system

Abstract

We provide the system. [Solution] An input method for receiving participant information, An analytical means for analyzing the received participant information and selecting an appropriate supplier, A reservation method that automatically makes reservations with selected suppliers, A change management system that contacts selected suppliers and confirms the changes in case of changes in the number of participants or schedule, A supplier management system that provides information on suppliers and accepts registrations, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In business activities, when a junior employee is appointed as the host of a banquet, they have to manually manage a variety of tasks, such as selecting an appropriate supplier based on the information of the participants, making reservations, handling changes in the number of people or schedule, and communicating with the supplier. This process requires time and effort and may interfere with the main business. Therefore, there is a need to streamline these operations and reduce the burden on the host duties.

Means for Solving the Problems

[0005] To address this challenge, we provide a system that receives participant information, analyzes it to select appropriate suppliers, and automatically executes reservations. Furthermore, it includes a mechanism to automatically contact suppliers and confirm changes in the number of participants or dates. Additionally, by providing a means to notify participants about fee collection based on the analyzed information, we offer a system that streamlines the organizing process.

[0006] "Participant information" refers to data about individual people attending a banquet or event, including, for example, name, age, job title, preferences, and possible dates for the event.

[0007] "Input means" refers to the interface through which a user provides data to a system, and includes devices such as keyboards, mice, and touchscreens, as well as appropriate software.

[0008] "Analysis methods" refer to the processes and tools used to analyze received information and find valuable conclusions or options, and in this context, it specifically refers to the function of selecting stores and service providers based on AI algorithms.

[0009] "Suppliers" refer to organizations or facilities that provide services or goods to participants, and in this context, this mainly includes restaurants and similar establishments.

[0010] "Reservation method" refers to a function that carries out the process of securing a supplier's facilities or services at a pre-specified date and time.

[0011] "Change management mechanisms" refer to functions that appropriately handle changes to the original schedule or requests and coordinate with suppliers and stakeholders.

[0012] "Supplier management means" refers to a function that allows suppliers to register with the system and provide and update information about their services, and provides an interface for creating and managing supplier profiles.

[0013] "Notification methods" refer to functions for manually or automatically sending important information and notifications to users or participants, and in this context, they are particularly used for notifications such as membership fee collection. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] The AI ​​system for organizing banquets based on the present invention is designed to efficiently automate the tasks of organizing banquets. This system operates in a manner where the user inputs participant information from a terminal, and the server analyzes that data. The following describes specific embodiments for implementing the present invention.

[0036] First, the user uses a terminal to input the information necessary for organizing the event into the system. This information includes participants' names, ages, positions, preferences, budget, and proposed dates. This information is retrieved by the terminal and sent to the server.

[0037] Next, the server analyzes the received information and uses an AI algorithm to select the most suitable supplier (restaurant or service provider). This algorithm uses its accumulated database and information on partner suppliers to select the supplier that best matches the participant's preferences. In this process, the server picks out multiple candidates and narrows down the options to the best choice.

[0038] Once the selection is complete, the server automatically makes a reservation with the supplier using the online reservation system. The reservation details are then notified to the user and provided as a confirmation email. This frees the organizer from the hassle of making reservations manually.

[0039] Furthermore, if a user changes the number of participants or the date using their device, that change information is sent back to the server. The server then notifies the supplier of the changes and automatically handles securing additional space and confirming cancellation fees. As soon as it receives a response from the supplier, it notifies the user of that information.

[0040] Furthermore, the server can automatically send reminders to participants about collecting their membership fees. This feature eliminates the need for organizers to contact participants individually, allowing for more efficient fundraising.

[0041] As a concrete example, consider a scenario where 10 young employees are organizing a company party. The user inputs details into the system, such as the participants' preferences ("Japanese food"), a budget ("4,000 yen per person"), and a preferred date ("May 20th"). Based on this information, the server searches for a suitable Japanese restaurant, automatically makes a reservation at a restaurant with availability on the preferred date, and notifies the user of the details. Subsequently, if the number of participants changes, the server automatically adjusts the reservation and notifies the user of the confirmed changes.

[0042] In this way, the AI ​​system for organizing banquets can automate a large portion of the organizing tasks, reducing the workload for users.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user logs into the system via their device and enters participant information. This information includes the participant's name, age, job title, preferences, budget, and preferred dates. The device then sends this data to the server.

[0046] Step 2:

[0047] The server analyzes the received participant information and uses an AI algorithm to select multiple potential suppliers based on the participant's preferences and budget. The selection is made by searching for suitable stores in a database on the network.

[0048] Step 3:

[0049] The server evaluates the selected candidate stores and determines the best store. Selection criteria include store reviews, ratings, distance, price range, etc. The server then selects the most suitable store from the candidates.

[0050] Step 4:

[0051] The server automatically makes a reservation at a selected restaurant. Using an online reservation system, it secures seats according to the desired date, time, and number of people. The user is then notified of the reservation confirmation.

[0052] Step 5:

[0053] When a user changes the number of participants or the date from their device, they send that information to the server. The server then contacts the supplier based on the changes to confirm whether the changes are possible.

[0054] Step 6:

[0055] The server receives confirmation from the supplier and notifies the user once the changes are finalized. It also informs the user whether or not a cancellation fee will apply.

[0056] Step 7:

[0057] The server sends reminders to participants about collecting membership fees at pre-set times. Payment methods and deadlines are communicated via email or messaging apps.

[0058] Step 8:

[0059] When a supplier registers with the system, the server provides an interface and accepts registration information. The server handles billing for registration fees and promotions for new registrations.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] In modern meetings and gatherings, organizers face a wide range of challenges. Specifically, these include complex tasks such as managing participant information, selecting appropriate suppliers, handling reservations, and responding to changes in participant numbers and dates. Performing these tasks manually is time-consuming and laborious, placing a significant burden on busy organizers. Therefore, there is a need for systems that streamline these tasks and reduce the burden on organizers.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes an input means for users to input participant information via a terminal, a transmission means for transmitting participant information collected by the terminal to the server, and an analysis means for the server to analyze the received participant information using an AI model and select an appropriate supplier. This makes it possible to automate the cumbersome organizing tasks and operate the event efficiently.

[0065] A "user" refers to the entity that accesses the system and inputs the necessary information.

[0066] "Terminal" refers to a device such as a computer or smartphone that a user uses to input information.

[0067] A "server" refers to a central computer system that receives information sent from terminals and processes it for tasks such as analysis, reservations, and notifications.

[0068] "Participant information" refers to detailed data about each individual attending a meeting, which users enter into the system.

[0069] An "AI model" refers to a system that uses artificial intelligence to analyze data and includes algorithms for selecting the most suitable supplier.

[0070] "Suppliers" refer to restaurants, service providers, and other businesses that provide the services and goods necessary for an event or meeting.

[0071] "Analysis means" refers to a series of processes and algorithms used by the server to process the received information and select the appropriate supplier.

[0072] "Reservation method" refers to a function that automatically makes reservations with suppliers selected by the server.

[0073] "Change management means" refers to a function that communicates user-entered changes to suppliers and manages their response.

[0074] "Supplier management means" refers to functions that manage supplier information and support the registration of new suppliers.

[0075] "Notification means" refers to the methods and functions that a system uses to provide important information to users or participants.

[0076] This invention is a system that efficiently automates the tasks of organizing banquets. The system automates everything from selecting appropriate suppliers to confirming reservations by having users input participant information using a terminal, which is then received and analyzed by a server. The hardware consists of a standard computer and mobile terminal, utilizing a cloud server as needed. Part of the software incorporates a generative AI model to perform data analysis for selecting the optimal supplier.

[0077] First, the user enters participant information such as name, age, position, preferences, budget, and preferred dates into the system using a terminal. This data is sent from the terminal to the server, which uses a generative AI model to analyze the data and select the supplier that best matches the participant's preferences from its database. The server then automatically makes a reservation with the selected supplier via an API. The user is notified of the reservation results and details, thus freeing them from physical procedures.

[0078] As a practical example, consider a banquet for 10 young employees. The user enters prompt text into the system such as "Participant information: Name, age, preference: Japanese food, budget: 4000 yen per person, proposed date: May 20th." The AI ​​then analyzes a list of Japanese restaurants, selects a restaurant that meets the criteria, and automatically confirms the reservation. At this time, the server also automates the confirmation of the reservation and the handling of changes in the number of participants, ensuring smooth communication and inquiries with suppliers.

[0079] In this way, the system reduces the burden on the organizer and enables efficient management of banquets.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The user enters participant information using a device.

[0083] In terms of the specific process, the user enters participant information such as name, age, job title, preferences, budget, and preferred dates into an input form on the device.

[0084] The input data is temporarily stored on the terminal.

[0085] Step 2:

[0086] The device sends the participant information it has collected to the server.

[0087] Specifically, the device transmits the collected data to the server via the internet.

[0088] In this process, data is securely transferred using an encryption protocol. The input is participant information, and the output is data stored on the server.

[0089] Step 3:

[0090] The server analyzes the participant information it receives using an AI model.

[0091] The server receives participant information as input and uses a generative AI model to analyze the database to find suppliers that meet the participant's preferences.

[0092] On the server, a prompt message is generated, and an algorithm selects the most appropriate supplier based on the data. This analysis process outputs a list of candidate suppliers.

[0093] Step 4:

[0094] The server automatically makes a reservation with the supplier it deems most suitable.

[0095] Specifically, the server automates the reservation process by accessing the supplier's reservation system API and providing the necessary input information.

[0096] The inputs are a supplier list and booking details, and the output is confirmed booking information.

[0097] Step 5:

[0098] The server notifies the user of the reservation information.

[0099] The server sends the reservation results to the user via email or app notification, allowing them to confirm the reservation details.

[0100] At this stage, reservation information is provided as output in a format that the user can verify.

[0101] Step 6:

[0102] When a user changes the number of participants or the schedule using their device, these changes are then communicated to the server.

[0103] The user enters the changes on the screen and sends them to the server.

[0104] The input is change information, and the output is the latest reservation data updated by the server.

[0105] Step 7:

[0106] The server receives the change information and contacts the supplier to modify the reservation details.

[0107] The server sends change information to the supplier's system, waits for a response, and then provides that information as feedback to the user.

[0108] In this process, the input is the changes made, and the output is the confirmation result from the supplier and the update reservation information based on that confirmation.

[0109] (Application Example 1)

[0110] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0111] Currently, organizing banquets and events requires considerable effort and time. Among these tasks, gathering participant information, selecting the most suitable suppliers, booking procedures, and managing changes to participant numbers and dates are particularly cumbersome. There is a need to streamline these tasks and reduce the burden through automation. Furthermore, it would be desirable for users to be able to provide information via voice input, and for appropriate plans to be immediately proposed and confirmed based on that information.

[0112] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0113] In this invention, the server includes an information acquisition means for receiving participant information, an information analysis means for analyzing the received participant information and selecting an appropriate supplier, and a voice input means for acquiring participant information using speech recognition. This automates many of the organizing tasks and enables quick and efficient reservations, changes, and adjustments through intuitive voice operation.

[0114] "Information acquisition means" refers to a method or device for collecting information from participants.

[0115] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and selecting the most suitable supplier.

[0116] "Reservation processing means" refers to a method or apparatus for automatically executing a reservation with a selected supplier.

[0117] "Change adjustment means" refers to a method or device for contacting the supplier and confirming and adjusting the changes when the number of participants or the schedule changes.

[0118] "Information management means" refers to a method or apparatus for managing information about suppliers and accepting supplier registrations.

[0119] "Voice input means" refers to a method or device for obtaining information from participants using speech recognition technology.

[0120] A "plan proposal means" is a method or device for proposing and notifying participants of an optimal plan based on information acquired via voice.

[0121] This invention is a system for streamlining the tasks of organizing banquets and events. The server has an information acquisition means for receiving participant information, an information analysis means for analyzing the acquired participant information, and a voice input means for acquiring information using speech recognition. When a user gives instructions by voice through a terminal, the voice input means converts this into text data. The converted data is sent to the server and analyzed by the information analysis means. Here, the supplier best suited to the participants' preferences, budget, and schedule is selected.

[0122] Once the selection is complete, the reservation processing system automatically makes the reservation. Reservation information and suggested plans are fed back to the user through the plan suggestion system. If the user wants to update participant information, they can do so by voice command using their terminal. For example, if the user says, "Tell me some restaurants you recommend for a birthday party next Saturday," the server will select a restaurant based on that information and suggest a suitable plan.

[0123] This system uses the "speech_recognition" library as its speech recognition technology, and for server-side information analysis, it utilizes information from partner suppliers and accumulated databases. Furthermore, notifications and suggestions are sent immediately to the terminal after selection. It is also possible to propose plans using a generated AI model. An example of a prompt message would be, "Please suggest the best dinner location based on the user's preferences."

