system

Abstract

Provide a system. The present invention includes: a means for receiving a theme and purpose of a meeting and automatically generating an agenda based on the theme and purpose; A means to receive a list of participants, check the schedules of each participant, select a common free time, and send a notification; A means to use AI models to generate real-time comments, discussion summaries and closing statements during meetings; A way to convert meeting audio into text, extract key points and create meeting minutes, A means to distribute the created minutes to participants by email, A system including:

Description

[Technical Field]

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

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

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

[0004] In recent years, there has been a demand for more efficient meetings, but the entire process from preparing for a meeting to running it and following up after it has ended requires a great deal of time and effort. Efficiency is particularly challenging in processes such as creating an agenda, checking participants' schedules, encouraging participants to speak during the meeting, and creating minutes. For this reason, there is a growing need for a system that can integrate and automate these tasks. [Means for solving the problem]

[0005] The present invention provides a system that receives a meeting's theme and purpose and automatically generates an agenda based on the theme and purpose. It also includes a means for receiving a list of participants, checking each participant's schedule using a calendar API, selecting a common free time, and sending a meeting notification. During the meeting, an AI model is used to generate comments, a discussion summary, and a closing statement in real time, which are provided to the facilitator. The system also includes a means for converting the meeting audio into text, extracting key points, creating minutes, and distributing the minutes to participants via email.

[0006] A "theme" is the main topic or purpose to be discussed at a meeting.

[0007] An "agenda" is a pre-planned document that outlines the topics and order of discussion for a meeting.

[0008] A "participant list" is a list of people who plan to attend a meeting.

[0009] A "schedule" is a timetable of planned activities or events.

[0010] A "Calendar API" is an interface that allows software applications to access, retrieve, and manipulate a user's calendar information.

[0011] "Common free time" refers to a time period when all participants of the meeting are available to attend.

[0012] "Notification" is the activity of informing participants of important information such as the date, time, and location of the meeting.

[0013] An "AI model" is a computational model that uses artificial intelligence algorithms and programs to perform specific tasks.

[0014] "Speech comments" are prompts used by the facilitator or other participants to encourage speaking during a meeting.

[0015] A "discussion summary" is a concise summary of the contents of the meeting.

[0016] "Closing content" is a statement that marks the end of the meeting and informs participants of the results of the meeting and next steps.

[0017] "Convert to text" is the process of converting voice data into text information.

[0018] "Key points" are matters or key points that deserve particular attention during a meeting.

[0019] "Minutes" are official documents that record what was discussed at a meeting.

[0020] "Mail delivery" refers to the process of sending information via electronic mail. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0026] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0027] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] The present invention is a system that can consistently and efficiently carry out the entire process from preparation to progress of a meeting, as well as follow-up after the meeting has ended. A specific embodiment of this system will be described below.

[0043] Agenda creation

[0044] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[0045] Schedule confirmation and meeting notifications

[0046] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0047] Conference facilitator support

[0048] The server uses an AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[0049] Minutes creation

[0050] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. The generated minutes are then sent to the user's device for review.

[0051] Email distribution of meeting minutes

[0052] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0053] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and all participants can share information smoothly.

[0054] The processing flow will be explained below.

[0055] Program processing steps

[0056] Pre-meeting preparation

[0057] Step 1:

[0058] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[0059] Step 2:

[0060] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[0061] Step 3:

[0062] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[0063] Step 4:

[0064] The user inputs a list of participants and registers them in the system.

[0065] Step 5:

[0066] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[0067] Step 6:

[0068] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[0069] Step 7:

[0070] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[0071] Meeting progress

[0072] Step 8:

[0073] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[0074] Step 9:

[0075] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[0076] Step 10:

[0077] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[0078] Post-meeting process

[0079] Step 11:

[0080] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[0081] Step 12:

[0082] The server uses natural language processing technology to extract important points from the converted text, organizes the main points, and creates minutes.

[0083] Step 13:

[0084] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[0085] Step 14:

[0086] The user approves the confirmed minutes.

[0087] Step 15:

[0088] The server distributes the final confirmed minutes by email based on the participant list.

[0089] By following these steps, a system can be created that can efficiently execute the entire process from preparing for a meeting to conducting and following up on it.

[0090] Example 1

[0091] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0092] Preparing for, conducting, and following up on a meeting requires a lot of time and effort. Creating an agenda, coordinating participants' schedules, encouraging participants to speak during the meeting, and creating minutes are often done manually, resulting in inefficiencies. Furthermore, if these tasks are not performed thoroughly, the quality of the meeting may decline and its effectiveness may be impaired. This invention aims to solve these problems by providing a system that automates and streamlines the entire process of a meeting.

[0093] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0094] In this invention, the server includes means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose, means for receiving a participant list, checking the schedules of each participant, selecting a common free time and sending a notification, means for generating remarks, comments, a discussion summary and closing content in real time using a generative AI model during the meeting, means for converting the speech of the meeting into text and extracting important points to create minutes, and means for distributing the created minutes to participants by email. This makes it possible to consistently streamline the processes of preparing, conducting and following up on a meeting.

[0095] "Conference theme and objectives" refers to the central topics or subjects to be discussed at the conference and the purpose for which the conference is being held.

[0096] An "agenda" is a document that lists the items or topics to be discussed at a meeting and the order in which they will be discussed.

[0097] "Participant List" means a list of names and contact information for people who will be attending a meeting.

[0098] "Schedule" refers to the schedule information and free time of each participant.

[0099] "Notification" refers to a message sent to inform participants of information such as the date, time, location, and content of a meeting.

[0100] "Generative AI models" refer to algorithms or systems that use artificial intelligence to generate comments, discussion summaries, and closing statements during meetings in real time.

[0101] "Meeting audio" refers to the content of conversations and discussions that occur during a meeting.

[0102] "Convert to text" refers to the process of converting audio data into text data using language processing techniques.

[0103] "Key points" refer to the main points and conclusions extracted from the discussions during the meeting.

[0104] "Minutes" refers to a document that records the contents of discussions, important remarks, decisions, etc. that took place during a meeting.

[0105] "Delivery by email" refers to the act of sending specific information to a designated recipient using email.

[0106] "Schedule Management API" means an application programming interface used to obtain schedules and availability of participants.

[0107] The present invention is a system for efficiently preparing for a meeting, conducting the meeting, and following up after the meeting. This system operates mainly by exchanging data between a server, terminals, and users. Specific embodiments of the present invention are described below.

[0108] First, the user inputs the topic and purpose of the meeting. For example, prompts such as "Topic: Project progress" or "Objective: Decide next steps" are entered. This input is entered as text information into a form on the user's device and sent to the server by pressing the send button.

[0109] The server then refers to its internal database based on the theme and purpose provided by the user to select relevant topics. This involves searching for relevant data using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" from past data related to the theme "Project Progress." The server then uses an AI model to automatically generate an agenda and sends it to the user's device. This process uses a template-based approach to generate the agenda.

[0110] Next, the user checks the contents of the agenda and makes corrections or additional comments as necessary. This checking is done by checking the contents of the agenda displayed on the terminal.

[0111] After that, the user uploads the list of participants for the meeting. This information is provided via a CSV file or a web form. The server receives the participant list and uses a schedule management API to check each participant's schedule. For example, it uses the Google® Calendar API to obtain each participant's free time and selects a common free time based on that information.

[0112] The selected meeting time is sent to all participants as a notification by the server, which includes the date, time, location and agenda of the meeting. This notification is sent using a mail server.

[0113] During the meeting, the server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time. For example, comments such as "Please tell us your opinion on this point" are generated to support the progress of the meeting. The server also monitors the progress of the discussion and provides summaries and closing comments at appropriate times, thereby improving the efficiency of the meeting.

[0114] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology. Specifically, it uses the Google Speech-to-Text API to convert the audio data into text. It then uses natural language processing technology to extract key points and automatically generate minutes. These minutes are then sent to the user's device.

[0115] Finally, the server distributes the generated minutes to the participants by email. For example, minutes containing the meeting schedule and content, agenda, and decisions are sent to the participants' mailboxes.

[0116] In this way, the system of the present invention consistently improves efficiency from meeting preparation to progress and follow-up, making the entire business process smoother.

[0117] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0118] Step 1:

[0119] The user inputs the topic and purpose of the meeting.

[0120] Input: Theme "Project Progress", Objective "Determine next steps"

[0121] Output: The input data is sent to the server

[0122] Specific operation: The user enters the topic and purpose into the form on the terminal and presses the submit button, which sends the data to the server.

[0123] Step 2:

[0124] The server consults an internal database based on the received theme and purpose.

[0125] Input: Theme and Objective Data

[0126] Output: Related topics

[0127] Specific operation: The server uses input data as a trigger to search the database for related topics using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" as topics related to "Project Progress."

[0128] Step 3:

[0129] The server automatically generates an agenda based on relevant topics.

[0130] Input: Related topics

[0131] Output: Auto-generated agenda

[0132] How it works: Using an AI model, the extracted topics are incorporated into a template to automatically generate an agenda, which is then sent to the user's device.

[0133] Step 4:

[0134] The user checks the contents of the agenda.

[0135] Input: Auto-generated agenda

[0136] Output: Confirmed agenda, comments or corrections

[0137] Specific operation: The user checks the contents of the agenda displayed on the terminal and makes corrections or additional comments if necessary.

[0138] Step 5:

[0139] The user uploads the participant list.

[0140] Input: Participant list (e.g., CSV file)

[0141] Output: The participant list is sent to the server

[0142] Specific operation: The user selects the participant list from the terminal and presses the upload button to send it to the server.

[0143] Step 6:

[0144] The server uses a schedule management API to check the schedule of each participant.

[0145] Input: Participant list

[0146] Output: Free time for each participant

[0147] Specific operation: Using the Google Calendar API, etc., a request is sent to check the free time of participants. The server aggregates the obtained free time and finds common free time.

[0148] Step 7:

[0149] The server selects the best meeting time and sends a notification.

[0150] Input: Availability of each participant

[0151] Output: Meeting notification

[0152] Specific operation: Calculates common free time based on the obtained free time information and selects the optimal meeting time. Sends a notification containing the selected meeting time and agenda to all participants using a mail server.

[0153] Step 8:

[0154] The server uses the generative AI model to generate comments in real time during the meeting.

[0155] Input: Meeting progress

[0156] Output: Comment

[0157] How it works: Using a generative AI model, it generates comments in real time, allowing the facilitator to encourage discussion.

[0158] Step 9:

[0159] The server generates a discussion summary and closing message.

[0160] Input: Meeting progress

[0161] Output: Summary and closing message

[0162] What it does: It uses natural language processing technology to extract key points and conclusions, and generates summaries and closing messages at appropriate times during the meeting.

[0163] Step 10:

[0164] The server receives the audio files of the conference and uses speech recognition technology to convert the speech to text.

[0165] Input: Meeting audio file

[0166] Output: Text data

[0167] Specific operation: After the meeting ends, the meeting audio is uploaded to the server and the audio data is converted to text using the Google Speech-to-Text API or similar.

[0168] Step 11:

[0169] The server extracts important points and creates minutes.

[0170] Input: Text data

[0171] Output:Minutes

[0172] Specific operation: Uses natural language processing technology to extract key points from text data and automatically generate meeting minutes.

[0173] Step 12:

[0174] The server transmits the generated minutes to the user's terminal.

[0175] Input: Minutes

[0176] Output: Confirmed transcript

[0177] Specific operation: The automatically generated minutes are sent to the user's device and the user confirms them.

[0178] Step 13:

[0179] The server distributes the confirmed minutes to the participants by email.

[0180] Input: Confirmed minutes

[0181] Output: Delivered minutes

[0182] Specific operation: The confirmed minutes are distributed to all participants via the mail server.

[0183] (Application example 1)

[0184] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0185] Currently, there is no system in place that can efficiently manage the progress of work within the factory, from preparing for meetings to proceeding with them and following up after they have been completed. In particular, it is difficult for each worker and manager to grasp the work situation in real time and receive appropriate instructions, and there is a problem that important incidents are not recorded and shared on the spot. This hinders work efficiency and the effective progress of meetings.

[0186] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0187] In this invention, the server includes means for receiving the theme and purpose of a meeting and automatically generating an agenda based on the theme and purpose, means for receiving a list of participants, checking each participant's schedule, selecting a common free time and sending a notification, means for generating comments, a discussion summary, and closing content in real time using a generative AI model during the meeting, means for converting the meeting audio into text and extracting important points to create minutes, means for distributing the created minutes to participants by email, means for checking the progress of work in the factory in real time and providing instructions for the next step with audio and visual information, and means for recording and sharing important incidents on the spot using a smart device, thereby enabling more efficient work in the factory and more effective meetings.

[0188] An "agenda" is a plan that summarizes the topics and progress of a meeting or discussion.

[0189] A "generative AI model" is a software system that uses artificial intelligence techniques to analyze data and automatically generate sentences and responses.

[0190] "Speech comments" are comments that include suggestions or questions to assist participants in making statements during a meeting.

[0191] A "discussion summary" is a concise summary of the discussions that took place during the meeting.

[0192] "Closing content" is content that summarizes the discussion and provides next steps at the end of the meeting.

[0193] "Speech-to-text" is the process of converting spoken words into written information using speech recognition technology.

[0194] Minutes are a written record of what was said at a meeting that can be referenced later.

[0195] "Inside the factory" refers to the interior of a building or facility where manufacturing operations take place.

[0196] "Progress of work" is information that indicates the current achievement level and progress of work or tasks.

[0197] "Guiding with audio and visual information" means providing instructions and guidance using audio and visual methods.

[0198] "Smart devices" generally refer to electronic devices that can connect to the Internet and have a variety of functions, such as smartphones and smart glasses.

[0199] "Incident" means an unexpected occurrence or problem, including any particularly problematic situation or accident.

[0200] "Real-time" refers to processing or operations that are performed in synchronization with actual time.

[0201] The present invention is a system that can efficiently and consistently manage the progress of work in a factory, as well as the preparation for and progress of meetings, and follow-up after the meetings have ended. Specific embodiments of this system will be described below.

[0202] Agenda creation

[0203] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Agenda A," "Agenda B," and "Agenda C" are automatically generated.

[0204] Schedule confirmation and meeting notifications

[0205] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0206] Conference facilitator support

[0207] The server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[0208] Minutes creation

[0209] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. This process uses technologies such as Google's speech recognition API. The generated minutes are then sent to the user's device for review.

[0210] Email distribution of meeting minutes

[0211] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0212] Real-time confirmation and instructions for factory operations

[0213] The server allows users to check the progress of work in real time through smart devices (e.g., smart glasses) worn in the factory. This allows instructions for the next step to be given through voice and visual information, improving work efficiency. For example, when a specific process is completed, an automatic instruction such as "Start process X next" is issued.

[0214] Recording and sharing critical incidents

[0215] Users can use their smart devices to record important incidents in real time and send them to a server. The server then immediately shares the received incident information with relevant personnel and managers. For example, when a facility failure is detected, on-site workers can take a picture of the faulty area through smart glasses and upload it to the server, enabling a prompt response.

[0216] Prompt Sentence Examples

[0217] Below are some examples of specific prompt sentences.

[0218] "Prepare for a meeting to decide next steps for project progress. The participants are Person A and Person B. Check your mutual availability and communicate an appropriate meeting time."

[0219] In this way, by using the system of the present invention, it is possible to improve the efficiency of work within a factory and to conduct meetings effectively.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Step 1:

[0222] The server receives the meeting topic and purpose from the user. For example, the topic and purpose can be "Project Progress" and "Determine Next Steps." Based on this input, the server references its internal database and selects relevant topics. This data reference process is performed by searching the database for past meeting records and standard agenda lists to extract relevant topics. The output is an automatically generated agenda.

[0223] Step 2:

[0224] The server sends the generated agenda to the user's device. The user checks the agenda on the device and makes any necessary modifications. During this modification process, the user adds additional agenda items or deletes unnecessary items. The modified agenda is then resent from the device to the server, and the final agenda is confirmed. The input is the generated agenda, and the output is the final confirmed agenda.

[0225] Step 3:

[0226] The server receives the list of participants and checks each participant's schedule. This check process involves using a calendar API to obtain participants' free time slots. The server then saves the obtained schedule information in a database and compares the schedules of all participants to find common free time slots. The output is the optimal meeting time.

[0227] Step 4:

[0228] The server creates a meeting notice based on the optimal meeting time and the confirmed agenda. The generated meeting notice includes the meeting date, time, location, and agenda. This meeting notice is sent to participants via email or calendar invitation. The input is the optimal meeting time and agenda, and the output is the meeting notice.

[0229] Step 5:

[0230] During the meeting, the server uses a generative AI model to generate comments, discussion summaries, and closing statements in real time. This information is generated at the appropriate time while monitoring the progress of the meeting and displayed on the facilitator's device. Users can proceed with the meeting while referring to the displayed information. The input is the audio data and progress of the meeting, and the output is comments, discussion summaries, and closing statements.

[0231] Step 6:

[0232] The server receives the audio file of the meeting and converts it into text using speech recognition technology. During the conversion process, the audio data is analyzed using Google's speech recognition API and converted into text information. Key points are extracted from this text data using natural language processing technology. The extracted key points are organized to create minutes of the meeting and sent to the user's device. The input is the audio file of the meeting, and the output is the generated minutes.

[0233] Step 7:

[0234] The server distributes the confirmed minutes by email based on the participant list. In this distribution process, the generated minutes are formatted as the body of an email and sent to the participants' email addresses. This allows participants to review the contents of the meeting and take further action. The input is the generated minutes, and the output is the email in which the minutes were distributed.

[0235] Step 8:

[0236] The server allows users to check the progress of work in real time through smart devices worn in the factory. In this process, the server analyzes data sent from the smart device in real time and provides instructions for the next step through audio and visual information. For example, when a specific process is completed, an instruction such as "Please start process X next" is automatically generated and displayed on the user's device. The input is data from the smart device, and the output is the generated instruction.

