system

Abstract

システムを提供する。【解決手段】参加者の予定情報を解析し、最適な会議時間を提案する手段と、目的に応じた会議議題を自動生成し、参加者に共有する手段と、会議中に音声を認識してテキスト化し、議事記録を自動生成する手段と、生成された議事記録を整理し、参加者に通知する手段と、参加者に対し、行動項目を自動抽出して通知する手段と、会議後に次の会議の日程を自動で調整する手段と、過去の会議データを分析し、改善提案を生成する手段と、を含むシステム。

Description

【Technical Field】 , , 【0004】 , , , , 【0005】 , , , , , 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In a conventional conference system, since the schedule adjustment of participants and the creation of efficient topics are carried out manually, it takes a lot of time for preparation and is inefficient. Also, the recording of in-meeting content and the identification of action items are troublesome, and the burden on participants is large. Furthermore, there is a problem that follow-up after the meeting and adjustment of the next meeting require individual responses, and overall management is complicated. 【Means for Solving the Problems】 【0005】 This invention provides means for analyzing participants' schedules and proposing optimal meeting times to improve the overall efficiency of meetings, for automatically generating and sharing meeting agendas according to the purpose, and for recognizing speech during meetings, converting it to text, and automatically generating meeting minutes. It also includes means for organizing and notifying the generated meeting minutes, for automatically extracting and notifying action items, and for automatically adjusting the schedule for the next meeting. Furthermore, it includes means for analyzing past meeting data and generating improvement suggestions. This automates the entire process from meeting preparation to follow-up, reducing the burden on participants while maximizing the effectiveness of meetings. 【0006】 "Participant schedule information" refers to data on each meeting participant's available time slots and pre-scheduled appointments within a specific time frame. 【0007】 "Methods for suggesting meeting times" refers to a function that calculates and presents the optimal start and end times for a meeting based on the participants' schedules. 【0008】 "Methods for automatically generating meeting agendas" refers to a function that automatically creates an agenda list for conducting a meeting based on the purpose of the meeting and past records. 【0009】 "A means of recognizing speech, converting it to text, and automatically generating meeting minutes" refers to a function that converts speech during a meeting into text data in real time, and then automatically organizes and generates a formal record based on that data. 【0010】 "Means for organizing and notifying meeting minutes" refers to a function that organizes the generated meeting content into an easy-to-understand format and electronically notifies participants. 【0011】 "Method for automatically extracting and notifying action items" refers to a function that automatically identifies specific action plans decided during a meeting and notifies the person in charge. 【0012】 "A means of automatically adjusting the date of the next meeting" refers to a function that automatically calculates a suitable date and time for the next meeting, proposes it to the participants, and reflects the final decision in the schedule. 【0013】 "A means of analyzing past meeting data and generating improvement suggestions" refers to a function that analyzes past meeting records as digital data in a single batch and provides suggestions for improving future meeting management. [Brief explanation of the drawing] 【0014】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This 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 Example 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】 【0015】 Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 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. 【0020】 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). 【0021】 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." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 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. 【0025】 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). 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 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. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 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. 【0032】 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. 【0033】 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. 【0034】 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". 【0035】 This invention provides a system for automating the preparation, conduct, and follow-up of meetings. This system is primarily server-centric, with terminals and users involved in each process. 【0036】 The server accesses the user's (participant's) calendar information and suggests the optimal meeting time. This frees users from the hassle of scheduling. Furthermore, the server uses AI based on the meeting's purpose to automatically generate appropriate agenda items. This generated agenda is notified to the user in advance, allowing them to check the necessary information before the meeting begins. 【0037】 During the meeting, an AI agent installed on the device supports the proceedings. This includes agenda-based time management and topic presentation. In particular, it utilizes speech recognition technology to transcribe participants' statements in real time and send them to the server. This process allows the server to automatically create meeting minutes and provide users with an accurate record of the meeting. 【0038】 After the meeting ends, the server automatically organizes the generated minutes and shares them with the participants. Furthermore, it extracts the action items decided during the meeting, creates a to-do list, and notifies the respective responsible users. This allows users to properly manage their tasks and ensure the smooth progress of the project. 【0039】 The server automatically adjusts the schedule for the next meeting and notifies participants (users) of the results. This streamlines the ongoing meeting schedule. In addition, the server, equipped with analytical capabilities, analyzes past meeting data to understand participant speaking frequency and meeting pace. Based on this data, it provides users with specific improvement suggestions. 【0040】 As a concrete example, let's assume this system is used to ensure the smooth running of a regular weekly meeting. In this case, the server picks out available time slots from the participants' calendars and suggests a date for the next meeting. During the meeting, an AI agent manages the time and generates meeting minutes in real time by transcribing speech into text. After the meeting, the minutes are organized and a push notification is sent, and action items are automatically assigned to the responsible parties. In this way, each step of meeting management is optimized to ensure smooth progress. 【0041】 The following describes the processing flow. 【0042】 Step 1: 【0043】 The server accesses the calendar information shared by meeting participants to detect available time slots. Based on this, an AI algorithm calculates the optimal meeting time and suggests it to the user. 【0044】 Step 2: 【0045】 The server analyzes the meeting's objectives and past records to automatically generate an appropriate agenda. This agenda is then sent to users via email or a notification system. 【0046】 Step 3: 【0047】 At the start of the meeting, an AI agent installed on the device assists with the progress in real time. The device keeps track of the time according to the agenda and provides reminders to the user to switch topics as needed. 【0048】 Step 4: 【0049】 The terminal uses speech recognition technology to transcribe the speech of meeting participants into text in real time and sends the generated text to the server. 【0050】 Step 5: 【0051】 The server analyzes the received text data and organizes it as meeting minutes. These minutes are then structured and edited as needed and provided to users promptly after the meeting. 【0052】 Step 6: 【0053】 The server automatically extracts action items from the discussions during the meeting and creates a to-do list. These task lists are then notified to the users assigned to them. 【0054】 Step 7: 【0055】 After the meeting ends, the server readjusts the date for the next meeting and updates the users' calendars. Once an optimal date and time are found, all relevant users are notified. 【0056】 Step 8: 【0057】 The server analyzes all previously recorded meeting data and identifies areas for improvement based on the pace of discussion and the frequency of contributions. The analysis results are provided to the user in report format, which can be used to improve future meetings. 【0058】 (Example 1) 【0059】 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." 【0060】 Meeting preparation, conducting, and follow-up require significant time and effort, and there is a need to address the inefficiencies in scheduling participants, setting agendas, recording meetings, and managing tasks. 【0061】 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. 【0062】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating a meeting agenda tailored to the purpose using a generative AI model and sharing it with participants, and means for managing meeting time and presenting topics during the meeting using an AI agent. This simplifies meeting preparation and enables efficient meeting progress and follow-up. 【0063】 A "device that analyzes participants' schedule information and suggests the optimal meeting time" is a function that collects schedule data from individual participants and automatically calculates and suggests the meeting time that is most convenient for everyone to attend. 【0064】 The "device that automatically generates meeting agendas according to purpose using an AI model and shares them with participants" is a system that generates an agenda based on the purpose of the meeting, constructs the proposed agenda using natural language generation technology, and has a function to share the content with participants in advance. 【0065】 A "device that recognizes speech during a meeting, converts it to text, and automatically generates meeting minutes" is a technology that converts meeting audio data into text data in real time and generates meeting minutes immediately based on that data. 【0066】 A "device for organizing generated meeting minutes and notifying participants" is a system that organizes automatically generated meeting minutes and efficiently sends necessary information to participants. 【0067】 A "device that automatically extracts and notifies participants of action items" is a system that identifies tasks and action items from the meeting content and notifies the responsible parties of them. 【0068】 A "device that automatically adjusts the date of the next meeting after a meeting" is a function that checks the updated schedules of participants again for ongoing meetings and automatically adjusts the date for the next meeting. 【0069】 A "device that analyzes past meeting data and generates improvement suggestions" is a system that analyzes stored meeting information and, based on the insights gained, creates recommendations that contribute to improving the efficiency of meetings. 【0070】 A "device that uses an AI agent for time management and topic presentation" is a function that uses artificial intelligence to control the progress of a meeting in a timely manner and to raise and support topics based on a pre-set agenda. 【0071】 This invention is a system designed to streamline meeting management and is primarily built around a server. The server collects scheduling information managed by participants and calculates the optimal meeting time. This process utilizes APIs from common scheduling tools. For example, it retrieves data through the API of a digital calendar system and automatically detects and suggests available times for all participants. 【0072】 The server automatically generates agenda items tailored to the meeting's objectives using a generative AI model. This AI model utilizes a large-scale language model equipped with natural language processing technology. The model receives prompts such as "Generate three necessary agenda items for next week's project meeting" as input and generates an appropriate agenda based on them. The generated agenda is shared with participants via email and a notification system, allowing for prior review. 【0073】 During meetings, each terminal is equipped with a dedicated AI agent that manages time and presents topics. This AI agent uses speech recognition technology to transcribe participants' statements in real time and sends this data to a server. This allows the server to generate meeting minutes quickly and accurately. Open-source or commercial speech recognition engines are used for speech recognition. 【0074】 After the meeting, the server organizes the generated minutes and notifies the participants. During this process, an AI model automatically extracts the action items identified during the meeting and notifies each participant via email or other means. As a result, users can effectively manage their tasks and facilitate the smooth progress of the project. 【0075】 Furthermore, the server automatically schedules the next meeting and notifies participants of the results. By analyzing past meeting data, it generates and provides users with specific suggestions to improve the efficiency of meetings. In this way, the present invention is a system that streamlines and reduces the workload of all processes related to meetings. 【0076】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0077】 Step 1: 【0078】 The server collects participant schedule information. It retrieves schedule data from participants' digital calendars as input. Based on the retrieved schedule information, it performs data analysis to identify available time slots. This then outputs data to suggest the optimal meeting time. 【0079】 Step 2: 【0080】 The server automatically generates meeting agendas using a generative AI model. The input is information about the meeting's purpose and past agenda items. The generative AI model uses natural language processing based on this information to set appropriate agenda items. The generated agenda is then provided as output and shared with participants. 【0081】 Step 3: 【0082】 The device recognizes and transcribes audio during a meeting. It uses participant speech data captured via microphones as input. A speech recognition engine processes the audio data in real time and converts it to text. This conversion result is sent to a server and output as data for generating meeting minutes. 【0083】 Step 4: 【0084】 The server automatically generates meeting minutes based on the received text data. The text data obtained in step 3 is used as input, and formatting and summarization processes are performed. The meeting minutes are quickly compiled and distributed to participants via email or notification. 【0085】 Step 5: 【0086】 The server automatically extracts the action items decided during the meeting. The meeting minutes generated in step 4 are used as input. The generation AI model is used to identify the target of each action item and create a to-do list. Each action item is notified to the relevant participants and output as their assigned task. 【0087】 Step 6: 【0088】 The server automatically schedules the next meeting. It uses updated participant schedule information and past meeting history as input. It analyzes the schedules, selects a date and time when everyone can attend, and outputs it as the next meeting date. Participants are notified of the result. 【0089】 (Application Example 1) 【0090】 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." 【0091】 In smart cities, there is a need to facilitate communication between local communities and administrative agencies and to effectively conduct meetings with local residents. In particular, automating and streamlining all steps of meeting preparation, management, and follow-up is a key challenge. Furthermore, the use of artificial intelligence for creative agenda generation and timely information provision to participants is essential for revitalizing local communities. 【0092】 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. 【0093】 This invention includes a server that analyzes participants' schedule information and proposes an optimal meeting time, a server that automatically generates meeting agendas using an AI model and shares them with participants, and a server that optimizes and automates meetings specifically for smart cities. This enables smooth operation of meetings in local communities and effective communication with residents. 【0094】 "Participants" refer to the individual people who attend a meeting or conference, and are the subjects for whom scheduling and information provision are handled by the system. 【0095】 "Meeting time" refers to the time when participants gather to discuss a specific topic, and is a time proposed for the purpose of efficient communication. 【0096】 An "agenda" refers to the topics or subjects discussed at a meeting or conference, and is automatically generated by a generative AI model based on relevant information. 【0097】 "Speech recognition" refers to a technology that converts participants' spoken words during a meeting into text, and is used for the automatic generation of meeting minutes. 【0098】 "Meeting minutes" are documents that faithfully record the statements and decisions made at meetings or conferences, and are the contents that are communicated to the participants. 【0099】 "Action items" refer to tasks and responsibilities assigned to participants as specific actions decided at the meeting. 【0100】 A "generative AI model" is an artificial intelligence technology used to automatically create meeting agendas and improvement proposals based on past data and new information. 【0101】 A "smart city" refers to a city that utilizes information technology to improve the efficiency of urban management and residents' lives, with the aim of promoting the development of the local community. 【0102】 "Optimization" refers to methods aimed at improving the efficiency of meeting management and eliminating waste of time and resources. 【0103】 To implement this invention, it is necessary to build a system that proposes the optimal meeting time based on participants' schedule information and automatically generates the meeting agenda using an AI model. This system will facilitate smooth meetings between local communities and government agencies and will also manage follow-up activities from start to finish. 【0104】 The server first collects participants' calendar information and processes the data on a cloud environment, specifically on a typical cloud server (e.g., AWS® or Google® Cloud). Based on the collected data, it calculates the optimal meeting time and notifies the participants. Participants' devices include smartphones, tablets, and PCs. 【0105】 For meeting agendas, generative AI models (such as natural language processing models like GPT-4®) can be used. The server generates agendas based on past meeting data and shares them with participants. Google Cloud Speech-to-Text is used for speech recognition technology, transcribing participants' speech in real time and sending it to the server. Based on this, meeting minutes are automatically generated and organized. 【0106】 As a concrete example, consider a community meeting between the city hall and local residents. To ensure the efficient operation of this meeting, the schedules of all participants are coordinated, and a prompt is given to the AI ​​model to generate an agenda for the next meeting, such as, "Generate an agenda for the next meeting on the local disaster prevention plan. Please take past meeting records into consideration and include new proposals." This prompt allows the AI ​​model to propose a creative agenda. 