System

Abstract

A system is provided.SOLUTION: A system comprising: means for sensing event data entered by a user; means for transmitting the event data to a server; means for analyzing the event data at the server and generating an appropriate animal movement; means for transmitting the generated animal movement to a terminal; and means for displaying the received animal movement on a screen of the terminal in real time.SELECTED DRAWING: Figure 1

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, people are often encouraged to keep pets to alleviate the loneliness and stress of living alone. However, pet ownership comes with many hurdles, such as allergies, pet odors, and the responsibility of daily care. These issues create a need for solutions that are equally effective for people who find it difficult to keep pets. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that allows users to interact with virtual pets using a smartphone. This system includes a means for detecting event data entered by the user and transmitting the data to a server. The server then analyzes the received event data and generates appropriate animal movements based on the user's actions. The generated movements are then transmitted from the server to a device and displayed on the device in real time. This allows users to experience interacting with a real pet. Furthermore, by using a generation AI, it is possible to analyze user actions with high accuracy and provide seamless pet movements in real time. Furthermore, by using coordinate data and timestamps to identify the type of user action, it is possible to accurately generate pet movements that match the user's intentions. This provides a means to alleviate loneliness without the hassle of allergies, odors, or the burden of caring for a pet.

[0006] A "user" is someone who uses the system to interact with a virtual pet.

[0007] "Event data" is data that the device senses when a user touches or swipes the smartphone screen, and includes coordinate data and timestamps.

[0008] A "terminal" is a device such as a smartphone or tablet that senses user operations, collects event data, and transmits it to a server.

[0009] The "server" is a device that receives and analyzes event data sent from the terminal, and is a computer system that performs processing to generate appropriate animal movements.

[0010] "Generative AI" is an artificial intelligence module that runs on the server and analyzes user event data to generate the movements of a virtual pet.

[0011] "Animal movements" refer to the animations and behaviors of virtual pets generated by the generation AI, which change in response to user input.

[0012] "Interaction data" is data that shows the movements and reactions of animals generated by the generation AI, and is sent from the server to the terminal.

[0013] "Real-time" means responding immediately to user input, with the animal's reaction displayed with minimal delay.

[0014] "Coordinate data" is information that indicates a specific position on the screen, including the start point, path, and end point of a user's touch or swipe.

[0015] A "timestamp" is information indicating the time at which a user operation was performed, and is collected as part of the event data. [Brief explanation of the drawings]

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

[0017] 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.

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

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] As one embodiment of the present invention, a virtual pet interaction system using a smartphone will be described in detail below.

[0038] System configuration

[0039] The system consists of a "terminal" that detects user operations, a "server" that analyzes the operation data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to detect user operations and a communication module that transmits event data to the server. The server uses generative AI to analyze the user's operation data and generate virtual pet animations in real time.

[0040] Program processing (natural language explanation)

[0041] User operation detection

[0042] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. Each action is also time-stamped, and the time information of the action is also collected.

[0043] Sending operation data

[0044] The device sends the collected coordinate data and timestamp to the server as event data. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0045] Analysis and movement generation by the server

[0046] The server analyzes the received event data. At this time, a generation AI is used to determine what kind of operation the user performed. For example, if the operation was stroking, it is determined that the appropriate action would be for the pet to wag its tail in delight. Based on this determination, the generation AI generates the movements and expressions of the virtual pet and compiles them as animation data.

[0047] Sending interaction data

[0048] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[0049] Specific examples

[0050] When the user pets the pet, the following steps are performed.

[0051] 1. User operation detection

[0052] The user strokes the image of the pet with their finger.

[0053] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[0054] 2. Sending operation data

[0055] The terminal transmits this data to the server.

[0056] 3. Analysis and movement generation by the server

[0057] The server analyzes the received data and recognizes that the user has performed a stroking action.

[0058] The generating AI responds to user input by generating a happy expression and tail-wagging behavior for the pet.

[0059] 4. Sending Interaction Data

[0060] The server transmits the generated animation data to the terminal.

[0061] 5. Real-time updates

[0062] The device displays the received animation data and plays back the pet's tail-wagging action in real time.

[0063] Users can visually see their pet's joy on the screen.

[0064] This system allows users to have an experience that feels like interacting with a real pet, helping to alleviate feelings of loneliness and reduce stress. It also serves as a new means of solving traditional problems with pet ownership, such as allergies, odors, and the burden of caring for a pet.

[0065] The processing flow will be explained below.

[0066] Step 1:

[0067] The user touches or swipes the smartphone screen.

[0068] The user strokes the image of the pet with his / her finger.

[0069] Step 2:

[0070] The terminal senses the user's operation and records the coordinate data and a timestamp.

[0071] The device collects touch point start and end points and swipe trajectory data.

[0072] The time information when the operation was performed is obtained as a timestamp.

[0073] Step 3:

[0074] The terminal transmits the collected event data to the server.

[0075] The terminal assembles the coordinate data and timestamp into a data packet and transmits it to the server in real time.

[0076] Step 4:

[0077] The server analyzes the received event data.

[0078] The server analyzes the data and recognizes the type of user operation (for example, stroking).

[0079] Based on the analysis results, it is decided what reaction the pet will have.

[0080] Step 5:

[0081] The server uses generative AI to generate animal movements and expressions in response to user input.

[0082] Based on the analysis results, the generation AI generates animation data for the virtual pet's happy expression and tail wagging.

[0083] The server assembles the generated animal movements into data packets.

[0084] Step 6:

[0085] The server transmits the generated interaction data to the terminal.

[0086] The server collects animation data into packets and sends them to the terminal.

[0087] Step 7:

[0088] The terminal displays the received animation data in real time.

[0089] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[0090] Users can instantly watch their pet wag its tail and show signs of happiness on the screen.

[0091] Example 1

[0092] 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."

[0093] Conventional virtual pet systems suffer from delayed responses to user operations and a lack of real-time capabilities. Furthermore, the animals' reactions to various user operation patterns are limited, resulting in a lack of interactive experience. Furthermore, conventional systems have difficulty analyzing complex operations and generating movements, making it difficult to improve the user experience.