[0237] Step 9:

[0238] Users use smart devices to record important incidents in real time and send them to a server. In this process, users use their smart devices to record images and text of incidents and upload them to the server. The server analyzes the received incident information and immediately shares it with relevant personnel and managers. The input is the incident information recorded by the user, and the output is the analyzed incident information and its sharing.

[0239] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0240] The present invention is a system that can consistently and efficiently handle everything from preparing for a meeting to proceeding with it and follow-up after it has ended, and it also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of this system are described below.

[0241] Agenda creation

[0242] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[0243] Schedule confirmation and meeting notifications

[0244] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0245] Supporting meeting progress with an emotion engine

[0246] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[0247] Conference facilitator support

[0248] The server monitors the progress of the meeting and presents comments to the facilitator at appropriate times. Using data from the emotion engine, it generates comments that reflect the user's emotional state. For example, it generates specific, positive comments such as, "Please tell us more about your opinion."

[0249] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing of the discussion are generated in real time as the discussion progresses and provided to the facilitator.

[0250] Minutes creation

[0251] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[0252] Email distribution of meeting minutes

[0253] The server distributes the confirmed minutes by email based on the participant list. By receiving the email, participants can reconfirm the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions are distributed.

[0254] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and the meeting can be optimally progressed according to the emotional state of the user.

[0255] The processing flow will be explained below.

[0256] Program processing steps

[0257] Pre-meeting preparation

[0258] Step 1:

[0259] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[0260] Step 2:

[0261] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[0262] Step 3:

[0263] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[0264] Step 4:

[0265] The user inputs a list of participants and registers them in the system.

[0266] Step 5:

[0267] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[0268] Step 6:

[0269] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[0270] Step 7:

[0271] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[0272] Meeting progress

[0273] Step 8:

[0274] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[0275] Step 9:

[0276] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[0277] Step 10:

[0278] The server uses an emotion engine to recognize the user's emotions and adjusts the comments, discussion summary, and closing statement in real time. For example, if the user is frustrated, the server generates a comment such as "Let's take a short break and resume."

[0279] Step 11:

[0280] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[0281] Step 12:

[0282] The terminal (facilitator) checks the summary and closing content provided by the server and uses them at the appropriate time.

[0283] Post-meeting process

[0284] Step 13:

[0285] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[0286] Step 14:

[0287] The server uses natural language processing technology to extract important points from the converted text and create minutes, while an emotion engine also reflects the user's emotional state as information.

[0288] Step 15:

[0289] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[0290] Step 16:

[0291] The user approves the confirmed minutes.

[0292] Step 17:

[0293] The server distributes the final confirmed minutes by email based on the participant list.

[0294] In this way, by using the system of the present invention, the entire process from preparing for a meeting to conducting it and following up can be carried out efficiently, and the optimal progress can be achieved according to the emotional state of the user.

[0295] Example 2

[0296] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0297] In conventional conferencing systems, preparation, progress, and follow-up of meetings were carried out separately, making efficient operation difficult. Furthermore, it was not possible to adjust the progress of the meeting by taking into account the user's emotional state, which made it easy for participants to feel fatigued or stressed. Furthermore, it was difficult to generate summaries of comments and discussions in real time, making it difficult to conduct meetings quickly and accurately.

[0298] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose; means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification; means for generating remarks, comments, a discussion summary, and closing content in real time using a generative AI model during the meeting; means for converting the meeting audio into text, extracting important points, and creating minutes; means for distributing the created minutes to participants by email; and means including an emotion engine that recognizes emotions from the user's facial expressions and voice during the meeting and adjusts the progress of the meeting based on the recognized emotions. This not only enables consistent and efficient preparation, progress, and follow-up of the meeting, but also enables optimal progress according to the user's emotional state.

[0299] "Theme" refers to the subject matter of the conference or the issue area that will be the focus of discussion.

[0300] "Purpose" refers to the specific goals or results that the meeting aims to achieve.

[0301] An "agenda" refers to a list of topics or items to be discussed at a meeting.

[0302] "Participant List" means the list of individuals or entities that will be attending a Conference.

[0303] A "schedule" indicates the schedule and free time of each participant during a specific period.

[0304] "Notification" refers to a means of communication to inform participants of information such as the date, time, location, and agenda of a meeting.

[0305] "Generative AI model" refers to a model that uses artificial intelligence technology to automatically generate text and comments from data.

[0306] A "summary" is a concise summary of what was discussed and said during a meeting.

[0307] "Closing content" refers to the summary and instructions for next steps given at the end of the meeting.

[0308] "Speech recognition technology" refers to technology that converts speech into text.

[0309] "Natural language processing technology" refers to technology for analyzing text data and performing semantic analysis and information extraction.

[0310] An "emotion engine" is a system that recognizes emotions from a user's facial expressions and voice, and generates appropriate comments and actions based on that information.

[0311] "Email" refers to a means for sending and receiving communications over a network such as the Internet.

[0312] The present invention is a system that can consistently and efficiently prepare for, conduct, and follow up on a meeting after it has ended. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of the present invention are described below.

[0313] First, the user inputs the theme and purpose of the meeting into the system. Based on this theme and purpose, the server references its internal database and automatically generates an agenda. For example, if the theme is "New Product Development Meeting" and the purpose is "Schedule Adjustment," the server will automatically generate topics such as "Sharing Market Research Results," "Identifying Technical Issues," and "Promotion Plan." The generated agenda is sent to the user's device, where the user can check the contents.

[0314] The server then receives a list of participants attending the meeting. Based on this list, the server uses a calendar API (e.g., Google Calendar API or Microsoft® Outlook API) to check the schedules of each participant. It then finds common free time slots, selects the optimal meeting time, and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if participants' free time slots are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," the server selects "Tuesday 14:00-15:00" as the common free time slot.

[0315] During the meeting, the server uses an emotion engine to recognize emotions in real time from the user's facial expressions and voice. For example, if a user feels irritated or tired, the server generates a relaxing comment such as "Let's take a short break and resume," and provides it to the facilitator. The emotion engine uses, for example, IBM Watson (registered trademark) Tone Analyzer or Microsoft Azure (registered trademark) Emotion API.

[0316] Furthermore, the server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, positive comments such as "Please tell us more about your opinion" are generated as specific examples based on the user's emotional state. The facilitator checks the comments provided by the server and uses them at the appropriate time. Additionally, a discussion summary and closing statement are generated in real time as the meeting progresses and provided to the facilitator.

[0317] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology (e.g., Google Cloud Speech-to-Text or Amazon Transcribe). It then uses natural language processing technology (e.g., NLTK or spaCy) to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also used in this process, generating minutes that reflect the user's emotional state.

[0318] Finally, the server distributes the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. The minutes include key points such as the meeting schedule and content, agenda, and decisions.

[0319] Prompt Sentence Examples

[0320] 1. Example agenda-building prompts:

[0321] The theme of the meeting is "New Product Development Meeting" and the purpose is "Schedule Adjustment." Please generate a relevant agenda.

[0322] 2. Example prompts for support from the Emotion Engine:

[0323] A user appears frustrated during a meeting. Generate a comment to encourage them to relax.

[0324] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0325] Processing step details

[0326] Step 1:

[0327] The user enters the topic and purpose of the meeting.

[0328] Input: Meeting topic (e.g., "New Product Development Meeting") and purpose (e.g., "Scheduling").

[0329] How it works: The user enters the subject and purpose into the system's input form.

[0330] Output: The input data is sent to the server.

[0331] Step 2:

[0332] The server refers to an internal database, selects relevant topics, and generates an agenda.

[0333] Input: The subject and purpose entered by the user.

[0334] How it works: Based on the theme and purpose, the server queries a database such as MySQL (registered trademark) or PostgreSQL to retrieve related topics. This allows topics such as "Sharing market research results" and "Identifying technical issues" to be selected. An agenda is generated based on this.

[0335] Output: The generated agenda.

[0336] Step 3:

[0337] The server sends the generated agenda to the user's terminal.

[0338] Input: The generated agenda.

[0339] How it works: The server converts the agenda into JSON or XML format and sends it to the user's device.

[0340] Output: The agenda displayed on the user's terminal.

[0341] Step 4:

[0342] The user checks the agenda on the device and makes any necessary corrections.

[0343] Input: User feedback (suggested corrections).

[0344] Action: The user enters any necessary corrections to the confirmed agenda and submits it to the system.

[0345] Output: The revised agenda.

[0346] Step 5:

[0347] The user enters the participant list for the meeting.

[0348] Input: Participant list.

[0349] How it works: A user enters the names and contact information of participants into the system.

[0350] Output: The input data is sent to the server.

[0351] Step 6:

[0352] The server uses the calendar API to check the schedules of participants.

[0353] Input: Participant list.

[0354] How it works: The server uses the Google Calendar API or Microsoft Outlook API to retrieve the schedules of each participant.

[0355] Output: Schedule data for each participant.

[0356] Step 7:

[0357] The server finds common free time and selects the best time to meet.

[0358] Input: Schedule data for each participant.

[0359] How it works: The server parses the schedule data and identifies common free times.

[0360] Output: The best meeting time selected.

[0361] Step 8:

[0362] The server sends a meeting notification to the participants.

[0363] Input: Selected meeting time, location, and agenda.

[0364] How it works: The server generates notifications and sends them to participants via email or a notification system.

[0365] Output: Meeting notification sent to participants.

[0366] Step 9:

[0367] The server activates an emotion engine and recognizes emotions from the facial expressions and voices of users during the meeting.

[0368] Input: Audio and video data during the conference.

[0369] How it works: The server analyzes emotions using an emotion engine (e.g., IBM Watson Tone Analyzer or Microsoft Azure Emotion API), which identifies the user's emotions, such as "irritation" or "tiredness."

[0370] Output: User emotion data.

[0371] Step 10:

[0372] The server generates comments and summaries of the meeting progress in real time based on the emotional data.

[0373] Input: User emotion data and meeting progress data.

[0374] How it works: The server uses a generative AI model to generate a comment, such as "Let's take a short break and then resume."

[0375] Output: Generated comments and summaries.

[0376] Step 11:

[0377] The server presents comments to the facilitator and monitors progress.

[0378] Input: Generated comments and summaries.

[0379] How it works: The server presents comments in real time to the facilitator's device and keeps track of the progress.

[0380] Output: Comments displayed on the facilitator's terminal.

[0381] Step 12:

[0382] The server receives the audio file of the meeting and converts it into text using speech recognition technology.

[0383] Input: Meeting audio file.

[0384] How it works: The server converts speech to text using Google Cloud Speech-to-Text or Amazon Transcribe.

[0385] Output: The converted text data.

[0386] Step 13:

[0387] The server extracts key points and creates minutes.

[0388] Input: Text data.

[0389] How it works: The server uses natural language processing technology (e.g., NLTK or spaCy) to extract important points, organize the main points, and create meeting minutes. It may also use data from the emotion engine.

[0390] Output: The generated transcript.

[0391] Step 14:

[0392] The server will deliver the confirmed minutes to the participants by email.

[0393] Input: Generated meeting minutes and participant list.

[0394] What it does: The server creates emails and distributes the minutes to participants.

[0395] Output: Minutes delivered to participants.

[0396] (Application example 2)

[0397] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0398] While conventional meeting support systems can efficiently prepare, conduct, and follow up on meetings, they are unable to take into account the emotions of participants during the meeting, which can affect participants' motivation and the progress of the meeting. Furthermore, in factory meetings, in particular, many participants are pressed for time and work, making it necessary to further improve the efficiency of meetings. Therefore, there is a need for a system that can recognize the emotional state of participants during a meeting in real time and adjust the progress of the meeting based on that information.

[0399] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically generating an agenda based on the theme and purpose of the meeting, means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification, means for generating remarks, comments, a discussion summary, and closing content in real time using an AI model during the meeting, means for converting the meeting audio into text, extracting important points, and creating minutes, means for distributing the created minutes to participants by email, and means for recognizing the emotions of participants during the meeting and adjusting the progress based on the emotion data. This enables consistent and efficient processing from meeting preparation to progress and follow-up, and further enables the meeting to proceed optimally in accordance with the emotions of the participants.

[0400] A "meeting theme" is a specific topic or agenda that is central to the meeting and determines the purpose and direction of the meeting.

[0401] "Purpose" is the specific goal or intention to be achieved in the meeting, and is the standard for the success of the meeting.

[0402] An "agenda" is a list of topics and schedules for a meeting, and is used to indicate the structure of the meeting.

[0403] A "participant list" is a list of people who will be attending a meeting, and is the basic information for organizing and announcing the meeting.

[0404] "Schedule" is information indicating the participants' schedules and free time, and is used to determine the date and time of the conference.

[0405] "Notification" is a means of communication to inform participants of the date, time, location, agenda, etc. of a meeting.

[0406] An "AI model" is an algorithm or program that uses artificial intelligence, and is a means of automating data analysis and decision-making.

[0407] "Comments" are opinions or responses made during a meeting to encourage discussion.

[0408] A "discussion summary" is a concise summary of the important discussions and conclusions that took place during the meeting, and is used to guide the progress of the meeting and subsequent actions.

[0409] "Closing content" is information about conclusions and next steps that are summarized at the end of the meeting and are used to conclude the meeting.

[0410] "Convert to text" is the process of converting audio data or other forms of information into written information.

[0411] "Key points" are the main issues or decisions to be discussed during the meeting.

[0412] Minutes are documents that record what was said and decided during a meeting, and are used to review the contents of the meeting later.

[0413] "Emotions" refer to the psychological state of participants as perceived from their facial expressions and voices, and affect the progress and atmosphere of the meeting.

[0414] "Emotion data" is data that expresses the emotional state of participants in numerical values ​​or categories, and is used to adjust the progress of the meeting.

[0415] This system aims to support meetings within factories, and can consistently and efficiently handle everything from meeting preparation to progress and follow-up. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting.

[0416] Agenda creation

[0417] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide on Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[0418] Schedule confirmation and meeting notifications

[0419] The server receives the participant list and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds common free time and selects the optimal meeting time. It then sends a notification to the participants based on this information. The notification includes the meeting date, time, location, and agenda. For example, if participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0420] Supporting meeting progress with an emotion engine

[0421] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[0422] Conference facilitator support

[0423] The server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, comments are generated based on the user's emotional state. For example, specific, positive comments such as "Please tell us more about your opinion" are generated. The device (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing statement of the discussion are generated in real time as the meeting progresses and provided to the facilitator.

[0424] Minutes creation

[0425] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[0426] Email distribution of meeting minutes

[0427] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0428] Hardware or software used

[0429] server

[0430] User devices (smartphones, tablets, desktop PCs, etc.)

[0431] Calendar API (e.g. Google Calendar API)

[0432] Emotion recognition library (e.g., EmotionRecognition)

[0433] Speech recognition library (e.g., SpeechRecognition)

[0434] Natural language processing libraries (e.g., NLP)

[0435] Prompt Sentence Examples

[0436] Theme: Project progress

[0437] Objective: Determine next steps

[0438] It analyzes the content of meeting discussions in real time and generates comments such as "Let's take a short break and then resume" if participants seem frustrated.

[0439] In this way, by using this system, meeting support within the factory will be made more efficient and the meeting will proceed in an optimal manner according to the user's emotions.

[0440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0441] Step 1:

[0442] The server receives the meeting theme and purpose from the user. As input, the "meeting theme" and "purpose" provided by the user are required. Based on these inputs, the server refers to its internal database and selects relevant topics. Through this data processing, it automatically generates an agenda and sends the generated agenda as output to the user's terminal.

[0443] Step 2:

[0444] The server receives the participant list from the user. After receiving the participant list as input, it checks the schedule information of each participant using a calendar API. The server analyzes the schedule data and finds common free time through data calculations. As a result, it selects the optimal meeting time and sends a notification. This notification includes the meeting date and time, location, and agenda. As output, a notification of the specified date, time, and location is sent to the participant's device.

[0445] Step 3:

[0446] The server uses an AI model during the meeting to generate comments, discussion summaries, and closing statements in real time. It uses the meeting's audio data as input, performs speech recognition, and converts it into text data. Based on this, the generative AI model calculates the comments and discussion summaries, which are presented to the facilitator in real time. The generated comments and summaries are displayed on the facilitator's device as output.

[0447] Step 4:

[0448] The server uses an emotion engine to recognize the emotions of participants during a meeting in real time. Audio and video data are used as input. The emotion engine analyzes the emotion data and recognizes the user's emotional state. Based on this, it generates comments to adjust the progress of the meeting and provides them to the facilitator. For example, if a user feels irritated or tired, it outputs a comment such as "Let's take a short break and resume," and displays it on the facilitator's device.

[0449] Step 5:

[0450] The server receives the audio files of the meeting and converts them into text using speech recognition technology. The audio files recorded during the meeting are required as input. Natural language processing technology is used to extract important points from the converted text data. This data processing process organizes the main points and generates minutes of the meeting. As an output, the generated minutes are provided to the user for confirmation.

[0451] Step 6:

[0452] The server distributes the minutes by email based on the participant list. The input requires the confirmed minutes and the participant list. The server sends the minutes to each participant's email address. As an output, minutes are sent to all participants' email addresses to reconfirm the contents of the meeting. This allows them to take the next step.

[0453] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0454] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0455] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0456] [Second embodiment]

[0457] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0458] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0459] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0460] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0461] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0462] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0463] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0464] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0465] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0466] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0467] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0468] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0469] The present invention is a system that can consistently and efficiently carry out the entire process from preparation to progress of a meeting, as well as follow-up after the meeting has ended. A specific embodiment of this system will be described below.