[0124] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0125] Step 1:

[0126] The user activates a voice input method using a terminal and provides information about the event verbally. This input is converted to text by speech recognition technology. The input is audio data, and the output is text data. Specifically, speech recognition involves capturing audio through a microphone.

[0127] Step 2:

[0128] The server passes the text data obtained via voice input to the information analysis system. Here, the system selects the optimal supplier based on supplier information stored in the database and participant conditions (preferences, budget, schedule, etc.). The input is text data, and the output is a list of optimal suppliers. A generative AI model is used for data analysis, filtering through a vast number of candidates.

[0129] Step 3:

[0130] The server automatically sends reservation requests to selected suppliers using the reservation processing mechanism. This step involves API calls or online form submissions to the supplier's reservation system. The input is a list of selected suppliers, and the output is reservation confirmation information. Reservation details are processed through the registered API.

[0131] Step 4:

[0132] The user receives booking confirmation information and suggested plans on their device. This information is notified to the user through a plan suggestion system. The input is booking confirmation information, and the output is the plan details displayed on the device. When notifying the user, they can choose between voice or text.

[0133] Step 5:

[0134] Users can modify participant information and event conditions as needed, and send a new request to the server via their device. This new information is then transmitted to the server using voice input. The input is the updated participant information, and the output is the latest selection results and updated information. The system quickly recognizes the changes, and the re-analysis process starts automatically.

[0135] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0136] The system based on this invention incorporates an emotion engine to optimize the user experience and provides more personalized automation of event planning tasks. The following describes specific embodiments for carrying out this invention.

[0137] In this system, users first input participant information using a terminal. This information includes participants' personal data and details of the event. The terminal then sends this information to the server.

[0138] Next, the server utilizes an emotion engine to recognize emotions from the user's voice tone and text input. The emotion engine can analyze emotional states such as joy, dissatisfaction, and anticipation in real time.

[0139] Based on the results of emotion recognition, the server adjusts the criteria for selecting suppliers. For example, if a user expresses particularly cheerful emotions, it will prioritize selecting highly-rated restaurants or establishments offering special services. The emotion engine can also customize the services offered by suppliers to meet individual needs.

[0140] Once the selection is complete, the server automatically makes a reservation at the chosen store and notifies the user of the reservation details. Furthermore, even if the user requests a change from their device, the server, via the emotion engine, reconfirms the user's emotional state and proposes a solution that suits their feelings.

[0141] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server, based on the detection of anxiety by its emotion engine, selects a venue with a high satisfaction rating in the past and provides emphasized support features. Similarly, when sending notifications about collecting membership fees, the server detects changes in emotion and optimizes the notification content as needed.

[0142] Thus, the present invention provides an automated system for organizing tasks that takes user emotions into consideration, achieving deeper customization and greater flexibility than conventional systems.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] The user logs into the system using a terminal and enters participant information and banquet details. This includes data such as participants' names, ages, preferences, budget, and preferred dates. The terminal then sends this information to the server.

[0146] Step 2:

[0147] The server analyzes the received information. During this process, the emotion engine analyzes the user's emotions from their voice tone and text data. The emotion engine determines emotional states such as joy, anxiety, and anticipation.

[0148] Step 3:

[0149] Based on the analysis results from the emotion engine, the server adjusts the supplier selection criteria. For example, if the user's input indicates heightened emotions, the server will prioritize selecting restaurants with a special atmosphere or highly-rated establishments.

[0150] Step 4:

[0151] The server automatically makes a reservation with a selected supplier. After the reservation is confirmed, the server notifies the user of the details. This information includes the reservation details and directions to the store.

[0152] Step 5:

[0153] If a user needs to change the number of participants or the schedule via their device, the server uses an emotion engine to re-evaluate the user's emotional state. If the user is feeling anxious, it will suggest additional support options.

[0154] Step 6:

[0155] The server contacts the supplier to obtain approval for the changes. Once the changes are approved, the server notifies the user of the result. If cancellation fees apply, the information will also be provided in an emotionally sensitive manner.

[0156] Step 7:

[0157] The server sends reminders for membership fee collection at pre-configured times. During this process, the emotion engine adjusts the notification content to match the user's emotions, facilitating smooth communication.

[0158] This process allows systems incorporating an emotion engine to provide a personalized user experience that goes beyond typical event management tasks.

[0159] (Example 2)

[0160] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0161] Current automated systems for event planning, designed to maximize user experience, have the challenge of not being able to adequately personalize them because they do not take into account the emotional state of participants. Furthermore, they lack real-time, optimized responses when selecting suppliers or changing reservations.

[0162] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0163] In this invention, the server includes an information acquisition means for acquiring participant attributes, an analysis means for analyzing emotions based on the acquired participant attributes, and a selection means for selecting an appropriate supplier based on the analyzed emotions. This makes it possible to select the optimal supplier while considering the participants' emotions in real time.

[0164] "Participant attributes" refer to basic information related to the participant, including name, contact information, and intention to participate.

[0165] "Information acquisition means" refers to the method or process by which the server collects basic information about participants.

[0166] "Analytical means for analyzing emotions" refers to methods or processes for determining a participant's emotional state by analyzing their voice tone and text data.

[0167] "Supplier" refers to a business entity or individual that can provide services to users.

[0168] "Selection method" refers to a method or process for selecting the most appropriate supplier based on analyzed sentiment information.

[0169] "Processing means" refers to the method or process for making reservations or contacting selected suppliers.

[0170] "Update method" refers to the method or process for communicating new information to selected suppliers and reflecting that information when reservations or schedules are changed.

[0171] "Management function" refers to a set of methods or procedures for collecting and maintaining information about suppliers.

[0172] "Notification function" refers to a method or system for providing participants or users with necessary information and updates.

[0173] This system automates event planning tasks while considering the emotional state of participants to maximize the user experience. Specifically, it employs a configuration centered around users, terminals, and servers.

[0174] The user uses a device to enter information such as participant attributes. This information includes name, contact information, intention to participate, and details of the event. The device then sends this data to the server.

[0175] The server first receives participant attributes using an information acquisition method. Next, it uses an emotion engine as an analysis method, and analyzes the data using a speech recognition API or natural language processing library (e.g., Google® Cloud Natural Language API) to extract the participants' emotions. Based on these analysis results, it uses an algorithm as a selection method to select the most appropriate supplier.

[0176] Furthermore, the server uses processing mechanisms to automatically make reservations with selected suppliers. Information collection and management from suppliers are handled by the management function. If reservation details or changes occur, the information is transmitted to the supplier via the update mechanism, and the changes are reflected. Participants and users are sent information as needed through the notification function.

[0177] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server uses an emotion engine to detect this anxiety, selects a supplier with a history of high customer satisfaction, and provides special support features. Similarly, when sending out membership fee collection notifications, the server detects changes in emotion and provides the most appropriate notification content.

[0178] An example of a prompt to input into the generating AI model is, "If a user is feeling a little anxious about organizing an event for the first time, what kind of support can be offered?"

[0179] In this way, the system takes participants' emotions into consideration in real time, enabling more personalized automation of event planning tasks.

[0180] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0181] Step 1:

[0182] Users use a terminal to enter participant attributes and details of the banquet. The entered data includes name, contact information, participation intention, date of the banquet, and location. This information is collected in the terminal's input fields and formatted into a data format before transmission.

[0183] Step 2:

[0184] The terminal sends formatted participant information to the server. This transmission primarily uses the HTTPS protocol to ensure the security of the information. The data is received on the server side and stored in a database for subsequent processing.

[0185] Step 3:

[0186] The server uses information retrieval methods to extract participant attributes from the database. Based on this information, it prepares an input dataset for sentiment analysis. The extracted data is converted into voice input or text data.

[0187] Step 4:

[0188] The server activates the emotion engine and performs sentiment analysis using the dataset. This analysis utilizes speech recognition APIs and natural language processing libraries to calculate sentiment parameters from the input data. The output sentiment parameters include joy, anxiety, and anticipation.

[0189] Step 5:

[0190] The server uses a selection method to select suppliers based on sentiment parameters. It filters the supplier database based on high ratings and specific services to generate a list of optimal suppliers.

[0191] Step 6:

[0192] The server automatically makes reservations with selected suppliers using a processing mechanism. Reservation information is sent via the supplier's API, and the reservation is confirmed. The confirmed reservation information is then notified to the user by the server.

[0193] Step 7:

[0194] Upon user request, a change request is sent from the terminal to the server. The server uses an update mechanism to share the changes with the supplier, who then verifies and updates the changes. The user is then notified of the changes.

[0195] This series of processes allows users to receive personalized service that takes into account the feelings of the participants, and automates the tasks of event organizers.

[0196] (Application Example 2)

[0197] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0198] Traditional event planning processes often fail to efficiently gather participant information and consider their emotions, resulting in a lack of personalization and flexibility in the user experience. Furthermore, the absence of appropriate, emotion-based suggestions can lead to events failing to meet expectations.

[0199] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0200] In this invention, the server includes information receiving means for acquiring participant attribute information, information analysis means for identifying appropriate recipients based on the acquired participant information, and sentiment analysis means for determining the user's emotional state and optimizing the suggested content based on that state. This enables personalized event planning and efficient information sharing.

[0201] "Participant attribute information" refers to information including personal data and preferences of people associated with the event.

[0202] "Information receiving means" refers to devices or methods for obtaining relevant information from participants.

[0203] A "recipient" refers to an external location or service provider selected for an event or service.

[0204] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and emotional data to select appropriate recipients.

[0205] "Reservation execution means" refers to a device or procedure for automatically establishing a reservation for a specified recipient.

[0206] "Change adjustment means" refers to a method or device for coordinating changes to the scale or date and time of an event with the provider, and for confirming and managing the changes.

[0207] "Information management means" refers to devices or systems for managing recipient information and receiving necessary user input.

[0208] "User's emotional state" refers to the type and intensity of emotions a user exhibits at a particular point in time.

[0209] "Emotional analysis means" refers to a method or device that analyzes a user's voice or text, determines their emotional state, and reflects that in the suggested content.

[0210] To implement this invention, the system is configured as follows: The server acquires participant attribute information received from the user's terminal using information receiving means. Information analysis means on the server analyzes this information and identifies the optimal recipient. At that time, emotion analysis means determines the user's emotional state and optimizes the suggested content based on the analysis results.

[0211] The reservation execution mechanism automatically completes the reservation with the specified provider. The change adjustment mechanism processes changes to the number of participants and date / time from the user, coordinates with the provider, and confirms the changes. After receiving confirmation of the changes from the provider, the user is notified of the details through the information management mechanism.

[0212] Specific technologies include speech recognition software (e.g., Google Speech-to-Text) and sentiment analysis engines (e.g., IBM Watson® Emotion Analysis). Data is processed on cloud-based servers and updated in real time.

[0213] For example, if a user enters "I want to plan my daughter's birthday party" on their device, this information is sent to the server, and sentiment analysis determines that the user has a high level of anticipation. Based on this, suggestions are provided, including particularly highly-rated restaurants and services.

[0214] Example of a prompt:

[0215] "Please tell the user about their birthday plans. Take their feelings into consideration and generate appropriate suggestions."

[0216] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0217] Step 1:

[0218] The terminal receives participant attribute information and initial event information entered by the user. This input includes participant names, interests, and the date and time of the event. The information is formatted appropriately and sent to the server.

[0219] Step 2:

[0220] The server acquires participant information transmitted from the terminal using information receiving means. Based on the acquired information, it analyzes this data using information analysis means. As part of the data processing, filtering is performed to identify recipients that match the participant's preferences and attributes.

[0221] Step 3:

[0222] The server uses emotion analysis tools to determine the user's emotional state from their voice or text input. This process uses an emotion analysis engine to analyze voice waveforms or text patterns as input and generate emotions such as joy, anticipation, and dissatisfaction as output.

[0223] Step 4:

[0224] The server determines appropriate recipient candidates based on the analyzed information and emotional state. The information analysis means selects recipients by referring to their evaluations and past user feedback. The list of selected recipients is passed to the reservation execution means.

[0225] Step 5:

[0226] The server automatically makes a reservation to the specified recipient using the reservation execution mechanism. Reservation confirmation data is generated as output and fed back to the user's terminal for verification.

[0227] Step 6:

[0228] If a user wishes to make changes, the server receives a change request from the terminal. The change adjustment mechanism then reconciles with the supplier and confirms the changes. The user is notified of the changes and the confirmation result, and this information is recorded as new information.

[0229] Step 7:

[0230] The server uses information management tools to register and manage recipient information, and updates necessary information as needed. This ensures that users receive the latest recipient information. In addition, feedback based on user sentiment is generated as prompt messages and recorded for future suggestions.

