system

Abstract

Provide a system. [Solution] a means for users to create their own avatar; a means for the user to configure the tone and wording of the notification text; A means for users to customize notification settings for each application; a server means for receiving notifications from each application; A means for the server to filter notifications based on user settings and cut out unnecessary notifications; A means for the AI ​​to generate text tailored to the user's preferences for the required notifications; a server means for transmitting the generated notification text to a user's terminal; The user's device will display the notification text. A system including:

Description

[Technical Field]

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

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

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

[0004] In modern society, smartphones and other mobile devices are equipped with a wide variety of applications, but notifications from these applications can become excessive, causing annoyances for users. Users must manually distinguish between necessary and unnecessary notifications, which leads to notification fatigue. Furthermore, the content and presentation of notifications often do not match users' preferences, reducing their effectiveness. To address these issues, a system is needed that automatically filters notifications and provides notifications customized to users' preferences. [Means for solving the problem]

[0005] The present invention provides a means for users to create their own avatar and set the tone and expression of notification text. This allows users to create a notification environment that suits their preferences. Furthermore, it provides a means for users to customize notification settings for each application. Notifications from each application are centrally aggregated by a server, which then filters them based on the user's settings and cuts out unnecessary notifications. For necessary notifications, a generation AI generates text tailored to the user's preferences, and the server sends the generated notification text to the user's device. Finally, it provides a means for the user's device to display the notification text, particularly using an avatar. This allows users to effectively receive only the information they need, without stress.

[0006] An "avatar" is a character created by a user to virtually represent themselves.

[0007] A "notification" is information sent from an application to a user.

[0008] "Generative AI" is a technology that uses artificial intelligence to generate sentences tailored to the user's preferences.

[0009] "Filtering" is the process of separating wanted information from unwanted information based on specific criteria.

[0010] A "server" is a computer system that manages information on a network and aggregates and processes notifications from applications.

[0011] "Device" refers to a smartphone, tablet, or other mobile device used by a user.

[0012] "Customization" refers to adjusting settings and content to meet a user's individual needs and preferences.

[0013] "Notification settings" are settings that determine the types and conditions of notifications that a user wants to receive.

[0014] The "notification text" is text that conveys the content of the notification to the user. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] User Preferences

[0037] 1. Create an avatar

[0038] Users install a specific application on their smartphone, tablet, or other device. When they open the application, they are guided to a screen where they can create their own avatar. Here, they can freely customize their character's appearance, clothing, and other aspects.

[0039] 2. Setting up the generated AI

[0040] The user is then taken to a screen where they can set the tone and expression of the notification text to the AI ​​generator. Here, they can set the style of the notification (e.g., casual, formal, humorous, etc.) and the type of emojis and emoticons to use.

[0041] 3. Notification filtering settings

[0042] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This setting information is stored on the server.

[0043] Sending and filtering notifications

[0044] 4. Notification Occurrence

[0045] Each application (e.g., news app, SNS app, etc.) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[0046] 5. Receiving and filtering notifications

[0047] The server receives notification data sent from the application. The received notification data is evaluated based on the filter settings for each user. The server cuts out notifications that the user deems unnecessary and selects only important notifications. This filtering process leaves only the notification information that is valuable to the user.

[0048] 6. Notification Text Generation

[0049] For notifications that pass the filter, the AI ​​generates notification text that matches the user's preferences. For example, if the user has selected a casual style, the AI ​​generates a text such as "⚽New sports news!"

[0050] Notification presentation

[0051] 7. Sending Notifications

[0052] The server sends the generated notification text and necessary metadata (such as the user's avatar information) to the user's device.

[0053] 8. Display of notifications

[0054] The user's device receives the notification data sent from the server. The device displays the notification using the user's avatar along with the notification text. For example, if the user is using the Zepeto app, the avatar displays a notification saying "⚽New sports news!"

[0055] Specific examples

[0056] User configuration example

[0057] User name: Sato-san

[0058] Avatar Creation: Sato created a casually dressed character as his avatar.

[0059] Generator AI settings: Sato set the tone of notifications to a casual style and specified that emojis be used frequently.

[0060] Notification filter settings: Sato set his news app to receive "only sports-related notifications" and his social media app to receive "all notifications."

[0061] Notification processing example

[0062] Notification occurs: The news app generates "sports-related news" and sends it to the server.

[0063] Receiving and filtering notifications: The server receives the notification data and determines that "sports related news" is the notification that needs to be sent.

[0064] Notification text generation: The AI ​​generates casual notification text such as "⚽There's new sports news!"

[0065] Sending notification: The server sends the generated notification text and avatar information to Mr. Sato's device.

[0066] Displaying the notification: Sato's device receives a notification and his avatar displays "⚽New sports news!"

[0067] This embodiment frees users from annoying notifications and allows them to receive valuable information tailored to their preferences without stress.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] User: Install the application on the device and enter the avatar creation screen. Freely set the avatar's appearance, clothing, hairstyle, etc. Once complete, save the avatar information.

[0071] Step 2:

[0072] User: Go to the AI ​​generation settings screen and customize the tone and expression of the notification text. For example, choose a casual tone and a preference for using lots of emojis. This setting is saved on the server.

[0073] Step 3:

[0074] User: Go to the notification filtering settings screen for each application. Here, for example, you can set a news app to only receive sports-related notifications, and a social media app to receive all notifications. The settings are sent to the server and saved.

[0075] Step 4:

[0076] Each application generates a notification when a condition is met and sends the notification data to the server. The notification data includes the type, content, and time of the notification.

[0077] Step 5:

[0078] Server: Receives notification data sent from applications. Evaluates received notifications based on each user's filter settings and filters out unnecessary notifications. For example, if a "political news notification" is received, it is determined to be unnecessary based on the user's settings and is filtered out.

[0079] Step 6:

[0080] Server: For notifications that pass the filter, the AI ​​generates notification text tailored to the user's preferences. For example, if a sports-related news notification passes the filter, the AI ​​creates a casual text such as "⚽There's new sports news!"

[0081] Step 7:

[0082] Server: The server sends the generated notification text and avatar information to the user's device. The notification data includes the notification content, the application that generated it, the user ID, etc.

[0083] Step 8:

[0084] Device: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, the avatar displays "⚽New sports news!" through the Zepeto app.

[0085] Through this series of steps, users can customize their notification environment and receive only the information that matters to them without being overwhelmed with unnecessary notifications.

[0086] Example 1

[0087] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0088] Currently, users receive many notifications from multiple software applications, which can lead to users missing important notifications. Furthermore, the content and style of notifications often do not suit users' preferences, causing users to find them annoying. This reduces the efficiency of notifications and impairs the user experience.

[0089] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0090] In this invention, the server includes: means for a user to create their own character; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each software application; server means for receiving notifications from each software application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to easily check only important information, freeing them from annoying notifications and providing a comfortable user experience.

[0091] A "character" is an avatar, such as a virtual person or animal, that a user creates to represent themselves.

[0092] A "notification text" is a text message that is generated based on specific conditions and sent to the user.

[0093] A "generative AI model" is an artificial intelligence algorithm that generates notification text based on user settings.

[0094] "Software applications" are programs used by users, such as news apps and social networking apps.

[0095] A "server" is a computer system that receives notification data from an application and performs processing based on user settings.

[0096] "Filtering" is a process that removes notifications that the user deems unnecessary and selects only important notifications.

[0097] A "terminal" is a device used by a user, such as a smartphone or tablet.

[0098] "Metadata" is supplementary data such as user avatar information that accompanies the notification text.

[0099] This system allows users to efficiently manage notifications from multiple software applications and receive them in a format that suits their preferences. The system is primarily composed of a user's device, a server, and a generative AI model.

[0100] First, the user installs a specific application on their device. When they open the application, they are guided to a screen where they can create a character. Here, the user can freely customize the character's appearance and clothing. For example, the user can choose hairstyle and clothing color to determine the character's detailed appearance.

[0101] Next, users are taken to a screen where they can set the tone and expression of the notification text. They can choose the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. Users can do this by using drop-down menus and sliders.

[0102] Users are then taken to a screen where they can customize notification settings for each software application: for a news app, they can choose to receive only sports-related notifications, and for a social networking app, they can choose to receive all notifications. This setting information is then stored on the server.

[0103] Notifications from each software application are generated when certain conditions are met and sent to a server. For example, a news application generates sports-related news and sends it to a server. The server evaluates the received notification data based on the filter settings for each user. Unnecessary notifications are cut out, and only important notifications are selected.

[0104] For the filtered notifications, the server uses a generative AI model to generate sentences tailored to the user's preferences. If the user selects a casual style, a notification sentence such as "⚽There's new sports news!" is generated. An example of a prompt sentence is "Please tell me how to filter sports-related notifications generated by a news app and send them to the user in a casual tone."

[0105] The generated notification text and necessary metadata (such as the user's character information) are sent from the server to the user's device. In response, the user's device displays the notification text. In this case, the character displays a notification saying, "⚽There's new sports news!" Notifications are generally displayed in a pop-up format.

[0106] This embodiment allows users to be freed from annoying notifications and receive valuable information tailored to their preferences without stress. The system realizes efficient notification management and improves the user experience.

[0107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0108] Step 1:

[0109] Users install a specific application on their device and open the avatar creation screen. They customize the character's appearance and clothing. Input includes information such as the user's chosen hairstyle and clothing color, and the avatar's appearance data is generated based on this information.

[0110] Step 2:

[0111] The user navigates to a page where they can set the tone and expression of their notification text. Here, they select the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons they want to use. The input is the user's notification style and emoji settings, and the output is the saved settings.

[0112] Step 3:

[0113] The user navigates to a page where they can customize notification settings for each software application. The input is the user's notification filter settings (e.g., "only receive sports-related notifications"), which are sent to the server and stored. The output is notification filter settings for each application.

[0114] Step 4:

[0115] Each software application generates a notification when a certain condition is met. For example, a news app generates a sports-related news item and sends the notification data to a server. The input is the generated notification data, and the output is the notification data received by the server.

[0116] Step 5:

[0117] The server evaluates the notification data it receives based on the filter settings for each user. Specifically, the server references the user's settings information stored in a database and cuts out unnecessary notifications. The input is the received notification data and the user's filter settings, and the output is the filtered important notification data.

[0118] Step 6:

[0119] The server uses a generative AI model to generate notification text for the filtered notification data. The input is the filtered notification data and the user's notification style settings, and the output is the generated notification text. For example, if the user selects a casual style, the generated notification text will read, "⚽There's new sports news!"

[0120] Step 7:

[0121] The server sends the generated notification text and necessary metadata (e.g., user avatar information) to the user's device. The input is the generated notification text and avatar data, and the output is the sent notification packet.

[0122] Step 8:

[0123] The user's device receives the notification data sent from the server. The device displays the notification text in a pop-up format, and the user's avatar presents the notification. The input is the notification data received from the server, and the output is the notification text displayed on the screen. The notification is displayed in the form of "⚽There is new sports news!"

[0124] (Application example 1)

[0125] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0126] Conventional notification systems lack sufficient notification filtering and customization based on user interests and preferences, and the wide range of information they provide can be distracting. Furthermore, notification text is often boring and unattractive, making it difficult to attract users' attention. Furthermore, notification content is often simply displayed as text, which is often counterintuitive.

[0127] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0128] In this invention, the server includes a means for the user to create their own avatar, a means for the user to set the tone and expression of the notification text, and a means for the user to customize the notification settings for each application. This allows the generation AI to generate text tailored to the user's preferences, increasing interest in necessary notifications while minimizing annoyance. In addition, displaying customized notification text using the user's avatar provides intuitive and attractive notifications.

[0129] "Means for users to create their own avatar" refers to a function that allows users to create and customize a character that will represent their own identity.

[0130] The "means for the user to set the tone and expression of the notification text" is a function that allows the user to individually set the style and expression of the notification text that they receive.

[0131] "Means for users to customize notification settings for each application" refers to a function that allows users to individually set notification content and reception conditions for each application they use.

[0132] The "server means for receiving notifications from each application" is a server-side function for aggregating and receiving notification data sent from a plurality of applications.

[0133] "Means for the server to filter notifications based on user settings and cut out unnecessary notifications" is a function that allows the server to sort the notification data received according to the user's settings and delete notifications that are deemed unnecessary.

[0134] "Means for the generation AI to generate text tailored to the user's preferences for required notifications" is a function that enables the generation AI to create customized notification text based on the user's preferences and settings, based on filtered notifications.

[0135] "Server means for transmitting the generated notification text and associated metadata to the user's terminal" is a server-side function for transferring the generated notification text and associated data to the user's terminal.

[0136] The "means for the user's terminal to display the notification text" is a function for visually displaying the notification text on the user's terminal.

[0137] "Means for filtering notifications that are limited to the user's interests and for the generation AI to generate customized text for specific notifications" refers to a function that selects notifications based on the user's interests and allows the generation AI to create customized text for the content of the selected notifications.

[0138] The "means for displaying a customized notification text using a user's avatar" is a function for displaying a specific customized notification text using a user's avatar.

[0139] A system for implementing the invention includes the following elements:

[0140] 1. User Initial Settings

[0141] Creating an avatar

[0142] Users install the application on their devices (smartphones, tablets, etc.). When they open the application, they are guided to an avatar creation screen where they can freely customize the appearance and clothing of their character.

[0143] Notification text settings

[0144] The user is taken to a screen where they can set the tone and expression of the notification text. They can set the style of the notification (casual, formal, humorous, etc.) and the type of emojis or emoticons to use.

[0145] Configuring Notification Filtering

[0146] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This information is stored on the server.

[0147] 2. Sending and filtering notifications

[0148] Notification occurs

[0149] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[0150] Receiving and filtering notifications

[0151] The server receives notification data sent from applications. The received notification data is evaluated based on the filter settings for each user, and unnecessary notifications are cut out and only valuable notifications are selected.

[0152] Notification text generation

[0153] For notifications that pass the filter, the generative AI model generates notification text that matches the user's preferences. For example, if the user has chosen a casual style, a notification such as "⚽New sports news!" will be generated.

[0154] 3. Notification

[0155] Sending notifications

[0156] The server sends the generated notification text and related metadata (such as avatar information) to the user's device.

[0157] Viewing notifications

[0158] The user's device receives the notification data sent from the server and displays the notification text on the device. The notification text is displayed using the user's avatar, making the notification visually appealing.

[0159] Component Description

[0160] server

[0161] The server is responsible for receiving, evaluating, and filtering notification data, and generating notification text using a generative AI model. This includes a server (e.g., Flask, Django) for processing HTTP requests and a generative AI model (e.g., GPT-3 (registered trademark)).

[0162] User terminal

[0163] The user terminal is a smartphone, tablet, or the like, and receives notification data sent from the server and displays the notification using an avatar.

[0164] Specific examples

[0165] Example 1

[0166] If a user wants to receive notifications in the "Fashion" category, they can select "Fashion" in the settings screen and set the notification style to "Casual." This will cause the generative AI model to generate casual-style notification text.

[0167] Prompt Sentence Example 1

[0168] Consider a generated AI response to "New sales information has arrived in the fashion category."

[0169] Example 2

[0170] If a user has chosen not to receive notifications in the "Electronic Devices" category, the server will filter notifications in that category and not send them to the user.

[0171] Prompt Sentence Example 2

[0172] Ignore the "New items in stock in the electronics category."

[0173] This system allows users to receive only the information they are interested in, making it easy to get important information without feeling distracted. The use of avatars also makes notifications visually appealing, improving the user experience.

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] A user installs the application on their device and opens it. They are then guided to the avatar creation screen to create their own character. This step takes as input the user's choices (appearance, clothing) and generates as output a customized avatar.

[0177] Step 2:

[0178] The user is taken to a screen where they can set the tone and expression of the notification text. At this stage, the user sets the style of the notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. The user's settings are the input, and the settings data is saved as the output.

[0179] Step 3:

[0180] The user is taken to a screen where they can customize notification settings for each application. For example, for a news app, the user sets the notification categories they want to receive (e.g., sports, politics). The input is the user's notification settings, and the output is the notification filter settings, which are saved on the server.

[0181] Step 4:

[0182] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met and sends the notification data to the server. The input is the notification data of each application, and the output is stored on the server.

[0183] Step 5:

[0184] The server evaluates the received notification data and filters it based on the user's settings. The server analyzes the notification data and cuts out notifications that the user deems unnecessary. The input is the notification data stored on the server and the user's filter settings, and the output is the filtered notification data.

[0185] Step 6:

[0186] For notification data that passes filtering, the server uses a generative AI model to generate notification text tailored to the user's preferences. Style settings such as "casual" or "formal" are input into the generative AI model, and customized notification text is obtained as output. For example, the generated text for the prompt "New sale information for the fashion category has arrived" is "A new fashion sale has started!"

[0187] Step 7:

[0188] The server sends the generated notification text and related metadata (e.g., avatar information) to the user's device. The generated notification text and metadata are input, and are sent to the user's device as output.

[0189] Step 8:

[0190] The user's device receives the notification data sent from the server and displays the notification text on the device. At this time, an avatar is also displayed to make the notification visually appealing. The input is the notification data received from the server, and the output is the notification displayed on the device screen.

[0191] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0192] User Preferences

[0193] 1. Create an avatar

[0194] Users install a specific application on their smartphone, tablet, or other device and navigate to the avatar creation screen. Here, users can customize their character's appearance and clothing. Once the avatar creation is complete, the avatar information is saved on the server.

[0195] 2. Setting up the generated AI

[0196] The user is taken to a screen where they can set the tone and expression of the notification text, select the notification style (casual, formal, humorous, etc.) and the type of emoji, and save the settings to the server.

[0197] 3. Notification filtering settings

[0198] The user navigates to the notification filtering settings screen for each application, where they can set the news app to only receive sports-related notifications and the social networking app to receive all notifications. These settings are then stored on the server.

[0199] Emotion Engine Settings

[0200] 4. Initializing the Emotion Engine

[0201] The emotion engine is initialized using the camera and microphone built into the user's device. Based on the user's facial expressions and tone of voice, the emotion engine is adjusted to recognize the user's emotions.

