system

Abstract

We provide the system. [Solution] A means for an information processing device to analyze a message received from a communication terminal, A means for registering schedule information in a calendar based on the information extracted by the aforementioned analysis means, A means for generating proposed information based on the aforementioned scheduled information, Means for notifying a communication terminal of the generated proposal information, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern information society, when a user communicates within a messaging application, there is a problem that the user has to switch between multiple applications to perform task management and schedule adjustment. As a result, information may be lost and management may be complicated, which may reduce the user experience. Furthermore, there is also a problem that the user has to manually prepare for events and select related facilities, and there is a lack of efficient support for daily life.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system in which an information processing device analyzes messages received from a communication terminal to extract schedule information and registers that schedule information in a calendar. This allows important information in messages to be managed automatically, reducing the effort required for users to manually check the information. Furthermore, the system generates a list of facilities related to the event based on the extracted information and notifies the communication terminal, thereby providing efficient information to support user decision-making. In addition, by suggesting optimal information based on past history, the system personalizes the user experience and improves convenience.

[0006] An "information processing device" is a device that analyzes data received from a communication terminal and performs appropriate processing on it.

[0007] A "communication terminal" is a device used by a user to send and receive information, and includes, for example, smartphones and tablets.

[0008] A "message" refers to information such as text, audio, and images exchanged via a communication device.

[0009] "Analyzing" refers to the process of examining received data, understanding its content, and extracting necessary information.

[0010] "Schedule information" refers to information related to a specific activity or event, such as the date and time, participants, and location.

[0011] "Adding to the calendar" is the process of organizing extracted schedule information and reflecting it in a predetermined time schedule.

[0012] "Suggestion information" refers to relevant options and advice generated with the aim of supporting the user's decision-making.

[0013] "Notifying" means sending a message generated by the system to the user's communication terminal to draw attention to or prompt action.

[0014] The "facility list" is a list of stores, locations, etc. selected based on specific criteria and is presented as options for events and activities.

[0015] "History information" refers to data related to the activities and selections of users recorded in the past.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of 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.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention provides an information processing system for streamlining the management of daily tasks and schedules by utilizing messages transmitted by users through communication terminals. The following describes in detail the embodiments of this system.

[0038] First, users exchange messages with friends and colleagues as usual using their communication devices. These messages may include information about schedules, such as dates, times, and event details.

[0039] Upon receiving these messages, the server immediately begins analyzing them. An information analysis module built into the server understands the message content and extracts important schedule information. For example, if a message is received stating "Meeting tomorrow at 3pm," the server identifies the date, time, and event (meeting), and then registers it in the calendar.

[0040] Subsequently, the server generates helpful suggestions for the user based on the registered schedule information. This process utilizes the user's past history to create suggestion information such as a list of facilities related to the event.

[0041] The server generates suggestion and notification information, which is then sent to the communication terminal. The terminal immediately notifies the user of this information visually or audibly. For example, this could include information such as "We recommend a restaurant near the meeting."

[0042] Specifically, when a user sends a message saying "Dinner with friends this weekend," the server uses this information to generate a list of restaurants suitable for the time and place and suggests them to the user. This allows the user to choose the best option from the suggested choices and efficiently prepare for the dinner.

[0043] This system allows users to seamlessly manage tasks and schedules within messaging applications, receiving automated assistance without requiring complex operations. This is expected to significantly improve the convenience of daily life.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users use their communication devices to send messages to friends and colleagues. These messages may include information about appointments and events.

[0047] Step 2:

[0048] The server receives a message from the communication terminal. It passes the message to the information analysis module within the server, which then begins analyzing its contents.

[0049] Step 3:

[0050] The server's information analysis module automatically extracts information related to the event from the message. For example, it analyzes the date, time, event name, and participant information.

[0051] Step 4:

[0052] Based on the schedule information extracted by the server, a new event is registered in the user's calendar. Reminder notifications are also set during the calendar registration process.

[0053] Step 5:

[0054] The server uses the registered event information to generate relevant suggestion information for the user. This suggestion information includes a list of suitable venues for the event and recommended options.

[0055] Step 6:

[0056] The server sends suggestion and notification information to the communication terminal. The terminal receives this information and notifies the user. The notification is made via screen display or audio alert.

[0057] Step 7:

[0058] The user reviews the notification and chooses an action based on the suggested information. If necessary, they provide feedback to the server to update the information.

[0059] (Example 1)

[0060] 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."

[0061] In daily life, manually entering and managing schedules is time-consuming and prone to oversight. Furthermore, obtaining appropriate suggestions based on these schedules is not easy, hindering users' efficient actions.

[0062] 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.

[0063] In this invention, the server includes means for analyzing text information received by an information processing system from a communication device, means for registering the schedule information extracted by the analysis means into a schedule table, and means for generating recommendation information based on the schedule information and past history. This allows users to manage their schedules effortlessly and obtain relevant and useful suggestion information.

[0064] An "information processing system" is a mechanism that handles a series of processes, including receiving text information from communication devices, analyzing it, registering it, and sending notifications.

[0065] "Communication equipment" refers to devices that users use on a daily basis and that send and receive information via a network.

[0066] "Text information" refers to data containing sentences transmitted by users using communication devices, and is a message expressed in natural language.

[0067] "Analysis means" refers to technology that has the function of understanding the content of text information and extracting related planned information and patterns.

[0068] "Schedule information" refers to data used to identify and manage dates, times, and events related to a user's schedule.

[0069] A "schedule" is a digital or physical management tool where schedule information is registered.

[0070] "Recommendation information" refers to suggestion data generated based on scheduled information and past history, designed to support user behavior.

[0071] A "notification method" is a technology that communicates generated recommendation information to the user and allows them to confirm it.

[0072] This information processing system transmits text information through communication devices that users use on a daily basis, and uses that information to manage schedules and generate suggestion information. The following describes a specific embodiment of this system.

[0073] The server first receives text information transmitted from communication devices. This text information is a message written in natural language and may include schedule and event information found in everyday conversation. The server has a built-in parsing module that implements natural language processing technology and performs analysis on the received text information. The parsing module uses open-source natural language processing libraries (e.g., NLTK and spaCy).

[0074] After analysis, the server automatically registers the extracted schedule information into the user's calendar application. At this time, the calendar application is synchronized with the server, allowing the user to manually check their schedule later.

[0075] Next, the server uses historical data and analyzed schedule information to generate recommendations for the user. This generation process utilizes a generative AI model that learns patterns from past user behavior. As a result, useful recommendations are generated for the user, such as lists of relevant facilities and activities.

[0076] Finally, the generated recommendation information is notified to the communication device, and the terminal immediately provides the user with a visual or audio notification. This allows the user to obtain useful information without any additional effort.

[0077] As a concrete example, suppose a user sends a message saying, "I'm going to see a movie on Saturday." In this case, the server analyzes this information, registers it in the calendar, and generates recommendation information, including a list of restaurants around the movie theater, and notifies the communication device. An example of a prompt message to the generating AI model in this case would be, "Please generate suggestions for related facilities based on my schedule." The introduction of this system makes it easier for users to manage their schedules, enabling them to live more efficiently in their daily lives.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The user sends text information using a communication device. The input is a message written in natural language as if it were everyday conversation. Specifically, it might be something like, "Let's go to lunch next Friday." This input itself is transmitted to the server via the communication network.

[0081] Step 2:

[0082] The server receives text information from the communication terminal. A natural language processing module within the server analyzes this text information. Specifically, it tokenizes the text information and extracts date, time, and event information. It analyzes keywords such as "next Friday" and "lunch" from the input message and outputs this as schedule information.

[0083] Step 3:

[0084] The server registers the information into the user's calendar based on the analyzed schedule information. The input for this is the schedule information extracted in step 2. The server synchronizes with the calendar management system and automatically adds "Lunch next Friday" to the calendar. As a result, a digital calendar with detailed schedule information is output.

[0085] Step 4:

[0086] The server uses historical data and the schedule information generated in step 2 to create recommendation information via a generative AI model. The input for this process is similar past schedules and related event information. The generative AI model analyzes past patterns and outputs recommendation information such as "recommended restaurants near your lunch location."

[0087] Step 5:

[0088] The server generates recommendation information and notifies the communication terminal. The user's terminal receives this information and performs the specific action of displaying the notification to the user. Visually, the user is presented with a notification such as, "There are some recommended restaurants near you for lunch." As a result, the user receives output that allows them to quickly obtain useful information.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] In modern life, managing daily tasks and schedules is a significant burden for individuals. Therefore, there is a need for information processing systems that efficiently automate these processes, improving quality of life without requiring users to manually manage schedules or plan their schedules.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes means for analyzing messages received from a communication terminal by an information processing device, means for registering schedule information on a recording medium based on the information extracted by the analysis means, means for generating suggestion content based on the schedule information, means for notifying the communication terminal of the generated suggestion content, and means for a life support device to autonomously manage and suggest the user's schedule based on the suggestion content. This makes it possible to improve the efficiency of daily life without the user having to perform complex operations.

[0094] An "information processing device" is a device that analyzes messages from communication terminals and extracts and processes important data.

[0095] A "communication terminal" is a digital device used by a user to send messages.

[0096] "Analysis means" refers to a function that extracts date, time, and event information from received messages.

[0097] "Schedule information" refers to information about dates, times, and events extracted by the analysis method.

[0098] A "recording medium" is a data storage device used to save schedule information.

[0099] "Proposed content" refers to data generated based on scheduled information, which includes suggestions that are beneficial to the user.

[0100] "Means of notification" refers to a method of informing the user of the generated proposal content via a communication terminal.

[0101] "Life support devices" are autonomous digital devices designed to assist users in their daily lives.

[0102] This invention is a system that efficiently manages and suggests schedule and task information that naturally arises when a user sends a message using a communication terminal that the user uses on a daily basis.

[0103] After receiving a message from a communication terminal, the server performs analysis using an information processing device. Specifically, it uses message analysis software (e.g., a natural language processing library) to extract date, time, and event information. The analyzed information is saved to a recording medium as schedule information. This eliminates the need for users to manually input information.

[0104] Next, the server uses the extracted schedule information to generate suggestions. The generated suggestions are sent to the communication terminal, and the user can plan their actions based on them. In this process, information is integrated using a calendar API (e.g., Google® Calendar API), and a life support device autonomously assists with schedule management based on the user's past behavior patterns.

[0105] For example, if a user sends a message saying, "I have a meeting with a friend tomorrow at 3 PM," the server uses this information to suggest necessary settings and preparations before the meeting and notifies the user of recommended cafes near the meeting place. This allows the user to handle everyday tasks more efficiently and improves their quality of life.

[0106] An example of a prompt for a generative AI model is, "Based on the expected weather and traffic conditions, please suggest what preparations I should make for the lunch meeting I've identified for tomorrow at noon." This allows the user to choose the most appropriate action from a set of options.

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The server receives a message from the communication terminal. This message becomes the input. Specifically, the server uses a message receiving module to capture the message data from the terminal.

[0110] Step 2:

[0111] The server uses message analysis software to analyze the received message. The input is the message received in step 1, and here, natural language processing (NLP) techniques are used to extract date, time, and event information from the message. This analysis outputs the schedule information.