[0231] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0232] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0233] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0234] [Second Embodiment]

[0235] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0236] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0237] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0238] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0239] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0240] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0241] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0242] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0243] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0244] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0245] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0246] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0247] The AI ​​system for organizing banquets based on the present invention is designed to efficiently automate the tasks of organizing banquets. This system operates in a manner where the user inputs participant information from a terminal, and the server analyzes that data. The following describes specific embodiments for implementing the present invention.

[0248] First, the user uses a terminal to input the information necessary for organizing the event into the system. This information includes participants' names, ages, positions, preferences, budget, and proposed dates. This information is retrieved by the terminal and sent to the server.

[0249] Next, the server analyzes the received information and uses an AI algorithm to select the most suitable supplier (restaurant or service provider). This algorithm uses its accumulated database and information on partner suppliers to select the supplier that best matches the participant's preferences. In this process, the server picks out multiple candidates and narrows down the options to the best choice.

[0250] Once the selection is complete, the server automatically makes a reservation with the supplier using the online reservation system. The reservation details are then notified to the user and provided as a confirmation email. This frees the organizer from the hassle of making reservations manually.

[0251] Furthermore, if a user changes the number of participants or the date using their device, that change information is sent back to the server. The server then notifies the supplier of the changes and automatically handles securing additional space and confirming cancellation fees. As soon as it receives a response from the supplier, it notifies the user of that information.

[0252] Furthermore, the server can automatically send reminders to participants about collecting their membership fees. This feature eliminates the need for organizers to contact participants individually, allowing for more efficient fundraising.

[0253] As a concrete example, consider a scenario where 10 young employees are organizing a company party. The user inputs details into the system, such as the participants' preferences ("Japanese food"), a budget ("4,000 yen per person"), and a preferred date ("May 20th"). Based on this information, the server searches for a suitable Japanese restaurant, automatically makes a reservation at a restaurant with availability on the preferred date, and notifies the user of the details. Subsequently, if the number of participants changes, the server automatically adjusts the reservation and notifies the user of the confirmed changes.

[0254] In this way, the AI ​​system for organizing banquets can automate a large portion of the organizing tasks, reducing the workload for users.

[0255] The following describes the processing flow.

[0256] Step 1:

[0257] The user logs into the system via their device and enters participant information. This information includes the participant's name, age, job title, preferences, budget, and preferred dates. The device then sends this data to the server.

[0258] Step 2:

[0259] The server analyzes the received participant information and uses an AI algorithm to select multiple potential suppliers based on the participant's preferences and budget. The selection is made by searching for suitable stores in a database on the network.

[0260] Step 3:

[0261] The server evaluates the selected candidate stores and determines the best store. Selection criteria include store reviews, ratings, distance, price range, etc. The server then selects the most suitable store from the candidates.

[0262] Step 4:

[0263] The server automatically makes a reservation at a selected restaurant. Using an online reservation system, it secures seats according to the desired date, time, and number of people. The user is then notified of the reservation confirmation.

[0264] Step 5:

[0265] When a user changes the number of participants or the date from their device, they send that information to the server. The server then contacts the supplier based on the changes to confirm whether the changes are possible.

[0266] Step 6:

[0267] The server receives confirmation from the supplier and notifies the user once the changes are finalized. It also informs the user whether or not a cancellation fee will apply.

[0268] Step 7:

[0269] The server sends reminders to participants about collecting membership fees at pre-set times. Payment methods and deadlines are communicated via email or messaging apps.

[0270] Step 8:

[0271] When a supplier registers with the system, the server provides an interface and accepts registration information. The server handles billing for registration fees and promotions for new registrations.

[0272] (Example 1)

[0273] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0274] In modern meetings and gatherings, organizers face a wide range of challenges. Specifically, these include complex tasks such as managing participant information, selecting appropriate suppliers, handling reservations, and responding to changes in participant numbers and dates. Performing these tasks manually is time-consuming and laborious, placing a significant burden on busy organizers. Therefore, there is a need for systems that streamline these tasks and reduce the burden on organizers.

[0275] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0276] In this invention, the server includes an input means for users to input participant information via a terminal, a transmission means for transmitting participant information collected by the terminal to the server, and an analysis means for the server to analyze the received participant information using an AI model and select an appropriate supplier. This makes it possible to automate the cumbersome organizing tasks and operate the event efficiently.

[0277] A "user" refers to the entity that accesses the system and inputs the necessary information.

[0278] "Terminal" refers to a device such as a computer or smartphone that a user uses to input information.

[0279] "Server" refers to a central computer system that receives information sent from a terminal and performs processes such as analysis, reservation, and notification.

[0280] "Participant information" refers to detailed data regarding individual persons who participate in a meeting and are input by a user into the system.

[0281] "AI model" refers to a system that includes an algorithm for analyzing data using artificial intelligence to select an optimal provider.

[0282] "Provider" refers to a restaurant, service provider, etc. that provides services or goods required for an event or meeting.

[0283] "Analysis means" refers to a series of processes and algorithms for the server to process the received information and select an appropriate provider.

[0284] "Reservation means" refers to a function for the server to automatically make a reservation with the selected provider.

[0285] "Change management means" refers to a function for contacting the provider about the changes input by the user and managing the response.

[0286] "Provider management means" refers to a function for managing provider information and supporting the registration of new providers.

[0287] "Notification means" refers to a method or function for the system to provide important information to users and participants.

[0288] This invention is a system that efficiently automates the tasks of organizing banquets. The system automates everything from selecting appropriate suppliers to confirming reservations by having users input participant information using a terminal, which is then received and analyzed by a server. The hardware consists of a standard computer and mobile terminal, utilizing a cloud server as needed. Part of the software incorporates a generative AI model to perform data analysis for selecting the optimal supplier.

[0289] First, the user enters participant information such as name, age, position, preferences, budget, and preferred dates into the system using a terminal. This data is sent from the terminal to the server, which uses a generative AI model to analyze the data and select the supplier that best matches the participant's preferences from its database. The server then automatically makes a reservation with the selected supplier via an API. The user is notified of the reservation results and details, thus freeing them from physical procedures.

[0290] As a practical example, consider a banquet for 10 young employees. The user enters prompt text into the system such as "Participant information: Name, age, preference: Japanese food, budget: 4000 yen per person, proposed date: May 20th." The AI ​​then analyzes a list of Japanese restaurants, selects a restaurant that meets the criteria, and automatically confirms the reservation. At this time, the server also automates the confirmation of the reservation and the handling of changes in the number of participants, ensuring smooth communication and inquiries with suppliers.

[0291] In this way, the system reduces the burden on the organizer and enables efficient management of banquets.

[0292] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0293] Step 1:

[0294] The user enters participant information using a device.

[0295] As a specific operation, the user inputs participant information such as name, age, position, hobbies, budget, and candidate dates into the input form of the terminal.

[0296] The data entered is temporarily stored on the terminal side.

[0297] Step 2:

[0298] The terminal sends the participant information collected to the server.

[0299] Specifically, the terminal sends the collected data to the server via the Internet.

[0300] At this time, the data is securely transferred by using an encryption protocol. The input is the participant information, and the output is the data stored on the server.

[0301] Step 3:

[0302] The server analyzes the participant information received with the generated AI model.

[0303] The server receives the participant information as input and analyzes the suppliers that meet the requirements from the database using the generated AI model.

[0304] On the server, a prompt sentence is generated, and the algorithm selects the most appropriate supplier based on the data. The output of this analysis process is a list of candidate suppliers.

[0305] Step 4:

[0306] The server automatically makes a reservation for the supplier determined to be the best.

[0307] Specifically, the server accesses the reservation system API of the supplier and automates the reservation process by providing the necessary input information.

[0308] The inputs are a supplier list and booking details, and the output is confirmed booking information.

[0309] Step 5:

[0310] The server notifies the user of the reservation information.

[0311] The server sends the reservation results to the user via email or app notification, allowing them to confirm the reservation details.

[0312] At this stage, reservation information is provided as output in a format that the user can verify.

[0313] Step 6:

[0314] When a user changes the number of participants or the schedule using their device, these changes are then communicated to the server.

[0315] The user enters the changes on the screen and sends them to the server.

[0316] The input is change information, and the output is the latest reservation data updated by the server.

[0317] Step 7:

[0318] The server receives the change information and contacts the supplier to modify the reservation details.

[0319] The server sends change information to the supplier's system, waits for a response, and then provides that information as feedback to the user.

[0320] In this process, the input is the changes made, and the output is the confirmation result from the supplier and the update reservation information based on that confirmation.

[0321] (Application Example 1)

[0322] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0323] Currently, organizing banquets and events requires considerable effort and time. Among these tasks, gathering participant information, selecting the most suitable suppliers, booking procedures, and managing changes to participant numbers and dates are particularly cumbersome. There is a need to streamline these tasks and reduce the burden through automation. Furthermore, it would be desirable for users to be able to provide information via voice input, and for appropriate plans to be immediately proposed and confirmed based on that information.

[0324] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0325] In this invention, the server includes an information acquisition means for receiving participant information, an information analysis means for analyzing the received participant information and selecting an appropriate supplier, and a voice input means for acquiring participant information using speech recognition. This automates many of the organizing tasks and enables quick and efficient reservations, changes, and adjustments through intuitive voice operation.

[0326] "Information acquisition means" refers to a method or device for collecting information from participants.

[0327] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and selecting the most suitable supplier.

[0328] "Reservation processing means" refers to a method or apparatus for automatically executing a reservation with a selected supplier.

[0329] "Change adjustment means" refers to a method or device for contacting the supplier and confirming and adjusting the changes when the number of participants or the schedule changes.

[0330] "Information management means" refers to a method or apparatus for managing information about suppliers and accepting supplier registrations.

[0331] "Voice input means" refers to a method or device for obtaining information from participants using speech recognition technology.

[0332] A "plan proposal means" is a method or device for proposing and notifying participants of an optimal plan based on information acquired via voice.

[0333] This invention is a system for streamlining the tasks of organizing banquets and events. The server has an information acquisition means for receiving participant information, an information analysis means for analyzing the acquired participant information, and a voice input means for acquiring information using speech recognition. When a user gives instructions by voice through a terminal, the voice input means converts this into text data. The converted data is sent to the server and analyzed by the information analysis means. Here, the supplier best suited to the participants' preferences, budget, and schedule is selected.

[0334] Once the selection is complete, the reservation processing system automatically makes the reservation. Reservation information and suggested plans are fed back to the user through the plan suggestion system. If the user wants to update participant information, they can do so by voice command using their terminal. For example, if the user says, "Tell me some restaurants you recommend for a birthday party next Saturday," the server will select a restaurant based on that information and suggest a suitable plan.

[0335] This system uses the "speech_recognition" library as its speech recognition technology, and for server-side information analysis, it utilizes information from partner suppliers and accumulated databases. Furthermore, notifications and suggestions are sent immediately to the terminal after selection. It is also possible to propose plans using a generated AI model. An example of a prompt message would be, "Please suggest the best dinner location based on the user's preferences."

[0336] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0337] Step 1:

[0338] The user activates a voice input method using a terminal and provides information about the event verbally. This input is converted to text by speech recognition technology. The input is audio data, and the output is text data. Specifically, speech recognition involves capturing audio through a microphone.

[0339] Step 2:

[0340] The server passes the text data obtained via voice input to the information analysis system. Here, the system selects the optimal supplier based on supplier information stored in the database and participant conditions (preferences, budget, schedule, etc.). The input is text data, and the output is a list of optimal suppliers. A generative AI model is used for data analysis, filtering through a vast number of candidates.

[0341] Step 3:

[0342] The server automatically sends reservation requests to selected suppliers using the reservation processing mechanism. This step involves API calls or online form submissions to the supplier's reservation system. The input is a list of selected suppliers, and the output is reservation confirmation information. Reservation details are processed through the registered API.

[0343] Step 4:

[0344] The user receives booking confirmation information and suggested plans on their device. This information is notified to the user through a plan suggestion system. The input is booking confirmation information, and the output is the plan details displayed on the device. When notifying the user, they can choose between voice or text.

[0345] Step 5:

[0346] Users can modify participant information and event conditions as needed, and send a new request to the server via their device. This new information is then transmitted to the server using voice input. The input is the updated participant information, and the output is the latest selection results and updated information. The system quickly recognizes the changes, and the re-analysis process starts automatically.

[0347] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0348] The system based on this invention incorporates an emotion engine to optimize the user experience and provides more personalized automation of event planning tasks. The following describes specific embodiments for carrying out this invention.

[0349] In this system, users first input participant information using a terminal. This information includes participants' personal data and details of the event. The terminal then sends this information to the server.