[0202] Sending and filtering notifications

[0203] 5. Notification Occurrence

[0204] When a condition is met, each application generates a notification and sends the notification data to the server, including the type of notification and the time of occurrence.

[0205] 6. Receiving and filtering notifications

[0206] The server receives notification data sent from the application and evaluates the notifications based on the user's filter settings. Unnecessary notifications are cut off and only necessary notifications remain.

[0207] 7. Notification Text Generation

[0208] For notifications that pass the filter, the AI ​​generator generates notification text tailored to the user's preferences. Furthermore, the emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the notification text accordingly. For example, if the user is feeling down, an encouraging message can be added.

[0209] Notification presentation

[0210] 8. Sending Notifications

[0211] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's emotional data.

[0212] 9. Display of notifications

[0213] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0214] Specific examples

[0215] User configuration example

[0216] User name: Kato-san

[0217] Avatar creation: Kato creates an avatar in casual clothing and saves it on the server.

[0218] Generative AI settings: We set the tone of notifications to be casual and specified frequent use of emojis.

[0219] Notification filter settings: Set your news app to only receive sports-related notifications, and your social media apps to receive all notifications.

[0220] Emotion engine setting example

[0221] Emotion engine initialization: Kato's device was initialized to recognize Kato's emotions using the camera and microphone.

[0222] Notification processing example

[0223] Notification occurs: A news app generates sports-related news and sends it to the server.

[0224] Receiving and filtering notifications: The server receives notification data and selects the required notifications based on the filter settings.

[0225] Notification text generation: The AI ​​generates a casual text like "⚽There's new sports news!" The emotion engine recognizes the user's emotion as "joy" and adds more positive expressions.

[0226] Notification presentation example

[0227] Sending notification: The server sends the generated notification text, avatar information, and emotion data to Kato's device.

[0228] Displaying a notification: Kato's device receives a notification and his avatar displays a smiling message saying, "⚽There's new sports news!"

[0229] This specific embodiment allows users to receive notifications that are adapted to their emotions in real time, providing a more personalized user experience.

[0230] The processing flow will be explained below.

[0231] Step 1:

[0232] User: Installs the application on the device and goes to the avatar creation screen. The user can freely set the avatar's appearance, clothing, hairstyle, skin color, etc. The completed avatar information is sent to the server and saved.

[0233] Step 2:

[0234] User: Go to the generated AI settings screen and customize the tone and expression of the notification text. For example, select a casual style and a preference for using lots of emojis. The settings are sent to the server and saved.

[0235] Step 3:

[0236] User: Go to the notification filtering settings screen for each application. For example, in a news app, set "Receive only sports-related notifications," and in a social networking app, set "Receive all notifications." These settings are sent to the server and saved.

[0237] Step 4:

[0238] User: Initializes the emotion engine using the device's built-in camera and microphone. The emotion engine is adjusted to recognize the user's facial expressions and tone of voice. This setting is managed by the server.

[0239] Step 5:

[0240] Each application generates a notification when a specific condition is met and sends the notification data to the server. The notification data includes information such as the type of notification, its content, and the time of occurrence.

[0241] Step 6:

[0242] Server: Receives notification data sent from the application. The server evaluates notifications based on the filter settings for each user and cuts out unnecessary notifications. For example, if a "political news notification" is determined to be unnecessary, the notification will be discarded.

[0243] Step 7:

[0244] Server: For notifications that pass the filter, the generation AI generates notification text tailored to the user's preferences. In addition, the emotion engine recognizes the user's emotions and adjusts the tone and expression of the notification text based on those emotions. For example, if the user is feeling down, it adds an encouraging message.

[0245] Step 8:

[0246] Server: The server sends the generated notification text, avatar information, and emotion data to the user's device, including the notification content, the application from which it originated, and the user ID.

[0247] Step 9:

[0248] Terminal: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0249] Examples:

[0250] Example user settings: Takahashi created an avatar with casual clothing and hairstyle, and selected a casual tone of voice and a style that makes heavy use of emojis in the AI ​​generation settings. He also set the news app to receive "sports-related notifications only" and the social media app to receive all notifications.

[0251] Emotion engine configuration example: The emotion engine was initialized to recognize Takahashi's emotions using the device's camera and microphone.

[0252] Example of notification processing: A news app generates sports-related news and sends it to the server. The server receives and filters the notifications, and the generation AI generates a casual sentence such as "⚽There's new sports news!". The emotion engine recognizes Takahashi's emotion as "joy" and adds a more positive expression. The notification is sent to Takahashi's device, and the avatar displays the notification with a smiling face.

[0253] Example 2

[0254] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0255] Conventional notification systems have the problem that it is difficult for users to receive only the information they need, and the notification language is uniform, making it impossible to provide a personalized user experience. In addition, the notification text does not adapt to the user's emotions, which reduces the value of the notifications received by the user and does not improve the user experience.

[0256] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0257] In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; means for recognizing the user's emotions using a camera and microphone built into the user's terminal; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; means for the generative AI model to recognize the user's emotions and adjust the tone and expression of the notification text; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to receive only the information they need, and the notification text adapts to the user's emotions in real time, providing a personalized user experience.

[0258] An "avatar" is a virtual character that a user creates to visually represent themselves and customize their appearance and clothing.

[0259] "Tone and expression of notification text" refers to settings such as how notification messages are written and their style, the choice of words used, and the use of emoticons.

[0260] "Notification settings" refers to settings for customizing the types of notifications and filtering conditions that a user wants to receive for each application.

[0261] "Camera and microphone" refers to hardware devices used to sense a user's facial expressions and tone of voice and recognize emotions.

[0262] A "server" is a computer system that receives and processes data from multiple users and transmits the necessary information to the users' terminals.

[0263] "Filtering" refers to the process in which the server removes unnecessary data from the received notification data and selects only the necessary data based on the user's settings.

[0264] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate notification text based on a user's settings and preferences.

[0265] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to recognize the user's current emotional state.

[0266] "Notification text" refers to a message sent to a user, generated by filtering or a generative AI model.

[0267] A "user's device" is a device used by a user, such as a smartphone, tablet, or computer, that has the ability to receive and display notifications.

[0268] "Emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to estimate the emotions the user is currently feeling.

[0269] The system of the present invention provides a way for users to receive personalized and customized notifications. The main elements of the system include a user device, a server, and a generative AI model.

[0270] User Preferences

[0271] First, the user installs a dedicated application on their device. Then, the user launches the application and accesses the avatar creation screen. Here, the user customizes the character's appearance and clothing to create an avatar. The completed avatar information is sent to the server and stored in a database.

[0272] Next, the user is taken to a screen where they can set the tone and expression of the notification text. For example, they can choose the notification style (casual, formal, humorous) and specify the type of emojis to use. These settings are sent to the server and stored for each user.

[0273] Additionally, users can customize notification settings for each application, for example, to receive only sports-related notifications in a news app, or all notifications in a social networking app, which are also stored on the server.

[0274] Emotion Engine Settings

[0275] The user's device is equipped with a built-in camera and microphone, which are used to initialize the emotion engine. The user makes various facial expressions and speaks in different tones in front of the camera to collect data that the system uses to recognize the user's emotions. This data is sent to the server, where the user's basic emotional patterns are recorded.

[0276] Sending and filtering notifications

[0277] When a specific condition is met, each application generates a notification and sends the notification data to the server. The server receives this notification data and filters out unnecessary notifications based on the user's filter settings. For notifications that pass the filter, the generative AI model generates text tailored to the user's preferences.

[0278] The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text. For example, if the user is feeling down, the generative AI model will add an encouraging message.

[0279] Notification presentation

[0280] The server sends the generated notification text and avatar information to the user's device. It also sends information to adjust the avatar's facial expressions and movements based on the latest emotional data. The user's device displays the received notification data, and the avatar changes its facial expressions and movements to match the user's emotions while displaying the notification text. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0281] Specific examples

[0282] As an example of a real user configuration, a user can create an avatar, set notification style to casual, set to frequently use emojis, set to receive only sports-related notifications in a news app, and receive all notifications in a social networking app.

[0283] For example, you can use prompts like the following to feed a generative AI model:

[0284] "Generate a notification message for when the user is happy. The message is about sports news."

[0285] This specific embodiment allows users to receive personalized notifications in real time, and the system can present notifications in a way that reflects the user's emotions, greatly improving the user experience.

[0286] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0287] Program processing flow

[0288] Step 1:

[0289] The user installs the dedicated application on their device. The user downloads the application from the App Store or GOOGLE PLAY® Store and installs it. The application performs initial setup and displays a screen prompting the user to create an avatar.

[0290] Input: App download request from App Store or Google Play Store

[0291] Output: Installed dedicated application

[0292] Step 2:

[0293] The user goes to the avatar creation screen and customizes the character's appearance and clothing. The user selects each part, such as the head, hairstyle, clothing, and accessories, to complete the customization. The completed avatar information is sent to the server.

[0294] Input: Information about the avatar parts selected by the user

[0295] Output: Avatar information stored on the server

[0296] Step 3:

[0297] The user accesses the notification text settings screen and selects the notification style (casual, formal, humorous, etc.) and the type of emoji. These settings are sent to the server.

[0298] Input: Notification style and emoji type

[0299] Output: Notification settings saved on the server

[0300] Step 4:

[0301] The user goes to a screen where they can customize notification settings for each application and select the types of notifications they want to receive. The settings are then sent to the server.

[0302] Input: Notification filter settings for each application

[0303] Output: Notification settings for each application stored on the server

[0304] Step 5:

[0305] The user's device activates the camera and microphone to collect the user's facial expressions and tone of voice, which initializes the emotion engine so that it can recognize the user's emotions. The initialization data is then sent to the server.

[0306] Input: User's facial expressions and tone of voice

[0307] Output: Emotion recognition data stored on the server

[0308] Step 6:

[0309] Each application generates a notification when a specific condition is met and sends the notification data to the server.

[0310] Input: Application-generated notification data

[0311] Output: Notification data sent to the server

[0312] Step 7:

[0313] The server receives notification data sent from the application and filters notifications based on the user's settings, removing unnecessary notifications and selecting only necessary notifications.

[0314] Input: Notification data sent to the server

[0315] Output: Filtered notification data

[0316] Step 8:

[0317] The generative AI model generates text tailored to the user's preferences from the notification data that passes the filter. The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text.

[0318] Input: filtered notification data, user emotion data

[0319] Output: A customized notification text generated by the generative AI model

[0320] Step 9:

[0321] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's latest emotional data.

[0322] Input: Generated notification text, avatar information, user emotion data

[0323] Output: Notification data sent to the user's device

[0324] Step 10:

[0325] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0326] Input: Notification data received from the server

[0327] Output: Displaying an emotion-adaptive notification

[0328] (Application example 2)

[0329] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] In modern virtual stores, personalizing and enhancing the user experience is an important challenge. In particular, providing notifications based on the user's emotions can increase user engagement and boost purchasing motivation. However, existing systems lack the means to recognize the user's emotions in real time and adjust the notification content and avatar display based on those emotions, making it difficult to provide a personalized experience.

[0331] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generation AI to generate text tailored to the user's preferences for necessary notifications; emotion recognition means for recognizing the user's emotions and adjusting the notification text based on the emotions; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This makes it possible to adjust the notification text according to the user's emotions and provide a personalized experience.

[0332] An "avatar" is a digital character that a user creates to represent themselves within a virtual environment.

[0333] A "notification" is information or a message sent from each application to the user.

[0334] "Generative AI" is an artificial intelligence system that automatically generates text based on the user's settings and preferences.

[0335] "Emotion recognition" is a technology that analyzes a user's facial expressions and tone of voice to detect their emotional state at that time.

[0336] "Filtering" is the process by which the server cuts out unnecessary notifications based on the user's settings and selects only the necessary notifications.

[0337] The "server" is a central management system that manages user settings and notification data, and receives, filters, and sends notifications from each application.

[0338] A "terminal" is a device used by a user, such as a smartphone, tablet, or computer.

[0339] A "personalized experience" is a user experience that is customized to fit the individual preferences and feelings of each user.

[0340] System Overview

[0341] This invention is a system for a virtual store that senses user emotions and generates and displays personalized notifications. It mainly consists of the following elements:

[0342] 1. How users create their own avatar: Using a device (smartphone, tablet, computer), users create a digital character that represents them in a virtual environment.

[0343] 2. A means for users to set the tone and expression of notification text: Users use their devices to customize the tone (casual, formal, etc.) and expression (use of emojis, etc.) of notification text.

[0344] 3. A way for users to customize notification settings for each application: Users customize the types of notifications they want to receive from specific applications.

[0345] 4. Emotion recognition means: Using the device's built-in camera and microphone, the device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0346] 5. Means for the generative AI to generate text tailored to the user's preferences: The server uses the generative AI model to generate text tailored to the user's preferences for the filtered notifications.

[0347] 6. A means for the server to filter notifications based on user settings and cut out unnecessary notifications: Receive notifications from each application and filter out unnecessary notifications based on user settings.

[0348] 7. Server means for transmitting the generated notification text to the user's terminal: The filtered notification text is transmitted to the user's terminal.

[0349] 8. Means for the user's device to display the notification text: The user's device displays the generated notification text, and the avatar presents the notification with facial expressions and movements that correspond to the emotion.

[0350] Hardware and Software Details

[0351] Hardware:

[0352] Smartphones, tablets, computers (user devices)

[0353] Camera and microphone (for emotion recognition)

[0354] software:

[0355] Generative AI model: Hugging Face natural language processing model

[0356] Emotion Recognition Software: Hugging Face's Sentiment-Analysis Pipeline

[0357] Server system: A server that receives, filters, and sends notifications

[0358] Explanation of the processing flow

[0359] 1. User creates an avatar:

[0360] Using an application on the device, users create an avatar, which is used to represent them within the virtual store and provide a personalized experience.

[0361] 2. Notification text settings:

[0362] Users can set their preferences for the tone and expression of notifications from a screen where they can choose things like a casual tone and the inclusion of emojis.

[0363] 3. Customize your notification settings:

[0364] Users customize the types of notifications they receive from each application, for example, they can receive only news notifications from certain categories.

[0365] 4. Initialize emotion recognition:

[0366] The user's device uses a camera and microphone to recognize the user's emotions, performing initial setup and training models to analyze facial expressions and tone of voice.

[0367] 5. Notification Generation and Filtering:

[0368] Notifications are received from each application and filtered by the server based on the user's settings. Only the filtered notifications are processed by the generative AI model to create notification text tailored to the user's preferences.

[0369] 6. Sending and Displaying Notifications:

[0370] The generated notification text is sent from the server to the user's device, where it is displayed by the avatar, who then displays the text and makes facial expressions and movements according to the user's emotions.

[0371] Specific examples

[0372] User state: The camera captures your face and the microphone records your voice when you are using the device.

[0373] Emotion recognition result: The user is recognized as happy.

[0374] Generated notification: "🌟Announcement from your virtual store🌟Check out our new arrivals!"

[0375] Prompt Sentence Examples

[0376] Prompt: "Generate a message to keep the user happy and notify him of new products."

[0377] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0378] Step 1:

[0379] The user creates an avatar. Using an application on their device, the user creates a digital character (avatar) to represent themselves. As input, the user selects appearance, clothing, accessories, etc., and as output, the avatar information is generated and stored on the server. This avatar is later used to display notifications.

[0380] Step 2:

[0381] The user configures the tone and expression of the notification text. Using the device, the user accesses a screen that allows them to customize the tone (e.g., casual, formal) and expression (e.g., type of emoji) of the notification text. User preferences are provided as input, and the configuration information is saved on the server as output.

[0382] Step 3:

[0383] Users customize notification settings for each application. Users can finely customize notification settings from news apps, social networking apps, etc., by setting the types of notifications they want to receive and filter conditions. Notification setting information for each application is provided as input, and individual settings are saved on the server as output.

[0384] Step 4:

[0385] Initialize emotion recognition. The emotion recognition model is calibrated and initialized using the camera and microphone built into the user's device. Data captured from the user's facial expressions and tone of voice is used as input, and emotion recognition model parameters are set as output.

[0386] Step 5:

[0387] The server receives notifications from each application. The server receives notification data sent from different applications in a unified manner. Notification data is sent to the server as input and accumulated on the server as output.

[0388] Step 6:

[0389] The server filters notifications. It filters the received notification data based on the user's pre-defined settings and cuts out unnecessary notifications. It takes raw notification data as input and provides filtered notification data as output.

[0390] Step 7:

[0391] The generation AI generates notification text. For the filtered notifications, the generation AI generates text tailored to the user's preferences. The filtered notification data and user settings are provided as input, and customized notification text is created as output.

[0392] Step 8:

[0393] The device performs emotion recognition. It analyzes the user's facial expressions and voice in real time to recognize their current emotional state. Real-time data from the camera and microphone is used as input, and emotion recognition results are obtained as output.

[0394] Step 9:

[0395] The server adjusts the notification text. Based on the emotion recognition results, the server adjusts the already generated notification text according to the user's emotion. The generated notification text and the emotion recognition results are provided as input, and the adjusted notification text is obtained as output.

[0396] Step 10:

[0397] The server sends the adjusted notification text and avatar information to the terminal. The server sends the adjusted notification text and avatar information according to the emotion to the user's terminal. The adjusted notification text and avatar information are provided as input, and the data is sent to the terminal as output.

[0398] Step 11:

[0399] The device displays the notification text. The user's device displays the adjusted notification text along with the avatar's facial expressions and movements. The adjusted notification text and avatar information are provided as input, and the notification is displayed as output.

[0400] Prompt Sentence Examples

[0401] Prompt: "Generate a message to keep the user happy and notify him of new products."

[0402] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0403] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0404] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0405] [Second embodiment]

[0406] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0407] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0408] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0409] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0410] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0411] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0412] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0413] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0414] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0415] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0416] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0417] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0418] User Preferences

[0419] 1. Create an avatar

[0420] Users install a specific application on their smartphone, tablet, or other device. When they open the application, they are guided to a screen where they can create their own avatar. Here, they can freely customize their character's appearance, clothing, and other aspects.

