system

Abstract

We provide the system. [Solution] A means of obtaining user input information in voice or text format, A means for analyzing acquired information and generating schedule or task information, A means for determining the priority of schedule or task information and generating reminders, A means of sending a reminder as a push notification to the user's device, A means of providing a chat function to facilitate communication among family members, A means of monitoring users' health information and providing appropriate health management suggestions, A system that includes this.

Description

Technical Field

[0005] ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including: receiving a user utterance; adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot; encoding the prompt; and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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 modern families, the schedule and task management of all family members have become complicated, and there are problems such as easy omission and duplication of schedules. Such a situation has become a factor causing insufficient communication among family members and anxiety about health management, especially for the elderly. Furthermore, since the schedules and tasks of each member are not efficiently integrated and prioritized, the improvement of the quality of life of the whole family is hindered.

Means for Solving the Problems

[0005] This invention provides a system that generates schedule or task information by acquiring and analyzing user input information in voice or text format. This system analyzes the acquired information, sets priorities, generates reminders, and sends push notifications to the user's device. This process allows for centralized management of schedules and tasks for all family members. Furthermore, it provides a chat function to facilitate smooth communication among family members and improves quality of life by monitoring user health information and providing appropriate health management suggestions.

[0006] "User input information" refers to data related to schedules and tasks that users provide via voice or text.

[0007] "Analysis" is the process of processing user input information to extract details of schedules and tasks.

[0008] "Schedule or task information" refers to the details of appointments or tasks compiled based on a specific date, time, location, and content.

[0009] "Priority" refers to the order or ranking determined based on the importance or urgency of schedule or task information.

[0010] A "reminder" is a notification or alert set to remind a user of an appointment or task.

[0011] A "push notification" is an automatically generated notification message that is sent directly to the user's device.

[0012] The "chat function" is a feature designed to support communication between users via text messages.

[0013] "Health information" refers to data and records related to an individual's physical condition, exercise, and health status.

[0014] "Health management suggestions" refer to advice and plans regarding exercise and maintaining health, provided based on the user's health information. [Brief explanation of the drawing]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered 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.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered 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, and the like.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] The system of the present invention has the function of efficiently managing user input information and centrally processing schedules and tasks among family members. The user starts by inputting daily schedules and tasks by voice or text. The terminal receives this user input and, if necessary, converts the voice input into text format using speech recognition technology. The converted data is transmitted from the terminal to the server via the network.

[0037] The server analyzes the received data using natural language processing algorithms to extract schedule or task information. The extracted information is then prioritized based on its importance and urgency, optimizing the schedule. Based on this optimized information, the server sends push notifications as reminders to the user's device at the appropriate time. These notifications are received on the device and serve to prevent users from missing appointments or tasks by providing alerts.

[0038] The system also includes a chat function to facilitate communication among family members. Users can use their devices to exchange messages with family members regarding schedules and tasks. This feature makes it easier to adjust and confirm schedules, and helps to resolve communication breakdowns.

[0039] Furthermore, the server has the functionality to monitor health information and provide personalized health management suggestions for elderly users or those requiring health management. Health status data is collected and analyzed from the user's daily activities. Based on this, the server provides users with specific suggestions for exercise and health maintenance, supporting improvements in their lifestyle.

[0040] As a concrete example, consider a scenario where a user enters a schedule item by voice, such as "Lunch with a friend this Saturday at 2 PM." The device converts the voice to text and sends it to the server. The server analyzes the data, cross-references it with other schedules, and records the lunch appointment for 2 PM on Saturday, along with its priority. Then, on Friday afternoon, it sends a push notification reminder to the user for confirmation. This integration allows users to reliably manage important appointments.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users enter schedules and tasks into the device using voice or text. In the case of voice input, the device uses speech recognition technology to convert the voice data into text format.

[0044] Step 2:

[0045] The terminal sends the converted text data to the server. The transmission is encrypted to ensure data integrity and security.

[0046] Step 3:

[0047] The server analyzes the received data. Using natural language processing algorithms, it extracts important elements from the information, such as date and time, event type, and task type.

[0048] Step 4:

[0049] The server uses the extracted information to compare it with existing schedules and check for any overlaps or inconsistencies. Then, an AI algorithm is used to determine the priority of the schedules.

[0050] Step 5:

[0051] The server stores the determined schedule information in a database. Furthermore, it performs customizations that take into account user preferences and past usage patterns.

[0052] Step 6:

[0053] The server generates a reminder on the user's device at the optimal time and sends it as a push notification. This notification includes schedule details and alerts based on importance.

[0054] Step 7:

[0055] Users can use their devices to check push notifications and, if necessary, change schedules or reset tasks. They can also coordinate and confirm things with family members through the chat function.

[0056] Step 8:

[0057] The server receives and analyzes health information from specific users, such as the elderly. Based on the analysis results, it generates and provides health management suggestions tailored to the user.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] In modern times, coordinating schedules and managing daily health among family members has become increasingly complex. Traditional methods have made it difficult to efficiently manage individual schedules and health information. In particular, there is a lack of adequate support for the elderly and users who require health management. Therefore, there is a need to develop a system that centrally manages individual schedules and health status and facilitates communication among family members.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating schedule or task information, and means for determining the priority of the schedule or task information and generating reminders. This enables multiple users to efficiently manage information, avoid missing important appointments, and facilitate smooth communication within families, as well as monitoring and suggesting health information.

[0063] "User input information" refers to data provided by users to the system, including information about schedules and tasks expressed in voice or text format.

[0064] "Analysis" refers to the process of processing user input information acquired by the system and extracting necessary schedule or work information.

[0065] "Schedule or task information" refers to data that shows the details of the actions or tasks that the user plans to perform or complete.

[0066] A "reminder" is an alert that notifies a user in advance of a specific appointment or task.

[0067] "Push notifications" are a technology that allows a system to instantly send information such as reminders to a user's device.

[0068] "Communication function" refers to a message exchange function provided by the system to facilitate information exchange among family members.

[0069] "Health information" refers to data about a user's lifestyle and physical condition, and is used for health management.

[0070] "Health management suggestions" refer to specific advice provided by the system based on the user's health information, regarding lifestyle improvements and health promotion.

[0071] "Daily activity data" refers to information about the actions a user takes on a daily basis, and is used to assess and suggest improvements to their health status.

[0072] This invention provides a system for efficiently managing user input information and effectively handling family schedules and tasks. In this system, the user, terminal, and server work together. Users can input daily schedules and tasks in voice or text format using terminals such as smartphones or personal computers. In the case of voice input, the terminal utilizes speech recognition technology to convert the voice data into text data. For this purpose, speech recognition software such as Google® Speech-to-Text API can be used.

[0073] The converted information is sent from the terminal to the server via the internet. The server analyzes the received information using advanced natural language processing algorithms. For example, it may use spaCy or the Google Cloud Natural Language API to extract information about schedules and tasks. The server then processes the data to evaluate the importance and urgency of each task and appointment and set priorities.

[0074] Furthermore, based on the optimized schedule information, the server sends reminders as push notifications to the user's device. This reminder function ensures that users are always aware of their appointments. For example, if a user enters a schedule request by voice, such as "Lunch with a friend next Saturday at 2pm," the data is processed appropriately and the schedule is optimized. Then, a reminder is sent one day before the appointment to remind the user.

[0075] Furthermore, this system provides a chat function to assist communication among family members. Users can use this function to share information about schedules and tasks within the family. This facilitates smoother scheduling and helps resolve communication breakdowns.

[0076] Furthermore, the server monitors the user's health information and provides appropriate health management suggestions. By analyzing data collected from daily activities and providing personalized advice on exercise and health maintenance, it improves the user's quality of life. As an example of a prompt message, entering a question such as "Tell me how you share weekend plans with your family" will display suggestions and ways to utilize the system's integration functions.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] Users access their smartphones or computers and input their schedules and tasks in voice or text format. For example, they might use a microphone to voice-input something like, "Lunch with a friend next Saturday at 2pm." This input becomes the starting data for the system.

[0080] Step 2:

[0081] The device receives the user's voice input and converts the speech to text using speech recognition software. Specifically, it uses a speech recognition API to output the voice signal as character data. This character data is then passed on to the next processing step.

[0082] Step 3:

[0083] The terminal sends the converted text data to the server over the network. The transmitted data is then passed to the server as schedule or task information. This data transfer enables information exchange between systems.

[0084] Step 4:

[0085] The server analyzes the received text data using natural language processing algorithms. Specifically, it analyzes the text using an NLP library to extract the date, time, and content of the schedule. This process generates schedule or task information.

[0086] Step 5:

[0087] Based on the schedule information obtained through analysis, the server evaluates the importance and urgency of each appointment and sets priorities. This priority data is used to optimize the schedule. This process results in a rational arrangement of appointments.

[0088] Step 6:

[0089] The server sends reminders as push notifications to the user's device based on optimized scheduling information. These reminders include alerts for important appointments. This notification prompts the user to review their schedule and is provided as output.

[0090] Step 7:

[0091] Users share schedule information with family members using the device's chat function. Specifically, they exchange information by sending it as text messages. This function serves as an output that simplifies information sharing among family members.

[0092] Step 8:

[0093] The server collects data on the user's daily activities and monitors their health. It incorporates data such as daily steps and sleep quality to help provide health management suggestions. This process generates personalized health advice.

[0094] (Application Example 1)

[0095] 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."

[0096] Traditionally, shift management and task sharing among staff in physical stores have often relied on manual adjustments and individual communication methods, resulting in inefficient operations. Furthermore, a lack of real-time communication among staff hinders operational efficiency and planned customer service. This invention aims to solve these problems and improve operational efficiency in physical stores.

[0097] 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.

[0098] In this invention, the server includes means for acquiring information in voice or text format, means for analyzing the acquired information and generating schedule and task information, and means for managing employee schedules using voice input and enabling rapid communication within the group. This enables efficient management of staff schedules and tasks in physical stores, and facilitates rapid information sharing and communication among staff.

[0099] "User input information" refers to task and schedule information provided by the user in voice or text format.

[0100] "Analysis" is the process of generating schedules and tasks based on the acquired information.

[0101] "Schedule or task information" refers to information about appointments and work items generated through analysis.

[0102] "Priority" is an indicator used to evaluate the importance and urgency of schedule or task information and to determine the order in which it should be presented.

[0103] A "reminder" is a notification that helps users remember and complete appointments and tasks.

[0104] A "push notification" is a notification that is automatically sent to a user's device.

[0105] An "information processing device" is a device that converts voice input into text data and performs other calculations and communications.

[0106] "Communication functions" refer to features that facilitate message exchange and information sharing within a group.

[0107] "Health management suggestions" refer to advice on lifestyle habits and exercise that is provided taking into account the user's health condition.

[0108] "Employee schedule management" refers to a function for organizing and coordinating the shifts and tasks of store staff.

[0109] "Rapid communication" refers to a state where necessary information can be shared and exchanged among staff members immediately.

[0110] The system for realizing this application consists of an information processing device and a server. The terminal, acting as the information processing device, first acquires input information from the user in the form of voice or text. When voice input is used, the system converts the voice into text data using the speech recognition software "Google Cloud Speech-to-Text".

[0111] The device then sends the acquired text data to the server via the network. The server analyzes the text data using the natural language processing library "NLTK" and extracts information about schedules and tasks. Based on this, task priorities are determined and reminders are generated. This reminder information is sent to the user's information processing device as a push notification via "Firebase Cloud Messaging".

[0112] Furthermore, the server uses "Firebase Realtime Database" to provide communication capabilities that support smooth communication within the group. This communication capability enables real-time information sharing regarding schedules and tasks among store staff. Through this, the server plays a role in achieving efficient business operations and preventing omissions and errors in tasks.