[0094] 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.

[0095] In this invention, the server includes a means for analyzing event data input by the user, a means for generating appropriate animal movements using a generation AI, and a means for transmitting the generated animal movements to the terminal, thereby providing a virtual pet system that responds to user operations in real time.

[0096] "Event data" is data that includes operation information input by the user.

[0097] The "server" is a computing device that analyzes the received event data and performs the processing to generate appropriate animal movements.

[0098] "Generative AI" is an artificial intelligence model that learns user operation data and generates appropriate animal movements and facial expressions based on the input.

[0099] "Coordinate data" is data that indicates a specific position on the screen that the user touched.

[0100] A "timestamp" is data that records the specific time at which a user operation was performed.

[0101] "Real-time update" means that data is received and displayed almost simultaneously, providing feedback to the user without delay.

[0102] The "screen" is a display device that allows the user to input operations and visually confirm the movements and expressions of the animals.

[0103] The present invention relates to a system that allows users to enjoy the real-time reactions of a virtual pet by operating a touch screen. The system includes a terminal that detects user operations, a server that analyzes the operation data and generates appropriate movements, and a terminal that displays the generated movements.

[0104] Hardware and Software Configuration

[0105] The main components of the system are:

[0106] Device:

[0107] Touchscreen: Sensitive to user touches and swipes.

[0108] Communication module: Provides a communication means for transmitting detected operation data to the server.

[0109] server:

[0110] Generative AI (e.g., OpenAI's GPT-4®): Analyzes user operation data and generates the movements and expressions of a virtual pet based on that data.

[0111] Analysis device: Analyzes the event data sent from the device.

[0112] Data processing and calculation

[0113] User operation detection

[0114] When a user strokes or taps a virtual pet on the smartphone touchscreen, the device collects coordinate data of the operation position and swipe trajectory data, and assigns a timestamp to the data.

[0115] Sending operation data

[0116] The terminal assembles the collected coordinate data and timestamp into a packet as event data and sends it to the server via the communication module.

[0117] Analysis and movement generation by the server

[0118] The server uses a generative AI to analyze the received event data. Based on the analysis results, it determines whether the user's action is a stroking or tapping, and generates appropriate movements and expressions for the virtual pet. For example, if the user stroking the pet, the server generates a motion that makes the pet wag its tail in joy.

[0119] Sending interaction data

[0120] The generated animation data is sent from the server to the device, where it is displayed on the device's touch screen in real time.

[0121] Specific examples

[0122] The sequence of actions a user can take to pet a virtual pet is shown below.

[0123] 1. The user strokes the pet image for 2 seconds.

[0124] 2. The device records the coordinate data of the touch point (x1, y1) to (x2, y2) and the timestamp (t1, t2).

[0125] 3. The device collects this data into packets and sends them to the server.

[0126] 4. The server uses generative AI to analyze the data and generate an animation of your pet happily wagging its tail.

[0127] 5. The server assembles the generated animation data into packets and sends them to the device.

[0128] 6. The device analyzes the received animation data and displays the pet's tail-wagging motion in real time.

[0129] 7. Users can visually see their pets enjoying themselves.

[0130] Prompt Sentence Examples

[0131] Below is an example of a prompt sentence to the generative AI model to test the specific behavior of the system.

[0132] prompt:

[0133] The user stroked the virtual pet on the smartphone screen for two seconds. The device detected this action and recorded the coordinate data (x1, y1) to (x2, y2) and the timestamp (t1, t2). The data was sent to the server, which used a generative AI to generate an animation of the pet happily wagging its tail. The animation data was sent to the device in real time, allowing the user to observe the pet's happy behavior in real time on their smartphone.

[0134] This system allows users to enjoy real-time interactions with virtual pets, allowing them to experience the human touch while avoiding the problems of keeping a real pet.

[0135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0136] Step 1:

[0137] User operation detection

[0138] Input: The user operates the smartphone's touchscreen.

[0139] Specific action: The user strokes the image of the virtual pet for 2 seconds.

[0140] Data processing: The device's touchscreen records the coordinate data of the operation position (x1, y1) to (x2, y2), the swipe trajectory data, and the timestamp (t1, t2).

[0141] Output: Touch point coordinate data, swipe trajectory data, timestamp.

[0142] Step 2:

[0143] Sending operation data

[0144] Input: Recorded coordinate data, swipe trajectory data, timestamp.

[0145] Specific operation: The terminal collects data and organizes it into packets.

[0146] Data processing: Packaging data into packets for transmission.

[0147] Output: Data packet to send to the server.

[0148] Step 3:

[0149] Analysis and movement generation by the server

[0150] Input: Data packets sent from the terminal.

[0151] Specific operation: The server receives the data packet and uses the generated AI to analyze the operational data.

[0152] Data processing: Through analysis, the system determines that the user's action is a stroking motion and generates the animal's movements accordingly.

[0153] Output: Animation data of a happy virtual pet wagging its tail.

[0154] Step 4:

[0155] Sending interaction data

[0156] Input: The generated animation data.

[0157] Specific operation: The server packs the animation data into packets.

[0158] Data processing: Packaging animation data into packets for transmission.

[0159] Output: Animation data packets for sending to the device.

[0160] Step 5:

[0161] Real-time updates

[0162] Input: Animation data packet sent by the server.

[0163] Specific operation: The device receives the animation data and displays it on the touch screen.

[0164] Data processing: Analyze animation data and reproduce the movements of your virtual pet.

[0165] Output: The user can observe the happy tail wagging of the virtual pet in real time on the device screen.

[0166] (Application example 1)

[0167] 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."

[0168] In today's food delivery services, users have limited ways to enjoy the waiting time for their order. Furthermore, systems that provide conversational and emotional interactions to increase engagement and reduce stress are lacking. Furthermore, there is a demand for services that can respond in real time to specific user actions.

[0169] 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.