[0350] Next, the server utilizes an emotion engine to recognize emotions from the user's voice tone and text input. The emotion engine can analyze emotional states such as joy, dissatisfaction, and anticipation in real time.

[0351] Based on the results of emotion recognition, the server adjusts the criteria for selecting suppliers. For example, if a user expresses particularly cheerful emotions, it will prioritize selecting highly-rated restaurants or establishments offering special services. The emotion engine can also customize the services offered by suppliers to meet individual needs.

[0352] Once the selection is complete, the server automatically makes a reservation at the chosen store and notifies the user of the reservation details. Furthermore, even if the user requests a change from their device, the server, via the emotion engine, reconfirms the user's emotional state and proposes a solution that suits their feelings.

[0353] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server, based on the detection of anxiety by its emotion engine, selects a venue with a high satisfaction rating in the past and provides emphasized support features. Similarly, when sending notifications about collecting membership fees, the server detects changes in emotion and optimizes the notification content as needed.

[0354] Thus, the present invention provides an automated system for organizing tasks that takes user emotions into consideration, achieving deeper customization and greater flexibility than conventional systems.

[0355] The following describes the processing flow.

[0356] Step 1:

[0357] The user logs into the system using a terminal and enters participant information and banquet details. This includes data such as participants' names, ages, preferences, budget, and preferred dates. The terminal then sends this information to the server.

[0358] Step 2:

[0359] The server analyzes the received information. During this process, the emotion engine analyzes the user's emotions from their voice tone and text data. The emotion engine determines emotional states such as joy, anxiety, and anticipation.

[0360] Step 3:

[0361] Based on the analysis results from the emotion engine, the server adjusts the supplier selection criteria. For example, if the user's input indicates heightened emotions, the server will prioritize selecting restaurants with a special atmosphere or highly-rated establishments.

[0362] Step 4:

[0363] The server automatically makes a reservation with a selected supplier. After the reservation is confirmed, the server notifies the user of the details. This information includes the reservation details and directions to the store.

[0364] Step 5:

[0365] If a user needs to change the number of participants or the schedule via their device, the server uses an emotion engine to re-evaluate the user's emotional state. If the user is feeling anxious, it will suggest additional support options.

[0366] Step 6:

[0367] The server contacts the supplier to obtain approval for the changes. Once the changes are approved, the server notifies the user of the result. If cancellation fees apply, the information will also be provided in an emotionally sensitive manner.

[0368] Step 7:

[0369] The server sends reminders for membership fee collection at pre-configured times. During this process, the emotion engine adjusts the notification content to match the user's emotions, facilitating smooth communication.

[0370] This process allows systems incorporating an emotion engine to provide a personalized user experience that goes beyond typical event management tasks.

[0371] (Example 2)

[0372] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0373] Current automated systems for event planning, designed to maximize user experience, have the challenge of not being able to adequately personalize them because they do not take into account the emotional state of participants. Furthermore, they lack real-time, optimized responses when selecting suppliers or changing reservations.

[0374] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0375] In this invention, the server includes an information acquisition means for acquiring participant attributes, an analysis means for analyzing emotions based on the acquired participant attributes, and a selection means for selecting an appropriate supplier based on the analyzed emotions. This makes it possible to select the optimal supplier while considering the participants' emotions in real time.

[0376] "Participant attributes" refer to basic information related to the participant, including name, contact information, and intention to participate.

[0377] "Information acquisition means" refers to the method or process by which the server collects basic information about participants.

[0378] "Analytical means for analyzing emotions" refers to methods or processes for determining a participant's emotional state by analyzing their voice tone and text data.

[0379] "Supplier" refers to a business entity or individual that can provide services to users.

[0380] "Selection method" refers to a method or process for selecting the most appropriate supplier based on analyzed sentiment information.

[0381] "Processing means" refers to the method or process for making reservations or contacting selected suppliers.

[0382] "Update method" refers to the method or process for communicating new information to selected suppliers and reflecting that information when reservations or schedules are changed.

[0383] "Management function" refers to a set of methods or procedures for collecting and maintaining information about suppliers.

[0384] "Notification function" refers to a method or system for providing participants or users with necessary information and updates.

[0385] This system automates event planning tasks while considering the emotional state of participants to maximize the user experience. Specifically, it employs a configuration centered around users, terminals, and servers.

[0386] The user uses a device to enter information such as participant attributes. This information includes name, contact information, intention to participate, and details of the event. The device then sends this data to the server.

[0387] The server first receives participant attributes using an information acquisition method. Next, it uses an emotion engine as an analysis method, utilizing a speech recognition API or natural language processing library (e.g., Google Cloud Natural Language API) to analyze the data and extract the participants' emotions. Based on these analysis results, it uses an algorithm as a selection method to select the most appropriate supplier.

[0388] Furthermore, the server uses processing mechanisms to automatically make reservations with selected suppliers. Information collection and management from suppliers are handled by the management function. If reservation details or changes occur, the information is transmitted to the supplier via the update mechanism, and the changes are reflected. Participants and users are sent information as needed through the notification function.

[0389] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server uses an emotion engine to detect this anxiety, selects a supplier with a history of high customer satisfaction, and provides special support features. Similarly, when sending out membership fee collection notifications, the server detects changes in emotion and provides the most appropriate notification content.

[0390] An example of a prompt to input into the generating AI model is, "If a user is feeling a little anxious about organizing an event for the first time, what kind of support can be offered?"

[0391] In this way, the system takes participants' emotions into consideration in real time, enabling more personalized automation of event planning tasks.

[0392] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0393] Step 1:

[0394] Users use a terminal to enter participant attributes and details of the banquet. The entered data includes name, contact information, participation intention, date of the banquet, and location. This information is collected in the terminal's input fields and formatted into a data format before transmission.

[0395] Step 2:

[0396] The terminal sends formatted participant information to the server. This transmission primarily uses the HTTPS protocol to ensure the security of the information. The data is received on the server side and stored in a database for subsequent processing.

[0397] Step 3:

[0398] The server uses information retrieval methods to extract participant attributes from the database. Based on this information, it prepares an input dataset for sentiment analysis. The extracted data is converted into voice input or text data.

[0399] Step 4:

[0400] The server activates the emotion engine and performs sentiment analysis using the dataset. This analysis utilizes speech recognition APIs and natural language processing libraries to calculate sentiment parameters from the input data. The output sentiment parameters include joy, anxiety, and anticipation.

[0401] Step 5:

[0402] The server uses a selection method to select suppliers based on sentiment parameters. It filters the supplier database based on high ratings and specific services to generate a list of optimal suppliers.

[0403] Step 6:

[0404] The server automatically makes reservations with selected suppliers using a processing mechanism. Reservation information is sent via the supplier's API, and the reservation is confirmed. The confirmed reservation information is then notified to the user by the server.

[0405] Step 7:

[0406] Upon user request, a change request is sent from the terminal to the server. The server uses an update mechanism to share the changes with the supplier, who then verifies and updates the changes. The user is then notified of the changes.

[0407] This series of processes allows users to receive personalized service that takes into account the feelings of the participants, and automates the tasks of event organizers.

[0408] (Application Example 2)

[0409] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0410] Traditional event planning processes often fail to efficiently gather participant information and consider their emotions, resulting in a lack of personalization and flexibility in the user experience. Furthermore, the absence of appropriate, emotion-based suggestions can lead to events failing to meet expectations.

[0411] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0412] In this invention, the server includes information receiving means for acquiring participant attribute information, information analysis means for identifying appropriate recipients based on the acquired participant information, and sentiment analysis means for determining the user's emotional state and optimizing the suggested content based on that state. This enables personalized event planning and efficient information sharing.

[0413] "Participant attribute information" refers to information including personal data and preferences of people associated with the event.

[0414] "Information receiving means" refers to devices or methods for obtaining relevant information from participants.

[0415] A "recipient" refers to an external location or service provider selected for an event or service.

[0416] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and emotional data to select appropriate recipients.

[0417] "Reservation execution means" refers to a device or procedure for automatically establishing a reservation for a specified recipient.

[0418] "Change adjustment means" refers to a method or device for coordinating changes to the scale or date and time of an event with the provider, and for confirming and managing the changes.

[0419] "Information management means" refers to devices or systems for managing recipient information and receiving necessary user input.

[0420] "User's emotional state" refers to the type and intensity of emotions a user exhibits at a particular point in time.

[0421] "Emotional analysis means" refers to a method or device that analyzes a user's voice or text, determines their emotional state, and reflects that in the suggested content.

[0422] To implement this invention, the system is configured as follows: The server acquires participant attribute information received from the user's terminal using information receiving means. Information analysis means on the server analyzes this information and identifies the optimal recipient. At that time, emotion analysis means determines the user's emotional state and optimizes the suggested content based on the analysis results.

[0423] The reservation execution mechanism automatically completes the reservation with the specified provider. The change adjustment mechanism processes changes to the number of participants and date / time from the user, coordinates with the provider, and confirms the changes. After receiving confirmation of the changes from the provider, the user is notified of the details through the information management mechanism.

[0424] Specific technologies include speech recognition software (e.g., Google Speech-to-Text) and sentiment analysis engines (e.g., IBM Watson Emotion Analysis). Data is processed on cloud-based servers and updated in real time.

[0425] For example, if a user enters "I want to plan my daughter's birthday party" on their device, this information is sent to the server, and sentiment analysis determines that the user has a high level of anticipation. Based on this, suggestions are provided, including particularly highly-rated restaurants and services.

[0426] Example of a prompt:

[0427] "Please tell the user about their birthday plans. Take their feelings into consideration and generate appropriate suggestions."

[0428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0429] Step 1:

[0430] The terminal receives participant attribute information and initial event information entered by the user. This input includes participant names, interests, and the date and time of the event. The information is formatted appropriately and sent to the server.

[0431] Step 2:

[0432] The server acquires participant information transmitted from the terminal using information receiving means. Based on the acquired information, it analyzes this data using information analysis means. As part of the data processing, filtering is performed to identify recipients that match the participant's preferences and attributes.

[0433] Step 3:

[0434] The server uses emotion analysis tools to determine the user's emotional state from their voice or text input. This process uses an emotion analysis engine to analyze voice waveforms or text patterns as input and generate emotions such as joy, anticipation, and dissatisfaction as output.

[0435] Step 4:

[0436] The server determines appropriate recipient candidates based on the analyzed information and emotional state. The information analysis means selects recipients by referring to their evaluations and past user feedback. The list of selected recipients is passed to the reservation execution means.

[0437] Step 5:

[0438] The server automatically makes a reservation to the specified recipient using the reservation execution mechanism. Reservation confirmation data is generated as output and fed back to the user's terminal for verification.

[0439] Step 6:

[0440] If a user wishes to make changes, the server receives a change request from the terminal. The change adjustment mechanism then reconciles with the supplier and confirms the changes. The user is notified of the changes and the confirmation result, and this information is recorded as new information.

[0441] Step 7:

[0442] The server uses information management tools to register and manage recipient information, and updates necessary information as needed. This ensures that users receive the latest recipient information. In addition, feedback based on user sentiment is generated as prompt messages and recorded for future suggestions.

[0443] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0444] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0445] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0446] [Third Embodiment]

[0447] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0448] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0449] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0450] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0451] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0452] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0453] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0454] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0455] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0456] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0457] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0458] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0459] The AI ​​system for organizing banquets based on the present invention is designed to efficiently automate the tasks of organizing banquets. This system operates in a manner where the user inputs participant information from a terminal, and the server analyzes that data. The following describes specific embodiments for implementing the present invention.

[0460] First, the user uses a terminal to input the information necessary for organizing the event into the system. This information includes participants' names, ages, positions, preferences, budget, and proposed dates. This information is retrieved by the terminal and sent to the server.

[0461] Next, the server analyzes the received information and uses an AI algorithm to select the most suitable supplier (restaurant or service provider). This algorithm uses its accumulated database and information on partner suppliers to select the supplier that best matches the participant's preferences. In this process, the server picks out multiple candidates and narrows down the options to the best choice.

[0462] Once the selection is complete, the server automatically makes a reservation with the supplier using the online reservation system. The reservation details are then notified to the user and provided as a confirmation email. This frees the organizer from the hassle of making reservations manually.

[0463] Furthermore, if a user changes the number of participants or the date using their device, that change information is sent back to the server. The server then notifies the supplier of the changes and automatically handles securing additional space and confirming cancellation fees. As soon as it receives a response from the supplier, it notifies the user of that information.

[0464] Furthermore, the server can automatically send reminders to participants about collecting their membership fees. This feature eliminates the need for organizers to contact participants individually, allowing for more efficient fundraising.