[0470] Agenda creation

[0471] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[0472] Schedule confirmation and meeting notifications

[0473] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0474] Conference facilitator support

[0475] The server uses an AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[0476] Minutes creation

[0477] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. The generated minutes are then sent to the user's device for review.

[0478] Email distribution of meeting minutes

[0479] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0480] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and all participants can share information smoothly.

[0481] The processing flow will be explained below.

[0482] Program processing steps

[0483] Pre-meeting preparation

[0484] Step 1:

[0485] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[0486] Step 2:

[0487] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[0488] Step 3:

[0489] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[0490] Step 4:

[0491] The user inputs a list of participants and registers them in the system.

[0492] Step 5:

[0493] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[0494] Step 6:

[0495] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[0496] Step 7:

[0497] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[0498] Meeting progress

[0499] Step 8:

[0500] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[0501] Step 9:

[0502] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[0503] Step 10:

[0504] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[0505] Post-meeting process

[0506] Step 11:

[0507] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[0508] Step 12:

[0509] The server uses natural language processing technology to extract important points from the converted text, organizes the main points, and creates minutes.

[0510] Step 13:

[0511] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[0512] Step 14:

[0513] The user approves the confirmed minutes.

[0514] Step 15:

[0515] The server distributes the final confirmed minutes by email based on the participant list.

[0516] By following these steps, a system can be created that can efficiently execute the entire process from preparing for a meeting to conducting and following up on it.

[0517] Example 1

[0518] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0519] Preparing for, conducting, and following up on a meeting requires a lot of time and effort. Creating an agenda, coordinating participants' schedules, encouraging participants to speak during the meeting, and creating minutes are often done manually, resulting in inefficiencies. Furthermore, if these tasks are not performed thoroughly, the quality of the meeting may decline and its effectiveness may be impaired. This invention aims to solve these problems by providing a system that automates and streamlines the entire process of a meeting.

[0520] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0521] In this invention, the server includes means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose, means for receiving a participant list, checking the schedules of each participant, selecting a common free time and sending a notification, means for generating remarks, comments, a discussion summary and closing content in real time using a generative AI model during the meeting, means for converting the speech of the meeting into text and extracting important points to create minutes, and means for distributing the created minutes to participants by email. This makes it possible to consistently streamline the processes of preparing, conducting and following up on a meeting.

[0522] "Conference theme and objectives" refers to the central topics or subjects to be discussed at the conference and the purpose for which the conference is being held.

[0523] An "agenda" is a document that lists the items or topics to be discussed at a meeting and the order in which they will be discussed.

[0524] "Participant List" means a list of names and contact information for people who will be attending a meeting.

[0525] "Schedule" refers to the schedule information and free time of each participant.

[0526] "Notification" refers to a message sent to inform participants of information such as the date, time, location, and content of a meeting.

[0527] "Generative AI models" refer to algorithms and systems that use artificial intelligence to generate comments, discussion summaries, and closing statements during meetings in real time.

[0528] "Meeting audio" refers to the content of conversations and discussions that occur during a meeting.

[0529] "Convert to text" refers to the process of converting audio data into text data using language processing techniques.

[0530] "Key points" refer to the main points and conclusions extracted from the discussions during the meeting.

[0531] "Minutes" refers to a document that records the contents of discussions, important remarks, decisions, etc. that took place during a meeting.

[0532] "Delivery by email" refers to the act of sending specific information to a designated recipient using email.

[0533] "Schedule Management API" means an application programming interface used to obtain schedules and availability of participants.

[0534] The present invention is a system for efficiently preparing for a meeting, conducting the meeting, and following up after the meeting. This system operates mainly by exchanging data between a server, terminals, and users. Specific embodiments of the present invention are described below.

[0535] First, the user inputs the topic and purpose of the meeting. For example, prompts such as "Topic: Project progress" or "Objective: Decide next steps" are entered. This input is entered as text information into a form on the user's device and sent to the server by pressing the send button.

[0536] The server then refers to its internal database based on the theme and purpose provided by the user to select relevant topics. This involves searching for relevant data using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" from past data related to the theme "Project Progress." The server then uses an AI model to automatically generate an agenda and sends it to the user's device. This process uses a template-based approach to generate the agenda.

[0537] Next, the user checks the contents of the agenda and makes corrections or additional comments as necessary. This checking is done by checking the contents of the agenda displayed on the terminal.

[0538] After that, the user uploads the list of participants for the meeting. This information is provided via a CSV file or a web form. The server receives the participant list and uses a schedule management API to check each participant's schedule. For example, it uses the Google Calendar API to obtain each participant's free time and selects a common free time based on that information.

[0539] The selected meeting time is sent to all participants as a notification by the server, which includes the date, time, location and agenda of the meeting. This notification is sent using a mail server.

[0540] During the meeting, the server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time. For example, comments such as "Please tell us your opinion on this point" are generated to support the progress of the meeting. The server also monitors the progress of the discussion and provides summaries and closing comments at appropriate times, thereby improving the efficiency of the meeting.

[0541] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology. Specifically, it uses the Google Speech-to-Text API to convert the audio data into text. It then uses natural language processing technology to extract key points and automatically generate minutes. These minutes are then sent to the user's device.

[0542] Finally, the server distributes the generated minutes to the participants by email. For example, minutes containing the meeting schedule and content, agenda, and decisions are sent to the participants' mailboxes.

[0543] In this way, the system of the present invention consistently improves efficiency from meeting preparation to progress and follow-up, making the entire business process smoother.

[0544] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] The user inputs the topic and purpose of the meeting.

[0547] Input: Theme "Project Progress", Objective "Determine next steps"

[0548] Output: The input data is sent to the server

[0549] Specific operation: The user enters the topic and purpose into the form on the terminal and presses the submit button, which sends the data to the server.

[0550] Step 2:

[0551] The server consults an internal database based on the received theme and purpose.

[0552] Input: Theme and Objective Data

[0553] Output: Related topics

[0554] Specific operation: The server uses input data as a trigger to search the database for related topics using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" as topics related to "Project Progress."

[0555] Step 3:

[0556] The server automatically generates an agenda based on relevant topics.

[0557] Input: Related topics

[0558] Output: Auto-generated agenda

[0559] How it works: Using an AI model, the extracted topics are incorporated into a template to automatically generate an agenda, which is then sent to the user's device.

[0560] Step 4:

[0561] The user checks the contents of the agenda.

[0562] Input: Auto-generated agenda

[0563] Output: Confirmed agenda, comments or corrections

[0564] Specific operation: The user checks the contents of the agenda displayed on the terminal and makes corrections or additional comments if necessary.

[0565] Step 5:

[0566] The user uploads the participant list.

[0567] Input: Participant list (e.g., CSV file)

[0568] Output: The participant list is sent to the server

[0569] Specific operation: The user selects the participant list from the terminal and presses the upload button to send it to the server.

[0570] Step 6:

[0571] The server uses a schedule management API to check the schedule of each participant.

[0572] Input: Participant list

[0573] Output: Free time for each participant

[0574] Specific operation: Using the Google Calendar API, etc., a request is sent to check the free time of participants. The server aggregates the obtained free time and finds common free time.

[0575] Step 7:

[0576] The server selects the best meeting time and sends a notification.

[0577] Input: Availability of each participant

[0578] Output: Meeting notification

[0579] Specific operation: Calculates common free time based on the obtained free time information and selects the optimal meeting time. Sends a notification containing the selected meeting time and agenda to all participants using a mail server.

[0580] Step 8:

[0581] The server uses the generative AI model to generate comments in real time during the meeting.

[0582] Input: Meeting progress

[0583] Output: Comment

[0584] How it works: Using a generative AI model, it generates comments in real time, allowing the facilitator to encourage discussion.

[0585] Step 9:

[0586] The server generates a discussion summary and closing message.

[0587] Input: Meeting progress

[0588] Output: Summary and closing message

[0589] What it does: It uses natural language processing technology to extract key points and conclusions, and generates summaries and closing messages at appropriate times during the meeting.

[0590] Step 10:

[0591] The server receives the audio files of the conference and uses speech recognition technology to convert the speech to text.

[0592] Input: Meeting audio file

[0593] Output: Text data

[0594] Specific operation: After the meeting ends, the meeting audio is uploaded to the server and the audio data is converted to text using the Google Speech-to-Text API or similar.

[0595] Step 11:

[0596] The server extracts important points and creates minutes.

[0597] Input: Text data

[0598] Output:Minutes

[0599] Specific operation: Uses natural language processing technology to extract key points from text data and automatically generate meeting minutes.

[0600] Step 12:

[0601] The server transmits the generated minutes to the user's terminal.

[0602] Input: Minutes

[0603] Output: Confirmed transcript

[0604] Specific operation: The automatically generated minutes are sent to the user's device and the user confirms them.

[0605] Step 13:

[0606] The server distributes the confirmed minutes to the participants by email.

[0607] Input: Confirmed minutes

[0608] Output: Delivered minutes

[0609] Specific operation: The confirmed minutes are distributed to all participants via the mail server.

[0610] (Application example 1)

[0611] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0612] Currently, there is no system in place that can efficiently manage the progress of work within the factory, from preparing for meetings to proceeding with them and following up after they have been completed. In particular, it is difficult for each worker and manager to grasp the work situation in real time and receive appropriate instructions, and there is a problem that important incidents are not recorded and shared on the spot. This hinders work efficiency and the effective progress of meetings.

[0613] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0614] In this invention, the server includes means for receiving the theme and purpose of a meeting and automatically generating an agenda based on the theme and purpose, means for receiving a list of participants, checking each participant's schedule, selecting a common free time and sending a notification, means for generating comments, a discussion summary, and closing content in real time using a generative AI model during the meeting, means for converting the meeting audio into text and extracting important points to create minutes, means for distributing the created minutes to participants by email, means for checking the progress of work in the factory in real time and providing instructions for the next step with audio and visual information, and means for recording and sharing important incidents on the spot using a smart device, thereby enabling more efficient work in the factory and more effective meetings.

[0615] An "agenda" is a plan that summarizes the topics and progress of a meeting or discussion.

[0616] A "generative AI model" is a software system that uses artificial intelligence techniques to analyze data and automatically generate sentences and responses.

[0617] "Speech comments" are comments that include suggestions or questions to assist participants in making statements during a meeting.

[0618] A "discussion summary" is a concise summary of the discussions that took place during the meeting.

[0619] "Closing content" is content that summarizes the discussion and provides next steps at the end of the meeting.

[0620] "Speech-to-text" is the process of converting spoken words into written information using speech recognition technology.

[0621] Minutes are a written record of what was said at a meeting that can be referenced later.

[0622] "Inside the factory" refers to the interior of a building or facility where manufacturing operations take place.

[0623] "Progress of work" is information that indicates the current achievement level and progress of work or tasks.

[0624] "Guiding with audio and visual information" means providing instructions and guidance using audio and visual methods.

[0625] "Smart devices" generally refer to electronic devices that can connect to the Internet and have a variety of functions, such as smartphones and smart glasses.

[0626] "Incident" means an unexpected occurrence or problem, including any particularly problematic situation or accident.

[0627] "Real-time" refers to processing or operations that are performed in synchronization with actual time.

[0628] The present invention is a system that can efficiently and consistently manage the progress of work in a factory, as well as the preparation for and progress of meetings, and follow-up after the meetings have ended. Specific embodiments of this system will be described below.

[0629] Agenda creation

[0630] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Agenda A," "Agenda B," and "Agenda C" are automatically generated.

[0631] Schedule confirmation and meeting notifications

[0632] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0633] Conference facilitator support

[0634] The server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[0635] Minutes creation

[0636] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. This process uses technologies such as Google's speech recognition API. The generated minutes are then sent to the user's device for review.

[0637] Email distribution of meeting minutes

[0638] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0639] Real-time confirmation and instructions for factory operations

[0640] The server allows users to check the progress of work in real time through smart devices (e.g., smart glasses) worn in the factory. This allows instructions for the next step to be given through voice and visual information, improving work efficiency. For example, when a specific process is completed, an automatic instruction such as "Start process X next" is issued.

[0641] Recording and sharing critical incidents

[0642] Users can use their smart devices to record important incidents in real time and send them to a server. The server then immediately shares the received incident information with relevant personnel and managers. For example, when a facility failure is detected, on-site workers can take a picture of the faulty area through smart glasses and upload it to the server, enabling a prompt response.

[0643] Prompt Sentence Examples

[0644] Below are some examples of specific prompt sentences.

[0645] "Prepare for a meeting to decide next steps for project progress. The participants are Person A and Person B. Check your mutual availability and communicate an appropriate meeting time."

[0646] In this way, by using the system of the present invention, it is possible to improve the efficiency of work within a factory and to conduct meetings effectively.

[0647] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0648] Step 1:

[0649] The server receives the meeting topic and purpose from the user. For example, the topic and purpose can be "Project Progress" and "Determine Next Steps." Based on this input, the server references its internal database and selects relevant topics. This data reference process is performed by searching the database for past meeting records and standard agenda lists to extract relevant topics. The output is an automatically generated agenda.

[0650] Step 2:

[0651] The server sends the generated agenda to the user's device. The user checks the agenda on the device and makes any necessary modifications. During this modification process, the user adds additional agenda items or deletes unnecessary items. The modified agenda is then resent from the device to the server, and the final agenda is confirmed. The input is the generated agenda, and the output is the final confirmed agenda.

[0652] Step 3:

[0653] The server receives the list of participants and checks each participant's schedule. This check process involves using a calendar API to obtain participants' free time slots. The server then saves the obtained schedule information in a database and compares the schedules of all participants to find common free time slots. The output is the optimal meeting time.

[0654] Step 4:

[0655] The server creates a meeting notice based on the optimal meeting time and the confirmed agenda. The generated meeting notice includes the meeting date, time, location, and agenda. This meeting notice is sent to participants via email or calendar invitation. The input is the optimal meeting time and agenda, and the output is the meeting notice.

[0656] Step 5:

[0657] During the meeting, the server uses a generative AI model to generate comments, discussion summaries, and closing statements in real time. This information is generated at the appropriate time while monitoring the progress of the meeting and displayed on the facilitator's device. Users can proceed with the meeting while referring to the displayed information. The input is the audio data and progress of the meeting, and the output is comments, discussion summaries, and closing statements.

[0658] Step 6:

[0659] The server receives the audio file of the meeting and converts it into text using speech recognition technology. During the conversion process, the audio data is analyzed using Google's speech recognition API and converted into text information. Key points are extracted from this text data using natural language processing technology. The extracted key points are organized to create minutes of the meeting and sent to the user's device. The input is the audio file of the meeting, and the output is the generated minutes.

[0660] Step 7:

[0661] The server distributes the confirmed minutes by email based on the participant list. In this distribution process, the generated minutes are formatted as the body of an email and sent to the participants' email addresses. This allows participants to review the contents of the meeting and take further action. The input is the generated minutes, and the output is the email in which the minutes were distributed.

[0662] Step 8:

[0663] The server allows users to check the progress of work in real time through smart devices worn in the factory. In this process, the server analyzes data sent from the smart device in real time and provides instructions for the next step through audio and visual information. For example, when a specific process is completed, an instruction such as "Please start process X next" is automatically generated and displayed on the user's device. The input is data from the smart device, and the output is the generated instruction.

[0664] Step 9:

[0665] Users use smart devices to record important incidents in real time and send them to a server. In this process, users use their smart devices to record images and text of incidents and upload them to the server. The server analyzes the received incident information and immediately shares it with relevant personnel and managers. The input is the incident information recorded by the user, and the output is the analyzed incident information and its sharing.

[0666] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0667] The present invention is a system that can consistently and efficiently handle everything from preparing for a meeting to proceeding with it and follow-up after it has ended, and it also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of this system are described below.

[0668] Agenda creation

[0669] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[0670] Schedule confirmation and meeting notifications

[0671] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0672] Supporting meeting progress with an emotion engine

[0673] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[0674] Conference facilitator support

[0675] The server monitors the progress of the meeting and presents comments to the facilitator at appropriate times. Using data from the emotion engine, it generates comments that reflect the user's emotional state. For example, it generates specific, positive comments such as, "Please tell us more about your opinion."

[0676] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing of the discussion are generated in real time as the discussion progresses and provided to the facilitator.

[0677] Minutes creation

[0678] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[0679] Email distribution of meeting minutes

[0680] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0681] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and the meeting can be optimally progressed according to the emotional state of the user.

[0682] The processing flow will be explained below.

[0683] Program processing steps

[0684] Pre-meeting preparation

[0685] Step 1:

[0686] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[0687] Step 2:

[0688] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[0689] Step 3:

[0690] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[0691] Step 4:

[0692] The user inputs a list of participants and registers them in the system.

[0693] Step 5:

[0694] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[0695] Step 6:

[0696] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[0697] Step 7:

[0698] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[0699] Meeting progress

[0700] Step 8:

[0701] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[0702] Step 9:

[0703] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[0704] Step 10:

[0705] The server uses an emotion engine to recognize the user's emotions and adjusts the comments, discussion summary, and closing statement in real time. For example, if the user is frustrated, the server generates a comment such as "Let's take a short break and resume."

[0706] Step 11:

[0707] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[0708] Step 12:

[0709] The terminal (facilitator) checks the summary and closing content provided by the server and uses them at the appropriate time.

[0710] Post-meeting process

[0711] Step 13:

[0712] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[0713] Step 14:

[0714] The server uses natural language processing technology to extract important points from the converted text and create minutes, while an emotion engine also reflects the user's emotional state as information.

[0715] Step 15:

[0716] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[0717] Step 16:

[0718] The user approves the confirmed minutes.

[0719] Step 17:

[0720] The server distributes the final confirmed minutes by email based on the participant list.

[0721] In this way, by using the system of the present invention, the entire process from preparing for a meeting to conducting it and following up can be carried out efficiently, and the optimal progress can be achieved according to the emotional state of the user.