[0170] In this invention, the server includes means for detecting event data input by a user, means for transmitting the event data to the server, means for analyzing the event data and generating appropriate movements of a virtual character in the server, means for transmitting the generated movements of the virtual character to the terminal, means for displaying the received movements of the virtual character in real time on a display of the terminal, and means for the virtual character to generate a reaction related to a meal order in response to a specific operation by the user, thereby allowing the user to enjoy the time while waiting for their order, increasing engagement and reducing stress.

[0171] "User-input event data" refers to information about touches, swipes, clicks, and other actions performed by a user on a device, including touch point coordinate data and timestamps.

[0172] "Means for transmitting to the server" refers to a communication module or protocol that allows the terminal to transmit user operation data to the server in real time.

[0173] "Virtual character" refers to a digital character that runs on a computer and can interact with users.

[0174] "Virtual character movements" refers to various animations and reactions displayed by a virtual character, including expressions and movements such as happiness, sadness, and surprise.

[0175] "Means for transmitting to the terminal" refers to a communication module or protocol for transmitting animation data generated by the server to the terminal.

[0176] "Means for displaying in real time on a display" refers to a combination of software and hardware for instantly displaying the movements of a virtual character on the screen of a terminal.

[0177] "Specific user operations" refer to specific actions or inputs made by the user, such as ordering food or information about special dates.

[0178] The "means for generating a reaction related to a meal order" refers to a means for analyzing the user's meal order data and generating corresponding movements and facial expressions of the virtual character.

[0179] This invention is an interactive system that generates the movements of a virtual character based on event data entered by a user and displays reactions related to food orders. This section describes the program used to realize this system and the processing of that program.

[0180] Explanation of program processing

[0181] The system operates using a user terminal, a server, and a generative AI model.

[0182] Hardware and Software

[0183] User terminal: A device such as a smartphone or tablet, which includes a touchscreen, a communication module, and a display device.

[0184] Server: Cloud-based computing resources that run data analytics and generative AI models.

[0185] Generative AI model: For example, generative AI such as GPT-4 or DALL-E is used to analyze user operation data and generate the movements and facial expressions of a virtual character.

[0186] Data processing and calculation

[0187] 1. User event detection

[0188] When a user touches, swipes, or clicks on the smartphone screen, the action is detected by the user device, for example, when the user orders food from a food delivery app.

[0189] The user terminal records the coordinate data of the touch point, a timestamp, and the operation content (order data, etc.).

[0190] 2. Sending operation data

[0191] The user terminal transmits the collected event data (coordinate data, timestamp, and order data) to the server in real time.

[0192] 3. Analysis and movement generation by the server

[0193] The server analyzes the received event data and uses a generative AI model to generate appropriate movements and facial expressions for the virtual character.

[0194] For example, if a user orders a pizza, the generative AI generates a happy expression and tail wagging motion for the virtual character.

[0195] 4. Sending Interaction Data

[0196] The generated animation data is transmitted from the server to the user terminal.

[0197] 5. Real-time display

[0198] The user terminal immediately displays the received animation data, and the virtual character moves in real time.

[0199] This allows users to see the reactions of the virtual characters within the food delivery app, allowing them to enjoy the time they have while waiting for their order.

[0200] Adding specific examples

[0201] Example 1: When a user orders a pizza on a touchscreen, the user device collects coordinate data and order data and sends them to the server. The server then inputs a prompt to the generative AI model: "The user has ordered a pizza. Please generate a reaction that will make the pet happy.", and generates an animation of the virtual character.

[0202] Prompt Sentence Examples

[0203] "A user orders a pizza. Generate a reaction that will make their pet happy."

[0204] In this way, the present invention realizes a system that can provide interactive reactions to operations performed by users within a food delivery app, thereby increasing engagement.

[0205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0206] Step 1:

[0207] A user operates the touchscreen of a smartphone to order food using a food delivery app. This operation includes selecting a specific food menu item and confirming the order. Touchpoint coordinate data, a timestamp, and the order details (e.g., pizza) are collected as input. These event data are generated as output.

[0208] Step 2:

[0209] The terminal sends the collected event data (coordinate data, timestamp, and order details) to the server in real time. The input is the event data generated in step 1, and the output is the data sent to the server. The communication module is used to send the data quickly and accurately.

[0210] Step 3:

[0211] The server analyzes the received event data to understand the user's operation. This analysis includes extracting the meal order details from the event data. The input is the event data sent from the device, and the output is the order details data as the analysis result.

[0212] Step 4:

[0213] The server uses the generative AI model to generate the movements and expressions of the virtual character according to the user's order. Specifically, the prompt statement "The user has ordered a pizza. Please generate a reaction that will please the pet." is input into the generative AI model, and animation data is generated based on that. The order data and prompt statement from the analysis results are used as input, and the generated animation data is obtained as output.

[0214] Step 5:

[0215] The generated animation data is sent from the server to the user's device. The input is the animation data output from the generative AI model, and the output is the data sent to the device. The animation data is sent in real time using a communication module.

[0216] Step 6:

[0217] The user device displays the received animation data on a display in real time. Specifically, the virtual character displays movements such as a happy expression or a wagging tail. The input is the animation data sent from the server, and the output is the animation visually displayed to the user.

[0218] This series of processes allows users to enjoy an interactive experience with virtual characters through the food delivery app, making the waiting time for their order more enjoyable.

[0219] 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.

[0220] As one embodiment of the present invention, a system that combines a virtual pet interaction system using a smartphone with an emotion engine that analyzes the user's emotions will be described in detail.

[0221] System configuration

[0222] The system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to sense the user's operations and an emotion engine that analyzes emotions, as well as a communication module that collects this data and transmits it to the server. The server uses generative AI to analyze the user's operation data and emotion data and generates virtual pet animations in real time.

[0223] Program processing (natural language explanation)

[0224] Sensing user actions and emotions

[0225] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[0226] Sending operational and emotional data

[0227] The device sends the collected coordinate data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0228] Analysis and movement generation by the server

[0229] The server analyzes the received event data and emotion data. At this time, a generation AI is used to determine the type of user operation and the user's emotional state at the time. For example, if the user is stroking the pet and has a happy expression, it is determined that the pet should be more active and happy, wagging its tail. Based on this judgment, the generation AI generates the virtual pet's movements and expressions and compiles them as animation data.