[0465] As a concrete example, consider a scenario where 10 young employees are organizing a company party. The user inputs details into the system, such as the participants' preferences ("Japanese food"), a budget ("4,000 yen per person"), and a preferred date ("May 20th"). Based on this information, the server searches for a suitable Japanese restaurant, automatically makes a reservation at a restaurant with availability on the preferred date, and notifies the user of the details. Subsequently, if the number of participants changes, the server automatically adjusts the reservation and notifies the user of the confirmed changes.

[0466] In this way, the AI ​​system for organizing banquets can automate a large portion of the organizing tasks, reducing the workload for users.

[0467] The following describes the processing flow.

[0468] Step 1:

[0469] The user logs into the system via their device and enters participant information. This information includes the participant's name, age, job title, preferences, budget, and preferred dates. The device then sends this data to the server.

[0470] Step 2:

[0471] The server analyzes the received participant information and uses an AI algorithm to select multiple potential suppliers based on the participant's preferences and budget. The selection is made by searching for suitable stores in a database on the network.

[0472] Step 3:

[0473] The server evaluates the selected candidate stores and determines the best store. Selection criteria include store reviews, ratings, distance, price range, etc. The server then selects the most suitable store from the candidates.

[0474] Step 4:

[0475] The server automatically makes a reservation at a selected restaurant. Using an online reservation system, it secures seats according to the desired date, time, and number of people. The user is then notified of the reservation confirmation.

[0476] Step 5:

[0477] When a user changes the number of participants or the date from their device, they send that information to the server. The server then contacts the supplier based on the changes to confirm whether the changes are possible.

[0478] Step 6:

[0479] The server receives confirmation from the supplier and notifies the user once the changes are finalized. It also informs the user whether or not a cancellation fee will apply.

[0480] Step 7:

[0481] The server sends reminders to participants about collecting membership fees at pre-set times. Payment methods and deadlines are communicated via email or messaging apps.

[0482] Step 8:

[0483] When a supplier registers with the system, the server provides an interface and accepts registration information. The server handles billing for registration fees and promotions for new registrations.

[0484] (Example 1)

[0485] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0486] In modern meetings and gatherings, organizers face a wide range of challenges. Specifically, these include complex tasks such as managing participant information, selecting appropriate suppliers, handling reservations, and responding to changes in participant numbers and dates. Performing these tasks manually is time-consuming and laborious, placing a significant burden on busy organizers. Therefore, there is a need for systems that streamline these tasks and reduce the burden on organizers.

[0487] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0488] In this invention, the server includes an input means for users to input participant information via a terminal, a transmission means for transmitting participant information collected by the terminal to the server, and an analysis means for the server to analyze the received participant information using an AI model and select an appropriate supplier. This makes it possible to automate the cumbersome organizing tasks and operate the event efficiently.

[0489] A "user" refers to the entity that accesses the system and inputs the necessary information.

[0490] "Terminal" refers to a device such as a computer or smartphone that a user uses to input information.

[0491] A "server" refers to a central computer system that receives information sent from terminals and processes it for tasks such as analysis, reservations, and notifications.

[0492] "Participant information" refers to detailed data about each individual attending a meeting, which users enter into the system.

[0493] An "AI model" refers to a system that uses artificial intelligence to analyze data and includes algorithms for selecting the most suitable supplier.

[0494] "Suppliers" refer to restaurants, service providers, and other businesses that provide the services and goods necessary for an event or meeting.

[0495] "Analysis means" refers to a series of processes and algorithms used by the server to process the received information and select the appropriate supplier.

[0496] "Reservation method" refers to a function that automatically makes reservations with suppliers selected by the server.

[0497] "Change management means" refers to a function that communicates user-entered changes to suppliers and manages their response.

[0498] "Supplier management means" refers to functions that manage supplier information and support the registration of new suppliers.

[0499] "Notification means" refers to the methods and functions that a system uses to provide important information to users or participants.

[0500] This invention is a system that efficiently automates the tasks of organizing banquets. The system automates everything from selecting appropriate suppliers to confirming reservations by having users input participant information using a terminal, which is then received and analyzed by a server. The hardware consists of a standard computer and mobile terminal, utilizing a cloud server as needed. Part of the software incorporates a generative AI model to perform data analysis for selecting the optimal supplier.

[0501] First, the user enters participant information such as name, age, position, preferences, budget, and preferred dates into the system using a terminal. This data is sent from the terminal to the server, which uses a generative AI model to analyze the data and select the supplier that best matches the participant's preferences from its database. The server then automatically makes a reservation with the selected supplier via an API. The user is notified of the reservation results and details, thus freeing them from physical procedures.

[0502] As a practical example, consider a banquet for 10 young employees. The user enters prompt text into the system such as "Participant information: Name, age, preference: Japanese food, budget: 4000 yen per person, proposed date: May 20th." The AI ​​then analyzes a list of Japanese restaurants, selects a restaurant that meets the criteria, and automatically confirms the reservation. At this time, the server also automates the confirmation of the reservation and the handling of changes in the number of participants, ensuring smooth communication and inquiries with suppliers.

[0503] In this way, the system reduces the burden on the organizer and enables efficient management of banquets.

[0504] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0505] Step 1:

[0506] The user enters participant information using a device.

[0507] In terms of the specific process, the user enters participant information such as name, age, job title, preferences, budget, and preferred dates into an input form on the device.

[0508] The input data is temporarily stored on the terminal.

[0509] Step 2:

[0510] The device sends the participant information it has collected to the server.

[0511] Specifically, the device transmits the collected data to the server via the internet.

[0512] In this process, data is securely transferred using an encryption protocol. The input is participant information, and the output is data stored on the server.

[0513] Step 3:

[0514] The server analyzes the participant information it receives using an AI model.

[0515] The server receives participant information as input and uses a generative AI model to analyze the database to find suppliers that meet the participant's preferences.

[0516] On the server, a prompt message is generated, and an algorithm selects the most appropriate supplier based on the data. This analysis process outputs a list of candidate suppliers.

[0517] Step 4:

[0518] The server automatically makes a reservation with the supplier it deems most suitable.

[0519] Specifically, the server automates the reservation process by accessing the supplier's reservation system API and providing the necessary input information.

[0520] The inputs are a supplier list and booking details, and the output is confirmed booking information.

[0521] Step 5:

[0522] The server notifies the user of the reservation information.

[0523] The server sends the reservation results to the user via email or app notification, allowing them to confirm the reservation details.

[0524] At this stage, reservation information is provided as output in a format that the user can verify.

[0525] Step 6:

[0526] When a user changes the number of participants or the schedule using their device, these changes are then communicated to the server.

[0527] The user enters the changes on the screen and sends them to the server.

[0528] The input is change information, and the output is the latest reservation data updated by the server.

[0529] Step 7:

[0530] The server receives the change information and contacts the supplier to modify the reservation details.

[0531] The server sends change information to the supplier's system, waits for a response, and then provides that information as feedback to the user.

[0532] In this process, the input is the changes made, and the output is the confirmation result from the supplier and the update reservation information based on that confirmation.

[0533] (Application Example 1)

[0534] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0535] Currently, organizing banquets and events requires considerable effort and time. Among these tasks, gathering participant information, selecting the most suitable suppliers, booking procedures, and managing changes to participant numbers and dates are particularly cumbersome. There is a need to streamline these tasks and reduce the burden through automation. Furthermore, it would be desirable for users to be able to provide information via voice input, and for appropriate plans to be immediately proposed and confirmed based on that information.

[0536] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0537] In this invention, the server includes an information acquisition means for receiving participant information, an information analysis means for analyzing the received participant information and selecting an appropriate supplier, and a voice input means for acquiring participant information using speech recognition. This automates many of the organizing tasks and enables quick and efficient reservations, changes, and adjustments through intuitive voice operation.

[0538] "Information acquisition means" refers to a method or device for collecting information from participants.

[0539] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and selecting the most suitable supplier.

[0540] "Reservation processing means" refers to a method or apparatus for automatically executing a reservation with a selected supplier.

[0541] "Change adjustment means" refers to a method or device for contacting the supplier and confirming and adjusting the changes when the number of participants or the schedule changes.

[0542] "Information management means" refers to a method or apparatus for managing information about suppliers and accepting supplier registrations.

[0543] "Voice input means" refers to a method or device for obtaining information from participants using speech recognition technology.

[0544] A "plan proposal means" is a method or device for proposing and notifying participants of an optimal plan based on information acquired via voice.

[0545] This invention is a system for streamlining the tasks of organizing banquets and events. The server has an information acquisition means for receiving participant information, an information analysis means for analyzing the acquired participant information, and a voice input means for acquiring information using speech recognition. When a user gives instructions by voice through a terminal, the voice input means converts this into text data. The converted data is sent to the server and analyzed by the information analysis means. Here, the supplier best suited to the participants' preferences, budget, and schedule is selected.

[0546] Once the selection is complete, the reservation processing system automatically makes the reservation. Reservation information and suggested plans are fed back to the user through the plan suggestion system. If the user wants to update participant information, they can do so by voice command using their terminal. For example, if the user says, "Tell me some restaurants you recommend for a birthday party next Saturday," the server will select a restaurant based on that information and suggest a suitable plan.

[0547] This system uses the "speech_recognition" library as its speech recognition technology, and for server-side information analysis, it utilizes information from partner suppliers and accumulated databases. Furthermore, notifications and suggestions are sent immediately to the terminal after selection. It is also possible to propose plans using a generated AI model. An example of a prompt message would be, "Please suggest the best dinner location based on the user's preferences."

[0548] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0549] Step 1:

[0550] The user activates a voice input method using a terminal and provides information about the event verbally. This input is converted to text by speech recognition technology. The input is audio data, and the output is text data. Specifically, speech recognition involves capturing audio through a microphone.

[0551] Step 2:

[0552] The server passes the text data obtained via voice input to the information analysis system. Here, the system selects the optimal supplier based on supplier information stored in the database and participant conditions (preferences, budget, schedule, etc.). The input is text data, and the output is a list of optimal suppliers. A generative AI model is used for data analysis, filtering through a vast number of candidates.

[0553] Step 3:

[0554] The server automatically sends reservation requests to selected suppliers using the reservation processing mechanism. This step involves API calls or online form submissions to the supplier's reservation system. The input is a list of selected suppliers, and the output is reservation confirmation information. Reservation details are processed through the registered API.

[0555] Step 4:

[0556] The user receives booking confirmation information and suggested plans on their device. This information is notified to the user through a plan suggestion system. The input is booking confirmation information, and the output is the plan details displayed on the device. When notifying the user, they can choose between voice or text.

[0557] Step 5:

[0558] Users can modify participant information and event conditions as needed, and send a new request to the server via their device. This new information is then transmitted to the server using voice input. The input is the updated participant information, and the output is the latest selection results and updated information. The system quickly recognizes the changes, and the re-analysis process starts automatically.

[0559] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0560] The system based on this invention incorporates an emotion engine to optimize the user experience and provides more personalized automation of event planning tasks. The following describes specific embodiments for carrying out this invention.

[0561] In this system, users first input participant information using a terminal. This information includes participants' personal data and details of the event. The terminal then sends this information to the server.

[0562] Next, the server utilizes an emotion engine to recognize emotions from the user's voice tone and text input. The emotion engine can analyze emotional states such as joy, dissatisfaction, and anticipation in real time.

[0563] Based on the results of emotion recognition, the server adjusts the criteria for selecting suppliers. For example, if a user expresses particularly cheerful emotions, it will prioritize selecting highly-rated restaurants or establishments offering special services. The emotion engine can also customize the services offered by suppliers to meet individual needs.

[0564] Once the selection is complete, the server automatically makes a reservation at the chosen store and notifies the user of the reservation details. Furthermore, even if the user requests a change from their device, the server, via the emotion engine, reconfirms the user's emotional state and proposes a solution that suits their feelings.

[0565] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server, based on the detection of anxiety by its emotion engine, selects a venue with a high satisfaction rating in the past and provides emphasized support features. Similarly, when sending notifications about collecting membership fees, the server detects changes in emotion and optimizes the notification content as needed.

[0566] Thus, the present invention provides an automated system for organizing tasks that takes user emotions into consideration, achieving deeper customization and greater flexibility than conventional systems.

[0567] The following describes the processing flow.

[0568] Step 1:

[0569] The user logs into the system using a terminal and enters participant information and banquet details. This includes data such as participants' names, ages, preferences, budget, and preferred dates. The terminal then sends this information to the server.

[0570] Step 2:

[0571] The server analyzes the received information. During this process, the emotion engine analyzes the user's emotions from their voice tone and text data. The emotion engine determines emotional states such as joy, anxiety, and anticipation.

[0572] Step 3:

[0573] Based on the analysis results from the emotion engine, the server adjusts the supplier selection criteria. For example, if the user's input indicates heightened emotions, the server will prioritize selecting restaurants with a special atmosphere or highly-rated establishments.