[0112] Step 3:

[0113] The server saves the analyzed schedule information to a recording medium. The input is the schedule information extracted in step 2. This information is then saved to the database, which facilitates automated schedule management.

[0114] Step 4:

[0115] The server generates suggestions using the schedule information. The schedule information saved in step 3 is used as input. In this process, the generating AI model generates various types of information that should be suggested (e.g., restaurant information around the meeting place) based on past user behavior patterns.

[0116] Step 5:

[0117] The server notifies the communication terminal of the generated proposal. The input is the proposal generated in step 4, and the output is the notification to the user's communication terminal. This operation allows the user to review the proposal and take appropriate action.

[0118] Step 6:

[0119] The user manages their schedule using the assistive device based on the suggested content they receive. The input here is the suggested content received in step 5. Specifically, the user can check their schedule and perform tasks according to the suggestions from the assistive device.

[0120] 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.

[0121] This invention provides an information processing system that analyzes messages from users, registers schedule information and generates suggestion information, and recognizes the user's emotions to provide more appropriate suggestions. The embodiments of this invention are described in detail below.

[0122] Users send messages via their communication devices. These messages may include not only information about their usual schedules, but also content that reflects their emotions. For example, a conversation might occur where a user complains to a friend about a busy weekend.

[0123] The server receives this message and passes it to the information analysis module and the sentiment engine for analysis. The information analysis module extracts standard schedule information from the message, while the sentiment engine analyzes the user's emotional state. For example, the sentiment engine may recognize that the user is feeling stressed.

[0124] Once the schedule information is extracted, the server registers this information in the calendar. Based on the output of the emotion engine, the server uses means to personalize the suggested information. In particular, it generates a list of relaxation or entertainment facilities according to the user's emotions. This suggested information corresponds to the user's current emotional state and can increase user satisfaction.

[0125] Suggestion and notification information sent from the server is received by the communication terminal. The terminal displays this information, and the user selects an action based on the suggestion. For example, a user experiencing stress may be notified of information about nearby spas or relaxation facilities.

[0126] The advantage of this invention is that it provides optimized suggestions while taking into account the user's emotional state. This allows users to receive more personalized and meaningful suggestions and choose appropriate actions based on their emotional state. This system is expected to reduce stress in users' lives and improve convenience.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] Users use communication devices to exchange messages with friends and colleagues. These messages may include plans, events, and their emotions at the time.

[0130] Step 2:

[0131] The server receives a message from the user. The received message is passed to the server's information analysis module and emotion engine for analysis.

[0132] Step 3:

[0133] The server's information analysis module automatically extracts schedule-related information from the message. This includes date, time, location, and event name.

[0134] Step 4:

[0135] The server's emotion engine analyzes the user's emotions from the wording and expressions within the message and identifies their emotional state.

[0136] Step 5:

[0137] Based on the schedule information extracted by the server, the event is registered in the user's calendar. A reminder notification is set when the event is registered in the calendar.

[0138] Step 6:

[0139] The server generates suggestion information appropriate to the user's emotional state, as recognized by the emotion engine. This suggestion information includes a list of facilities and activity suggestions tailored to the user's emotions.

[0140] Step 7:

[0141] The server sends the proposed information and notification information it has created to the communication terminal. The terminal receives this information and displays and notifies the user.

[0142] Step 8:

[0143] The user reviews the notified information and selects from the suggested facilities and activities. If necessary, this information is fed back to the server via the device, and it is reflected in future suggestions.

[0144] (Example 2)

[0145] 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".

[0146] Conventional information processing systems simply registered and notified users of their schedules without considering their emotional state, resulting in a poor user experience and an inability to meet individual needs. As a result, the information users received was not always useful or relaxing, and improvements are needed to better address the user's psychological state, especially when they are experiencing stress.

[0147] 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.

[0148] In this invention, the server includes means for analyzing text received by an information processing device from a communication device, means for registering schedule information on a recording medium based on the information extracted by the analysis means, and means for generating individual suggestion information using a generative AI model based on the schedule information and the user's emotional state. This makes it possible to provide personalized suggestion information that takes the user's emotional state into consideration.

[0149] An "information processing device" is a device that analyzes messages and extracts and processes the necessary information.

[0150] "Communication equipment" refers to devices used to send and receive data between an information processing device and a user.

[0151] A "text" is a natural language message sent by a user via a communication device.

[0152] "Analysis means" refers to methods and techniques for analyzing received messages and extracting necessary information.

[0153] "Schedule information" refers to data used to record and manage a user's schedule.

[0154] A "recording medium" is a storage device used to save timetable information.

[0155] "Emotional state" refers to the user's psychological state, and is an indicator used to evaluate and judge this state.

[0156] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate individual suggestions based on various pieces of information.

[0157] "Suggested information" refers to information that indicates recommended actions or options, created based on the user's needs and emotional state.

[0158] This invention is an information processing system that processes messages from users, registers schedule information, and generates and notifies users of suggestion information tailored to their emotions. The system is primarily implemented using a server, a communication terminal, and a generative AI model.

[0159] Users send messages via their everyday communication devices. These messages may include information about their usual schedules and their emotions. For example, a message expressing stress might take the form of, "This weekend is going to be really busy, I need some time to relax."

[0160] The server sends messages received from communication terminals to the analysis module and sentiment analysis engine. This allows for the analysis of information related to schedules and emotional indicators within the messages. The analysis module uses natural language processing techniques to analyze the text and extract the desired information. The sentiment analysis engine identifies the user's emotional state from the text and generates suggestions using a generative AI model based on the results. If the sentiment analysis reveals the user's stress level, appropriate suggestions are provided.

[0161] Schedule information is registered on a recording medium, and the server uses this to efficiently manage the user's schedule. Meanwhile, based on the sentiment analysis results, a generative AI model generates suggestion information using prompt sentences explained in natural language. An example of a prompt sentence is, "Please suggest relaxation facilities that would be suitable if the user is feeling stressed."

[0162] The generated suggestion information is sent to the device and notified to the user. This suggestion information is based on the user's emotional state and may include, for example, "nearby spas" or "relaxation facilities." Based on the displayed information, the user can select the necessary reservations or actions.

[0163] In this way, the present invention aims to improve the user's quality of life by providing a personalized experience that takes into account the user's emotional state.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] The user sends a natural language message to the server via a communication device. This message may include information about their schedule and phrases indicating their feelings. A specific example is the message, "I'm stressed because I have a lot of work this weekend." The input data is this natural language message, and we proceed to the next step.

[0167] Step 2:

[0168] The server sends the received message to the analysis module. The analysis module uses natural language processing algorithms to identify and extract schedule-related information and phrases suggesting emotions from the message. The input is a message from the user, and the output is schedule information and emotion data. For example, keywords such as "weekend," "work," and "stress" may be extracted.

[0169] Step 3:

[0170] The server further analyzes the emotional data extracted from the message using an emotion analysis engine to recognize the user's emotional state. Here, the emotion analysis algorithm specifically identifies abstract emotional states. The input is the emotional data obtained in the previous step, and the output is the user's specific emotional state (e.g., stressed state).

[0171] Step 4:

[0172] The server uses a generative AI model to generate personalized suggestions based on the user's emotional state and schedule information. The prompt used is in the format, "Please suggest relaxation facilities if the user is feeling stressed." The input is the user's emotional state and the specified prompt, and the output is personalized suggestions. Specifically, a list of relaxation facilities is generated.

[0173] Step 5:

[0174] The server sends the generated suggestion information to the communication terminal and notifies the user. The input is the suggestion information obtained from the generating AI model, and the output is its display on the user interface. Based on the displayed information, the user can select actions for relaxation. For example, information on "nearby spas" or "yoga classes" may be presented on the terminal.

[0175] (Application Example 2)

[0176] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0177] In modern urban life, people need ways to cope with daily stress and emotional fluctuations. However, conventional scheduling systems have the challenge of not being able to provide personalized information that takes into account the user's emotions, and making suggestions that are appropriate to the user's psychological state.

[0178] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0179] In this invention, the server includes means for analyzing messages received by an information processing device from a communication device, means for acquiring emotional information using the information extracted by the analysis means and emotional analysis means, and for recording scheduled information, means for generating facility suggestion information based on the scheduled information and emotional information, and means for notifying the communication device of the generated facility suggestion information. This makes it possible to provide personalized suggestion information that takes into account the user's emotional state.

[0180] An "information processing device" is a device that has the function of receiving and analyzing messages.

[0181] A "communication device" is a device used to send and receive messages from users.

[0182] "Analysis means" refers to means that have processing capabilities to extract information from received messages and to understand the emotional state.

[0183] "Emotion analysis means" refers to a function that evaluates and obtains emotions from a user's message.

[0184] "Schedule information" refers to information extracted from messages and used to manage future actions and events.

[0185] "Facility suggestion information" refers to information that suggests the most suitable facilities and activities to the user based on their emotional and scheduled information.

[0186] "Means of notification" refers to the means of delivering the generated facility proposal information to the user's communication device.

[0187] This invention provides an information processing system that makes appropriate suggestions based on the emotional state of users within an urban environment. The system consists of an information processing device, a communication device, and a software program for coordinating these devices.

[0188] The server receives messages sent by users using communication devices and extracts schedule information and sentiment information from those messages through analysis and sentiment analysis means. This involves using specific software such as natural language processing libraries (e.g., Google Cloud Natural Language API) and sentiment analysis engines (e.g., Microsoft® Azure® Text Analytics).

[0189] Next, the server combines the extracted schedule and sentiment information to generate optimal facility recommendations for the user. This takes into account the user's current location and the available facility database to provide suitable relaxation facilities and entertainment options.

[0190] This generated facility suggestion information is transmitted to the user's communication device via a notification system. The terminal visually displays this information to the user, allowing the user to choose an action based on the suggestions. For example, if the user sends the message "I want to relax this weekend," the system will respond by suggesting nearby cafes and parks.

[0191] As a concrete example, an example of a prompt using a generative AI model is: "Extract the emotion from this user's message and suggest places that match that emotion. For example, if the user is looking to relax, list nearby cafes and parks." In this way, the present invention provides personalized information that responds to the user's emotions, thereby improving their quality of life.

[0192] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0193] Step 1:

[0194] A user uses a communication device to send a message as input. The message contains not only regular text information but also emotional content. This marks the beginning of data reception in the system.

[0195] Step 2:

[0196] The server receives a message from the user. Next, the information processing device uses a parsing mechanism with this message as input. Using a natural language processing library (e.g., Google Cloud Natural Language API), it extracts schedule information and obtains sentiment information using sentiment analysis functionality. The outputs are the extracted schedule information and sentiment information.

[0197] Step 3:

[0198] The server performs data calculations to generate facility suggestion information based on the obtained schedule and emotional information. It refers to the available facility database and filters and lists options that are appropriate for the user's current emotional state. This generates appropriate facility suggestion information.

[0199] Step 4:

[0200] The server uses a notification mechanism to send the generated facility suggestion information to the user's communication device as output. The information contains a list of facilities and services suggested to the user.

[0201] Step 5:

[0202] The terminal receives the suggestion information and displays it visually to the user. The user reviews the displayed suggestions and selects an action, such as visiting a suggested cafe. This step allows the system's suggestions to support the user's decision-making.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] 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.