[0230] Sending interaction data

[0231] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[0232] Specific examples

[0233] When the user pets the pet, the following steps are performed.

[0234] 1. Sensing user actions and emotions

[0235] The user strokes the image of the pet with their finger.

[0236] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[0237] The emotion engine analyzes the user's facial expressions and voice to collect data on happy emotions.

[0238] 2. Transmission of operational and emotional data

[0239] The terminal transmits this data to the server.

[0240] 3. Analysis and movement generation by the server

[0241] The server analyzes the received data and recognizes that the user is enjoying the stroking action.

[0242] The generative AI responds to the user's operations and emotions to generate more lively, happy expressions and tail-wagging movements for the pet.

[0243] 4. Sending Interaction Data

[0244] The server transmits the generated animation data to the terminal.

[0245] 5. Real-time updates

[0246] The device displays the received animation data and plays back the pet's active tail-wagging action in real time.

[0247] Users can visually see their pet's joy on the screen, and their own emotions will be elevated along with it.

[0248] This system allows users to have an experience that feels like interacting with a real pet, which helps to alleviate feelings of loneliness and relieve stress, and provides responses based on the user's emotions, allowing for a more intimate experience.It serves as a new means of solving traditional problems of pet ownership, such as allergies, odors, and the burden of caring for them.

[0249] The processing flow will be explained below.

[0250] Step 1:

[0251] The user touches or swipes the smartphone screen.

[0252] The user strokes the image of the pet with his / her finger.

[0253] Step 2:

[0254] The terminal senses the user's operation and records the coordinate data and a timestamp.

[0255] The device collects touch point start and end points and swipe trajectory data.

[0256] The time information when the operation was performed is obtained as a timestamp.

[0257] Step 3:

[0258] An emotion engine within the device analyzes the user's emotional state.

[0259] The device analyzes the user's facial expressions and voice and collects emotional data in real time.

[0260] Step 4:

[0261] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[0262] The terminal assembles this data into data packets and transmits them to the server in real time.

[0263] Step 5:

[0264] The server analyzes the received event data and emotion data.

[0265] The server analyzes the coordinate data and timestamp and identifies the type of user operation (for example, stroking).

[0266] The server analyzes the emotion data sent from the emotion engine and determines the user's emotional state.

[0267] Step 6:

[0268] The server uses generative AI to generate animal movements and expressions based on the user's actions and emotions.

[0269] The generative AI determines the virtual pet's behavior (e.g., wagging its tail happily, jumping, etc.) based on the user's actions and emotional state.

[0270] The server packages the generated animation data into data packets.

[0271] Step 7:

[0272] The server transmits the generated interaction data to the terminal.

[0273] The server collects animation data into packets and sends them to the terminal.

[0274] Step 8:

[0275] The terminal displays the received animation data in real time.

[0276] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[0277] Users can instantly see their pet wagging its tail and bouncing on the screen.

[0278] Specific examples

[0279] The process flow when the user is enjoying petting a pet is as follows.

[0280] 1. Step 1:

[0281] The user strokes the image of the pet with their finger.

[0282] 2. Step 2:

[0283] The device detects touch events on the screen and records the coordinate data of the touch point and the trajectory data of the swipe.

[0284] Record the timestamp of the operation.

[0285] 3. Step 3:

[0286] The device's emotion engine analyzes the user's facial expressions and voice to determine their feelings of enjoyment.

[0287] 4. Step 4:

[0288] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[0289] 5. Step 5:

[0290] The server analyzes the coordinate data and timestamp and recognizes that a stroking action has been performed.

[0291] The server analyzes the received emotional data and determines that the user is enjoying themselves.

[0292] 6. Step 6:

[0293] The generating AI responds to the user's operations and emotions to generate a lively and happy tail-wagging behavior for the pet.

[0294] The server packages the generated animation data into packets.

[0295] 7. Step 7:

[0296] The server transmits this data to the terminal.

[0297] 8. Step 8:

[0298] The device displays the received animation data in real time, recreating the action of your pet happily wagging its tail.

[0299] Users can visually see their pets' happy expressions and enjoy the experience even more.

[0300] This system allows users to have an experience similar to interacting with a real pet, which helps to alleviate feelings of loneliness and stress. Furthermore, by providing responses according to the user's emotional state, it allows for a more intimate and fulfilling interaction.

[0301] Example 2

[0302] 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."

[0303] Conventional virtual pet systems have limited response to user input and are unable to fully reflect the user's emotions. Real-time responses are also insufficient, making it difficult to improve the user experience. Furthermore, there is a lack of means to analyze the user's emotions, making it difficult to provide a more intimate experience.

[0304] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing event data and emotion data input by the user and generating appropriate virtual pet movements using a generation AI, means for determining the virtual pet's movements and facial expressions based on the received data, and means for transmitting the generated virtual pet movements to the terminal. This enables the virtual pet to move in a way that reflects the user's operations and emotions in real time.

[0305] "User" refers to the person who operates the system and interacts with the virtual pet.

[0306] "Event data" refers to input information such as touch points and swipe trajectories generated when a user operates a device such as a smartphone.

[0307] "Emotion data" refers to data analyzed by the emotion engine based on the user's facial expressions, voice, etc.

[0308] "Server" refers to a computer system that analyzes collected event data and emotion data and generates appropriate virtual pet movements.

[0309] "Generative AI" refers to artificial intelligence technology that analyzes user operations and emotional data to generate the movements and facial expressions of a virtual pet.

[0310] "Virtual pet" refers to a digital pet character that operates on a display device such as a smartphone.

[0311] A "timestamp" refers to data that records the time when a user performs an operation.

[0312] "Real-time" refers to processing that responds immediately to user operations and emotions.

[0313] "Coordinate data" refers to data that records the position information of operations performed by a user on a touch screen.