[0574] Step 4:

[0575] The server automatically makes a reservation with a selected supplier. After the reservation is confirmed, the server notifies the user of the details. This information includes the reservation details and directions to the store.

[0576] Step 5:

[0577] If a user needs to change the number of participants or the schedule via their device, the server uses an emotion engine to re-evaluate the user's emotional state. If the user is feeling anxious, it will suggest additional support options.

[0578] Step 6:

[0579] The server contacts the supplier to obtain approval for the changes. Once the changes are approved, the server notifies the user of the result. If cancellation fees apply, the information will also be provided in an emotionally sensitive manner.

[0580] Step 7:

[0581] The server sends reminders for membership fee collection at pre-configured times. During this process, the emotion engine adjusts the notification content to match the user's emotions, facilitating smooth communication.

[0582] This process allows systems incorporating an emotion engine to provide a personalized user experience that goes beyond typical event management tasks.

[0583] (Example 2)

[0584] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0585] Current automated systems for event planning, designed to maximize user experience, have the challenge of not being able to adequately personalize them because they do not take into account the emotional state of participants. Furthermore, they lack real-time, optimized responses when selecting suppliers or changing reservations.

[0586] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0587] In this invention, the server includes an information acquisition means for acquiring participant attributes, an analysis means for analyzing emotions based on the acquired participant attributes, and a selection means for selecting an appropriate supplier based on the analyzed emotions. This makes it possible to select the optimal supplier while considering the participants' emotions in real time.

[0588] "Participant attributes" refer to basic information related to the participant, including name, contact information, and intention to participate.

[0589] "Information acquisition means" refers to the method or process by which the server collects basic information about participants.

[0590] "Analytical means for analyzing emotions" refers to methods or processes for determining a participant's emotional state by analyzing their voice tone and text data.

[0591] "Supplier" refers to a business entity or individual that can provide services to users.

[0592] "Selection method" refers to a method or process for selecting the most appropriate supplier based on analyzed sentiment information.

[0593] "Processing means" refers to the method or process for making reservations or contacting selected suppliers.

[0594] "Update method" refers to the method or process for communicating new information to selected suppliers and reflecting that information when reservations or schedules are changed.

[0595] "Management function" refers to a set of methods or procedures for collecting and maintaining information about suppliers.

[0596] "Notification function" refers to a method or system for providing participants or users with necessary information and updates.

[0597] This system automates event planning tasks while considering the emotional state of participants to maximize the user experience. Specifically, it employs a configuration centered around users, terminals, and servers.

[0598] The user uses a device to enter information such as participant attributes. This information includes name, contact information, intention to participate, and details of the event. The device then sends this data to the server.

[0599] The server first receives participant attributes using an information acquisition method. Next, it uses an emotion engine as an analysis method, utilizing a speech recognition API or natural language processing library (e.g., Google Cloud Natural Language API) to analyze the data and extract the participants' emotions. Based on these analysis results, it uses an algorithm as a selection method to select the most appropriate supplier.

[0600] Furthermore, the server uses processing mechanisms to automatically make reservations with selected suppliers. Information collection and management from suppliers are handled by the management function. If reservation details or changes occur, the information is transmitted to the supplier via the update mechanism, and the changes are reflected. Participants and users are sent information as needed through the notification function.

[0601] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server uses an emotion engine to detect this anxiety, selects a supplier with a history of high customer satisfaction, and provides special support features. Similarly, when sending out membership fee collection notifications, the server detects changes in emotion and provides the most appropriate notification content.

[0602] An example of a prompt to input into the generating AI model is, "If a user is feeling a little anxious about organizing an event for the first time, what kind of support can be offered?"

[0603] In this way, the system takes participants' emotions into consideration in real time, enabling more personalized automation of event planning tasks.

[0604] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0605] Step 1:

[0606] Users use a terminal to enter participant attributes and details of the banquet. The entered data includes name, contact information, participation intention, date of the banquet, and location. This information is collected in the terminal's input fields and formatted into a data format before transmission.

[0607] Step 2:

[0608] The terminal sends formatted participant information to the server. This transmission primarily uses the HTTPS protocol to ensure the security of the information. The data is received on the server side and stored in a database for subsequent processing.

[0609] Step 3:

[0610] The server uses information retrieval methods to extract participant attributes from the database. Based on this information, it prepares an input dataset for sentiment analysis. The extracted data is converted into voice input or text data.

[0611] Step 4:

[0612] The server activates the emotion engine and performs sentiment analysis using the dataset. This analysis utilizes speech recognition APIs and natural language processing libraries to calculate sentiment parameters from the input data. The output sentiment parameters include joy, anxiety, and anticipation.

[0613] Step 5:

[0614] The server uses a selection method to select suppliers based on sentiment parameters. It filters the supplier database based on high ratings and specific services to generate a list of optimal suppliers.

[0615] Step 6:

[0616] The server automatically makes reservations with selected suppliers using a processing mechanism. Reservation information is sent via the supplier's API, and the reservation is confirmed. The confirmed reservation information is then notified to the user by the server.

[0617] Step 7:

[0618] Upon user request, a change request is sent from the terminal to the server. The server uses an update mechanism to share the changes with the supplier, who then verifies and updates the changes. The user is then notified of the changes.

[0619] This series of processes allows users to receive personalized service that takes into account the feelings of the participants, and automates the tasks of event organizers.

[0620] (Application Example 2)

[0621] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0622] Traditional event planning processes often fail to efficiently gather participant information and consider their emotions, resulting in a lack of personalization and flexibility in the user experience. Furthermore, the absence of appropriate, emotion-based suggestions can lead to events failing to meet expectations.

[0623] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0624] In this invention, the server includes information receiving means for acquiring participant attribute information, information analysis means for identifying appropriate recipients based on the acquired participant information, and sentiment analysis means for determining the user's emotional state and optimizing the suggested content based on that state. This enables personalized event planning and efficient information sharing.

[0625] "Participant attribute information" refers to information including personal data and preferences of people associated with the event.

[0626] "Information receiving means" refers to devices or methods for obtaining relevant information from participants.

[0627] A "recipient" refers to an external location or service provider selected for an event or service.

[0628] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and emotional data to select appropriate recipients.

[0629] "Reservation execution means" refers to a device or procedure for automatically establishing a reservation for a specified recipient.

[0630] "Change adjustment means" refers to a method or device for coordinating changes to the scale or date and time of an event with the provider, and for confirming and managing the changes.

[0631] "Information management means" refers to devices or systems for managing recipient information and receiving necessary user input.

[0632] "User's emotional state" refers to the type and intensity of emotions a user exhibits at a particular point in time.

[0633] "Emotional analysis means" refers to a method or device that analyzes a user's voice or text, determines their emotional state, and reflects that in the suggested content.

[0634] To implement this invention, the system is configured as follows: The server acquires participant attribute information received from the user's terminal using information receiving means. Information analysis means on the server analyzes this information and identifies the optimal recipient. At that time, emotion analysis means determines the user's emotional state and optimizes the suggested content based on the analysis results.

[0635] The reservation execution mechanism automatically completes the reservation with the specified provider. The change adjustment mechanism processes changes to the number of participants and date / time from the user, coordinates with the provider, and confirms the changes. After receiving confirmation of the changes from the provider, the user is notified of the details through the information management mechanism.

[0636] Specific technologies include speech recognition software (e.g., Google Speech-to-Text) and sentiment analysis engines (e.g., IBM Watson Emotion Analysis). Data is processed on cloud-based servers and updated in real time.

[0637] For example, if a user enters "I want to plan my daughter's birthday party" on their device, this information is sent to the server, and sentiment analysis determines that the user has a high level of anticipation. Based on this, suggestions are provided, including particularly highly-rated restaurants and services.

[0638] Example of a prompt:

[0639] "Please tell the user about their birthday plans. Take their feelings into consideration and generate appropriate suggestions."

[0640] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0641] Step 1:

[0642] The terminal receives participant attribute information and initial event information entered by the user. This input includes participant names, interests, and the date and time of the event. The information is formatted appropriately and sent to the server.

[0643] Step 2:

[0644] The server acquires participant information transmitted from the terminal using information receiving means. Based on the acquired information, it analyzes this data using information analysis means. As part of the data processing, filtering is performed to identify recipients that match the participant's preferences and attributes.

[0645] Step 3:

[0646] The server uses emotion analysis tools to determine the user's emotional state from their voice or text input. This process uses an emotion analysis engine to analyze voice waveforms or text patterns as input and generate emotions such as joy, anticipation, and dissatisfaction as output.

[0647] Step 4:

[0648] The server determines appropriate recipient candidates based on the analyzed information and emotional state. The information analysis means selects recipients by referring to their evaluations and past user feedback. The list of selected recipients is passed to the reservation execution means.

[0649] Step 5:

[0650] The server automatically makes a reservation to the specified recipient using the reservation execution mechanism. Reservation confirmation data is generated as output and fed back to the user's terminal for verification.

[0651] Step 6:

[0652] If a user wishes to make changes, the server receives a change request from the terminal. The change adjustment mechanism then reconciles with the supplier and confirms the changes. The user is notified of the changes and the confirmation result, and this information is recorded as new information.

[0653] Step 7:

[0654] The server uses information management tools to register and manage recipient information, and updates necessary information as needed. This ensures that users receive the latest recipient information. In addition, feedback based on user sentiment is generated as prompt messages and recorded for future suggestions.

[0655] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0656] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0657] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0658] [Fourth Embodiment]

[0659] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0660] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0661] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0662] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0663] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0664] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0665] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0666] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0667] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0668] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0669] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0670] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0671] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0672] The AI ​​system for organizing banquets based on the present invention is designed to efficiently automate the tasks of organizing banquets. This system operates in a manner where the user inputs participant information from a terminal, and the server analyzes that data. The following describes specific embodiments for implementing the present invention.

[0673] First, the user uses a terminal to input the information necessary for organizing the event into the system. This information includes participants' names, ages, positions, preferences, budget, and proposed dates. This information is retrieved by the terminal and sent to the server.

[0674] Next, the server analyzes the received information and uses an AI algorithm to select the most suitable supplier (restaurant or service provider). This algorithm uses its accumulated database and information on partner suppliers to select the supplier that best matches the participant's preferences. In this process, the server picks out multiple candidates and narrows down the options to the best choice.

[0675] Once the selection is complete, the server automatically makes a reservation with the supplier using the online reservation system. The reservation details are then notified to the user and provided as a confirmation email. This frees the organizer from the hassle of making reservations manually.

[0676] Furthermore, if a user changes the number of participants or the date using their device, that change information is sent back to the server. The server then notifies the supplier of the changes and automatically handles securing additional space and confirming cancellation fees. As soon as it receives a response from the supplier, it notifies the user of that information.

[0677] Furthermore, the server can automatically send reminders to participants about collecting their membership fees. This feature eliminates the need for organizers to contact participants individually, allowing for more efficient fundraising.

[0678] As a concrete example, consider a scenario where 10 young employees are organizing a company party. The user inputs details into the system, such as the participants' preferences ("Japanese food"), a budget ("4,000 yen per person"), and a preferred date ("May 20th"). Based on this information, the server searches for a suitable Japanese restaurant, automatically makes a reservation at a restaurant with availability on the preferred date, and notifies the user of the details. Subsequently, if the number of participants changes, the server automatically adjusts the reservation and notifies the user of the confirmed changes.

[0679] In this way, the AI ​​system for organizing banquets can automate a large portion of the organizing tasks, reducing the workload for users.

[0680] The following describes the processing flow.

[0681] Step 1:

[0682] The user logs into the system via their device and enters participant information. This information includes the participant's name, age, job title, preferences, budget, and preferred dates. The device then sends this data to the server.

[0683] Step 2:

[0684] The server analyzes the received participant information and uses an AI algorithm to select multiple potential suppliers based on the participant's preferences and budget. The selection is made by searching for suitable stores in a database on the network.

[0685] Step 3:

[0686] The server evaluates the selected candidate stores and determines the best store. Selection criteria include store reviews, ratings, distance, price range, etc. The server then selects the most suitable store from the candidates.

[0687] Step 4:

[0688] The server automatically makes a reservation at a selected restaurant. Using an online reservation system, it secures seats according to the desired date, time, and number of people. The user is then notified of the reservation confirmation.

[0689] Step 5:

[0690] When a user changes the number of participants or the date from their device, they send that information to the server. The server then contacts the supplier based on the changes to confirm whether the changes are possible.

[0691] Step 6:

[0692] The server receives confirmation from the supplier and notifies the user once the changes are finalized. It also informs the user whether or not a cancellation fee will apply.

[0693] Step 7:

[0694] The server sends reminders to participants about collecting membership fees at pre-set times. Payment methods and deadlines are communicated via email or messaging apps.