【0107】 This system will enable the revitalization of local communities and the improvement of communication efficiency in smart cities. 【0108】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0109】 Step 1: 【0110】 The server collects participants' calendar information. To process this information, it first retrieves appointments from the participants' smartphone or PC calendar apps. The input is the participants' calendar information, and the output is the base data for suggesting the optimal meeting time. The server analyzes the collected data in the cloud to identify available time slots. 【0111】 Step 2: 【0112】 The server proposes the optimal meeting time based on the identified free time. This step uses the parsed calendar information as input. The data calculation determines and selects the time when the most participants can attend. The output is a list of proposed meeting times, which is notified to participants via their terminals. 【0113】 Step 3: 【0114】 The server automatically generates meeting agendas using a generative AI model. This step uses past meeting data and related information as input. The generative AI model performs natural language processing based on this data to generate draft agendas. The output is the newly proposed agenda, which is shared with users via the terminal. 【0115】 Step 4: 【0116】 During the meeting, speech recognition software built into the terminal transcribes participants' speech into text. The input is real-time audio data, which is converted into text data by speech recognition technology. The output is the transcribed speech, which is then sent to the server. 【0117】 Step 5: 【0118】 The server automatically generates and organizes meeting minutes based on transcribed speech. This step uses speech recognition-generated text data as input. Data processing organizes the speech content in a logical sequence to create a complete meeting record. The output is the completed meeting minutes, which are then notified to the user. 【0119】 Step 6: 【0120】 After the meeting ends, the server automatically extracts the action items decided at the meeting and notifies the participants. The input for this process is the generated meeting minutes. The data processing extracts the action items and assigns them to the corresponding personnel. The output is a to-do list for each person in charge. 【0121】 Step 7: 【0122】 The server automatically adjusts the date for the next meeting. This step takes the participants' upcoming schedules as input, reconfirms their calendar information, and selects a suitable date. The output is the proposed time for the next meeting, which is notified to the participants in advance. 【0123】 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. 【0124】 This invention is a meeting support system that utilizes the emotional state of users during meetings to improve the efficiency and quality of meeting content. The system mainly consists of a server, terminals, and an emotion engine. 【0125】 The server collects the schedules of meeting participants and proposes the most suitable meeting date. It also automatically generates an agenda based on the meeting's purpose and shares it with participants via their devices at the start of the meeting. Using speech recognition technology, it records meeting comments as text data in real time and automatically generates meeting minutes on the server. 【0126】 The device incorporates an emotion engine that analyzes the user's emotional state in real time from the audio and video of meeting participants. This information is sent to a server and used to help with decision-making and adjusting the agenda during the ongoing meeting. For example, if a participant shows a negative reaction to a particular topic, the device displays an alert, allowing the user to take immediate action. 【0127】 After the meeting concludes, the server automatically distributes a comprehensive report to participants, including not only the minutes but also emotional states measured during the meeting. This report includes suggestions for improvement based on the frequency of contributions and emotional changes, which will be used to improve future meeting management. 【0128】 As a concrete example, let's assume this system is applied to a project progress meeting. Users can conduct the meeting according to the agenda suggested by the system. If a participant appears anxious during the discussion, their emotional data is detected via their device, and a break in the meeting is recommended. After the meeting, the emotional data is analyzed, and specific suggestions for improving collaborative efficiency are provided. 【0129】 Thus, the system of the present invention, which incorporates an emotion engine, reflects the psychological state of participants and optimizes decision-making in the meeting in progress. It is possible to simultaneously achieve a high level of automation and quality improvement in meeting management. 【0130】 The following describes the processing flow. 【0131】 Step 1: 【0132】 The server retrieves the user's calendar information and analyzes the availability of all participants. Based on this, it calculates the optimal meeting start and end times and proposes them to the user. The proposal is notified via email or scheduling app. 【0133】 Step 2: 【0134】 The server collects the meeting's purpose and relevant information, and uses AI to automatically generate an agenda. This agenda is sent to all meeting participants in advance via their devices. Users can review it and adjust the agenda content as needed. 【0135】 Step 3: 【0136】 The device activates its speech recognition function at the start of the meeting and transcribes participants' speech into text in real time. Simultaneously, the device uses its camera and microphone to analyze participants' facial expressions and voice tone, collecting emotional data. 【0137】 Step 4: 【0138】 The server analyzes the audio data transmitted from the terminal and automatically generates meeting minutes. It also understands the psychological reactions of participants during the meeting based on the collected emotional data. Based on this information, the server determines the recommended next action. 【0139】 Step 5: 【0140】 The device provides alerts based on participants' emotions. For example, if the emotion engine detects that a user is feeling stressed or frustrated, a notification will appear saying, "This topic is causing negative reactions. Please move on to the next topic or learn more." 【0141】 Step 6: 【0142】 After the meeting ends, the server automatically generates meeting minutes along with a report containing participant sentiment data. This report includes improvement suggestions based on the analysis and is delivered to users via email or a dedicated app. 【0143】 Step 7: 【0144】 Users will use this report to plan their next meeting. Based on the improvement suggestions, they will readjust the agenda and proceedings to prepare for the meeting to maximize its effectiveness. The server will also reschedule the next meeting and notify relevant parties of the details. 【0145】 (Example 2) 【0146】 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 as the "terminal". 【0147】 In today's business environment, many meetings are not conducted efficiently or effectively. While it's crucial to schedule meetings appropriately considering participants' availability, set agendas relevant to the meeting content, and accurately record what is said, these are often not done properly. Furthermore, understanding participants' emotional states and adjusting meetings accordingly is also difficult. Improving these conditions and enhancing the quality and efficiency of meetings is essential. 【0148】 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. 【0149】 In this invention, the server includes means for analyzing participants' schedule information and proposing an optimal meeting time; means for automatically generating and sharing meeting agendas according to the purpose using natural language generation methods; means for recognizing speech during the meeting, converting it to text, and automatically generating meeting minutes; means for analyzing participants' audio and video data and evaluating their emotional state; and means for providing suggestions for adjusting the meeting progress based on this emotional state. As a result, meetings can be efficiently planned based on participants' schedules and conducted in a way that reflects their emotions, thereby improving the quality and efficiency of meetings. 【0150】 "Analyzing participant schedule information" is the process of collecting schedule data for each individual attending a meeting and identifying the most suitable date and time for the meeting. 【0151】 "Suggesting the optimal meeting time" involves analyzing collected participant schedule data to determine and present dates that are available to the majority of participants. 【0152】 "Automatically generating meeting agendas using natural language generation techniques" refers to the process of automatically creating topics and items tailored to the purpose of a meeting by utilizing generative AI technology. 【0153】 "Sharing with participants" refers to the act of distributing generated information and data to those attending a meeting, thereby ensuring that the information is shared among them. 【0154】 "Speech recognition and text conversion" is a process that analyzes speech spoken during a meeting in real time and converts it into human-readable text data. 【0155】 "Automatically generating meeting minutes" refers to the process of organizing and saving text data generated during a meeting as an official report or record. 【0156】 "Analyzing audio and video data to evaluate emotional state" refers to the process of automatically determining the psychological or emotional state of participants from the audio and video recorded during the meeting. 【0157】 "Providing suggestions for adjusting meeting proceedings based on emotional states" refers to the act of using analyzed emotional data to propose improvements to meeting procedures and methods. 【0158】 This invention is a meeting support system that utilizes advanced data analysis technology and generative AI models to improve the user's meeting experience. The system mainly consists of a server, terminals, and an emotion analysis engine. 【0159】 The server collects user schedule information. Specifically, it analyzes user calendar data using APIs from common scheduling software. This allows it to calculate the optimal meeting time and propose it to each participant. Meeting agendas, tailored to the purpose of the meeting, are created by inputting prompts into a generative AI model that uses natural language generation technology. For example, using the prompt "Please list the main topics to be discussed at the next project meeting," the server selects and shares appropriate agenda items from the output generated by the AI. 【0160】 The device analyzes each user's voice and video in real time during a meeting. It uses an industry-standard speech-to-text engine for speech recognition, instantly transcribing spoken content into text. Furthermore, it incorporates an emotion analysis engine, analyzing emotional data from the voice and video to understand the user's psychological state. Based on this analysis, it provides real-time alerts and suggestions regarding meeting progress, supporting users in conducting meetings more smoothly. Similarly, it generates and provides users with a comprehensive meeting report that considers the frequency and pace of speech based on the emotional data. 【0161】 This system allows users to conduct meetings in a planned and flexible manner. For example, if many participants react negatively to a particular agenda item during a meeting, an alert is immediately displayed to draw attention to the issue, allowing for adjustments to the meeting's direction. After the meeting, it is also possible to consider specific improvement measures for the next meeting based on the data obtained from the comprehensive report. 【0162】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0163】 Step 1: 【0164】 The server retrieves schedule information from the user's scheduling software. The input is the user's calendar API, and the output is the user's schedule data. The server analyzes this data to calculate the optimal meeting time that all participants can attend. The calculated date and time are then notified to each user. 【0165】 Step 2: 【0166】 The server uses a generative AI model to automatically generate meeting agendas. The input here is a prompt, for example, "Please list three main topics for the next new product development meeting." The output is an agenda list generated by the AI, which is shared with each participant. 【0167】 Step 3: 【0168】 The terminal collects user audio in real time during meetings and transcribes it using a speech recognition engine. Audio data is the input, and the output is spoken text data. The terminal sends this text to a server to support the automatic generation of meeting minutes. 【0169】 Step 4: 【0170】 The terminal uses the user's voice and video data to evaluate their emotional state using an emotion analysis engine. The input is the voice and video data recorded during the meeting, and the output is the result of the emotional state evaluation. The terminal sends this result to a server, which is used to provide the user with suggestions regarding the progress of the meeting. 【0171】 Step 5: 【0172】 The server stores voice text and sentiment data obtained during the meeting and analyzes it in real time. The analysis generates specific suggestions and alerts regarding the meeting's progress, which are then displayed to the user. The input in this process is the entire dataset accumulated during the meeting, while the output is the suggestions for meeting progress. 【0173】 Step 6: 【0174】 After the meeting concludes, the server automatically generates a comprehensive report based on all the data. Inputs include voice-to-text, sentiment analysis results, and proposal history. The output is a detailed report covering the meeting's specifics, which is distributed to participants. This allows users to identify areas for improvement for future meetings. 【0175】 (Application Example 2) 【0176】 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". 【0177】 In team meetings at physical stores, the emotional state of participants can significantly impact the progress and outcome of the meeting. However, the lack of a system to appropriately interpret emotions from comments and facial expressions during the meeting and respond immediately can hinder communication and meeting efficiency. Systems and methods to address this challenge are needed. 【0178】 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. 【0179】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating meeting agendas according to the purpose and sharing them with participants, and means for analyzing participants' emotional states in real time and displaying warnings when negative reactions are detected. This makes it possible to accurately grasp the emotional states of meeting participants, facilitate smooth meeting progress, and improve the quality of discussions. 【0180】 "Schedule information" refers to data regarding the schedules and available time slots of meeting participants. 【0181】 "Meeting agenda" refers to the subject or topic to be discussed at a meeting. 【0182】 "Speech recognition" is a technology that converts speech into text data that a computer can understand. 【0183】 "Meeting minutes" are documents that organize the statements and decisions made during a meeting into text format. 【0184】 "Action items" refer to the actions or tasks that meeting participants should take next. 【0185】 "Real-time analysis" refers to processing and analyzing information at the very moment an event occurs. 【0186】 "Emotional state" refers to the psychological state of meeting participants and can be interpreted from their voice and facial expressions. 【0187】 A "warning message" is a message that is displayed to alert the user when certain conditions are met. 【0188】 An "improvement suggestion" is a specific proposal or opinion offered after analyzing the current situation, aimed at achieving better results. 【0189】 The system for implementing this invention consists of a server, a smart device (terminal), and an emotion analysis engine. The server analyzes the schedule information of meeting participants and proposes the optimal meeting time and agenda. The participants' smart devices are equipped with cameras and microphones, capturing audio and video in real time, which are then analyzed by the emotion analysis engine. This emotion data is transmitted to the server, enabling responses that correspond to the emotional state during the meeting. 【0190】 Specifically, the system uses the Google Cloud Speech-to-Text API to convert speech to text and the Microsoft® Azure® Emotion API to analyze participants' emotional states in real time. Additionally, Apache® Kafka is used to process large amounts of speech and emotional data in real time. This allows for a warning to be displayed on the device if negative emotions are detected in a participant. 【0191】 For example, in a staff meeting at a retail store, if a staff member expresses dissatisfaction during a discussion about promotional strategies, an alert based on emotional data will appear on their smart device, recommending a review of the agenda or the introduction of breaks in the meeting. After the meeting, improvement suggestions based on the analysis of emotional data will be provided along with the generated meeting minutes. 【0192】 Examples of prompts for a generative AI model are as follows: 【0193】 "Please develop an idea for a meeting assistant app that provides feedback based on the emotional state of staff during a meeting. The device used would be a smartphone or smart glasses, and it would provide alerts to participants in real time based on emotion analysis results." 【0194】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0195】 Step 1: 【0196】 The server receives participant schedule information and stores it in a database. It then analyzes the received schedule information and runs an algorithm to suggest the optimal meeting time. The input is participant schedule data, and the output is a suggestion for the optimal meeting time. 【0197】 Step 2: 【0198】 The server automatically generates an agenda based on the meeting's objectives. Using objective information obtained from participants as input, it outputs an agenda designed to maximize the meeting's effectiveness. This agenda information is sent to the terminal and shared with the participants. 【0199】 Step 3: 【0200】 The device captures audio and video during the meeting. Using the built-in microphone and camera, it collects participants' audio and video data in real time. Both of these data are sent to a server for processing. 【0201】 Step 4: 【0202】 The server converts the received audio data into text using the Google Cloud Speech-to-Text API. The input is audio data, and the output is its text representation. This generates meeting minutes. 【0203】 Step 5: 【0204】 The device uses the Microsoft Azure Emotion API to perform emotion analysis on participants' video data. The input is video data, and the analysis results in an output of emotional state (positive, negative, etc.). If a negative emotion is detected, a warning will be displayed on the device. 