 【0749】 Server Functions 【0750】 The server receives meeting information input and provides an interface for storing that information. It stores the meeting's purpose, goals, participants, and time allocation entered by the user in a database and maintains the functionality to support the progress of the meeting based on this information. 【0751】 The server also utilizes voice analysis technology to analyze the voice data transmitted from the terminal in real time. This analysis helps to understand the content of the discussion and suggests course corrections if it deviates from the set objectives. 【0752】 Furthermore, the server extracts emotional data from the facial expressions and tone of voice of meeting participants via an emotion engine. This data is dynamically analyzed during the meeting and used to adjust its progress. 【0753】 The server ultimately automatically generates meeting minutes based on the key points of the meeting and assigns tasks that take sentiment data into account. This includes suggesting communication strategies that consider the emotional state of each participant. 【0754】 Device functions 【0755】 The terminal receives progress corrections and sentiment-based suggestions from the server and notifies meeting participants in real time. This allows participants to participate in the discussion while being aware of their own emotional state and the progress of the meeting. 【0756】 Feedback based on sentiment data provided through the device enables participants to engage in more meaningful discussions. Furthermore, the device distributes generated meeting minutes and task information to participants after the meeting, facilitating subsequent actions. 【0757】 User actions 【0758】 The user first enters basic meeting information into the system. During the meeting, the terminal displays feedback from an emotion engine, allowing the user to adjust their comments and participation in the discussion. After the meeting, the user reviews the automatically generated minutes and tasks, making manual adjustments as needed. 【0759】 For example, if a user holds a meeting to get feedback on a presentation, the server analyzes the presenter's and audience's sentiment data and suggests adjustments to the presentation based on the audience's reactions. This information is shared with the presenter in real time via their device, providing valuable insights to improve the quality of the presentation. 【0760】 This system dynamically captures emotions during meetings and enables efficient progress, providing an advanced and effective solution to traditional meeting management. 【0761】 The following describes the processing flow. 【0762】 Step 1: 【0763】 The user enters the meeting's purpose, goals, participants, and time allocation into the interface. The server receives this information and stores it in a database. 【0764】 Step 2: 【0765】 The server retrieves data regarding the meeting schedule and structure, and checks the participant list. The terminal sends meeting notifications to participants, prompting them to prepare. 【0766】 Step 3: 【0767】 As soon as the meeting begins, the terminal captures the meeting audio and sends it to the server in real time. The server performs audio analysis to understand the content and progress of the discussion. 【0768】 Step 4: 【0769】 The server uses an emotion engine to analyze the tone of voice and facial expression data of meeting participants and obtain their emotional state. The emotional data is dynamically analyzed in conjunction with the progress of the meeting. 【0770】 Step 5: 【0771】 Based on the analysis results, the server detects deviations from the set objectives and goals and, if necessary, proposes course corrections that take sentiment data into consideration. The terminal then notifies the meeting participants of these suggestions. 【0772】 Step 6: 【0773】 After the meeting ends, the server automatically generates meeting minutes and assigns tasks considering emotional data. Specifically, it formulates task priorities and communication strategies based on each participant's emotional state. 【0774】 Step 7: 【0775】 The terminal distributes the generated meeting minutes and task information to participants, clarifying the next steps. Users review this information and make necessary corrections or additions to utilize the meeting results. 【0776】 (Example 2) 【0777】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0778】 Traditional meeting management systems failed to dynamically grasp participants' emotions and the progress of the meeting, and to adequately adjust the meeting's flow based on that information. This sometimes led to discussions deviating from the set objectives and goals, resulting in inefficient meetings. Furthermore, the lack of efficient means to summarize meeting results and appropriately translate them into subsequent actions sometimes hindered the smooth execution of post-meeting tasks. 【0779】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0780】 In this invention, the server includes a function for inputting information such as the purpose, goals, participants, and time allocation of a meeting; a function for processing the dialogue during the meeting based on the input information and adjusting the direction of the meeting; and a function for extracting and analyzing participants' emotional data in real time during the meeting and dynamically optimizing the progress. This not only enables effective management of the meeting progress and dynamic adjustments based on participants' emotions, but also allows for quick and accurate translation of meeting results into subsequent actions. 【0781】 The "objective of the meeting" refers to the ultimate goal of the meeting, and the specific results or conclusions that should be achieved when the meeting concludes. 【0782】 A "goal" refers to a specific objective that should be achieved in the short or long term during a meeting, and serves as a guide for the progress of the meeting. 【0783】 "Participants" refer to those who attend a meeting, engage in discussions and exchange opinions, and are the main actors in decision-making and information sharing. 【0784】 "Time allocation" refers to the distribution of time to each item or agenda item that makes up a meeting, and is a standard for conducting a meeting efficiently. 【0785】 "Speech processing" refers to the technology of analyzing audio data collected during a meeting, converting it into text, or extracting distinctive audio features. 