[0695] Step 8:

[0696] When a supplier registers with the system, the server provides an interface and accepts registration information. The server handles billing for registration fees and promotions for new registrations.

[0697] (Example 1)

[0698] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0699] In modern meetings and gatherings, organizers face a wide range of challenges. Specifically, these include complex tasks such as managing participant information, selecting appropriate suppliers, handling reservations, and responding to changes in participant numbers and dates. Performing these tasks manually is time-consuming and laborious, placing a significant burden on busy organizers. Therefore, there is a need for systems that streamline these tasks and reduce the burden on organizers.

[0700] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0701] In this invention, the server includes an input means for users to input participant information via a terminal, a transmission means for transmitting participant information collected by the terminal to the server, and an analysis means for the server to analyze the received participant information using an AI model and select an appropriate supplier. This makes it possible to automate the cumbersome organizing tasks and operate the event efficiently.

[0702] A "user" refers to the entity that accesses the system and inputs the necessary information.

[0703] "Terminal" refers to a device such as a computer or smartphone that a user uses to input information.

[0704] A "server" refers to a central computer system that receives information sent from terminals and processes it for tasks such as analysis, reservations, and notifications.

[0705] "Participant information" refers to detailed data about each individual attending a meeting, which users enter into the system.

[0706] An "AI model" refers to a system that uses artificial intelligence to analyze data and includes algorithms for selecting the most suitable supplier.

[0707] "Suppliers" refer to restaurants, service providers, and other businesses that provide the services and goods necessary for an event or meeting.

[0708] "Analysis means" refers to a series of processes and algorithms used by the server to process the received information and select the appropriate supplier.

[0709] "Reservation method" refers to a function that automatically makes reservations with suppliers selected by the server.

[0710] "Change management means" refers to a function that communicates user-entered changes to suppliers and manages their response.

[0711] "Supplier management means" refers to functions that manage supplier information and support the registration of new suppliers.

[0712] "Notification means" refers to the methods and functions that a system uses to provide important information to users or participants.

[0713] This invention is a system that efficiently automates the tasks of organizing banquets. The system automates everything from selecting appropriate suppliers to confirming reservations by having users input participant information using a terminal, which is then received and analyzed by a server. The hardware consists of a standard computer and mobile terminal, utilizing a cloud server as needed. Part of the software incorporates a generative AI model to perform data analysis for selecting the optimal supplier.

[0714] First, the user enters participant information such as name, age, position, preferences, budget, and preferred dates into the system using a terminal. This data is sent from the terminal to the server, which uses a generative AI model to analyze the data and select the supplier that best matches the participant's preferences from its database. The server then automatically makes a reservation with the selected supplier via an API. The user is notified of the reservation results and details, thus freeing them from physical procedures.

[0715] As a practical example, consider a banquet for 10 young employees. The user enters prompt text into the system such as "Participant information: Name, age, preference: Japanese food, budget: 4000 yen per person, proposed date: May 20th." The AI ​​then analyzes a list of Japanese restaurants, selects a restaurant that meets the criteria, and automatically confirms the reservation. At this time, the server also automates the confirmation of the reservation and the handling of changes in the number of participants, ensuring smooth communication and inquiries with suppliers.

[0716] In this way, the system reduces the burden on the organizer and enables efficient management of banquets.

[0717] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0718] Step 1:

[0719] The user enters participant information using a device.

[0720] In terms of the specific process, the user enters participant information such as name, age, job title, preferences, budget, and preferred dates into an input form on the device.

[0721] The input data is temporarily stored on the terminal.

[0722] Step 2:

[0723] The device sends the participant information it has collected to the server.

[0724] Specifically, the device transmits the collected data to the server via the internet.

[0725] In this process, data is securely transferred using an encryption protocol. The input is participant information, and the output is data stored on the server.

[0726] Step 3:

[0727] The server analyzes the participant information it receives using an AI model.

[0728] The server receives participant information as input and uses a generative AI model to analyze the database to find suppliers that meet the participant's preferences.

[0729] On the server, a prompt message is generated, and an algorithm selects the most appropriate supplier based on the data. This analysis process outputs a list of candidate suppliers.

[0730] Step 4:

[0731] The server automatically makes a reservation with the supplier it deems most suitable.

[0732] Specifically, the server automates the reservation process by accessing the supplier's reservation system API and providing the necessary input information.

[0733] The inputs are a supplier list and booking details, and the output is confirmed booking information.

[0734] Step 5:

[0735] The server notifies the user of the reservation information.

[0736] The server sends the reservation results to the user via email or app notification, allowing them to confirm the reservation details.

[0737] At this stage, reservation information is provided as output in a format that the user can verify.

[0738] Step 6:

[0739] When a user changes the number of participants or the schedule using their device, these changes are then communicated to the server.

[0740] The user enters the changes on the screen and sends them to the server.

[0741] The input is change information, and the output is the latest reservation data updated by the server.

[0742] Step 7:

[0743] The server receives the change information and contacts the supplier to modify the reservation details.

[0744] The server sends change information to the supplier's system, waits for a response, and then provides that information as feedback to the user.

[0745] In this process, the input is the changes made, and the output is the confirmation result from the supplier and the update reservation information based on that confirmation.

[0746] (Application Example 1)

[0747] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0748] Currently, organizing banquets and events requires considerable effort and time. Among these tasks, gathering participant information, selecting the most suitable suppliers, booking procedures, and managing changes to participant numbers and dates are particularly cumbersome. There is a need to streamline these tasks and reduce the burden through automation. Furthermore, it would be desirable for users to be able to provide information via voice input, and for appropriate plans to be immediately proposed and confirmed based on that information.

[0749] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0750] In this invention, the server includes an information acquisition means for receiving participant information, an information analysis means for analyzing the received participant information and selecting an appropriate supplier, and a voice input means for acquiring participant information using speech recognition. This automates many of the organizing tasks and enables quick and efficient reservations, changes, and adjustments through intuitive voice operation.

[0751] "Information acquisition means" refers to a method or device for collecting information from participants.

[0752] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and selecting the most suitable supplier.

[0753] "Reservation processing means" refers to a method or apparatus for automatically executing a reservation with a selected supplier.

[0754] "Change adjustment means" refers to a method or device for contacting the supplier and confirming and adjusting the changes when the number of participants or the schedule changes.

[0755] "Information management means" refers to a method or apparatus for managing information about suppliers and accepting supplier registrations.

[0756] "Voice input means" refers to a method or device for obtaining information from participants using speech recognition technology.

[0757] A "plan proposal means" is a method or device for proposing and notifying participants of an optimal plan based on information acquired via voice.

[0758] This invention is a system for streamlining the tasks of organizing banquets and events. The server has an information acquisition means for receiving participant information, an information analysis means for analyzing the acquired participant information, and a voice input means for acquiring information using speech recognition. When a user gives instructions by voice through a terminal, the voice input means converts this into text data. The converted data is sent to the server and analyzed by the information analysis means. Here, the supplier best suited to the participants' preferences, budget, and schedule is selected.

[0759] Once the selection is complete, the reservation processing system automatically makes the reservation. Reservation information and suggested plans are fed back to the user through the plan suggestion system. If the user wants to update participant information, they can do so by voice command using their terminal. For example, if the user says, "Tell me some restaurants you recommend for a birthday party next Saturday," the server will select a restaurant based on that information and suggest a suitable plan.

[0760] This system uses the "speech_recognition" library as its speech recognition technology, and for server-side information analysis, it utilizes information from partner suppliers and accumulated databases. Furthermore, notifications and suggestions are sent immediately to the terminal after selection. It is also possible to propose plans using a generated AI model. An example of a prompt message would be, "Please suggest the best dinner location based on the user's preferences."

[0761] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0762] Step 1:

[0763] The user activates a voice input method using a terminal and provides information about the event verbally. This input is converted to text by speech recognition technology. The input is audio data, and the output is text data. Specifically, speech recognition involves capturing audio through a microphone.

[0764] Step 2:

[0765] The server passes the text data obtained via voice input to the information analysis system. Here, the system selects the optimal supplier based on supplier information stored in the database and participant conditions (preferences, budget, schedule, etc.). The input is text data, and the output is a list of optimal suppliers. A generative AI model is used for data analysis, filtering through a vast number of candidates.

[0766] Step 3:

[0767] The server automatically sends reservation requests to selected suppliers using the reservation processing mechanism. This step involves API calls or online form submissions to the supplier's reservation system. The input is a list of selected suppliers, and the output is reservation confirmation information. Reservation details are processed through the registered API.

[0768] Step 4:

[0769] The user receives booking confirmation information and suggested plans on their device. This information is notified to the user through a plan suggestion system. The input is booking confirmation information, and the output is the plan details displayed on the device. When notifying the user, they can choose between voice or text.

[0770] Step 5:

[0771] Users can modify participant information and event conditions as needed, and send a new request to the server via their device. This new information is then transmitted to the server using voice input. The input is the updated participant information, and the output is the latest selection results and updated information. The system quickly recognizes the changes, and the re-analysis process starts automatically.

[0772] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0773] The system based on this invention incorporates an emotion engine to optimize the user experience and provides more personalized automation of event planning tasks. The following describes specific embodiments for carrying out this invention.

[0774] In this system, users first input participant information using a terminal. This information includes participants' personal data and details of the event. The terminal then sends this information to the server.

[0775] Next, the server utilizes an emotion engine to recognize emotions from the user's voice tone and text input. The emotion engine can analyze emotional states such as joy, dissatisfaction, and anticipation in real time.

[0776] Based on the results of emotion recognition, the server adjusts the criteria for selecting suppliers. For example, if a user expresses particularly cheerful emotions, it will prioritize selecting highly-rated restaurants or establishments offering special services. The emotion engine can also customize the services offered by suppliers to meet individual needs.

[0777] Once the selection is complete, the server automatically makes a reservation at the chosen store and notifies the user of the reservation details. Furthermore, even if the user requests a change from their device, the server, via the emotion engine, reconfirms the user's emotional state and proposes a solution that suits their feelings.

[0778] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server, based on the detection of anxiety by its emotion engine, selects a venue with a high satisfaction rating in the past and provides emphasized support features. Similarly, when sending notifications about collecting membership fees, the server detects changes in emotion and optimizes the notification content as needed.

[0779] Thus, the present invention provides an automated system for organizing tasks that takes user emotions into consideration, achieving deeper customization and greater flexibility than conventional systems.

[0780] The following describes the processing flow.

[0781] Step 1:

[0782] The user logs into the system using a terminal and enters participant information and banquet details. This includes data such as participants' names, ages, preferences, budget, and preferred dates. The terminal then sends this information to the server.

[0783] Step 2:

[0784] The server analyzes the received information. During this process, the emotion engine analyzes the user's emotions from their voice tone and text data. The emotion engine determines emotional states such as joy, anxiety, and anticipation.

[0785] Step 3:

[0786] Based on the analysis results from the emotion engine, the server adjusts the supplier selection criteria. For example, if the user's input indicates heightened emotions, the server will prioritize selecting restaurants with a special atmosphere or highly-rated establishments.

[0787] Step 4:

[0788] The server automatically makes a reservation with a selected supplier. After the reservation is confirmed, the server notifies the user of the details. This information includes the reservation details and directions to the store.

[0789] Step 5:

[0790] If a user needs to change the number of participants or the schedule via their device, the server uses an emotion engine to re-evaluate the user's emotional state. If the user is feeling anxious, it will suggest additional support options.

[0791] Step 6:

[0792] The server contacts the supplier to obtain approval for the changes. Once the changes are approved, the server notifies the user of the result. If cancellation fees apply, the information will also be provided in an emotionally sensitive manner.

[0793] Step 7:

[0794] The server sends reminders for membership fee collection at pre-configured times. During this process, the emotion engine adjusts the notification content to match the user's emotions, facilitating smooth communication.

[0795] This process allows systems incorporating an emotion engine to provide a personalized user experience that goes beyond typical event management tasks.

[0796] (Example 2)

[0797] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0798] Current automated systems for event planning, designed to maximize user experience, have the challenge of not being able to adequately personalize them because they do not take into account the emotional state of participants. Furthermore, they lack real-time, optimized responses when selecting suppliers or changing reservations.

[0799] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0800] In this invention, the server includes an information acquisition means for acquiring participant attributes, an analysis means for analyzing emotions based on the acquired participant attributes, and a selection means for selecting an appropriate supplier based on the analyzed emotions. This makes it possible to select the optimal supplier while considering the participants' emotions in real time.

[0801] "Participant attributes" refer to basic information related to the participant, including name, contact information, and intention to participate.

[0802] "Information acquisition means" refers to the method or process by which the server collects basic information about participants.

[0803] "Analytical means for analyzing emotions" refers to methods or processes for determining a participant's emotional state by analyzing their voice tone and text data.