[0421] 2. Setting up the generated AI

[0422] The user is then taken to a screen where they can set the tone and expression of the notification text to the AI ​​generator. Here, they can set the style of the notification (e.g., casual, formal, humorous, etc.) and the type of emojis and emoticons to use.

[0423] 3. Notification filtering settings

[0424] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This setting information is stored on the server.

[0425] Sending and filtering notifications

[0426] 4. Notification Occurrence

[0427] Each application (e.g., news app, SNS app, etc.) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[0428] 5. Receiving and filtering notifications

[0429] The server receives notification data sent from the application. The received notification data is evaluated based on the filter settings for each user. The server cuts out notifications that the user deems unnecessary and selects only important notifications. This filtering process leaves only the notification information that is valuable to the user.

[0430] 6. Notification Text Generation

[0431] For notifications that pass the filter, the AI ​​generates notification text that matches the user's preferences. For example, if the user has selected a casual style, the AI ​​generates a text such as "⚽New sports news!"

[0432] Notification presentation

[0433] 7. Sending Notifications

[0434] The server sends the generated notification text and necessary metadata (such as the user's avatar information) to the user's device.

[0435] 8. Display of notifications

[0436] The user's device receives the notification data sent from the server. The device displays the notification using the user's avatar along with the notification text. For example, if the user is using the Zepeto app, the avatar displays a notification saying "⚽New sports news!"

[0437] Specific examples

[0438] User configuration example

[0439] User name: Sato-san

[0440] Avatar Creation: Sato created a casually dressed character as his avatar.

[0441] Generator AI settings: Sato set the tone of notifications to a casual style and specified that emojis be used frequently.

[0442] Notification filter settings: Sato set his news app to receive "only sports-related notifications" and his social media app to receive "all notifications."

[0443] Notification processing example

[0444] Notification occurs: The news app generates "sports-related news" and sends it to the server.

[0445] Receiving and filtering notifications: The server receives the notification data and determines that "sports related news" is the notification that needs to be sent.

[0446] Notification text generation: The AI ​​generates casual notification text such as "⚽There's new sports news!"

[0447] Sending notification: The server sends the generated notification text and avatar information to Mr. Sato's device.

[0448] Displaying the notification: Sato's device receives a notification and his avatar displays "⚽New sports news!"

[0449] This embodiment frees users from annoying notifications and allows them to receive valuable information tailored to their preferences without stress.

[0450] The processing flow will be explained below.

[0451] Step 1:

[0452] User: Install the application on the device and enter the avatar creation screen. Freely set the avatar's appearance, clothing, hairstyle, etc. Once complete, save the avatar information.

[0453] Step 2:

[0454] User: Go to the AI ​​generation settings screen and customize the tone and expression of the notification text. For example, choose a casual tone and a preference for using lots of emojis. This setting is saved on the server.

[0455] Step 3:

[0456] User: Go to the notification filtering settings screen for each application. Here, for example, you can set a news app to only receive sports-related notifications, and a social media app to receive all notifications. The settings are sent to the server and saved.

[0457] Step 4:

[0458] Each application generates a notification when a condition is met and sends the notification data to the server. The notification data includes the type, content, and time of the notification.

[0459] Step 5:

[0460] Server: Receives notification data sent from applications. Evaluates received notifications based on each user's filter settings and filters out unnecessary notifications. For example, if a "political news notification" is received, it is determined to be unnecessary based on the user's settings and is filtered out.

[0461] Step 6:

[0462] Server: For notifications that pass the filter, the AI ​​generates notification text tailored to the user's preferences. For example, if a sports-related news notification passes the filter, the AI ​​creates a casual text such as "⚽There's new sports news!"

[0463] Step 7:

[0464] Server: The server sends the generated notification text and avatar information to the user's device. The notification data includes the notification content, the application that generated it, the user ID, etc.

[0465] Step 8:

[0466] Device: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, the avatar displays "⚽New sports news!" through the Zepeto app.

[0467] Through this series of steps, users can customize their notification environment and receive only the information that matters to them without being overwhelmed with unnecessary notifications.

[0468] Example 1

[0469] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0470] Currently, users receive many notifications from multiple software applications, which can lead to users missing important notifications. Furthermore, the content and style of notifications often do not suit users' preferences, causing users to find them annoying. This reduces the efficiency of notifications and impairs the user experience.

[0471] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0472] In this invention, the server includes: means for a user to create their own character; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each software application; server means for receiving notifications from each software application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to easily check only important information, freeing them from annoying notifications and providing a comfortable user experience.

[0473] A "character" is an avatar, such as a virtual person or animal, that a user creates to represent themselves.

[0474] A "notification text" is a text message that is generated based on specific conditions and sent to the user.

[0475] A "generative AI model" is an artificial intelligence algorithm that generates notification text based on user settings.

[0476] "Software applications" are programs used by users, such as news apps and social networking apps.

[0477] A "server" is a computer system that receives notification data from an application and performs processing based on user settings.

[0478] "Filtering" is a process that removes notifications that the user deems unnecessary and selects only important notifications.

[0479] A "terminal" is a device used by a user, such as a smartphone or tablet.

[0480] "Metadata" is supplementary data such as user avatar information that accompanies the notification text.

[0481] This system allows users to efficiently manage notifications from multiple software applications and receive them in a format that suits their preferences. The system is primarily composed of a user's device, a server, and a generative AI model.

[0482] First, the user installs a specific application on their device. When they open the application, they are guided to a screen where they can create a character. Here, the user can freely customize the character's appearance and clothing. For example, the user can choose hairstyle and clothing color to determine the character's detailed appearance.

[0483] Next, users are taken to a screen where they can set the tone and expression of the notification text. They can choose the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. Users can do this by using drop-down menus and sliders.

[0484] Users are then taken to a screen where they can customize notification settings for each software application: for a news app, they can choose to receive only sports-related notifications, and for a social networking app, they can choose to receive all notifications. This setting information is then stored on the server.

[0485] Notifications from each software application are generated when certain conditions are met and sent to a server. For example, a news application generates sports-related news and sends it to a server. The server evaluates the received notification data based on the filter settings for each user. Unnecessary notifications are cut out, and only important notifications are selected.

[0486] For the filtered notifications, the server uses a generative AI model to generate sentences tailored to the user's preferences. If the user selects a casual style, a notification sentence such as "⚽There's new sports news!" is generated. An example of a prompt sentence is "Please tell me how to filter sports-related notifications generated by a news app and send them to the user in a casual tone."

[0487] The generated notification text and necessary metadata (such as the user's character information) are sent from the server to the user's device. In response, the user's device displays the notification text. In this case, the character displays a notification saying, "⚽There's new sports news!" Notifications are generally displayed in a pop-up format.

[0488] This embodiment allows users to be freed from annoying notifications and receive valuable information tailored to their preferences without stress. The system realizes efficient notification management and improves the user experience.

[0489] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0490] Step 1:

[0491] Users install a specific application on their device and open the avatar creation screen. They customize the character's appearance and clothing. Input includes information such as the user's chosen hairstyle and clothing color, and the avatar's appearance data is generated based on this information.

[0492] Step 2:

[0493] The user navigates to a page where they can set the tone and expression of their notification text. Here, they select the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons they want to use. The input is the user's notification style and emoji settings, and the output is the saved settings.

[0494] Step 3:

[0495] The user navigates to a page where they can customize notification settings for each software application. The input is the user's notification filter settings (e.g., "only receive sports-related notifications"), which are sent to the server and stored. The output is notification filter settings for each application.

[0496] Step 4:

[0497] Each software application generates a notification when a certain condition is met. For example, a news app generates a sports-related news item and sends the notification data to a server. The input is the generated notification data, and the output is the notification data received by the server.

[0498] Step 5:

[0499] The server evaluates the notification data it receives based on the filter settings for each user. Specifically, the server references the user's settings information stored in a database and cuts out unnecessary notifications. The input is the received notification data and the user's filter settings, and the output is the filtered important notification data.

[0500] Step 6:

[0501] The server uses a generative AI model to generate notification text for the filtered notification data. The input is the filtered notification data and the user's notification style settings, and the output is the generated notification text. For example, if the user selects a casual style, the generated notification text will read, "⚽There's new sports news!"

[0502] Step 7:

[0503] The server sends the generated notification text and necessary metadata (e.g., user avatar information) to the user's device. The input is the generated notification text and avatar data, and the output is the sent notification packet.

[0504] Step 8:

[0505] The user's device receives the notification data sent from the server. The device displays the notification text in a pop-up format, and the user's avatar presents the notification. The input is the notification data received from the server, and the output is the notification text displayed on the screen. The notification is displayed in the form of "⚽There is new sports news!"

[0506] (Application example 1)

[0507] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0508] Conventional notification systems lack sufficient notification filtering and customization based on user interests and preferences, and the wide range of information they provide can be distracting. Furthermore, notification text is often boring and unattractive, making it difficult to attract users' attention. Furthermore, notification content is often simply displayed as text, which is often counterintuitive.

[0509] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0510] In this invention, the server includes a means for the user to create their own avatar, a means for the user to set the tone and expression of the notification text, and a means for the user to customize the notification settings for each application. This allows the generation AI to generate text tailored to the user's preferences, increasing interest in necessary notifications while minimizing annoyance. In addition, displaying customized notification text using the user's avatar provides intuitive and attractive notifications.

[0511] "Means for users to create their own avatar" refers to a function that allows users to create and customize a character that will represent their own identity.

[0512] The "means for the user to set the tone and expression of the notification text" is a function that allows the user to individually set the style and expression of the notification text that they receive.

[0513] "Means for users to customize notification settings for each application" refers to a function that allows users to individually set notification content and reception conditions for each application they use.

[0514] The "server means for receiving notifications from each application" is a server-side function for aggregating and receiving notification data sent from a plurality of applications.

[0515] "Means for the server to filter notifications based on user settings and cut out unnecessary notifications" is a function that allows the server to sort the notification data received according to the user's settings and delete notifications that are deemed unnecessary.

[0516] "Means for the generation AI to generate text tailored to the user's preferences for required notifications" is a function that enables the generation AI to create customized notification text based on the user's preferences and settings, based on filtered notifications.

[0517] "Server means for transmitting the generated notification text and associated metadata to the user's terminal" is a server-side function for transferring the generated notification text and associated data to the user's terminal.

[0518] The "means for the user's terminal to display the notification text" is a function for visually displaying the notification text on the user's terminal.

[0519] "Means for filtering notifications that are limited to the user's interests and for the generation AI to generate customized text for specific notifications" refers to a function that selects notifications based on the user's interests and allows the generation AI to create customized text for the content of the selected notifications.

[0520] The "means for displaying a customized notification text using a user's avatar" is a function for displaying a specific customized notification text using a user's avatar.

[0521] A system for implementing the invention includes the following elements:

[0522] 1. User Initial Settings

[0523] Creating an avatar

[0524] Users install the application on their devices (smartphones, tablets, etc.). When they open the application, they are guided to an avatar creation screen where they can freely customize the appearance and clothing of their character.

[0525] Notification text settings

[0526] The user is taken to a screen where they can set the tone and expression of the notification text. They can set the style of the notification (casual, formal, humorous, etc.) and the type of emojis or emoticons to use.

[0527] Configuring Notification Filtering

[0528] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This information is stored on the server.

[0529] 2. Sending and filtering notifications

[0530] Notification occurs

[0531] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[0532] Receiving and filtering notifications

[0533] The server receives notification data sent from applications. The received notification data is evaluated based on the filter settings for each user, and unnecessary notifications are cut out and only valuable notifications are selected.

[0534] Notification text generation

[0535] For notifications that pass the filter, the generative AI model generates notification text that matches the user's preferences. For example, if the user has chosen a casual style, a notification such as "⚽New sports news!" will be generated.

[0536] 3. Notification

[0537] Sending notifications

[0538] The server sends the generated notification text and related metadata (such as avatar information) to the user's device.

[0539] Viewing notifications

[0540] The user's device receives the notification data sent from the server and displays the notification text on the device. The notification text is displayed using the user's avatar, making the notification visually appealing.

[0541] Component Description

[0542] server

[0543] The server is responsible for receiving, evaluating, and filtering notification data, and generating notification text using a generative AI model. This includes a server (e.g., Flask, Django) for processing HTTP requests and a generative AI model (e.g., GPT-3).

[0544] User terminal

[0545] The user terminal is a smartphone, tablet, or the like, and receives notification data sent from the server and displays the notification using an avatar.

[0546] Specific examples

[0547] Example 1

[0548] If a user wants to receive notifications in the "Fashion" category, they can select "Fashion" in the settings screen and set the notification style to "Casual." This will cause the generative AI model to generate casual-style notification text.

[0549] Prompt Sentence Example 1

[0550] Consider a generated AI response to "New sales information has arrived in the fashion category."

[0551] Example 2

[0552] If a user has chosen not to receive notifications in the "Electronic Devices" category, the server will filter notifications in that category and not send them to the user.

[0553] Prompt Sentence Example 2

[0554] Ignore the "New items in stock in the electronics category."

[0555] This system allows users to receive only the information they are interested in, making it easy to get important information without feeling distracted. The use of avatars also makes notifications visually appealing, improving the user experience.

[0556] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0557] Step 1:

[0558] A user installs the application on their device and opens it. They are then guided to the avatar creation screen to create their own character. This step takes as input the user's choices (appearance, clothing) and generates as output a customized avatar.

[0559] Step 2:

[0560] The user is taken to a screen where they can set the tone and expression of the notification text. At this stage, the user sets the style of the notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. The user's settings are the input, and the settings data is saved as the output.

[0561] Step 3:

[0562] The user is taken to a screen where they can customize notification settings for each application. For example, for a news app, the user sets the notification categories they want to receive (e.g., sports, politics). The input is the user's notification settings, and the output is the notification filter settings, which are saved on the server.

[0563] Step 4:

[0564] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met and sends the notification data to the server. The input is the notification data of each application, and the output is stored on the server.

[0565] Step 5:

[0566] The server evaluates the received notification data and filters it based on the user's settings. The server analyzes the notification data and cuts out notifications that the user deems unnecessary. The input is the notification data stored on the server and the user's filter settings, and the output is the filtered notification data.

[0567] Step 6:

[0568] For notification data that passes filtering, the server uses a generative AI model to generate notification text tailored to the user's preferences. Style settings such as "casual" or "formal" are input into the generative AI model, and customized notification text is obtained as output. For example, the generated text for the prompt "New sale information for the fashion category has arrived" is "A new fashion sale has started!"

[0569] Step 7:

[0570] The server sends the generated notification text and related metadata (e.g., avatar information) to the user's device. The generated notification text and metadata are input, and are sent to the user's device as output.

[0571] Step 8:

[0572] The user's device receives the notification data sent from the server and displays the notification text on the device. At this time, an avatar is also displayed to make the notification visually appealing. The input is the notification data received from the server, and the output is the notification displayed on the device screen.

[0573] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0574] User Preferences

[0575] 1. Create an avatar

[0576] Users install a specific application on their smartphone, tablet, or other device and navigate to the avatar creation screen. Here, users can customize their character's appearance and clothing. Once the avatar creation is complete, the avatar information is saved on the server.

[0577] 2. Setting up the generated AI

[0578] The user is taken to a screen where they can set the tone and expression of the notification text, select the notification style (casual, formal, humorous, etc.) and the type of emoji, and save the settings to the server.

[0579] 3. Notification filtering settings

[0580] The user navigates to the notification filtering settings screen for each application, where they can set the news app to only receive sports-related notifications and the social networking app to receive all notifications. These settings are then stored on the server.

[0581] Emotion Engine Settings

[0582] 4. Initializing the Emotion Engine

[0583] The emotion engine is initialized using the camera and microphone built into the user's device. Based on the user's facial expressions and tone of voice, the emotion engine is adjusted to recognize the user's emotions.

[0584] Sending and filtering notifications

[0585] 5. Notification Occurrence

[0586] When a condition is met, each application generates a notification and sends the notification data to the server, including the type of notification and the time of occurrence.

[0587] 6. Receiving and filtering notifications

[0588] The server receives notification data sent from the application and evaluates the notifications based on the user's filter settings. Unnecessary notifications are cut off and only necessary notifications remain.

[0589] 7. Notification Text Generation

[0590] For notifications that pass the filter, the AI ​​generator generates notification text tailored to the user's preferences. Furthermore, the emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the notification text accordingly. For example, if the user is feeling down, an encouraging message can be added.

[0591] Notification presentation

[0592] 8. Sending Notifications

[0593] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's emotional data.

[0594] 9. Display of notifications

[0595] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0596] Specific examples

[0597] User configuration example

[0598] User name: Kato-san

[0599] Avatar creation: Kato creates an avatar in casual clothing and saves it on the server.

[0600] Generative AI settings: We set the tone of notifications to be casual and specified frequent use of emojis.

[0601] Notification filter settings: Set your news app to only receive sports-related notifications, and your social media apps to receive all notifications.

[0602] Emotion engine setting example

[0603] Emotion engine initialization: Kato's device was initialized to recognize Kato's emotions using the camera and microphone.

[0604] Notification processing example

[0605] Notification occurs: A news app generates sports-related news and sends it to the server.

[0606] Receiving and filtering notifications: The server receives notification data and selects the required notifications based on the filter settings.

[0607] Notification text generation: The AI ​​generates a casual text like "⚽There's new sports news!" The emotion engine recognizes the user's emotion as "joy" and adds more positive expressions.

[0608] Notification presentation example

[0609] Sending notification: The server sends the generated notification text, avatar information, and emotion data to Kato's device.

[0610] Displaying a notification: Kato's device receives a notification and his avatar displays a smiling message saying, "⚽There's new sports news!"

[0611] This specific embodiment allows users to receive notifications that are adapted to their emotions in real time, providing a more personalized user experience.

[0612] The processing flow will be explained below.