[0314] "Display Device" means a device, such as a smartphone or tablet, that visually displays the movements and reactions of a virtual pet.

[0315] This invention is a system that senses user operations and emotions, and generates and displays the movements of a virtual pet in real time based on those operations. This system consists of a "terminal" that senses user operations, a "server" that analyzes the operation and emotion data and generates appropriate movements, and a "terminal" that displays the generated movements.

[0316] Hardware and software used

[0317] Terminal

[0318] A device is a mobile device such as a smartphone or tablet, and includes the following elements:

[0319] Touchscreen sensor: Detects user touch and swipe actions.

[0320] Camera and microphone: Captures the user's facial expressions and voice, providing data for analysis by the emotion engine.

[0321] Emotion engine: A software module that analyzes emotions from the user's facial expressions and voice.

[0322] Communication module: Sends collected operation and emotion data to the server.

[0323] server

[0324] A server is a powerful computer system that includes the following components:

[0325] Data analysis module: Analyzes the operation data and emotion data sent from the terminal.

[0326] Generative AI: Artificial intelligence that generates appropriate movements and facial expressions for a virtual pet based on analysis results.

[0327] Communication module: Sends the generated animation data to the terminal.

[0328] Specific actions

[0329] Here's a concrete example of how this system works:

[0330] Sensing user actions and emotions

[0331] When a user touches or swipes the smartphone screen, the device detects the action. For example, if the user strokes the image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the device's built-in emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[0332] Sending operational and emotional data

[0333] The device sends the collected touch point coordinate data, swipe trajectory data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0334] Analysis and movement generation by the server

[0335] The server analyzes the received operation data and emotional data. Using a generation AI, it determines what the user's operation was and what their emotional state was at the time. For example, when a petting operation and a happy facial expression are detected, the generation AI determines that the pet's behavior is appropriate for making the pet happy. Based on this judgment, the server generates the virtual pet's movements and facial expressions and compiles them as animation data.

[0336] Sending interaction data and updating it in real time

[0337] The server sends the generated animation data to the device, which then receives the animation data and displays it in real time. For example, immediately after a user strokes a pet, the pet's tail wagging motion on the screen is reproduced in real time.

[0338] Prompt Sentence Examples

[0339] The user pets the pet using a smartphone. The emotion engine analyzes the user's happy facial expression and generates how the virtual pet will react based on that data.

[0340] Using this prompt, the generative AI model can generate specific actions.

[0341] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0342] Step 1: Sensing user actions and emotions

[0343] When a user touches or swipes the smartphone screen, the device's touchscreen sensor detects and records the coordinate data of the touch point and the swipe trajectory data as input. At the same time, the device's camera and microphone capture the user's facial expressions and voice and provide this data as input to the emotion engine. The emotion engine analyzes this data and generates the user's emotional state as output. Specifically, if a user strokes the image of a pet and says "cute" with a smile, the emotion engine will collect happy emotion data.

[0344] Step 2: Sending Operation and Emotion Data

[0345] The device collects the touch point coordinate data, swipe trajectory data, timestamps, and emotion data collected in step 1 as input and sends them to the server. Using the communication module, this data is sent to the server in real time. For example, the coordinate data of the moment you stroke your pet and the voice analysis results, such as "cute," are sent to the server.

[0346] Step 3: Server analysis and motion generation

[0347] The server receives the operation data and emotion data sent in step 2 and analyzes them as input in the data analysis module. Based on the analysis results, the generation AI determines the user's operation and emotional state, and generates appropriate movements and facial expressions for the virtual pet as output. For example, if a stroking operation and a happy emotion are detected, the generation AI determines that the pet will happily wag its tail and generates this as animation data.

[0348] Step 4: Sending interaction data

[0349] The server organizes the animation data generated in step 3 as input and sends it to the terminal. Using a communication module, the generated animation data is sent to the terminal in real time. For example, animation data of a pet wagging its tail is sent to the terminal.

[0350] Step 5: Real-time updates

[0351] The terminal receives the animation data sent in step 4 and processes it as input. The terminal plays the received animation data in real time on a display device, providing the user with visual feedback as output. For example, immediately after the user pets the pet, the pet's tail wagging action is displayed on the screen in real time. As a result, the user can see the pet's reaction immediately.

[0352] (Application example 2)

[0353] 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."

[0354] Conventional food delivery services have faced problems such as stress and dissatisfaction from users due to delivery delays and order cancellations. Furthermore, there is a lack of systems that can respond to users' emotions, creating a need for an improved user experience. This invention aims to solve these problems by analyzing users' emotions and providing a delivery experience that is customized accordingly.

[0355] 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 including an emotion engine that collects and analyzes user emotion data, means for generating the movements and facial expressions of the pseudo-creature based on the emotion data, and means for providing customized information based on the user's emotions and operations. This makes it possible to reduce user stress caused by delivery delays, order cancellations, etc., and improve the user experience.

[0356] "Event data input by a user" is operation information generated when a user operates a terminal, and is data indicating input actions such as touching, swiping, and clicking.

[0357] "Emotion data" is data that indicates the emotional state of the user analyzed from the user's voice, facial expression, gestures, etc., and is information that reflects the user's psychological state.

[0358] An "emotion engine" is software for analyzing a user's emotions, and is a program with the function of generating emotion data through facial expression recognition, voice analysis, etc.

[0359] "Generative AI" is an artificial intelligence technology that analyzes user operation data and emotional data and generates appropriate responses and actions based on that data.

[0360] A "pseudo-creature" is a virtual creature designed to interact with users like a virtual pet, and is a character that displays movements and expressions on a display.

[0361] "The behavior of the generated pseudo-creature" refers to the actions and reactions of the pseudo-creature determined by the generating AI based on the user's operations and emotions.

[0362] This invention is a system for food delivery services that analyzes user emotions and provides a customized delivery experience. This system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate actions, and a "terminal" that displays the generated actions.

[0363] System configuration

[0364] 1. Terminal

[0365] Touchscreen: Used to sense user interaction.