[0209] 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).

[0210] 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.

[0211] 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.

[0212] 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).

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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".

[0219] This invention provides an information processing system for streamlining the management of daily tasks and schedules by utilizing messages transmitted by users through communication terminals. The following describes in detail the embodiments of this system.

[0220] First, users exchange messages with friends and colleagues as usual using their communication devices. These messages may include information about schedules, such as dates, times, and event details.

[0221] Upon receiving these messages, the server immediately begins analyzing them. An information analysis module built into the server understands the message content and extracts important schedule information. For example, if a message is received stating "Meeting tomorrow at 3pm," the server identifies the date, time, and event (meeting), and then registers it in the calendar.

[0222] Subsequently, the server generates helpful suggestions for the user based on the registered schedule information. This process utilizes the user's past history to create suggestion information such as a list of facilities related to the event.

[0223] The server generates suggestion and notification information, which is then sent to the communication terminal. The terminal immediately notifies the user of this information visually or audibly. For example, this could include information such as "We recommend a restaurant near the meeting."

[0224] Specifically, when a user sends a message saying "Dinner with friends this weekend," the server uses this information to generate a list of restaurants suitable for the time and place and suggests them to the user. This allows the user to choose the best option from the suggested choices and efficiently prepare for the dinner.

[0225] This system allows users to seamlessly manage tasks and schedules within messaging applications, receiving automated assistance without requiring complex operations. This is expected to significantly improve the convenience of daily life.

[0226] The following describes the processing flow.

[0227] Step 1:

[0228] Users use their communication devices to send messages to friends and colleagues. These messages may include information about appointments and events.

[0229] Step 2:

[0230] The server receives a message from the communication terminal. It passes the message to the information analysis module within the server, which then begins analyzing its contents.

[0231] Step 3:

[0232] The server's information analysis module automatically extracts information related to the event from the message. For example, it analyzes the date, time, event name, and participant information.

[0233] Step 4:

[0234] Based on the schedule information extracted by the server, a new event is registered in the user's calendar. Reminder notifications are also set during the calendar registration process.

[0235] Step 5:

[0236] The server uses the registered event information to generate relevant suggestion information for the user. This suggestion information includes a list of suitable venues for the event and recommended options.

[0237] Step 6:

[0238] The server sends suggestion and notification information to the communication terminal. The terminal receives this information and notifies the user. The notification is made via screen display or audio alert.

[0239] Step 7:

[0240] The user reviews the notification and chooses an action based on the suggested information. If necessary, they provide feedback to the server to update the information.

[0241] (Example 1)

[0242] 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."

[0243] In daily life, manually entering and managing schedules is time-consuming and prone to oversight. Furthermore, obtaining appropriate suggestions based on these schedules is not easy, hindering users' efficient actions.

[0244] 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.

[0245] In this invention, the server includes means for analyzing text information received by an information processing system from a communication device, means for registering the schedule information extracted by the analysis means into a schedule table, and means for generating recommendation information based on the schedule information and past history. This allows users to manage their schedules effortlessly and obtain relevant and useful suggestion information.

[0246] An "information processing system" is a mechanism that handles a series of processes, including receiving text information from communication devices, analyzing it, registering it, and sending notifications.

[0247] "Communication equipment" refers to devices that users use on a daily basis and that send and receive information via a network.

[0248] "Text information" refers to data containing sentences transmitted by users using communication devices, and is a message expressed in natural language.

[0249] "Analysis means" refers to technology that has the function of understanding the content of text information and extracting related planned information and patterns.

[0250] "Schedule information" refers to data used to identify and manage dates, times, and events related to a user's schedule.

[0251] A "schedule" is a digital or physical management tool where schedule information is registered.

[0252] "Recommendation information" refers to suggestion data generated based on scheduled information and past history, designed to support user behavior.

[0253] A "notification method" is a technology that communicates generated recommendation information to the user and allows them to confirm it.

[0254] This information processing system transmits text information through communication devices that users use on a daily basis, and uses that information to manage schedules and generate suggestion information. The following describes a specific embodiment of this system.

[0255] The server first receives text information transmitted from communication devices. This text information is a message written in natural language and may include schedule and event information found in everyday conversation. The server has a built-in parsing module that implements natural language processing technology and performs analysis on the received text information. The parsing module uses open-source natural language processing libraries (e.g., NLTK and spaCy).

[0256] After analysis, the server automatically registers the extracted schedule information into the user's calendar application. At this time, the calendar application is synchronized with the server, allowing the user to manually check their schedule later.

[0257] Next, the server uses historical data and analyzed schedule information to generate recommendations for the user. This generation process utilizes a generative AI model that learns patterns from past user behavior. As a result, useful recommendations are generated for the user, such as lists of relevant facilities and activities.

[0258] Finally, the generated recommendation information is notified to the communication device, and the terminal immediately provides the user with a visual or audio notification. This allows the user to obtain useful information without any additional effort.

[0259] As a concrete example, suppose a user sends a message saying, "I'm going to see a movie on Saturday." In this case, the server analyzes this information, registers it in the calendar, and generates recommendation information, including a list of restaurants around the movie theater, and notifies the communication device. An example of a prompt message to the generating AI model in this case would be, "Please generate suggestions for related facilities based on my schedule." The introduction of this system makes it easier for users to manage their schedules, enabling them to live more efficiently in their daily lives.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The user sends text information using a communication device. The input is a message written in natural language as if it were everyday conversation. Specifically, it might be something like, "Let's go to lunch next Friday." This input itself is transmitted to the server via the communication network.

[0263] Step 2:

[0264] The server receives text information from the communication terminal. A natural language processing module within the server analyzes this text information. Specifically, it tokenizes the text information and extracts date, time, and event information. It analyzes keywords such as "next Friday" and "lunch" from the input message and outputs this as schedule information.

[0265] Step 3:

[0266] The server registers the information into the user's calendar based on the analyzed schedule information. The input for this is the schedule information extracted in step 2. The server synchronizes with the calendar management system and automatically adds "Lunch next Friday" to the calendar. As a result, a digital calendar with detailed schedule information is output.

[0267] Step 4:

[0268] The server uses historical data and the schedule information generated in step 2 to create recommendation information via a generative AI model. The input for this process is similar past schedules and related event information. The generative AI model analyzes past patterns and outputs recommendation information such as "recommended restaurants near your lunch location."

[0269] Step 5:

[0270] The server generates recommendation information and notifies the communication terminal. The user's terminal receives this information and performs the specific action of displaying the notification to the user. Visually, the user is presented with a notification such as, "There are some recommended restaurants near you for lunch." As a result, the user receives output that allows them to quickly obtain useful information.

[0271] (Application Example 1)

[0272] 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."

[0273] In modern life, managing daily tasks and schedules is a significant burden for individuals. Therefore, there is a need for information processing systems that efficiently automate these processes, improving quality of life without requiring users to manually manage schedules or plan their schedules.

[0274] 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.

[0275] In this invention, the server includes means for analyzing a message received by an information processing device from a communication terminal, means for registering schedule information in a recording medium based on the information extracted by the analyzing means, means for generating proposed content based on the schedule information, means for notifying the generated proposed content to the communication terminal, and means for the life support device to autonomously manage the user's schedule and make proposals based on the proposed content. Thereby, it becomes possible to improve the efficiency of daily life without the user performing complex operations.

[0276] The "information processing device" is a device for analyzing messages from communication terminals and extracting / processing important data.

[0277] The "communication terminal" is a digital device used by the user to send messages.

[0278] The "analyzing means" is a function for extracting date / time and event information from the received message.

[0279] The "schedule information" is information regarding the date / time and events extracted by the analyzing means.

[0280] The "recording medium" is a data storage for storing schedule information.

[0281] The "proposed content" is data generated based on the schedule information and including proposals beneficial to the user.

[0282] The "notifying means" is a method for notifying the generated proposed content to the user via the communication terminal.

[0283] The "life support device" is an autonomous digital device for supporting the user's daily life.

[0284] This invention is a system for efficiently managing and proposing schedule and task information that naturally occurs when sending messages, using the communication terminal commonly used by the user.

[0285] After receiving a message from the communication terminal, the server performs analysis using an information processing device. Specifically, it uses message analysis software (e.g., natural language processing library) to extract date and time, and event information. The analyzed information is stored in a recording medium as scheduled information. This eliminates the need for the user to manually input information.

[0286] Next, the server utilizes the extracted scheduled information to generate proposed content. The generated proposal is notified to the communication terminal, and the user can plan actions based on this. In this process, information is integrated using a calendar API (e.g., Google Calendar API), and a life support device based on the user's past behavior patterns autonomously assists in schedule management.

[0287] As a specific example, when the user sends a message saying "Meeting with friends at 3 PM tomorrow", the server proposes the necessary settings and preparations before the meeting based on this information, and notifies the recommended cafes near the meeting venue. This enables the user to process daily tasks more efficiently and improves the quality of life.

[0288] As an example of a prompt sentence for the generation AI model, there is "Please propose what preparations should be made based on the predicted weather and traffic conditions for the lunch meeting recognized tomorrow noon". This enables the user to take the optimal action from the options.

[0289] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0290] Step 1:

[0291] The server receives a message from the communication terminal. This message serves as the input. The specific operation performed here is to capture the message data from the terminal using a message reception module.

[0292] Step 2:

[0293] The server uses message analysis software to analyze the received message. The input is the message received in step 1, and here, natural language processing (NLP) techniques are used to extract date, time, and event information from the message. This analysis outputs the schedule information.

[0294] Step 3:

[0295] The server saves the analyzed schedule information to a recording medium. The input is the schedule information extracted in step 2. This information is then saved to the database, which facilitates automated schedule management.

[0296] Step 4:

[0297] The server generates suggestions using the schedule information. The schedule information saved in step 3 is used as input. In this process, the generating AI model generates various types of information that should be suggested (e.g., restaurant information around the meeting place) based on past user behavior patterns.

[0298] Step 5:

[0299] The server notifies the communication terminal of the generated proposal. The input is the proposal generated in step 4, and the output is the notification to the user's communication terminal. This operation allows the user to review the proposal and take appropriate action.

[0300] Step 6:

[0301] The user manages their schedule using the assistive device based on the suggested content they receive. The input here is the suggested content received in step 5. Specifically, the user can check their schedule and perform tasks according to the suggestions from the assistive device.

[0302] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0303] This invention provides an information processing system that analyzes messages from users, recognizes the emotions of users in addition to registering schedule information and generating proposal information, and makes more appropriate proposals. Hereinafter, embodiments of this invention will be described in detail.

[0304] The user transmits a message via the communication terminal. The message may include content reflecting emotions in addition to information regarding normal schedules. For example, this applies to cases where a conversation occurs in which the user vents to a friend about a busy weekend.

[0305] The server receives this message and passes it to the information analysis module and the emotion engine for analysis. The information analysis module extracts standard schedule information from the message, and at the same time, the emotion engine analyzes the user's emotional state. For example, there may be cases where the emotion engine recognizes that the user is feeling stressed.