【0205】 Step 6: 【0206】 After the meeting concludes, the server integrates audio and sentiment data to generate a comprehensive meeting report. Inputs include transcribed meeting minutes and analyzed sentiment states, while output is a final report containing improvement suggestions for participants. The generated report is distributed to participants to help them prepare for future meetings. 【0207】 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. 【0208】 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. 【0209】 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. 【0210】 [Second Embodiment] 【0211】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0212】 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. 【0213】 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). 【0214】 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. 【0215】 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. 【0216】 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). 【0217】 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. 【0218】 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. 【0219】 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. 【0220】 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. 【0221】 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. 【0222】 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". 【0223】 This invention provides a system for automating the preparation, conduct, and follow-up of meetings. This system is primarily server-centric, with terminals and users involved in each process. 【0224】 The server accesses the user's (participant's) calendar information and suggests the optimal meeting time. This frees users from the hassle of scheduling. Furthermore, the server uses AI based on the meeting's purpose to automatically generate appropriate agenda items. This generated agenda is notified to the user in advance, allowing them to check the necessary information before the meeting begins. 【0225】 During the meeting, an AI agent installed on the device supports the proceedings. This includes agenda-based time management and topic presentation. In particular, it utilizes speech recognition technology to transcribe participants' statements in real time and send them to the server. This process allows the server to automatically create meeting minutes and provide users with an accurate record of the meeting. 【0226】 After the meeting ends, the server automatically organizes the generated minutes and shares them with the participants. Furthermore, it extracts the action items decided during the meeting, creates a to-do list, and notifies the respective responsible users. This allows users to properly manage their tasks and ensure the smooth progress of the project. 【0227】 The server automatically adjusts the schedule for the next meeting and notifies participants (users) of the results. This streamlines the ongoing meeting schedule. In addition, the server, equipped with analytical capabilities, analyzes past meeting data to understand participant speaking frequency and meeting pace. Based on this data, it provides users with specific improvement suggestions. 【0228】 As a concrete example, let's assume this system is used to ensure the smooth running of a regular weekly meeting. In this case, the server picks out available time slots from the participants' calendars and suggests a date for the next meeting. During the meeting, an AI agent manages the time and generates meeting minutes in real time by transcribing speech into text. After the meeting, the minutes are organized and a push notification is sent, and action items are automatically assigned to the responsible parties. In this way, each step of meeting management is optimized to ensure smooth progress. 【0229】 The following describes the processing flow. 【0230】 Step 1: 【0231】 The server accesses the calendar information shared by meeting participants to detect available time slots. Based on this, an AI algorithm calculates the optimal meeting time and suggests it to the user. 【0232】 Step 2: 【0233】 The server analyzes the meeting's objectives and past records to automatically generate an appropriate agenda. This agenda is then sent to users via email or a notification system. 【0234】 Step 3: 【0235】 At the start of the meeting, an AI agent installed on the device assists with the progress in real time. The device keeps track of the time according to the agenda and provides reminders to the user to switch topics as needed. 【0236】 Step 4: 【0237】 The terminal uses speech recognition technology to transcribe the speech of meeting participants into text in real time and sends the generated text to the server. 【0238】 Step 5: 【0239】 The server analyzes the received text data and organizes it as meeting minutes. These minutes are then structured and edited as needed and provided to users promptly after the meeting. 【0240】 Step 6: 【0241】 The server automatically extracts action items from the discussions during the meeting and creates a to-do list. These task lists are then notified to the users assigned to them. 【0242】 Step 7: 【0243】 After the meeting ends, the server readjusts the date for the next meeting and updates the users' calendars. Once an optimal date and time are found, all relevant users are notified. 【0244】 Step 8: 【0245】 The server analyzes all previously recorded meeting data and identifies areas for improvement based on the pace of discussion and the frequency of contributions. The analysis results are provided to the user in report format, which can be used to improve future meetings. 【0246】 (Example 1) 【0247】 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". 【0248】 Meeting preparation, conducting, and follow-up require significant time and effort, and there is a need to address the inefficiencies in scheduling participants, setting agendas, recording meetings, and managing tasks. 【0249】 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. 【0250】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating a meeting agenda tailored to the purpose using a generative AI model and sharing it with participants, and means for managing meeting time and presenting topics during the meeting using an AI agent. This simplifies meeting preparation and enables efficient meeting progress and follow-up. 【0251】 A "device that analyzes participants' schedule information and suggests the optimal meeting time" is a function that collects schedule data from individual participants and automatically calculates and suggests the meeting time that is most convenient for everyone to attend. 【0252】 The "device that automatically generates meeting agendas according to purpose using an AI model and shares them with participants" is a system that generates an agenda based on the purpose of the meeting, constructs the proposed agenda using natural language generation technology, and has a function to share the content with participants in advance. 【0253】 A "device that recognizes speech during a meeting, converts it to text, and automatically generates meeting minutes" is a technology that converts meeting audio data into text data in real time and generates meeting minutes immediately based on that data. 【0254】 A "device for organizing generated meeting minutes and notifying participants" is a system that organizes automatically generated meeting minutes and efficiently sends necessary information to participants. 【0255】 A "device that automatically extracts and notifies participants of action items" is a system that identifies tasks and action items from the meeting content and notifies the responsible parties of them. 【0256】 A "device that automatically adjusts the date of the next meeting after a meeting" is a function that checks the updated schedules of participants again for ongoing meetings and automatically adjusts the date for the next meeting. 【0257】 A "device that analyzes past meeting data and generates improvement suggestions" is a system that analyzes stored meeting information and, based on the insights gained, creates recommendations that contribute to improving the efficiency of meetings. 【0258】 A "device that uses an AI agent for time management and topic presentation" is a function that uses artificial intelligence to control the progress of a meeting in a timely manner and to raise and support topics based on a pre-set agenda. 【0259】 This invention is a system designed to streamline meeting management and is primarily built around a server. The server collects scheduling information managed by participants and calculates the optimal meeting time. This process utilizes APIs from common scheduling tools. For example, it retrieves data through the API of a digital calendar system and automatically detects and suggests available times for all participants. 【0260】 The server automatically generates agenda items tailored to the meeting's objectives using a generative AI model. This AI model utilizes a large-scale language model equipped with natural language processing technology. The model receives prompts such as "Generate three necessary agenda items for next week's project meeting" as input and generates an appropriate agenda based on them. The generated agenda is shared with participants via email and a notification system, allowing for prior review. 【0261】 During meetings, each terminal is equipped with a dedicated AI agent that manages time and presents topics. This AI agent uses speech recognition technology to transcribe participants' statements in real time and sends this data to a server. This allows the server to generate meeting minutes quickly and accurately. Open-source or commercial speech recognition engines are used for speech recognition. 【0262】 After the meeting, the server organizes the generated minutes and notifies the participants. During this process, an AI model automatically extracts the action items identified during the meeting and notifies each participant via email or other means. As a result, users can effectively manage their tasks and facilitate the smooth progress of the project. 【0263】 Furthermore, the server automatically schedules the next meeting and notifies participants of the results. By analyzing past meeting data, it generates and provides users with specific suggestions to improve the efficiency of meetings. In this way, the present invention is a system that streamlines and reduces the workload of all processes related to meetings. 【0264】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0265】 Step 1: 【0266】 The server collects participant schedule information. It retrieves schedule data from participants' digital calendars as input. Based on the retrieved schedule information, it performs data analysis to identify available time slots. This then outputs data to suggest the optimal meeting time. 【0267】 Step 2: 【0268】 The server automatically generates meeting agendas using a generative AI model. The input is information about the meeting's purpose and past agenda items. The generative AI model uses natural language processing based on this information to set appropriate agenda items. The generated agenda is then provided as output and shared with participants. 【0269】 Step 3: 【0270】 The device recognizes and transcribes audio during a meeting. It uses participant speech data captured via microphones as input. A speech recognition engine processes the audio data in real time and converts it to text. This conversion result is sent to a server and output as data for generating meeting minutes. 【0271】 Step 4: 【0272】 The server automatically generates meeting minutes based on the received text data. The text data obtained in step 3 is used as input, and formatting and summarization processes are performed. The meeting minutes are quickly compiled and distributed to participants via email or notification. 【0273】 Step 5: 【0274】 The server automatically extracts the action items decided during the meeting. The meeting minutes generated in step 4 are used as input. The generation AI model is used to identify the target of each action item and create a to-do list. Each action item is notified to the relevant participants and output as their assigned task. 【0275】 Step 6: 【0276】 The server automatically schedules the next meeting. It uses updated participant schedule information and past meeting history as input. It analyzes the schedules, selects a date and time when everyone can attend, and outputs it as the next meeting date. Participants are notified of the result. 【0277】 (Application Example 1) 【0278】 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 glasses 214 will be referred to as the "terminal." 【0279】 In smart cities, there is a need to facilitate communication between local communities and administrative agencies and to effectively conduct meetings with local residents. In particular, automating and streamlining all steps of meeting preparation, management, and follow-up is a key challenge. Furthermore, the use of artificial intelligence for creative agenda generation and timely information provision to participants is essential for revitalizing local communities. 【0280】 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. 【0281】 This invention includes a server that analyzes participants' schedule information and proposes an optimal meeting time, a server that automatically generates meeting agendas using an AI model and shares them with participants, and a server that optimizes and automates meetings specifically for smart cities. This enables smooth operation of meetings in local communities and effective communication with residents. 【0282】 "Participant" refers to an individual person who participates in a meeting or conference and is the target of schedule adjustment and information provision by the system. 【0283】 "Meeting time" refers to the time when participants gather to discuss specific topics and is the time proposed for efficient communication. 【0284】 "Agenda item" refers to the content or theme discussed in a meeting or conference and is automatically created by the AI model generated based on relevant information. 【0285】 "Speech recognition" refers to the technology that converts the oral statements of participants during a meeting into text and is used for the automatic generation of meeting minutes. 【0286】 "Meeting record" refers to a document that faithfully records the statements and decisions made in a meeting or conference and is the content notified to participants. 【0287】 "Action item" refers to the tasks and responsibilities assigned to participants as specific actions determined in a meeting. 【0288】 "Generated AI model" refers to artificial intelligence technology used to automatically create meeting agenda items and improvement proposals based on past data and new information. 【0289】 "Smart city" refers to all initiatives that utilize information technology to make urban operations and residents' lives more efficient and is a city aimed at the development of the local community. 【0290】 "Optimization" refers to the means aimed at improving the efficiency of meeting operations and eliminating waste of time and resources. 【0291】 To implement this invention, it is necessary to build a system that proposes the optimal meeting time based on participants' schedule information and automatically generates the meeting agenda using an AI model. This system will facilitate smooth meetings between local communities and government agencies and will also manage follow-up activities from start to finish. 【0292】 The server first collects participants' calendar information and processes the data on a typical cloud server (such as AWS or Google Cloud) in a cloud environment. Based on the collected data, it calculates the optimal meeting time and notifies the participants. The devices used by participants include smartphones, tablets, and PCs. 【0293】 For meeting agendas, generative AI models (such as natural language processing models like GPT-4) can be used. The server generates agendas based on past meeting data and shares them with participants. Google Cloud Speech-to-Text is used for speech recognition technology, transcribing participants' speech in real time and sending it to the server. Based on this, meeting minutes are automatically generated and organized. 【0294】 As a concrete example, consider a community meeting between the city hall and local residents. To ensure the efficient operation of this meeting, the schedules of all participants are coordinated, and a prompt is given to the AI ​​model to generate an agenda for the next meeting, such as, "Generate an agenda for the next meeting on the local disaster prevention plan. Please take past meeting records into consideration and include new proposals." This prompt allows the AI ​​model to propose a creative agenda. 【0295】 This system will enable the revitalization of local communities and the improvement of communication efficiency in smart cities. 【0296】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0297】 Step 1: 【0298】 The server collects participants' calendar information. To process this information, it first retrieves appointments from the participants' smartphone or PC calendar apps. The input is the participants' calendar information, and the output is the base data for suggesting the optimal meeting time. The server analyzes the collected data in the cloud to identify available time slots. 【0299】 Step 2: 【0300】 The server proposes the optimal meeting time based on the identified free time. This step uses the parsed calendar information as input. The data calculation determines and selects the time when the most participants can attend. The output is a list of proposed meeting times, which is notified to participants via their terminals. 【0301】 Step 3: 【0302】 The server automatically generates meeting agendas using a generative AI model. This step uses past meeting data and related information as input. The generative AI model performs natural language processing based on this data to generate draft agendas. The output is the newly proposed agenda, which is shared with users via the terminal. 【0303】 Step 4: 【0304】 During the meeting, speech recognition software built into the terminal transcribes participants' speech into text. The input is real-time audio data, which is converted into text data by speech recognition technology. The output is the transcribed speech, which is then sent to the server. 【0305】 Step 5: 【0306】 The server automatically generates and organizes the minutes of the meeting based on the verbalized statements. In this step, the text data obtained through speech recognition is used as the input. In data processing, the content of the statements is sorted and organized to create a complete record of the meeting. The output is the completed minutes of the meeting, which are notified to the user. 【0307】 Step 6: 【0308】 After the meeting ends, the server automatically extracts the action items decided during the meeting and notifies the participants. The input here is the generated minutes of the meeting. In data calculation, the action items are extracted and assigned to the corresponding responsible persons. The output is a TODO list for each responsible person. 【0309】 Step 7: 【0310】 The server automatically adjusts the schedule for the next meeting. In this step, the future schedule data of the target participants is used as the input, and the calendar information is rechecked to select the schedule. The output is the proposed time for the next meeting, which is notified to the participants in advance. 【0311】 Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions. 【0312】 This invention is a meeting support system that utilizes the emotional state of the user during the meeting to improve the efficiency and quality of the meeting content. The system is mainly composed of a server, a terminal, and an emotion engine. 