[0366] Camera: Captures the user's facial expressions and collects emotional data.

[0367] Microphone: Captures the user's voice and analyzes emotional data.

[0368] Communication module: Sends collected operation data and emotion data to the server in real time.

[0369] 2. Server

[0370] Emotion engine (e.g., Affectiva API): Software that analyzes emotions from a user's facial expressions and voice.

[0371] Generative AI (e.g., GPT-4): Artificial intelligence that analyzes user actions and emotional data to generate appropriate behaviors and responses.

[0372] 3. Applications on the device

[0373] The behavior of the generated pseudo-creature is displayed in real time.

[0374] Program processing (natural language explanation)

[0375] Sensing user actions and emotions

[0376] When a user touches or swipes the smartphone screen, the corresponding device detects the action. For example, when a user places an order on a food delivery app, the operation data is recorded. Meanwhile, the user's face is captured by the camera and analyzed by the emotion engine. The user's voice is also collected by the microphone and analyzed as emotion data.

[0377] Sending operational and emotional data

[0378] The device sends the collected operation data, emotion data, and timestamps to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0379] Analysis and movement generation by the server

[0380] The server analyzes the received data using an emotion engine (Affectiva API) and a generative AI (GPT-4 model) to determine the user's actions and emotional state. For example, if a delivery is delayed, the emotion engine detects the user's dissatisfaction, and the generative AI generates actions of the simulated creature to comfort the user.

[0381] Sending and viewing interaction data

[0382] The server sends the generated animation data to the device, which receives the data and displays it to the user in real time, allowing the user to visually confirm the movements of the simulated creature and alleviate their emotions.

[0383] Specific examples

[0384] If delivery is delayed

[0385] 1. Sensing user actions and emotions

[0386] The user opens the delivery app to check the delivery status.

[0387] The camera captures the user's facial expressions and the emotion engine collects the displeased emotion data.

[0388] 2. Transmission of operational and emotional data

[0389] The terminal transmits this data to the server.

[0390] 3. Analysis and movement generation by the server

[0391] The server analyzes the delay notification and the displeased emotion data, and the generative AI (GPT-4) generates the behavior of a charming pseudo-creature that says, "Delicious food will arrive soon, so please be patient a little longer!"

[0392] 4. Sending and Displaying Interaction Data

[0393] The server transmits the generated data to the terminal and displays it to the user in real time.

[0394] Example prompts for generative AI models

[0395] User emotion: Sad

[0396] Delivery status: Delayed

[0397] Pet action: Generate an animation where the pet apologizes and says something funny to brighten the user's mood.

[0398] Using this prompt, the generative AI model generates an appropriate response and implements an action that corresponds to the user's emotions.

[0399] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0400] Step 1: Sensing user actions and emotions

[0401] A user places an order on a food delivery app. The device collects operation data through the touchscreen. It also uses a camera and microphone to capture the user's facial expressions and voice, obtaining emotion data. This data includes touch point coordinates, timestamps, and the analysis results (user's emotional state) by the emotion engine. The input is the operation data and emotion data, and the output is a data package.

[0402] Step 2: Sending Operation and Emotion Data

[0403] The terminal transmits the collected operation data and emotion data to the server in real time. Using the communication module, the operation data includes the coordinates of the touch points and a timestamp, and the emotion data includes the analysis results (for example, whether the user is happy or sad). The input is the operation data and emotion data, and the output is the state in which they are transmitted to the server.

[0404] Step 3: Server analysis and motion generation

[0405] The server analyzes the received operation data and emotional data. First, it examines the user's emotional state using an emotion engine (e.g., Affectiva API) and passes the results to a generation AI (e.g., GPT-4). The generation AI generates appropriate movements and facial expressions for the simulated creature based on the given prompts. For example, if a delivery is delayed or the user is in a bad mood, the simulated creature will generate movements to comfort the user. The input is operation data and emotional data, and the output is the movements (animation data) of the generated simulated creature.

[0406] Step 4: Sending interaction data

[0407] The server sends the generated motion data of the pseudo-creature to the terminal. When sent to the terminal, the animation data and an accompanying timestamp are included in the data package. The input is the generated animation data, and the output is the state of the transmitted data as it arrives at the terminal.

[0408] Step 5: Displaying the behavior of the mimic creature

[0409] The device interprets the received animation data and displays it to the user in real time. The animation engine renders the movements of the simulated creature and plays them on the screen, allowing the user to visually confirm how the simulated creature is behaving in accordance with their own emotions. The input is the animation data sent from the server, and the output is the movements played on the screen.

[0410] 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.

[0411] 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.

[0412] 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.

[0413] [Second embodiment]

[0414] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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).

[0420] 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. 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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."

[0426] As one embodiment of the present invention, a virtual pet interaction system using a smartphone will be described in detail below.

[0427] System configuration

[0428] The system consists of a "terminal" that detects user operations, a "server" that analyzes the operation data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to detect user operations and a communication module that transmits event data to the server. The server uses generative AI to analyze the user's operation data and generate virtual pet animations in real time.

[0429] Program processing (natural language explanation)

[0430] User operation detection

[0431] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. Each action is also time-stamped, and the time information of the action is also collected.

[0432] Sending operation data

[0433] The device sends the collected coordinate data and timestamp to the server as event data. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0434] Analysis and movement generation by the server

[0435] The server analyzes the received event data. At this time, a generation AI is used to determine what kind of operation the user performed. For example, if the operation was stroking, it is determined that the appropriate action would be for the pet to wag its tail in delight. Based on this determination, the generation AI generates the movements and expressions of the virtual pet and compiles them as animation data.

[0436] Sending interaction data

[0437] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[0438] Specific examples

[0439] When the user pets the pet, the following steps are performed.

[0440] 1. User operation detection

[0441] The user strokes the image of the pet with their finger.

[0442] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[0443] 2. Sending operation data

[0444] The terminal transmits this data to the server.

[0445] 3. Analysis and movement generation by the server

[0446] The server analyzes the received data and recognizes that the user has performed a stroking action.