[0722] Example 2

[0723] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0724] In conventional conferencing systems, preparation, progress, and follow-up of meetings were carried out separately, making efficient operation difficult. Furthermore, it was not possible to adjust the progress of the meeting by taking into account the user's emotional state, which made it easy for participants to feel fatigued or stressed. Furthermore, it was difficult to generate summaries of comments and discussions in real time, making it difficult to conduct meetings quickly and accurately.

[0725] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose; means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification; means for generating remarks, comments, a discussion summary, and closing content in real time using a generative AI model during the meeting; means for converting the meeting audio into text, extracting important points, and creating minutes; means for distributing the created minutes to participants by email; and means including an emotion engine that recognizes emotions from the user's facial expressions and voice during the meeting and adjusts the progress of the meeting based on the recognized emotions. This not only enables consistent and efficient preparation, progress, and follow-up of the meeting, but also enables optimal progress according to the user's emotional state.

[0726] "Theme" refers to the subject matter of the conference or the issue area that will be the focus of discussion.

[0727] "Purpose" refers to the specific goals or results that the meeting aims to achieve.

[0728] An "agenda" refers to a list of topics or items to be discussed at a meeting.

[0729] "Participant List" means the list of individuals or entities that will be attending a Conference.

[0730] A "schedule" indicates the schedule and free time of each participant during a specific period.

[0731] "Notification" refers to a means of communication to inform participants of information such as the date, time, location, and agenda of a meeting.

[0732] "Generative AI model" refers to a model that uses artificial intelligence technology to automatically generate text and comments from data.

[0733] A "summary" is a concise summary of what was discussed and said during a meeting.

[0734] "Closing content" refers to the summary and instructions for next steps given at the end of the meeting.

[0735] "Speech recognition technology" refers to technology that converts speech into text.

[0736] "Natural language processing technology" refers to technology for analyzing text data and performing semantic analysis and information extraction.

[0737] An "emotion engine" is a system that recognizes emotions from a user's facial expressions and voice, and generates appropriate comments and actions based on that information.

[0738] "Email" refers to a means for sending and receiving communications over a network such as the Internet.

[0739] The present invention is a system that can consistently and efficiently prepare for, conduct, and follow up on a meeting after it has ended. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of the present invention are described below.

[0740] First, the user inputs the theme and purpose of the meeting into the system. Based on this theme and purpose, the server references its internal database and automatically generates an agenda. For example, if the theme is "New Product Development Meeting" and the purpose is "Schedule Adjustment," the server will automatically generate topics such as "Sharing Market Research Results," "Identifying Technical Issues," and "Promotion Plan." The generated agenda is sent to the user's device, where the user can check the contents.

[0741] The server then receives a list of participants who will attend the meeting. Based on this list, the server uses a calendar API (e.g., Google Calendar API or Microsoft Outlook API) to check each participant's schedule. It then finds common free time slots, selects the optimal meeting time, and sends notifications to participants. The notifications include the meeting date, time, location, and agenda. For example, if participants' free time slots are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," the server selects "Tuesday 14:00-15:00" as the common free time slot.

[0742] During the meeting, the server uses an emotion engine to recognize emotions in real time from the user's facial expressions and voice. For example, if a user feels irritated or tired, the server will generate a relaxing comment such as "Let's take a short break and resume," and provide it to the facilitator. The emotion engine uses, for example, IBM Watson Tone Analyzer or Microsoft Azure Emotion API.

[0743] Furthermore, the server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, positive comments such as "Please tell us more about your opinion" are generated as specific examples based on the user's emotional state. The facilitator checks the comments provided by the server and uses them at the appropriate time. Additionally, a discussion summary and closing statement are generated in real time as the meeting progresses and provided to the facilitator.

[0744] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology (e.g., Google Cloud Speech-to-Text or Amazon Transcribe). It then uses natural language processing technology (e.g., NLTK or spaCy) to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also used in this process, generating minutes that reflect the user's emotional state.

[0745] Finally, the server distributes the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. The minutes include key points such as the meeting schedule and content, agenda, and decisions.

[0746] Prompt Sentence Examples

[0747] 1. Example agenda-building prompts:

[0748] The theme of the meeting is "New Product Development Meeting" and the purpose is "Schedule Adjustment." Please generate a relevant agenda.

[0749] 2. Example prompts for support from the Emotion Engine:

[0750] A user appears frustrated during a meeting. Generate a comment to encourage them to relax.

[0751] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0752] Processing step details

[0753] Step 1:

[0754] The user enters the topic and purpose of the meeting.

[0755] Input: Meeting topic (e.g., "New Product Development Meeting") and purpose (e.g., "Scheduling").

[0756] How it works: The user enters the subject and purpose into the system's input form.

[0757] Output: The input data is sent to the server.

[0758] Step 2:

[0759] The server refers to an internal database, selects relevant topics, and generates an agenda.

[0760] Input: The subject and purpose entered by the user.

[0761] How it works: Based on the theme and purpose, the server queries a database such as MySQL or PostgreSQL to retrieve relevant topics. This allows topics such as "Sharing market research results" and "Identifying technical issues" to be selected. An agenda is generated based on this.

[0762] Output: The generated agenda.

[0763] Step 3:

[0764] The server sends the generated agenda to the user's terminal.

[0765] Input: The generated agenda.

[0766] How it works: The server converts the agenda into JSON or XML format and sends it to the user's device.

[0767] Output: The agenda displayed on the user's terminal.

[0768] Step 4:

[0769] The user checks the agenda on the device and makes any necessary corrections.

[0770] Input: User feedback (suggested corrections).

[0771] Action: The user enters any necessary corrections to the confirmed agenda and submits it to the system.

[0772] Output: The revised agenda.

[0773] Step 5:

[0774] The user enters the participant list for the meeting.

[0775] Input: Participant list.

[0776] How it works: A user enters the names and contact information of participants into the system.

[0777] Output: The input data is sent to the server.

[0778] Step 6:

[0779] The server uses the calendar API to check the schedules of participants.

[0780] Input: Participant list.

[0781] How it works: The server uses the Google Calendar API or Microsoft Outlook API to retrieve the schedules of each participant.

[0782] Output: Schedule data for each participant.

[0783] Step 7:

[0784] The server finds common free time and selects the best time to meet.

[0785] Input: Schedule data for each participant.

[0786] How it works: The server parses the schedule data and identifies common free times.

[0787] Output: The best meeting time selected.

[0788] Step 8:

[0789] The server sends a meeting notification to the participants.

[0790] Input: Selected meeting time, location, and agenda.

[0791] How it works: The server generates notifications and sends them to participants via email or a notification system.

[0792] Output: Meeting notification sent to participants.

[0793] Step 9:

[0794] The server activates an emotion engine and recognizes emotions from the facial expressions and voices of users during the meeting.

[0795] Input: Audio and video data during the conference.

[0796] How it works: The server analyzes emotions using an emotion engine (e.g., IBM Watson Tone Analyzer or Microsoft Azure Emotion API), which identifies the user's emotions, such as "irritation" or "tiredness."

[0797] Output: User emotion data.

[0798] Step 10:

[0799] The server generates comments and summaries of the meeting progress in real time based on the emotional data.

[0800] Input: User emotion data and meeting progress data.

[0801] How it works: The server uses a generative AI model to generate a comment, such as "Let's take a short break and then resume."

[0802] Output: Generated comments and summaries.

[0803] Step 11:

[0804] The server presents comments to the facilitator and monitors progress.

[0805] Input: Generated comments and summaries.

[0806] How it works: The server presents comments in real time to the facilitator's device and keeps track of the progress.

[0807] Output: Comments displayed on the facilitator's terminal.

[0808] Step 12:

[0809] The server receives the audio file of the meeting and converts it into text using speech recognition technology.

[0810] Input: Meeting audio file.

[0811] How it works: The server converts speech to text using Google Cloud Speech-to-Text or Amazon Transcribe.

[0812] Output: The converted text data.

[0813] Step 13:

[0814] The server extracts key points and creates minutes.

[0815] Input: Text data.

[0816] How it works: The server uses natural language processing technology (e.g., NLTK or spaCy) to extract important points, organize the main points, and create meeting minutes. It may also use data from the emotion engine.

[0817] Output: The generated transcript.

[0818] Step 14:

[0819] The server will deliver the confirmed minutes to the participants by email.

[0820] Input: Generated meeting minutes and participant list.

[0821] What it does: The server creates emails and distributes the minutes to participants.

[0822] Output: Minutes delivered to participants.

[0823] (Application example 2)

[0824] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0825] While conventional meeting support systems can efficiently prepare, conduct, and follow up on meetings, they are unable to take into account the emotions of participants during the meeting, which can affect participants' motivation and the progress of the meeting. Furthermore, in factory meetings, in particular, many participants are pressed for time and work, making it necessary to further improve the efficiency of meetings. Therefore, there is a need for a system that can recognize the emotional state of participants during a meeting in real time and adjust the progress of the meeting based on that information.

[0826] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically generating an agenda based on the theme and purpose of the meeting, means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification, means for generating remarks, comments, a discussion summary, and closing content in real time using an AI model during the meeting, means for converting the meeting audio into text, extracting important points, and creating minutes, means for distributing the created minutes to participants by email, and means for recognizing the emotions of participants during the meeting and adjusting the progress based on the emotion data. This enables consistent and efficient processing from meeting preparation to progress and follow-up, and further enables the meeting to proceed optimally in accordance with the emotions of the participants.

[0827] A "meeting theme" is a specific topic or agenda that is central to the meeting and determines the purpose and direction of the meeting.

[0828] "Purpose" is the specific goal or intention to be achieved in the meeting, and is the standard for the success of the meeting.

[0829] An "agenda" is a list of topics and schedules for a meeting, and is used to indicate the structure of the meeting.

[0830] A "participant list" is a list of people who will be attending a meeting, and is the basic information for organizing and announcing the meeting.

[0831] "Schedule" is information indicating the participants' schedules and free time, and is used to determine the date and time of the conference.

[0832] "Notification" is a means of communication to inform participants of the date, time, location, agenda, etc. of a meeting.

[0833] An "AI model" is an algorithm or program that uses artificial intelligence, and is a means of automating data analysis and decision-making.

[0834] "Comments" are opinions or responses made during a meeting to encourage discussion.

[0835] A "discussion summary" is a concise summary of the important discussions and conclusions that took place during the meeting, and is used to guide the progress of the meeting and subsequent actions.

[0836] "Closing content" is information about conclusions and next steps that are summarized at the end of the meeting and are used to conclude the meeting.

[0837] "Convert to text" is the process of converting audio data or other forms of information into written information.

[0838] "Key points" are the main issues or decisions to be discussed during the meeting.

[0839] Minutes are documents that record what was said and decided during a meeting, and are used to review the contents of the meeting later.

[0840] "Emotions" refer to the psychological state of participants as perceived from their facial expressions and voices, and affect the progress and atmosphere of the meeting.

[0841] "Emotion data" is data that expresses the emotional state of participants in numerical values ​​or categories, and is used to adjust the progress of the meeting.

[0842] This system aims to support meetings within factories, and can consistently and efficiently handle everything from meeting preparation to progress and follow-up. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting.

[0843] Agenda creation

[0844] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide on Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[0845] Schedule confirmation and meeting notifications

[0846] The server receives the participant list and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds common free time and selects the optimal meeting time. It then sends a notification to the participants based on this information. The notification includes the meeting date, time, location, and agenda. For example, if participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0847] Supporting meeting progress with an emotion engine

[0848] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[0849] Conference facilitator support

[0850] The server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, comments are generated based on the user's emotional state. For example, specific, positive comments such as "Please tell us more about your opinion" are generated. The device (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing statement of the discussion are generated in real time as the meeting progresses and provided to the facilitator.

[0851] Minutes creation

[0852] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[0853] Email distribution of meeting minutes

[0854] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0855] Hardware or software used

[0856] server

[0857] User devices (smartphones, tablets, desktop PCs, etc.)

[0858] Calendar API (e.g. Google Calendar API)

[0859] Emotion recognition library (e.g., EmotionRecognition)

[0860] Speech recognition library (e.g., SpeechRecognition)

[0861] Natural language processing libraries (e.g., NLP)

[0862] Prompt Sentence Examples

[0863] Theme: Project progress

[0864] Objective: Determine next steps

[0865] It analyzes the content of meeting discussions in real time and generates comments such as "Let's take a short break and then resume" if participants seem frustrated.

[0866] In this way, by using this system, meeting support within the factory will be made more efficient and the meeting will proceed in an optimal manner according to the user's emotions.

[0867] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0868] Step 1:

[0869] The server receives the meeting theme and purpose from the user. As input, the "meeting theme" and "purpose" provided by the user are required. Based on these inputs, the server refers to its internal database and selects relevant topics. Through this data processing, it automatically generates an agenda and sends the generated agenda as output to the user's terminal.

[0870] Step 2:

[0871] The server receives the participant list from the user. After receiving the participant list as input, it checks the schedule information of each participant using a calendar API. The server analyzes the schedule data and finds common free time through data calculations. As a result, it selects the optimal meeting time and sends a notification. This notification includes the meeting date and time, location, and agenda. As output, a notification of the specified date, time, and location is sent to the participant's device.

[0872] Step 3:

[0873] The server uses an AI model during the meeting to generate comments, discussion summaries, and closing statements in real time. It uses the meeting's audio data as input, performs speech recognition, and converts it into text data. Based on this, the generative AI model calculates the comments and discussion summaries, which are presented to the facilitator in real time. The generated comments and summaries are displayed on the facilitator's device as output.

[0874] Step 4:

[0875] The server uses an emotion engine to recognize the emotions of participants during a meeting in real time. Audio and video data are used as input. The emotion engine analyzes the emotion data and recognizes the user's emotional state. Based on this, it generates comments to adjust the progress of the meeting and provides them to the facilitator. For example, if a user feels irritated or tired, it outputs a comment such as "Let's take a short break and resume," and displays it on the facilitator's device.

[0876] Step 5:

[0877] The server receives the audio files of the meeting and converts them into text using speech recognition technology. The audio files recorded during the meeting are required as input. Natural language processing technology is used to extract important points from the converted text data. This data processing process organizes the main points and generates minutes of the meeting. As an output, the generated minutes are provided to the user for confirmation.

[0878] Step 6:

[0879] The server distributes the minutes by email based on the participant list. The input requires the confirmed minutes and the participant list. The server sends the minutes to each participant's email address. As an output, minutes are sent to all participants' email addresses to reconfirm the contents of the meeting. This allows them to take the next step.

[0880] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0881] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0882] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0883] [Third embodiment]

[0884] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0885] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0886] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0887] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0888] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0889] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0890] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0891] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0892] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0893] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0894] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0895] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0896] The present invention is a system that can consistently and efficiently carry out the entire process from preparation to progress of a meeting, to follow-up after the meeting has ended. A specific embodiment of this system will be described below.

[0897] Agenda creation

[0898] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[0899] Schedule confirmation and meeting notifications

[0900] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[0901] Conference facilitator support

[0902] The server uses an AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[0903] Minutes creation

[0904] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. The generated minutes are then sent to the user's device for review.

[0905] Email distribution of meeting minutes

[0906] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[0907] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and all participants can share information smoothly.

[0908] The processing flow will be explained below.

[0909] Program processing steps

[0910] Pre-meeting preparation

[0911] Step 1:

[0912] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[0913] Step 2:

[0914] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[0915] Step 3:

[0916] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[0917] Step 4:

[0918] The user inputs a list of participants and registers them in the system.

[0919] Step 5:

[0920] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[0921] Step 6:

[0922] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[0923] Step 7:

[0924] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[0925] Meeting progress

[0926] Step 8:

[0927] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[0928] Step 9:

[0929] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[0930] Step 10:

[0931] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[0932] Post-meeting process

[0933] Step 11:

[0934] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[0935] Step 12:

[0936] The server uses natural language processing technology to extract important points from the converted text, organizes the main points, and creates minutes.

[0937] Step 13:

[0938] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[0939] Step 14:

[0940] The user approves the confirmed minutes.

[0941] Step 15:

[0942] The server distributes the final confirmed minutes by email based on the participant list.

[0943] By following these steps, a system can be created that can efficiently execute the entire process from preparing for a meeting to conducting and following up on it.

[0944] Example 1

[0945] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0946] Preparing for, conducting, and following up on a meeting requires a lot of time and effort. Creating an agenda, coordinating participants' schedules, encouraging participants to speak during the meeting, and creating minutes are often done manually, resulting in inefficiencies. Furthermore, if these tasks are not performed thoroughly, the quality of the meeting may decline and its effectiveness may be impaired. This invention aims to solve these problems by providing a system that automates and streamlines the entire process of a meeting.

[0947] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0948] In this invention, the server includes means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose, means for receiving a participant list, checking the schedules of each participant, selecting a common free time and sending a notification, means for generating remarks, comments, a discussion summary and closing content in real time using a generative AI model during the meeting, means for converting the speech of the meeting into text and extracting important points to create minutes, and means for distributing the created minutes to participants by email. This makes it possible to consistently streamline the processes of preparing, conducting and following up on a meeting.

[0949] "Conference theme and objectives" refers to the central topics or subjects to be discussed at the conference and the purpose for which the conference is being held.

[0950] An "agenda" is a document that lists the items or topics to be discussed at a meeting and the order in which they will be discussed.

[0951] "Participant List" means a list of names and contact information for people who will be attending a meeting.

[0952] "Schedule" refers to the schedule information and free time of each participant.

[0953] "Notification" refers to a message sent to inform participants of information such as the date, time, location, and content of a meeting.

[0954] "Generative AI models" refer to algorithms or systems that use artificial intelligence to generate comments, discussion summaries, and closing statements during meetings in real time.

[0955] "Meeting audio" refers to the content of conversations and discussions that occur during a meeting.

[0956] "Convert to text" refers to the process of converting audio data into text data using language processing techniques.