[0306] When the schedule information is extracted, the server registers this information in the calendar. Based on the output of the emotion engine, the server uses means to personalize the proposal information. In particular, a list of relaxation or entertainment facilities is generated according to the user's emotion. This proposal information corresponds to the user's current emotional state and can enhance the user's satisfaction.

[0307] The proposal information and notification information transmitted from the server are received by the communication terminal. The terminal displays this, and the user selects an action based on the proposal. For example, a user feeling stressed may be notified of information about a nearby spa or relaxation facility.

[0308] The advantage of this invention is that it provides optimized suggestions while taking into account the user's emotional state. This allows users to receive more personalized and meaningful suggestions and choose appropriate actions based on their emotional state. This system is expected to reduce stress in users' lives and improve convenience.

[0309] The following describes the processing flow.

[0310] Step 1:

[0311] Users use communication devices to exchange messages with friends and colleagues. These messages may include plans, events, and their emotions at the time.

[0312] Step 2:

[0313] The server receives a message from the user. The received message is passed to the server's information analysis module and emotion engine for analysis.

[0314] Step 3:

[0315] The server's information analysis module automatically extracts schedule-related information from the message. This includes date, time, location, and event name.

[0316] Step 4:

[0317] The server's emotion engine analyzes the user's emotions from the wording and expressions within the message and identifies their emotional state.

[0318] Step 5:

[0319] Based on the schedule information extracted by the server, the event is registered in the user's calendar. A reminder notification is set when the event is registered in the calendar.

[0320] Step 6:

[0321] The server generates suggestion information appropriate to the user's emotional state, as recognized by the emotion engine. This suggestion information includes a list of facilities and activity suggestions tailored to the user's emotions.

[0322] Step 7:

[0323] The server sends the proposed information and notification information it has created to the communication terminal. The terminal receives this information and displays and notifies the user.

[0324] Step 8:

[0325] The user reviews the notified information and selects from the suggested facilities and activities. If necessary, this information is fed back to the server via the device, and it is reflected in future suggestions.

[0326] (Example 2)

[0327] 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".

[0328] Conventional information processing systems simply registered and notified users of their schedules without considering their emotional state, resulting in a poor user experience and an inability to meet individual needs. As a result, the information users received was not always useful or relaxing, and improvements are needed to better address the user's psychological state, especially when they are experiencing stress.

[0329] 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.

[0330] In this invention, the server includes means for analyzing text received by an information processing device from a communication device, means for registering schedule information on a recording medium based on the information extracted by the analysis means, and means for generating individual suggestion information using a generative AI model based on the schedule information and the user's emotional state. This makes it possible to provide personalized suggestion information that takes the user's emotional state into consideration.

[0331] An "information processing device" is a device that analyzes messages and extracts and processes the necessary information.

[0332] "Communication equipment" refers to devices used to send and receive data between an information processing device and a user.

[0333] A "text" is a natural language message sent by a user via a communication device.

[0334] "Analysis means" refers to methods and techniques for analyzing received messages and extracting necessary information.

[0335] "Schedule information" refers to data used to record and manage a user's schedule.

[0336] A "recording medium" is a storage device used to save timetable information.

[0337] "Emotional state" refers to the user's psychological state, and is an indicator used to evaluate and judge this state.

[0338] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate individual suggestions based on various pieces of information.

[0339] "Suggested information" refers to information that indicates recommended actions or options, created based on the user's needs and emotional state.

[0340] This invention is an information processing system that processes messages from users, registers schedule information, and generates and notifies users of suggestion information tailored to their emotions. The system is primarily implemented using a server, a communication terminal, and a generative AI model.

[0341] Users send messages via their everyday communication devices. These messages may include information about their usual schedules and their emotions. For example, a message expressing stress might take the form of, "This weekend is going to be really busy, I need some time to relax."

[0342] The server sends messages received from communication terminals to the analysis module and sentiment analysis engine. This allows for the analysis of information related to schedules and emotional indicators within the messages. The analysis module uses natural language processing techniques to analyze the text and extract the desired information. The sentiment analysis engine identifies the user's emotional state from the text and generates suggestions using a generative AI model based on the results. If the sentiment analysis reveals the user's stress level, appropriate suggestions are provided.

[0343] Schedule information is registered on a recording medium, and the server uses this to efficiently manage the user's schedule. Meanwhile, based on the sentiment analysis results, a generative AI model generates suggestion information using prompt sentences explained in natural language. An example of a prompt sentence is, "Please suggest relaxation facilities that would be suitable if the user is feeling stressed."

[0344] The generated suggestion information is sent to the device and notified to the user. This suggestion information is based on the user's emotional state and may include, for example, "nearby spas" or "relaxation facilities." Based on the displayed information, the user can select the necessary reservations or actions.

[0345] In this way, the present invention aims to improve the user's quality of life by providing a personalized experience that takes into account the user's emotional state.

[0346] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0347] Step 1:

[0348] The user sends a natural language message to the server via a communication device. This message may include information about their schedule and phrases indicating their feelings. A specific example is the message, "I'm stressed because I have a lot of work this weekend." The input data is this natural language message, and we proceed to the next step.

[0349] Step 2:

[0350] The server sends the received message to the analysis module. The analysis module uses natural language processing algorithms to identify and extract schedule-related information and phrases suggesting emotions from the message. The input is a message from the user, and the output is schedule information and emotion data. For example, keywords such as "weekend," "work," and "stress" may be extracted.

[0351] Step 3:

[0352] The server further analyzes the emotional data extracted from the message using an emotion analysis engine to recognize the user's emotional state. Here, the emotion analysis algorithm specifically identifies abstract emotional states. The input is the emotional data obtained in the previous step, and the output is the user's specific emotional state (e.g., stressed state).

[0353] Step 4:

[0354] The server uses a generative AI model to generate personalized suggestions based on the user's emotional state and schedule information. The prompt used is in the format, "Please suggest relaxation facilities if the user is feeling stressed." The input is the user's emotional state and the specified prompt, and the output is personalized suggestions. Specifically, a list of relaxation facilities is generated.

[0355] Step 5:

[0356] The server sends the generated suggestion information to the communication terminal and notifies the user. The input is the suggestion information obtained from the generating AI model, and the output is its display on the user interface. Based on the displayed information, the user can select actions for relaxation. For example, information on "nearby spas" or "yoga classes" may be presented on the terminal.

[0357] (Application Example 2)

[0358] 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."

[0359] In modern urban life, people need ways to cope with daily stress and emotional fluctuations. However, conventional scheduling systems have the challenge of not being able to provide personalized information that takes into account the user's emotions, and making suggestions that are appropriate to the user's psychological state.

[0360] 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.

[0361] In this invention, the server includes means for analyzing messages received by an information processing device from a communication device, means for acquiring emotional information using the information extracted by the analysis means and emotional analysis means, and for recording scheduled information, means for generating facility suggestion information based on the scheduled information and emotional information, and means for notifying the communication device of the generated facility suggestion information. This makes it possible to provide personalized suggestion information that takes into account the user's emotional state.

[0362] An "information processing device" is a device that has the function of receiving and analyzing messages.

[0363] A "communication device" is a device used to send and receive messages from users.

[0364] "Analysis means" refers to means that have processing capabilities to extract information from received messages and to understand the emotional state.

[0365] "Emotion analysis means" refers to a function that evaluates and obtains emotions from a user's message.

[0366] "Schedule information" refers to information extracted from messages and used to manage future actions and events.

[0367] "Facility suggestion information" refers to information that suggests the most suitable facilities and activities to the user based on their emotional and scheduled information.

[0368] "Means of notification" refers to the means of delivering the generated facility proposal information to the user's communication device.

[0369] This invention provides an information processing system that makes appropriate suggestions based on the emotional state of users within an urban environment. The system consists of an information processing device, a communication device, and a software program for coordinating these devices.

[0370] The server receives messages sent by users using communication devices and extracts schedule information and sentiment information from those messages through analysis and sentiment analysis means. This involves using specific software such as natural language processing libraries (e.g., Google Cloud Natural Language API) and sentiment analysis engines (e.g., Microsoft Azure Text Analytics).

[0371] Next, the server combines the extracted schedule and sentiment information to generate optimal facility recommendations for the user. This takes into account the user's current location and the available facility database to provide suitable relaxation facilities and entertainment options.

[0372] This generated facility suggestion information is transmitted to the user's communication device via a notification system. The terminal visually displays this information to the user, allowing the user to choose an action based on the suggestions. For example, if the user sends the message "I want to relax this weekend," the system will respond by suggesting nearby cafes and parks.

[0373] As a concrete example, an example of a prompt using a generative AI model is: "Extract the emotion from this user's message and suggest places that match that emotion. For example, if the user is looking to relax, list nearby cafes and parks." In this way, the present invention provides personalized information that responds to the user's emotions, thereby improving their quality of life.

[0374] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0375] Step 1:

[0376] A user uses a communication device to send a message as input. The message contains not only regular text information but also emotional content. This marks the beginning of data reception in the system.

[0377] Step 2:

[0378] The server receives a message from the user. Next, the information processing device uses a parsing mechanism with this message as input. Using a natural language processing library (e.g., Google Cloud Natural Language API), it extracts schedule information and obtains sentiment information using sentiment analysis functionality. The outputs are the extracted schedule information and sentiment information.

[0379] Step 3:

[0380] The server performs data calculations to generate facility suggestion information based on the obtained schedule and emotional information. It refers to the available facility database and filters and lists options that are appropriate for the user's current emotional state. This generates appropriate facility suggestion information.

[0381] Step 4:

[0382] The server uses a notification mechanism to send the generated facility suggestion information to the user's communication device as output. The information contains a list of facilities and services suggested to the user.

[0383] Step 5:

[0384] The terminal receives the suggestion information and displays it visually to the user. The user reviews the displayed suggestions and selects an action, such as visiting a suggested cafe. This step allows the system's suggestions to support the user's decision-making.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] [Third Embodiment]

[0389] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0390] 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.

[0391] 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).

[0392] 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.

[0393] 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.

[0394] 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).

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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".

[0401] This invention provides an information processing system for streamlining the management of daily tasks and schedules by utilizing messages transmitted by users through communication terminals. The following describes in detail the embodiments of this system.

[0402] First, users exchange messages with friends and colleagues as usual using their communication devices. These messages may include information about schedules, such as dates, times, and event details.

[0403] Upon receiving these messages, the server immediately begins analyzing them. An information analysis module built into the server understands the message content and extracts important schedule information. For example, if a message is received stating "Meeting tomorrow at 3pm," the server identifies the date, time, and event (meeting), and then registers it in the calendar.

[0404] Subsequently, the server generates helpful suggestions for the user based on the registered schedule information. This process utilizes the user's past history to create suggestion information such as a list of facilities related to the event.

[0405] The server generates suggestion and notification information, which is then sent to the communication terminal. The terminal immediately notifies the user of this information visually or audibly. For example, this could include information such as "We recommend a restaurant near the meeting."

[0406] Specifically, when a user sends a message saying "Dinner with friends this weekend," the server uses this information to generate a list of restaurants suitable for the time and place and suggests them to the user. This allows the user to choose the best option from the suggested choices and efficiently prepare for the dinner.

[0407] This system allows users to seamlessly manage tasks and schedules within messaging applications, receiving automated assistance without requiring complex operations. This is expected to significantly improve the convenience of daily life.