【0313】 The server collects the schedule information of the meeting participants and proposes an optimal meeting schedule. Also, it automatically generates topics based on the purpose of the meeting and shares them with the participants via the terminal at the start of the meeting. Using the speech recognition function, the statements during the meeting are recorded in real time as text data, and the server automatically generates the minutes of the meeting. 【0314】 The device incorporates an emotion engine that analyzes the user's emotional state in real time from the audio and video of meeting participants. This information is sent to a server and used to help with decision-making and adjusting the agenda during the ongoing meeting. For example, if a participant shows a negative reaction to a particular topic, the device displays an alert, allowing the user to take immediate action. 【0315】 After the meeting concludes, the server automatically distributes a comprehensive report to participants, including not only the minutes but also emotional states measured during the meeting. This report includes suggestions for improvement based on the frequency of contributions and emotional changes, which will be used to improve future meeting management. 【0316】 As a concrete example, let's assume this system is applied to a project progress meeting. Users can conduct the meeting according to the agenda suggested by the system. If a participant appears anxious during the discussion, their emotional data is detected via their device, and a break in the meeting is recommended. After the meeting, the emotional data is analyzed, and specific suggestions for improving collaborative efficiency are provided. 【0317】 Thus, the system of the present invention, which incorporates an emotion engine, reflects the psychological state of participants and optimizes decision-making in the meeting in progress. It is possible to simultaneously achieve a high level of automation and quality improvement in meeting management. 【0318】 The following describes the processing flow. 【0319】 Step 1: 【0320】 The server retrieves the user's calendar information and analyzes the availability of all participants. Based on this, it calculates the optimal meeting start and end times and proposes them to the user. The proposal is notified via email or scheduling app. 【0321】 Step 2: 【0322】 The server collects the meeting's purpose and relevant information, and uses AI to automatically generate an agenda. This agenda is sent to all meeting participants in advance via their devices. Users can review it and adjust the agenda content as needed. 【0323】 Step 3: 【0324】 The device activates its speech recognition function at the start of the meeting and transcribes participants' speech into text in real time. Simultaneously, the device uses its camera and microphone to analyze participants' facial expressions and voice tone, collecting emotional data. 【0325】 Step 4: 【0326】 The server analyzes the audio data transmitted from the terminal and automatically generates meeting minutes. It also understands the psychological reactions of participants during the meeting based on the collected emotional data. Based on this information, the server determines the recommended next action. 【0327】 Step 5: 【0328】 The device provides alerts based on participants' emotions. For example, if the emotion engine detects that a user is feeling stressed or frustrated, a notification will appear saying, "This topic is causing negative reactions. Please move on to the next topic or learn more." 【0329】 Step 6: 【0330】 After the meeting ends, the server automatically generates meeting minutes along with a report containing participant sentiment data. This report includes improvement suggestions based on the analysis and is delivered to users via email or a dedicated app. 【0331】 Step 7: 【0332】 Users will use this report to plan their next meeting. Based on the improvement suggestions, they will readjust the agenda and proceedings to prepare for the meeting to maximize its effectiveness. The server will also reschedule the next meeting and notify relevant parties of the details. 【0333】 (Example 2) 【0334】 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". 【0335】 In today's business environment, many meetings are not conducted efficiently or effectively. While it's crucial to schedule meetings appropriately considering participants' availability, set agendas relevant to the meeting content, and accurately record what is said, these are often not done properly. Furthermore, understanding participants' emotional states and adjusting meetings accordingly is also difficult. Improving these conditions and enhancing the quality and efficiency of meetings is essential. 【0336】 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. 【0337】 In this invention, the server includes means for analyzing participants' schedule information and proposing an optimal meeting time; means for automatically generating and sharing meeting agendas according to the purpose using natural language generation methods; means for recognizing speech during the meeting, converting it to text, and automatically generating meeting minutes; means for analyzing participants' audio and video data and evaluating their emotional state; and means for providing suggestions for adjusting the meeting progress based on this emotional state. As a result, meetings can be efficiently planned based on participants' schedules and conducted in a way that reflects their emotions, thereby improving the quality and efficiency of meetings. 【0338】 "Analyzing participant schedule information" is the process of collecting schedule data for each individual attending a meeting and identifying the most suitable date and time for the meeting. 【0339】 "Suggesting the optimal meeting time" involves analyzing collected participant schedule data to determine and present dates that are available to the majority of participants. 【0340】 "Automatically generating meeting agendas using natural language generation techniques" refers to the process of automatically creating topics and items tailored to the purpose of a meeting by utilizing generative AI technology. 【0341】 "Sharing with participants" refers to the act of distributing generated information and data to those attending a meeting, thereby ensuring that the information is shared among them. 【0342】 "Speech recognition and text conversion" is a process that analyzes speech spoken during a meeting in real time and converts it into human-readable text data. 【0343】 "Automatically generating meeting minutes" refers to the process of organizing and saving text data generated during a meeting as an official report or record. 【0344】 "Analyzing audio and video data to evaluate emotional state" refers to the process of automatically determining the psychological or emotional state of participants from the audio and video recorded during the meeting. 【0345】 "Providing suggestions for adjusting meeting proceedings based on emotional states" refers to the act of using analyzed emotional data to propose improvements to meeting procedures and methods. 【0346】 This invention is a meeting support system that utilizes advanced data analysis technology and generative AI models to improve the user's meeting experience. The system mainly consists of a server, terminals, and an emotion analysis engine. 【0347】 The server collects user schedule information. Specifically, it analyzes user calendar data using APIs from common scheduling software. This allows it to calculate the optimal meeting time and propose it to each participant. Meeting agendas, tailored to the purpose of the meeting, are created by inputting prompts into a generative AI model that uses natural language generation technology. For example, using the prompt "Please list the main topics to be discussed at the next project meeting," the server selects and shares appropriate agenda items from the output generated by the AI. 【0348】 The device analyzes each user's voice and video in real time during a meeting. It uses an industry-standard speech-to-text engine for speech recognition, instantly transcribing spoken content into text. Furthermore, it incorporates an emotion analysis engine, analyzing emotional data from the voice and video to understand the user's psychological state. Based on this analysis, it provides real-time alerts and suggestions regarding meeting progress, supporting users in conducting meetings more smoothly. Similarly, it generates and provides users with a comprehensive meeting report that considers the frequency and pace of speech based on the emotional data. 【0349】 This system allows users to conduct meetings in a planned and flexible manner. For example, if many participants react negatively to a particular agenda item during a meeting, an alert is immediately displayed to draw attention to the issue, allowing for adjustments to the meeting's direction. After the meeting, it is also possible to consider specific improvement measures for the next meeting based on the data obtained from the comprehensive report. 【0350】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0351】 Step 1: 【0352】 The server retrieves schedule information from the user's scheduling software. The input is the user's calendar API, and the output is the user's schedule data. The server analyzes this data to calculate the optimal meeting time that all participants can attend. The calculated date and time are then notified to each user. 【0353】 Step 2: 【0354】 The server uses a generative AI model to automatically generate meeting agendas. The input here is a prompt, for example, "Please list three main topics for the next new product development meeting." The output is an agenda list generated by the AI, which is shared with each participant. 【0355】 Step 3: 【0356】 The terminal collects user audio in real time during meetings and transcribes it using a speech recognition engine. Audio data is the input, and the output is spoken text data. The terminal sends this text to a server to support the automatic generation of meeting minutes. 【0357】 Step 4: 【0358】 The terminal uses the user's voice and video data to evaluate their emotional state using an emotion analysis engine. The input is the voice and video data recorded during the meeting, and the output is the result of the emotional state evaluation. The terminal sends this result to a server, which is used to provide the user with suggestions regarding the progress of the meeting. 【0359】 Step 5: 【0360】 The server stores voice text and sentiment data obtained during the meeting and analyzes it in real time. The analysis generates specific suggestions and alerts regarding the meeting's progress, which are then displayed to the user. The input in this process is the entire dataset accumulated during the meeting, while the output is the suggestions for meeting progress. 【0361】 Step 6: 【0362】 After the meeting concludes, the server automatically generates a comprehensive report based on all the data. Inputs include voice-to-text, sentiment analysis results, and proposal history. The output is a detailed report covering the meeting's specifics, which is distributed to participants. This allows users to identify areas for improvement for future meetings. 【0363】 (Application Example 2) 【0364】 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 as the "terminal". 【0365】 In team meetings at physical stores, the emotional state of participants can significantly impact the progress and outcome of the meeting. However, the lack of a system to appropriately interpret emotions from comments and facial expressions during the meeting and respond immediately can hinder communication and meeting efficiency. Systems and methods to address this challenge are needed. 【0366】 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. 【0367】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating meeting agendas according to the purpose and sharing them with participants, and means for analyzing participants' emotional states in real time and displaying warnings when negative reactions are detected. This makes it possible to accurately grasp the emotional states of meeting participants, facilitate smooth meeting progress, and improve the quality of discussions. 【0368】 "Schedule information" refers to data regarding the schedules and available time slots of meeting participants. 【0369】 "Meeting agenda" refers to the subject or topic to be discussed at a meeting. 【0370】 "Speech recognition" is a technology that converts speech into text data that a computer can understand. 【0371】 "Meeting minutes" are documents that organize the statements and decisions made during a meeting into text format. 【0372】 "Action items" refer to the actions or tasks that meeting participants should take next. 【0373】 "Real-time analysis" refers to processing and analyzing information at the very moment an event occurs. 【0374】 "Emotional state" refers to the psychological state of meeting participants and can be interpreted from their voice and facial expressions. 【0375】 A "warning message" is a message that is displayed to alert the user when certain conditions are met. 【0376】 An "improvement suggestion" is a specific proposal or opinion offered after analyzing the current situation, aimed at achieving better results. 【0377】 The system for implementing this invention consists of a server, a smart device (terminal), and an emotion analysis engine. The server analyzes the schedule information of meeting participants and proposes the optimal meeting time and agenda. The participants' smart devices are equipped with cameras and microphones, capturing audio and video in real time, which are then analyzed by the emotion analysis engine. This emotion data is transmitted to the server, enabling responses that correspond to the emotional state during the meeting. 【0378】 Specifically, the system uses the Google Cloud Speech-to-Text API to convert speech to text and the Microsoft Azure Emotion API to analyze participants' emotional states in real time. Additionally, Apache Kafka is used to process large amounts of speech and emotional data in real time. This allows for a warning to be displayed on the device if negative emotions are detected in a participant. 【0379】 For example, in a staff meeting at a retail store, if a staff member expresses dissatisfaction during a discussion about promotional strategies, an alert based on emotional data will appear on their smart device, recommending a review of the agenda or the introduction of breaks in the meeting. After the meeting, improvement suggestions based on the analysis of emotional data will be provided along with the generated meeting minutes. 【0380】 Examples of prompts for a generative AI model are as follows: 【0381】 "Please develop an idea for a meeting assistant app that provides feedback based on the emotional state of staff during a meeting. The device used would be a smartphone or smart glasses, and it would provide alerts to participants in real time based on emotion analysis results." 【0382】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0383】 Step 1: 【0384】 The server receives participant schedule information and stores it in a database. It then analyzes the received schedule information and runs an algorithm to suggest the optimal meeting time. The input is participant schedule data, and the output is a suggestion for the optimal meeting time. 【0385】 Step 2: 【0386】 The server automatically generates an agenda based on the meeting's objectives. Using objective information obtained from participants as input, it outputs an agenda designed to maximize the meeting's effectiveness. This agenda information is sent to the terminal and shared with the participants. 【0387】 Step 3: 【0388】 The device captures audio and video during the meeting. Using the built-in microphone and camera, it collects participants' audio and video data in real time. Both of these data are sent to a server for processing. 【0389】 Step 4: 【0390】 The server converts the received audio data into text using the Google Cloud Speech-to-Text API. The input is audio data, and the output is its text representation. This generates meeting minutes. 【0391】 Step 5: 【0392】 The device uses the Microsoft Azure Emotion API to perform emotion analysis on participants' video data. The input is video data, and the analysis results in an output of emotional state (positive, negative, etc.). If a negative emotion is detected, a warning will be displayed on the device. 【0393】 Step 6: 【0394】 After the meeting concludes, the server integrates audio and sentiment data to generate a comprehensive meeting report. Inputs include transcribed meeting minutes and analyzed sentiment states, while output is a final report containing improvement suggestions for participants. The generated report is distributed to participants to help them prepare for future meetings. 【0395】 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. 【0396】 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. 【0397】 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. 【0398】 [Third Embodiment] 【0399】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0400】 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. 【0401】 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). 【0402】 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. 【0403】 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. 【0404】 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). 【0405】 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. 【0406】 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. 【0407】 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. 【0408】 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. 【0409】 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. 【0410】 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". 【0411】 This invention provides a system for automating the preparation, conduct, and follow-up of meetings. This system is primarily server-centric, with terminals and users involved in each process. 【0412】 The server accesses the user's (participant's) calendar information and suggests the optimal meeting time. This frees users from the hassle of scheduling. Furthermore, the server uses AI based on the meeting's purpose to automatically generate appropriate agenda items. This generated agenda is notified to the user in advance, allowing them to check the necessary information before the meeting begins. 【0413】 During the meeting, an AI agent installed on the device supports the proceedings. This includes agenda-based time management and topic presentation. In particular, it utilizes speech recognition technology to transcribe participants' statements in real time and send them to the server. This process allows the server to automatically create meeting minutes and provide users with an accurate record of the meeting. 【0414】 After the meeting ends, the server automatically organizes the generated minutes and shares them with the participants. Furthermore, it extracts the action items decided during the meeting, creates a to-do list, and notifies the respective responsible users. This allows users to properly manage their tasks and ensure the smooth progress of the project. 【0415】 The server automatically adjusts the schedule for the next meeting and notifies participants (users) of the results. This streamlines the ongoing meeting schedule. In addition, the server, equipped with analytical capabilities, analyzes past meeting data to understand participant speaking frequency and meeting pace. Based on this data, it provides users with specific improvement suggestions. 