【0786】 The "ability to adjust the direction of progress" refers to the ability to propose course corrections when discussions or dialogues during a meeting deviate from the set objectives or goals. 【0787】 "Emotional data" refers to information that quantifies or categorizes the feelings and attitudes extracted from participants' facial expressions, tone of voice, and word choice. 【0788】 The "dynamic optimization function" refers to the ability to perform optimal progress and adjustments on the spot based on data acquired in real time during a meeting. 【0789】 This invention is a system that innovatively supports meeting management, and aims to improve the efficiency and outcome of meetings, particularly by utilizing participant emotional data. The system consists of a server, terminals, users, and an emotional engine. 【0790】 Server Role 【0791】 The server first receives information from the user, such as the purpose, goals, participants, and time allocation of the meeting. This information is stored in a database and forms the foundation for supporting the overall progress of the meeting. For speech processing technology, cloud services such as the Google Cloud Speech-to-Text API are used to transcribe the audio data during the meeting in real time and determine whether the discussion content deviates from the set goals. In addition, sentiment analysis tools such as the Microsoft Azure Emotion API are used to analyze emotional data from the tone of voice and facial expressions of the participants. 【0792】 Terminal role 【0793】 The terminal receives real-time updates from the server during the meeting, including proposed revisions and sentiment-based suggestions, and notifies participants. This allows participants to adjust their comments and discussions on the spot. After the meeting ends, the terminal distributes meeting minutes and tasks automatically generated by the server to participants, supporting them in carrying out their next actions. 【0794】 User interaction 【0795】 Users establish a foundation for meeting management by inputting basic meeting information into the system. During the meeting, users can adjust the direction of the discussion by referring to the feedback provided by the terminal. After the meeting, users can review the generated minutes and tasks and make manual adjustments as needed. 【0796】 Specific example 【0797】 A concrete example is a case where users hold a meeting to gather feedback for product development. In this case, the server analyzes participants' sentiment data in real time and suggests course corrections to the discussion based on how each comment is received. This information is immediately shared with the user via their terminal, providing insights to make the discussion more effective. 【0798】 Example of a prompt 【0799】 "Please describe a system that analyzes participants' emotions during product development feedback meetings, measures their reactions, and suggests adjustments to the process." 【0800】 Thus, the present invention enables meeting management that takes participants' emotions into consideration, and is a system that yields superior results compared to conventional management methods. 【0801】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0802】 Step 1: 【0803】 Users input basic information into the system, such as the purpose, goals, participants, and time allocation of the meeting. This information is sent to the server and stored in the database. The entered information is processed as initial setup data to support the progress of the meeting. 【0804】 Step 2: 【0805】 The terminal sends the audio data collected during the meeting to the server. The server converts this data into text using speech analysis technology. Specifically, it processes the audio data using the Google Cloud Speech-to-Text API and generates the result as text output. This makes it possible to monitor the content of the discussion. 【0806】 Step 3: 【0807】 The server analyzes the converted text data in real time to determine whether the meeting is deviating from its set objectives and goals. This analysis uses natural language processing techniques, making decisions by analyzing keywords and context. As output, suggested revisions to the meeting's progress are generated as needed. 【0808】 Step 4: 【0809】 The server uses an emotion engine to extract participant emotion data. Audio and video data from the meeting are used as input, and emotion analysis tools such as the Microsoft Azure Emotion API categorize and quantify participants' emotions. This information becomes output data used to adjust the meeting's progress. 【0810】 Step 5: 【0811】 The server generates proposed revisions and sentiment-based suggestions based on the meeting's progress and sentiment data, and sends them to the terminal. The terminal notifies participants in real time, helping users adjust their comments and discussions on the spot. 【0812】 Step 6: 【0813】 Once the meeting concludes, the server automatically generates meeting minutes based on the audio analysis results and the recorded proceedings. This process extracts key points and decisions made during the meeting and outputs them in a structured document format. The generated minutes are then shared with the participants. 【0814】 Step 7: 【0815】 Ultimately, the server assigns tasks to each participant, taking emotional data into consideration, and proposes the optimal communication strategy. The output tasks, which take each participant's emotional state into account, are synchronized to the communication application via the terminal to support the next action. 【0816】 (Application Example 2) 【0817】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0818】 Modern family communication presents a challenge in preventing conflicts arising from emotional misunderstandings. In particular, family dialogue requires flexible responses to changing emotions, but appropriate real-time feedback is often lacking. This can hinder smooth and meaningful communication. 【0819】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0820】 In this invention, the server includes means for inputting information such as the purpose, goals, participants, and time allocation of a meeting; means for performing voice analysis of the discussion during the meeting based on the input information and correcting the course of progress; and means for observing conversations within the home, analyzing the emotions of the participants, and suggesting ways to proceed. This makes it possible to analyze emotions during conversations within the home, enabling more constructive and smoother communication. 