[0804] "Supplier" refers to a business entity or individual that can provide services to users.

[0805] "Selection method" refers to a method or process for selecting the most appropriate supplier based on analyzed sentiment information.

[0806] "Processing means" refers to the method or process for making reservations or contacting selected suppliers.

[0807] "Update method" refers to the method or process for communicating new information to selected suppliers and reflecting that information when reservations or schedules are changed.

[0808] "Management function" refers to a set of methods or procedures for collecting and maintaining information about suppliers.

[0809] "Notification function" refers to a method or system for providing participants or users with necessary information and updates.

[0810] This system automates event planning tasks while considering the emotional state of participants to maximize the user experience. Specifically, it employs a configuration centered around users, terminals, and servers.

[0811] The user uses a device to enter information such as participant attributes. This information includes name, contact information, intention to participate, and details of the event. The device then sends this data to the server.

[0812] The server first receives participant attributes using an information acquisition method. Next, it uses an emotion engine as an analysis method, utilizing a speech recognition API or natural language processing library (e.g., Google Cloud Natural Language API) to analyze the data and extract the participants' emotions. Based on these analysis results, it uses an algorithm as a selection method to select the most appropriate supplier.

[0813] Furthermore, the server uses processing mechanisms to automatically make reservations with selected suppliers. Information collection and management from suppliers are handled by the management function. If reservation details or changes occur, the information is transmitted to the supplier via the update mechanism, and the changes are reflected. Participants and users are sent information as needed through the notification function.

[0814] For example, if a user enters "I'm a little nervous because this is my first time organizing an event," the server uses an emotion engine to detect this anxiety, selects a supplier with a history of high customer satisfaction, and provides special support features. Similarly, when sending out membership fee collection notifications, the server detects changes in emotion and provides the most appropriate notification content.

[0815] An example of a prompt to input into the generating AI model is, "If a user is feeling a little anxious about organizing an event for the first time, what kind of support can be offered?"

[0816] In this way, the system takes participants' emotions into consideration in real time, enabling more personalized automation of event planning tasks.

[0817] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0818] Step 1:

[0819] Users use a terminal to enter participant attributes and details of the banquet. The entered data includes name, contact information, participation intention, date of the banquet, and location. This information is collected in the terminal's input fields and formatted into a data format before transmission.

[0820] Step 2:

[0821] The terminal sends formatted participant information to the server. This transmission primarily uses the HTTPS protocol to ensure the security of the information. The data is received on the server side and stored in a database for subsequent processing.

[0822] Step 3:

[0823] The server uses information retrieval methods to extract participant attributes from the database. Based on this information, it prepares an input dataset for sentiment analysis. The extracted data is converted into voice input or text data.

[0824] Step 4:

[0825] The server activates the emotion engine and performs sentiment analysis using the dataset. This analysis utilizes speech recognition APIs and natural language processing libraries to calculate sentiment parameters from the input data. The output sentiment parameters include joy, anxiety, and anticipation.

[0826] Step 5:

[0827] The server uses a selection method to select suppliers based on sentiment parameters. It filters the supplier database based on high ratings and specific services to generate a list of optimal suppliers.

[0828] Step 6:

[0829] The server automatically makes reservations with selected suppliers using a processing mechanism. Reservation information is sent via the supplier's API, and the reservation is confirmed. The confirmed reservation information is then notified to the user by the server.

[0830] Step 7:

[0831] Upon user request, a change request is sent from the terminal to the server. The server uses an update mechanism to share the changes with the supplier, who then verifies and updates the changes. The user is then notified of the changes.

[0832] This series of processes allows users to receive personalized service that takes into account the feelings of the participants, and automates the tasks of event organizers.

[0833] (Application Example 2)

[0834] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0835] Traditional event planning processes often fail to efficiently gather participant information and consider their emotions, resulting in a lack of personalization and flexibility in the user experience. Furthermore, the absence of appropriate, emotion-based suggestions can lead to events failing to meet expectations.

[0836] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0837] In this invention, the server includes information receiving means for acquiring participant attribute information, information analysis means for identifying appropriate recipients based on the acquired participant information, and sentiment analysis means for determining the user's emotional state and optimizing the suggested content based on that state. This enables personalized event planning and efficient information sharing.

[0838] "Participant attribute information" refers to information including personal data and preferences of people associated with the event.

[0839] "Information receiving means" refers to devices or methods for obtaining relevant information from participants.

[0840] A "recipient" refers to an external location or service provider selected for an event or service.

[0841] "Information analysis means" refers to a method or apparatus for analyzing acquired participant information and emotional data to select appropriate recipients.

[0842] "Reservation execution means" refers to a device or procedure for automatically establishing a reservation for a specified recipient.

[0843] "Change adjustment means" refers to a method or device for coordinating changes to the scale or date and time of an event with the provider, and for confirming and managing the changes.

[0844] "Information management means" refers to devices or systems for managing recipient information and receiving necessary user input.

[0845] "User's emotional state" refers to the type and intensity of emotions a user exhibits at a particular point in time.

[0846] "Emotional analysis means" refers to a method or device that analyzes a user's voice or text, determines their emotional state, and reflects that in the suggested content.

[0847] To implement this invention, the system is configured as follows: The server acquires participant attribute information received from the user's terminal using information receiving means. Information analysis means on the server analyzes this information and identifies the optimal recipient. At that time, emotion analysis means determines the user's emotional state and optimizes the suggested content based on the analysis results.

[0848] The reservation execution mechanism automatically completes the reservation with the specified provider. The change adjustment mechanism processes changes to the number of participants and date / time from the user, coordinates with the provider, and confirms the changes. After receiving confirmation of the changes from the provider, the user is notified of the details through the information management mechanism.

[0849] Specific technologies include speech recognition software (e.g., Google Speech-to-Text) and sentiment analysis engines (e.g., IBM Watson Emotion Analysis). Data is processed on cloud-based servers and updated in real time.

[0850] For example, if a user enters "I want to plan my daughter's birthday party" on their device, this information is sent to the server, and sentiment analysis determines that the user has a high level of anticipation. Based on this, suggestions are provided, including particularly highly-rated restaurants and services.

[0851] Example of a prompt:

[0852] "Please tell the user about their birthday plans. Take their feelings into consideration and generate appropriate suggestions."

[0853] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0854] Step 1:

[0855] The terminal receives participant attribute information and initial event information entered by the user. This input includes participant names, interests, and the date and time of the event. The information is formatted appropriately and sent to the server.

[0856] Step 2:

[0857] The server acquires participant information transmitted from the terminal using information receiving means. Based on the acquired information, it analyzes this data using information analysis means. As part of the data processing, filtering is performed to identify recipients that match the participant's preferences and attributes.

[0858] Step 3:

[0859] The server uses emotion analysis tools to determine the user's emotional state from their voice or text input. This process uses an emotion analysis engine to analyze voice waveforms or text patterns as input and generate emotions such as joy, anticipation, and dissatisfaction as output.

[0860] Step 4:

[0861] The server determines appropriate recipient candidates based on the analyzed information and emotional state. The information analysis means selects recipients by referring to their evaluations and past user feedback. The list of selected recipients is passed to the reservation execution means.

[0862] Step 5:

[0863] The server automatically makes a reservation to the specified recipient using the reservation execution mechanism. Reservation confirmation data is generated as output and fed back to the user's terminal for verification.

[0864] Step 6:

[0865] If a user wishes to make changes, the server receives a change request from the terminal. The change adjustment mechanism then reconciles with the supplier and confirms the changes. The user is notified of the changes and the confirmation result, and this information is recorded as new information.

[0866] Step 7:

[0867] The server uses information management tools to register and manage recipient information, and updates necessary information as needed. This ensures that users receive the latest recipient information. In addition, feedback based on user sentiment is generated as prompt messages and recorded for future suggestions.

[0868] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0869] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0870] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0871] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0872] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0873] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0874] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0875] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0876] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0877] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0878] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0879] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0880] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0881] 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.

[0882] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0883] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0884] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0885] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0886] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0887] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0888] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0889] The following is further disclosed regarding the embodiments described above.

[0890] (Claim 1)

[0891] An input method for receiving participant information,

[0892] An analytical means for analyzing the received participant information and selecting an appropriate supplier,

[0893] A reservation method that automatically makes reservations with selected suppliers,

[0894] A change management system that contacts selected suppliers and confirms the changes in case of changes in the number of participants or schedule,

[0895] A supplier management system that provides information on suppliers and accepts registrations,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, further comprising a notification means for notifying participants of the collection of membership fees based on the analyzed information.

[0899] (Claim 3)

[0900] The system according to claim 1, wherein the change management means includes means for receiving the supplier's confirmation result regarding the changes and notifying the user of that information.

[0901] "Example 1"

[0902] (Claim 1)

[0903] An input method in which the user enters participant information via a terminal,

[0904] A transmission means that sends participant information collected by the terminal to the server,

[0905] An analytical means that uses an AI model to analyze participant information received by the server and select an appropriate supplier,

[0906] A reservation method that automatically makes reservations with suppliers selected by the server,

[0907] A change management system in which, when a user enters changes to the number of people or schedule from their terminal, the server contacts the supplier to confirm the changes,

[0908] A notification mechanism in which the server receives the change confirmation result from the supplier and notifies the user,

[0909] A supplier management system that provides information about suppliers and accepts registrations from suppliers,

[0910] A system that includes this.

[0911] (Claim 2)

[0912] The system according to claim 1, comprising a notification means for automatically notifying participants of membership fee collection based on the analyzed information.

[0913] (Claim 3)

[0914] The system according to claim 1, wherein the change management means includes means for receiving the supplier's confirmation result regarding the changes and notifying the user of that information.

[0915] "Application Example 1"

[0916] (Claim 1)

[0917] Information acquisition methods for receiving participant information,

[0918] An information analysis tool that analyzes the received participant information to select an appropriate supplier,

[0919] A reservation processing means that automatically makes reservations for selected suppliers,

[0920] A change adjustment mechanism to contact the selected supplier and confirm the changes in case of changes in the number of people or schedule,

[0921] Information management means for providing information about suppliers and accepting registrations,

[0922] A voice input means that acquires participant information using speech recognition,

[0923] A plan proposal means that notifies participants of the proposed plan based on voice instructions,

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, further comprising an information notification means for notifying participants of membership fee collection based on analyzed information.

[0927] (Claim 3)

[0928] The system according to claim 1, wherein the change adjustment means includes means for receiving the supplier's response to the changes and notifying the participants of that information.

[0929] "Example 2 of combining an emotion engine"

[0930] (Claim 1)

[0931] Information acquisition method for obtaining participant attributes,

[0932] An analytical method for analyzing emotions based on acquired participant attributes,

[0933] A selection method for selecting appropriate suppliers based on analyzed emotions,

[0934] A processing method that automatically makes reservations to selected suppliers,

[0935] A means of updating information to the selected supplier in case of changes in the number of people or schedule,

[0936] A management function that provides information related to suppliers and accepts registrations,

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, further comprising a notification function that notifies participants of fee collection based on analyzed sentiment data.

[0940] (Claim 3)

[0941] The system according to claim 1, wherein the update means includes means for obtaining the supplier's confirmation result corresponding to the changes and communicating that information to the user.

[0942] "Application example 2 when combining with an emotional engine"

[0943] (Claim 1)

[0944] Information receiving means for obtaining participant attribute information,

[0945] Information analysis means to identify appropriate recipients based on acquired participant information,

[0946] A reservation execution method that automatically completes the reservation for the specified provider,

[0947] When the size or schedule of a gathering changes, a means of adjusting the changes is provided to coordinate with the provider and confirm the changes.

[0948] An information management system that presents information about the recipient and accepts registration,

[0949] An emotion analysis means that determines the emotional state of the user and optimizes the suggested content based on that state,

[0950] A system that includes this.

[0951] (Claim 2)

[0952] The system according to claim 1, comprising a notification means for providing necessary notifications to participants based on analyzed information and user sentiment.

[0953] (Claim 3)

[0954] The system according to claim 1, wherein the change adjustment means includes a notification means that receives the results of the confirmation of the changes and provides the information to the user. [Explanation of symbols]

[0955] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for receiving participant information, An analytical means for analyzing the received participant information and selecting an appropriate supplier, A reservation method that automatically makes reservations with selected suppliers, A change management system that contacts selected suppliers and confirms the changes in case of changes in the number of participants or schedule, A supplier management system that provides information on suppliers and accepts registrations, A system that includes this.

2. The system according to claim 1, further comprising a notification means for notifying participants of the collection of membership fees based on the analyzed information.

3. The system according to claim 1, wherein the change management means includes means for receiving the supplier's confirmation result regarding the changes and notifying the user of that information.

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