[0957] "Key points" refer to the main points and conclusions extracted from the discussions during the meeting.

[0958] "Minutes" refers to a document that records the contents of discussions, important remarks, decisions, etc. that took place during a meeting.

[0959] "Delivery by email" refers to the act of sending specific information to a designated recipient using email.

[0960] "Schedule Management API" means an application programming interface used to obtain schedules and availability of participants.

[0961] The present invention is a system for efficiently preparing for a meeting, conducting the meeting, and following up after the meeting. This system operates mainly by exchanging data between a server, terminals, and users. Specific embodiments of the present invention are described below.

[0962] First, the user inputs the topic and purpose of the meeting. For example, prompts such as "Topic: Project progress" or "Objective: Decide next steps" are entered. This input is entered as text information into a form on the user's device and sent to the server by pressing the send button.

[0963] The server then refers to its internal database based on the theme and purpose provided by the user to select relevant topics. This involves searching for relevant data using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" from past data related to the theme "Project Progress." The server then uses an AI model to automatically generate an agenda and sends it to the user's device. This process uses a template-based approach to generate the agenda.

[0964] Next, the user checks the contents of the agenda and makes corrections or additional comments as necessary. This checking is done by checking the contents of the agenda displayed on the terminal.

[0965] After that, the user uploads the list of participants for the meeting. This information is provided via a CSV file or a web form. The server receives the participant list and uses a schedule management API to check each participant's schedule. For example, it uses the Google Calendar API to obtain each participant's free time and selects a common free time based on that information.

[0966] The selected meeting time is sent to all participants as a notification by the server, which includes the date, time, location and agenda of the meeting. This notification is sent using a mail server.

[0967] During the meeting, the server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time. For example, comments such as "Please tell us your opinion on this point" are generated to support the progress of the meeting. The server also monitors the progress of the discussion and provides summaries and closing comments at appropriate times, thereby improving the efficiency of the meeting.

[0968] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology. Specifically, it uses the Google Speech-to-Text API to convert the audio data into text. It then uses natural language processing technology to extract key points and automatically generate minutes. These minutes are then sent to the user's device.

[0969] Finally, the server distributes the generated minutes to the participants by email. For example, minutes containing the meeting schedule and content, agenda, and decisions are sent to the participants' mailboxes.

[0970] In this way, the system of the present invention consistently improves efficiency from meeting preparation to progress and follow-up, making the entire business process smoother.

[0971] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0972] Step 1:

[0973] The user inputs the topic and purpose of the meeting.

[0974] Input: Theme "Project Progress", Objective "Determine next steps"

[0975] Output: The input data is sent to the server

[0976] Specific operation: The user enters the topic and purpose into the form on the terminal and presses the submit button, which sends the data to the server.

[0977] Step 2:

[0978] The server consults an internal database based on the received theme and purpose.

[0979] Input: Theme and Objective Data

[0980] Output: Related topics

[0981] Specific operation: The server uses input data as a trigger to search the database for related topics using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" as topics related to "Project Progress."

[0982] Step 3:

[0983] The server automatically generates an agenda based on relevant topics.

[0984] Input: Related topics

[0985] Output: Auto-generated agenda

[0986] How it works: Using an AI model, the extracted topics are incorporated into a template to automatically generate an agenda, which is then sent to the user's device.

[0987] Step 4:

[0988] The user checks the contents of the agenda.

[0989] Input: Auto-generated agenda

[0990] Output: Confirmed agenda, comments or corrections

[0991] Specific operation: The user checks the contents of the agenda displayed on the terminal and makes corrections or additional comments if necessary.

[0992] Step 5:

[0993] The user uploads the participant list.

[0994] Input: Participant list (e.g., CSV file)

[0995] Output: The participant list is sent to the server

[0996] Specific operation: The user selects the participant list from the terminal and presses the upload button to send it to the server.

[0997] Step 6:

[0998] The server uses a schedule management API to check the schedule of each participant.

[0999] Input: Participant list

[1000] Output: Free time for each participant

[1001] Specific operation: Using the Google Calendar API, etc., a request is sent to check the free time of participants. The server aggregates the obtained free time and finds common free time.

[1002] Step 7:

[1003] The server selects the best meeting time and sends a notification.

[1004] Input: Availability of each participant

[1005] Output: Meeting notification

[1006] Specific operation: Calculates common free time based on the obtained free time information and selects the optimal meeting time. Sends a notification containing the selected meeting time and agenda to all participants using a mail server.

[1007] Step 8:

[1008] The server uses the generative AI model to generate comments in real time during the meeting.

[1009] Input: Meeting progress

[1010] Output: Comment

[1011] How it works: Using a generative AI model, it generates comments in real time, allowing the facilitator to encourage discussion.

[1012] Step 9:

[1013] The server generates a discussion summary and closing message.

[1014] Input: Meeting progress

[1015] Output: Summary and closing message

[1016] What it does: It uses natural language processing technology to extract key points and conclusions, and generates summaries and closing messages at appropriate times during the meeting.

[1017] Step 10:

[1018] The server receives the audio files of the conference and uses speech recognition technology to convert the speech to text.

[1019] Input: Meeting audio file

[1020] Output: Text data

[1021] Specific operation: After the meeting ends, the meeting audio is uploaded to the server and the audio data is converted to text using the Google Speech-to-Text API or similar.

[1022] Step 11:

[1023] The server extracts important points and creates minutes.

[1024] Input: Text data

[1025] Output:Minutes

[1026] Specific operation: Uses natural language processing technology to extract key points from text data and automatically generate meeting minutes.

[1027] Step 12:

[1028] The server transmits the generated minutes to the user's terminal.

[1029] Input: Minutes

[1030] Output: Confirmed transcript

[1031] Specific operation: The automatically generated minutes are sent to the user's device and the user confirms them.

[1032] Step 13:

[1033] The server distributes the confirmed minutes to the participants by email.

[1034] Input: Confirmed minutes

[1035] Output: Delivered minutes

[1036] Specific operation: The confirmed minutes are distributed to all participants via the mail server.

[1037] (Application example 1)

[1038] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1039] Currently, there is no system in place that can efficiently manage the progress of work within the factory, from preparing for meetings to proceeding with them and following up after they have been completed. In particular, it is difficult for each worker and manager to grasp the work situation in real time and receive appropriate instructions, and there is a problem that important incidents are not recorded and shared on the spot. This hinders work efficiency and the effective progress of meetings.

[1040] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1041] In this invention, the server includes means for receiving the theme and purpose of a meeting and automatically generating an agenda based on the theme and purpose, means for receiving a list of participants, checking each participant's schedule, selecting a common free time and sending a notification, means for generating comments, a discussion summary, and closing content in real time using a generative AI model during the meeting, means for converting the meeting audio into text and extracting important points to create minutes, means for distributing the created minutes to participants by email, means for checking the progress of work in the factory in real time and providing instructions for the next step with audio and visual information, and means for recording and sharing important incidents on the spot using a smart device, thereby enabling more efficient work in the factory and more effective meetings.

[1042] An "agenda" is a plan that summarizes the topics and progress of a meeting or discussion.

[1043] A "generative AI model" is a software system that uses artificial intelligence techniques to analyze data and automatically generate sentences and responses.

[1044] "Speech comments" are comments that include suggestions or questions to assist participants in making statements during a meeting.

[1045] A "discussion summary" is a concise summary of the discussions that took place during the meeting.

[1046] "Closing content" is content that summarizes the discussion and provides next steps at the end of the meeting.

[1047] "Speech-to-text" is the process of converting spoken words into written information using speech recognition technology.

[1048] Minutes are a written record of what was said at a meeting that can be referenced later.

[1049] "Inside the factory" refers to the interior of a building or facility where manufacturing operations take place.

[1050] "Progress of work" is information that indicates the current achievement level and progress of work or tasks.

[1051] "Guiding with audio and visual information" means providing instructions and guidance using audio and visual methods.

[1052] "Smart devices" generally refer to electronic devices that can connect to the Internet and have a variety of functions, such as smartphones and smart glasses.

[1053] "Incident" means an unexpected occurrence or problem, including any particularly problematic situation or accident.

[1054] "Real-time" refers to processing or operations that are performed in synchronization with actual time.

[1055] The present invention is a system that can efficiently and consistently manage the progress of work in a factory, as well as the preparation for and progress of meetings, and follow-up after the meetings have ended. Specific embodiments of this system will be described below.

[1056] Agenda creation

[1057] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Agenda A," "Agenda B," and "Agenda C" are automatically generated.

[1058] Schedule confirmation and meeting notifications

[1059] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[1060] Conference facilitator support

[1061] The server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[1062] Minutes creation

[1063] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. This process uses technologies such as Google's speech recognition API. The generated minutes are then sent to the user's device for review.

[1064] Email distribution of meeting minutes

[1065] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[1066] Real-time confirmation and instructions for factory operations

[1067] The server allows users to check the progress of work in real time through smart devices (e.g., smart glasses) worn in the factory. This allows instructions for the next step to be given through voice and visual information, improving work efficiency. For example, when a specific process is completed, an automatic instruction such as "Start process X next" is issued.

[1068] Recording and sharing critical incidents

[1069] Users can use their smart devices to record important incidents in real time and send them to a server. The server then immediately shares the received incident information with relevant personnel and managers. For example, when a facility failure is detected, on-site workers can take a picture of the faulty area through smart glasses and upload it to the server, enabling a prompt response.

[1070] Prompt Sentence Examples

[1071] Below are some examples of specific prompt sentences.

[1072] "Prepare for a meeting to decide next steps for project progress. The participants are Person A and Person B. Check your mutual availability and communicate an appropriate meeting time."

[1073] In this way, by using the system of the present invention, it is possible to improve the efficiency of work within a factory and to conduct meetings effectively.

[1074] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1075] Step 1:

[1076] The server receives the meeting topic and purpose from the user. For example, the topic and purpose can be "Project Progress" and "Determine Next Steps." Based on this input, the server references its internal database and selects relevant topics. This data reference process is performed by searching the database for past meeting records and standard agenda lists to extract relevant topics. The output is an automatically generated agenda.

[1077] Step 2:

[1078] The server sends the generated agenda to the user's device. The user checks the agenda on the device and makes any necessary modifications. During this modification process, the user adds additional agenda items or deletes unnecessary items. The modified agenda is then resent from the device to the server, and the final agenda is confirmed. The input is the generated agenda, and the output is the final confirmed agenda.

[1079] Step 3:

[1080] The server receives the list of participants and checks each participant's schedule. This check process involves using a calendar API to obtain participants' free time slots. The server then saves the obtained schedule information in a database and compares the schedules of all participants to find common free time slots. The output is the optimal meeting time.

[1081] Step 4:

[1082] The server creates a meeting notice based on the optimal meeting time and the confirmed agenda. The generated meeting notice includes the meeting date, time, location, and agenda. This meeting notice is sent to participants via email or calendar invitation. The input is the optimal meeting time and agenda, and the output is the meeting notice.

[1083] Step 5:

[1084] During the meeting, the server uses a generative AI model to generate comments, discussion summaries, and closing statements in real time. This information is generated at the appropriate time while monitoring the progress of the meeting and displayed on the facilitator's device. Users can proceed with the meeting while referring to the displayed information. The input is the audio data and progress of the meeting, and the output is comments, discussion summaries, and closing statements.

[1085] Step 6:

[1086] The server receives the audio file of the meeting and converts it into text using speech recognition technology. During the conversion process, the audio data is analyzed using Google's speech recognition API and converted into text information. Key points are extracted from this text data using natural language processing technology. The extracted key points are organized to create minutes of the meeting and sent to the user's device. The input is the audio file of the meeting, and the output is the generated minutes.

[1087] Step 7:

[1088] The server distributes the confirmed minutes by email based on the participant list. In this distribution process, the generated minutes are formatted as the body of an email and sent to the participants' email addresses. This allows participants to review the contents of the meeting and take further action. The input is the generated minutes, and the output is the email in which the minutes were distributed.

[1089] Step 8:

[1090] The server allows users to check the progress of work in real time through smart devices worn in the factory. In this process, the server analyzes data sent from the smart device in real time and provides instructions for the next step through audio and visual information. For example, when a specific process is completed, an instruction such as "Please start process X next" is automatically generated and displayed on the user's device. The input is data from the smart device, and the output is the generated instruction.

[1091] Step 9:

[1092] Users use smart devices to record important incidents in real time and send them to a server. In this process, users use their smart devices to record images and text of incidents and upload them to the server. The server analyzes the received incident information and immediately shares it with relevant personnel and managers. The input is the incident information recorded by the user, and the output is the analyzed incident information and its sharing.

[1093] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1094] The present invention is a system that can consistently and efficiently handle everything from preparing for a meeting to proceeding with it and follow-up after it has ended, and it also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of this system are described below.

[1095] Agenda creation

[1096] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[1097] Schedule confirmation and meeting notifications

[1098] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[1099] Supporting meeting progress with an emotion engine

[1100] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[1101] Conference facilitator support

[1102] The server monitors the progress of the meeting and presents comments to the facilitator at appropriate times. Using data from the emotion engine, it generates comments that reflect the user's emotional state. For example, it generates specific, positive comments such as, "Please tell us more about your opinion."

[1103] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing of the discussion are generated in real time as the discussion progresses and provided to the facilitator.

[1104] Minutes creation

[1105] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[1106] Email distribution of meeting minutes

[1107] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[1108] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and the meeting can be optimally progressed according to the emotional state of the user.

[1109] The processing flow will be explained below.

[1110] Program processing steps

[1111] Pre-meeting preparation

[1112] Step 1:

[1113] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[1114] Step 2:

[1115] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[1116] Step 3:

[1117] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[1118] Step 4:

[1119] The user inputs a list of participants and registers them in the system.

[1120] Step 5:

[1121] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[1122] Step 6:

[1123] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[1124] Step 7:

[1125] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[1126] Meeting progress

[1127] Step 8:

[1128] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[1129] Step 9:

[1130] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[1131] Step 10:

[1132] The server uses an emotion engine to recognize the user's emotions and adjusts the comments, discussion summary, and closing statement in real time. For example, if the user is frustrated, the server generates a comment such as "Let's take a short break and resume."

[1133] Step 11:

[1134] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[1135] Step 12:

[1136] The terminal (facilitator) checks the summary and closing content provided by the server and uses them at the appropriate time.

[1137] Post-meeting process

[1138] Step 13:

[1139] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[1140] Step 14:

[1141] The server uses natural language processing technology to extract important points from the converted text and create minutes, while an emotion engine also reflects the user's emotional state as information.

[1142] Step 15:

[1143] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[1144] Step 16:

[1145] The user approves the confirmed minutes.

[1146] Step 17:

[1147] The server distributes the final confirmed minutes by email based on the participant list.

[1148] In this way, by using the system of the present invention, the entire process from preparing for a meeting to conducting it and following up can be carried out efficiently, and the optimal progress can be achieved according to the emotional state of the user.

[1149] Example 2

[1150] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1151] In conventional conferencing systems, preparation, progress, and follow-up of meetings were carried out separately, making efficient operation difficult. Furthermore, it was not possible to adjust the progress of the meeting by taking into account the user's emotional state, which made it easy for participants to feel fatigued or stressed. Furthermore, it was difficult to generate summaries of comments and discussions in real time, making it difficult to conduct meetings quickly and accurately.

[1152] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose; means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification; means for generating remarks, comments, a discussion summary, and closing content in real time using a generative AI model during the meeting; means for converting the meeting audio into text, extracting important points, and creating minutes; means for distributing the created minutes to participants by email; and means including an emotion engine that recognizes emotions from the user's facial expressions and voice during the meeting and adjusts the progress of the meeting based on the recognized emotions. This not only enables consistent and efficient preparation, progress, and follow-up of the meeting, but also enables optimal progress according to the user's emotional state.

[1153] "Theme" refers to the subject matter of the conference or the issue area that will be the focus of discussion.

[1154] "Purpose" refers to the specific goals or results that the meeting aims to achieve.

[1155] An "agenda" refers to a list of topics or items to be discussed at a meeting.

[1156] "Participant List" means the list of individuals or entities that will be attending a Conference.

[1157] A "schedule" indicates the schedule and free time of each participant during a specific period.

[1158] "Notification" refers to a means of communication to inform participants of information such as the date, time, location, and agenda of a meeting.

[1159] "Generative AI model" refers to a model that uses artificial intelligence technology to automatically generate text and comments from data.

[1160] A "summary" is a concise summary of what was discussed and said during a meeting.

[1161] "Closing content" refers to the summary and instructions for next steps given at the end of the meeting.

[1162] "Speech recognition technology" refers to technology that converts speech into text.

[1163] "Natural language processing technology" refers to technology for analyzing text data and performing semantic analysis and information extraction.

[1164] An "emotion engine" is a system that recognizes emotions from a user's facial expressions and voice, and generates appropriate comments and actions based on that information.

[1165] "Email" refers to a means for sending and receiving communications over a network such as the Internet.

[1166] The present invention is a system that can consistently and efficiently prepare for, conduct, and follow up on a meeting after it has ended. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of the present invention are described below.

[1167] First, the user inputs the theme and purpose of the meeting into the system. Based on this theme and purpose, the server references its internal database and automatically generates an agenda. For example, if the theme is "New Product Development Meeting" and the purpose is "Schedule Adjustment," the server will automatically generate topics such as "Sharing Market Research Results," "Identifying Technical Issues," and "Promotion Plan." The generated agenda is sent to the user's device, where the user can check the contents.

[1168] The server then receives a list of participants who will attend the meeting. Based on this list, the server uses a calendar API (e.g., Google Calendar API or Microsoft Outlook API) to check each participant's schedule. It then finds common free time slots, selects the optimal meeting time, and sends notifications to participants. The notifications include the meeting date, time, location, and agenda. For example, if participants' free time slots are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," the server selects "Tuesday 14:00-15:00" as the common free time slot.