【0416】 As a concrete example, let's assume this system is used to ensure the smooth running of a regular weekly meeting. In this case, the server picks out available time slots from the participants' calendars and suggests a date for the next meeting. During the meeting, an AI agent manages the time and generates meeting minutes in real time by transcribing speech into text. After the meeting, the minutes are organized and a push notification is sent, and action items are automatically assigned to the responsible parties. In this way, each step of meeting management is optimized to ensure smooth progress. 【0417】 The following describes the processing flow. 【0418】 Step 1: 【0419】 The server accesses the calendar information shared by meeting participants to detect available time slots. Based on this, an AI algorithm calculates the optimal meeting time and suggests it to the user. 【0420】 Step 2: 【0421】 The server analyzes the meeting's objectives and past records to automatically generate an appropriate agenda. This agenda is then sent to users via email or a notification system. 【0422】 Step 3: 【0423】 At the start of the meeting, an AI agent installed on the device assists with the progress in real time. The device keeps track of the time according to the agenda and provides reminders to the user to switch topics as needed. 【0424】 Step 4: 【0425】 The terminal uses speech recognition technology to transcribe the speech of meeting participants into text in real time and sends the generated text to the server. 【0426】 Step 5: 【0427】 The server analyzes the received text data and organizes it as meeting minutes. These minutes are then structured and edited as needed and provided to users promptly after the meeting. 【0428】 Step 6: 【0429】 The server automatically extracts action items from the discussions during the meeting and creates a to-do list. These task lists are then notified to the users assigned to them. 【0430】 Step 7: 【0431】 After the meeting ends, the server readjusts the date for the next meeting and updates the users' calendars. Once an optimal date and time are found, all relevant users are notified. 【0432】 Step 8: 【0433】 The server analyzes all previously recorded meeting data and identifies areas for improvement based on the pace of discussion and the frequency of contributions. The analysis results are provided to the user in report format, which can be used to improve future meetings. 【0434】 (Example 1) 【0435】 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." 【0436】 Meeting preparation, conducting, and follow-up require significant time and effort, and there is a need to address the inefficiencies in scheduling participants, setting agendas, recording meetings, and managing tasks. 【0437】 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. 【0438】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating a meeting agenda tailored to the purpose using a generative AI model and sharing it with participants, and means for managing meeting time and presenting topics during the meeting using an AI agent. This simplifies meeting preparation and enables efficient meeting progress and follow-up. 【0439】 A "device that analyzes participants' schedule information and suggests the optimal meeting time" is a function that collects schedule data from individual participants and automatically calculates and suggests the meeting time that is most convenient for everyone to attend. 【0440】 The "device that automatically generates meeting agendas according to purpose using an AI model and shares them with participants" is a system that generates an agenda based on the purpose of the meeting, constructs the proposed agenda using natural language generation technology, and has a function to share the content with participants in advance. 【0441】 A "device that recognizes speech during a meeting, converts it to text, and automatically generates meeting minutes" is a technology that converts meeting audio data into text data in real time and generates meeting minutes immediately based on that data. 【0442】 A "device for organizing generated meeting minutes and notifying participants" is a system that organizes automatically generated meeting minutes and efficiently sends necessary information to participants. 【0443】 A "device that automatically extracts and notifies participants of action items" is a system that identifies tasks and action items from the meeting content and notifies the responsible parties of them. 【0444】 A "device that automatically adjusts the date of the next meeting after a meeting" is a function that checks the updated schedules of participants again for ongoing meetings and automatically adjusts the date for the next meeting. 【0445】 A "device that analyzes past meeting data and generates improvement suggestions" is a system that analyzes stored meeting information and, based on the insights gained, creates recommendations that contribute to improving the efficiency of meetings. 【0446】 A "device that uses an AI agent for time management and topic presentation" is a function that uses artificial intelligence to control the progress of a meeting in a timely manner and to raise and support topics based on a pre-set agenda. 【0447】 This invention is a system designed to streamline meeting management and is primarily built around a server. The server collects scheduling information managed by participants and calculates the optimal meeting time. This process utilizes APIs from common scheduling tools. For example, it retrieves data through the API of a digital calendar system and automatically detects and suggests available times for all participants. 【0448】 The server automatically generates agenda items tailored to the meeting's objectives using a generative AI model. This AI model utilizes a large-scale language model equipped with natural language processing technology. The model receives prompts such as "Generate three necessary agenda items for next week's project meeting" as input and generates an appropriate agenda based on them. The generated agenda is shared with participants via email and a notification system, allowing for prior review. 【0449】 During meetings, each terminal is equipped with a dedicated AI agent that manages time and presents topics. This AI agent uses speech recognition technology to transcribe participants' statements in real time and sends this data to a server. This allows the server to generate meeting minutes quickly and accurately. Open-source or commercial speech recognition engines are used for speech recognition. 【0450】 After the meeting, the server organizes the generated minutes and notifies the participants. During this process, an AI model automatically extracts the action items identified during the meeting and notifies each participant via email or other means. As a result, users can effectively manage their tasks and facilitate the smooth progress of the project. 【0451】 Furthermore, the server automatically schedules the next meeting and notifies participants of the results. By analyzing past meeting data, it generates and provides users with specific suggestions to improve the efficiency of meetings. In this way, the present invention is a system that streamlines and reduces the workload of all processes related to meetings. 【0452】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0453】 Step 1: 【0454】 The server collects participant schedule information. It retrieves schedule data from participants' digital calendars as input. Based on the retrieved schedule information, it performs data analysis to identify available time slots. This then outputs data to suggest the optimal meeting time. 【0455】 Step 2: 【0456】 The server automatically generates meeting agendas using a generative AI model. The input is information about the meeting's purpose and past agenda items. The generative AI model uses natural language processing based on this information to set appropriate agenda items. The generated agenda is then provided as output and shared with participants. 【0457】 Step 3: 【0458】 The device recognizes and transcribes audio during a meeting. It uses participant speech data captured via microphones as input. A speech recognition engine processes the audio data in real time and converts it to text. This conversion result is sent to a server and output as data for generating meeting minutes. 【0459】 Step 4: 【0460】 The server automatically generates meeting minutes based on the received text data. The text data obtained in step 3 is used as input, and formatting and summarization processes are performed. The meeting minutes are quickly compiled and distributed to participants via email or notification. 【0461】 Step 5: 【0462】 The server automatically extracts the action items decided during the meeting. The meeting minutes generated in step 4 are used as input. The generation AI model is used to identify the target of each action item and create a to-do list. Each action item is notified to the relevant participants and output as their assigned task. 【0463】 Step 6: 【0464】 The server automatically schedules the next meeting. It uses updated participant schedule information and past meeting history as input. It analyzes the schedules, selects a date and time when everyone can attend, and outputs it as the next meeting date. Participants are notified of the result. 【0465】 (Application Example 1) 【0466】 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." 【0467】 In smart cities, there is a need to facilitate communication between local communities and administrative agencies and to effectively conduct meetings with local residents. In particular, automating and streamlining all steps of meeting preparation, management, and follow-up is a key challenge. Furthermore, the use of artificial intelligence for creative agenda generation and timely information provision to participants is essential for revitalizing local communities. 【0468】 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. 【0469】 This invention includes a server that analyzes participants' schedule information and proposes an optimal meeting time, a server that automatically generates meeting agendas using an AI model and shares them with participants, and a server that optimizes and automates meetings specifically for smart cities. This enables smooth operation of meetings in local communities and effective communication with residents. 【0470】 "Participants" refer to the individual people who attend a meeting or conference, and are the subjects for whom scheduling and information provision are handled by the system. 【0471】 "Meeting time" refers to the time when participants gather to discuss a specific topic, and is a time proposed for the purpose of efficient communication. 【0472】 An "agenda" refers to the topics or subjects discussed at a meeting or conference, and is automatically generated by a generative AI model based on relevant information. 【0473】 "Speech recognition" refers to a technology that converts participants' spoken words during a meeting into text, and is used for the automatic generation of meeting minutes. 【0474】 "Meeting minutes" are documents that faithfully record the statements and decisions made at meetings or conferences, and are the contents that are communicated to the participants. 【0475】 "Action items" refer to tasks and responsibilities assigned to participants as specific actions decided at the meeting. 【0476】 A "generative AI model" is an artificial intelligence technology used to automatically create meeting agendas and improvement proposals based on past data and new information. 【0477】 A "smart city" refers to a city that utilizes information technology to improve the efficiency of urban management and residents' lives, with the aim of promoting the development of the local community. 【0478】 "Optimization" refers to methods aimed at improving the efficiency of meeting management and eliminating waste of time and resources. 【0479】 To implement this invention, it is necessary to build a system that proposes the optimal meeting time based on participants' schedule information and automatically generates the meeting agenda using an AI model. This system will facilitate smooth meetings between local communities and government agencies and will also manage follow-up activities from start to finish. 【0480】 The server first collects participants' calendar information and processes the data on a typical cloud server (such as AWS or Google Cloud) in a cloud environment. Based on the collected data, it calculates the optimal meeting time and notifies the participants. The devices used by participants include smartphones, tablets, and PCs. 【0481】 For meeting agendas, generative AI models (such as natural language processing models like GPT-4) can be used. The server generates agendas based on past meeting data and shares them with participants. Google Cloud Speech-to-Text is used for speech recognition technology, transcribing participants' speech in real time and sending it to the server. Based on this, meeting minutes are automatically generated and organized. 【0482】 As a concrete example, consider a community meeting between the city hall and local residents. To ensure the efficient operation of this meeting, the schedules of all participants are coordinated, and a prompt is given to the AI ​​model to generate an agenda for the next meeting, such as, "Generate an agenda for the next meeting on the local disaster prevention plan. Please take past meeting records into consideration and include new proposals." This prompt allows the AI ​​model to propose a creative agenda. 【0483】 This system will enable the revitalization of local communities and the improvement of communication efficiency in smart cities. 【0484】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0485】 Step 1: 【0486】 The server collects participants' calendar information. To process this information, it first retrieves appointments from the participants' smartphone or PC calendar apps. The input is the participants' calendar information, and the output is the base data for suggesting the optimal meeting time. The server analyzes the collected data in the cloud to identify available time slots. 【0487】 Step 2: 【0488】 The server proposes the optimal meeting time based on the identified free time. This step uses the parsed calendar information as input. The data calculation determines and selects the time when the most participants can attend. The output is a list of proposed meeting times, which is notified to participants via their terminals. 【0489】 Step 3: 【0490】 The server automatically generates meeting agendas using a generative AI model. This step uses past meeting data and related information as input. The generative AI model performs natural language processing based on this data to generate draft agendas. The output is the newly proposed agenda, which is shared with users via the terminal. 【0491】 Step 4: 【0492】 During the meeting, speech recognition software built into the terminal transcribes participants' speech into text. The input is real-time audio data, which is converted into text data by speech recognition technology. The output is the transcribed speech, which is then sent to the server. 【0493】 Step 5: 【0494】 The server automatically generates and organizes meeting minutes based on transcribed speech. This step uses speech recognition-generated text data as input. Data processing organizes the speech content in a logical sequence to create a complete meeting record. The output is the completed meeting minutes, which are then notified to the user. 【0495】 Step 6: 【0496】 After the meeting ends, the server automatically extracts the action items decided at the meeting and notifies the participants. The input for this process is the generated meeting minutes. The data processing extracts the action items and assigns them to the corresponding personnel. The output is a to-do list for each person in charge. 【0497】 Step 7: 【0498】 The server automatically adjusts the date for the next meeting. This step takes the participants' upcoming schedules as input, reconfirms their calendar information, and selects a suitable date. The output is the proposed time for the next meeting, which is notified to the participants in advance. 【0499】 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. 【0500】 This invention is a meeting support system that utilizes the emotional state of users during meetings to improve the efficiency and quality of meeting content. The system mainly consists of a server, terminals, and an emotion engine. 【0501】 The server collects the schedules of meeting participants and proposes the most suitable meeting date. It also automatically generates an agenda based on the meeting's purpose and shares it with participants via their devices at the start of the meeting. Using speech recognition technology, it records meeting comments as text data in real time and automatically generates meeting minutes on the server. 【0502】 The device incorporates an emotion engine that analyzes the user's emotional state in real time from the audio and video of meeting participants. This information is sent to a server and used to help with decision-making and adjusting the agenda during the ongoing meeting. For example, if a participant shows a negative reaction to a particular topic, the device displays an alert, allowing the user to take immediate action. 【0503】 After the meeting concludes, the server automatically distributes a comprehensive report to participants, including not only the minutes but also emotional states measured during the meeting. This report includes suggestions for improvement based on the frequency of contributions and emotional changes, which will be used to improve future meeting management. 【0504】 As a concrete example, let's assume this system is applied to a project progress meeting. Users can conduct the meeting according to the agenda suggested by the system. If a participant appears anxious during the discussion, their emotional data is detected via their device, and a break in the meeting is recommended. After the meeting, the emotional data is analyzed, and specific suggestions for improving collaborative efficiency are provided. 【0505】 Thus, the system of the present invention, which incorporates an emotion engine, reflects the psychological state of participants and optimizes decision-making in the meeting in progress. It is possible to simultaneously achieve a high level of automation and quality improvement in meeting management. 【0506】 The following describes the processing flow. 【0507】 Step 1: 【0508】 The server retrieves the user's calendar information and analyzes the availability of all participants. Based on this, it calculates the optimal meeting start and end times and proposes them to the user. The proposal is notified via email or scheduling app. 【0509】 Step 2: 【0510】 The server collects the meeting's purpose and relevant information, and uses AI to automatically generate an agenda. This agenda is sent to all meeting participants in advance via their devices. Users can review it and adjust the agenda content as needed. 【0511】 Step 3: 【0512】 The device activates its speech recognition function at the start of the meeting and transcribes participants' speech into text in real time. Simultaneously, the device uses its camera and microphone to analyze participants' facial expressions and voice tone, collecting emotional data. 【0513】 Step 4: 【0514】 The server analyzes the audio data transmitted from the terminal and automatically generates meeting minutes. It also understands the psychological reactions of participants during the meeting based on the collected emotional data. Based on this information, the server determines the recommended next action. 