[0113] For example, if a store staff member uses voice input to say "Prepare for the weekend on Friday night," the terminal converts it to text and sends it to the server. Based on this information, the server ensures that all staff members are notified by push notifications that weekend preparations will be carried out.

[0114] An example of an input prompt for a generative AI model is: "Please provide ideas for an application that will help store staff efficiently manage shifts and tasks. Also, please describe in detail how to use a voice input system and push notification functionality." This prompt is expected to prompt the generative AI model to provide design ideas for the relevant application and hints for system improvements.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The user's voice or text input is acquired by the information processing device. In the case of voice input, the device uses "Google Cloud Speech-to-Text" to convert the voice data into text data and generate that text data. Based on the input, the voice data is converted into characters and made into a format that can be processed internally by the device.

[0118] Step 2:

[0119] The terminal sends the converted text data to the server via the network. The user input is sent to the server as text data, enabling analysis in the next stage.

[0120] Step 3:

[0121] The server analyzes the received text data using the natural language processing library "NLTK" to extract schedule and task information. This process extracts specific tasks and appointments, providing the system with the information to make subsequent decisions.

[0122] Step 4:

[0123] The server determines the priority of schedule or task information based on the analysis. In this prioritization process, different pieces of information are assigned different priorities based on urgency and importance.

[0124] Step 5:

[0125] The server generates reminders based on prioritized information and sends them to information processing devices as push notifications using Firebase Cloud Messaging. By delivering reminders to user devices, users will no longer miss tasks or schedules.

[0126] Step 6:

[0127] The server uses "Firebase Realtime Database" to activate a communication function that facilitates real-time communication between staff members. This function allows users to exchange messages with other staff members and share task-related information in real time.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention combines an emotion engine with an integrated family management system. The system is designed to recognize emotions from the user's everyday voice and text input and dynamically adjust schedule management and task suggestions accordingly.

[0130] Users input schedules and tasks via their device in voice or text format. The device analyzes the emotion of the voice input, converts it into text data, and sends it to the server. The server receives the input information and uses natural language processing and an emotion engine to determine the user's emotional state. Using this information, the server optimizes the priority of schedules or tasks and adjusts suggestions and reminders according to the user's current emotions.

[0131] This system, in particular, has the ability to reflect the results of the emotion engine in the generation of reminders and notifications, and to change the tone and content of messages to the user according to their psychological state at the time. For example, if the system detects that the user is stressed, it can send suggestions to alleviate tasks or messages of encouragement.

[0132] Furthermore, this emotion engine is integrated into family communication features, allowing for the adjustment of message content based on each member's emotional state during chat and messaging service interactions. This feature reduces misunderstandings and friction within families and promotes smoother communication.

[0133] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server's emotion engine will detect this emotion. As a result, the server can suggest relaxation techniques before the meeting and create a schedule to add enjoyable activities afterward. This entire process aims to improve the user's quality of life and enhance the overall well-being of the family.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] Users input schedules and tasks into the device via voice or text. In the case of voice input, the device uses speech recognition technology and an emotion engine to analyze the user's emotions from the voice and convert it into text data.

[0137] Step 2:

[0138] The device sends the converted text data and sentiment information to the server. The data is encrypted before transmission and sent securely over the network.

[0139] Step 3:

[0140] The server analyzes the received text data and sentiment information to extract schedule and task details. Natural language processing is then used to more accurately understand this data.

[0141] Step 4:

[0142] The server uses emotional information via an emotion engine to adjust the priority of extracted schedules and tasks. If the user is feeling stressed, it may lower the priority of tasks or offer encouraging suggestions.

[0143] Step 5:

[0144] The server generates reminders based on coordinated schedule information. It customizes the content and tone of the reminders based on emotional information, taking into account the user's psychological state.

[0145] Step 6:

[0146] The server sends reminders and notifications as push notifications to the user's device at the appropriate time. The content of the notifications is tailored to the user's current mood.

[0147] Step 7:

[0148] Users can check push notifications on their devices and modify schedules and tasks as needed. They can also use the chat function to communicate with family members and share necessary information.

[0149] Step 8:

[0150] In the family chat function, the server adjusts the content and tone of messages based on each member's emotional information to facilitate smoother communication.

[0151] (Example 2)

[0152] 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".

[0153] In managing family and personal schedules, traditional systems struggle to make dynamic adjustments that take user emotions into account. Furthermore, in family communication, the lack of emotionally-based adjustments leads to misunderstandings and friction.

[0154] 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.

[0155] In this invention, the server includes means for determining the user's emotional state, means for generating and optimizing schedule or task information based on the determined emotional state, and means for facilitating communication among family members and adjusting messages based on emotions. This makes it possible to adjust schedules and notifications according to the user's emotions, thereby improving the quality of communication among family members.

[0156] "User input information" refers to information provided by the user to the system in audio or text format.

[0157] "Emotional state" refers to the state of a user's psychological feelings and emotions, as analyzed from their speech and text.

[0158] "Schedule information" refers to information that shows daily plans and activities in advance.

[0159] "Task information" refers to information used to instruct or submit specific tasks or actions that a user should perform.

[0160] A "reminder" is a notification that prompts users to remember and complete their appointments and tasks.

[0161] "Push notifications" are real-time information notifications that are automatically sent to the user's device.

[0162] A "chat function" is a feature designed to facilitate two-way communication between individuals or groups using text.

[0163] "Emotion-based message adjustment" is a process that dynamically adjusts the content and tone of messages sent, taking into account the user's emotional state.

[0164] "Past activity history" refers to data recorded about a user's past activities and actions.

[0165] This invention is a system designed to support users' daily lives and aims to dynamically optimize schedule and task management based on the user's emotional state. The system performs emotional analysis based on information entered by the user in voice or text format and reflects the results in various suggestions.

[0166] The device receives voice input and converts it into text data using speech recognition software. For example, a speech recognition service can be used for speech recognition. Next, the text data is passed to an emotion analysis engine to determine the user's emotional state. Text analysis technology is used for emotion analysis.

[0167] The server receives emotion data and text data sent from the terminal. This data is analyzed using a generative AI model to optimize schedules and tasks according to the user's emotions. Natural language processing technology is used as the generative AI model.

[0168] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server will use emotion analysis to determine that the user is feeling "depressed." Based on this, the server can suggest ways to relax before the meeting or create a schedule that includes something enjoyable afterward. This entire process can improve the user's quality of life.

[0169] As an example of a prompt, you can give specific instructions to the AI, such as, "If the user is feeling anxious about the meeting, generate suggestions for ways to relax or positive messages." This prompt is passed to the AI ​​model, which then generates appropriate feedback.

[0170] Thus, the present invention aims to achieve schedule management that takes into account the user's emotions and to facilitate smooth communication among family members.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] Users input information about their daily schedules and tasks into the device in either voice or text format. The input information is converted from speech to text using speech recognition software. Specifically, if the user inputs "I'm feeling a bit depressed about next week's meeting...", the device will generate the text data "I'm feeling a bit depressed about next week's meeting...".

[0174] Step 2:

[0175] The device passes text data to an emotion analysis engine to determine the user's emotional state. The input is the text data generated in step 1. The emotion analysis engine analyzes keywords and context within the text and outputs an emotion such as "melancholy." This analysis makes it possible to identify the type and intensity of the emotion.

[0176] Step 3:

[0177] The terminal sends emotion data and text data to the server. In this step, the emotional information generated by the terminal is packaged in digital format and sent to the server over the network. The server then supplies the received data to the next analysis phase.

[0178] Step 4:

[0179] The server inputs received emotion data and text data into a generating AI model. This model uses natural language processing technology to analyze the user's statements in detail and generate appropriate feedback. Specifically, the server optimizes schedules and adjusts tasks according to emotions, and generates suggestions as output.

[0180] Step 5:

[0181] The server sends the generated feedback to the user's terminal and notifies the user. This feedback includes schedule adjustments and encouraging messages that take the user's feelings into consideration. For example, it might output a suggestion such as, "Why not try some ways to relax before the meeting?"

[0182] Step 6:

[0183] Users act based on feedback received from their devices. In this step, users review the suggestions provided and incorporate them into their actual schedules. This not only improves the quality of daily life but also enables more flexible responses that are tailored to their emotions.

[0184] (Application Example 2)

[0185] 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".

[0186] Traditional integrated family management systems lacked the dynamic ability to respond to users' emotional states, making it difficult to provide individualized services and suggestions based on their psychological state. Furthermore, in physical stores, it was impossible to offer product suggestions and services that aligned with customers' emotions, limiting the improvement of customer satisfaction. There is a need to solve these problems and realize a richer user experience.

[0187] 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.

[0188] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating work schedules or activity information, and means for analyzing customer emotional information and making specific product suggestions based on their psychological state. This enables appropriate schedule adjustments and task suggestions according to the user's emotional state, and allows for personalized product suggestions to customers even in physical stores.

[0189] 1. "User input information" refers to data provided by the user via voice or text, which serves as the basic information for the system to analyze and process.

[0190] 2. "Work schedule or activity information" refers to schedules and task plans generated based on user needs, and is information intended to improve the efficiency of daily life and work.

[0191] 3. A "notification" is information that the system sends to the user, and it functions as a reminder for scheduled tasks or events.

[0192] 4. A "push notification" is an alert-style message that is forcibly sent to a user's device, and is a method to immediately attract the user's attention.

[0193] 5. "Communication functions" refer to system features designed to support communication among family members and group members, facilitating smooth information sharing and communication.

[0194] 6. "Health management suggestions" refer to advice and guidance provided by the system to improve the user's health status, and the suggestions are aimed at maintaining and promoting health.

[0195] 7. "Emotional information" refers to data about the user's psychological state detected from their voice and facial expressions, and is information that quantitatively or qualitatively evaluates the user's emotions.

[0196] 8. "Product recommendations based on psychological state" refers to a system function that recommends products and services that are suitable for the user's current mental state, based on analyzed emotional information.

[0197] To implement this invention, a system is required in which a user, a server, and a terminal work in cooperation. The user provides input information to the terminal via voice or text. The terminal converts this information into a format that can be analyzed for sentiment and sends it to the server.

[0198] The server analyzes the user's emotional information using speech recognition systems and text analysis software. Emotion analysis engines such as IBM Watson® and Microsoft® Azure® are used for processing. Based on the emotional information obtained from the user's input, the psychological state is identified, and specific product suggestions are generated using an AI model.

[0199] As a concrete example, if a robot in a store reads a customer's voice and facial expressions and detects that the customer is "looking for a new experience," it can suggest information about new products on a promotion or demonstration events. The server then inputs a prompt into the AI ​​model asking, "What emotions is this customer currently feeling? What approach would be most effective based on that?" and determines the optimal suggestion.

[0200] This system allows users to receive more personalized schedules and product suggestions that are tailored to their emotions, and is expected to improve the customer experience in physical stores.

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] The user inputs information into the device via voice or text. The device receives this input and, in the case of voice input, converts it to text using a speech recognition system. In this process, voice data is converted into text data.

[0204] Step 2:

[0205] The terminal sends text data to the server. The server receives this text data and inputs it into the sentiment analysis engine. Here, the input is text data, and the output is an analysis result indicating the user's emotional state.

[0206] Step 3:

[0207] Based on the analysis results, the server uses a generative AI model to generate product suggestions tailored to the user's psychological state. In this process, emotional data is received as input, appropriate prompts are used to instruct the AI ​​model, and the optimal product suggestions are output.