[0408] The following describes the processing flow.

[0409] Step 1:

[0410] Users use their communication devices to send messages to friends and colleagues. These messages may include information about appointments and events.

[0411] Step 2:

[0412] The server receives a message from the communication terminal. It passes the message to the information analysis module within the server, which then begins analyzing its contents.

[0413] Step 3:

[0414] The server's information analysis module automatically extracts information related to the event from the message. For example, it analyzes the date, time, event name, and participant information.

[0415] Step 4:

[0416] Based on the schedule information extracted by the server, a new event is registered in the user's calendar. Reminder notifications are also set during the calendar registration process.

[0417] Step 5:

[0418] The server uses the registered event information to generate relevant suggestion information for the user. This suggestion information includes a list of suitable venues for the event and recommended options.

[0419] Step 6:

[0420] The server sends suggestion and notification information to the communication terminal. The terminal receives this information and notifies the user. The notification is made via screen display or audio alert.

[0421] Step 7:

[0422] The user reviews the notification and chooses an action based on the suggested information. If necessary, they provide feedback to the server to update the information.

[0423] (Example 1)

[0424] 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."

[0425] In daily life, manually entering and managing schedules is time-consuming and prone to oversight. Furthermore, obtaining appropriate suggestions based on these schedules is not easy, hindering users' efficient actions.

[0426] 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.

[0427] In this invention, the server includes means for analyzing text information received by an information processing system from a communication device, means for registering the schedule information extracted by the analysis means into a schedule table, and means for generating recommendation information based on the schedule information and past history. This allows users to manage their schedules effortlessly and obtain relevant and useful suggestion information.

[0428] An "information processing system" is a mechanism that handles a series of processes, including receiving text information from communication devices, analyzing it, registering it, and sending notifications.

[0429] "Communication equipment" refers to devices that users use on a daily basis and that send and receive information via a network.

[0430] "Text information" refers to data containing sentences transmitted by users using communication devices, and is a message expressed in natural language.

[0431] "Analysis means" refers to technology that has the function of understanding the content of text information and extracting related planned information and patterns.

[0432] "Schedule information" refers to data used to identify and manage dates, times, and events related to a user's schedule.

[0433] A "schedule" is a digital or physical management tool where schedule information is registered.

[0434] "Recommendation information" refers to suggestion data generated based on scheduled information and past history, designed to support user behavior.

[0435] A "notification method" is a technology that communicates generated recommendation information to the user and allows them to confirm it.

[0436] This information processing system transmits text information through communication devices that users use on a daily basis, and uses that information to manage schedules and generate suggestion information. The following describes a specific embodiment of this system.

[0437] The server first receives text information transmitted from communication devices. This text information is a message written in natural language and may include schedule and event information found in everyday conversation. The server has a built-in parsing module that implements natural language processing technology and performs analysis on the received text information. The parsing module uses open-source natural language processing libraries (e.g., NLTK and spaCy).

[0438] After analysis, the server automatically registers the extracted schedule information into the user's calendar application. At this time, the calendar application is synchronized with the server, allowing the user to manually check their schedule later.

[0439] Next, the server uses historical data and analyzed schedule information to generate recommendations for the user. This generation process utilizes a generative AI model that learns patterns from past user behavior. As a result, useful recommendations are generated for the user, such as lists of relevant facilities and activities.

[0440] Finally, the generated recommendation information is notified to the communication device, and the terminal immediately provides the user with a visual or audio notification. This allows the user to obtain useful information without any additional effort.

[0441] As a concrete example, suppose a user sends a message saying, "I'm going to see a movie on Saturday." In this case, the server analyzes this information, registers it in the calendar, and generates recommendation information, including a list of restaurants around the movie theater, and notifies the communication device. An example of a prompt message to the generating AI model in this case would be, "Please generate suggestions for related facilities based on my schedule." The introduction of this system makes it easier for users to manage their schedules, enabling them to live more efficiently in their daily lives.

[0442] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0443] Step 1:

[0444] The user sends text information using a communication device. The input is a message written in natural language as if it were everyday conversation. Specifically, it might be something like, "Let's go to lunch next Friday." This input itself is transmitted to the server via the communication network.

[0445] Step 2:

[0446] The server receives text information from the communication terminal. A natural language processing module within the server analyzes this text information. Specifically, it tokenizes the text information and extracts date, time, and event information. It analyzes keywords such as "next Friday" and "lunch" from the input message and outputs this as schedule information.

[0447] Step 3:

[0448] The server registers the information into the user's calendar based on the analyzed schedule information. The input for this is the schedule information extracted in step 2. The server synchronizes with the calendar management system and automatically adds "Lunch next Friday" to the calendar. As a result, a digital calendar with detailed schedule information is output.

[0449] Step 4:

[0450] The server uses historical data and the schedule information generated in step 2 to create recommendation information via a generative AI model. The input for this process is similar past schedules and related event information. The generative AI model analyzes past patterns and outputs recommendation information such as "recommended restaurants near your lunch location."

[0451] Step 5:

[0452] The server generates recommendation information and notifies the communication terminal. The user's terminal receives this information and performs the specific action of displaying the notification to the user. Visually, the user is presented with a notification such as, "There are some recommended restaurants near you for lunch." As a result, the user receives output that allows them to quickly obtain useful information.

[0453] (Application Example 1)

[0454] 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."

[0455] In modern life, managing daily tasks and schedules is a significant burden for individuals. Therefore, there is a need for information processing systems that efficiently automate these processes, improving quality of life without requiring users to manually manage schedules or plan their schedules.

[0456] 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.

[0457] In this invention, the server includes means for analyzing messages received from a communication terminal by an information processing device, means for registering schedule information on a recording medium based on the information extracted by the analysis means, means for generating suggestion content based on the schedule information, means for notifying the communication terminal of the generated suggestion content, and means for a life support device to autonomously manage and suggest the user's schedule based on the suggestion content. This makes it possible to improve the efficiency of daily life without the user having to perform complex operations.

[0458] An "information processing device" is a device that analyzes messages from communication terminals and extracts and processes important data.

[0459] A "communication terminal" is a digital device used by a user to send messages.

[0460] "Analysis means" refers to a function that extracts date, time, and event information from received messages.

[0461] "Schedule information" refers to information about dates, times, and events extracted by the analysis method.

[0462] A "recording medium" is a data storage device used to save schedule information.

[0463] "Proposed content" refers to data generated based on scheduled information, which includes suggestions that are beneficial to the user.

[0464] "Means of notification" refers to a method of informing the user of the generated proposal content via a communication terminal.

[0465] "Life support devices" are autonomous digital devices designed to assist users in their daily lives.

[0466] This invention is a system that efficiently manages and suggests schedule and task information that naturally arises when a user sends a message using a communication terminal that the user uses on a daily basis.

[0467] After receiving a message from a communication terminal, the server performs analysis using an information processing device. Specifically, it uses message analysis software (e.g., a natural language processing library) to extract date, time, and event information. The analyzed information is saved to a recording medium as schedule information. This eliminates the need for users to manually input information.

[0468] Next, the server uses the extracted schedule information to generate suggestions. The generated suggestions are sent to the communication terminal, and the user can plan their actions based on them. In this process, information is integrated using a calendar API (e.g., Google Calendar API), and a life support device autonomously assists with schedule management based on the user's past behavior patterns.

[0469] For example, if a user sends a message saying, "I have a meeting with a friend tomorrow at 3 PM," the server uses this information to suggest necessary settings and preparations before the meeting and notifies the user of recommended cafes near the meeting place. This allows the user to handle everyday tasks more efficiently and improves their quality of life.

[0470] An example of a prompt for a generative AI model is, "Based on the expected weather and traffic conditions, please suggest what preparations I should make for the lunch meeting I've identified for tomorrow at noon." This allows the user to choose the most appropriate action from a set of options.

[0471] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0472] Step 1:

[0473] The server receives a message from the communication terminal. This message becomes the input. Specifically, the server uses a message receiving module to capture the message data from the terminal.

[0474] Step 2:

[0475] The server uses message analysis software to analyze the received message. The input is the message received in step 1, and here, natural language processing (NLP) techniques are used to extract date, time, and event information from the message. This analysis outputs the schedule information.

[0476] Step 3:

[0477] The server saves the analyzed schedule information to a recording medium. The input is the schedule information extracted in step 2. This information is then saved to the database, which facilitates automated schedule management.

[0478] Step 4:

[0479] The server generates suggestions using the schedule information. The schedule information saved in step 3 is used as input. In this process, the generating AI model generates various types of information that should be suggested (e.g., restaurant information around the meeting place) based on past user behavior patterns.

[0480] Step 5:

[0481] The server notifies the communication terminal of the generated proposal. The input is the proposal generated in step 4, and the output is the notification to the user's communication terminal. This operation allows the user to review the proposal and take appropriate action.

[0482] Step 6:

[0483] The user manages their schedule using the assistive device based on the suggested content they receive. The input here is the suggested content received in step 5. Specifically, the user can check their schedule and perform tasks according to the suggestions from the assistive device.

[0484] 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.

[0485] This invention provides an information processing system that analyzes messages from users, registers schedule information and generates suggestion information, and recognizes the user's emotions to provide more appropriate suggestions. The embodiments of this invention are described in detail below.

[0486] Users send messages via their communication devices. These messages may include not only information about their usual schedules, but also content that reflects their emotions. For example, a conversation might occur where a user complains to a friend about a busy weekend.

[0487] The server receives this message and passes it to the information analysis module and the sentiment engine for analysis. The information analysis module extracts standard schedule information from the message, while the sentiment engine analyzes the user's emotional state. For example, the sentiment engine may recognize that the user is feeling stressed.

[0488] Once the schedule information is extracted, the server registers this information in the calendar. Based on the output of the emotion engine, the server uses means to personalize the suggested information. In particular, it generates a list of relaxation or entertainment facilities according to the user's emotions. This suggested information corresponds to the user's current emotional state and can increase user satisfaction.

[0489] Suggestion and notification information sent from the server is received by the communication terminal. The terminal displays this information, and the user selects an action based on the suggestion. For example, a user experiencing stress may be notified of information about nearby spas or relaxation facilities.

[0490] The advantage of this invention is that it provides optimized suggestions while taking into account the user's emotional state. This allows users to receive more personalized and meaningful suggestions and choose appropriate actions based on their emotional state. This system is expected to reduce stress in users' lives and improve convenience.

[0491] The following describes the processing flow.

[0492] Step 1:

[0493] Users use communication devices to exchange messages with friends and colleagues. These messages may include plans, events, and their emotions at the time.

[0494] Step 2:

[0495] The server receives a message from the user. The received message is passed to the server's information analysis module and emotion engine for analysis.

[0496] Step 3:

[0497] The server's information analysis module automatically extracts schedule-related information from the message. This includes date, time, location, and event name.

[0498] Step 4:

[0499] The server's emotion engine analyzes the user's emotions from the wording and expressions within the message and identifies their emotional state.

[0500] Step 5:

[0501] Based on the schedule information extracted by the server, the event is registered in the user's calendar. A reminder notification is set when the event is registered in the calendar.