【0821】 A "meeting" is a place where multiple participants gather to share information and discuss in order to achieve a specific purpose or goal. 【0822】 "Purpose" refers to the specific main theme or goal that should be achieved during the process of a meeting or discussion. 【0823】 "Participants" refer to individuals who gather in a meeting or discussion to exchange opinions and share information. 【0824】 "Time allocation" refers to the distribution of time allocated to each topic throughout a meeting or discussion. 【0825】 "Voice analysis" is a technology that analyzes participants' statements in order to understand the content of a discussion. 【0826】 "Correcting the course of progress" means appropriately adjusting the content and flow of a meeting or discussion so that it does not deviate from its set objectives. 【0827】 "Emotional analysis" is a technique that analyzes participants' emotions from their tone of voice and facial expressions during conversations. 【0828】 A "proposal" is the act of presenting specific policies or action plans to improve the process or dialogue. 【0829】 "Automatically generating records" means that the system automatically transcribes important information from conversations and dialogues into written form. 【0830】 "Next steps" refer to the specific actions each participant should take based on the outcome of the conversation. 【0831】 To implement this invention, it is necessary to construct a system using a server, a terminal, and an emotion analysis engine. The server includes a database for managing information such as the purpose, goals, participants, and time allocation related to meetings and conversations within the home. The server uses speech analysis technology to analyze the content of discussions and conversations in real time and suggests corrections to the process if it deviates from the set goals. 【0832】 Furthermore, the server extracts emotional data from participants' facial expressions and tone of voice via an emotion analysis engine. This extracted emotional data is used to adjust the flow of the conversation, allowing the server to make appropriate suggestions in real time. Specifically, for example, if an emotional conflict arises during a conversation, the server can suggest a reconciliation or a change of topic. 【0833】 The terminal notifies participants in meetings and discussions in real time of proposed revisions and feedback based on sentiment analysis sent from the server. Based on this information, participants can adjust their statements and achieve more meaningful communication. 【0834】 The user inputs basic conversation information into the server through the interface and receives emotional feedback via their device. This allows for dynamic adjustments to the conversation's progression, and ultimately, the automatically generated record can be reviewed and edited as needed. An example of a prompt for the generating AI model is, "Scenario where a family conversation has started to become confrontational: Please suggest something for when Mom is feeling frustrated." 【0835】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0836】 Step 1: 【0837】 The user enters basic information about the meeting or home conversation (purpose, goals, participants, time allocation) into the device. The entered information is sent to the server and stored in the database. Based on this information, the system is ready for subsequent voice analysis and sentiment analysis. 【0838】 Step 2: 【0839】 The server receives audio data transmitted from terminals in real time. It uses a speech analysis engine to analyze the content of discussions and conversations. The input is audio data, and the output is a textualized transcript of the discussion and identification of topics. This analysis allows for an evaluation of progress toward the set objectives and goals. 【0840】 Step 3: 【0841】 The server uses an emotion analysis engine to extract emotional data from participants' audio and camera footage. The inputs are audio and video data, and the output is the analysis of their emotional state. For example, it assesses levels of joy, anger, and stress based on voice tone and facial expression changes. This information can then be used to adjust the program's progress. 【0842】 Step 4: 【0843】 The server integrates the results of speech analysis and sentiment analysis to generate suggested course corrections and emotion-based recommendations. The input is the speech analysis results and sentiment analysis results, and the output is a suggested message. Specifically, it provides concrete actions to correct the course of the conversation and emotionally conscious directions for the discussion. 【0844】 Step 5: 【0845】 The terminal notifies participants in real time of suggestion messages received from the server. The output is visual or auditory suggestion information provided to participants. This allows participants to immediately adjust the flow of the conversation and achieve emotionally resonant communication. 【0846】 Step 6: 【0847】 After the conversation ends, the server automatically generates a summary of the conversation's key points and assigns tasks to each participant. The input is the audio data of the entire conversation and the analysis results, while the output is a text-based record and task assignments. This automatically generated record is provided to the user via their terminal, allowing for editing and additions as needed. 【0848】 The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0849】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0850】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0851】 Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0852】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0853】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0854】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0855】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0856】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0857】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0858】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0859】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0860】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0861】 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. 