[0208] Step 4:

[0209] The generated product proposals are sent from the server to the terminal, which then displays them to the user. In this step, product proposal data is entered and displayed in a format that the user can visually verify.

[0210] Step 5:

[0211] If the user accepts the suggestion, the device sends feedback to the server again and saves it as history. This input is the result of the user's selection, and the data is updated based on the feedback received to improve the accuracy of future suggestions.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] 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.

[0218] 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).

[0219] 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.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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".

[0228] The system of the present invention has the function of efficiently managing user input information and centrally processing schedules and tasks among family members. The user starts by inputting daily schedules and tasks by voice or text. The terminal receives this user input and, if necessary, converts the voice input into text format using speech recognition technology. The converted data is transmitted from the terminal to the server via the network.

[0229] The server analyzes the received data using natural language processing algorithms to extract schedule or task information. The extracted information is then prioritized based on its importance and urgency, optimizing the schedule. Based on this optimized information, the server sends push notifications as reminders to the user's device at the appropriate time. These notifications are received on the device and serve to prevent users from missing appointments or tasks by providing alerts.

[0230] The system also includes a chat function to facilitate communication among family members. Users can use their devices to exchange messages with family members regarding schedules and tasks. This feature makes it easier to adjust and confirm schedules, and helps to resolve communication breakdowns.

[0231] Furthermore, the server has the functionality to monitor health information and provide personalized health management suggestions for elderly users or those requiring health management. Health status data is collected and analyzed from the user's daily activities. Based on this, the server provides users with specific suggestions for exercise and health maintenance, supporting improvements in their lifestyle.

[0232] As a concrete example, consider a scenario where a user enters a schedule item by voice, such as "Lunch with a friend this Saturday at 2 PM." The device converts the voice to text and sends it to the server. The server analyzes the data, cross-references it with other schedules, and records the lunch appointment for 2 PM on Saturday, along with its priority. Then, on Friday afternoon, it sends a push notification reminder to the user for confirmation. This integration allows users to reliably manage important appointments.

[0233] The following describes the processing flow.

[0234] Step 1:

[0235] Users enter schedules and tasks into the device using voice or text. In the case of voice input, the device uses speech recognition technology to convert the voice data into text format.

[0236] Step 2:

[0237] The terminal sends the converted text data to the server. The transmission is encrypted to ensure data integrity and security.

[0238] Step 3:

[0239] The server analyzes the received data. Using natural language processing algorithms, it extracts important elements from the information, such as date and time, event type, and task type.

[0240] Step 4:

[0241] The server uses the extracted information to compare it with existing schedules and check for any overlaps or inconsistencies. Then, an AI algorithm is used to determine the priority of the schedules.

[0242] Step 5:

[0243] The server stores the determined schedule information in a database. Furthermore, it performs customizations that take into account user preferences and past usage patterns.

[0244] Step 6:

[0245] The server generates a reminder on the user's device at the optimal time and sends it as a push notification. This notification includes schedule details and alerts based on importance.

[0246] Step 7:

[0247] Users can use their devices to check push notifications and, if necessary, change schedules or reset tasks. They can also coordinate and confirm things with family members through the chat function.

[0248] Step 8:

[0249] The server receives and analyzes health information from specific users, such as the elderly. Based on the analysis results, it generates and provides health management suggestions tailored to the user.

[0250] (Example 1)

[0251] 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."

[0252] In modern times, coordinating schedules and managing daily health among family members has become increasingly complex. Traditional methods have made it difficult to efficiently manage individual schedules and health information. In particular, there is a lack of adequate support for the elderly and users who require health management. Therefore, there is a need to develop a system that centrally manages individual schedules and health status and facilitates communication among family members.

[0253] 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.

[0254] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating schedule or task information, and means for determining the priority of the schedule or task information and generating reminders. This enables multiple users to efficiently manage information, avoid missing important appointments, and facilitate smooth communication within families, as well as monitoring and suggesting health information.

[0255] "User input information" refers to data provided by users to the system, including information about schedules and tasks expressed in voice or text format.

[0256] "Analysis" refers to the process of processing user input information acquired by the system and extracting necessary schedule or work information.

[0257] "Schedule or task information" refers to data that shows the details of the actions or tasks that the user plans to perform or complete.

[0258] A "reminder" is an alert that notifies a user in advance of a specific appointment or task.

[0259] "Push notifications" are a technology that allows a system to instantly send information such as reminders to a user's device.

[0260] "Communication function" refers to a message exchange function provided by the system to facilitate information exchange among family members.

[0261] "Health information" refers to data about a user's lifestyle and physical condition, and is used for health management.

[0262] "Health management suggestions" refer to specific advice provided by the system based on the user's health information, regarding lifestyle improvements and health promotion.

[0263] "Daily activity data" refers to information about the actions a user takes on a daily basis, and is used to assess and suggest improvements to their health status.

[0264] This invention provides a system for efficiently managing user input information and effectively handling family schedules and tasks. In this system, the user, terminal, and server work together. Users can input daily schedules and tasks in voice or text format using terminals such as smartphones or personal computers. For voice input, the terminal utilizes speech recognition technology to convert voice data into text data. For this purpose, speech recognition software such as the Google Speech-to-Text API can be used.

[0265] The converted information is sent from the terminal to the server via the internet. The server analyzes the received information using advanced natural language processing algorithms. For example, it may use spaCy or the Google Cloud Natural Language API to extract information about schedules and tasks. The server then processes the data to evaluate the importance and urgency of each task and appointment and set priorities.

[0266] Furthermore, based on the optimized schedule information, the server sends reminders as push notifications to the user's device. This reminder function ensures that users are always aware of their appointments. For example, if a user enters a schedule request by voice, such as "Lunch with a friend next Saturday at 2pm," the data is processed appropriately and the schedule is optimized. Then, a reminder is sent one day before the appointment to remind the user.

[0267] Furthermore, this system provides a chat function to assist communication among family members. Users can use this function to share information about schedules and tasks within the family. This facilitates smoother scheduling and helps resolve communication breakdowns.

[0268] Furthermore, the server monitors the user's health information and provides appropriate health management suggestions. By analyzing data collected from daily activities and providing personalized advice on exercise and health maintenance, it improves the user's quality of life. As an example of a prompt message, entering a question such as "Tell me how you share weekend plans with your family" will display suggestions and ways to utilize the system's integration functions.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] Users access their smartphones or computers and input their schedules and tasks in voice or text format. For example, they might use a microphone to voice-input something like, "Lunch with a friend next Saturday at 2pm." This input becomes the starting data for the system.

[0272] Step 2:

[0273] The device receives the user's voice input and converts the speech to text using speech recognition software. Specifically, it uses a speech recognition API to output the voice signal as character data. This character data is then passed on to the next processing step.

[0274] Step 3:

[0275] The terminal sends the converted text data to the server over the network. The transmitted data is then passed to the server as schedule or task information. This data transfer enables information exchange between systems.

[0276] Step 4:

[0277] The server analyzes the received text data using natural language processing algorithms. Specifically, the text is analyzed by an NLP library to extract the date, time, and content of the schedule. Through this process, schedule or task information is generated.

[0278] Step 5:

[0279] Based on the schedule information obtained through analysis, the server evaluates the importance and urgency of each schedule and sets priorities. The priority data is used for schedule optimization. Through this process, a reasonable arrangement of schedules is obtained.

[0280] Step 6:

[0281] Based on the optimized schedule information, the server sends a reminder as a push notification to the user's terminal. The reminder includes an alert notifying important schedules. This notification prompts the user to confirm their schedules and is provided as an output.

[0282] Step 7:

[0283] The user uses the chat function on the terminal to share schedule information with family members. Specifically, information exchange is realized by sending text messages. This function serves as an output that simplifies information sharing among family members.

[0284] Step 8:

[0285] The server collects the user's daily activity data and monitors their health status. It takes in data such as daily step counts and sleep quality and uses it to provide suggestions for health management. Through this process, individualized health advice is output.

[0286] (Application Example 1)

[0287] 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."

[0288] Traditionally, shift management and task sharing among staff in physical stores have often relied on manual adjustments and individual communication methods, resulting in inefficient operations. Furthermore, a lack of real-time communication among staff hinders operational efficiency and planned customer service. This invention aims to solve these problems and improve operational efficiency in physical stores.

[0289] 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.

[0290] In this invention, the server includes means for acquiring information in voice or text format, means for analyzing the acquired information and generating schedule and task information, and means for managing employee schedules using voice input and enabling rapid communication within the group. This enables efficient management of staff schedules and tasks in physical stores, and facilitates rapid information sharing and communication among staff.

[0291] "User input information" refers to task and schedule information provided by the user in voice or text format.

[0292] "Analysis" is the process of generating schedules and tasks based on the acquired information.

[0293] "Schedule or task information" refers to information about appointments and work items generated through analysis.

[0294] "Priority" is an indicator used to evaluate the importance and urgency of schedule or task information and to determine the order in which it should be presented.

[0295] A "reminder" is a notification that helps users remember and complete appointments and tasks.

[0296] A "push notification" is a notification that is automatically sent to a user's device.

[0297] An "information processing device" is a device that converts voice input into text data and performs other calculations and communications.

[0298] "Communication functions" refer to features that facilitate message exchange and information sharing within a group.

[0299] "Health management suggestions" refer to advice on lifestyle habits and exercise that is provided taking into account the user's health condition.

[0300] "Employee schedule management" refers to a function for organizing and coordinating the shifts and tasks of store staff.

[0301] "Rapid communication" refers to a state where necessary information can be shared and exchanged among staff members immediately.

[0302] The system for realizing this application consists of an information processing device and a server. The terminal, acting as the information processing device, first acquires input information from the user in the form of voice or text. When voice input is used, the system converts the voice into text data using the speech recognition software "Google Cloud Speech-to-Text".

[0303] The device then sends the acquired text data to the server via the network. The server analyzes the text data using the natural language processing library "NLTK" and extracts information about schedules and tasks. Based on this, task priorities are determined and reminders are generated. This reminder information is sent to the user's information processing device as a push notification via "Firebase Cloud Messaging".

[0304] Furthermore, the server uses "Firebase Realtime Database" to provide a communication function to support smooth communication within the group. This communication function enables real-time information sharing about schedules and tasks among store staff. Through this, the server plays a role in realizing efficient business operations and preventing omissions in business processes.

[0305] As a specific example, when a store staff enters "Weekend preparation on Friday night" by voice input, the terminal converts it into text and sends it to the server. Based on this information, the server ensures transmission by sending a push notification to all staff about the planned weekend preparation. [[ID=​​​​​​​​​​​​​​​​​​​​​​​

[0312] Step 3:

[0313] The server analyzes the received text data using the natural language processing library "NLTK" to extract schedule and task information. This process extracts specific tasks and appointments, providing the system with the information to make subsequent decisions.

[0314] Step 4:

[0315] The server determines the priority of schedule or task information based on the analysis. In this prioritization process, different pieces of information are assigned different priorities based on urgency and importance.

[0316] Step 5:

[0317] The server generates reminders based on prioritized information and sends them to information processing devices as push notifications using Firebase Cloud Messaging. By delivering reminders to user devices, users will no longer miss tasks or schedules.

[0318] Step 6:

[0319] The server uses "Firebase Realtime Database" to activate a communication function that facilitates real-time communication between staff members. This function allows users to exchange messages with other staff members and share task-related information in real time.

[0320] 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.

[0321] This invention combines an emotion engine with an integrated family management system. The system is designed to recognize emotions from the user's everyday voice and text input and dynamically adjust schedule management and task suggestions accordingly.