[1169] During the meeting, the server uses an emotion engine to recognize emotions in real time from the user's facial expressions and voice. For example, if a user feels irritated or tired, the server will generate a relaxing comment such as "Let's take a short break and resume," and provide it to the facilitator. The emotion engine uses, for example, IBM Watson Tone Analyzer or Microsoft Azure Emotion API.

[1170] Furthermore, the server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, positive comments such as "Please tell us more about your opinion" are generated as specific examples based on the user's emotional state. The facilitator checks the comments provided by the server and uses them at the appropriate time. Additionally, a discussion summary and closing statement are generated in real time as the meeting progresses and provided to the facilitator.

[1171] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology (e.g., Google Cloud Speech-to-Text or Amazon Transcribe). It then uses natural language processing technology (e.g., NLTK or spaCy) to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also used in this process, generating minutes that reflect the user's emotional state.

[1172] Finally, the server distributes the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. The minutes include key points such as the meeting schedule and content, agenda, and decisions.

[1173] Prompt Sentence Examples

[1174] 1. Example agenda-building prompts:

[1175] The theme of the meeting is "New Product Development Meeting" and the purpose is "Schedule Adjustment." Please generate a relevant agenda.

[1176] 2. Example prompts for support from the Emotion Engine:

[1177] A user appears frustrated during a meeting. Generate a comment to encourage them to relax.

[1178] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1179] Processing step details

[1180] Step 1:

[1181] The user enters the topic and purpose of the meeting.

[1182] Input: Meeting topic (e.g., "New Product Development Meeting") and purpose (e.g., "Scheduling").

[1183] How it works: The user enters the subject and purpose into the system's input form.

[1184] Output: The input data is sent to the server.

[1185] Step 2:

[1186] The server refers to an internal database, selects relevant topics, and generates an agenda.

[1187] Input: The subject and purpose entered by the user.

[1188] How it works: Based on the theme and purpose, the server queries a database such as MySQL or PostgreSQL to retrieve relevant topics. This allows topics such as "Sharing market research results" and "Identifying technical issues" to be selected. An agenda is generated based on this.

[1189] Output: The generated agenda.

[1190] Step 3:

[1191] The server sends the generated agenda to the user's terminal.

[1192] Input: The generated agenda.

[1193] How it works: The server converts the agenda into JSON or XML format and sends it to the user's device.

[1194] Output: The agenda displayed on the user's terminal.

[1195] Step 4:

[1196] The user checks the agenda on the device and makes any necessary corrections.

[1197] Input: User feedback (suggested corrections).

[1198] Action: The user enters any necessary corrections to the confirmed agenda and submits it to the system.

[1199] Output: The revised agenda.

[1200] Step 5:

[1201] The user enters the participant list for the meeting.

[1202] Input: Participant list.

[1203] How it works: A user enters the names and contact information of participants into the system.

[1204] Output: The input data is sent to the server.

[1205] Step 6:

[1206] The server uses the calendar API to check the schedules of participants.

[1207] Input: Participant list.

[1208] How it works: The server uses the Google Calendar API or Microsoft Outlook API to retrieve the schedules of each participant.

[1209] Output: Schedule data for each participant.

[1210] Step 7:

[1211] The server finds common free time and selects the best time to meet.

[1212] Input: Schedule data for each participant.

[1213] How it works: The server parses the schedule data and identifies common free times.

[1214] Output: The best meeting time selected.

[1215] Step 8:

[1216] The server sends a meeting notification to the participants.

[1217] Input: Selected meeting time, location, and agenda.

[1218] How it works: The server generates notifications and sends them to participants via email or a notification system.

[1219] Output: Meeting notification sent to participants.

[1220] Step 9:

[1221] The server activates an emotion engine and recognizes emotions from the facial expressions and voices of users during the meeting.

[1222] Input: Audio and video data during the conference.

[1223] How it works: The server analyzes emotions using an emotion engine (e.g., IBM Watson Tone Analyzer or Microsoft Azure Emotion API), which identifies the user's emotions, such as "irritation" or "tiredness."

[1224] Output: User emotion data.

[1225] Step 10:

[1226] The server generates comments and summaries of the meeting progress in real time based on the emotional data.

[1227] Input: User emotion data and meeting progress data.

[1228] How it works: The server uses a generative AI model to generate a comment, such as "Let's take a short break and then resume."

[1229] Output: Generated comments and summaries.

[1230] Step 11:

[1231] The server presents comments to the facilitator and monitors progress.

[1232] Input: Generated comments and summaries.

[1233] How it works: The server presents comments in real time to the facilitator's device and keeps track of the progress.

[1234] Output: Comments displayed on the facilitator's terminal.

[1235] Step 12:

[1236] The server receives the audio file of the meeting and converts it into text using speech recognition technology.

[1237] Input: Meeting audio file.

[1238] How it works: The server converts speech to text using Google Cloud Speech-to-Text or Amazon Transcribe.

[1239] Output: The converted text data.

[1240] Step 13:

[1241] The server extracts key points and creates minutes.

[1242] Input: Text data.

[1243] How it works: The server uses natural language processing technology (e.g., NLTK or spaCy) to extract important points, organize the main points, and create meeting minutes. It may also use data from the emotion engine.

[1244] Output: The generated transcript.

[1245] Step 14:

[1246] The server will deliver the confirmed minutes to the participants by email.

[1247] Input: Generated meeting minutes and participant list.

[1248] What it does: The server creates emails and distributes the minutes to participants.

[1249] Output: Minutes delivered to participants.

[1250] (Application example 2)

[1251] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1252] While conventional meeting support systems can efficiently prepare, conduct, and follow up on meetings, they are unable to take into account the emotions of participants during the meeting, which can affect participants' motivation and the progress of the meeting. Furthermore, in factory meetings, in particular, many participants are pressed for time and work, making it necessary to further improve the efficiency of meetings. Therefore, there is a need for a system that can recognize the emotional state of participants during a meeting in real time and adjust the progress of the meeting based on that information.

[1253] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically generating an agenda based on the theme and purpose of the meeting, means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification, means for generating remarks, comments, a discussion summary, and closing content in real time using an AI model during the meeting, means for converting the meeting audio into text, extracting important points, and creating minutes, means for distributing the created minutes to participants by email, and means for recognizing the emotions of participants during the meeting and adjusting the progress based on the emotion data. This enables consistent and efficient processing from meeting preparation to progress and follow-up, and further enables the meeting to proceed optimally in accordance with the emotions of the participants.

[1254] A "meeting theme" is a specific topic or agenda that is central to the meeting and determines the purpose and direction of the meeting.

[1255] "Purpose" is the specific goal or intention to be achieved in the meeting, and is the standard for the success of the meeting.

[1256] An "agenda" is a list of topics and schedules for a meeting, and is used to indicate the structure of the meeting.

[1257] A "participant list" is a list of people who will be attending a meeting, and is the basic information for organizing and announcing the meeting.

[1258] "Schedule" is information indicating the participants' schedules and free time, and is used to determine the date and time of the conference.

[1259] "Notification" is a means of communication to inform participants of the date, time, location, agenda, etc. of a meeting.

[1260] An "AI model" is an algorithm or program that uses artificial intelligence, and is a means of automating data analysis and decision-making.

[1261] "Comments" are opinions or responses made during a meeting to encourage discussion.

[1262] A "discussion summary" is a concise summary of the important discussions and conclusions that took place during the meeting, and is used to guide the progress of the meeting and subsequent actions.

[1263] "Closing content" is information about conclusions and next steps that are summarized at the end of the meeting and are used to conclude the meeting.

[1264] "Convert to text" is the process of converting audio data or other forms of information into written information.

[1265] "Key points" are the main issues or decisions to be discussed during the meeting.

[1266] Minutes are documents that record what was said and decided during a meeting, and are used to review the contents of the meeting later.

[1267] "Emotions" refer to the psychological state of participants as perceived from their facial expressions and voices, and affect the progress and atmosphere of the meeting.

[1268] "Emotion data" is data that expresses the emotional state of participants in numerical values ​​or categories, and is used to adjust the progress of the meeting.

[1269] This system aims to support meetings within factories, and can consistently and efficiently handle everything from meeting preparation to progress and follow-up. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting.

[1270] Agenda creation

[1271] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide on Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[1272] Schedule confirmation and meeting notifications

[1273] The server receives the participant list and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds common free time and selects the optimal meeting time. It then sends a notification to the participants based on this information. The notification includes the meeting date, time, location, and agenda. For example, if participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[1274] Supporting meeting progress with an emotion engine

[1275] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[1276] Conference facilitator support

[1277] The server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, comments are generated based on the user's emotional state. For example, specific, positive comments such as "Please tell us more about your opinion" are generated. The device (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing statement of the discussion are generated in real time as the meeting progresses and provided to the facilitator.

[1278] Minutes creation

[1279] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[1280] Email distribution of meeting minutes

[1281] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[1282] Hardware or software used

[1283] server

[1284] User devices (smartphones, tablets, desktop PCs, etc.)

[1285] Calendar API (e.g. Google Calendar API)

[1286] Emotion recognition library (e.g., EmotionRecognition)

[1287] Speech recognition library (e.g., SpeechRecognition)

[1288] Natural language processing libraries (e.g., NLP)

[1289] Prompt Sentence Examples

[1290] Theme: Project progress

[1291] Objective: Determine next steps

[1292] It analyzes the content of meeting discussions in real time and generates comments such as "Let's take a short break and then resume" if participants seem frustrated.

[1293] In this way, by using this system, meeting support within the factory will be made more efficient and the meeting will proceed in an optimal manner according to the user's emotions.

[1294] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1295] Step 1:

[1296] The server receives the meeting theme and purpose from the user. As input, the "meeting theme" and "purpose" provided by the user are required. Based on these inputs, the server refers to its internal database and selects relevant topics. Through this data processing, it automatically generates an agenda and sends the generated agenda as output to the user's terminal.

[1297] Step 2:

[1298] The server receives the participant list from the user. After receiving the participant list as input, it checks the schedule information of each participant using a calendar API. The server analyzes the schedule data and finds common free time through data calculations. As a result, it selects the optimal meeting time and sends a notification. This notification includes the meeting date and time, location, and agenda. As output, a notification of the specified date, time, and location is sent to the participant's device.

[1299] Step 3:

[1300] The server uses an AI model during the meeting to generate comments, discussion summaries, and closing statements in real time. It uses the meeting's audio data as input, performs speech recognition, and converts it into text data. Based on this, the generative AI model calculates the comments and discussion summaries, which are presented to the facilitator in real time. The generated comments and summaries are displayed on the facilitator's device as output.

[1301] Step 4:

[1302] The server uses an emotion engine to recognize the emotions of participants during a meeting in real time. Audio and video data are used as input. The emotion engine analyzes the emotion data and recognizes the user's emotional state. Based on this, it generates comments to adjust the progress of the meeting and provides them to the facilitator. For example, if a user feels irritated or tired, it outputs a comment such as "Let's take a short break and resume," and displays it on the facilitator's device.

[1303] Step 5:

[1304] The server receives the audio files of the meeting and converts them into text using speech recognition technology. The audio files recorded during the meeting are required as input. Natural language processing technology is used to extract important points from the converted text data. This data processing process organizes the main points and generates minutes of the meeting. As an output, the generated minutes are provided to the user for confirmation.

[1305] Step 6:

[1306] The server distributes the minutes by email based on the participant list. The input requires the confirmed minutes and the participant list. The server sends the minutes to each participant's email address. As an output, minutes are sent to all participants' email addresses to reconfirm the contents of the meeting. This allows them to take the next step.

[1307] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1308] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1309] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1310] [Fourth embodiment]

[1311] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1312] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1313] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1314] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1315] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1316] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1317] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1318] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1319] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1320] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1321] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1322] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1323] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1324] The present invention is a system that can consistently and efficiently carry out the entire process from preparation to progress of a meeting, to follow-up after the meeting has ended. A specific embodiment of this system will be described below.

[1325] Agenda creation

[1326] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[1327] Schedule confirmation and meeting notifications

[1328] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[1329] Conference facilitator support

[1330] The server uses an AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[1331] Minutes creation

[1332] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. The generated minutes are then sent to the user's device for review.

[1333] Email distribution of meeting minutes

[1334] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[1335] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and all participants can share information smoothly.

[1336] The processing flow will be explained below.

[1337] Program processing steps

[1338] Pre-meeting preparation

[1339] Step 1:

[1340] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[1341] Step 2:

[1342] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[1343] Step 3:

[1344] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[1345] Step 4:

[1346] The user inputs a list of participants and registers them in the system.

[1347] Step 5:

[1348] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[1349] Step 6:

[1350] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[1351] Step 7:

[1352] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[1353] Meeting progress

[1354] Step 8:

[1355] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[1356] Step 9:

[1357] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[1358] Step 10:

[1359] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[1360] Post-meeting process

[1361] Step 11:

[1362] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[1363] Step 12:

[1364] The server uses natural language processing technology to extract important points from the converted text, organizes the main points, and creates minutes.

[1365] Step 13:

[1366] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[1367] Step 14:

[1368] The user approves the confirmed minutes.

[1369] Step 15:

[1370] The server distributes the final confirmed minutes by email based on the participant list.

[1371] By following these steps, a system can be created that can efficiently execute the entire process from preparing for a meeting to conducting and following up on it.

[1372] Example 1

[1373] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1374] Preparing for, conducting, and following up on a meeting requires a lot of time and effort. Creating an agenda, coordinating participants' schedules, encouraging participants to speak during the meeting, and creating minutes are often done manually, resulting in inefficiencies. Furthermore, if these tasks are not performed thoroughly, the quality of the meeting may decline and its effectiveness may be impaired. This invention aims to solve these problems by providing a system that automates and streamlines the entire process of a meeting.

[1375] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1376] In this invention, the server includes means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose, means for receiving a participant list, checking the schedules of each participant, selecting a common free time and sending a notification, means for generating remarks, comments, a discussion summary and closing content in real time using a generative AI model during the meeting, means for converting the speech of the meeting into text and extracting important points to create minutes, and means for distributing the created minutes to participants by email. This makes it possible to consistently streamline the processes of preparing, conducting and following up on a meeting.

[1377] "Conference theme and objectives" refers to the central topics or subjects to be discussed at the conference and the purpose for which the conference is being held.

[1378] An "agenda" is a document that lists the items or topics to be discussed at a meeting and the order in which they will be discussed.

[1379] "Participant List" means a list of names and contact information for people who will be attending a meeting.

[1380] "Schedule" refers to the schedule information and free time of each participant.

[1381] "Notification" refers to a message sent to inform participants of information such as the date, time, location, and content of a meeting.

[1382] "Generative AI models" refer to algorithms or systems that use artificial intelligence to generate comments, discussion summaries, and closing statements during meetings in real time.

[1383] "Meeting audio" refers to the content of conversations and discussions that occur during a meeting.

[1384] "Convert to text" refers to the process of converting audio data into text data using language processing techniques.

[1385] "Key points" refer to the main points and conclusions extracted from the discussions during the meeting.

[1386] "Minutes" refers to a document that records the contents of discussions, important remarks, decisions, etc. that took place during a meeting.

[1387] "Delivery by email" refers to the act of sending specific information to a designated recipient using email.

[1388] "Schedule Management API" means an application programming interface used to obtain schedules and availability of participants.

[1389] The present invention is a system for efficiently preparing for a meeting, conducting the meeting, and following up after the meeting. This system operates mainly by exchanging data between a server, terminals, and users. Specific embodiments of the present invention are described below.

[1390] First, the user inputs the topic and purpose of the meeting. For example, prompts such as "Topic: Project progress" or "Objective: Decide next steps" are entered. This input is entered as text information into a form on the user's device and sent to the server by pressing the send button.

[1391] The server then refers to its internal database based on the theme and purpose provided by the user to select relevant topics. This involves searching for relevant data using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" from past data related to the theme "Project Progress." The server then uses an AI model to automatically generate an agenda and sends it to the user's device. This process uses a template-based approach to generate the agenda.

[1392] Next, the user checks the contents of the agenda and makes corrections or additional comments as necessary. This checking is done by checking the contents of the agenda displayed on the terminal.

[1393] After that, the user uploads the list of participants for the meeting. This information is provided via a CSV file or a web form. The server receives the participant list and uses a schedule management API to check each participant's schedule. For example, it uses the Google Calendar API to obtain each participant's free time and selects a common free time based on that information.

[1394] The selected meeting time is sent to all participants as a notification by the server, which includes the date, time, location and agenda of the meeting. This notification is sent using a mail server.

[1395] During the meeting, the server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time. For example, comments such as "Please tell us your opinion on this point" are generated to support the progress of the meeting. The server also monitors the progress of the discussion and provides summaries and closing comments at appropriate times, thereby improving the efficiency of the meeting.

[1396] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology. Specifically, it uses the Google Speech-to-Text API to convert the audio data into text. It then uses natural language processing technology to extract key points and automatically generate minutes. These minutes are then sent to the user's device.

[1397] Finally, the server distributes the generated minutes to the participants by email. For example, minutes containing the meeting schedule and content, agenda, and decisions are sent to the participants' mailboxes.

[1398] In this way, the system of the present invention consistently improves efficiency from meeting preparation to progress and follow-up, making the entire business process smoother.

[1399] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1400] Step 1:

[1401] The user inputs the topic and purpose of the meeting.

[1402] Input: Theme "Project Progress", Objective "Determine next steps"

[1403] Output: The input data is sent to the server

[1404] Specific operation: The user enters the topic and purpose into the form on the terminal and presses the submit button, which sends the data to the server.

[1405] Step 2:

[1406] The server consults an internal database based on the received theme and purpose.