【0515】 Step 5: 【0516】 The device provides alerts based on participants' emotions. For example, if the emotion engine detects that a user is feeling stressed or frustrated, a notification will appear saying, "This topic is causing negative reactions. Please move on to the next topic or learn more." 【0517】 Step 6: 【0518】 After the meeting ends, the server automatically generates meeting minutes along with a report containing participant sentiment data. This report includes improvement suggestions based on the analysis and is delivered to users via email or a dedicated app. 【0519】 Step 7: 【0520】 Users will use this report to plan their next meeting. Based on the improvement suggestions, they will readjust the agenda and proceedings to prepare for the meeting to maximize its effectiveness. The server will also reschedule the next meeting and notify relevant parties of the details. 【0521】 (Example 2) 【0522】 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." 【0523】 In today's business environment, many meetings are not conducted efficiently or effectively. While it's crucial to schedule meetings appropriately considering participants' availability, set agendas relevant to the meeting content, and accurately record what is said, these are often not done properly. Furthermore, understanding participants' emotional states and adjusting meetings accordingly is also difficult. Improving these conditions and enhancing the quality and efficiency of meetings is essential. 【0524】 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. 【0525】 In this invention, the server includes means for analyzing participants' schedule information and proposing an optimal meeting time; means for automatically generating and sharing meeting agendas according to the purpose using natural language generation methods; means for recognizing speech during the meeting, converting it to text, and automatically generating meeting minutes; means for analyzing participants' audio and video data and evaluating their emotional state; and means for providing suggestions for adjusting the meeting progress based on this emotional state. As a result, meetings can be efficiently planned based on participants' schedules and conducted in a way that reflects their emotions, thereby improving the quality and efficiency of meetings. 【0526】 "Analyzing participant schedule information" is the process of collecting schedule data for each individual attending a meeting and identifying the most suitable date and time for the meeting. 【0527】 "Suggesting the optimal meeting time" involves analyzing collected participant schedule data to determine and present dates that are available to the majority of participants. 【0528】 "Automatically generating meeting agendas using natural language generation techniques" refers to the process of automatically creating topics and items tailored to the purpose of a meeting by utilizing generative AI technology. 【0529】 "Sharing with participants" refers to the act of distributing generated information and data to those attending a meeting, thereby ensuring that the information is shared among them. 【0530】 "Speech recognition and text conversion" is a process that analyzes speech spoken during a meeting in real time and converts it into human-readable text data. 【0531】 "Automatically generating meeting minutes" refers to the process of organizing and saving text data generated during a meeting as an official report or record. 【0532】 "Analyzing audio and video data to evaluate emotional state" refers to the process of automatically determining the psychological or emotional state of participants from the audio and video recorded during the meeting. 【0533】 "Providing suggestions for adjusting meeting proceedings based on emotional states" refers to the act of using analyzed emotional data to propose improvements to meeting procedures and methods. 【0534】 This invention is a meeting support system that utilizes advanced data analysis technology and generative AI models to improve the user's meeting experience. The system mainly consists of a server, terminals, and an emotion analysis engine. 【0535】 The server collects user schedule information. Specifically, it analyzes user calendar data using APIs from common scheduling software. This allows it to calculate the optimal meeting time and propose it to each participant. Meeting agendas, tailored to the purpose of the meeting, are created by inputting prompts into a generative AI model that uses natural language generation technology. For example, using the prompt "Please list the main topics to be discussed at the next project meeting," the server selects and shares appropriate agenda items from the output generated by the AI. 【0536】 The device analyzes each user's voice and video in real time during a meeting. It uses an industry-standard speech-to-text engine for speech recognition, instantly transcribing spoken content into text. Furthermore, it incorporates an emotion analysis engine, analyzing emotional data from the voice and video to understand the user's psychological state. Based on this analysis, it provides real-time alerts and suggestions regarding meeting progress, supporting users in conducting meetings more smoothly. Similarly, it generates and provides users with a comprehensive meeting report that considers the frequency and pace of speech based on the emotional data. 【0537】 This system allows users to conduct meetings in a planned and flexible manner. For example, if many participants react negatively to a particular agenda item during a meeting, an alert is immediately displayed to draw attention to the issue, allowing for adjustments to the meeting's direction. After the meeting, it is also possible to consider specific improvement measures for the next meeting based on the data obtained from the comprehensive report. 【0538】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0539】 Step 1: 【0540】 The server retrieves schedule information from the user's scheduling software. The input is the user's calendar API, and the output is the user's schedule data. The server analyzes this data to calculate the optimal meeting time that all participants can attend. The calculated date and time are then notified to each user. 【0541】 Step 2: 【0542】 The server uses a generative AI model to automatically generate meeting agendas. The input here is a prompt, for example, "Please list three main topics for the next new product development meeting." The output is an agenda list generated by the AI, which is shared with each participant. 【0543】 Step 3: 【0544】 The terminal collects user audio in real time during meetings and transcribes it using a speech recognition engine. Audio data is the input, and the output is spoken text data. The terminal sends this text to a server to support the automatic generation of meeting minutes. 【0545】 Step 4: 【0546】 The terminal uses the user's voice and video data to evaluate their emotional state using an emotion analysis engine. The input is the voice and video data recorded during the meeting, and the output is the result of the emotional state evaluation. The terminal sends this result to a server, which is used to provide the user with suggestions regarding the progress of the meeting. 【0547】 Step 5: 【0548】 The server stores voice text and sentiment data obtained during the meeting and analyzes it in real time. The analysis generates specific suggestions and alerts regarding the meeting's progress, which are then displayed to the user. The input in this process is the entire dataset accumulated during the meeting, while the output is the suggestions for meeting progress. 【0549】 Step 6: 【0550】 After the meeting concludes, the server automatically generates a comprehensive report based on all the data. Inputs include voice-to-text, sentiment analysis results, and proposal history. The output is a detailed report covering the meeting's specifics, which is distributed to participants. This allows users to identify areas for improvement for future meetings. 【0551】 (Application Example 2) 【0552】 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." 【0553】 In team meetings at physical stores, the emotional state of participants can significantly impact the progress and outcome of the meeting. However, the lack of a system to appropriately interpret emotions from comments and facial expressions during the meeting and respond immediately can hinder communication and meeting efficiency. Systems and methods to address this challenge are needed. 【0554】 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. 【0555】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating meeting agendas according to the purpose and sharing them with participants, and means for analyzing participants' emotional states in real time and displaying warnings when negative reactions are detected. This makes it possible to accurately grasp the emotional states of meeting participants, facilitate smooth meeting progress, and improve the quality of discussions. 【0556】 "Schedule information" refers to data regarding the schedules and available time slots of meeting participants. 【0557】 "Meeting agenda" refers to the subject or topic to be discussed at a meeting. 【0558】 "Speech recognition" is a technology that converts speech into text data that a computer can understand. 【0559】 "Meeting minutes" are documents that organize the statements and decisions made during a meeting into text format. 【0560】 "Action items" refer to the actions or tasks that meeting participants should take next. 【0561】 "Real-time analysis" refers to processing and analyzing information at the very moment an event occurs. 【0562】 "Emotional state" refers to the psychological state of meeting participants and can be interpreted from their voice and facial expressions. 【0563】 A "warning message" is a message that is displayed to alert the user when certain conditions are met. 【0564】 An "improvement suggestion" is a specific proposal or opinion offered after analyzing the current situation, aimed at achieving better results. 【0565】 The system for implementing this invention consists of a server, a smart device (terminal), and an emotion analysis engine. The server analyzes the schedule information of meeting participants and proposes the optimal meeting time and agenda. The participants' smart devices are equipped with cameras and microphones, capturing audio and video in real time, which are then analyzed by the emotion analysis engine. This emotion data is transmitted to the server, enabling responses that correspond to the emotional state during the meeting. 【0566】 Specifically, the system uses the Google Cloud Speech-to-Text API to convert speech to text and the Microsoft Azure Emotion API to analyze participants' emotional states in real time. Additionally, Apache Kafka is used to process large amounts of speech and emotional data in real time. This allows for a warning to be displayed on the device if negative emotions are detected in a participant. 【0567】 For example, in a staff meeting at a retail store, if a staff member expresses dissatisfaction during a discussion about promotional strategies, an alert based on emotional data will appear on their smart device, recommending a review of the agenda or the introduction of breaks in the meeting. After the meeting, improvement suggestions based on the analysis of emotional data will be provided along with the generated meeting minutes. 【0568】 Examples of prompts for a generative AI model are as follows: 【0569】 "Please develop an idea for a meeting assistant app that provides feedback based on the emotional state of staff during a meeting. The device used would be a smartphone or smart glasses, and it would provide alerts to participants in real time based on emotion analysis results." 【0570】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0571】 Step 1: 【0572】 The server receives participant schedule information and stores it in a database. It then analyzes the received schedule information and runs an algorithm to suggest the optimal meeting time. The input is participant schedule data, and the output is a suggestion for the optimal meeting time. 【0573】 Step 2: 【0574】 The server automatically generates an agenda based on the meeting's objectives. Using objective information obtained from participants as input, it outputs an agenda designed to maximize the meeting's effectiveness. This agenda information is sent to the terminal and shared with the participants. 【0575】 Step 3: 【0576】 The device captures audio and video during the meeting. Using the built-in microphone and camera, it collects participants' audio and video data in real time. Both of these data are sent to a server for processing. 【0577】 Step 4: 【0578】 The server converts the received audio data into text using the Google Cloud Speech-to-Text API. The input is audio data, and the output is its text representation. This generates meeting minutes. 【0579】 Step 5: 【0580】 The device uses the Microsoft Azure Emotion API to perform emotion analysis on participants' video data. The input is video data, and the analysis results in an output of emotional state (positive, negative, etc.). If a negative emotion is detected, a warning will be displayed on the device. 【0581】 Step 6: 【0582】 After the meeting concludes, the server integrates audio and sentiment data to generate a comprehensive meeting report. Inputs include transcribed meeting minutes and analyzed sentiment states, while output is a final report containing improvement suggestions for participants. The generated report is distributed to participants to help them prepare for future meetings. 【0583】 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. 【0584】 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. 【0585】 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. 【0586】 [Fourth Embodiment] 【0587】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0588】 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. 【0589】 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). 【0590】 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. 【0591】 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. 【0592】 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). 【0593】 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. 【0594】 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. 【0595】 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. 【0596】 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. 【0597】 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. 【0598】 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. 【0599】 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". 【0600】 This invention provides a system for automating the preparation, conduct, and follow-up of meetings. This system is primarily server-centric, with terminals and users involved in each process. 【0601】 The server accesses the user's (participant's) calendar information and suggests the optimal meeting time. This frees users from the hassle of scheduling. Furthermore, the server uses AI based on the meeting's purpose to automatically generate appropriate agenda items. This generated agenda is notified to the user in advance, allowing them to check the necessary information before the meeting begins. 【0602】 During the meeting, an AI agent installed on the device supports the proceedings. This includes agenda-based time management and topic presentation. In particular, it utilizes speech recognition technology to transcribe participants' statements in real time and send them to the server. This process allows the server to automatically create meeting minutes and provide users with an accurate record of the meeting. 【0603】 After the meeting ends, the server automatically organizes the generated minutes and shares them with the participants. Furthermore, it extracts the action items decided during the meeting, creates a to-do list, and notifies the respective responsible users. This allows users to properly manage their tasks and ensure the smooth progress of the project. 【0604】 The server automatically adjusts the schedule for the next meeting and notifies participants (users) of the results. This streamlines the ongoing meeting schedule. In addition, the server, equipped with analytical capabilities, analyzes past meeting data to understand participant speaking frequency and meeting pace. Based on this data, it provides users with specific improvement suggestions. 【0605】 As a concrete example, let's assume this system is used to ensure the smooth running of a regular weekly meeting. In this case, the server picks out available time slots from the participants' calendars and suggests a date for the next meeting. During the meeting, an AI agent manages the time and generates meeting minutes in real time by transcribing speech into text. After the meeting, the minutes are organized and a push notification is sent, and action items are automatically assigned to the responsible parties. In this way, each step of meeting management is optimized to ensure smooth progress. 【0606】 The following describes the processing flow. 【0607】 Step 1: 【0608】 The server accesses the calendar information shared by meeting participants to detect available time slots. Based on this, an AI algorithm calculates the optimal meeting time and suggests it to the user. 【0609】 Step 2: 【0610】 The server analyzes the meeting's objectives and past records to automatically generate an appropriate agenda. This agenda is then sent to users via email or a notification system. 【0611】 Step 3: 【0612】 At the start of the meeting, an AI agent installed on the device assists with the progress in real time. The device keeps track of the time according to the agenda and provides reminders to the user to switch topics as needed. 【0613】 Step 4: 【0614】 The terminal uses speech recognition technology to transcribe the speech of meeting participants into text in real time and sends the generated text to the server. 【0615】 Step 5: 【0616】 The server analyzes the received text data and organizes it as meeting minutes. These minutes are then structured and edited as needed and provided to users promptly after the meeting. 【0617】 Step 6: 【0618】 The server automatically extracts action items from the discussions during the meeting and creates a to-do list. These task lists are then notified to the users assigned to them. 【0619】 Step 7: 【0620】 After the meeting ends, the server readjusts the date for the next meeting and updates the users' calendars. Once an optimal date and time are found, all relevant users are notified. 【0621】 Step 8: 【0622】 The server analyzes all previously recorded meeting data and identifies areas for improvement based on the pace of discussion and the frequency of contributions. The analysis results are provided to the user in report format, which can be used to improve future meetings. 【0623】 (Example 1) 【0624】 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". 【0625】 Meeting preparation, conducting, and follow-up require significant time and effort, and there is a need to address the inefficiencies in scheduling participants, setting agendas, recording meetings, and managing tasks. 【0626】 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. 【0627】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating a meeting agenda tailored to the purpose using a generative AI model and sharing it with participants, and means for managing meeting time and presenting topics during the meeting using an AI agent. This simplifies meeting preparation and enables efficient meeting progress and follow-up. 