[0613] Step 1:

[0614] User: Installs the application on the device and goes to the avatar creation screen. The user can freely set the avatar's appearance, clothing, hairstyle, skin color, etc. The completed avatar information is sent to the server and saved.

[0615] Step 2:

[0616] User: Go to the generated AI settings screen and customize the tone and expression of the notification text. For example, select a casual style and a preference for using lots of emojis. The settings are sent to the server and saved.

[0617] Step 3:

[0618] User: Go to the notification filtering settings screen for each application. For example, in a news app, set "Receive only sports-related notifications," and in a social networking app, set "Receive all notifications." These settings are sent to the server and saved.

[0619] Step 4:

[0620] User: Initializes the emotion engine using the device's built-in camera and microphone. The emotion engine is adjusted to recognize the user's facial expressions and tone of voice. This setting is managed by the server.

[0621] Step 5:

[0622] Each application generates a notification when a specific condition is met and sends the notification data to the server. The notification data includes information such as the type of notification, its content, and the time of occurrence.

[0623] Step 6:

[0624] Server: Receives notification data sent from the application. The server evaluates notifications based on the filter settings for each user and cuts out unnecessary notifications. For example, if a "political news notification" is determined to be unnecessary, the notification will be discarded.

[0625] Step 7:

[0626] Server: For notifications that pass the filter, the generation AI generates notification text tailored to the user's preferences. In addition, the emotion engine recognizes the user's emotions and adjusts the tone and expression of the notification text based on those emotions. For example, if the user is feeling down, it adds an encouraging message.

[0627] Step 8:

[0628] Server: The server sends the generated notification text, avatar information, and emotion data to the user's device, including the notification content, the application from which it originated, and the user ID.

[0629] Step 9:

[0630] Terminal: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0631] Examples:

[0632] Example user settings: Takahashi created an avatar with casual clothing and hairstyle, and selected a casual tone of voice and a style that makes heavy use of emojis in the AI ​​generation settings. He also set the news app to receive "sports-related notifications only" and the social media app to receive all notifications.

[0633] Emotion engine configuration example: The emotion engine was initialized to recognize Takahashi's emotions using the device's camera and microphone.

[0634] Example of notification processing: A news app generates sports-related news and sends it to the server. The server receives and filters the notifications, and the generation AI generates a casual sentence such as "⚽There's new sports news!". The emotion engine recognizes Takahashi's emotion as "joy" and adds a more positive expression. The notification is sent to Takahashi's device, and the avatar displays the notification with a smiling face.

[0635] Example 2

[0636] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0637] Conventional notification systems have the problem that it is difficult for users to receive only the information they need, and the notification language is uniform, making it impossible to provide a personalized user experience. In addition, the notification text does not adapt to the user's emotions, which reduces the value of the notifications received by the user and does not improve the user experience.

[0638] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0639] In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; means for recognizing the user's emotions using a camera and microphone built into the user's terminal; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; means for the generative AI model to recognize the user's emotions and adjust the tone and expression of the notification text; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to receive only the information they need, and the notification text adapts to the user's emotions in real time, providing a personalized user experience.

[0640] An "avatar" is a virtual character that a user creates to visually represent themselves and customize their appearance and clothing.

[0641] "Tone and expression of notification text" refers to settings such as how notification messages are written and their style, the choice of words used, and the use of emoticons.

[0642] "Notification settings" refers to settings for customizing the types of notifications and filtering conditions that a user wants to receive for each application.

[0643] "Camera and microphone" refers to hardware devices used to sense a user's facial expressions and tone of voice and recognize emotions.

[0644] A "server" is a computer system that receives and processes data from multiple users and transmits the necessary information to the users' terminals.

[0645] "Filtering" refers to the process in which the server removes unnecessary data from the received notification data and selects only the necessary data based on the user's settings.

[0646] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate notification text based on a user's settings and preferences.

[0647] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to recognize the user's current emotional state.

[0648] "Notification text" refers to a message sent to a user, generated by filtering or a generative AI model.

[0649] A "user's device" is a device used by a user, such as a smartphone, tablet, or computer, that has the ability to receive and display notifications.

[0650] "Emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to estimate the emotions the user is currently feeling.

[0651] The system of the present invention provides a way for users to receive personalized and customized notifications. The main elements of the system include a user device, a server, and a generative AI model.

[0652] User Preferences

[0653] First, the user installs a dedicated application on their device. Then, the user launches the application and accesses the avatar creation screen. Here, the user customizes the character's appearance and clothing to create an avatar. The completed avatar information is sent to the server and stored in a database.

[0654] Next, the user is taken to a screen where they can set the tone and expression of the notification text. For example, they can choose the notification style (casual, formal, humorous) and specify the type of emojis to use. These settings are sent to the server and stored for each user.

[0655] Additionally, users can customize notification settings for each application, for example, to receive only sports-related notifications in a news app, or all notifications in a social networking app, which are also stored on the server.

[0656] Emotion Engine Settings

[0657] The user's device is equipped with a built-in camera and microphone, which are used to initialize the emotion engine. The user makes various facial expressions and speaks in different tones in front of the camera to collect data that the system uses to recognize the user's emotions. This data is sent to the server, where the user's basic emotional patterns are recorded.

[0658] Sending and filtering notifications

[0659] When a specific condition is met, each application generates a notification and sends the notification data to the server. The server receives this notification data and filters out unnecessary notifications based on the user's filter settings. For notifications that pass the filter, the generative AI model generates text tailored to the user's preferences.

[0660] The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text. For example, if the user is feeling down, the generative AI model will add an encouraging message.

[0661] Notification presentation

[0662] The server sends the generated notification text and avatar information to the user's device. It also sends information to adjust the avatar's facial expressions and movements based on the latest emotional data. The user's device displays the received notification data, and the avatar changes its facial expressions and movements to match the user's emotions while displaying the notification text. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0663] Specific examples

[0664] As an example of a real user configuration, a user can create an avatar, set notification style to casual, set to frequently use emojis, set to receive only sports-related notifications in a news app, and receive all notifications in a social networking app.

[0665] For example, you can use prompts like the following to feed a generative AI model:

[0666] "Generate a notification message for when the user is happy. The message is about sports news."

[0667] This specific embodiment allows users to receive personalized notifications in real time, and the system can present notifications in a way that reflects the user's emotions, greatly improving the user experience.

[0668] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0669] Program processing flow

[0670] Step 1:

[0671] The user installs the dedicated application on their device. The user downloads the application from the App Store or Google Play Store and installs it. The application performs initial setup and displays a screen prompting the user to create an avatar.

[0672] Input: App download request from App Store or Google Play Store

[0673] Output: Installed dedicated application

[0674] Step 2:

[0675] The user goes to the avatar creation screen and customizes the character's appearance and clothing. The user selects each part, such as the head, hairstyle, clothing, and accessories, to complete the customization. The completed avatar information is sent to the server.

[0676] Input: Information about the avatar parts selected by the user

[0677] Output: Avatar information stored on the server

[0678] Step 3:

[0679] The user accesses the notification text settings screen and selects the notification style (casual, formal, humorous, etc.) and the type of emoji. These settings are sent to the server.

[0680] Input: Notification style and emoji type

[0681] Output: Notification settings saved on the server

[0682] Step 4:

[0683] The user goes to a screen where they can customize notification settings for each application and select the types of notifications they want to receive. The settings are then sent to the server.

[0684] Input: Notification filter settings for each application

[0685] Output: Notification settings for each application stored on the server

[0686] Step 5:

[0687] The user's device activates the camera and microphone to collect the user's facial expressions and tone of voice, which initializes the emotion engine so that it can recognize the user's emotions. The initialization data is then sent to the server.

[0688] Input: User's facial expressions and tone of voice

[0689] Output: Emotion recognition data stored on the server

[0690] Step 6:

[0691] Each application generates a notification when a specific condition is met and sends the notification data to the server.

[0692] Input: Application-generated notification data

[0693] Output: Notification data sent to the server

[0694] Step 7:

[0695] The server receives notification data sent from the application and filters notifications based on the user's settings, removing unnecessary notifications and selecting only necessary notifications.

[0696] Input: Notification data sent to the server

[0697] Output: Filtered notification data

[0698] Step 8:

[0699] The generative AI model generates text tailored to the user's preferences from the notification data that passes the filter. The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text.

[0700] Input: filtered notification data, user emotion data

[0701] Output: A customized notification text generated by the generative AI model

[0702] Step 9:

[0703] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's latest emotional data.

[0704] Input: Generated notification text, avatar information, user emotion data

[0705] Output: Notification data sent to the user's device

[0706] Step 10:

[0707] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0708] Input: Notification data received from the server

[0709] Output: Displaying an emotion-adaptive notification

[0710] (Application example 2)

[0711] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0712] In modern virtual stores, personalizing and enhancing the user experience is an important challenge. In particular, providing notifications based on the user's emotions can increase user engagement and boost purchasing motivation. However, existing systems lack the means to recognize the user's emotions in real time and adjust the notification content and avatar display based on those emotions, making it difficult to provide a personalized experience.

[0713] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generation AI to generate text tailored to the user's preferences for necessary notifications; emotion recognition means for recognizing the user's emotions and adjusting the notification text based on the emotions; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This makes it possible to adjust the notification text according to the user's emotions and provide a personalized experience.

[0714] An "avatar" is a digital character that a user creates to represent themselves within a virtual environment.

[0715] A "notification" is information or a message sent from each application to the user.

[0716] "Generative AI" is an artificial intelligence system that automatically generates text based on the user's settings and preferences.

[0717] "Emotion recognition" is a technology that analyzes a user's facial expressions and tone of voice to detect their emotional state at that time.

[0718] "Filtering" is the process by which the server cuts out unnecessary notifications based on the user's settings and selects only the necessary notifications.

[0719] The "server" is a central management system that manages user settings and notification data, and receives, filters, and sends notifications from each application.

[0720] A "terminal" is a device used by a user, such as a smartphone, tablet, or computer.

[0721] A "personalized experience" is a user experience that is customized to fit the individual preferences and feelings of each user.

[0722] System Overview

[0723] This invention is a system for a virtual store that senses user emotions and generates and displays personalized notifications. It mainly consists of the following elements:

[0724] 1. How users create their own avatar: Using a device (smartphone, tablet, computer), users create a digital character that represents them in a virtual environment.

[0725] 2. A means for users to set the tone and expression of notification text: Users use their devices to customize the tone (casual, formal, etc.) and expression (use of emojis, etc.) of notification text.

[0726] 3. A way for users to customize notification settings for each application: Users customize the types of notifications they want to receive from specific applications.

[0727] 4. Emotion recognition means: Using the device's built-in camera and microphone, the device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0728] 5. Means for the generative AI to generate text tailored to the user's preferences: The server uses the generative AI model to generate text tailored to the user's preferences for the filtered notifications.

[0729] 6. A means for the server to filter notifications based on user settings and cut out unnecessary notifications: Receive notifications from each application and filter out unnecessary notifications based on user settings.

[0730] 7. Server means for transmitting the generated notification text to the user's terminal: The filtered notification text is transmitted to the user's terminal.

[0731] 8. Means for the user's device to display the notification text: The user's device displays the generated notification text, and the avatar presents the notification with facial expressions and movements that correspond to the emotion.

[0732] Hardware and Software Details

[0733] Hardware:

[0734] Smartphones, tablets, computers (user devices)

[0735] Camera and microphone (for emotion recognition)

[0736] software:

[0737] Generative AI model: Hugging Face natural language processing model

[0738] Emotion Recognition Software: Hugging Face's Sentiment-Analysis Pipeline

[0739] Server system: A server that receives, filters, and sends notifications

[0740] Explanation of the processing flow

[0741] 1. User creates an avatar:

[0742] Using an application on the device, users create an avatar, which is used to represent them within the virtual store and provide a personalized experience.

[0743] 2. Notification text settings:

[0744] Users can set their preferences for the tone and expression of notifications from a screen where they can choose things like a casual tone and the inclusion of emojis.

[0745] 3. Customize your notification settings:

[0746] Users customize the types of notifications they receive from each application, for example, they can receive only news notifications from certain categories.

[0747] 4. Initialize emotion recognition:

[0748] The user's device uses a camera and microphone to recognize the user's emotions, performing initial setup and training models to analyze facial expressions and tone of voice.

[0749] 5. Notification Generation and Filtering:

[0750] Notifications are received from each application and filtered by the server based on the user's settings. Only the filtered notifications are processed by the generative AI model to create notification text tailored to the user's preferences.

[0751] 6. Sending and Displaying Notifications:

[0752] The generated notification text is sent from the server to the user's device, where it is displayed by the avatar, who then displays the text and makes facial expressions and movements according to the user's emotions.

[0753] Specific examples

[0754] User state: The camera captures your face and the microphone records your voice when you are using the device.

[0755] Emotion recognition result: The user is recognized as happy.

[0756] Generated notification: "🌟Announcement from your virtual store🌟Check out our new arrivals!"

[0757] Prompt Sentence Examples

[0758] Prompt: "Generate a message to keep the user happy and notify him of new products."

[0759] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0760] Step 1:

[0761] The user creates an avatar. Using an application on their device, the user creates a digital character (avatar) to represent themselves. As input, the user selects appearance, clothing, accessories, etc., and as output, the avatar information is generated and stored on the server. This avatar is later used to display notifications.

[0762] Step 2:

[0763] The user configures the tone and expression of the notification text. Using the device, the user accesses a screen that allows them to customize the tone (e.g., casual, formal) and expression (e.g., type of emoji) of the notification text. User preferences are provided as input, and the configuration information is saved on the server as output.

[0764] Step 3:

[0765] Users customize notification settings for each application. Users can finely customize notification settings from news apps, social networking apps, etc., by setting the types of notifications they want to receive and filter conditions. Notification setting information for each application is provided as input, and individual settings are saved on the server as output.

[0766] Step 4:

[0767] Initialize emotion recognition. The emotion recognition model is calibrated and initialized using the camera and microphone built into the user's device. Data captured from the user's facial expressions and tone of voice is used as input, and emotion recognition model parameters are set as output.

[0768] Step 5:

[0769] The server receives notifications from each application. The server receives notification data sent from different applications in a unified manner. Notification data is sent to the server as input and accumulated on the server as output.

[0770] Step 6:

[0771] The server filters notifications. It filters the received notification data based on the user's pre-defined settings and cuts out unnecessary notifications. It takes raw notification data as input and provides filtered notification data as output.

[0772] Step 7:

[0773] The generation AI generates notification text. For the filtered notifications, the generation AI generates text tailored to the user's preferences. The filtered notification data and user settings are provided as input, and customized notification text is created as output.

[0774] Step 8:

[0775] The device performs emotion recognition. It analyzes the user's facial expressions and voice in real time to recognize their current emotional state. Real-time data from the camera and microphone is used as input, and emotion recognition results are obtained as output.

[0776] Step 9:

[0777] The server adjusts the notification text. Based on the emotion recognition results, the server adjusts the already generated notification text according to the user's emotion. The generated notification text and the emotion recognition results are provided as input, and the adjusted notification text is obtained as output.

[0778] Step 10:

[0779] The server sends the adjusted notification text and avatar information to the terminal. The server sends the adjusted notification text and avatar information according to the emotion to the user's terminal. The adjusted notification text and avatar information are provided as input, and the data is sent to the terminal as output.

[0780] Step 11:

[0781] The device displays the notification text. The user's device displays the adjusted notification text along with the avatar's facial expressions and movements. The adjusted notification text and avatar information are provided as input, and the notification is displayed as output.

[0782] Prompt Sentence Examples

[0783] Prompt: "Generate a message to keep the user happy and notify him of new products."

[0784] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0785] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0786] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0787] [Third embodiment]

[0788] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0789] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0790] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0791] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0792] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0793] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0794] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0795] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0796] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0797] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0798] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0799] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0800] User Preferences

[0801] 1. Create an avatar

[0802] Users install a specific application on their smartphone, tablet, or other device. When they open the application, they are guided to a screen where they can create their own avatar. Here, they can freely customize their character's appearance, clothing, and other aspects.

[0803] 2. Setting up the generated AI

[0804] The user is then taken to a screen where they can set the tone and expression of the notification text to the AI ​​generator. Here, they can set the style of the notification (e.g., casual, formal, humorous, etc.) and the type of emojis and emoticons to use.

[0805] 3. Notification filtering settings

[0806] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This setting information is stored on the server.

[0807] Sending and filtering notifications

[0808] 4. Notification Occurrence

[0809] Each application (e.g., news app, SNS app, etc.) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[0810] 5. Receiving and filtering notifications

[0811] The server receives notification data sent from the application. The received notification data is evaluated based on the filter settings for each user. The server cuts out notifications that the user deems unnecessary and selects only important notifications. This filtering process leaves only the notification information that is valuable to the user.

[0812] 6. Notification Text Generation

[0813] For notifications that pass the filter, the AI ​​generates notification text that matches the user's preferences. For example, if the user has selected a casual style, the AI ​​generates a text such as "⚽New sports news!"

[0814] Notification presentation

[0815] 7. Sending Notifications

[0816] The server sends the generated notification text and necessary metadata (such as the user's avatar information) to the user's device.

[0817] 8. Display of notifications

[0818] The user's device receives the notification data sent from the server. The device displays the notification using the user's avatar along with the notification text. For example, if the user is using the Zepeto app, the avatar displays a notification saying "⚽New sports news!"

[0819] Specific examples

[0820] User configuration example

[0821] User name: Sato-san

[0822] Avatar Creation: Sato created a casually dressed character as his avatar.

[0823] Generator AI settings: Sato set the tone of notifications to a casual style and specified that emojis be used frequently.

[0824] Notification filter settings: Sato set his news app to receive "only sports-related notifications" and his social media app to receive "all notifications."

[0825] Notification processing example

[0826] Notification occurs: The news app generates "sports-related news" and sends it to the server.

[0827] Receiving and filtering notifications: The server receives the notification data and determines that "sports related news" is the notification that needs to be sent.

[0828] Notification text generation: The AI ​​generates casual notification text such as "⚽There's new sports news!"