[1407] Input: Theme and Objective Data

[1408] Output: Related topics

[1409] Specific operation: The server uses input data as a trigger to search the database for related topics using SQL queries. For example, it extracts "Topic A," "Topic B," and "Topic C" as topics related to "Project Progress."

[1410] Step 3:

[1411] The server automatically generates an agenda based on relevant topics.

[1412] Input: Related topics

[1413] Output: Auto-generated agenda

[1414] How it works: Using an AI model, the extracted topics are incorporated into a template to automatically generate an agenda, which is then sent to the user's device.

[1415] Step 4:

[1416] The user checks the contents of the agenda.

[1417] Input: Auto-generated agenda

[1418] Output: Confirmed agenda, comments or corrections

[1419] Specific operation: The user checks the contents of the agenda displayed on the terminal and makes corrections or additional comments if necessary.

[1420] Step 5:

[1421] The user uploads the participant list.

[1422] Input: Participant list (e.g., CSV file)

[1423] Output: The participant list is sent to the server

[1424] Specific operation: The user selects the participant list from the terminal and presses the upload button to send it to the server.

[1425] Step 6:

[1426] The server uses a schedule management API to check the schedule of each participant.

[1427] Input: Participant list

[1428] Output: Free time for each participant

[1429] Specific operation: Using the Google Calendar API, etc., a request is sent to check the free time of participants. The server aggregates the obtained free time and finds common free time.

[1430] Step 7:

[1431] The server selects the best meeting time and sends a notification.

[1432] Input: Availability of each participant

[1433] Output: Meeting notification

[1434] Specific operation: Calculates common free time based on the obtained free time information and selects the optimal meeting time. Sends a notification containing the selected meeting time and agenda to all participants using a mail server.

[1435] Step 8:

[1436] The server uses the generative AI model to generate comments in real time during the meeting.

[1437] Input: Meeting progress

[1438] Output: Comment

[1439] How it works: Using a generative AI model, it generates comments in real time, allowing the facilitator to encourage discussion.

[1440] Step 9:

[1441] The server generates a discussion summary and closing message.

[1442] Input: Meeting progress

[1443] Output: Summary and closing message

[1444] What it does: It uses natural language processing technology to extract key points and conclusions, and generates summaries and closing messages at appropriate times during the meeting.

[1445] Step 10:

[1446] The server receives the audio files of the conference and uses speech recognition technology to convert the speech to text.

[1447] Input: Meeting audio file

[1448] Output: Text data

[1449] Specific operation: After the meeting ends, the meeting audio is uploaded to the server and the audio data is converted to text using the Google Speech-to-Text API or similar.

[1450] Step 11:

[1451] The server extracts important points and creates minutes.

[1452] Input: Text data

[1453] Output:Minutes

[1454] Specific operation: Uses natural language processing technology to extract key points from text data and automatically generate meeting minutes.

[1455] Step 12:

[1456] The server transmits the generated minutes to the user's terminal.

[1457] Input: Minutes

[1458] Output: Confirmed transcript

[1459] Specific operation: The automatically generated minutes are sent to the user's device and the user confirms them.

[1460] Step 13:

[1461] The server distributes the confirmed minutes to the participants by email.

[1462] Input: Confirmed minutes

[1463] Output: Delivered minutes

[1464] Specific operation: The confirmed minutes are distributed to all participants via the mail server.

[1465] (Application example 1)

[1466] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1467] Currently, there is no system in place that can efficiently manage the progress of work within the factory, from preparing for meetings to proceeding with them and following up after they have been completed. In particular, it is difficult for each worker and manager to grasp the work situation in real time and receive appropriate instructions, and there is a problem that important incidents are not recorded and shared on the spot. This hinders work efficiency and the effective progress of meetings.

[1468] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1469] In this invention, the server includes means for receiving the theme and purpose of a meeting and automatically generating an agenda based on the theme and purpose, means for receiving a list of participants, checking each participant's schedule, selecting a common free time and sending a notification, means for generating comments, a discussion summary, and closing content in real time using a generative AI model during the meeting, means for converting the meeting audio into text and extracting important points to create minutes, means for distributing the created minutes to participants by email, means for checking the progress of work in the factory in real time and providing instructions for the next step with audio and visual information, and means for recording and sharing important incidents on the spot using a smart device, thereby enabling more efficient work in the factory and more effective meetings.

[1470] An "agenda" is a plan that summarizes the topics and progress of a meeting or discussion.

[1471] A "generative AI model" is a software system that uses artificial intelligence techniques to analyze data and automatically generate sentences and responses.

[1472] "Speech comments" are comments that include suggestions or questions to assist participants in making statements during a meeting.

[1473] A "discussion summary" is a concise summary of the discussions that took place during the meeting.

[1474] "Closing content" is content that summarizes the discussion and provides next steps at the end of the meeting.

[1475] "Speech-to-text" is the process of converting spoken words into written information using speech recognition technology.

[1476] Minutes are a written record of what was said at a meeting that can be referenced later.

[1477] "Inside the factory" refers to the interior of a building or facility where manufacturing operations take place.

[1478] "Progress of work" is information that indicates the current achievement level and progress of work or tasks.

[1479] "Guiding with audio and visual information" means providing instructions and guidance using audio and visual methods.

[1480] "Smart devices" generally refer to electronic devices that can connect to the Internet and have a variety of functions, such as smartphones and smart glasses.

[1481] "Incident" means an unexpected occurrence or problem, including any particularly problematic situation or accident.

[1482] "Real-time" refers to processing or operations that are performed in synchronization with actual time.

[1483] The present invention is a system that can efficiently and consistently manage the progress of work in a factory, as well as the preparation, progress, and post-conference follow-up of meetings. Specific embodiments of this system are described below.

[1484] Agenda creation

[1485] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Agenda A," "Agenda B," and "Agenda C" are automatically generated.

[1486] Schedule confirmation and meeting notifications

[1487] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[1488] Conference facilitator support

[1489] The server uses the generative AI model to generate comments, discussion summaries, and closing messages in real time during a meeting. This allows the facilitator to encourage participation and efficiently manage the meeting. For example, a comment such as "Please tell us your opinion on this point" can be generated, making it easier for participants to actively express their opinions. The server also monitors the progress of the meeting and generates discussion summaries and closing messages at appropriate times.

[1490] Minutes creation

[1491] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. This process uses technologies such as Google's speech recognition API. The generated minutes are then sent to the user's device for review.

[1492] Email distribution of meeting minutes

[1493] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[1494] Real-time confirmation and instructions for factory operations

[1495] The server allows users to check the progress of work in real time through smart devices (e.g., smart glasses) worn in the factory. This allows instructions for the next step to be given through voice and visual information, improving work efficiency. For example, when a specific process is completed, an automatic instruction such as "Start process X next" is issued.

[1496] Recording and sharing critical incidents

[1497] Users can use their smart devices to record important incidents in real time and send them to a server. The server then immediately shares the received incident information with relevant personnel and managers. For example, when a facility failure is detected, on-site workers can take a picture of the faulty area through smart glasses and upload it to the server, enabling a prompt response.

[1498] Prompt Sentence Examples

[1499] Below are some examples of specific prompt sentences.

[1500] "Prepare for a meeting to decide next steps for project progress. The participants are Person A and Person B. Check your mutual availability and communicate an appropriate meeting time."

[1501] In this way, by using the system of the present invention, it is possible to improve the efficiency of work within a factory and to conduct meetings effectively.

[1502] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1503] Step 1:

[1504] The server receives the meeting topic and purpose from the user. For example, the topic and purpose can be "Project Progress" and "Determine Next Steps." Based on this input, the server references its internal database and selects relevant topics. This data reference process is performed by searching the database for past meeting records and standard agenda lists to extract relevant topics. The output is an automatically generated agenda.

[1505] Step 2:

[1506] The server sends the generated agenda to the user's device. The user checks the agenda on the device and makes any necessary modifications. During this modification process, the user adds additional agenda items or deletes unnecessary items. The modified agenda is then resent from the device to the server, and the final agenda is confirmed. The input is the generated agenda, and the output is the final confirmed agenda.

[1507] Step 3:

[1508] The server receives the list of participants and checks each participant's schedule. This check process involves using a calendar API to obtain participants' free time slots. The server then saves the obtained schedule information in a database and compares the schedules of all participants to find common free time slots. The output is the optimal meeting time.

[1509] Step 4:

[1510] The server creates a meeting notice based on the optimal meeting time and the confirmed agenda. The generated meeting notice includes the meeting date, time, location, and agenda. This meeting notice is sent to participants via email or calendar invitation. The input is the optimal meeting time and agenda, and the output is the meeting notice.

[1511] Step 5:

[1512] During the meeting, the server uses a generative AI model to generate comments, discussion summaries, and closing statements in real time. This information is generated at the appropriate time while monitoring the progress of the meeting and displayed on the facilitator's device. Users can proceed with the meeting while referring to the displayed information. The input is the audio data and progress of the meeting, and the output is comments, discussion summaries, and closing statements.

[1513] Step 6:

[1514] The server receives the audio file of the meeting and converts it into text using speech recognition technology. During the conversion process, the audio data is analyzed using Google's speech recognition API and converted into text information. Key points are extracted from this text data using natural language processing technology. The extracted key points are organized to create minutes of the meeting and sent to the user's device. The input is the audio file of the meeting, and the output is the generated minutes.

[1515] Step 7:

[1516] The server distributes the confirmed minutes by email based on the participant list. In this distribution process, the generated minutes are formatted as the body of an email and sent to the participants' email addresses. This allows participants to review the contents of the meeting and take further action. The input is the generated minutes, and the output is the email in which the minutes were distributed.

[1517] Step 8:

[1518] The server allows users to check the progress of work in real time through smart devices worn in the factory. In this process, the server analyzes data sent from the smart device in real time and provides instructions for the next step through audio and visual information. For example, when a specific process is completed, an instruction such as "Please start process X next" is automatically generated and displayed on the user's device. The input is data from the smart device, and the output is the generated instruction.

[1519] Step 9:

[1520] Users use smart devices to record important incidents in real time and send them to a server. In this process, users use their smart devices to record images and text of incidents and upload them to the server. The server analyzes the received incident information and immediately shares it with relevant personnel and managers. The input is the incident information recorded by the user, and the output is the analyzed incident information and its sharing.

[1521] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1522] The present invention is a system that can consistently and efficiently handle everything from preparing for a meeting to proceeding with it and follow-up after it has ended, and it also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of this system are described below.

[1523] Agenda creation

[1524] The server first receives the meeting theme and purpose from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[1525] Schedule confirmation and meeting notifications

[1526] The server receives the list of participants and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds a common free time. It then selects the optimal meeting time and sends a notification to the participants. The notification includes the meeting date, time, location, and agenda. For example, if the participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[1527] Supporting meeting progress with an emotion engine

[1528] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[1529] Conference facilitator support

[1530] The server monitors the progress of the meeting and presents comments to the facilitator at appropriate times. Using data from the emotion engine, it generates comments that reflect the user's emotional state. For example, it generates specific, positive comments such as, "Please tell us more about your opinion."

[1531] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing of the discussion are generated in real time as the discussion progresses and provided to the facilitator.

[1532] Minutes creation

[1533] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[1534] Email distribution of meeting minutes

[1535] The server distributes the confirmed minutes by email based on the participant list. By receiving the email, participants can reconfirm the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions are distributed.

[1536] In this way, by using the system of the present invention, the preparation, progress, and follow-up of a meeting can be made more efficient, and the meeting can be optimally progressed according to the emotional state of the user.

[1537] The processing flow will be explained below.

[1538] Program processing steps

[1539] Pre-meeting preparation

[1540] Step 1:

[1541] The user inputs the topic and purpose of the meeting, which helps the system understand the subject of the meeting.

[1542] Step 2:

[1543] The server searches for relevant topics from an internal database based on the theme and purpose input by the user, and automatically generates an agenda.

[1544] Step 3:

[1545] The server transmits the generated agenda to the user's terminal, allowing the user to review the agenda and modify it as necessary.

[1546] Step 4:

[1547] The user inputs a list of participants and registers them in the system.

[1548] Step 5:

[1549] The server receives the list of participants and checks the schedule of each participant using a calendar API.

[1550] Step 6:

[1551] The server finds common free time from the acquired schedule information and selects the optimal meeting time.

[1552] Step 7:

[1553] The server emails the meeting notice to the participants, including the selected meeting time and the generated agenda.

[1554] Meeting progress

[1555] Step 8:

[1556] The server monitors the progress of the conference and presents comments to the facilitator at appropriate times.

[1557] Step 9:

[1558] The terminal (facilitator) checks the comments provided by the server and uses them at the appropriate time.

[1559] Step 10:

[1560] The server uses an emotion engine to recognize the user's emotions and adjusts the comments, discussion summary, and closing statement in real time. For example, if the user is frustrated, the server generates a comment such as "Let's take a short break and resume."

[1561] Step 11:

[1562] The server generates a summary and closing contents of the discussion in real time as the meeting progresses and provides them to the facilitator.

[1563] Step 12:

[1564] The terminal (facilitator) checks the summary and closing content provided by the server and uses them at the appropriate time.

[1565] Post-meeting process

[1566] Step 13:

[1567] The server receives the audio files of the conference and converts them into text using speech recognition technology.

[1568] Step 14:

[1569] The server uses natural language processing technology to extract important points from the converted text and create minutes, while an emotion engine also reflects the user's emotional state as information.

[1570] Step 15:

[1571] The server transmits the generated minutes to the user's terminal, and the user checks the minutes.

[1572] Step 16:

[1573] The user approves the confirmed minutes.

[1574] Step 17:

[1575] The server distributes the final confirmed minutes by email based on the participant list.

[1576] In this way, by using the system of the present invention, the entire process from preparing for a meeting to conducting it and following up can be carried out efficiently, and the optimal progress can be achieved according to the emotional state of the user.

[1577] Example 2

[1578] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1579] In conventional conferencing systems, preparation, progress, and follow-up of meetings were carried out separately, making efficient operation difficult. Furthermore, it was not possible to adjust the progress of the meeting by taking into account the user's emotional state, which made it easy for participants to feel fatigued or stressed. Furthermore, it was difficult to generate summaries of comments and discussions in real time, making it difficult to conduct meetings quickly and accurately.

[1580] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving the theme and purpose of the meeting and automatically generating an agenda based on the theme and purpose; means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification; means for generating remarks, comments, a discussion summary, and closing content in real time using a generative AI model during the meeting; means for converting the meeting audio into text, extracting important points, and creating minutes; means for distributing the created minutes to participants by email; and means including an emotion engine that recognizes emotions from the user's facial expressions and voice during the meeting and adjusts the progress of the meeting based on the recognized emotions. This not only enables consistent and efficient preparation, progress, and follow-up of the meeting, but also enables optimal progress according to the user's emotional state.

[1581] "Theme" refers to the subject matter of the conference or the issue area that will be the focus of discussion.

[1582] "Purpose" refers to the specific goals or results that the meeting aims to achieve.

[1583] An "agenda" refers to a list of topics or items to be discussed at a meeting.

[1584] "Participant List" means the list of individuals or entities that will be attending a Conference.

[1585] A "schedule" indicates the schedule and free time of each participant during a specific period.

[1586] "Notification" refers to a means of communication to inform participants of information such as the date, time, location, and agenda of a meeting.

[1587] "Generative AI model" refers to a model that uses artificial intelligence technology to automatically generate text and comments from data.

[1588] A "summary" is a concise summary of what was discussed and said during a meeting.

[1589] "Closing content" refers to the summary and instructions for next steps given at the end of the meeting.

[1590] "Speech recognition technology" refers to technology that converts speech into text.

[1591] "Natural language processing technology" refers to technology for analyzing text data and performing semantic analysis and information extraction.

[1592] An "emotion engine" is a system that recognizes emotions from a user's facial expressions and voice, and generates appropriate comments and actions based on that information.

[1593] "Email" refers to a means for sending and receiving communications over a network such as the Internet.

[1594] The present invention is a system that can consistently and efficiently prepare for, conduct, and follow up on a meeting after it has ended. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting. Specific embodiments of the present invention are described below.

[1595] First, the user inputs the theme and purpose of the meeting into the system. Based on this theme and purpose, the server references its internal database and automatically generates an agenda. For example, if the theme is "New Product Development Meeting" and the purpose is "Schedule Adjustment," the server will automatically generate topics such as "Sharing Market Research Results," "Identifying Technical Issues," and "Promotion Plan." The generated agenda is sent to the user's device, where the user can check the contents.

[1596] The server then receives a list of participants who will attend the meeting. Based on this list, the server uses a calendar API (e.g., Google Calendar API or Microsoft Outlook API) to check each participant's schedule. It then finds common free time slots, selects the optimal meeting time, and sends notifications to participants. The notifications include the meeting date, time, location, and agenda. For example, if participants' free time slots are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," the server selects "Tuesday 14:00-15:00" as the common free time slot.

[1597] During the meeting, the server uses an emotion engine to recognize emotions in real time from the user's facial expressions and voice. For example, if a user feels irritated or tired, the server will generate a relaxing comment such as "Let's take a short break and resume," and provide it to the facilitator. The emotion engine uses, for example, IBM Watson Tone Analyzer or Microsoft Azure Emotion API.

[1598] Furthermore, the server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, positive comments such as "Please tell us more about your opinion" are generated as specific examples based on the user's emotional state. The facilitator checks the comments provided by the server and uses them at the appropriate time. Additionally, a discussion summary and closing statement are generated in real time as the meeting progresses and provided to the facilitator.

[1599] After the meeting ends, the server receives the audio file and converts it into text using speech recognition technology (e.g., Google Cloud Speech-to-Text or Amazon Transcribe). It then uses natural language processing technology (e.g., NLTK or spaCy) to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also used in this process, generating minutes that reflect the user's emotional state.

[1600] Finally, the server distributes the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. The minutes include key points such as the meeting schedule and content, agenda, and decisions.