【0628】 A "device that analyzes participants' schedule information and suggests the optimal meeting time" is a function that collects schedule data from individual participants and automatically calculates and suggests the meeting time that is most convenient for everyone to attend. 【0629】 The "device that automatically generates meeting agendas according to purpose using an AI model and shares them with participants" is a system that generates an agenda based on the purpose of the meeting, constructs the proposed agenda using natural language generation technology, and has a function to share the content with participants in advance. 【0630】 A "device that recognizes speech during a meeting, converts it to text, and automatically generates meeting minutes" is a technology that converts meeting audio data into text data in real time and generates meeting minutes immediately based on that data. 【0631】 A "device for organizing generated meeting minutes and notifying participants" is a system that organizes automatically generated meeting minutes and efficiently sends necessary information to participants. 【0632】 A "device that automatically extracts and notifies participants of action items" is a system that identifies tasks and action items from the meeting content and notifies the responsible parties of them. 【0633】 A "device that automatically adjusts the date of the next meeting after a meeting" is a function that checks the updated schedules of participants again for ongoing meetings and automatically adjusts the date for the next meeting. 【0634】 A "device that analyzes past meeting data and generates improvement suggestions" is a system that analyzes stored meeting information and, based on the insights gained, creates recommendations that contribute to improving the efficiency of meetings. 【0635】 A "device that uses an AI agent for time management and topic presentation" is a function that uses artificial intelligence to control the progress of a meeting in a timely manner and to raise and support topics based on a pre-set agenda. 【0636】 This invention is a system designed to streamline meeting management and is primarily built around a server. The server collects scheduling information managed by participants and calculates the optimal meeting time. This process utilizes APIs from common scheduling tools. For example, it retrieves data through the API of a digital calendar system and automatically detects and suggests available times for all participants. 【0637】 The server automatically generates agenda items tailored to the meeting's objectives using a generative AI model. This AI model utilizes a large-scale language model equipped with natural language processing technology. The model receives prompts such as "Generate three necessary agenda items for next week's project meeting" as input and generates an appropriate agenda based on them. The generated agenda is shared with participants via email and a notification system, allowing for prior review. 【0638】 During meetings, each terminal is equipped with a dedicated AI agent that manages time and presents topics. This AI agent uses speech recognition technology to transcribe participants' statements in real time and sends this data to a server. This allows the server to generate meeting minutes quickly and accurately. Open-source or commercial speech recognition engines are used for speech recognition. 【0639】 After the meeting, the server organizes the generated minutes and notifies the participants. During this process, an AI model automatically extracts the action items identified during the meeting and notifies each participant via email or other means. As a result, users can effectively manage their tasks and facilitate the smooth progress of the project. 【0640】 Furthermore, the server automatically schedules the next meeting and notifies participants of the results. By analyzing past meeting data, it generates and provides users with specific suggestions to improve the efficiency of meetings. In this way, the present invention is a system that streamlines and reduces the workload of all processes related to meetings. 【0641】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0642】 Step 1: 【0643】 The server collects participant schedule information. It retrieves schedule data from participants' digital calendars as input. Based on the retrieved schedule information, it performs data analysis to identify available time slots. This then outputs data to suggest the optimal meeting time. 【0644】 Step 2: 【0645】 The server automatically generates meeting agendas using a generative AI model. The input is information about the meeting's purpose and past agenda items. The generative AI model uses natural language processing based on this information to set appropriate agenda items. The generated agenda is then provided as output and shared with participants. 【0646】 Step 3: 【0647】 The device recognizes and transcribes audio during a meeting. It uses participant speech data captured via microphones as input. A speech recognition engine processes the audio data in real time and converts it to text. This conversion result is sent to a server and output as data for generating meeting minutes. 【0648】 Step 4: 【0649】 The server automatically generates meeting minutes based on the received text data. The text data obtained in step 3 is used as input, and formatting and summarization processes are performed. The meeting minutes are quickly compiled and distributed to participants via email or notification. 【0650】 Step 5: 【0651】 The server automatically extracts the action items decided during the meeting. The meeting minutes generated in step 4 are used as input. The generation AI model is used to identify the target of each action item and create a to-do list. Each action item is notified to the relevant participants and output as their assigned task. 【0652】 Step 6: 【0653】 The server automatically schedules the next meeting. It uses updated participant schedule information and past meeting history as input. It analyzes the schedules, selects a date and time when everyone can attend, and outputs it as the next meeting date. Participants are notified of the result. 【0654】 (Application Example 1) 【0655】 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". 【0656】 In smart cities, there is a need to facilitate communication between local communities and administrative agencies and to effectively conduct meetings with local residents. In particular, automating and streamlining all steps of meeting preparation, management, and follow-up is a key challenge. Furthermore, the use of artificial intelligence for creative agenda generation and timely information provision to participants is essential for revitalizing local communities. 【0657】 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. 【0658】 This invention includes a server that analyzes participants' schedule information and proposes an optimal meeting time, a server that automatically generates meeting agendas using an AI model and shares them with participants, and a server that optimizes and automates meetings specifically for smart cities. This enables smooth operation of meetings in local communities and effective communication with residents. 【0659】 "Participants" refer to the individual people who attend a meeting or conference, and are the subjects for whom scheduling and information provision are handled by the system. 【0660】 "Meeting time" refers to the time when participants gather to discuss a specific topic, and is a time proposed for the purpose of efficient communication. 【0661】 An "agenda" refers to the topics or subjects discussed at a meeting or conference, and is automatically generated by a generative AI model based on relevant information. 【0662】 "Speech recognition" refers to a technology that converts participants' spoken words during a meeting into text, and is used for the automatic generation of meeting minutes. 【0663】 "Meeting minutes" are documents that faithfully record the statements and decisions made at meetings or conferences, and are the contents that are communicated to the participants. 【0664】 "Action items" refer to tasks and responsibilities assigned to participants as specific actions decided at the meeting. 【0665】 A "generative AI model" is an artificial intelligence technology used to automatically create meeting agendas and improvement proposals based on past data and new information. 【0666】 A "smart city" refers to a city that utilizes information technology to improve the efficiency of urban management and residents' lives, with the aim of promoting the development of the local community. 【0667】 "Optimization" refers to methods aimed at improving the efficiency of meeting management and eliminating waste of time and resources. 【0668】 To implement this invention, it is necessary to build a system that proposes the optimal meeting time based on participants' schedule information and automatically generates the meeting agenda using an AI model. This system will facilitate smooth meetings between local communities and government agencies and will also manage follow-up activities from start to finish. 【0669】 The server first collects participants' calendar information and processes the data on a typical cloud server (such as AWS or Google Cloud) in a cloud environment. Based on the collected data, it calculates the optimal meeting time and notifies the participants. The devices used by participants include smartphones, tablets, and PCs. 【0670】 For meeting agendas, generative AI models (such as natural language processing models like GPT-4) can be used. The server generates agendas based on past meeting data and shares them with participants. Google Cloud Speech-to-Text is used for speech recognition technology, transcribing participants' speech in real time and sending it to the server. Based on this, meeting minutes are automatically generated and organized. 【0671】 As a concrete example, consider a community meeting between the city hall and local residents. To ensure the efficient operation of this meeting, the schedules of all participants are coordinated, and a prompt is given to the AI ​​model to generate an agenda for the next meeting, such as, "Generate an agenda for the next meeting on the local disaster prevention plan. Please take past meeting records into consideration and include new proposals." This prompt allows the AI ​​model to propose a creative agenda. 【0672】 This system will enable the revitalization of local communities and the improvement of communication efficiency in smart cities. 【0673】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0674】 Step 1: 【0675】 The server collects participants' calendar information. To process this information, it first retrieves appointments from the participants' smartphone or PC calendar apps. The input is the participants' calendar information, and the output is the base data for suggesting the optimal meeting time. The server analyzes the collected data in the cloud to identify available time slots. 【0676】 Step 2: 【0677】 The server proposes the optimal meeting time based on the identified free time. This step uses the parsed calendar information as input. The data calculation determines and selects the time when the most participants can attend. The output is a list of proposed meeting times, which is notified to participants via their terminals. 【0678】 Step 3: 【0679】 The server automatically generates meeting agendas using a generative AI model. This step uses past meeting data and related information as input. The generative AI model performs natural language processing based on this data to generate draft agendas. The output is the newly proposed agenda, which is shared with users via the terminal. 【0680】 Step 4: 【0681】 During the meeting, speech recognition software built into the terminal transcribes participants' speech into text. The input is real-time audio data, which is converted into text data by speech recognition technology. The output is the transcribed speech, which is then sent to the server. 【0682】 Step 5: 【0683】 The server automatically generates and organizes meeting minutes based on transcribed speech. This step uses speech recognition-generated text data as input. Data processing organizes the speech content in a logical sequence to create a complete meeting record. The output is the completed meeting minutes, which are then notified to the user. 【0684】 Step 6: 【0685】 After the meeting ends, the server automatically extracts the action items decided at the meeting and notifies the participants. The input for this process is the generated meeting minutes. The data processing extracts the action items and assigns them to the corresponding personnel. The output is a to-do list for each person in charge. 【0686】 Step 7: 【0687】 The server automatically adjusts the date for the next meeting. This step takes the participants' upcoming schedules as input, reconfirms their calendar information, and selects a suitable date. The output is the proposed time for the next meeting, which is notified to the participants in advance. 【0688】 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. 【0689】 This invention is a meeting support system that utilizes the emotional state of users during meetings to improve the efficiency and quality of meeting content. The system mainly consists of a server, terminals, and an emotion engine. 【0690】 The server collects the schedules of meeting participants and proposes the most suitable meeting date. It also automatically generates an agenda based on the meeting's purpose and shares it with participants via their devices at the start of the meeting. Using speech recognition technology, it records meeting comments as text data in real time and automatically generates meeting minutes on the server. 【0691】 The device incorporates an emotion engine that analyzes the user's emotional state in real time from the audio and video of meeting participants. This information is sent to a server and used to help with decision-making and adjusting the agenda during the ongoing meeting. For example, if a participant shows a negative reaction to a particular topic, the device displays an alert, allowing the user to take immediate action. 【0692】 After the meeting concludes, the server automatically distributes a comprehensive report to participants, including not only the minutes but also emotional states measured during the meeting. This report includes suggestions for improvement based on the frequency of contributions and emotional changes, which will be used to improve future meeting management. 【0693】 As a concrete example, let's assume this system is applied to a project progress meeting. Users can conduct the meeting according to the agenda suggested by the system. If a participant appears anxious during the discussion, their emotional data is detected via their device, and a break in the meeting is recommended. After the meeting, the emotional data is analyzed, and specific suggestions for improving collaborative efficiency are provided. 【0694】 Thus, the system of the present invention, which incorporates an emotion engine, reflects the psychological state of participants and optimizes decision-making in the meeting in progress. It is possible to simultaneously achieve a high level of automation and quality improvement in meeting management. 【0695】 The following describes the processing flow. 【0696】 Step 1: 【0697】 The server retrieves the user's calendar information and analyzes the availability of all participants. Based on this, it calculates the optimal meeting start and end times and proposes them to the user. The proposal is notified via email or scheduling app. 【0698】 Step 2: 【0699】 The server collects the meeting's purpose and relevant information, and uses AI to automatically generate an agenda. This agenda is sent to all meeting participants in advance via their devices. Users can review it and adjust the agenda content as needed. 【0700】 Step 3: 【0701】 The device activates its speech recognition function at the start of the meeting and transcribes participants' speech into text in real time. Simultaneously, the device uses its camera and microphone to analyze participants' facial expressions and voice tone, collecting emotional data. 【0702】 Step 4: 【0703】 The server analyzes the audio data transmitted from the terminal and automatically generates meeting minutes. It also understands the psychological reactions of participants during the meeting based on the collected emotional data. Based on this information, the server determines the recommended next action. 【0704】 Step 5: 【0705】 The device provides alerts based on participants' emotions. For example, if the emotion engine detects that a user is feeling stressed or frustrated, a notification will appear saying, "This topic is causing negative reactions. Please move on to the next topic or learn more." 【0706】 Step 6: 【0707】 After the meeting ends, the server automatically generates meeting minutes along with a report containing participant sentiment data. This report includes improvement suggestions based on the analysis and is delivered to users via email or a dedicated app. 【0708】 Step 7: 【0709】 Users will use this report to plan their next meeting. Based on the improvement suggestions, they will readjust the agenda and proceedings to prepare for the meeting to maximize its effectiveness. The server will also reschedule the next meeting and notify relevant parties of the details. 【0710】 (Example 2) 【0711】 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". 【0712】 In today's business environment, many meetings are not conducted efficiently or effectively. While it's crucial to schedule meetings appropriately considering participants' availability, set agendas relevant to the meeting content, and accurately record what is said, these are often not done properly. Furthermore, understanding participants' emotional states and adjusting meetings accordingly is also difficult. Improving these conditions and enhancing the quality and efficiency of meetings is essential. 【0713】 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. 【0714】 In this invention, the server includes means for analyzing participants' schedule information and proposing an optimal meeting time; means for automatically generating and sharing meeting agendas according to the purpose using natural language generation methods; means for recognizing speech during the meeting, converting it to text, and automatically generating meeting minutes; means for analyzing participants' audio and video data and evaluating their emotional state; and means for providing suggestions for adjusting the meeting progress based on this emotional state. As a result, meetings can be efficiently planned based on participants' schedules and conducted in a way that reflects their emotions, thereby improving the quality and efficiency of meetings. 【0715】 "Analyzing participant schedule information" is the process of collecting schedule data for each individual attending a meeting and identifying the most suitable date and time for the meeting. 【0716】 "Suggesting the optimal meeting time" involves analyzing collected participant schedule data to determine and present dates that are available to the majority of participants. 【0717】 "Automatically generating meeting agendas using natural language generation techniques" refers to the process of automatically creating topics and items tailored to the purpose of a meeting by utilizing generative AI technology. 【0718】 "Sharing with participants" refers to the act of distributing generated information and data to those attending a meeting, thereby ensuring that the information is shared among them. 