[0502] Step 6:

[0503] The server generates suggestion information appropriate to the user's emotional state, as recognized by the emotion engine. This suggestion information includes a list of facilities and activity suggestions tailored to the user's emotions.

[0504] Step 7:

[0505] The server sends the proposed information and notification information it has created to the communication terminal. The terminal receives this information and displays and notifies the user.

[0506] Step 8:

[0507] The user reviews the notified information and selects from the suggested facilities and activities. If necessary, this information is fed back to the server via the device, and it is reflected in future suggestions.

[0508] (Example 2)

[0509] 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."

[0510] Conventional information processing systems simply registered and notified users of their schedules without considering their emotional state, resulting in a poor user experience and an inability to meet individual needs. As a result, the information users received was not always useful or relaxing, and improvements are needed to better address the user's psychological state, especially when they are experiencing stress.

[0511] 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.

[0512] In this invention, the server includes means for analyzing text received by an information processing device from a communication device, means for registering schedule information on a recording medium based on the information extracted by the analysis means, and means for generating individual suggestion information using a generative AI model based on the schedule information and the user's emotional state. This makes it possible to provide personalized suggestion information that takes the user's emotional state into consideration.

[0513] An "information processing device" is a device that analyzes messages and extracts and processes the necessary information.

[0514] "Communication equipment" refers to devices used to send and receive data between an information processing device and a user.

[0515] A "text" is a natural language message sent by a user via a communication device.

[0516] "Analysis means" refers to methods and techniques for analyzing received messages and extracting necessary information.

[0517] "Schedule information" refers to data used to record and manage a user's schedule.

[0518] A "recording medium" is a storage device used to save timetable information.

[0519] "Emotional state" refers to the user's psychological state, and is an indicator used to evaluate and judge this state.

[0520] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate individual suggestions based on various pieces of information.

[0521] "Suggested information" refers to information that indicates recommended actions or options, created based on the user's needs and emotional state.

[0522] This invention is an information processing system that processes messages from users, registers schedule information, and generates and notifies users of suggestion information tailored to their emotions. The system is primarily implemented using a server, a communication terminal, and a generative AI model.

[0523] Users send messages via their everyday communication devices. These messages may include information about their usual schedules and their emotions. For example, a message expressing stress might take the form of, "This weekend is going to be really busy, I need some time to relax."

[0524] The server sends messages received from communication terminals to the analysis module and sentiment analysis engine. This allows for the analysis of information related to schedules and emotional indicators within the messages. The analysis module uses natural language processing techniques to analyze the text and extract the desired information. The sentiment analysis engine identifies the user's emotional state from the text and generates suggestions using a generative AI model based on the results. If the sentiment analysis reveals the user's stress level, appropriate suggestions are provided.

[0525] Schedule information is registered on a recording medium, and the server uses this to efficiently manage the user's schedule. Meanwhile, based on the sentiment analysis results, a generative AI model generates suggestion information using prompt sentences explained in natural language. An example of a prompt sentence is, "Please suggest relaxation facilities that would be suitable if the user is feeling stressed."

[0526] The generated suggestion information is sent to the device and notified to the user. This suggestion information is based on the user's emotional state and may include, for example, "nearby spas" or "relaxation facilities." Based on the displayed information, the user can select the necessary reservations or actions.

[0527] In this way, the present invention aims to improve the user's quality of life by providing a personalized experience that takes into account the user's emotional state.

[0528] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0529] Step 1:

[0530] The user sends a natural language message to the server via a communication device. This message may include information about their schedule and phrases indicating their feelings. A specific example is the message, "I'm stressed because I have a lot of work this weekend." The input data is this natural language message, and we proceed to the next step.

[0531] Step 2:

[0532] The server sends the received message to the analysis module. The analysis module uses natural language processing algorithms to identify and extract schedule-related information and phrases suggesting emotions from the message. The input is a message from the user, and the output is schedule information and emotion data. For example, keywords such as "weekend," "work," and "stress" may be extracted.

[0533] Step 3:

[0534] The server further analyzes the emotional data extracted from the message using an emotion analysis engine to recognize the user's emotional state. Here, the emotion analysis algorithm specifically identifies abstract emotional states. The input is the emotional data obtained in the previous step, and the output is the user's specific emotional state (e.g., stressed state).

[0535] Step 4:

[0536] The server uses a generative AI model to generate personalized suggestions based on the user's emotional state and schedule information. The prompt used is in the format, "Please suggest relaxation facilities if the user is feeling stressed." The input is the user's emotional state and the specified prompt, and the output is personalized suggestions. Specifically, a list of relaxation facilities is generated.

[0537] Step 5:

[0538] The server sends the generated suggestion information to the communication terminal and notifies the user. The input is the suggestion information obtained from the generating AI model, and the output is its display on the user interface. Based on the displayed information, the user can select actions for relaxation. For example, information on "nearby spas" or "yoga classes" may be presented on the terminal.

[0539] (Application Example 2)

[0540] 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."

[0541] In modern urban life, people need ways to cope with daily stress and emotional fluctuations. However, conventional scheduling systems have the challenge of not being able to provide personalized information that takes into account the user's emotions, and making suggestions that are appropriate to the user's psychological state.

[0542] 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.

[0543] In this invention, the server includes means for analyzing messages received by an information processing device from a communication device, means for acquiring emotional information using the information extracted by the analysis means and emotional analysis means, and for recording scheduled information, means for generating facility suggestion information based on the scheduled information and emotional information, and means for notifying the communication device of the generated facility suggestion information. This makes it possible to provide personalized suggestion information that takes into account the user's emotional state.

[0544] An "information processing device" is a device that has the function of receiving and analyzing messages.

[0545] A "communication device" is a device used to send and receive messages from users.

[0546] "Analysis means" refers to means that have processing capabilities to extract information from received messages and to understand the emotional state.

[0547] "Emotion analysis means" refers to a function that evaluates and obtains emotions from a user's message.

[0548] "Schedule information" refers to information extracted from messages and used to manage future actions and events.

[0549] "Facility suggestion information" refers to information that suggests the most suitable facilities and activities to the user based on their emotional and scheduled information.

[0550] "Means of notification" refers to the means of delivering the generated facility proposal information to the user's communication device.

[0551] This invention provides an information processing system that makes appropriate suggestions based on the emotional state of users within an urban environment. The system consists of an information processing device, a communication device, and a software program for coordinating these devices.

[0552] The server receives messages sent by users using communication devices and extracts schedule information and sentiment information from those messages through analysis and sentiment analysis means. This involves using specific software such as natural language processing libraries (e.g., Google Cloud Natural Language API) and sentiment analysis engines (e.g., Microsoft Azure Text Analytics).

[0553] Next, the server combines the extracted schedule and sentiment information to generate optimal facility recommendations for the user. This takes into account the user's current location and the available facility database to provide suitable relaxation facilities and entertainment options.

[0554] This generated facility suggestion information is transmitted to the user's communication device via a notification system. The terminal visually displays this information to the user, allowing the user to choose an action based on the suggestions. For example, if the user sends the message "I want to relax this weekend," the system will respond by suggesting nearby cafes and parks.

[0555] As a concrete example, an example of a prompt using a generative AI model is: "Extract the emotion from this user's message and suggest places that match that emotion. For example, if the user is looking to relax, list nearby cafes and parks." In this way, the present invention provides personalized information that responds to the user's emotions, thereby improving their quality of life.

[0556] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0557] Step 1:

[0558] A user uses a communication device to send a message as input. The message contains not only regular text information but also emotional content. This marks the beginning of data reception in the system.

[0559] Step 2:

[0560] The server receives a message from the user. Next, the information processing device uses a parsing mechanism with this message as input. Using a natural language processing library (e.g., Google Cloud Natural Language API), it extracts schedule information and obtains sentiment information using sentiment analysis functionality. The outputs are the extracted schedule information and sentiment information.

[0561] Step 3:

[0562] The server performs data calculations to generate facility suggestion information based on the obtained schedule and emotional information. It refers to the available facility database and filters and lists options that are appropriate for the user's current emotional state. This generates appropriate facility suggestion information.

[0563] Step 4:

[0564] The server uses a notification mechanism to send the generated facility suggestion information to the user's communication device as output. The information contains a list of facilities and services suggested to the user.

[0565] Step 5:

[0566] The terminal receives the suggestion information and displays it visually to the user. The user reviews the displayed suggestions and selects an action, such as visiting a suggested cafe. This step allows the system's suggestions to support the user's decision-making.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] [Fourth Embodiment]

[0571] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0572] 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.

[0573] 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).

[0574] 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.

[0575] 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.

[0576] 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).

[0577] 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.

[0578] 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.

[0579] 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.

[0580] 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.

[0581] 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.

[0582] 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.

[0583] 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".

[0584] This invention provides an information processing system for streamlining the management of daily tasks and schedules by utilizing messages transmitted by users through communication terminals. The following describes in detail the embodiments of this system.

[0585] First, users exchange messages with friends and colleagues as usual using their communication devices. These messages may include information about schedules, such as dates, times, and event details.

[0586] Upon receiving these messages, the server immediately begins analyzing them. An information analysis module built into the server understands the message content and extracts important schedule information. For example, if a message is received stating "Meeting tomorrow at 3pm," the server identifies the date, time, and event (meeting), and then registers it in the calendar.

[0587] Subsequently, the server generates helpful suggestions for the user based on the registered schedule information. This process utilizes the user's past history to create suggestion information such as a list of facilities related to the event.

[0588] The server generates suggestion and notification information, which is then sent to the communication terminal. The terminal immediately notifies the user of this information visually or audibly. For example, this could include information such as "We recommend a restaurant near the meeting."

[0589] Specifically, when a user sends a message saying "Dinner with friends this weekend," the server uses this information to generate a list of restaurants suitable for the time and place and suggests them to the user. This allows the user to choose the best option from the suggested choices and efficiently prepare for the dinner.

[0590] This system allows users to seamlessly manage tasks and schedules within messaging applications, receiving automated assistance without requiring complex operations. This is expected to significantly improve the convenience of daily life.

[0591] The following describes the processing flow.

[0592] Step 1:

[0593] Users use their communication devices to send messages to friends and colleagues. These messages may include information about appointments and events.

[0594] Step 2:

[0595] The server receives a message from the communication terminal. It passes the message to the information analysis module within the server, which then begins analyzing its contents.

[0596] Step 3:

[0597] The server's information analysis module automatically extracts information related to the event from the message. For example, it analyzes the date, time, event name, and participant information.

[0598] Step 4:

[0599] Based on the schedule information extracted by the server, a new event is registered in the user's calendar. Reminder notifications are also set during the calendar registration process.

[0600] Step 5:

[0601] The server uses the registered event information to generate relevant suggestion information for the user. This suggestion information includes a list of suitable venues for the event and recommended options.

[0602] Step 6:

[0603] The server sends suggestion and notification information to the communication terminal. The terminal receives this information and notifies the user. The notification is made via screen display or audio alert.

[0604] Step 7:

[0605] The user reviews the notification and chooses an action based on the suggested information. If necessary, they provide feedback to the server to update the information.

[0606] (Example 1)

[0607] 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".