[0322] Users input schedules and tasks via their device in voice or text format. The device analyzes the emotion of the voice input, converts it into text data, and sends it to the server. The server receives the input information and uses natural language processing and an emotion engine to determine the user's emotional state. Using this information, the server optimizes the priority of schedules or tasks and adjusts suggestions and reminders according to the user's current emotions.

[0323] This system, in particular, has the ability to reflect the results of the emotion engine in the generation of reminders and notifications, and to change the tone and content of messages to the user according to their psychological state at the time. For example, if the system detects that the user is stressed, it can send suggestions to alleviate tasks or messages of encouragement.

[0324] Furthermore, this emotion engine is integrated into family communication features, allowing for the adjustment of message content based on each member's emotional state during chat and messaging service interactions. This feature reduces misunderstandings and friction within families and promotes smoother communication.

[0325] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server's emotion engine will detect this emotion. As a result, the server can suggest relaxation techniques before the meeting and create a schedule to add enjoyable activities afterward. This entire process aims to improve the user's quality of life and enhance the overall well-being of the family.

[0326] The following describes the processing flow.

[0327] Step 1:

[0328] Users input schedules and tasks into the device via voice or text. In the case of voice input, the device uses speech recognition technology and an emotion engine to analyze the user's emotions from the voice and convert it into text data.

[0329] Step 2:

[0330] The device sends the converted text data and sentiment information to the server. The data is encrypted before transmission and sent securely over the network.

[0331] Step 3:

[0332] The server analyzes the received text data and sentiment information to extract schedule and task details. Natural language processing is then used to more accurately understand this data.

[0333] Step 4:

[0334] The server uses emotional information via an emotion engine to adjust the priority of extracted schedules and tasks. If the user is feeling stressed, it may lower the priority of tasks or offer encouraging suggestions.

[0335] Step 5:

[0336] The server generates reminders based on coordinated schedule information. It customizes the content and tone of the reminders based on emotional information, taking into account the user's psychological state.

[0337] Step 6:

[0338] The server sends reminders and notifications as push notifications to the user's device at the appropriate time. The content of the notifications is tailored to the user's current mood.

[0339] Step 7:

[0340] Users check push notifications on their devices and modify schedules and tasks as needed. They also use the chat function to communicate with family members and share necessary information.

[0341] Step 8:

[0342] In the family chat function, the server adjusts the content and tone of messages based on each member's emotional information to facilitate smoother communication.

[0343] (Example 2)

[0344] 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".

[0345] In managing family and personal schedules, traditional systems struggle to make dynamic adjustments that take user emotions into account. Furthermore, in family communication, the lack of emotionally-based adjustments leads to misunderstandings and friction.

[0346] 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.

[0347] In this invention, the server includes means for determining the user's emotional state, means for generating and optimizing schedule or task information based on the determined emotional state, and means for facilitating communication among family members and adjusting messages based on emotions. This makes it possible to adjust schedules and notifications according to the user's emotions, thereby improving the quality of communication among family members.

[0348] "User input information" refers to information provided by the user to the system in audio or text format.

[0349] "Emotional state" refers to the state of a user's psychological feelings and emotions, as analyzed from their speech and text.

[0350] "Schedule information" refers to information that shows daily plans and activities in advance.

[0351] "Task information" refers to information used to instruct or submit specific tasks or actions that a user should perform.

[0352] A "reminder" is a notification that prompts users to remember and complete their appointments and tasks.

[0353] "Push notifications" are real-time information notifications that are automatically sent to the user's device.

[0354] A "chat function" is a feature designed to facilitate two-way communication between individuals or groups using text.

[0355] "Emotion-based message adjustment" is a process that dynamically adjusts the content and tone of messages sent, taking into account the user's emotional state.

[0356] "Past activity history" refers to data recorded about a user's past activities and actions.

[0357] This invention is a system designed to support users' daily lives and aims to dynamically optimize schedule and task management based on the user's emotional state. The system performs emotional analysis based on information entered by the user in voice or text format and reflects the results in various suggestions.

[0358] The device receives voice input and converts it into text data using speech recognition software. For example, a speech recognition service can be used for speech recognition. Next, the text data is passed to an emotion analysis engine to determine the user's emotional state. Text analysis technology is used for emotion analysis.

[0359] The server receives emotion data and text data sent from the terminal. This data is analyzed using a generative AI model to optimize schedules and tasks according to the user's emotions. Natural language processing technology is used as the generative AI model.

[0360] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server will use emotion analysis to determine that the user is feeling "depressed." Based on this, the server can suggest ways to relax before the meeting or create a schedule that includes something enjoyable afterward. This entire process can improve the user's quality of life.

[0361] As an example of a prompt, you can give specific instructions to the AI, such as, "If the user is feeling anxious about the meeting, generate suggestions for ways to relax or positive messages." This prompt is passed to the AI ​​model, which then generates appropriate feedback.

[0362] Thus, the present invention aims to achieve schedule management that takes into account the user's emotions and to facilitate smooth communication among family members.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] Users input information about their daily schedules and tasks into the device in either voice or text format. The input information is converted from speech to text using speech recognition software. Specifically, if the user inputs "I'm feeling a bit depressed about next week's meeting...", the device will generate the text data "I'm feeling a bit depressed about next week's meeting...".

[0366] Step 2:

[0367] The device passes text data to an emotion analysis engine to determine the user's emotional state. The input is the text data generated in step 1. The emotion analysis engine analyzes keywords and context within the text and outputs an emotion such as "melancholy." This analysis makes it possible to identify the type and intensity of the emotion.

[0368] Step 3:

[0369] The terminal sends emotion data and text data to the server. In this step, the emotional information generated by the terminal is packaged in digital format and sent to the server over the network. The server then feeds the received data into the next analysis phase.

[0370] Step 4:

[0371] The server inputs received emotion data and text data into a generating AI model. This model uses natural language processing technology to analyze the user's statements in detail and generate appropriate feedback. Specifically, the server optimizes schedules and adjusts tasks according to emotions, and generates suggestions as output.

[0372] Step 5:

[0373] The server sends the generated feedback to the user's terminal and notifies the user. This feedback includes schedule adjustments and encouraging messages that take the user's feelings into consideration. For example, it might output a suggestion such as, "Why not try some ways to relax before the meeting?"

[0374] Step 6:

[0375] Users act based on feedback received from their devices. In this step, users review the suggestions provided and incorporate them into their actual schedules. This not only improves the quality of daily life but also enables more flexible responses that are tailored to their emotions.

[0376] (Application Example 2)

[0377] 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."

[0378] Traditional integrated family management systems lacked the dynamic ability to respond to users' emotional states, making it difficult to provide individualized services and suggestions based on their psychological state. Furthermore, in physical stores, it was impossible to offer product suggestions and services that aligned with customers' emotions, limiting the improvement of customer satisfaction. There is a need to solve these problems and realize a richer user experience.

[0379] 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.

[0380] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating work schedules or activity information, and means for analyzing customer emotional information and making specific product suggestions based on their psychological state. This enables appropriate schedule adjustments and task suggestions according to the user's emotional state, and allows for personalized product suggestions to customers even in physical stores.

[0381] 1. "User input information" refers to data provided by the user via voice or text, which serves as the basic information for the system to analyze and process.

[0382] 2. "Work schedule or activity information" refers to schedules and task plans generated based on user needs, and is information intended to improve the efficiency of daily life and work.

[0383] 3. A "notification" is information that the system sends to the user, and it functions as a reminder for scheduled tasks or events.

[0384] 4. A "push notification" is an alert-style message that is forcibly sent to a user's device, and is a method to immediately attract the user's attention.

[0385] 5. "Communication functions" refer to system features designed to support communication among family members and group members, facilitating smooth information sharing and communication.

[0386] 6. "Health management suggestions" refer to advice and guidance provided by the system to improve the user's health status, and the suggestions are aimed at maintaining and promoting health.

[0387] 7. "Emotional information" refers to data about the user's psychological state detected from their voice and facial expressions, and is information that quantitatively or qualitatively evaluates the user's emotions.

[0388] 8. "Product recommendations based on psychological state" refers to a system function that recommends products and services that are suitable for the user's current mental state, based on analyzed emotional information.

[0389] To implement this invention, a system is required in which a user, a server, and a terminal work in cooperation. The user provides input information to the terminal via voice or text. The terminal converts this information into a format that can be analyzed for sentiment and sends it to the server.

[0390] The server analyzes the user's emotional information using speech recognition systems and text analysis software. Emotion analysis engines such as IBM Watson and Microsoft Azure are used for processing. Based on the emotional information obtained from the user's input, the psychological state is identified, and specific product suggestions are generated using an AI model.

[0391] As a concrete example, if a robot in a store reads a customer's voice and facial expressions and detects that the customer is "looking for a new experience," it can suggest information about new products on a promotion or demonstration events. The server then inputs a prompt into the AI ​​model asking, "What emotions is this customer currently feeling? What approach would be most effective based on that?" and determines the optimal suggestion.

[0392] This system allows users to receive more personalized schedules and product suggestions that are tailored to their emotions, and is expected to improve the customer experience in physical stores.

[0393] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0394] Step 1:

[0395] The user inputs information into the device via voice or text. The device receives this input and, in the case of voice input, converts it to text using a speech recognition system. In this process, voice data is converted into text data.

[0396] Step 2:

[0397] The terminal sends text data to the server. The server receives this text data and inputs it into the sentiment analysis engine. Here, the input is text data, and the output is an analysis result indicating the user's emotional state.

[0398] Step 3:

[0399] Based on the analysis results, the server uses a generative AI model to generate product suggestions tailored to the user's psychological state. In this process, emotional data is received as input, appropriate prompts are used to instruct the AI ​​model, and the optimal product suggestions are output.

[0400] Step 4:

[0401] The generated product proposals are sent from the server to the terminal, which then displays them to the user. In this step, product proposal data is entered and displayed in a format that the user can visually verify.

[0402] Step 5:

[0403] If the user accepts the suggestion, the device sends feedback to the server again and saves it as history. This input is the result of the user's selection, and the data is updated based on the feedback received to improve the accuracy of future suggestions.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] [Third Embodiment]

[0408] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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".

[0420] The system of the present invention has the function of efficiently managing user input information and centrally processing schedules and tasks among family members. The user starts by inputting daily schedules and tasks by voice or text. The terminal receives this user input and, if necessary, converts the voice input into text format using speech recognition technology. The converted data is transmitted from the terminal to the server via the network.

[0421] The server analyzes the received data using natural language processing algorithms to extract schedule or task information. The extracted information is then prioritized based on its importance and urgency, optimizing the schedule. Based on this optimized information, the server sends push notifications as reminders to the user's device at the appropriate time. These notifications are received on the device and serve to prevent users from missing appointments or tasks by providing alerts.

[0422] The system also includes a chat function to facilitate communication among family members. Users can use their devices to exchange messages with family members regarding schedules and tasks. This feature makes it easier to adjust and confirm schedules, and helps to resolve communication breakdowns.

[0423] Furthermore, the server has the functionality to monitor health information and provide personalized health management suggestions for elderly users or those requiring health management. Health status data is collected and analyzed from the user's daily activities. Based on this, the server provides users with specific suggestions for exercise and health maintenance, supporting improvements in their lifestyle.

[0424] As a concrete example, consider a scenario where a user enters a schedule item by voice, such as "Lunch with a friend this Saturday at 2 PM." The device converts the voice to text and sends it to the server. The server analyzes the data, cross-references it with other schedules, and records the lunch appointment for 2 PM on Saturday, along with its priority. Then, on Friday afternoon, it sends a push notification reminder to the user for confirmation. This integration allows users to reliably manage important appointments.

[0425] The following describes the processing flow.