[0447] The generating AI responds to user input by generating a happy expression and tail-wagging behavior for the pet.

[0448] 4. Sending Interaction Data

[0449] The server transmits the generated animation data to the terminal.

[0450] 5. Real-time updates

[0451] The device displays the received animation data and plays back the pet's tail-wagging action in real time.

[0452] Users can visually see their pet's joy on the screen.

[0453] This system allows users to have an experience that feels like interacting with a real pet, helping to alleviate feelings of loneliness and reduce stress. It also serves as a new means of solving traditional problems with pet ownership, such as allergies, odors, and the burden of caring for a pet.

[0454] The processing flow will be explained below.

[0455] Step 1:

[0456] The user touches or swipes the smartphone screen.

[0457] The user strokes the image of the pet with his / her finger.

[0458] Step 2:

[0459] The terminal senses the user's operation and records the coordinate data and a timestamp.

[0460] The device collects touch point start and end points and swipe trajectory data.

[0461] The time information when the operation was performed is obtained as a timestamp.

[0462] Step 3:

[0463] The terminal transmits the collected event data to the server.

[0464] The terminal assembles the coordinate data and timestamp into a data packet and transmits it to the server in real time.

[0465] Step 4:

[0466] The server analyzes the received event data.

[0467] The server analyzes the data and recognizes the type of user operation (for example, stroking).

[0468] Based on the analysis results, it is decided what reaction the pet will have.

[0469] Step 5:

[0470] The server uses generative AI to generate animal movements and expressions in response to user input.

[0471] Based on the analysis results, the generation AI generates animation data for the virtual pet's happy expression and tail wagging.

[0472] The server assembles the generated animal movements into data packets.

[0473] Step 6:

[0474] The server transmits the generated interaction data to the terminal.

[0475] The server collects animation data into packets and sends them to the terminal.

[0476] Step 7:

[0477] The terminal displays the received animation data in real time.

[0478] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[0479] Users can instantly watch their pet wag its tail and show signs of happiness on the screen.

[0480] Example 1

[0481] 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."

[0482] Conventional virtual pet systems suffer from delayed responses to user operations and a lack of real-time capabilities. Furthermore, the animals' reactions to various user operation patterns are limited, resulting in a lack of interactive experience. Furthermore, conventional systems have difficulty analyzing complex operations and generating movements, making it difficult to improve the user experience.

[0483] 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.

[0484] In this invention, the server includes a means for analyzing event data input by the user, a means for generating appropriate animal movements using a generation AI, and a means for transmitting the generated animal movements to the terminal, thereby providing a virtual pet system that responds to user operations in real time.

[0485] "Event data" is data that includes operation information input by the user.

[0486] The "server" is a computing device that analyzes the received event data and performs the processing to generate appropriate animal movements.

[0487] "Generative AI" is an artificial intelligence model that learns user operation data and generates appropriate animal movements and facial expressions based on the input.

[0488] "Coordinate data" is data that indicates a specific position on the screen that the user touched.

[0489] A "timestamp" is data that records the specific time at which a user operation was performed.

[0490] "Real-time update" means that data is received and displayed almost simultaneously, providing feedback to the user without delay.

[0491] The "screen" is a display device that allows the user to input operations and visually confirm the movements and expressions of the animals.

[0492] The present invention relates to a system that allows users to enjoy the real-time reactions of a virtual pet by operating a touch screen. The system includes a terminal that detects user operations, a server that analyzes the operation data and generates appropriate movements, and a terminal that displays the generated movements.

[0493] Hardware and Software Configuration

[0494] The main components of the system are:

[0495] Device:

[0496] Touchscreen: Sensitive to user touches and swipes.

[0497] Communication module: Provides a communication means for transmitting detected operation data to the server.

[0498] server:

[0499] Generative AI (e.g., OpenAI's GPT-4): Analyzes user operation data and generates the movements and expressions of a virtual pet based on that data.

[0500] Analysis device: Analyzes the event data sent from the device.

[0501] Data processing and calculation

[0502] User operation detection

[0503] When a user strokes or taps a virtual pet on the smartphone touchscreen, the device collects coordinate data of the operation position and swipe trajectory data, and assigns a timestamp to the data.

[0504] Sending operation data

[0505] The terminal assembles the collected coordinate data and timestamp into a packet as event data and sends it to the server via the communication module.

[0506] Analysis and movement generation by the server

[0507] The server uses a generative AI to analyze the received event data. Based on the analysis results, it determines whether the user's action is a stroking or tapping, and generates appropriate movements and expressions for the virtual pet. For example, if the user stroking the pet, the server generates a motion that makes the pet wag its tail in joy.

[0508] Sending interaction data

[0509] The generated animation data is sent from the server to the device, where it is displayed on the device's touch screen in real time.

[0510] Specific examples

[0511] The sequence of actions a user can take to pet a virtual pet is shown below.

[0512] 1. The user strokes the pet image for 2 seconds.

[0513] 2. The device records the coordinate data of the touch point (x1, y1) to (x2, y2) and the timestamp (t1, t2).

[0514] 3. The device collects this data into packets and sends them to the server.

[0515] 4. The server uses generative AI to analyze the data and generate an animation of your pet happily wagging its tail.

[0516] 5. The server assembles the generated animation data into packets and sends them to the device.

[0517] 6. The device analyzes the received animation data and displays the pet's tail-wagging motion in real time.

[0518] 7. Users can visually see their pets enjoying themselves.

[0519] Prompt Sentence Examples

[0520] Below is an example of a prompt sentence to the generative AI model to test the specific behavior of the system.

[0521] prompt:

[0522] The user stroked the virtual pet on the smartphone screen for two seconds. The device detected this action and recorded the coordinate data (x1, y1) to (x2, y2) and the timestamp (t1, t2). The data was sent to the server, which used a generative AI to generate an animation of the pet happily wagging its tail. The animation data was sent to the device in real time, allowing the user to observe the pet's happy behavior in real time on their smartphone.