[0829] Sending notification: The server sends the generated notification text and avatar information to Mr. Sato's device.

[0830] Displaying the notification: Sato's device receives a notification and his avatar displays "⚽New sports news!"

[0831] This embodiment frees users from annoying notifications and allows them to receive valuable information tailored to their preferences without stress.

[0832] The processing flow will be explained below.

[0833] Step 1:

[0834] User: Install the application on the device and enter the avatar creation screen. Freely set the avatar's appearance, clothing, hairstyle, etc. Once complete, save the avatar information.

[0835] Step 2:

[0836] User: Go to the AI ​​generation settings screen and customize the tone and expression of the notification text. For example, choose a casual tone and a preference for using lots of emojis. This setting is saved on the server.

[0837] Step 3:

[0838] User: Go to the notification filtering settings screen for each application. Here, for example, you can set a news app to only receive sports-related notifications, and a social media app to receive all notifications. The settings are sent to the server and saved.

[0839] Step 4:

[0840] Each application generates a notification when a condition is met and sends the notification data to the server. The notification data includes the type, content, and time of the notification.

[0841] Step 5:

[0842] Server: Receives notification data sent from applications. Evaluates received notifications based on each user's filter settings and filters out unnecessary notifications. For example, if a "political news notification" is received, it is determined to be unnecessary based on the user's settings and is filtered out.

[0843] Step 6:

[0844] Server: For notifications that pass the filter, the AI ​​generates notification text tailored to the user's preferences. For example, if a sports-related news notification passes the filter, the AI ​​creates a casual text such as "⚽There's new sports news!"

[0845] Step 7:

[0846] Server: The server sends the generated notification text and avatar information to the user's device. The notification data includes the notification content, the application that generated it, the user ID, etc.

[0847] Step 8:

[0848] Device: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, the avatar displays "⚽New sports news!" through the Zepeto app.

[0849] Through this series of steps, users can customize their notification environment and receive only the information that matters to them without being overwhelmed with unnecessary notifications.

[0850] Example 1

[0851] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0852] Currently, users receive many notifications from multiple software applications, which can lead to users missing important notifications. Furthermore, the content and style of notifications often do not suit users' preferences, causing users to find them annoying. This reduces the efficiency of notifications and impairs the user experience.

[0853] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0854] In this invention, the server includes: means for a user to create their own character; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each software application; server means for receiving notifications from each software application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to easily check only important information, freeing them from annoying notifications and providing a comfortable user experience.

[0855] A "character" is an avatar, such as a virtual person or animal, that a user creates to represent themselves.

[0856] A "notification text" is a text message that is generated based on specific conditions and sent to the user.

[0857] A "generative AI model" is an artificial intelligence algorithm that generates notification text based on user settings.

[0858] "Software applications" are programs used by users, such as news apps and social networking apps.

[0859] A "server" is a computer system that receives notification data from an application and performs processing based on user settings.

[0860] "Filtering" is a process that removes notifications that the user deems unnecessary and selects only important notifications.

[0861] A "terminal" is a device used by a user, such as a smartphone or tablet.

[0862] "Metadata" is supplementary data such as user avatar information that accompanies the notification text.

[0863] This system allows users to efficiently manage notifications from multiple software applications and receive them in a format that suits their preferences. The system is primarily composed of a user's device, a server, and a generative AI model.

[0864] First, the user installs a specific application on their device. When they open the application, they are guided to a screen where they can create a character. Here, the user can freely customize the character's appearance and clothing. For example, the user can choose hairstyle and clothing color to determine the character's detailed appearance.

[0865] Next, users are taken to a screen where they can set the tone and expression of the notification text. They can choose the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. Users can do this by using drop-down menus and sliders.

[0866] Users are then taken to a screen where they can customize notification settings for each software application: for a news app, they can choose to receive only sports-related notifications, and for a social networking app, they can choose to receive all notifications. This setting information is then stored on the server.

[0867] Notifications from each software application are generated when certain conditions are met and sent to a server. For example, a news application generates sports-related news and sends it to a server. The server evaluates the received notification data based on the filter settings for each user. Unnecessary notifications are cut out, and only important notifications are selected.

[0868] For the filtered notifications, the server uses a generative AI model to generate sentences tailored to the user's preferences. If the user selects a casual style, a notification sentence such as "⚽There's new sports news!" is generated. An example of a prompt sentence is "Please tell me how to filter sports-related notifications generated by a news app and send them to the user in a casual tone."

[0869] The generated notification text and necessary metadata (such as the user's character information) are sent from the server to the user's device. In response, the user's device displays the notification text. In this case, the character displays a notification saying, "⚽There's new sports news!" Notifications are generally displayed in a pop-up format.

[0870] This embodiment allows users to be freed from annoying notifications and receive valuable information tailored to their preferences without stress. The system realizes efficient notification management and improves the user experience.

[0871] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0872] Step 1:

[0873] Users install a specific application on their device and open the avatar creation screen. They customize the character's appearance and clothing. Input includes information such as the user's chosen hairstyle and clothing color, and the avatar's appearance data is generated based on this information.

[0874] Step 2:

[0875] The user navigates to a page where they can set the tone and expression of their notification text. Here, they select the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons they want to use. The input is the user's notification style and emoji settings, and the output is the saved settings.

[0876] Step 3:

[0877] The user navigates to a page where they can customize notification settings for each software application. The input is the user's notification filter settings (e.g., "only receive sports-related notifications"), which are sent to the server and stored. The output is notification filter settings for each application.

[0878] Step 4:

[0879] Each software application generates a notification when a certain condition is met. For example, a news app generates a sports-related news item and sends the notification data to a server. The input is the generated notification data, and the output is the notification data received by the server.

[0880] Step 5:

[0881] The server evaluates the notification data it receives based on the filter settings for each user. Specifically, the server references the user's settings information stored in a database and cuts out unnecessary notifications. The input is the received notification data and the user's filter settings, and the output is the filtered important notification data.

[0882] Step 6:

[0883] The server uses a generative AI model to generate notification text for the filtered notification data. The input is the filtered notification data and the user's notification style settings, and the output is the generated notification text. For example, if the user selects a casual style, the generated notification text will read, "⚽There's new sports news!"

[0884] Step 7:

[0885] The server sends the generated notification text and necessary metadata (e.g., user avatar information) to the user's device. The input is the generated notification text and avatar data, and the output is the sent notification packet.

[0886] Step 8:

[0887] The user's device receives the notification data sent from the server. The device displays the notification text in a pop-up format, and the user's avatar presents the notification. The input is the notification data received from the server, and the output is the notification text displayed on the screen. The notification is displayed in the form of "⚽There is new sports news!"

[0888] (Application example 1)

[0889] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0890] Conventional notification systems lack sufficient notification filtering and customization based on user interests and preferences, and the wide range of information they provide can be distracting. Furthermore, notification text is often boring and unattractive, making it difficult to attract users' attention. Furthermore, notification content is often simply displayed as text, which is often counterintuitive.

[0891] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0892] In this invention, the server includes a means for the user to create their own avatar, a means for the user to set the tone and expression of the notification text, and a means for the user to customize the notification settings for each application. This allows the generation AI to generate text tailored to the user's preferences, increasing interest in necessary notifications while minimizing annoyance. In addition, displaying customized notification text using the user's avatar provides intuitive and attractive notifications.

[0893] "Means for users to create their own avatar" refers to a function that allows users to create and customize a character that will represent their own identity.

[0894] The "means for the user to set the tone and expression of the notification text" is a function that allows the user to individually set the style and expression of the notification text that they receive.

[0895] "Means for users to customize notification settings for each application" refers to a function that allows users to individually set notification content and reception conditions for each application they use.

[0896] The "server means for receiving notifications from each application" is a server-side function for aggregating and receiving notification data sent from a plurality of applications.

[0897] "Means for the server to filter notifications based on user settings and cut out unnecessary notifications" is a function that allows the server to sort the notification data received according to the user's settings and delete notifications that are deemed unnecessary.

[0898] "Means for the generation AI to generate text tailored to the user's preferences for required notifications" is a function that enables the generation AI to create customized notification text based on the user's preferences and settings, based on filtered notifications.

[0899] "Server means for transmitting the generated notification text and associated metadata to the user's terminal" is a server-side function for transferring the generated notification text and associated data to the user's terminal.

[0900] The "means for the user's terminal to display the notification text" is a function for visually displaying the notification text on the user's terminal.

[0901] "Means for filtering notifications that are limited to the user's interests and for the generation AI to generate customized text for specific notifications" refers to a function that selects notifications based on the user's interests and allows the generation AI to create customized text for the content of the selected notifications.

[0902] The "means for displaying a customized notification text using a user's avatar" is a function for displaying a specific customized notification text using a user's avatar.

[0903] A system for implementing the invention includes the following elements:

[0904] 1. User Initial Settings

[0905] Creating an avatar

[0906] Users install the application on their devices (smartphones, tablets, etc.). When they open the application, they are guided to an avatar creation screen where they can freely customize the appearance and clothing of their character.

[0907] Notification text settings

[0908] The user is taken to a screen where they can set the tone and expression of the notification text. They can set the style of the notification (casual, formal, humorous, etc.) and the type of emojis or emoticons to use.

[0909] Configuring Notification Filtering

[0910] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This information is stored on the server.

[0911] 2. Sending and filtering notifications

[0912] Notification occurs

[0913] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[0914] Receiving and filtering notifications

[0915] The server receives notification data sent from applications. The received notification data is evaluated based on the filter settings for each user, and unnecessary notifications are cut out and only valuable notifications are selected.

[0916] Notification text generation

[0917] For notifications that pass the filter, the generative AI model generates notification text that matches the user's preferences. For example, if the user has chosen a casual style, a notification such as "⚽New sports news!" will be generated.

[0918] 3. Notification

[0919] Sending notifications

[0920] The server sends the generated notification text and related metadata (such as avatar information) to the user's device.

[0921] Viewing notifications

[0922] The user's device receives the notification data sent from the server and displays the notification text on the device. The notification text is displayed using the user's avatar, making the notification visually appealing.

[0923] Component Description

[0924] server

[0925] The server is responsible for receiving, evaluating, and filtering notification data, and generating notification text using a generative AI model. This includes a server (e.g., Flask, Django) for processing HTTP requests and a generative AI model (e.g., GPT-3).

[0926] User terminal

[0927] The user terminal is a smartphone, tablet, or the like, and receives notification data sent from the server and displays the notification using an avatar.

[0928] Specific examples

[0929] Example 1

[0930] If a user wants to receive notifications in the "Fashion" category, they can select "Fashion" in the settings screen and set the notification style to "Casual." This will cause the generative AI model to generate casual-style notification text.

[0931] Prompt Sentence Example 1

[0932] Consider a generated AI response to "New sales information has arrived in the fashion category."

[0933] Example 2

[0934] If a user has chosen not to receive notifications in the "Electronic Devices" category, the server will filter notifications in that category and not send them to the user.

[0935] Prompt Sentence Example 2

[0936] Ignore the "New items in stock in the electronics category."

[0937] This system allows users to receive only the information they are interested in, making it easy to get important information without feeling distracted. The use of avatars also makes notifications visually appealing, improving the user experience.

[0938] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0939] Step 1:

[0940] A user installs the application on their device and opens it. They are then guided to the avatar creation screen to create their own character. This step takes as input the user's choices (appearance, clothing) and generates as output a customized avatar.

[0941] Step 2:

[0942] The user is taken to a screen where they can set the tone and expression of the notification text. At this stage, the user sets the style of the notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. The user's settings are the input, and the settings data is saved as the output.

[0943] Step 3:

[0944] The user is taken to a screen where they can customize notification settings for each application. For example, for a news app, the user sets the notification categories they want to receive (e.g., sports, politics). The input is the user's notification settings, and the output is the notification filter settings, which are saved on the server.

[0945] Step 4:

[0946] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met and sends the notification data to the server. The input is the notification data of each application, and the output is stored on the server.

[0947] Step 5:

[0948] The server evaluates the received notification data and filters it based on the user's settings. The server analyzes the notification data and cuts out notifications that the user deems unnecessary. The input is the notification data stored on the server and the user's filter settings, and the output is the filtered notification data.

[0949] Step 6:

[0950] For notification data that passes filtering, the server uses a generative AI model to generate notification text tailored to the user's preferences. Style settings such as "casual" or "formal" are input into the generative AI model, and customized notification text is obtained as output. For example, the generated text for the prompt "New sale information for the fashion category has arrived" is "A new fashion sale has started!"

[0951] Step 7:

[0952] The server sends the generated notification text and related metadata (e.g., avatar information) to the user's device. The generated notification text and metadata are input, and are sent to the user's device as output.

[0953] Step 8:

[0954] The user's device receives the notification data sent from the server and displays the notification text on the device. At this time, an avatar is also displayed to make the notification visually appealing. The input is the notification data received from the server, and the output is the notification displayed on the device screen.

[0955] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0956] User Preferences

[0957] 1. Create an avatar

[0958] Users install a specific application on their smartphone, tablet, or other device and navigate to the avatar creation screen. Here, users can customize their character's appearance and clothing. Once the avatar creation is complete, the avatar information is saved on the server.

[0959] 2. Setting up the generated AI

[0960] The user is taken to a screen where they can set the tone and expression of the notification text, select the notification style (casual, formal, humorous, etc.) and the type of emoji, and save the settings to the server.

[0961] 3. Notification filtering settings

[0962] The user navigates to the notification filtering settings screen for each application, where they can set the news app to only receive sports-related notifications and the social networking app to receive all notifications. These settings are then stored on the server.

[0963] Emotion Engine Settings

[0964] 4. Initializing the Emotion Engine

[0965] The emotion engine is initialized using the camera and microphone built into the user's device. Based on the user's facial expressions and tone of voice, the emotion engine is adjusted to recognize the user's emotions.

[0966] Sending and filtering notifications

[0967] 5. Notification Occurrence

[0968] When a condition is met, each application generates a notification and sends the notification data to the server, including the type of notification and the time of occurrence.

[0969] 6. Receiving and filtering notifications

[0970] The server receives notification data sent from the application and evaluates the notifications based on the user's filter settings. Unnecessary notifications are cut off and only necessary notifications remain.

[0971] 7. Notification Text Generation

[0972] For notifications that pass the filter, the AI ​​generator generates notification text tailored to the user's preferences. Furthermore, the emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the notification text accordingly. For example, if the user is feeling down, an encouraging message can be added.

[0973] Notification presentation

[0974] 8. Sending Notifications

[0975] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's emotional data.

[0976] 9. Display of notifications

[0977] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[0978] Specific examples

[0979] User configuration example

[0980] User name: Kato-san

[0981] Avatar creation: Kato creates an avatar in casual clothing and saves it on the server.

[0982] Generative AI settings: We set the tone of notifications to be casual and specified frequent use of emojis.

[0983] Notification filter settings: Set your news app to only receive sports-related notifications, and your social media apps to receive all notifications.

[0984] Emotion engine setting example

[0985] Emotion engine initialization: Kato's device was initialized to recognize Kato's emotions using the camera and microphone.

[0986] Notification processing example

[0987] Notification occurs: A news app generates sports-related news and sends it to the server.

[0988] Receiving and filtering notifications: The server receives notification data and selects the required notifications based on the filter settings.

[0989] Notification text generation: The AI ​​generates a casual text like "⚽There's new sports news!" The emotion engine recognizes the user's emotion as "joy" and adds more positive expressions.

[0990] Notification presentation example

[0991] Sending notification: The server sends the generated notification text, avatar information, and emotion data to Kato's device.

[0992] Displaying a notification: Kato's device receives a notification and his avatar displays a smiling message saying, "⚽There's new sports news!"

[0993] This specific embodiment allows users to receive notifications that are adapted to their emotions in real time, providing a more personalized user experience.

[0994] The processing flow will be explained below.

[0995] Step 1:

[0996] User: Installs the application on the device and goes to the avatar creation screen. The user can freely set the avatar's appearance, clothing, hairstyle, skin color, etc. The completed avatar information is sent to the server and saved.

[0997] Step 2:

[0998] User: Go to the generated AI settings screen and customize the tone and expression of the notification text. For example, select a casual style and a preference for using lots of emojis. The settings are sent to the server and saved.

[0999] Step 3:

[1000] User: Go to the notification filtering settings screen for each application. For example, in a news app, set "Receive only sports-related notifications," and in a social networking app, set "Receive all notifications." These settings are sent to the server and saved.

[1001] Step 4:

[1002] User: Initializes the emotion engine using the device's built-in camera and microphone. The emotion engine is adjusted to recognize the user's facial expressions and tone of voice. This setting is managed by the server.

[1003] Step 5:

[1004] Each application generates a notification when a specific condition is met and sends the notification data to the server. The notification data includes information such as the type of notification, its content, and the time of occurrence.

[1005] Step 6:

[1006] Server: Receives notification data sent from the application. The server evaluates notifications based on the filter settings for each user and cuts out unnecessary notifications. For example, if a "political news notification" is determined to be unnecessary, the notification will be discarded.

[1007] Step 7:

[1008] Server: For notifications that pass the filter, the generation AI generates notification text tailored to the user's preferences. In addition, the emotion engine recognizes the user's emotions and adjusts the tone and expression of the notification text based on those emotions. For example, if the user is feeling down, it adds an encouraging message.

[1009] Step 8:

[1010] Server: The server sends the generated notification text, avatar information, and emotion data to the user's device, including the notification content, the application from which it originated, and the user ID.

[1011] Step 9:

[1012] Terminal: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, if the user is happy, the avatar will display the notification with a smiling face.

[1013] Examples:

[1014] Example user settings: Takahashi created an avatar with casual clothing and hairstyle, and selected a casual tone of voice and a style that makes heavy use of emojis in the AI ​​generation settings. He also set the news app to receive "sports-related notifications only" and the social media app to receive all notifications.

[1015] Emotion engine configuration example: The emotion engine was initialized to recognize Takahashi's emotions using the device's camera and microphone.