[0608] In daily life, manually entering and managing schedules is time-consuming and prone to oversight. Furthermore, obtaining appropriate suggestions based on these schedules is not easy, hindering users' efficient actions.

[0609] 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.

[0610] In this invention, the server includes means for analyzing text information received by an information processing system from a communication device, means for registering the schedule information extracted by the analysis means into a schedule table, and means for generating recommendation information based on the schedule information and past history. This allows users to manage their schedules effortlessly and obtain relevant and useful suggestion information.

[0611] An "information processing system" is a mechanism that handles a series of processes, including receiving text information from communication devices, analyzing it, registering it, and sending notifications.

[0612] "Communication equipment" refers to devices that users use on a daily basis and that send and receive information via a network.

[0613] "Text information" refers to data containing sentences transmitted by users using communication devices, and is a message expressed in natural language.

[0614] "Analysis means" refers to technology that has the function of understanding the content of text information and extracting related planned information and patterns.

[0615] "Schedule information" refers to data used to identify and manage dates, times, and events related to a user's schedule.

[0616] A "schedule" is a digital or physical management tool where schedule information is registered.

[0617] "Recommendation information" refers to suggestion data generated based on scheduled information and past history, designed to support user behavior.

[0618] A "notification method" is a technology that communicates generated recommendation information to the user and allows them to confirm it.

[0619] This information processing system transmits text information through communication devices that users use on a daily basis, and uses that information to manage schedules and generate suggestion information. The following describes a specific embodiment of this system.

[0620] The server first receives text information transmitted from communication devices. This text information is a message written in natural language and may include schedule and event information found in everyday conversation. The server has a built-in parsing module that implements natural language processing technology and performs analysis on the received text information. The parsing module uses open-source natural language processing libraries (e.g., NLTK and spaCy).

[0621] After analysis, the server automatically registers the extracted schedule information into the user's calendar application. At this time, the calendar application is synchronized with the server, allowing the user to manually check their schedule later.

[0622] Next, the server uses historical data and analyzed schedule information to generate recommendations for the user. This generation process utilizes a generative AI model that learns patterns from past user behavior. As a result, useful recommendations are generated for the user, such as lists of relevant facilities and activities.

[0623] Finally, the generated recommendation information is notified to the communication device, and the terminal immediately provides the user with a visual or audio notification. This allows the user to obtain useful information without any additional effort.

[0624] As a concrete example, suppose a user sends a message saying, "I'm going to see a movie on Saturday." In this case, the server analyzes this information, registers it in the calendar, and generates recommendation information, including a list of restaurants around the movie theater, and notifies the communication device. An example of a prompt message to the generating AI model in this case would be, "Please generate suggestions for related facilities based on my schedule." The introduction of this system makes it easier for users to manage their schedules, enabling them to live more efficiently in their daily lives.

[0625] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0626] Step 1:

[0627] The user sends text information using a communication device. The input is a message written in natural language as if it were everyday conversation. Specifically, it might be something like, "Let's go to lunch next Friday." This input itself is transmitted to the server via the communication network.

[0628] Step 2:

[0629] The server receives text information from the communication terminal. A natural language processing module within the server analyzes this text information. Specifically, it tokenizes the text information and extracts date, time, and event information. It analyzes keywords such as "next Friday" and "lunch" from the input message and outputs this as schedule information.

[0630] Step 3:

[0631] The server registers the information into the user's calendar based on the analyzed schedule information. The input for this is the schedule information extracted in step 2. The server synchronizes with the calendar management system and automatically adds "Lunch next Friday" to the calendar. As a result, a digital calendar with detailed schedule information is output.

[0632] Step 4:

[0633] The server uses historical data and the schedule information generated in step 2 to create recommendation information via a generative AI model. The input for this process is similar past schedules and related event information. The generative AI model analyzes past patterns and outputs recommendation information such as "recommended restaurants near your lunch location."

[0634] Step 5:

[0635] The server generates recommendation information and notifies the communication terminal. The user's terminal receives this information and performs the specific action of displaying the notification to the user. Visually, the user is presented with a notification such as, "There are some recommended restaurants near you for lunch." As a result, the user receives output that allows them to quickly obtain useful information.

[0636] (Application Example 1)

[0637] 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".

[0638] In modern life, managing daily tasks and schedules is a significant burden for individuals. Therefore, there is a need for information processing systems that efficiently automate these processes, improving quality of life without requiring users to manually manage schedules or plan their schedules.

[0639] 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.

[0640] In this invention, the server includes means for analyzing messages received from a communication terminal by an information processing device, means for registering schedule information on a recording medium based on the information extracted by the analysis means, means for generating suggestion content based on the schedule information, means for notifying the communication terminal of the generated suggestion content, and means for a life support device to autonomously manage and suggest the user's schedule based on the suggestion content. This makes it possible to improve the efficiency of daily life without the user having to perform complex operations.

[0641] An "information processing device" is a device that analyzes messages from communication terminals and extracts and processes important data.

[0642] A "communication terminal" is a digital device used by a user to send messages.

[0643] "Analysis means" refers to a function that extracts date, time, and event information from received messages.

[0644] "Schedule information" refers to information about dates, times, and events extracted by the analysis method.

[0645] A "recording medium" is a data storage device used to save schedule information.

[0646] "Proposed content" refers to data generated based on scheduled information, which includes suggestions that are beneficial to the user.

[0647] "Means of notification" refers to a method of informing the user of the generated proposal content via a communication terminal.

[0648] "Life support devices" are autonomous digital devices designed to assist users in their daily lives.

[0649] This invention is a system that efficiently manages and suggests schedule and task information that naturally arises when a user sends a message using a communication terminal that the user uses on a daily basis.

[0650] After receiving a message from a communication terminal, the server performs analysis using an information processing device. Specifically, it uses message analysis software (e.g., a natural language processing library) to extract date, time, and event information. The analyzed information is saved to a recording medium as schedule information. This eliminates the need for users to manually input information.

[0651] Next, the server uses the extracted schedule information to generate suggestions. The generated suggestions are sent to the communication terminal, and the user can plan their actions based on them. In this process, information is integrated using a calendar API (e.g., Google Calendar API), and a life support device autonomously assists with schedule management based on the user's past behavior patterns.

[0652] For example, if a user sends a message saying, "I have a meeting with a friend tomorrow at 3 PM," the server uses this information to suggest necessary settings and preparations before the meeting and notifies the user of recommended cafes near the meeting place. This allows the user to handle everyday tasks more efficiently and improves their quality of life.

[0653] An example of a prompt for a generative AI model is, "Based on the expected weather and traffic conditions, please suggest what preparations I should make for the lunch meeting I've identified for tomorrow at noon." This allows the user to choose the most appropriate action from a set of options.

[0654] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0655] Step 1:

[0656] The server receives a message from the communication terminal. This message becomes the input. Specifically, the server uses a message receiving module to capture the message data from the terminal.

[0657] Step 2:

[0658] The server uses message analysis software to analyze the received message. The input is the message received in step 1, and here, natural language processing (NLP) techniques are used to extract date, time, and event information from the message. This analysis outputs the schedule information.

[0659] Step 3:

[0660] The server saves the analyzed schedule information to a recording medium. The input is the schedule information extracted in step 2. This information is then saved to the database, which facilitates automated schedule management.

[0661] Step 4:

[0662] The server generates suggestions using the schedule information. The schedule information saved in step 3 is used as input. In this process, the generating AI model generates various types of information that should be suggested (e.g., restaurant information around the meeting place) based on past user behavior patterns.

[0663] Step 5:

[0664] The server notifies the communication terminal of the generated proposal. The input is the proposal generated in step 4, and the output is the notification to the user's communication terminal. This operation allows the user to review the proposal and take appropriate action.

[0665] Step 6:

[0666] The user manages their schedule using the assistive device based on the suggested content they receive. The input here is the suggested content received in step 5. Specifically, the user can check their schedule and perform tasks according to the suggestions from the assistive device.

[0667] 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.

[0668] This invention provides an information processing system that analyzes messages from users, registers schedule information and generates suggestion information, and recognizes the user's emotions to provide more appropriate suggestions. The embodiments of this invention are described in detail below.

[0669] Users send messages via their communication devices. These messages may include not only information about their usual schedules, but also content that reflects their emotions. For example, a conversation might occur where a user complains to a friend about a busy weekend.

[0670] The server receives this message and passes it to the information analysis module and the sentiment engine for analysis. The information analysis module extracts standard schedule information from the message, while the sentiment engine analyzes the user's emotional state. For example, the sentiment engine may recognize that the user is feeling stressed.

[0671] Once the schedule information is extracted, the server registers this information in the calendar. Based on the output of the emotion engine, the server uses means to personalize the suggested information. In particular, it generates a list of relaxation or entertainment facilities according to the user's emotions. This suggested information corresponds to the user's current emotional state and can increase user satisfaction.

[0672] Suggestion and notification information sent from the server is received by the communication terminal. The terminal displays this information, and the user selects an action based on the suggestion. For example, a user experiencing stress may be notified of information about nearby spas or relaxation facilities.

[0673] The advantage of this invention is that it provides optimized suggestions while taking into account the user's emotional state. This allows users to receive more personalized and meaningful suggestions and choose appropriate actions based on their emotional state. This system is expected to reduce stress in users' lives and improve convenience.

[0674] The following describes the processing flow.

[0675] Step 1:

[0676] Users use communication devices to exchange messages with friends and colleagues. These messages may include plans, events, and their emotions at the time.

[0677] Step 2:

[0678] The server receives a message from the user. The received message is passed to the server's information analysis module and emotion engine for analysis.

[0679] Step 3:

[0680] The server's information analysis module automatically extracts schedule-related information from the message. This includes date, time, location, and event name.

[0681] Step 4:

[0682] The server's emotion engine analyzes the user's emotions from the wording and expressions within the message and identifies their emotional state.

[0683] Step 5:

[0684] Based on the schedule information extracted by the server, the event is registered in the user's calendar. A reminder notification is set when the event is registered in the calendar.

[0685] Step 6:

[0686] The server generates suggestion information appropriate to the user's emotional state, as recognized by the emotion engine. This suggestion information includes a list of facilities and activity suggestions tailored to the user's emotions.

[0687] Step 7:

[0688] The server sends the proposed information and notification information it has created to the communication terminal. The terminal receives this information and displays and notifies the user.

[0689] Step 8:

[0690] The user reviews the notified information and selects from the suggested facilities and activities. If necessary, this information is fed back to the server via the device, and it is reflected in future suggestions.

[0691] (Example 2)

[0692] 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".

[0693] Conventional information processing systems simply registered and notified users of their schedules without considering their emotional state, resulting in a poor user experience and an inability to meet individual needs. As a result, the information users received was not always useful or relaxing, and improvements are needed to better address the user's psychological state, especially when they are experiencing stress.

[0694] 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.

[0695] In this invention, the server includes means for analyzing text received by an information processing device from a communication device, means for registering schedule information on a recording medium based on the information extracted by the analysis means, and means for generating individual suggestion information using a generative AI model based on the schedule information and the user's emotional state. This makes it possible to provide personalized suggestion information that takes the user's emotional state into consideration.

[0696] An "information processing device" is a device that analyzes messages and extracts and processes the necessary information.