【0719】 "Speech recognition and text conversion" is a process that analyzes speech spoken during a meeting in real time and converts it into human-readable text data. 【0720】 "Automatically generating meeting minutes" refers to the process of organizing and saving text data generated during a meeting as an official report or record. 【0721】 "Analyzing audio and video data to evaluate emotional state" refers to the process of automatically determining the psychological or emotional state of participants from the audio and video recorded during the meeting. 【0722】 "Providing suggestions for adjusting meeting proceedings based on emotional states" refers to the act of using analyzed emotional data to propose improvements to meeting procedures and methods. 【0723】 This invention is a meeting support system that utilizes advanced data analysis technology and generative AI models to improve the user's meeting experience. The system mainly consists of a server, terminals, and an emotion analysis engine. 【0724】 The server collects user schedule information. Specifically, it analyzes user calendar data using APIs from common scheduling software. This allows it to calculate the optimal meeting time and propose it to each participant. Meeting agendas, tailored to the purpose of the meeting, are created by inputting prompts into a generative AI model that uses natural language generation technology. For example, using the prompt "Please list the main topics to be discussed at the next project meeting," the server selects and shares appropriate agenda items from the output generated by the AI. 【0725】 The device analyzes each user's voice and video in real time during a meeting. It uses an industry-standard speech-to-text engine for speech recognition, instantly transcribing spoken content into text. Furthermore, it incorporates an emotion analysis engine, analyzing emotional data from the voice and video to understand the user's psychological state. Based on this analysis, it provides real-time alerts and suggestions regarding meeting progress, supporting users in conducting meetings more smoothly. Similarly, it generates and provides users with a comprehensive meeting report that considers the frequency and pace of speech based on the emotional data. 【0726】 This system allows users to conduct meetings in a planned and flexible manner. For example, if many participants react negatively to a particular agenda item during a meeting, an alert is immediately displayed to draw attention to the issue, allowing for adjustments to the meeting's direction. After the meeting, it is also possible to consider specific improvement measures for the next meeting based on the data obtained from the comprehensive report. 【0727】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0728】 Step 1: 【0729】 The server retrieves schedule information from the user's scheduling software. The input is the user's calendar API, and the output is the user's schedule data. The server analyzes this data to calculate the optimal meeting time that all participants can attend. The calculated date and time are then notified to each user. 【0730】 Step 2: 【0731】 The server uses a generative AI model to automatically generate meeting agendas. The input here is a prompt, for example, "Please list three main topics for the next new product development meeting." The output is an agenda list generated by the AI, which is shared with each participant. 【0732】 Step 3: 【0733】 The terminal collects user audio in real time during meetings and transcribes it using a speech recognition engine. Audio data is the input, and the output is spoken text data. The terminal sends this text to a server to support the automatic generation of meeting minutes. 【0734】 Step 4: 【0735】 The terminal uses the user's voice and video data to evaluate their emotional state using an emotion analysis engine. The input is the voice and video data recorded during the meeting, and the output is the result of the emotional state evaluation. The terminal sends this result to a server, which is used to provide the user with suggestions regarding the progress of the meeting. 【0736】 Step 5: 【0737】 The server stores voice text and sentiment data obtained during the meeting and analyzes it in real time. The analysis generates specific suggestions and alerts regarding the meeting's progress, which are then displayed to the user. The input in this process is the entire dataset accumulated during the meeting, while the output is the suggestions for meeting progress. 【0738】 Step 6: 【0739】 After the meeting concludes, the server automatically generates a comprehensive report based on all the data. Inputs include voice-to-text, sentiment analysis results, and proposal history. The output is a detailed report covering the meeting's specifics, which is distributed to participants. This allows users to identify areas for improvement for future meetings. 【0740】 (Application Example 2) 【0741】 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". 【0742】 In team meetings at physical stores, the emotional state of participants can significantly impact the progress and outcome of the meeting. However, the lack of a system to appropriately interpret emotions from comments and facial expressions during the meeting and respond immediately can hinder communication and meeting efficiency. Systems and methods to address this challenge are needed. 【0743】 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. 【0744】 In this invention, the server includes means for analyzing participants' schedule information and proposing the optimal meeting time, means for automatically generating meeting agendas according to the purpose and sharing them with participants, and means for analyzing participants' emotional states in real time and displaying warnings when negative reactions are detected. This makes it possible to accurately grasp the emotional states of meeting participants, facilitate smooth meeting progress, and improve the quality of discussions. 【0745】 "Schedule information" refers to data regarding the schedules and available time slots of meeting participants. 【0746】 "Meeting agenda" refers to the subject or topic to be discussed at a meeting. 【0747】 "Speech recognition" is a technology that converts speech into text data that a computer can understand. 【0748】 "Meeting minutes" are documents that organize the statements and decisions made during a meeting into text format. 【0749】 "Action items" refer to the actions or tasks that meeting participants should take next. 【0750】 "Real-time analysis" refers to processing and analyzing information at the very moment an event occurs. 【0751】 "Emotional state" refers to the psychological state of meeting participants and can be interpreted from their voice and facial expressions. 【0752】 A "warning message" is a message that is displayed to alert the user when certain conditions are met. 【0753】 An "improvement suggestion" is a specific proposal or opinion offered after analyzing the current situation, aimed at achieving better results. 【0754】 The system for implementing this invention consists of a server, a smart device (terminal), and an emotion analysis engine. The server analyzes the schedule information of meeting participants and proposes the optimal meeting time and agenda. The participants' smart devices are equipped with cameras and microphones, capturing audio and video in real time, which are then analyzed by the emotion analysis engine. This emotion data is transmitted to the server, enabling responses that correspond to the emotional state during the meeting. 【0755】 Specifically, the system uses the Google Cloud Speech-to-Text API to convert speech to text and the Microsoft Azure Emotion API to analyze participants' emotional states in real time. Additionally, Apache Kafka is used to process large amounts of speech and emotional data in real time. This allows for a warning to be displayed on the device if negative emotions are detected in a participant. 【0756】 For example, in a staff meeting at a retail store, if a staff member expresses dissatisfaction during a discussion about promotional strategies, an alert based on emotional data will appear on their smart device, recommending a review of the agenda or the introduction of breaks in the meeting. After the meeting, improvement suggestions based on the analysis of emotional data will be provided along with the generated meeting minutes. 【0757】 Examples of prompts for a generative AI model are as follows: 【0758】 "Please develop an idea for a meeting assistant app that provides feedback based on the emotional state of staff during a meeting. The device used would be a smartphone or smart glasses, and it would provide alerts to participants in real time based on emotion analysis results." 【0759】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0760】 Step 1: 【0761】 The server receives participant schedule information and stores it in a database. It then analyzes the received schedule information and runs an algorithm to suggest the optimal meeting time. The input is participant schedule data, and the output is a suggestion for the optimal meeting time. 【0762】 Step 2: 【0763】 The server automatically generates an agenda based on the meeting's objectives. Using objective information obtained from participants as input, it outputs an agenda designed to maximize the meeting's effectiveness. This agenda information is sent to the terminal and shared with the participants. 【0764】 Step 3: 【0765】 The device captures audio and video during the meeting. Using the built-in microphone and camera, it collects participants' audio and video data in real time. Both of these data are sent to a server for processing. 【0766】 Step 4: 【0767】 The server converts the received audio data into text using the Google Cloud Speech-to-Text API. The input is audio data, and the output is its text representation. This generates meeting minutes. 【0768】 Step 5: 【0769】 The device uses the Microsoft Azure Emotion API to perform emotion analysis on participants' video data. The input is video data, and the analysis results in an output of emotional state (positive, negative, etc.). If a negative emotion is detected, a warning will be displayed on the device. 【0770】 Step 6: 【0771】 After the meeting concludes, the server integrates audio and sentiment data to generate a comprehensive meeting report. Inputs include transcribed meeting minutes and analyzed sentiment states, while output is a final report containing improvement suggestions for participants. The generated report is distributed to participants to help them prepare for future meetings. 【0772】 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. 【0773】 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. 【0774】 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 robot 414. 【0775】 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. 【0776】 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. 【0777】 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. 【0778】 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. 【0779】 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. 【0780】 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." 【0781】 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. 【0782】 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. 【0783】 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. 【0784】 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. 【0785】 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. 【0786】 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. 【0787】 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 this memory. 【0788】 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. 【0789】 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. 【0790】 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. 【0791】 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. 【0792】 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 to be incorporated by reference. 【0793】 The following is further disclosed regarding the embodiments described above. 【0794】 (Claim 1) 【0795】 A method for analyzing participants' schedule information and suggesting the optimal meeting time, 【0796】 A means of automatically generating meeting agendas tailored to the purpose and sharing them with participants, 【0797】 A method for recognizing speech during a meeting, converting it to text, and automatically generating meeting minutes, 【0798】 A means of organizing the generated meeting minutes and notifying participants, 【0799】 A means of automatically extracting and notifying participants of action items, 【0800】 A method to automatically schedule the next meeting after the current meeting, 【0801】 A means of analyzing past meeting data and generating improvement suggestions, 【0802】 A system that includes this. 【0803】 (Claim 2) 【0804】 The system according to claim 1, which monitors the progress of a meeting in real time and displays reminders based on the agenda. 【0805】 (Claim 3) 【0806】 The system according to claim 1, which analyzes the voices of participants and provides a report on the frequency of their speech and the pace of the meeting. 【0807】 "Example 1" 【0808】 (Claim 1) 【0809】 A device that analyzes participants' schedule information and suggests the optimal meeting time, 【0810】 A device that automatically generates meeting agendas tailored to the purpose using an AI model and shares them with participants, 【0811】 A device that recognizes speech during a meeting, converts it to text, and automatically generates meeting minutes, 【0812】 A device that organizes the generated meeting minutes and notifies the participants, 【0813】 A device that automatically extracts and notifies participants of action items, 【0814】 A device that automatically schedules the next meeting after the previous one, 【0815】 A device that analyzes past meeting data and generates improvement suggestions, 【0816】 A device that uses an AI agent to manage time and present topics, 【0817】 A system that includes this. 【0818】 (Claim 2) 【0819】 The system according to claim 1, which transcribes participants' voices into text in real time, sends them to a server, and generates meeting minutes. 【0820】 (Claim 3) 【0821】 The system according to claim 1, which analyzes the frequency of participants' contributions and the pace of the meeting and provides the results in a report format. 【0822】 "Application Example 1" 【0823】 (Claim 1) 【0824】 A method for analyzing participants' schedule information and suggesting the optimal meeting time, 【0825】 A means of automatically generating meeting agendas tailored to the purpose and sharing them with participants, 【0826】 A means of recognizing speech during a meeting, converting it to text, and automatically generating meeting minutes, 【0827】 A means of organizing the generated meeting minutes and notifying participants, 【0828】 A means of automatically extracting and notifying participants of action items, 【0829】 A method for automatically scheduling the next meeting after the current one, 【0830】 A means of analyzing past meeting data and generating improvement suggestions, 【0831】 A means to automate and optimize community meetings specifically for smart city regional management operations, 【0832】 A means of providing calendar-linked notification features for community leaders, 【0833】 A means of utilizing generative AI models to creatively generate meeting agendas, 【0834】 A system that includes this. 【0835】 (Claim 2) 【0836】 The system according to claim 1, which monitors the progress of a meeting in real time and displays reminders based on the agenda. 【0837】 (Claim 3) 【0838】 The system according to claim 1, which analyzes the voices of participants and provides a report in which the frequency of their speech and the pace of the meeting progress. 【0839】 "Example 2 of combining an emotion engine" 【0840】 (Claim 1) 【0841】 A method for analyzing participants' schedule information and suggesting the optimal meeting time, 【0842】 A means of automatically generating meeting agendas tailored to the purpose using natural language generation methods and sharing them with participants, 【0843】 A method for recognizing speech during a meeting, converting it to text, and automatically generating meeting minutes, 【0844】 A means of organizing the generated meeting minutes and notifying participants, 【0845】 A means of analyzing participants' audio and video data to evaluate their emotional state, 【0846】 A means of providing suggestions for adjusting the meeting proceedings based on this emotional state, 【0847】 A method to automatically schedule the next meeting after the current meeting, 【0848】 A means of analyzing past meeting data and generating improvement suggestions, 【0849】 A system that includes this. 【0850】 (Claim 2) 【0851】 The system according to claim 1, which monitors the progress of a meeting in real time and displays reminders based on the meeting content using a generative AI method. 【0852】 (Claim 3) 【0853】 The system according to claim 1, which analyzes participants' voice data and provides a report in which the frequency of speech, the pace of the meeting, and emotional changes are recorded. 【0854】 "Application example 2 when combining with an emotional engine" 【0855】 (Claim 1) 【0856】 A method for analyzing participants' schedule information and suggesting the optimal meeting time, 【0857】 A means of automatically generating meeting agendas tailored to the purpose and sharing them with participants, 【0858】 A method for recognizing speech during a meeting, converting it to text, and automatically generating meeting minutes, 【0859】 A means of organizing the generated meeting minutes and notifying participants, 【0860】 A means of automatically extracting and notifying participants of action items, 【0861】 A method to automatically schedule the next meeting after the current meeting, 【0862】 A means of analyzing the emotional state of participants in real time and displaying a warning if a negative reaction is detected, 【0863】 A means of analyzing past meeting data and sentiment data to generate improvement suggestions, 【0864】 A system that includes this. 【0865】 (Claim 2) 【0866】 The system according to claim 1, which monitors the progress of a meeting in real time and displays reminders based on the agenda. 【0867】 (Claim 3) 【0868】 The system according to claim 1, which analyzes the voices of participants and provides a report on the frequency of their speech and the pace of the meeting. [Explanation of symbols] 【0869】 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 method for analyzing participants' schedule information and suggesting the optimal meeting time, A means of automatically generating meeting agendas tailored to the purpose and sharing them with participants, A method for recognizing speech during a meeting, converting it to text, and automatically generating meeting minutes, A means of organizing the generated meeting minutes and notifying participants, A means of automatically extracting and notifying participants of action items, A method to automatically schedule the next meeting after the current meeting, A means of analyzing past meeting data and generating improvement suggestions, A system that includes this. [Claim 2] The system according to claim 1, which monitors the progress of a meeting in real time and displays reminders based on the agenda. [Claim 3] The system according to claim 1, which analyzes the voices of participants and provides a report in which the frequency of their speech and the pace of the meeting progress.

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