[1016] Example of notification processing: A news app generates sports-related news and sends it to the server. The server receives and filters the notifications, and the generation AI generates a casual sentence such as "⚽There's new sports news!". The emotion engine recognizes Takahashi's emotion as "joy" and adds a more positive expression. The notification is sent to Takahashi's device, and the avatar displays the notification with a smiling face.

[1017] Example 2

[1018] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1019] Conventional notification systems have the problem that it is difficult for users to receive only the information they need, and the notification language is uniform, making it impossible to provide a personalized user experience. In addition, the notification text does not adapt to the user's emotions, which reduces the value of the notifications received by the user and does not improve the user experience.

[1020] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1021] In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; means for recognizing the user's emotions using a camera and microphone built into the user's terminal; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; means for the generative AI model to recognize the user's emotions and adjust the tone and expression of the notification text; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to receive only the information they need, and the notification text adapts to the user's emotions in real time, providing a personalized user experience.

[1022] An "avatar" is a virtual character that a user creates to visually represent themselves and customize their appearance and clothing.

[1023] "Tone and expression of notification text" refers to settings such as how notification messages are written and their style, the choice of words used, and the use of emoticons.

[1024] "Notification settings" refers to settings for customizing the types of notifications and filtering conditions that a user wants to receive for each application.

[1025] "Camera and microphone" refers to hardware devices used to sense a user's facial expressions and tone of voice and recognize emotions.

[1026] A "server" is a computer system that receives and processes data from multiple users and transmits the necessary information to the users' terminals.

[1027] "Filtering" refers to the process in which the server removes unnecessary data from the received notification data and selects only the necessary data based on the user's settings.

[1028] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate notification text based on a user's settings and preferences.

[1029] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to recognize the user's current emotional state.

[1030] "Notification text" refers to a message sent to a user, generated by filtering or a generative AI model.

[1031] A "user's device" is a device used by a user, such as a smartphone, tablet, or computer, that has the ability to receive and display notifications.

[1032] "Emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to estimate the emotions the user is currently feeling.

[1033] The system of the present invention provides a way for users to receive personalized and customized notifications. The main elements of the system include a user device, a server, and a generative AI model.

[1034] User Preferences

[1035] First, the user installs a dedicated application on their device. Then, the user launches the application and accesses the avatar creation screen. Here, the user customizes the character's appearance and clothing to create an avatar. The completed avatar information is sent to the server and stored in a database.

[1036] Next, the user is taken to a screen where they can set the tone and expression of the notification text. For example, they can choose the notification style (casual, formal, humorous) and specify the type of emojis to use. These settings are sent to the server and stored for each user.

[1037] Additionally, users can customize notification settings for each application, for example, to receive only sports-related notifications in a news app, or all notifications in a social networking app, which are also stored on the server.

[1038] Emotion Engine Settings

[1039] The user's device is equipped with a built-in camera and microphone, which are used to initialize the emotion engine. The user makes various facial expressions and speaks in different tones in front of the camera to collect data that the system uses to recognize the user's emotions. This data is sent to the server, where the user's basic emotional patterns are recorded.

[1040] Sending and filtering notifications

[1041] When a specific condition is met, each application generates a notification and sends the notification data to the server. The server receives this notification data and filters out unnecessary notifications based on the user's filter settings. For notifications that pass the filter, the generative AI model generates text tailored to the user's preferences.

[1042] The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text. For example, if the user is feeling down, the generative AI model will add an encouraging message.

[1043] Notification presentation

[1044] The server sends the generated notification text and avatar information to the user's device. It also sends information to adjust the avatar's facial expressions and movements based on the latest emotional data. The user's device displays the received notification data, and the avatar changes its facial expressions and movements to match the user's emotions while displaying the notification text. For example, if the user is happy, the avatar will display the notification with a smiling face.

[1045] Specific examples

[1046] As an example of a real user configuration, a user can create an avatar, set notification style to casual, set to frequently use emojis, set to receive only sports-related notifications in a news app, and receive all notifications in a social networking app.

[1047] For example, you can use prompts like the following to feed a generative AI model:

[1048] "Generate a notification message for when the user is happy. The message is about sports news."

[1049] This specific embodiment allows users to receive personalized notifications in real time, and the system can present notifications in a way that reflects the user's emotions, greatly improving the user experience.

[1050] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1051] Program processing flow

[1052] Step 1:

[1053] The user installs the dedicated application on their device. The user downloads the application from the App Store or Google Play Store and installs it. The application performs initial setup and displays a screen prompting the user to create an avatar.

[1054] Input: App download request from App Store or Google Play Store

[1055] Output: Installed dedicated application

[1056] Step 2:

[1057] The user goes to the avatar creation screen and customizes the character's appearance and clothing. The user selects each part, such as the head, hairstyle, clothing, and accessories, to complete the customization. The completed avatar information is sent to the server.

[1058] Input: Information about the avatar parts selected by the user

[1059] Output: Avatar information stored on the server

[1060] Step 3:

[1061] The user accesses the notification text settings screen and selects the notification style (casual, formal, humorous, etc.) and the type of emoji. These settings are sent to the server.

[1062] Input: Notification style and emoji type

[1063] Output: Notification settings saved on the server

[1064] Step 4:

[1065] The user goes to a screen where they can customize notification settings for each application and select the types of notifications they want to receive. The settings are then sent to the server.

[1066] Input: Notification filter settings for each application

[1067] Output: Notification settings for each application stored on the server

[1068] Step 5:

[1069] The user's device activates the camera and microphone to collect the user's facial expressions and tone of voice, which initializes the emotion engine so that it can recognize the user's emotions. The initialization data is then sent to the server.

[1070] Input: User's facial expressions and tone of voice

[1071] Output: Emotion recognition data stored on the server

[1072] Step 6:

[1073] Each application generates a notification when a specific condition is met and sends the notification data to the server.

[1074] Input: Application-generated notification data

[1075] Output: Notification data sent to the server

[1076] Step 7:

[1077] The server receives notification data sent from the application and filters notifications based on the user's settings, removing unnecessary notifications and selecting only necessary notifications.

[1078] Input: Notification data sent to the server

[1079] Output: Filtered notification data

[1080] Step 8:

[1081] The generative AI model generates text tailored to the user's preferences from the notification data that passes the filter. The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text.

[1082] Input: filtered notification data, user emotion data

[1083] Output: A customized notification text generated by the generative AI model

[1084] Step 9:

[1085] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's latest emotional data.

[1086] Input: Generated notification text, avatar information, user emotion data

[1087] Output: Notification data sent to the user's device

[1088] Step 10:

[1089] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[1090] Input: Notification data received from the server

[1091] Output: Displaying an emotion-adaptive notification

[1092] (Application example 2)

[1093] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1094] In modern virtual stores, personalizing and enhancing the user experience is an important challenge. In particular, providing notifications based on the user's emotions can increase user engagement and boost purchasing motivation. However, existing systems lack the means to recognize the user's emotions in real time and adjust the notification content and avatar display based on those emotions, making it difficult to provide a personalized experience.

[1095] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generation AI to generate text tailored to the user's preferences for necessary notifications; emotion recognition means for recognizing the user's emotions and adjusting the notification text based on the emotions; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This makes it possible to adjust the notification text according to the user's emotions and provide a personalized experience.

[1096] An "avatar" is a digital character that a user creates to represent themselves within a virtual environment.

[1097] A "notification" is information or a message sent from each application to the user.

[1098] "Generative AI" is an artificial intelligence system that automatically generates text based on the user's settings and preferences.

[1099] "Emotion recognition" is a technology that analyzes a user's facial expressions and tone of voice to detect their emotional state at that time.

[1100] "Filtering" is the process by which the server cuts out unnecessary notifications based on the user's settings and selects only the necessary notifications.

[1101] The "server" is a central management system that manages user settings and notification data, and receives, filters, and sends notifications from each application.

[1102] A "terminal" is a device used by a user, such as a smartphone, tablet, or computer.

[1103] A "personalized experience" is a user experience that is customized to fit the individual preferences and feelings of each user.

[1104] System Overview

[1105] This invention is a system for a virtual store that senses user emotions and generates and displays personalized notifications. It mainly consists of the following elements:

[1106] 1. How users create their own avatar: Using a device (smartphone, tablet, computer), users create a digital character that represents them in a virtual environment.

[1107] 2. A means for users to set the tone and expression of notification text: Users use their devices to customize the tone (casual, formal, etc.) and expression (use of emojis, etc.) of notification text.

[1108] 3. A way for users to customize notification settings for each application: Users customize the types of notifications they want to receive from specific applications.

[1109] 4. Emotion recognition means: Using the device's built-in camera and microphone, the device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[1110] 5. Means for the generative AI to generate text tailored to the user's preferences: The server uses the generative AI model to generate text tailored to the user's preferences for the filtered notifications.

[1111] 6. A means for the server to filter notifications based on user settings and cut out unnecessary notifications: Receive notifications from each application and filter out unnecessary notifications based on user settings.

[1112] 7. Server means for transmitting the generated notification text to the user's terminal: The filtered notification text is transmitted to the user's terminal.

[1113] 8. Means for the user's device to display the notification text: The user's device displays the generated notification text, and the avatar presents the notification with facial expressions and movements that correspond to the emotion.

[1114] Hardware and Software Details

[1115] Hardware:

[1116] Smartphones, tablets, computers (user devices)

[1117] Camera and microphone (for emotion recognition)

[1118] software:

[1119] Generative AI model: Hugging Face natural language processing model

[1120] Emotion Recognition Software: Hugging Face's Sentiment-Analysis Pipeline

[1121] Server system: A server that receives, filters, and sends notifications

[1122] Explanation of the processing flow

[1123] 1. User creates an avatar:

[1124] Using an application on the device, users create an avatar, which is used to represent them within the virtual store and provide a personalized experience.

[1125] 2. Notification text settings:

[1126] Users can set their preferences for the tone and expression of notifications from a screen where they can choose things like a casual tone and the inclusion of emojis.

[1127] 3. Customize your notification settings:

[1128] Users customize the types of notifications they receive from each application, for example, they can receive only news notifications from certain categories.

[1129] 4. Initialize emotion recognition:

[1130] The user's device uses a camera and microphone to recognize the user's emotions, performing initial setup and training models to analyze facial expressions and tone of voice.

[1131] 5. Notification Generation and Filtering:

[1132] Notifications are received from each application and filtered by the server based on the user's settings. Only the filtered notifications are processed by the generative AI model to create notification text tailored to the user's preferences.

[1133] 6. Sending and Displaying Notifications:

[1134] The generated notification text is sent from the server to the user's device, where it is displayed by the avatar, who then displays the text and makes facial expressions and movements according to the user's emotions.

[1135] Specific examples

[1136] User state: The camera captures your face and the microphone records your voice when you are using the device.

[1137] Emotion recognition result: The user is recognized as happy.

[1138] Generated notification: "🌟Announcement from your virtual store🌟Check out our new arrivals!"

[1139] Prompt Sentence Examples

[1140] Prompt: "Generate a message to keep the user happy and notify him of new products."

[1141] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1142] Step 1:

[1143] The user creates an avatar. Using an application on their device, the user creates a digital character (avatar) to represent themselves. As input, the user selects appearance, clothing, accessories, etc., and as output, the avatar information is generated and stored on the server. This avatar is later used to display notifications.

[1144] Step 2:

[1145] The user configures the tone and expression of the notification text. Using the device, the user accesses a screen that allows them to customize the tone (e.g., casual, formal) and expression (e.g., type of emoji) of the notification text. User preferences are provided as input, and the configuration information is saved on the server as output.

[1146] Step 3:

[1147] Users customize notification settings for each application. Users can finely customize notification settings from news apps, social networking apps, etc., by setting the types of notifications they want to receive and filter conditions. Notification setting information for each application is provided as input, and individual settings are saved on the server as output.

[1148] Step 4:

[1149] Initialize emotion recognition. The emotion recognition model is calibrated and initialized using the camera and microphone built into the user's device. Data captured from the user's facial expressions and tone of voice is used as input, and emotion recognition model parameters are set as output.

[1150] Step 5:

[1151] The server receives notifications from each application. The server receives notification data sent from different applications in a unified manner. Notification data is sent to the server as input and accumulated on the server as output.

[1152] Step 6:

[1153] The server filters notifications. It filters the received notification data based on the user's pre-defined settings and cuts out unnecessary notifications. It takes raw notification data as input and provides filtered notification data as output.

[1154] Step 7:

[1155] The generation AI generates notification text. For the filtered notifications, the generation AI generates text tailored to the user's preferences. The filtered notification data and user settings are provided as input, and customized notification text is created as output.

[1156] Step 8:

[1157] The device performs emotion recognition. It analyzes the user's facial expressions and voice in real time to recognize their current emotional state. Real-time data from the camera and microphone is used as input, and emotion recognition results are obtained as output.

[1158] Step 9:

[1159] The server adjusts the notification text. Based on the emotion recognition results, the server adjusts the already generated notification text according to the user's emotion. The generated notification text and the emotion recognition results are provided as input, and the adjusted notification text is obtained as output.

[1160] Step 10:

[1161] The server sends the adjusted notification text and avatar information to the terminal. The server sends the adjusted notification text and avatar information according to the emotion to the user's terminal. The adjusted notification text and avatar information are provided as input, and the data is sent to the terminal as output.

[1162] Step 11:

[1163] The device displays the notification text. The user's device displays the adjusted notification text along with the avatar's facial expressions and movements. The adjusted notification text and avatar information are provided as input, and the notification is displayed as output.

[1164] Prompt Sentence Examples

[1165] Prompt: "Generate a message to keep the user happy and notify him of new products."

[1166] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1167] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1168] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1169] [Fourth embodiment]

[1170] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1171] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1172] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1173] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1174] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1175] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1176] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1177] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1178] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1179] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1180] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1181] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1182] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1183] User Preferences

[1184] 1. Create an avatar

[1185] Users install a specific application on their smartphone, tablet, or other device. When they open the application, they are guided to a screen where they can create their own avatar. Here, they can freely customize their character's appearance, clothing, and other aspects.

[1186] 2. Setting up the generated AI

[1187] The user is then taken to a screen where they can set the tone and expression of the notification text to the AI ​​generator. Here, they can set the style of the notification (e.g., casual, formal, humorous, etc.) and the type of emojis and emoticons to use.

[1188] 3. Notification filtering settings

[1189] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This setting information is stored on the server.

[1190] Sending and filtering notifications

[1191] 4. Notification Occurrence

[1192] Each application (e.g., news app, SNS app, etc.) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[1193] 5. Receiving and filtering notifications

[1194] The server receives notification data sent from the application. The received notification data is evaluated based on the filter settings for each user. The server cuts out notifications that the user deems unnecessary and selects only important notifications. This filtering process leaves only the notification information that is valuable to the user.

[1195] 6. Notification Text Generation

[1196] For notifications that pass the filter, the AI ​​generates notification text that matches the user's preferences. For example, if the user has selected a casual style, the AI ​​generates a text such as "⚽New sports news!"

[1197] Notification presentation

[1198] 7. Sending Notifications

[1199] The server sends the generated notification text and necessary metadata (such as the user's avatar information) to the user's device.

[1200] 8. Display of notifications

[1201] The user's device receives the notification data sent from the server. The device displays the notification using the user's avatar along with the notification text. For example, if the user is using the Zepeto app, the avatar displays a notification saying "⚽New sports news!"

[1202] Specific examples

[1203] User configuration example

[1204] User name: Sato-san

[1205] Avatar Creation: Sato created a casually dressed character as his avatar.

[1206] Generator AI settings: Sato set the tone of notifications to a casual style and specified that emojis be used frequently.

[1207] Notification filter settings: Sato set his news app to receive "only sports-related notifications" and his social media app to receive "all notifications."

[1208] Notification processing example

[1209] Notification occurs: The news app generates "sports-related news" and sends it to the server.

[1210] Receiving and filtering notifications: The server receives the notification data and determines that "sports related news" is the notification that needs to be sent.

[1211] Notification text generation: The AI ​​generates casual notification text such as "⚽There's new sports news!"

[1212] Sending notification: The server sends the generated notification text and avatar information to Mr. Sato's device.

[1213] Displaying the notification: Sato's device receives a notification and his avatar displays "⚽New sports news!"

[1214] This embodiment frees users from annoying notifications and allows them to receive valuable information tailored to their preferences without stress.

[1215] The processing flow will be explained below.

[1216] Step 1:

[1217] User: Install the application on the device and enter the avatar creation screen. Freely set the avatar's appearance, clothing, hairstyle, etc. Once complete, save the avatar information.

[1218] Step 2:

[1219] User: Go to the AI ​​generation settings screen and customize the tone and expression of the notification text. For example, choose a casual tone and a preference for using lots of emojis. This setting is saved on the server.

[1220] Step 3:

[1221] User: Go to the notification filtering settings screen for each application. Here, for example, you can set a news app to only receive sports-related notifications, and a social media app to receive all notifications. The settings are sent to the server and saved.

[1222] Step 4:

[1223] Each application generates a notification when a condition is met and sends the notification data to the server. The notification data includes the type, content, and time of the notification.

[1224] Step 5:

[1225] Server: Receives notification data sent from applications. Evaluates received notifications based on each user's filter settings and filters out unnecessary notifications. For example, if a "political news notification" is received, it is determined to be unnecessary based on the user's settings and is filtered out.

[1226] Step 6:

[1227] Server: For notifications that pass the filter, the AI ​​generates notification text tailored to the user's preferences. For example, if a sports-related news notification passes the filter, the AI ​​creates a casual text such as "⚽There's new sports news!"

[1228] Step 7:

[1229] Server: The server sends the generated notification text and avatar information to the user's device. The notification data includes the notification content, the application that generated it, the user ID, etc.

[1230] Step 8:

[1231] Device: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, the avatar displays "⚽New sports news!" through the Zepeto app.

[1232] Through this series of steps, users can customize their notification environment and receive only the information that matters to them without being overwhelmed with unnecessary notifications.