[0426] Step 1:

[0427] Users enter schedules and tasks into the device using voice or text. In the case of voice input, the device uses speech recognition technology to convert the voice data into text format.

[0428] Step 2:

[0429] The terminal sends the converted text data to the server. The transmission is encrypted to ensure data integrity and security.

[0430] Step 3:

[0431] The server analyzes the received data. Using natural language processing algorithms, it extracts important elements from the information, such as date and time, event type, and task type.

[0432] Step 4:

[0433] The server uses the extracted information to compare it with existing schedules and check for any overlaps or inconsistencies. Then, an AI algorithm is used to determine the priority of the schedules.

[0434] Step 5:

[0435] The server stores the determined schedule information in a database. Furthermore, it performs customizations that take into account user preferences and past usage patterns.

[0436] Step 6:

[0437] The server generates a reminder on the user's device at the optimal time and sends it as a push notification. This notification includes schedule details and alerts based on importance.

[0438] Step 7:

[0439] Users can use their devices to check push notifications and, if necessary, change schedules or reset tasks. They can also coordinate and confirm things with family members through the chat function.

[0440] Step 8:

[0441] The server receives and analyzes health information from specific users, such as the elderly. Based on the analysis results, it generates and provides health management suggestions tailored to the user.

[0442] (Example 1)

[0443] 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."

[0444] In modern times, coordinating schedules and managing daily health among family members has become increasingly complex. Traditional methods have made it difficult to efficiently manage individual schedules and health information. In particular, there is a lack of adequate support for the elderly and users who require health management. Therefore, there is a need to develop a system that centrally manages individual schedules and health status and facilitates communication among family members.

[0445] 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.

[0446] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating schedule or task information, and means for determining the priority of the schedule or task information and generating reminders. This enables multiple users to efficiently manage information, avoid missing important appointments, and facilitate smooth communication within families, as well as monitoring and suggesting health information.

[0447] "User input information" refers to data provided by users to the system, including information about schedules and tasks expressed in voice or text format.

[0448] "Analysis" refers to the process of processing user input information acquired by the system and extracting necessary schedule or work information.

[0449] "Schedule or task information" refers to data that shows the details of the actions or tasks that the user plans to perform or complete.

[0450] A "reminder" is an alert that notifies a user in advance of a specific appointment or task.

[0451] "Push notifications" are a technology that allows a system to instantly send information such as reminders to a user's device.

[0452] "Communication function" refers to a message exchange function provided by the system to facilitate information exchange among family members.

[0453] "Health information" refers to data about a user's lifestyle and physical condition, and is used for health management.

[0454] "Health management suggestions" refer to specific advice provided by the system based on the user's health information, regarding lifestyle improvements and health promotion.

[0455] "Daily activity data" refers to information about the actions a user takes on a daily basis, and is used to assess and suggest improvements to their health status.

[0456] This invention provides a system for efficiently managing user input information and effectively handling family schedules and tasks. In this system, the user, terminal, and server work together. Users can input daily schedules and tasks in voice or text format using terminals such as smartphones or personal computers. For voice input, the terminal utilizes speech recognition technology to convert voice data into text data. For this purpose, speech recognition software such as the Google Speech-to-Text API can be used.

[0457] The converted information is sent from the terminal to the server via the internet. The server analyzes the received information using advanced natural language processing algorithms. For example, it may use spaCy or the Google Cloud Natural Language API to extract information about schedules and tasks. The server then processes the data to evaluate the importance and urgency of each task and appointment and set priorities.

[0458] Furthermore, based on the optimized schedule information, the server sends reminders as push notifications to the user's device. This reminder function ensures that users are always aware of their appointments. For example, if a user enters a schedule request by voice, such as "Lunch with a friend next Saturday at 2pm," the data is processed appropriately and the schedule is optimized. Then, a reminder is sent one day before the appointment to remind the user.

[0459] Furthermore, this system provides a chat function to assist communication among family members. Users can use this function to share information about schedules and tasks within the family. This facilitates smoother scheduling and helps resolve communication breakdowns.

[0460] Furthermore, the server monitors the user's health information and provides appropriate health management suggestions. By analyzing data collected from daily activities and providing personalized advice on exercise and health maintenance, it improves the user's quality of life. As an example of a prompt message, entering a question such as "Tell me how you share weekend plans with your family" will display suggestions and ways to utilize the system's integration functions.

[0461] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0462] Step 1:

[0463] Users access their smartphones or computers and input their schedules and tasks in voice or text format. For example, they might use a microphone to voice-input something like, "Lunch with a friend next Saturday at 2pm." This input becomes the starting data for the system.

[0464] Step 2:

[0465] The device receives the user's voice input and converts the speech to text using speech recognition software. Specifically, it uses a speech recognition API to output the voice signal as character data. This character data is then passed on to the next processing step.

[0466] Step 3:

[0467] The terminal sends the converted text data to the server over the network. The transmitted data is then passed to the server as schedule or task information. This data transfer enables information exchange between systems.

[0468] Step 4:

[0469] The server analyzes the received text data using natural language processing algorithms. Specifically, it analyzes the text using an NLP library to extract the date, time, and content of the schedule. This process generates schedule or task information.

[0470] Step 5:

[0471] Based on the schedule information obtained through analysis, the server evaluates the importance and urgency of each appointment and sets priorities. This priority data is used to optimize the schedule. This process results in a rational arrangement of appointments.

[0472] Step 6:

[0473] The server sends reminders as push notifications to the user's device based on optimized scheduling information. These reminders include alerts for important appointments. This notification prompts the user to review their schedule and is provided as output.

[0474] Step 7:

[0475] Users share schedule information with family members using the device's chat function. Specifically, they exchange information by sending it as text messages. This function serves as an output that simplifies information sharing among family members.

[0476] Step 8:

[0477] The server collects data on the user's daily activities and monitors their health. It incorporates data such as daily steps and sleep quality to help provide health management suggestions. This process generates personalized health advice.

[0478] (Application Example 1)

[0479] 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."

[0480] Traditionally, shift management and task sharing among staff in physical stores have often relied on manual adjustments and individual communication methods, resulting in inefficient operations. Furthermore, a lack of real-time communication among staff hinders operational efficiency and planned customer service. This invention aims to solve these problems and improve operational efficiency in physical stores.

[0481] 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.

[0482] In this invention, the server includes means for acquiring information in voice or text format, means for analyzing the acquired information and generating schedule and task information, and means for managing employee schedules using voice input and enabling rapid communication within the group. This enables efficient management of staff schedules and tasks in physical stores, and facilitates rapid information sharing and communication among staff.

[0483] "User input information" refers to task and schedule information provided by the user in voice or text format.

[0484] "Analysis" is the process of generating schedules and tasks based on the acquired information.

[0485] "Schedule or task information" refers to information about appointments and work items generated through analysis.

[0486] "Priority" is an indicator used to evaluate the importance and urgency of schedule or task information and to determine the order in which it should be presented.

[0487] A "reminder" is a notification that helps users remember and complete appointments and tasks.

[0488] A "push notification" is a notification that is automatically sent to a user's device.

[0489] An "information processing device" is a device that converts voice input into text data and performs other calculations and communications.

[0490] "Communication functions" refer to features that facilitate message exchange and information sharing within a group.

[0491] "Health management suggestions" refer to advice on lifestyle habits and exercise that is provided taking into account the user's health condition.

[0492] "Employee schedule management" refers to a function for organizing and coordinating the shifts and tasks of store staff.

[0493] "Rapid communication" refers to a state where necessary information can be shared and exchanged among staff members immediately.

[0494] The system for realizing this application consists of an information processing device and a server. The terminal, acting as the information processing device, first acquires input information from the user in the form of voice or text. When voice input is used, the system converts the voice into text data using the speech recognition software "Google Cloud Speech-to-Text".

[0495] The device then sends the acquired text data to the server via the network. The server analyzes the text data using the natural language processing library "NLTK" and extracts information about schedules and tasks. Based on this, task priorities are determined and reminders are generated. This reminder information is sent to the user's information processing device as a push notification via "Firebase Cloud Messaging".

[0496] Furthermore, the server uses "Firebase Realtime Database" to provide communication capabilities that support smooth communication within the group. This communication capability enables real-time information sharing regarding schedules and tasks among store staff. Through this, the server plays a role in achieving efficient business operations and preventing omissions and errors in tasks.

[0497] For example, if a store staff member uses voice input to say "Prepare for the weekend on Friday night," the terminal converts it to text and sends it to the server. Based on this information, the server ensures that all staff members are notified by push notifications that weekend preparations will be carried out.

[0498] An example of an input prompt for a generative AI model is: "Please provide ideas for an application that will help store staff efficiently manage shifts and tasks. Also, please describe in detail how to use a voice input system and push notification functionality." This prompt is expected to prompt the generative AI model to provide design ideas for the relevant application and hints for system improvements.

[0499] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0500] Step 1:

[0501] The user's voice or text input is acquired by the information processing device. In the case of voice input, the device uses "Google Cloud Speech-to-Text" to convert the voice data into text data and generate that text data. Based on the input, the voice data is converted into characters and made into a format that can be processed internally by the device.

[0502] Step 2:

[0503] The terminal sends the converted text data to the server via the network. The user input is sent to the server as text data, enabling analysis in the next stage.

[0504] Step 3:

[0505] The server analyzes the received text data using the natural language processing library "NLTK" to extract schedule and task information. This process extracts specific tasks and appointments, providing the system with the information to make subsequent decisions.

[0506] Step 4:

[0507] The server determines the priority of schedule or task information based on the analysis. In this prioritization process, different pieces of information are assigned different priorities based on urgency and importance.

[0508] Step 5:

[0509] The server generates reminders based on prioritized information and sends them to information processing devices as push notifications using Firebase Cloud Messaging. By delivering reminders to user devices, users will no longer miss tasks or schedules.

[0510] Step 6:

[0511] The server uses "Firebase Realtime Database" to activate a communication function that facilitates real-time communication between staff members. This function allows users to exchange messages with other staff members and share task-related information in real time.

[0512] 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.

[0513] This invention combines an emotion engine with an integrated family management system. The system is designed to recognize emotions from the user's everyday voice and text input and dynamically adjust schedule management and task suggestions accordingly.

[0514] Users input schedules and tasks via their device in voice or text format. The device analyzes the emotion of the voice input, converts it into text data, and sends it to the server. The server receives the input information and uses natural language processing and an emotion engine to determine the user's emotional state. Using this information, the server optimizes the priority of schedules or tasks and adjusts suggestions and reminders according to the user's current emotions.

[0515] This system, in particular, has the ability to reflect the results of the emotion engine in the generation of reminders and notifications, and to change the tone and content of messages to the user according to their psychological state at the time. For example, if the system detects that the user is stressed, it can send suggestions to alleviate tasks or messages of encouragement.

[0516] Furthermore, this emotion engine is integrated into family communication features, allowing for the adjustment of message content based on each member's emotional state during chat and messaging service interactions. This feature reduces misunderstandings and friction within families and promotes smoother communication.

[0517] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server's emotion engine will detect this emotion. As a result, the server can suggest relaxation techniques before the meeting and create a schedule to add enjoyable activities afterward. This entire process aims to improve the user's quality of life and enhance the overall well-being of the family.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] Users input schedules and tasks into the device via voice or text. In the case of voice input, the device uses speech recognition technology and an emotion engine to analyze the user's emotions from the voice and convert it into text data.

[0521] Step 2:

[0522] The device sends the converted text data and sentiment information to the server. The data is encrypted before transmission and sent securely over the network.

[0523] Step 3:

[0524] The server analyzes the received text data and sentiment information to extract schedule and task details. Natural language processing is then used to more accurately understand this data.