[0697] "Communication equipment" refers to devices used to send and receive data between an information processing device and a user.

[0698] A "text" is a natural language message sent by a user via a communication device.

[0699] "Analysis means" refers to methods and techniques for analyzing received messages and extracting necessary information.

[0700] "Schedule information" refers to data used to record and manage a user's schedule.

[0701] A "recording medium" is a storage device used to save timetable information.

[0702] "Emotional state" refers to the user's psychological state, and is an indicator used to evaluate and judge this state.

[0703] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate individual suggestions based on various pieces of information.

[0704] "Suggested information" refers to information that indicates recommended actions or options, created based on the user's needs and emotional state.

[0705] This invention is an information processing system that processes messages from users, registers schedule information, and generates and notifies users of suggestion information tailored to their emotions. The system is primarily implemented using a server, a communication terminal, and a generative AI model.

[0706] Users send messages via their everyday communication devices. These messages may include information about their usual schedules and their emotions. For example, a message expressing stress might take the form of, "This weekend is going to be really busy, I need some time to relax."

[0707] The server sends messages received from communication terminals to the analysis module and sentiment analysis engine. This allows for the analysis of information related to schedules and emotional indicators within the messages. The analysis module uses natural language processing techniques to analyze the text and extract the desired information. The sentiment analysis engine identifies the user's emotional state from the text and generates suggestions using a generative AI model based on the results. If the sentiment analysis reveals the user's stress level, appropriate suggestions are provided.

[0708] Schedule information is registered on a recording medium, and the server uses this to efficiently manage the user's schedule. Meanwhile, based on the sentiment analysis results, a generative AI model generates suggestion information using prompt sentences explained in natural language. An example of a prompt sentence is, "Please suggest relaxation facilities that would be suitable if the user is feeling stressed."

[0709] The generated suggestion information is sent to the device and notified to the user. This suggestion information is based on the user's emotional state and may include, for example, "nearby spas" or "relaxation facilities." Based on the displayed information, the user can select the necessary reservations or actions.

[0710] In this way, the present invention aims to improve the user's quality of life by providing a personalized experience that takes into account the user's emotional state.

[0711] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0712] Step 1:

[0713] The user sends a natural language message to the server via a communication device. This message may include information about their schedule and phrases indicating their feelings. A specific example is the message, "I'm stressed because I have a lot of work this weekend." The input data is this natural language message, and we proceed to the next step.

[0714] Step 2:

[0715] The server sends the received message to the analysis module. The analysis module uses natural language processing algorithms to identify and extract schedule-related information and phrases suggesting emotions from the message. The input is a message from the user, and the output is schedule information and emotion data. For example, keywords such as "weekend," "work," and "stress" may be extracted.

[0716] Step 3:

[0717] The server further analyzes the emotional data extracted from the message using an emotion analysis engine to recognize the user's emotional state. Here, the emotion analysis algorithm specifically identifies abstract emotional states. The input is the emotional data obtained in the previous step, and the output is the user's specific emotional state (e.g., stressed state).

[0718] Step 4:

[0719] The server uses a generative AI model to generate personalized suggestions based on the user's emotional state and schedule information. The prompt used is in the format, "Please suggest relaxation facilities if the user is feeling stressed." The input is the user's emotional state and the specified prompt, and the output is personalized suggestions. Specifically, a list of relaxation facilities is generated.

[0720] Step 5:

[0721] The server sends the generated suggestion information to the communication terminal and notifies the user. The input is the suggestion information obtained from the generating AI model, and the output is its display on the user interface. Based on the displayed information, the user can select actions for relaxation. For example, information on "nearby spas" or "yoga classes" may be presented on the terminal.

[0722] (Application Example 2)

[0723] 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".

[0724] In modern urban life, people need ways to cope with daily stress and emotional fluctuations. However, conventional scheduling systems have the challenge of not being able to provide personalized information that takes into account the user's emotions, and making suggestions that are appropriate to the user's psychological state.

[0725] 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.

[0726] In this invention, the server includes means for analyzing messages received by an information processing device from a communication device, means for acquiring emotional information using the information extracted by the analysis means and emotional analysis means, and for recording scheduled information, means for generating facility suggestion information based on the scheduled information and emotional information, and means for notifying the communication device of the generated facility suggestion information. This makes it possible to provide personalized suggestion information that takes into account the user's emotional state.

[0727] An "information processing device" is a device that has the function of receiving and analyzing messages.

[0728] A "communication device" is a device used to send and receive messages from users.

[0729] "Analysis means" refers to means that have processing capabilities to extract information from received messages and to understand the emotional state.

[0730] "Emotion analysis means" refers to a function that evaluates and obtains emotions from a user's message.

[0731] "Schedule information" refers to information extracted from messages and used to manage future actions and events.

[0732] "Facility suggestion information" refers to information that suggests the most suitable facilities and activities to the user based on their emotional and scheduled information.

[0733] "Means of notification" refers to the means of delivering the generated facility proposal information to the user's communication device.

[0734] This invention provides an information processing system that makes appropriate suggestions based on the emotional state of users within an urban environment. The system consists of an information processing device, a communication device, and a software program for coordinating these devices.

[0735] The server receives messages sent by users using communication devices and extracts schedule information and sentiment information from those messages through analysis and sentiment analysis means. This involves using specific software such as natural language processing libraries (e.g., Google Cloud Natural Language API) and sentiment analysis engines (e.g., Microsoft Azure Text Analytics).

[0736] Next, the server combines the extracted schedule and sentiment information to generate optimal facility recommendations for the user. This takes into account the user's current location and the available facility database to provide suitable relaxation facilities and entertainment options.

[0737] This generated facility suggestion information is transmitted to the user's communication device via a notification system. The terminal visually displays this information to the user, allowing the user to choose an action based on the suggestions. For example, if the user sends the message "I want to relax this weekend," the system will respond by suggesting nearby cafes and parks.

[0738] As a concrete example, an example of a prompt using a generative AI model is: "Extract the emotion from this user's message and suggest places that match that emotion. For example, if the user is looking to relax, list nearby cafes and parks." In this way, the present invention provides personalized information that responds to the user's emotions, thereby improving their quality of life.

[0739] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0740] Step 1:

[0741] A user uses a communication device to send a message as input. The message contains not only regular text information but also emotional content. This marks the beginning of data reception in the system.

[0742] Step 2:

[0743] The server receives a message from the user. Next, the information processing device uses a parsing mechanism with this message as input. Using a natural language processing library (e.g., Google Cloud Natural Language API), it extracts schedule information and obtains sentiment information using sentiment analysis functionality. The outputs are the extracted schedule information and sentiment information.

[0744] Step 3:

[0745] The server performs data calculations to generate facility suggestion information based on the obtained schedule and emotional information. It refers to the available facility database and filters and lists options that are appropriate for the user's current emotional state. This generates appropriate facility suggestion information.

[0746] Step 4:

[0747] The server uses a notification mechanism to send the generated facility suggestion information to the user's communication device as output. The information contains a list of facilities and services suggested to the user.

[0748] Step 5:

[0749] The terminal receives the suggestion information and displays it visually to the user. The user reviews the displayed suggestions and selects an action, such as visiting a suggested cafe. This step allows the system's suggestions to support the user's decision-making.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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."

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0771] The following is further disclosed regarding the embodiments described above.

[0772] (Claim 1)

[0773] A means for an information processing device to analyze a message received from a communication terminal,

[0774] A means for registering schedule information in a calendar based on the information extracted by the aforementioned analysis means,

[0775] A means for generating proposed information based on the aforementioned scheduled information,

[0776] Means for notifying a communication terminal of the generated proposal information,

[0777] A system that includes this.

[0778] (Claim 2)

[0779] The system according to claim 1, wherein the proposed information includes a list of facilities related to the event.

[0780] (Claim 3)

[0781] The system according to claim 1, wherein the analysis means includes means for extracting patterns from messages based on past historical information.

[0782] "Example 1"

[0783] (Claim 1)

[0784] A means for an information processing system to analyze text information received from a communication device,

[0785] A means for registering the schedule information extracted by the aforementioned analysis means into a schedule table,

[0786] A means for generating recommendation information based on the aforementioned schedule information and past history,

[0787] A means for notifying a communication device of the generated recommendation information,

[0788] A system that includes this.

[0789] (Claim 2)

[0790] The system according to claim 1, wherein the recommendation information includes a list of locations related to the event.

[0791] (Claim 3)

[0792] The system according to claim 1, wherein the analysis means includes means for extracting patterns from text information based on past history.

[0793] "Application Example 1"

[0794] (Claim 1)

[0795] A means for an information processing device to analyze a message received from a communication terminal,

[0796] A means for registering scheduled information on a recording medium based on the information extracted by the aforementioned analysis means,

[0797] A means for generating proposal content based on the aforementioned schedule information,

[0798] Means for notifying a communication terminal of the generated proposal content,

[0799] Based on the above proposal, a means by which a life support device autonomously manages and makes suggestions for the user's schedule,

[0800] A system that includes this.

[0801] (Claim 2)

[0802] The system according to claim 1, wherein the proposed content includes a list of locations related to the activity.

[0803] (Claim 3)

[0804] The system according to claim 1, wherein the analysis means includes means for extracting regularities from messages based on past historical information.

[0805] "Example 2 of combining an emotion engine"

[0806] (Claim 1)

[0807] A means for an information processing device to analyze a sentence received from a communication device,

[0808] A means for registering timetable information in a recording medium based on the information extracted by the aforementioned analysis means,

[0809] A means for generating individual suggestion information using a generative AI model based on the aforementioned timetable information and the user's emotional state,

[0810] Means for notifying a communication device of the generated proposal information,

[0811] A system that includes this.

[0812] (Claim 2)

[0813] The system according to claim 1, wherein the proposed information includes items related to entertainment facilities.

[0814] (Claim 3)

[0815] The system according to claim 1, wherein the analysis means includes means for extracting sentiment patterns from sentences based on past historical information and language data, and optimizing suggestions.

[0816] "Application example 2 when combining with an emotional engine"

[0817] (Claim 1)

[0818] A means for an information processing device to analyze a message received from a communication device,

[0819] A means for acquiring emotional information using the information extracted by the aforementioned analysis means and the emotional analysis means, and for recording planned information,

[0820] A means for generating facility proposal information based on the aforementioned schedule information and sentiment information,

[0821] Means for notifying a communication device of the generated facility proposal information,

[0822] A system that includes this.

[0823] (Claim 2)

[0824] The system according to claim 1, wherein the proposed facility information includes a list of items related to facilities within a city.

[0825] (Claim 3)

[0826] The system according to claim 1, wherein the analysis means includes means for extracting formulas from messages based on past historical information, and further includes sentiment analysis means. [Explanation of Symbols]

[0827] 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 for an information processing device to analyze a message received from a communication terminal, A means for registering schedule information in a calendar based on the information extracted by the aforementioned analysis means, A means for generating proposed information based on the aforementioned scheduled information, Means for notifying a communication terminal of the generated proposal information, A system that includes this.

2. The system according to claim 1, wherein the proposed information includes a list of facilities related to the event.

3. The system according to claim 1, wherein the analysis means includes means for extracting patterns from messages based on past historical information.

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