[1233] Example 1

[1234] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1235] Currently, users receive many notifications from multiple software applications, which can lead to users missing important notifications. Furthermore, the content and style of notifications often do not suit users' preferences, causing users to find them annoying. This reduces the efficiency of notifications and impairs the user experience.

[1236] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1237] In this invention, the server includes: means for a user to create their own character; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each software application; server means for receiving notifications from each software application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to easily check only important information, freeing them from annoying notifications and providing a comfortable user experience.

[1238] A "character" is an avatar, such as a virtual person or animal, that a user creates to represent themselves.

[1239] A "notification text" is a text message that is generated based on specific conditions and sent to the user.

[1240] A "generative AI model" is an artificial intelligence algorithm that generates notification text based on user settings.

[1241] "Software applications" are programs used by users, such as news apps and social networking apps.

[1242] A "server" is a computer system that receives notification data from an application and performs processing based on user settings.

[1243] "Filtering" is a process that removes notifications that the user deems unnecessary and selects only important notifications.

[1244] A "terminal" is a device used by a user, such as a smartphone or tablet.

[1245] "Metadata" is supplementary data such as user avatar information that accompanies the notification text.

[1246] This system allows users to efficiently manage notifications from multiple software applications and receive them in a format that suits their preferences. The system is primarily composed of a user's device, a server, and a generative AI model.

[1247] First, the user installs a specific application on their device. When they open the application, they are guided to a screen where they can create a character. Here, the user can freely customize the character's appearance and clothing. For example, the user can choose hairstyle and clothing color to determine the character's detailed appearance.

[1248] Next, users are taken to a screen where they can set the tone and expression of the notification text. They can choose the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. Users can do this by using drop-down menus and sliders.

[1249] Users are then taken to a screen where they can customize notification settings for each software application: for a news app, they can choose to receive only sports-related notifications, and for a social networking app, they can choose to receive all notifications. This setting information is then stored on the server.

[1250] Notifications from each software application are generated when certain conditions are met and sent to a server. For example, a news application generates sports-related news and sends it to a server. The server evaluates the received notification data based on the filter settings for each user. Unnecessary notifications are cut out, and only important notifications are selected.

[1251] For the filtered notifications, the server uses a generative AI model to generate sentences tailored to the user's preferences. If the user selects a casual style, a notification sentence such as "⚽There's new sports news!" is generated. An example of a prompt sentence is "Please tell me how to filter sports-related notifications generated by a news app and send them to the user in a casual tone."

[1252] The generated notification text and necessary metadata (such as the user's character information) are sent from the server to the user's device. In response, the user's device displays the notification text. In this case, the character displays a notification saying, "⚽There's new sports news!" Notifications are generally displayed in a pop-up format.

[1253] This embodiment allows users to be freed from annoying notifications and receive valuable information tailored to their preferences without stress. The system realizes efficient notification management and improves the user experience.

[1254] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1255] Step 1:

[1256] Users install a specific application on their device and open the avatar creation screen. They customize the character's appearance and clothing. Input includes information such as the user's chosen hairstyle and clothing color, and the avatar's appearance data is generated based on this information.

[1257] Step 2:

[1258] The user navigates to a page where they can set the tone and expression of their notification text. Here, they select the style of notification (casual, formal, humorous, etc.) and the type of emojis and emoticons they want to use. The input is the user's notification style and emoji settings, and the output is the saved settings.

[1259] Step 3:

[1260] The user navigates to a page where they can customize notification settings for each software application. The input is the user's notification filter settings (e.g., "only receive sports-related notifications"), which are sent to the server and stored. The output is notification filter settings for each application.

[1261] Step 4:

[1262] Each software application generates a notification when a certain condition is met. For example, a news app generates a sports-related news item and sends the notification data to a server. The input is the generated notification data, and the output is the notification data received by the server.

[1263] Step 5:

[1264] The server evaluates the notification data it receives based on the filter settings for each user. Specifically, the server references the user's settings information stored in a database and cuts out unnecessary notifications. The input is the received notification data and the user's filter settings, and the output is the filtered important notification data.

[1265] Step 6:

[1266] The server uses a generative AI model to generate notification text for the filtered notification data. The input is the filtered notification data and the user's notification style settings, and the output is the generated notification text. For example, if the user selects a casual style, the generated notification text will read, "⚽There's new sports news!"

[1267] Step 7:

[1268] The server sends the generated notification text and necessary metadata (e.g., user avatar information) to the user's device. The input is the generated notification text and avatar data, and the output is the sent notification packet.

[1269] Step 8:

[1270] The user's device receives the notification data sent from the server. The device displays the notification text in a pop-up format, and the user's avatar presents the notification. The input is the notification data received from the server, and the output is the notification text displayed on the screen. The notification is displayed in the form of "⚽There is new sports news!"

[1271] (Application example 1)

[1272] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1273] Conventional notification systems lack sufficient notification filtering and customization based on user interests and preferences, and the wide range of information they provide can be distracting. Furthermore, notification text is often boring and unattractive, making it difficult to attract users' attention. Furthermore, notification content is often simply displayed as text, which is often counterintuitive.

[1274] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1275] In this invention, the server includes a means for the user to create their own avatar, a means for the user to set the tone and expression of the notification text, and a means for the user to customize the notification settings for each application. This allows the generation AI to generate text tailored to the user's preferences, increasing interest in necessary notifications while minimizing annoyance. In addition, displaying customized notification text using the user's avatar provides intuitive and attractive notifications.

[1276] "Means for users to create their own avatar" refers to a function that allows users to create and customize a character that will represent their own identity.

[1277] The "means for the user to set the tone and expression of the notification text" is a function that allows the user to individually set the style and expression of the notification text that they receive.

[1278] "Means for users to customize notification settings for each application" refers to a function that allows users to individually set notification content and reception conditions for each application they use.

[1279] The "server means for receiving notifications from each application" is a server-side function for aggregating and receiving notification data sent from a plurality of applications.

[1280] "Means for the server to filter notifications based on user settings and cut out unnecessary notifications" is a function that allows the server to sort the notification data received according to the user's settings and delete notifications that are deemed unnecessary.

[1281] "Means for the generation AI to generate text tailored to the user's preferences for required notifications" is a function that enables the generation AI to create customized notification text based on the user's preferences and settings, based on filtered notifications.

[1282] "Server means for transmitting the generated notification text and associated metadata to the user's terminal" is a server-side function for transferring the generated notification text and associated data to the user's terminal.

[1283] The "means for the user's terminal to display the notification text" is a function for visually displaying the notification text on the user's terminal.

[1284] "Means for filtering notifications that are limited to the user's interests and for the generation AI to generate customized text for specific notifications" refers to a function that selects notifications based on the user's interests and allows the generation AI to create customized text for the content of the selected notifications.

[1285] The "means for displaying a customized notification text using a user's avatar" is a function for displaying a specific customized notification text using a user's avatar.

[1286] A system for implementing the invention includes the following elements:

[1287] 1. User Initial Settings

[1288] Creating an avatar

[1289] Users install the application on their devices (smartphones, tablets, etc.). When they open the application, they are guided to an avatar creation screen where they can freely customize the appearance and clothing of their character.

[1290] Notification text settings

[1291] The user is taken to a screen where they can set the tone and expression of the notification text. They can set the style of the notification (casual, formal, humorous, etc.) and the type of emojis or emoticons to use.

[1292] Configuring Notification Filtering

[1293] Users are directed to a screen where they can customize notification settings for each application. For example, they can set "Receive only sports-related notifications" for a news app, or "Receive all notifications" for a social networking app. This information is stored on the server.

[1294] 2. Sending and filtering notifications

[1295] Notification occurs

[1296] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met, and the generated notification data is sent to the server.

[1297] Receiving and filtering notifications

[1298] The server receives notification data sent from applications. The received notification data is evaluated based on the filter settings for each user, and unnecessary notifications are cut out and only valuable notifications are selected.

[1299] Notification text generation

[1300] For notifications that pass the filter, the generative AI model generates notification text that matches the user's preferences. For example, if the user has chosen a casual style, a notification such as "⚽New sports news!" will be generated.

[1301] 3. Notification

[1302] Sending notifications

[1303] The server sends the generated notification text and related metadata (such as avatar information) to the user's device.

[1304] Viewing notifications

[1305] The user's device receives the notification data sent from the server and displays the notification text on the device. The notification text is displayed using the user's avatar, making the notification visually appealing.

[1306] Component Description

[1307] server

[1308] The server is responsible for receiving, evaluating, and filtering notification data, and generating notification text using a generative AI model. This includes a server (e.g., Flask, Django) for processing HTTP requests and a generative AI model (e.g., GPT-3).

[1309] User terminal

[1310] The user terminal is a smartphone, tablet, or the like, and receives notification data sent from the server and displays the notification using an avatar.

[1311] Specific examples

[1312] Example 1

[1313] If a user wants to receive notifications in the "Fashion" category, they can select "Fashion" in the settings screen and set the notification style to "Casual." This will cause the generative AI model to generate casual-style notification text.

[1314] Prompt Sentence Example 1

[1315] Consider a generated AI response to "New sales information has arrived in the fashion category."

[1316] Example 2

[1317] If a user has chosen not to receive notifications in the "Electronic Devices" category, the server will filter notifications in that category and not send them to the user.

[1318] Prompt Sentence Example 2

[1319] Ignore the "New items in stock in the electronics category."

[1320] This system allows users to receive only the information they are interested in, making it easy to get important information without feeling distracted. The use of avatars also makes notifications visually appealing, improving the user experience.

[1321] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1322] Step 1:

[1323] A user installs the application on their device and opens it. They are then guided to the avatar creation screen to create their own character. This step takes as input the user's choices (appearance, clothing) and generates as output a customized avatar.

[1324] Step 2:

[1325] The user is taken to a screen where they can set the tone and expression of the notification text. At this stage, the user sets the style of the notification (casual, formal, humorous, etc.) and the type of emojis and emoticons to use. The user's settings are the input, and the settings data is saved as the output.

[1326] Step 3:

[1327] The user is taken to a screen where they can customize notification settings for each application. For example, for a news app, the user sets the notification categories they want to receive (e.g., sports, politics). The input is the user's notification settings, and the output is the notification filter settings, which are saved on the server.

[1328] Step 4:

[1329] Each application (such as a news app or a social networking app) generates a notification when certain conditions are met and sends the notification data to the server. The input is the notification data of each application, and the output is stored on the server.

[1330] Step 5:

[1331] The server evaluates the received notification data and filters it based on the user's settings. The server analyzes the notification data and cuts out notifications that the user deems unnecessary. The input is the notification data stored on the server and the user's filter settings, and the output is the filtered notification data.

[1332] Step 6:

[1333] For notification data that passes filtering, the server uses a generative AI model to generate notification text tailored to the user's preferences. Style settings such as "casual" or "formal" are input into the generative AI model, and customized notification text is obtained as output. For example, the generated text for the prompt "New sale information for the fashion category has arrived" is "A new fashion sale has started!"

[1334] Step 7:

[1335] The server sends the generated notification text and related metadata (e.g., avatar information) to the user's device. The generated notification text and metadata are input, and are sent to the user's device as output.

[1336] Step 8:

[1337] The user's device receives the notification data sent from the server and displays the notification text on the device. At this time, an avatar is also displayed to make the notification visually appealing. The input is the notification data received from the server, and the output is the notification displayed on the device screen.

[1338] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1339] User Preferences

[1340] 1. Create an avatar

[1341] Users install a specific application on their smartphone, tablet, or other device and navigate to the avatar creation screen. Here, users can customize their character's appearance and clothing. Once the avatar creation is complete, the avatar information is saved on the server.

[1342] 2. Setting up the generated AI

[1343] The user is taken to a screen where they can set the tone and expression of the notification text, select the notification style (casual, formal, humorous, etc.) and the type of emoji, and save the settings to the server.

[1344] 3. Notification filtering settings

[1345] The user navigates to the notification filtering settings screen for each application, where they can set the news app to only receive sports-related notifications and the social networking app to receive all notifications. These settings are then stored on the server.

[1346] Emotion Engine Settings

[1347] 4. Initializing the Emotion Engine

[1348] The emotion engine is initialized using the camera and microphone built into the user's device. Based on the user's facial expressions and tone of voice, the emotion engine is adjusted to recognize the user's emotions.

[1349] Sending and filtering notifications

[1350] 5. Notification Occurrence

[1351] When a condition is met, each application generates a notification and sends the notification data to the server, including the type of notification and the time of occurrence.

[1352] 6. Receiving and filtering notifications

[1353] The server receives notification data sent from the application and evaluates the notifications based on the user's filter settings. Unnecessary notifications are cut off and only necessary notifications remain.

[1354] 7. Notification Text Generation

[1355] For notifications that pass the filter, the AI ​​generator generates notification text tailored to the user's preferences. Furthermore, the emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the notification text accordingly. For example, if the user is feeling down, an encouraging message can be added.

[1356] Notification presentation

[1357] 8. Sending Notifications

[1358] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's emotional data.

[1359] 9. Display of notifications

[1360] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[1361] Specific examples

[1362] User configuration example

[1363] User name: Kato-san

[1364] Avatar creation: Kato creates an avatar in casual clothing and saves it on the server.

[1365] Generative AI settings: We set the tone of notifications to be casual and specified frequent use of emojis.

[1366] Notification filter settings: Set your news app to only receive sports-related notifications, and your social media apps to receive all notifications.

[1367] Emotion engine setting example

[1368] Emotion engine initialization: Kato's device was initialized to recognize Kato's emotions using the camera and microphone.

[1369] Notification processing example

[1370] Notification occurs: A news app generates sports-related news and sends it to the server.

[1371] Receiving and filtering notifications: The server receives notification data and selects the required notifications based on the filter settings.

[1372] Notification text generation: The AI ​​generates a casual text like "⚽There's new sports news!" The emotion engine recognizes the user's emotion as "joy" and adds more positive expressions.

[1373] Notification presentation example

[1374] Sending notification: The server sends the generated notification text, avatar information, and emotion data to Kato's device.

[1375] Displaying a notification: Kato's device receives a notification and his avatar displays a smiling message saying, "⚽There's new sports news!"

[1376] This specific embodiment allows users to receive notifications that are adapted to their emotions in real time, providing a more personalized user experience.

[1377] The processing flow will be explained below.

[1378] Step 1:

[1379] User: Installs the application on the device and goes to the avatar creation screen. The user can freely set the avatar's appearance, clothing, hairstyle, skin color, etc. The completed avatar information is sent to the server and saved.

[1380] Step 2:

[1381] User: Go to the generated AI settings screen and customize the tone and expression of the notification text. For example, select a casual style and a preference for using lots of emojis. The settings are sent to the server and saved.

[1382] Step 3:

[1383] User: Go to the notification filtering settings screen for each application. For example, in a news app, set "Receive only sports-related notifications," and in a social networking app, set "Receive all notifications." These settings are sent to the server and saved.

[1384] Step 4:

[1385] User: Initializes the emotion engine using the device's built-in camera and microphone. The emotion engine is adjusted to recognize the user's facial expressions and tone of voice. This setting is managed by the server.

[1386] Step 5:

[1387] Each application generates a notification when a specific condition is met and sends the notification data to the server. The notification data includes information such as the type of notification, its content, and the time of occurrence.

[1388] Step 6:

[1389] Server: Receives notification data sent from the application. The server evaluates notifications based on the filter settings for each user and cuts out unnecessary notifications. For example, if a "political news notification" is determined to be unnecessary, the notification will be discarded.

[1390] Step 7:

[1391] Server: For notifications that pass the filter, the generation AI generates notification text tailored to the user's preferences. In addition, the emotion engine recognizes the user's emotions and adjusts the tone and expression of the notification text based on those emotions. For example, if the user is feeling down, it adds an encouraging message.

[1392] Step 8:

[1393] Server: The server sends the generated notification text, avatar information, and emotion data to the user's device, including the notification content, the application from which it originated, and the user ID.

[1394] Step 9:

[1395] Terminal: Receives notification data sent from the server. Analyzes the notification data and displays the notification text using the user's avatar. For example, if the user is happy, the avatar will display the notification with a smiling face.

[1396] Examples:

[1397] Example user settings: Takahashi created an avatar with casual clothing and hairstyle, and selected a casual tone of voice and a style that makes heavy use of emojis in the AI ​​generation settings. He also set the news app to receive "sports-related notifications only" and the social media app to receive all notifications.

[1398] Emotion engine configuration example: The emotion engine was initialized to recognize Takahashi's emotions using the device's camera and microphone.

[1399] Example of notification processing: A news app generates sports-related news and sends it to the server. The server receives and filters the notifications, and the generation AI generates a casual sentence such as "⚽There's new sports news!". The emotion engine recognizes Takahashi's emotion as "joy" and adds a more positive expression. The notification is sent to Takahashi's device, and the avatar displays the notification with a smiling face.

[1400] Example 2

[1401] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1402] Conventional notification systems have the problem that it is difficult for users to receive only the information they need, and the notification language is uniform, making it impossible to provide a personalized user experience. In addition, the notification text does not adapt to the user's emotions, which reduces the value of the notifications received by the user and does not improve the user experience.

[1403] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1404] In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; means for recognizing the user's emotions using a camera and microphone built into the user's terminal; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generative AI model to generate text tailored to the user's preferences for necessary notifications; means for the generative AI model to recognize the user's emotions and adjust the tone and expression of the notification text; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This allows the user to receive only the information they need, and the notification text adapts to the user's emotions in real time, providing a personalized user experience.

[1405] An "avatar" is a virtual character that a user creates to visually represent themselves and customize their appearance and clothing.

[1406] "Tone and expression of notification text" refers to settings such as how notification messages are written and their style, the choice of words used, and the use of emoticons.

[1407] "Notification settings" refers to settings for customizing the types of notifications and filtering conditions that a user wants to receive for each application.

[1408] "Camera and microphone" refers to hardware devices used to sense a user's facial expressions and tone of voice and recognize emotions.

[1409] A "server" is a computer system that receives and processes data from multiple users and transmits the necessary information to the users' terminals.