[1601] Prompt Sentence Examples

[1602] 1. Example agenda-building prompts:

[1603] The theme of the meeting is "New Product Development Meeting" and the purpose is "Schedule Adjustment." Please generate a relevant agenda.

[1604] 2. Example prompts for support from the Emotion Engine:

[1605] A user appears frustrated during a meeting. Generate a comment to encourage them to relax.

[1606] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1607] Processing step details

[1608] Step 1:

[1609] The user enters the topic and purpose of the meeting.

[1610] Input: Meeting topic (e.g., "New Product Development Meeting") and purpose (e.g., "Scheduling").

[1611] How it works: The user enters the subject and purpose into the system's input form.

[1612] Output: The input data is sent to the server.

[1613] Step 2:

[1614] The server refers to an internal database, selects relevant topics, and generates an agenda.

[1615] Input: The subject and purpose entered by the user.

[1616] How it works: Based on the theme and purpose, the server queries a database such as MySQL or PostgreSQL to retrieve relevant topics. This allows topics such as "Sharing market research results" and "Identifying technical issues" to be selected. An agenda is generated based on this.

[1617] Output: The generated agenda.

[1618] Step 3:

[1619] The server sends the generated agenda to the user's terminal.

[1620] Input: The generated agenda.

[1621] How it works: The server converts the agenda into JSON or XML format and sends it to the user's device.

[1622] Output: The agenda displayed on the user's terminal.

[1623] Step 4:

[1624] The user checks the agenda on the device and makes any necessary corrections.

[1625] Input: User feedback (suggested corrections).

[1626] Action: The user enters any necessary corrections to the confirmed agenda and submits it to the system.

[1627] Output: The revised agenda.

[1628] Step 5:

[1629] The user enters the participant list for the meeting.

[1630] Input: Participant list.

[1631] How it works: A user enters the names and contact information of participants into the system.

[1632] Output: The input data is sent to the server.

[1633] Step 6:

[1634] The server uses the calendar API to check the schedules of participants.

[1635] Input: Participant list.

[1636] How it works: The server uses the Google Calendar API or Microsoft Outlook API to retrieve the schedules of each participant.

[1637] Output: Schedule data for each participant.

[1638] Step 7:

[1639] The server finds common free time and selects the best time to meet.

[1640] Input: Schedule data for each participant.

[1641] How it works: The server parses the schedule data and identifies common free times.

[1642] Output: The best meeting time selected.

[1643] Step 8:

[1644] The server sends a meeting notification to the participants.

[1645] Input: Selected meeting time, location, and agenda.

[1646] How it works: The server generates notifications and sends them to participants via email or a notification system.

[1647] Output: Meeting notification sent to participants.

[1648] Step 9:

[1649] The server activates an emotion engine and recognizes emotions from the facial expressions and voices of users during the meeting.

[1650] Input: Audio and video data during the conference.

[1651] How it works: The server analyzes emotions using an emotion engine (e.g., IBM Watson Tone Analyzer or Microsoft Azure Emotion API), which identifies the user's emotions, such as "irritation" or "tiredness."

[1652] Output: User emotion data.

[1653] Step 10:

[1654] The server generates comments and summaries of the meeting progress in real time based on the emotional data.

[1655] Input: User emotion data and meeting progress data.

[1656] How it works: The server uses a generative AI model to generate a comment, such as "Let's take a short break and then resume."

[1657] Output: Generated comments and summaries.

[1658] Step 11:

[1659] The server presents comments to the facilitator and monitors progress.

[1660] Input: Generated comments and summaries.

[1661] How it works: The server presents comments in real time to the facilitator's device and keeps track of the progress.

[1662] Output: Comments displayed on the facilitator's terminal.

[1663] Step 12:

[1664] The server receives the audio file of the meeting and converts it into text using speech recognition technology.

[1665] Input: Meeting audio file.

[1666] How it works: The server converts speech to text using Google Cloud Speech-to-Text or Amazon Transcribe.

[1667] Output: The converted text data.

[1668] Step 13:

[1669] The server extracts key points and creates minutes.

[1670] Input: Text data.

[1671] How it works: The server uses natural language processing technology (e.g., NLTK or spaCy) to extract important points, organize the main points, and create meeting minutes. It may also use data from the emotion engine.

[1672] Output: The generated transcript.

[1673] Step 14:

[1674] The server will deliver the confirmed minutes to the participants by email.

[1675] Input: Generated meeting minutes and participant list.

[1676] What it does: The server creates emails and distributes the minutes to participants.

[1677] Output: Minutes delivered to participants.

[1678] (Application example 2)

[1679] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1680] While conventional meeting support systems can efficiently prepare, conduct, and follow up on meetings, they are unable to take into account the emotions of participants during the meeting, which can affect participants' motivation and the progress of the meeting. Furthermore, in factory meetings, in particular, many participants are pressed for time and work, making it necessary to further improve the efficiency of meetings. Therefore, there is a need for a system that can recognize the emotional state of participants during a meeting in real time and adjust the progress of the meeting based on that information.

[1681] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically generating an agenda based on the theme and purpose of the meeting, means for receiving a participant list, checking each participant's schedule, selecting a common free time, and sending a notification, means for generating remarks, comments, a discussion summary, and closing content in real time using an AI model during the meeting, means for converting the meeting audio into text, extracting important points, and creating minutes, means for distributing the created minutes to participants by email, and means for recognizing the emotions of participants during the meeting and adjusting the progress based on the emotion data. This enables consistent and efficient processing from meeting preparation to progress and follow-up, and further enables the meeting to proceed optimally in accordance with the emotions of the participants.

[1682] A "meeting theme" is a specific topic or agenda that is central to the meeting and determines the purpose and direction of the meeting.

[1683] "Purpose" is the specific goal or intention to be achieved in the meeting, and is the standard for the success of the meeting.

[1684] An "agenda" is a list of topics and schedules for a meeting, and is used to indicate the structure of the meeting.

[1685] A "participant list" is a list of people who will be attending a meeting, and is the basic information for organizing and announcing the meeting.

[1686] "Schedule" is information indicating the participants' schedules and free time, and is used to determine the date and time of the conference.

[1687] "Notification" is a means of communication to inform participants of the date, time, location, agenda, etc. of a meeting.

[1688] An "AI model" is an algorithm or program that uses artificial intelligence, and is a means of automating data analysis and decision-making.

[1689] "Comments" are opinions or responses made during a meeting to encourage discussion.

[1690] A "discussion summary" is a concise summary of the important discussions and conclusions that took place during the meeting, and is used to guide the progress of the meeting and subsequent actions.

[1691] "Closing content" is information about conclusions and next steps that are summarized at the end of the meeting and are used to conclude the meeting.

[1692] "Convert to text" is the process of converting audio data or other forms of information into written information.

[1693] "Key points" are the main issues or decisions to be discussed during the meeting.

[1694] Minutes are documents that record what was said and decided during a meeting, and are used to review the contents of the meeting later.

[1695] "Emotions" refer to the psychological state of participants as perceived from their facial expressions and voices, and affect the progress and atmosphere of the meeting.

[1696] "Emotion data" is data that expresses the emotional state of participants in numerical values ​​or categories, and is used to adjust the progress of the meeting.

[1697] This system aims to support meetings within factories, and can consistently and efficiently handle everything from meeting preparation to progress and follow-up. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the progress of the meeting.

[1698] Agenda creation

[1699] The server first receives the theme and purpose of the meeting from the user. Based on this input, it references an internal database and selects related topics. This automatically generates an agenda. The generated agenda is then sent to the user's device, where the user can check the contents. For example, if the theme is "Project Progress" and the purpose is "Decide on Next Steps," related topics such as "Topic A," "Topic B," and "Topic C" are automatically generated.

[1700] Schedule confirmation and meeting notifications

[1701] The server receives the participant list and checks each participant's schedule using a calendar API. Based on the obtained schedule information, it finds common free time and selects the optimal meeting time. It then sends a notification to the participants based on this information. The notification includes the meeting date, time, location, and agenda. For example, if participants' free times are "Monday 10:00-11:00" and "Tuesday 14:00-15:00," Tuesday 14:00-15:00 is selected as the common free time.

[1702] Supporting meeting progress with an emotion engine

[1703] The server uses an emotion engine to recognize emotions from users' facial expressions and voices during the meeting. Based on this information, it adjusts comments, discussion summaries, and closing statements in real time. Specifically, if a user feels irritated or tired, it generates a more relaxing comment and provides it to the facilitator. For example, it might generate a comment such as, "Let's take a short break and then resume."

[1704] Conference facilitator support

[1705] The server monitors the progress of the meeting and presents comments to the facilitator at the appropriate time. Utilizing data from the emotion engine, comments are generated based on the user's emotional state. For example, specific, positive comments such as "Please tell us more about your opinion" are generated. The device (facilitator) checks the comments provided by the server and uses them at the appropriate time. In addition, a summary and closing statement of the discussion are generated in real time as the meeting progresses and provided to the facilitator.

[1706] Minutes creation

[1707] The server receives the audio file of the meeting and converts it into text using speech recognition technology. It then uses natural language processing technology to extract key points from the converted text, organizes the main points, and creates minutes. Emotional data from the emotion engine is also utilized in this process, allowing the minutes to be generated in a way that reflects the user's emotional state.

[1708] Email distribution of meeting minutes

[1709] The server will then distribute the confirmed minutes via email based on the participant list. By receiving the email, participants can review the contents of the meeting and take action accordingly. For example, minutes containing key points such as the meeting schedule and content, agenda, and decisions will be distributed.

[1710] Hardware or software used

[1711] server

[1712] User devices (smartphones, tablets, desktop PCs, etc.)

[1713] Calendar API (e.g. Google Calendar API)

[1714] Emotion recognition library (e.g., EmotionRecognition)

[1715] Speech recognition library (e.g., SpeechRecognition)

[1716] Natural language processing libraries (e.g., NLP)

[1717] Prompt Sentence Examples

[1718] Theme: Project progress

[1719] Objective: Determine next steps

[1720] It analyzes the content of meeting discussions in real time and generates comments such as "Let's take a short break and then resume" if participants seem frustrated.

[1721] In this way, by using this system, meeting support within the factory will be made more efficient and the meeting will proceed in an optimal manner according to the user's emotions.

[1722] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1723] Step 1:

[1724] The server receives the meeting theme and purpose from the user. As input, the "meeting theme" and "purpose" provided by the user are required. Based on these inputs, the server refers to its internal database and selects relevant topics. Through this data processing, it automatically generates an agenda and sends the generated agenda as output to the user's terminal.

[1725] Step 2:

[1726] The server receives the participant list from the user. After receiving the participant list as input, it checks the schedule information of each participant using a calendar API. The server analyzes the schedule data and finds common free time through data calculations. As a result, it selects the optimal meeting time and sends a notification. This notification includes the meeting date and time, location, and agenda. As output, a notification of the specified date, time, and location is sent to the participant's device.

[1727] Step 3:

[1728] The server uses an AI model during the meeting to generate comments, discussion summaries, and closing statements in real time. It uses the meeting's audio data as input, performs speech recognition, and converts it into text data. Based on this, the generative AI model calculates the comments and discussion summaries, which are presented to the facilitator in real time. The generated comments and summaries are displayed on the facilitator's device as output.

[1729] Step 4:

[1730] The server uses an emotion engine to recognize the emotions of participants during a meeting in real time. Audio and video data are used as input. The emotion engine analyzes the emotion data and recognizes the user's emotional state. Based on this, it generates comments to adjust the progress of the meeting and provides them to the facilitator. For example, if a user feels irritated or tired, it outputs a comment such as "Let's take a short break and resume," and displays it on the facilitator's device.

[1731] Step 5:

[1732] The server receives the audio files of the meeting and converts them into text using speech recognition technology. The audio files recorded during the meeting are required as input. Natural language processing technology is used to extract important points from the converted text data. This data processing process organizes the main points and generates minutes of the meeting. As an output, the generated minutes are provided to the user for confirmation.

[1733] Step 6:

[1734] The server distributes the minutes by email based on the participant list. The input requires the confirmed minutes and the participant list. The server sends the minutes to each participant's email address. As an output, minutes are sent to all participants' email addresses to reconfirm the contents of the meeting. This allows them to take the next step.

[1735] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1736] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1737] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1738] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1739] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1740] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1741] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1742] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1743] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1744] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1745] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1746] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1747] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1748] 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.

[1749] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1750] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1751] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1752] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1753] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1754] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1755] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1756] The following is further disclosed regarding the above embodiment.

[1757] (Claim 1)

[1758] means for receiving a theme and purpose of a meeting and automatically generating an agenda based on said theme and purpose;

[1759] A means to receive a list of participants, check the schedules of each participant, select a common free time, and send a notification;

[1760] A means to use AI models to generate real-time comments, discussion summaries and closing statements during meetings;

[1761] A way to convert meeting audio into text, extract key points and create meeting minutes,

[1762] A means to distribute the created minutes to participants by email,

[1763] A system including:

[1764] (Claim 2)

[1765] 10. The system according to claim 1, further comprising means for monitoring the progress of the conference and determining timing of remarks when generating remarks during the conference.

[1766] (Claim 3)

[1767] 2. The system according to claim 1, wherein the means for checking the schedules of participants before the meeting and notifying them of the meeting uses a calendar API to obtain the free time of participants.

[1768] "Example 1"

[1769] (Claim 1)

[1770] means for receiving a theme and purpose of a meeting and automatically generating an agenda based on said theme and purpose;

[1771] A means of receiving a list of participants, checking the schedules of each participant, selecting a common free time, and sending a notification;

[1772] A means of generating comments, discussion summaries, and closing statements in real time using generative AI models during meetings;

[1773] A way to convert meeting audio into text, extract key points and create meeting minutes,

[1774] A means to distribute the created minutes to participants by email,

[1775] A system including:

[1776] (Claim 2)

[1777] 10. The system according to claim 1, further comprising means for monitoring the progress of the conference and determining timing of remarks when generating remarks during the conference.

[1778] (Claim 3)

[1779] 2. The system according to claim 1, wherein the means for checking the schedules of participants before the meeting and notifying them of the meeting uses a schedule management API to obtain the free time of participants.

[1780] "Application Example 1"

[1781] (Claim 1)

[1782] means for receiving a theme and purpose of a meeting and automatically generating an agenda based on said theme and purpose;

[1783] A means to receive a list of participants, check the schedules of each participant, select a common free time, and send a notification;

[1784] A means of generating comments, discussion summaries, and closing statements in real time using generative AI models during meetings;

[1785] A way to convert meeting audio into text, extract key points and create meeting minutes,

[1786] A means to distribute the created minutes to participants by email,

[1787] A means to check the progress of work within the factory in real time and provide instructions for the next step with audio and visual information,

[1788] A means to record and share critical incidents on the spot using smart devices,

[1789] A system including:

[1790] (Claim 2)

[1791] 2. The system according to claim 1, further comprising a means for monitoring the progress of the conference and determining timing of remarks when generating remarks during the conference.

[1792] (Claim 3)

[1793] 2. The system according to claim 1, wherein the means for checking the schedules of participants before the meeting and notifying them of the meeting uses a calendar API to obtain the free time of participants.

[1794] "Example 2: Combining Emotion Engines"

[1795] (Claim 1)

[1796] means for receiving a theme and purpose of a meeting and automatically generating an agenda based on said theme and purpose;

[1797] A means to receive a list of participants, check the schedules of each participant, select a common free time, and send a notification;

[1798] A means of generating comments, discussion summaries, and closing statements in real time using generative AI models during meetings;

[1799] A way to convert meeting audio into text, extract key points and create meeting minutes,

[1800] A means for distributing the created minutes to participants by email;

[1801] a means including an emotion engine that recognizes emotions from facial expressions and voices of users during a conference and adjusts the progress of the conference based on the recognized emotions;

[1802] A system including:

[1803] (Claim 2)

[1804] 10. The system according to claim 1, further comprising means for monitoring the progress of the conference and determining timing of remarks when generating remarks during the conference.

[1805] (Claim 3)

[1806] 2. The system according to claim 1, wherein the means for checking the schedules of participants before the meeting and notifying them of the meeting uses a calendar API to obtain the free time of participants.

[1807] "Application example 2 when combining emotion engines"

[1808] (Claim 1)

[1809] means for receiving a theme and purpose of a meeting and automatically generating an agenda based on said theme and purpose;

[1810] A means to receive a list of participants, check the schedules of each participant, select a common free time, and send a notification;

[1811] A means to use AI models to generate real-time comments, discussion summaries and closing statements during meetings;

[1812] A way to convert meeting audio into text, extract key points and create meeting minutes,

[1813] A means to distribute the created minutes to participants by email,

[1814] A means for recognizing emotions of participants during a meeting and adjusting the progress based on the emotion data;

[1815] A system including:

[1816] (Claim 2)

[1817] 10. The system according to claim 1, further comprising means for monitoring the progress of the conference and determining timing of remarks when generating remarks during the conference.

[1818] (Claim 3)

[1819] 2. The system according to claim 1, wherein the means for checking the schedules of participants before the meeting and notifying them of the meeting uses a calendar API to obtain the free time of participants. [Explanation of symbols]

[1820] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a theme and purpose of a meeting and automatically generating an agenda based on said theme and purpose; A means to receive a list of participants, check the schedules of each participant, select a common free time, and send a notification; A means to use AI models to generate real-time comments, discussion summaries and closing statements during meetings; A way to convert meeting audio into text, extract key points and create meeting minutes, A means to distribute the created minutes to participants by email, A system including:

2. The system according to claim 1 , further comprising means for monitoring the progress of the conference and determining timing of remarks when generating remarks during the conference.

3. 2. The system according to claim 1, wherein the means for checking the schedules of participants before the meeting and notifying them of the meeting uses a calendar API to obtain the free times of participants.

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