[0525] Step 4:

[0526] The server uses emotional information via an emotion engine to adjust the priority of extracted schedules and tasks. If the user is feeling stressed, it may lower the priority of tasks or offer encouraging suggestions.

[0527] Step 5:

[0528] The server generates reminders based on coordinated schedule information. It customizes the content and tone of the reminders based on emotional information, taking into account the user's psychological state.

[0529] Step 6:

[0530] The server sends reminders and notifications as push notifications to the user's device at the appropriate time. The content of the notifications is tailored to the user's current mood.

[0531] Step 7:

[0532] Users can check push notifications on their devices and modify schedules and tasks as needed. They can also use the chat function to communicate with family members and share necessary information.

[0533] Step 8:

[0534] In the family chat function, the server adjusts the content and tone of messages based on each member's emotional information to facilitate smoother communication.

[0535] (Example 2)

[0536] 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."

[0537] In managing family and personal schedules, traditional systems struggle to make dynamic adjustments that take user emotions into account. Furthermore, in family communication, the lack of emotionally-based adjustments leads to misunderstandings and friction.

[0538] 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.

[0539] In this invention, the server includes means for determining the user's emotional state, means for generating and optimizing schedule or task information based on the determined emotional state, and means for facilitating communication among family members and adjusting messages based on emotions. This makes it possible to adjust schedules and notifications according to the user's emotions, thereby improving the quality of communication among family members.

[0540] "User input information" refers to information provided by the user to the system in audio or text format.

[0541] "Emotional state" refers to the state of a user's psychological feelings and emotions, as analyzed from their speech and text.

[0542] "Schedule information" refers to information that shows daily plans and activities in advance.

[0543] "Task information" refers to information used to instruct or submit specific tasks or actions that a user should perform.

[0544] A "reminder" is a notification that prompts users to remember and complete their appointments and tasks.

[0545] "Push notifications" are real-time information notifications that are automatically sent to the user's device.

[0546] A "chat function" is a feature designed to facilitate two-way communication between individuals or groups using text.

[0547] "Emotion-based message adjustment" is a process that dynamically adjusts the content and tone of messages sent, taking into account the user's emotional state.

[0548] "Past activity history" refers to data recorded about a user's past activities and actions.

[0549] This invention is a system designed to support users' daily lives and aims to dynamically optimize schedule and task management based on the user's emotional state. The system performs emotional analysis based on information entered by the user in voice or text format and reflects the results in various suggestions.

[0550] The device receives voice input and converts it into text data using speech recognition software. For example, a speech recognition service can be used for speech recognition. Next, the text data is passed to an emotion analysis engine to determine the user's emotional state. Text analysis technology is used for emotion analysis.

[0551] The server receives emotion data and text data sent from the terminal. This data is analyzed using a generative AI model to optimize schedules and tasks according to the user's emotions. Natural language processing technology is used as the generative AI model.

[0552] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server will use emotion analysis to determine that the user is feeling "depressed." Based on this, the server can suggest ways to relax before the meeting or create a schedule that includes something enjoyable afterward. This entire process can improve the user's quality of life.

[0553] As an example of a prompt, you can give specific instructions to the AI, such as, "If the user is feeling anxious about the meeting, generate suggestions for ways to relax or positive messages." This prompt is passed to the AI ​​model, which then generates appropriate feedback.

[0554] Thus, the present invention aims to achieve schedule management that takes into account the user's emotions and to facilitate smooth communication among family members.

[0555] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0556] Step 1:

[0557] Users input information about their daily schedules and tasks into the device in either voice or text format. The input information is converted from speech to text using speech recognition software. Specifically, if the user inputs "I'm feeling a bit depressed about next week's meeting...", the device will generate the text data "I'm feeling a bit depressed about next week's meeting...".

[0558] Step 2:

[0559] The device passes text data to an emotion analysis engine to determine the user's emotional state. The input is the text data generated in step 1. The emotion analysis engine analyzes keywords and context within the text and outputs an emotion such as "melancholy." This analysis makes it possible to identify the type and intensity of the emotion.

[0560] Step 3:

[0561] The terminal sends emotion data and text data to the server. In this step, the emotional information generated by the terminal is packaged in digital format and sent to the server over the network. The server then supplies the received data to the next analysis phase.

[0562] Step 4:

[0563] The server inputs received emotion data and text data into a generating AI model. This model uses natural language processing technology to analyze the user's statements in detail and generate appropriate feedback. Specifically, the server optimizes schedules and adjusts tasks according to emotions, and generates suggestions as output.

[0564] Step 5:

[0565] The server sends the generated feedback to the user's terminal and notifies the user. This feedback includes schedule adjustments and encouraging messages that take the user's feelings into consideration. For example, it might output a suggestion such as, "Why not try some ways to relax before the meeting?"

[0566] Step 6:

[0567] Users act based on feedback received from their devices. In this step, users review the suggestions provided and incorporate them into their actual schedules. This not only improves the quality of daily life but also enables more flexible responses that are tailored to their emotions.

[0568] (Application Example 2)

[0569] 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."

[0570] Traditional integrated family management systems lacked the dynamic ability to respond to users' emotional states, making it difficult to provide individualized services and suggestions based on their psychological state. Furthermore, in physical stores, it was impossible to offer product suggestions and services that aligned with customers' emotions, limiting the improvement of customer satisfaction. There is a need to solve these problems and realize a richer user experience.

[0571] 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.

[0572] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating work schedules or activity information, and means for analyzing customer emotional information and making specific product suggestions based on their psychological state. This enables appropriate schedule adjustments and task suggestions according to the user's emotional state, and allows for personalized product suggestions to customers even in physical stores.

[0573] 1. "User input information" refers to data provided by the user via voice or text, which serves as the basic information for the system to analyze and process.

[0574] 2. "Work schedule or activity information" refers to schedules and task plans generated based on user needs, and is information intended to improve the efficiency of daily life and work.

[0575] 3. A "notification" is information that the system sends to the user, and it functions as a reminder for scheduled tasks or events.

[0576] 4. A "push notification" is an alert-style message that is forcibly sent to a user's device, and is a method to immediately attract the user's attention.

[0577] 5. "Communication functions" refer to system features designed to support communication among family members and group members, facilitating smooth information sharing and communication.

[0578] 6. "Health management suggestions" refer to advice and guidance provided by the system to improve the user's health status, and the suggestions are aimed at maintaining and promoting health.

[0579] 7. "Emotional information" refers to data about the user's psychological state detected from their voice and facial expressions, and is information that quantitatively or qualitatively evaluates the user's emotions.

[0580] 8. "Product recommendations based on psychological state" refers to a system function that recommends products and services that are suitable for the user's current mental state, based on analyzed emotional information.

[0581] To implement this invention, a system is required in which a user, a server, and a terminal work in cooperation. The user provides input information to the terminal via voice or text. The terminal converts this information into a format that can be analyzed for sentiment and sends it to the server.

[0582] The server analyzes the user's emotional information using speech recognition systems and text analysis software. Emotion analysis engines such as IBM Watson and Microsoft Azure are used for processing. Based on the emotional information obtained from the user's input, the psychological state is identified, and specific product suggestions are generated using an AI model.

[0583] As a concrete example, if a robot in a store reads a customer's voice and facial expressions and detects that the customer is "looking for a new experience," it can suggest information about new products on a promotion or demonstration events. The server then inputs a prompt into the AI ​​model asking, "What emotions is this customer currently feeling? What approach would be most effective based on that?" and determines the optimal suggestion.

[0584] This system allows users to receive more personalized schedules and product suggestions that are tailored to their emotions, and is expected to improve the customer experience in physical stores.

[0585] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0586] Step 1:

[0587] The user inputs information into the device via voice or text. The device receives this input and, in the case of voice input, converts it to text using a speech recognition system. In this process, voice data is converted into text data.

[0588] Step 2:

[0589] The terminal sends text data to the server. The server receives this text data and inputs it into the sentiment analysis engine. Here, the input is text data, and the output is an analysis result indicating the user's emotional state.

[0590] Step 3:

[0591] Based on the analysis results, the server uses a generative AI model to generate product suggestions tailored to the user's psychological state. In this process, emotional data is received as input, appropriate prompts are used to instruct the AI ​​model, and the optimal product suggestions are output.

[0592] Step 4:

[0593] The generated product proposals are sent from the server to the terminal, which then displays them to the user. In this step, product proposal data is entered and displayed in a format that the user can visually verify.

[0594] Step 5:

[0595] If the user accepts the suggestion, the device sends feedback to the server again and saves it as history. This input is the result of the user's selection, and the data is updated based on the feedback received to improve the accuracy of future suggestions.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] [Fourth Embodiment]

[0600] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0601] 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.

[0602] 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).

[0603] 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.

[0604] 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.

[0605] 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).

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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".

[0613] The system of the present invention has the function of efficiently managing user input information and centrally processing schedules and tasks among family members. The user starts by inputting daily schedules and tasks by voice or text. The terminal receives this user input and, if necessary, converts the voice input into text format using speech recognition technology. The converted data is transmitted from the terminal to the server via the network.

[0614] The server analyzes the received data using natural language processing algorithms to extract schedule or task information. The extracted information is then prioritized based on its importance and urgency, optimizing the schedule. Based on this optimized information, the server sends push notifications as reminders to the user's device at the appropriate time. These notifications are received on the device and serve to prevent users from missing appointments or tasks by providing alerts.

[0615] The system also includes a chat function to facilitate communication among family members. Users can use their devices to exchange messages with family members regarding schedules and tasks. This feature makes it easier to adjust and confirm schedules, and helps to resolve communication breakdowns.

[0616] Furthermore, the server has the functionality to monitor health information and provide personalized health management suggestions for elderly users or those requiring health management. Health status data is collected and analyzed from the user's daily activities. Based on this, the server provides users with specific suggestions for exercise and health maintenance, supporting improvements in their lifestyle.

[0617] As a concrete example, consider a scenario where a user enters a schedule item by voice, such as "Lunch with a friend this Saturday at 2 PM." The device converts the voice to text and sends it to the server. The server analyzes the data, cross-references it with other schedules, and records the lunch appointment for 2 PM on Saturday, along with its priority. Then, on Friday afternoon, it sends a push notification reminder to the user for confirmation. This integration allows users to reliably manage important appointments.

[0618] The following describes the processing flow.

[0619] Step 1:

[0620] Users enter schedules and tasks into the device using voice or text. In the case of voice input, the device uses speech recognition technology to convert the voice data into text format.

[0621] Step 2:

[0622] The terminal sends the converted text data to the server. The transmission is encrypted to ensure data integrity and security.

[0623] Step 3:

[0624] The server analyzes the received data. Using natural language processing algorithms, it extracts important elements from the information, such as date and time, event type, and task type.

[0625] Step 4:

[0626] The server uses the extracted information to compare it with existing schedules and check for any overlaps or inconsistencies. Then, an AI algorithm is used to determine the priority of the schedules.

[0627] Step 5:

[0628] The server stores the determined schedule information in a database. Furthermore, it performs customizations that take into account user preferences and past usage patterns.

[0629] Step 6:

[0630] The server generates a reminder on the user's device at the optimal time and sends it as a push notification. This notification includes schedule details and alerts based on importance.

[0631] Step 7:

[0632] Users can use their devices to check push notifications and, if necessary, change schedules or reset tasks. They can also coordinate and confirm things with family members through the chat function.

[0633] Step 8:

[0634] The server receives and analyzes health information from specific users, such as the elderly. Based on the analysis results, it generates and provides health management suggestions tailored to the user.

[0635] (Example 1)

[0636] 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".