[1410] "Filtering" refers to the process in which the server removes unnecessary data from the received notification data and selects only the necessary data based on the user's settings.

[1411] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate notification text based on a user's settings and preferences.

[1412] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to recognize the user's current emotional state.

[1413] "Notification text" refers to a message sent to a user, generated by filtering or a generative AI model.

[1414] A "user's device" is a device used by a user, such as a smartphone, tablet, or computer, that has the ability to receive and display notifications.

[1415] "Emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to estimate the emotions the user is currently feeling.

[1416] The system of the present invention provides a way for users to receive personalized and customized notifications. The main elements of the system include a user device, a server, and a generative AI model.

[1417] User Preferences

[1418] First, the user installs a dedicated application on their device. Then, the user launches the application and accesses the avatar creation screen. Here, the user customizes the character's appearance and clothing to create an avatar. The completed avatar information is sent to the server and stored in a database.

[1419] Next, the user is taken to a screen where they can set the tone and expression of the notification text. For example, they can choose the notification style (casual, formal, humorous) and specify the type of emojis to use. These settings are sent to the server and stored for each user.

[1420] Additionally, users can customize notification settings for each application, for example, to receive only sports-related notifications in a news app, or all notifications in a social networking app, which are also stored on the server.

[1421] Emotion Engine Settings

[1422] The user's device is equipped with a built-in camera and microphone, which are used to initialize the emotion engine. The user makes various facial expressions and speaks in different tones in front of the camera to collect data that the system uses to recognize the user's emotions. This data is sent to the server, where the user's basic emotional patterns are recorded.

[1423] Sending and filtering notifications

[1424] When a specific condition is met, each application generates a notification and sends the notification data to the server. The server receives this notification data and filters out unnecessary notifications based on the user's filter settings. For notifications that pass the filter, the generative AI model generates text tailored to the user's preferences.

[1425] The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text. For example, if the user is feeling down, the generative AI model will add an encouraging message.

[1426] Notification presentation

[1427] The server sends the generated notification text and avatar information to the user's device. It also sends information to adjust the avatar's facial expressions and movements based on the latest emotional data. The user's device displays the received notification data, and the avatar changes its facial expressions and movements to match the user's emotions while displaying the notification text. For example, if the user is happy, the avatar will display the notification with a smiling face.

[1428] Specific examples

[1429] As an example of a real user configuration, a user can create an avatar, set notification style to casual, set to frequently use emojis, set to receive only sports-related notifications in a news app, and receive all notifications in a social networking app.

[1430] For example, you can use prompts like the following to feed a generative AI model:

[1431] "Generate a notification message for when the user is happy. The message is about sports news."

[1432] This specific embodiment allows users to receive personalized notifications in real time, and the system can present notifications in a way that reflects the user's emotions, greatly improving the user experience.

[1433] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1434] Program processing flow

[1435] Step 1:

[1436] The user installs the dedicated application on their device. The user downloads the application from the App Store or Google Play Store and installs it. The application performs initial setup and displays a screen prompting the user to create an avatar.

[1437] Input: App download request from App Store or Google Play Store

[1438] Output: Installed dedicated application

[1439] Step 2:

[1440] The user goes to the avatar creation screen and customizes the character's appearance and clothing. The user selects each part, such as the head, hairstyle, clothing, and accessories, to complete the customization. The completed avatar information is sent to the server.

[1441] Input: Information about the avatar parts selected by the user

[1442] Output: Avatar information stored on the server

[1443] Step 3:

[1444] The user accesses the notification text settings screen and selects the notification style (casual, formal, humorous, etc.) and the type of emoji. These settings are sent to the server.

[1445] Input: Notification style and emoji type

[1446] Output: Notification settings saved on the server

[1447] Step 4:

[1448] The user goes to a screen where they can customize notification settings for each application and select the types of notifications they want to receive. The settings are then sent to the server.

[1449] Input: Notification filter settings for each application

[1450] Output: Notification settings for each application stored on the server

[1451] Step 5:

[1452] The user's device activates the camera and microphone to collect the user's facial expressions and tone of voice, which initializes the emotion engine so that it can recognize the user's emotions. The initialization data is then sent to the server.

[1453] Input: User's facial expressions and tone of voice

[1454] Output: Emotion recognition data stored on the server

[1455] Step 6:

[1456] Each application generates a notification when a specific condition is met and sends the notification data to the server.

[1457] Input: Application-generated notification data

[1458] Output: Notification data sent to the server

[1459] Step 7:

[1460] The server receives notification data sent from the application and filters notifications based on the user's settings, removing unnecessary notifications and selecting only necessary notifications.

[1461] Input: Notification data sent to the server

[1462] Output: Filtered notification data

[1463] Step 8:

[1464] The generative AI model generates text tailored to the user's preferences from the notification data that passes the filter. The emotion engine recognizes the user's emotions in real time and adjusts the tone and expression of the generated notification text.

[1465] Input: filtered notification data, user emotion data

[1466] Output: A customized notification text generated by the generative AI model

[1467] Step 9:

[1468] The server sends the generated notification text and avatar information to the user's device, along with information to adjust the avatar's facial expressions and movements based on the user's latest emotional data.

[1469] Input: Generated notification text, avatar information, user emotion data

[1470] Output: Notification data sent to the user's device

[1471] Step 10:

[1472] The notification data received by the user's device is displayed. The avatar presents the notification text while changing its facial expressions and movements to match the user's emotions. For example, if the user is happy, the avatar will display the notification with a smiling face.

[1473] Input: Notification data received from the server

[1474] Output: Displaying an emotion-adaptive notification

[1475] (Application example 2)

[1476] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1477] In modern virtual stores, personalizing and enhancing the user experience is an important challenge. In particular, providing notifications based on the user's emotions can increase user engagement and boost purchasing motivation. However, existing systems lack the means to recognize the user's emotions in real time and adjust the notification content and avatar display based on those emotions, making it difficult to provide a personalized experience.

[1478] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to create their own avatar; means for a user to set the tone and expression of notification text; means for a user to customize notification settings for each application; server means for receiving notifications from each application; means for the server to filter notifications based on the user's settings and cut out unnecessary notifications; means for a generation AI to generate text tailored to the user's preferences for necessary notifications; emotion recognition means for recognizing the user's emotions and adjusting the notification text based on the emotions; server means for transmitting the generated notification text to the user's terminal; and means for the user's terminal to display the notification text. This makes it possible to adjust the notification text according to the user's emotions and provide a personalized experience.

[1479] An "avatar" is a digital character that a user creates to represent themselves within a virtual environment.

[1480] A "notification" is information or a message sent from each application to the user.

[1481] "Generative AI" is an artificial intelligence system that automatically generates text based on the user's settings and preferences.

[1482] "Emotion recognition" is a technology that analyzes a user's facial expressions and tone of voice to detect their emotional state at that time.

[1483] "Filtering" is the process by which the server cuts out unnecessary notifications based on the user's settings and selects only the necessary notifications.

[1484] The "server" is a central management system that manages user settings and notification data, and receives, filters, and sends notifications from each application.

[1485] A "terminal" is a device used by a user, such as a smartphone, tablet, or computer.

[1486] A "personalized experience" is a user experience that is customized to fit the individual preferences and feelings of each user.

[1487] System Overview

[1488] This invention is a system for a virtual store that senses user emotions and generates and displays personalized notifications. It mainly consists of the following elements:

[1489] 1. How users create their own avatar: Using a device (smartphone, tablet, computer), users create a digital character that represents them in a virtual environment.

[1490] 2. A means for users to set the tone and expression of notification text: Users use their devices to customize the tone (casual, formal, etc.) and expression (use of emojis, etc.) of notification text.

[1491] 3. A way for users to customize notification settings for each application: Users customize the types of notifications they want to receive from specific applications.

[1492] 4. Emotion recognition means: Using the device's built-in camera and microphone, the device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[1493] 5. Means for the generative AI to generate text tailored to the user's preferences: The server uses the generative AI model to generate text tailored to the user's preferences for the filtered notifications.

[1494] 6. A means for the server to filter notifications based on user settings and cut out unnecessary notifications: Receive notifications from each application and filter out unnecessary notifications based on user settings.

[1495] 7. Server means for transmitting the generated notification text to the user's terminal: The filtered notification text is transmitted to the user's terminal.

[1496] 8. Means for the user's device to display the notification text: The user's device displays the generated notification text, and the avatar presents the notification with facial expressions and movements that correspond to the emotion.

[1497] Hardware and Software Details

[1498] Hardware:

[1499] Smartphones, tablets, computers (user devices)

[1500] Camera and microphone (for emotion recognition)

[1501] software:

[1502] Generative AI model: Hugging Face natural language processing model

[1503] Emotion Recognition Software: Hugging Face's Sentiment-Analysis Pipeline

[1504] Server system: A server that receives, filters, and sends notifications

[1505] Explanation of the processing flow

[1506] 1. User creates an avatar:

[1507] Using an application on the device, users create an avatar, which is used to represent them within the virtual store and provide a personalized experience.

[1508] 2. Notification text settings:

[1509] Users can set their preferences for the tone and expression of notifications from a screen where they can choose things like a casual tone and the inclusion of emojis.

[1510] 3. Customize your notification settings:

[1511] Users customize the types of notifications they receive from each application, for example, they can receive only news notifications from certain categories.

[1512] 4. Initialize emotion recognition:

[1513] The user's device uses a camera and microphone to recognize the user's emotions, performing initial setup and training models to analyze facial expressions and tone of voice.

[1514] 5. Notification Generation and Filtering:

[1515] Notifications are received from each application and filtered by the server based on the user's settings. Only the filtered notifications are processed by the generative AI model to create notification text tailored to the user's preferences.

[1516] 6. Sending and Displaying Notifications:

[1517] The generated notification text is sent from the server to the user's device, where it is displayed by the avatar, who then displays the text and makes facial expressions and movements according to the user's emotions.

[1518] Specific examples

[1519] User state: The camera captures your face and the microphone records your voice when you are using the device.

[1520] Emotion recognition result: The user is recognized as happy.

[1521] Generated notification: "🌟Announcement from your virtual store🌟Check out our new arrivals!"

[1522] Prompt Sentence Examples

[1523] Prompt: "Generate a message to keep the user happy and notify him of new products."

[1524] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1525] Step 1:

[1526] The user creates an avatar. Using an application on their device, the user creates a digital character (avatar) to represent themselves. As input, the user selects appearance, clothing, accessories, etc., and as output, the avatar information is generated and stored on the server. This avatar is later used to display notifications.

[1527] Step 2:

[1528] The user configures the tone and expression of the notification text. Using the device, the user accesses a screen that allows them to customize the tone (e.g., casual, formal) and expression (e.g., type of emoji) of the notification text. User preferences are provided as input, and the configuration information is saved on the server as output.

[1529] Step 3:

[1530] Users customize notification settings for each application. Users can finely customize notification settings from news apps, social networking apps, etc., by setting the types of notifications they want to receive and filter conditions. Notification setting information for each application is provided as input, and individual settings are saved on the server as output.

[1531] Step 4:

[1532] Initialize emotion recognition. The emotion recognition model is calibrated and initialized using the camera and microphone built into the user's device. Data captured from the user's facial expressions and tone of voice is used as input, and emotion recognition model parameters are set as output.

[1533] Step 5:

[1534] The server receives notifications from each application. The server receives notification data sent from different applications in a unified manner. Notification data is sent to the server as input and accumulated on the server as output.

[1535] Step 6:

[1536] The server filters notifications. It filters the received notification data based on the user's pre-defined settings and cuts out unnecessary notifications. It takes raw notification data as input and provides filtered notification data as output.

[1537] Step 7:

[1538] The generation AI generates notification text. For the filtered notifications, the generation AI generates text tailored to the user's preferences. The filtered notification data and user settings are provided as input, and customized notification text is created as output.

[1539] Step 8:

[1540] The device performs emotion recognition. It analyzes the user's facial expressions and voice in real time to recognize their current emotional state. Real-time data from the camera and microphone is used as input, and emotion recognition results are obtained as output.

[1541] Step 9:

[1542] The server adjusts the notification text. Based on the emotion recognition results, the server adjusts the already generated notification text according to the user's emotion. The generated notification text and the emotion recognition results are provided as input, and the adjusted notification text is obtained as output.

[1543] Step 10:

[1544] The server sends the adjusted notification text and avatar information to the terminal. The server sends the adjusted notification text and avatar information according to the emotion to the user's terminal. The adjusted notification text and avatar information are provided as input, and the data is sent to the terminal as output.

[1545] Step 11:

[1546] The device displays the notification text. The user's device displays the adjusted notification text along with the avatar's facial expressions and movements. The adjusted notification text and avatar information are provided as input, and the notification is displayed as output.

[1547] Prompt Sentence Examples

[1548] Prompt: "Generate a message to keep the user happy and notify him of new products."

[1549] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1550] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1551] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1552] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1553] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1554] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1555] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1556] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1557] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1558] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1559] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1560] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1561] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1562] 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.

[1563] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1564] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1565] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1566] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1567] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1568] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1569] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1570] The following is further disclosed regarding the above embodiment.

[1571] (Claim 1)

[1572] a means for users to create their own avatar;

[1573] a means for the user to configure the tone and wording of the notification text;

[1574] A means for users to customize notification settings for each application;

[1575] a server means for receiving notifications from each application;

[1576] A means for the server to filter notifications based on user settings and cut out unnecessary notifications;

[1577] A means for the AI ​​to generate text tailored to the user's preferences for the required notifications;

[1578] a server means for transmitting the generated notification text to a user's terminal;

[1579] A means for the user's device to display the notification text

[1580] A system including:

[1581] (Claim 2)

[1582] 10. The system of claim 1, wherein an avatar presents the generated notification text.

[1583] (Claim 3)

[1584] The system according to claim 1, wherein the server aggregates and centrally filters notifications from each application.

[1585] "Example 1"

[1586] (Claim 1)

[1587] a means for users to create their own characters;

[1588] a means for the user to configure the tone and wording of the notification text;

[1589] a means for a user to customize notification settings for each software application;

[1590] server means for receiving notifications from each software application;

[1591] A means for the server to filter notifications based on user settings and cut out unnecessary notifications;

[1592] A means for the generative AI model to generate text tailored to the user's preferences for the required notification;

[1593] a server means for transmitting the generated notification text to a user's terminal;

[1594] A means for the user's device to display the notification text

[1595] A system including:

[1596] (Claim 2)

[1597] 10. The system of claim 1, wherein the character presents the generated notification text.

[1598] (Claim 3)

[1599] 10. The system of claim 1, wherein the server aggregates and centrally filters notifications from each software application.

[1600] "Application Example 1"

[1601] (Claim 1)

[1602] a means for users to create their own avatar;

[1603] a means for the user to configure the tone and wording of the notification text;

[1604] A means for users to customize notification settings for each application;

[1605] a server means for receiving notifications from each application;

[1606] A means for the server to filter notifications based on user settings and cut out unnecessary notifications;

[1607] A means for the AI ​​to generate text tailored to the user's preferences for the required notifications;

[1608] a server means for transmitting the generated notification text and related metadata to a user terminal;

[1609] A means for displaying a notification text on the user's terminal;

[1610] A means for filtering notifications that are limited to the user's interests and generating customized sentences for specific notifications using AI;

[1611] A means to display customized notification text using a user's avatar

[1612] A system including:

[1613] (Claim 2)

[1614] 10. The system of claim 1, wherein an avatar presents the generated notification text.

[1615] (Claim 3)

[1616] The system according to claim 1, wherein the server aggregates and centrally filters notifications from each application.

[1617] "Example 2: Combining Emotion Engines"

[1618] (Claim 1)

[1619] a means for users to create their own avatar;

[1620] a means for the user to configure the tone and wording of the notification text;

[1621] A means for users to customize notification settings for each application;

[1622] A means for recognizing a user's emotion using a camera and a microphone built into the user's device;

[1623] a server means for receiving notifications from each application;

[1624] A means for the server to filter notifications based on user settings and cut out unnecessary notifications;

[1625] A means for the generative AI model to generate text tailored to the user's preferences for the required notification;

[1626] A means for the generative AI model to recognize the user's emotions and adjust the tone and expression of the notification text;

[1627] a server means for transmitting the generated notification text to a user's terminal;

[1628] The system includes means for the user's terminal to display notification text.

[1629] (Claim 2)

[1630] 10. The system of claim 1, wherein an avatar presents the generated notification text.

[1631] (Claim 3)

[1632] The system according to claim 1, wherein the server aggregates and centrally filters notifications from each application.

[1633] "Application example 2 when combining emotion engines"

[1634] (Claim 1)

[1635] a means for users to create their own avatar;

[1636] a means for the user to configure the tone and wording of the notification text;

[1637] A means for users to customize notification settings for each application;

[1638] a server means for receiving notifications from each application;

[1639] A means for the server to filter notifications based on user settings and cut out unnecessary notifications;

[1640] A means for the AI ​​to generate text tailored to the user's preferences for the required notifications;

[1641] emotion recognition means for recognizing a user's emotion and adjusting the notification text accordingly;

[1642] a server means for transmitting the generated notification text to a user's terminal;

[1643] A means for the user's device to display the notification text

[1644] A system including:

[1645] (Claim 2)

[1646] The system according to claim 1, wherein the avatar presents the generated notification text and changes its facial expression and movements according to the user's emotions.

[1647] (Claim 3)

[1648] The system according to claim 1, wherein the server aggregates and centrally filters notifications from each application. [Explanation of symbols]

[1649] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for users to create their own avatar; a means for the user to configure the tone and wording of the notification text; A means for users to customize notification settings for each application; a server means for receiving notifications from each application; A means for the server to filter notifications based on user settings and cut out unnecessary notifications; A means for the AI ​​to generate text tailored to the user's preferences for the required notifications; a server means for transmitting the generated notification text to a user's terminal; The user's device will display the notification text. A system including:

2. The system of claim 1 , wherein an avatar presents the generated notification text.

3. The system according to claim 1 , wherein notifications from each application are aggregated and centrally filtered by a server.

Images