【0862】 Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0863】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0864】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0865】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0866】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0867】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0868】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0869】 The following is further disclosed regarding the embodiments described above. 【0870】 (Claim 1) 【0871】 A means of inputting information such as the purpose, goals, participants, and time allocation of the meeting, 【0872】 A means of analyzing the audio of the discussion during the meeting based on the input information and correcting the course of the discussion, 【0873】 A means to automatically generate meeting minutes based on the meeting results, and to automatically assign and share tasks for the next steps, 【0874】 A system that includes this. 【0875】 (Claim 2) 【0876】 The system according to claim 1, further comprising means for suggesting corrections to the progress if the content of the discussion deviates from the set objectives or goals based on speech analysis. 【0877】 (Claim 3) 【0878】 The system according to claim 1, comprising means for generating meeting minutes and distributing task assignment information to relevant parties. 【0879】 "Example 1" 【0880】 (Claim 1) 【0881】 A means of inputting data such as the purpose, objectives, participants, and time allocation of the meeting, 【0882】 A means of analyzing the conversation during communication based on the input data and correcting the course of the conversation, 【0883】 A means of processing audio data in real time using a generative machine learning model, 【0884】 A means of selecting the next topic based on the analysis results and making a proposal, 【0885】 A means for automatically generating records based on the dialogue results and automatically assigning and distributing tasks for the next activity, 【0886】 A system that includes this. 【0887】 (Claim 2) 【0888】 The system according to claim 1, further comprising means for suggesting corrections to the progress if the content of the discussion deviates from the set purpose or objectives based on speech analysis. 【0889】 (Claim 3) 【0890】 The system according to claim 1, comprising means for generating records and distributing work assignment information to relevant parties. 【0891】 "Application Example 1" 【0892】 (Claim 1) 【0893】 A means of entering meeting information, 【0894】 A means for analyzing a conversation based on input information and correcting its trajectory, 【0895】 A means for automatically generating information based on meeting results, and automatically assigning and sharing the content of the next steps, 【0896】 A means of analyzing conversation content in real time and making suggestions, 【0897】 A system that includes this. 【0898】 (Claim 2) 【0899】 The system according to claim 1, further comprising means for suggesting a correction to the progress if the content deviates from the set goal based on voice analysis. 【0900】 (Claim 3) 【0901】 The system according to claim 1, comprising means for distributing generated information and assignment information to relevant parties. 【0902】 "Example 2 of combining an emotion engine" 【0903】 (Claim 1) 【0904】 It has a function to input information such as the purpose, goals, participants, and time allocation of the meeting, 【0905】 Based on the input information, it processes the dialogue during the meeting into audio and adjusts the direction of the discussion. 【0906】 The system extracts and analyzes participants' emotional data in real time during meetings, and dynamically optimizes the meeting's progress. 【0907】 Features that automatically generate summaries based on meeting results, and automatically assign and share tasks for the next action, 【0908】 A system that includes this. 【0909】 (Claim 2) 【0910】 The system according to claim 1, further comprising a function that, based on speech processing and emotion analysis, suggests adjusting the progress of a dialogue if the dialogue deviates from the set purpose or goal. 【0911】 (Claim 3) 【0912】 The system according to claim 1, further comprising a function for generating summaries and communicating task assignment information to relevant parties. 【0913】 "Application example 2 when combining with an emotional engine" 【0914】 (Claim 1) 【0915】 A means of inputting information such as the purpose, goals, participants, and time allocation of the meeting, 【0916】 A means of analyzing the audio of the discussion during the meeting based on the input information and correcting the course of the discussion, 【0917】 A method for observing conversations within the family, analyzing the emotions of the participants, and proposing a course of action, 【0918】 A means for automatically generating a record based on the results of a conversation, and for automatically assigning and sharing the next steps, 【0919】 A system that includes this. 【0920】 (Claim 2) 【0921】 The system according to claim 1, further comprising means for suggesting corrections to the progress if the content of the conversation deviates from the set purpose or goal based on speech analysis. 【0922】 (Claim 3) 【0923】 The system according to claim 1, comprising means for generating records and distributing information on assigned actions to relevant parties. [Explanation of symbols] 【0924】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means of inputting information such as the purpose, goals, participants, and time allocation of the meeting, A means of analyzing the audio of the discussion during the meeting based on the input information and correcting the course of the discussion, A means to automatically generate meeting minutes based on the meeting results, and to automatically assign and share tasks for the next steps, A system that includes this. [Claim 2] The system according to claim 1, further comprising means for suggesting corrections to the progress if the content of the discussion deviates from the set objectives or goals based on speech analysis. [Claim 3] The system according to claim 1, comprising means for generating meeting minutes and distributing task assignment information to relevant parties.

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