[0637] In modern times, coordinating schedules and managing daily health among family members has become increasingly complex. Traditional methods have made it difficult to efficiently manage individual schedules and health information. In particular, there is a lack of adequate support for the elderly and users who require health management. Therefore, there is a need to develop a system that centrally manages individual schedules and health status and facilitates communication among family members.

[0638] 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.

[0639] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating schedule or task information, and means for determining the priority of the schedule or task information and generating reminders. This enables multiple users to efficiently manage information, avoid missing important appointments, and facilitate smooth communication within families, as well as monitoring and suggesting health information.

[0640] "User input information" refers to data provided by users to the system, including information about schedules and tasks expressed in voice or text format.

[0641] "Analysis" refers to the process of processing user input information acquired by the system and extracting necessary schedule or work information.

[0642] "Schedule or task information" refers to data that shows the details of the actions or tasks that the user plans to perform or complete.

[0643] A "reminder" is an alert that notifies a user in advance of a specific appointment or task.

[0644] "Push notifications" are a technology that allows a system to instantly send information such as reminders to a user's device.

[0645] "Communication function" refers to a message exchange function provided by the system to facilitate the smooth exchange of information among family members.

[0646] "Health information" refers to data about a user's lifestyle and physical condition, and is used for health management.

[0647] "Health management suggestions" refer to specific advice provided by the system based on the user's health information, regarding lifestyle improvements and health promotion.

[0648] "Daily activity data" refers to information about the actions a user takes on a daily basis, and is used to assess and suggest improvements to their health status.

[0649] This invention provides a system for efficiently managing user input information and effectively handling family schedules and tasks. In this system, the user, terminal, and server work together. Users can input daily schedules and tasks in voice or text format using terminals such as smartphones or personal computers. For voice input, the terminal utilizes speech recognition technology to convert voice data into text data. For this purpose, speech recognition software such as the Google Speech-to-Text API can be used.

[0650] The converted information is sent from the terminal to the server via the internet. The server analyzes the received information using advanced natural language processing algorithms. For example, it may use spaCy or the Google Cloud Natural Language API to extract information about schedules and tasks. The server then processes the data to evaluate the importance and urgency of each task and appointment and set priorities.

[0651] Furthermore, based on the optimized schedule information, the server sends reminders as push notifications to the user's device. This reminder function ensures that users are always aware of their appointments. For example, if a user enters a schedule request by voice, such as "Lunch with a friend next Saturday at 2pm," the data is processed appropriately and the schedule is optimized. Then, a reminder is sent one day before the appointment to remind the user.

[0652] Furthermore, this system provides a chat function to assist communication among family members. Users can use this function to share information about schedules and tasks within the family. This facilitates smoother scheduling and helps resolve communication breakdowns.

[0653] Furthermore, the server monitors the user's health information and provides appropriate health management suggestions. By analyzing data collected from daily activities and providing personalized advice on exercise and health maintenance, it improves the user's quality of life. As an example of a prompt message, entering a question such as "Tell me how you share weekend plans with your family" will display suggestions and ways to utilize the system's integration functions.

[0654] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0655] Step 1:

[0656] Users access their smartphones or computers and input their schedules and tasks in voice or text format. For example, they might use a microphone to voice-input something like, "Lunch with a friend next Saturday at 2pm." This input becomes the starting data for the system.

[0657] Step 2:

[0658] The device receives the user's voice input and converts the speech to text using speech recognition software. Specifically, it uses a speech recognition API to output the voice signal as character data. This character data is then passed on to the next processing step.

[0659] Step 3:

[0660] The terminal sends the converted text data to the server over the network. The transmitted data is then passed to the server as schedule or task information. This data transfer enables information exchange between systems.

[0661] Step 4:

[0662] The server analyzes the received text data using natural language processing algorithms. Specifically, it analyzes the text using an NLP library to extract the date, time, and content of the schedule. This process generates schedule or task information.

[0663] Step 5:

[0664] Based on the schedule information obtained through analysis, the server evaluates the importance and urgency of each appointment and sets priorities. This priority data is used to optimize the schedule. This process results in a rational arrangement of appointments.

[0665] Step 6:

[0666] The server sends reminders as push notifications to the user's device based on optimized scheduling information. These reminders include alerts for important appointments. This notification prompts the user to review their schedule and is provided as output.

[0667] Step 7:

[0668] Users share schedule information with family members using the device's chat function. Specifically, they exchange information by sending it as text messages. This function serves as an output that simplifies information sharing among family members.

[0669] Step 8:

[0670] The server collects data on the user's daily activities and monitors their health. It incorporates data such as daily steps and sleep quality to help provide health management suggestions. This process generates personalized health advice.

[0671] (Application Example 1)

[0672] 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".

[0673] Traditionally, shift management and task sharing among staff in physical stores have often relied on manual adjustments and individual communication methods, resulting in inefficient operations. Furthermore, a lack of real-time communication among staff hinders operational efficiency and planned customer service. This invention aims to solve these problems and improve operational efficiency in physical stores.

[0674] 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.

[0675] In this invention, the server includes means for acquiring information in voice or text format, means for analyzing the acquired information and generating schedule and task information, and means for managing employee schedules using voice input and enabling rapid communication within the group. This enables efficient management of staff schedules and tasks in physical stores, and facilitates rapid information sharing and communication among staff.

[0676] "User input information" refers to task and schedule information provided by the user in voice or text format.

[0677] "Analysis" is the process of generating schedules and tasks based on the acquired information.

[0678] "Schedule or task information" refers to information about appointments and work items generated through analysis.

[0679] "Priority" is an indicator used to evaluate the importance and urgency of schedule or task information and to determine the order in which it should be presented.

[0680] A "reminder" is a notification that helps users remember and complete appointments and tasks.

[0681] A "push notification" is a notification that is automatically sent to a user's device.

[0682] An "information processing device" is a device that converts voice input into text data and performs other calculations and communications.

[0683] "Communication functions" refer to features that facilitate message exchange and information sharing within a group.

[0684] "Health management suggestions" refer to advice on lifestyle habits and exercise that is provided taking into account the user's health condition.

[0685] "Employee schedule management" refers to a function for organizing and coordinating the shifts and tasks of store staff.

[0686] "Rapid communication" refers to a state where necessary information can be shared and exchanged among staff members immediately.

[0687] The system for realizing this application consists of an information processing device and a server. The terminal, acting as the information processing device, first acquires input information from the user in the form of voice or text. When voice input is used, the system converts the voice into text data using the speech recognition software "Google Cloud Speech-to-Text".

[0688] The device then sends the acquired text data to the server via the network. The server analyzes the text data using the natural language processing library "NLTK" and extracts information about schedules and tasks. Based on this, task priorities are determined and reminders are generated. This reminder information is sent to the user's information processing device as a push notification via "Firebase Cloud Messaging".

[0689] Furthermore, the server uses "Firebase Realtime Database" to provide communication capabilities that support smooth communication within the group. This communication capability enables real-time information sharing regarding schedules and tasks among store staff. Through this, the server plays a role in achieving efficient business operations and preventing omissions and errors in tasks.

[0690] For example, if a store staff member uses voice input to say "Prepare for the weekend on Friday night," the terminal converts it to text and sends it to the server. Based on this information, the server ensures that all staff members are notified by push notifications that weekend preparations will be carried out.

[0691] An example of an input prompt for a generative AI model is: "Please provide ideas for an application that will help store staff efficiently manage shifts and tasks. Also, please describe in detail how to use a voice input system and push notification functionality." This prompt is expected to prompt the generative AI model to provide design ideas for the relevant application and hints for system improvements.

[0692] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0693] Step 1:

[0694] The user's voice or text input is acquired by the information processing device. In the case of voice input, the device uses "Google Cloud Speech-to-Text" to convert the voice data into text data and generate that text data. Based on the input, the voice data is converted into characters and made into a format that can be processed internally by the device.

[0695] Step 2:

[0696] The terminal sends the converted text data to the server via the network. The user input is sent to the server as text data, enabling analysis in the next stage.

[0697] Step 3:

[0698] The server analyzes the received text data using the natural language processing library "NLTK" to extract schedule and task information. This process extracts specific tasks and appointments, providing the system with the information to make subsequent decisions.

[0699] Step 4:

[0700] The server determines the priority of schedule or task information based on the analysis. In this prioritization process, different pieces of information are assigned different priorities based on urgency and importance.

[0701] Step 5:

[0702] The server generates reminders based on prioritized information and sends them to information processing devices as push notifications using Firebase Cloud Messaging. By delivering reminders to user devices, users will no longer miss tasks or schedules.

[0703] Step 6:

[0704] The server uses "Firebase Realtime Database" to activate a communication function that facilitates real-time communication between staff members. This function allows users to exchange messages with other staff members and share task-related information in real time.

[0705] 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.

[0706] This invention combines an emotion engine with an integrated family management system. The system is designed to recognize emotions from the user's everyday voice and text input and dynamically adjust schedule management and task suggestions accordingly.

[0707] Users input schedules and tasks via their device in voice or text format. The device analyzes the emotion of the voice input, converts it into text data, and sends it to the server. The server receives the input information and uses natural language processing and an emotion engine to determine the user's emotional state. Using this information, the server optimizes the priority of schedules or tasks and adjusts suggestions and reminders according to the user's current emotions.

[0708] This system, in particular, has the ability to reflect the results of the emotion engine in the generation of reminders and notifications, and to change the tone and content of messages to the user according to their psychological state at the time. For example, if the system detects that the user is stressed, it can send suggestions to alleviate tasks or messages of encouragement.

[0709] Furthermore, this emotion engine is integrated into family communication features, allowing for the adjustment of message content based on each member's emotional state during chat and messaging service interactions. This feature reduces misunderstandings and friction within families and promotes smoother communication.

[0710] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server's emotion engine will detect this emotion. As a result, the server can suggest relaxation techniques before the meeting and create a schedule to add enjoyable activities afterward. This entire process aims to improve the user's quality of life and enhance the overall well-being of the family.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] Users input schedules and tasks into the device via voice or text. In the case of voice input, the device uses speech recognition technology and an emotion engine to analyze the user's emotions from the voice and convert it into text data.

[0714] Step 2:

[0715] The device sends the converted text data and sentiment information to the server. The data is encrypted before transmission and sent securely over the network.

[0716] Step 3:

[0717] The server analyzes the received text data and sentiment information to extract schedule and task details. Natural language processing is then used to more accurately understand this data.

[0718] Step 4:

[0719] The server uses emotional information via an emotion engine to adjust the priority of extracted schedules and tasks. If the user is feeling stressed, it may lower the priority of tasks or offer encouraging suggestions.

[0720] Step 5:

[0721] The server generates reminders based on coordinated schedule information. It customizes the content and tone of the reminders based on emotional information, taking into account the user's psychological state.

[0722] Step 6:

[0723] The server sends reminders and notifications as push notifications to the user's device at the appropriate time. The content of the notifications is tailored to the user's current mood.

[0724] Step 7:

[0725] Users can check push notifications on their devices and modify schedules and tasks as needed. They can also use the chat function to communicate with family members and share necessary information.

[0726] Step 8:

[0727] In the family chat function, the server adjusts the content and tone of messages based on each member's emotional information to facilitate smoother communication.

[0728] (Example 2)

[0729] 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".

[0730] In managing family and personal schedules, traditional systems struggle to make dynamic adjustments that take user emotions into account. Furthermore, in family communication, the lack of emotionally-based adjustments leads to misunderstandings and friction.

[0731] 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.

[0732] In this invention, the server includes means for determining the user's emotional state, means for generating and optimizing schedule or task information based on the determined emotional state, and means for facilitating communication among family members and adjusting messages based on emotions. This makes it possible to adjust schedules and notifications according to the user's emotions, thereby improving the quality of communication among family members.

[0733] "User input information" refers to information provided by the user to the system in audio or text format.

[0734] "Emotional state" refers to the state of a user's psychological feelings and emotions, as analyzed from their speech and text.

[0735] "Schedule information" refers to information that shows daily plans and activities in advance.

[0736] "Task information" refers to information used to instruct or submit specific tasks or actions that a user should perform.

[0737] A "reminder" is a notification that prompts users to remember and complete their appointments and tasks.

[0738] "Push notifications" are real-time information notifications that are automatically sent to the user's device.

[0739] A "chat function" is a feature designed to facilitate two-way communication between individuals or groups using text.

[0740] "Emotion-based message adjustment" is a process that dynamically adjusts the content and tone of messages sent, taking into account the user's emotional state.

[0741] "Past activity history" refers to data recorded about a user's past activities and actions.

[0742] This invention is a system designed to support users' daily lives and aims to dynamically optimize schedule and task management based on the user's emotional state. The system performs emotional analysis based on information entered by the user in voice or text format and reflects the results in various suggestions.

[0743] The device receives voice input and converts it into text data using speech recognition software. For example, a speech recognition service can be used for speech recognition. Next, the text data is passed to an emotion analysis engine to determine the user's emotional state. Text analysis technology is used for emotion analysis.

[0744] The server receives emotion data and text data sent from the terminal. This data is analyzed using a generative AI model to optimize schedules and tasks according to the user's emotions. Natural language processing technology is used as the generative AI model.

[0745] For example, if a user enters "I'm feeling a bit depressed about next week's meeting...", the server will use emotion analysis to determine that the user is feeling "depressed." Based on this, the server can suggest ways to relax before the meeting or create a schedule that includes something enjoyable afterward. This entire process can improve the user's quality of life.

[0746] As an example of a prompt, you can give specific instructions to the AI, such as, "If the user is feeling anxious about the meeting, generate suggestions for ways to relax or positive messages." This prompt is passed to the AI ​​model, which then generates appropriate feedback.

[0747] Thus, the present invention aims to achieve schedule management that takes into account the user's emotions and to facilitate smooth communication among family members.

[0748] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0749] Step 1:

[0750] Users input information about their daily schedules and tasks into the device in either voice or text format. The input information is converted from speech to text using speech recognition software. Specifically, if the user inputs "I'm feeling a bit depressed about next week's meeting...", the device will generate the text data "I'm feeling a bit depressed about next week's meeting...".

[0751] Step 2:

[0752] The device passes text data to an emotion analysis engine to determine the user's emotional state. The input is the text data generated in step 1. The emotion analysis engine analyzes keywords and context within the text and outputs an emotion such as "melancholy." This analysis makes it possible to identify the type and intensity of the emotion.

[0753] Step 3:

[0754] The terminal sends emotion data and text data to the server. In this step, the emotional information generated by the terminal is packaged in digital format and sent to the server over the network. The server then supplies the received data to the next analysis phase.

[0755] Step 4:

[0756] The server inputs received emotion data and text data into a generating AI model. This model uses natural language processing technology to analyze the user's statements in detail and generate appropriate feedback. Specifically, the server optimizes schedules and adjusts tasks according to emotions, and generates suggestions as output.

[0757] Step 5:

[0758] The server sends the generated feedback to the user's terminal and notifies the user. This feedback includes schedule adjustments and encouraging messages that take the user's feelings into consideration. For example, it might output a suggestion such as, "Why not try some ways to relax before the meeting?"

[0759] Step 6:

[0760] Users act based on feedback received from their devices. In this step, users review the suggestions provided and incorporate them into their actual schedules. This not only improves the quality of daily life but also enables more flexible responses that are tailored to their emotions.

[0761] (Application Example 2)

[0762] 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".

[0763] Traditional integrated family management systems lacked the dynamic ability to respond to users' emotional states, making it difficult to provide individualized services and suggestions based on their psychological state. Furthermore, in physical stores, it was impossible to offer product suggestions and services that aligned with customers' emotions, limiting the improvement of customer satisfaction. There is a need to solve these problems and realize a richer user experience.

[0764] 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.

[0765] In this invention, the server includes means for acquiring user input information in voice or text format, means for analyzing the acquired information and generating work schedules or activity information, and means for analyzing customer emotional information and making specific product suggestions based on their psychological state. This enables appropriate schedule adjustments and task suggestions according to the user's emotional state, and allows for personalized product suggestions to customers even in physical stores.

[0766] 1. "User input information" refers to data provided by the user via voice or text, which serves as the basic information for the system to analyze and process.

[0767] 2. "Work schedule or activity information" refers to schedules and task plans generated based on user needs, and is information intended to improve the efficiency of daily life and work.

[0768] 3. A "notification" is information that the system sends to the user, and it functions as a reminder for scheduled tasks or events.

[0769] 4. A "push notification" is an alert-style message that is forcibly sent to a user's device, and is a method to immediately attract the user's attention.

[0770] 5. "Communication functions" refer to system features designed to support communication among family members and group members, facilitating smooth information sharing and communication.

[0771] 6. "Health management suggestions" refer to advice and guidance provided by the system to improve the user's health status, and the suggestions are aimed at maintaining and promoting health.

[0772] 7. "Emotional information" refers to data about the user's psychological state detected from their voice and facial expressions, and is information that quantitatively or qualitatively evaluates the user's emotions.

[0773] 8. "Product recommendations based on psychological state" refers to a system function that recommends products and services that are suitable for the user's current mental state, based on analyzed emotional information.

[0774] To implement this invention, a system is required in which a user, a server, and a terminal work in cooperation. The user provides input information to the terminal via voice or text. The terminal converts this information into a format that can be analyzed for sentiment and sends it to the server.

[0775] The server analyzes the user's emotional information using speech recognition systems and text analysis software. Emotion analysis engines such as IBM Watson and Microsoft Azure are used for processing. Based on the emotional information obtained from the user's input, the psychological state is identified, and specific product suggestions are generated using an AI model.

[0776] As a concrete example, if a robot in a store reads a customer's voice and facial expressions and detects that the customer is "looking for a new experience," it can suggest information about new products on a promotion or demonstration events. The server then inputs a prompt into the AI ​​model asking, "What emotions is this customer currently feeling? What approach would be most effective based on that?" and determines the optimal suggestion.

[0777] This system allows users to receive more personalized schedules and product suggestions that are tailored to their emotions, and is expected to improve the customer experience in physical stores.

[0778] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0779] Step 1:

[0780] The user inputs information into the device via voice or text. The device receives this input and, in the case of voice input, converts it to text using a speech recognition system. In this process, voice data is converted into text data.

[0781] Step 2:

[0782] The terminal sends text data to the server. The server receives this text data and inputs it into the sentiment analysis engine. Here, the input is text data, and the output is an analysis result indicating the user's emotional state.

[0783] Step 3:

[0784] Based on the analysis results, the server uses a generative AI model to generate product suggestions tailored to the user's psychological state. In this process, emotional data is received as input, appropriate prompts are used to instruct the AI ​​model, and the optimal product suggestions are output.

[0785] Step 4:

[0786] The generated product proposals are sent from the server to the terminal, which then displays them to the user. In this step, product proposal data is entered and displayed in a format that the user can visually verify.

[0787] Step 5:

[0788] If the user accepts the suggestion, the device sends feedback to the server again and saves it as history. This input is the result of the user's selection, and the data is updated based on the feedback received to improve the accuracy of future suggestions.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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."

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] The following is further disclosed regarding the embodiments described above.

[0811] (Claim 1)

[0812] A means of obtaining user input information in voice or text format,

[0813] A means for analyzing acquired information and generating schedule or task information,

[0814] A means for determining the priority of schedule or task information and generating reminders,

[0815] A means of sending a reminder as a push notification to the user's device,

[0816] A means of providing a chat function to facilitate communication among family members,

[0817] A means of monitoring users' health information and providing appropriate health management suggestions,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, further comprising means for learning the user's past behavior history and making customized suggestions.

[0821] (Claim 3)

[0822] The system according to claim 1, comprising means for converting voice input from a user device into text data.

[0823] "Example 1"

[0824] (Claim 1)

[0825] A means of obtaining user input information in voice or text format,

[0826] A means for analyzing acquired information and generating schedule or work information,

[0827] A means for determining the priority of scheduled or work information and generating reminders,

[0828] A means of sending a reminder as a notification to the user's device,

[0829] A means of providing communication functions that facilitate information exchange among family members,

[0830] A means of monitoring users' health information and providing appropriate health management suggestions,

[0831] A means of collecting users' daily activity data and providing health recommendations based on the analysis results,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, further comprising means for learning the user's past behavioral history and making customized suggestions.

[0835] (Claim 3)

[0836] The system according to claim 1, comprising means for converting voice input from a user device into text data.

[0837] "Application Example 1"

[0838] (Claim 1)

[0839] A means of obtaining user input information in voice or text format,

[0840] A means for analyzing acquired information and generating schedule or task information,

[0841] A means for determining the priority of schedule or task information and generating reminders,

[0842] A means for sending a reminder as a push notification to an information processing device,

[0843] A means of providing communication functions that facilitate communication within a group,

[0844] A means of monitoring users' health information and providing appropriate health management suggestions,

[0845] A means of managing employee schedules using voice input and enabling rapid communication within a group,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, further comprising means for learning the user's past behavior history and making customized suggestions.

[0849] (Claim 3)

[0850] The system according to claim 1, comprising means for converting voice input from an information processing device into text data.

[0851] "Example 2 of combining an emotion engine"

[0852] (Claim 1)

[0853] A means of obtaining user input information in voice or text format,

[0854] A means of analyzing acquired information and determining emotional state,

[0855] A means for generating and optimizing schedule or task information based on the determined emotional state,

[0856] A means for dynamically determining the priority of schedule or task information based on emotions and generating reminders,

[0857] A means of sending a reminder as a push notification to the user's device,

[0858] It provides a chat function to facilitate communication among family members and a means of adjusting messages based on emotions.

[0859] A means of monitoring the user's emotional state and providing appropriate suggestions,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, further comprising means for learning the user's past behavioral and emotional history and making customized suggestions.

[0863] (Claim 3)

[0864] The system according to claim 1, comprising means for converting voice input from a user terminal into text data and performing sentiment analysis.

[0865] "Application example 2 when combining with an emotional engine"

[0866] (Claim 1)

[0867] A means of obtaining user input information in voice or text format,

[0868] A means for analyzing acquired information and generating work schedules or activity information,

[0869] A means for determining the priority of work schedules or activity information and generating notifications,

[0870] A means of sending notifications to user devices as push notifications,

[0871] A means of providing communication functions that facilitate communication among family members,

[0872] A means of monitoring users' health information and providing appropriate health management suggestions,

[0873] A means of analyzing customer emotional information and making specific product suggestions based on their psychological state,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, further comprising means for learning the user's past behavior history and making customized suggestions.

[0877] (Claim 3)

[0878] The system according to claim 1, comprising means for converting voice input from a user device into text data. [Explanation of symbols]

[0879] 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. A means of obtaining user input information in voice or text format, A means for analyzing acquired information and generating schedule or task information, A means for determining the priority of schedule or task information and generating reminders, A means of sending a reminder as a push notification to the user's device, A means of providing a chat function to facilitate communication among family members, A means of monitoring users' health information and providing appropriate health management suggestions, A system that includes this.

2. The system according to claim 1, further comprising means for learning the user's past behavior history and making customized suggestions.

3. The system according to claim 1, comprising means for converting voice input from a user device into text data.

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