[0523] This system allows users to enjoy real-time interactions with virtual pets, allowing them to experience the human touch while avoiding the problems of keeping a real pet.

[0524] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0525] Step 1:

[0526] User operation detection

[0527] Input: The user operates the smartphone's touchscreen.

[0528] Specific action: The user strokes the image of the virtual pet for 2 seconds.

[0529] Data processing: The device's touchscreen records the coordinate data of the operation position (x1, y1) to (x2, y2), the swipe trajectory data, and the timestamp (t1, t2).

[0530] Output: Touch point coordinate data, swipe trajectory data, timestamp.

[0531] Step 2:

[0532] Sending operation data

[0533] Input: Recorded coordinate data, swipe trajectory data, timestamp.

[0534] Specific operation: The terminal collects data and organizes it into packets.

[0535] Data processing: Packaging data into packets for transmission.

[0536] Output: Data packet to send to the server.

[0537] Step 3:

[0538] Analysis and movement generation by the server

[0539] Input: Data packets sent from the terminal.

[0540] Specific operation: The server receives the data packet and uses the generated AI to analyze the operational data.

[0541] Data processing: Through analysis, the system determines that the user's action is a stroking motion and generates the animal's movements accordingly.

[0542] Output: Animation data of a happy virtual pet wagging its tail.

[0543] Step 4:

[0544] Sending interaction data

[0545] Input: The generated animation data.

[0546] Specific operation: The server packs the animation data into packets.

[0547] Data processing: Packaging animation data into packets for transmission.

[0548] Output: Animation data packets for sending to the device.

[0549] Step 5:

[0550] Real-time updates

[0551] Input: Animation data packet sent by the server.

[0552] Specific operation: The device receives the animation data and displays it on the touch screen.

[0553] Data processing: Analyze animation data and reproduce the movements of your virtual pet.

[0554] Output: The user can observe the happy tail wagging of the virtual pet in real time on the device screen.

[0555] (Application example 1)

[0556] 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."

[0557] In today's food delivery services, users have limited ways to enjoy the waiting time for their order. Furthermore, systems that provide conversational and emotional interactions to increase engagement and reduce stress are lacking. Furthermore, there is a demand for services that can respond in real time to specific user actions.

[0558] 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.

[0559] In this invention, the server includes means for detecting event data input by a user, means for transmitting the event data to the server, means for analyzing the event data and generating appropriate movements of a virtual character in the server, means for transmitting the generated movements of the virtual character to the terminal, means for displaying the received movements of the virtual character in real time on a display of the terminal, and means for the virtual character to generate a reaction related to a meal order in response to a specific operation by the user, thereby allowing the user to enjoy the time while waiting for their order, increasing engagement and reducing stress.

[0560] "User-input event data" refers to information about touches, swipes, clicks, and other actions performed by a user on a device, including touch point coordinate data and timestamps.

[0561] "Means for transmitting to the server" refers to a communication module or protocol that allows the terminal to transmit user operation data to the server in real time.

[0562] "Virtual character" refers to a digital character that runs on a computer and can interact with users.

[0563] "Virtual character movements" refers to various animations and reactions displayed by a virtual character, including expressions and movements such as happiness, sadness, and surprise.

[0564] "Means for transmitting to the terminal" refers to a communication module or protocol for transmitting animation data generated by the server to the terminal.

[0565] "Means for displaying in real time on a display" refers to a combination of software and hardware for instantly displaying the movements of a virtual character on the screen of a terminal.

[0566] "Specific user operations" refer to specific actions or inputs made by the user, such as ordering food or information about special dates.

[0567] The "means for generating a reaction related to a meal order" refers to a means for analyzing the user's meal order data and generating corresponding movements and facial expressions of the virtual character.

[0568] This invention is an interactive system that generates the movements of a virtual character based on event data entered by a user and displays reactions related to food orders. This section describes the program used to realize this system and the processing of that program.

[0569] Explanation of program processing

[0570] The system operates using a user terminal, a server, and a generative AI model.

[0571] Hardware and Software

[0572] User terminal: A device such as a smartphone or tablet, which includes a touchscreen, a communication module, and a display device.

[0573] Server: Cloud-based computing resources that run data analytics and generative AI models.

[0574] Generative AI model: For example, generative AI such as GPT-4 or DALL-E is used to analyze user operation data and generate the movements and facial expressions of a virtual character.

[0575] Data processing and calculation

[0576] 1. User event detection

[0577] When a user touches, swipes, or clicks on the smartphone screen, the action is detected by the user device, for example, when the user orders food from a food delivery app.

[0578] The user terminal records the coordinate data of the touch point, a timestamp, and the operation content (order data, etc.).

[0579] 2. Sending operation data

[0580] The user terminal transmits the collected event data (coordinate data, timestamp, and order data) to the server in real time.

[0581] 3. Analysis and movement generation by the server

[0582] The server analyzes the received event data and uses a generative AI model to generate appropriate movements and facial expressions for the virtual character.

[0583] For example, if a user orders a pizza, the generative AI generates a happy expression and tail wagging motion for the virtual character.

[0584] 4. Sending Interaction Data

[0585] The generated animation data is transmitted from the server to the user terminal.

[0586] 5. Real-time display

[0587] The user terminal immediately displays the received animation data, and the virtual character moves in real time.

[0588] This allows users to see the reactions of the virtual characters within the food delivery app, allowing them to enjoy the time they have while waiting for their order.

[0589] Adding specific examples

[0590] Example 1: When a user orders a pizza on a touchscreen, the user device collects coordinate data and order data and sends them to the server. The server then inputs a prompt to the generative AI model: "The user has ordered a pizza. Please generate a reaction that will make the pet happy.", and generates an animation of the virtual character.

[0591] Prompt Sentence Examples

[0592] "A user orders a pizza. Generate a reaction that will make their pet happy."

[0593] In this way, the present invention realizes a system that can provide interactive reactions to operations performed by users within a food delivery app, thereby increasing engagement.

[0594] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0595] Step 1:

[0596] A user operates the touchscreen of a smartphone to order food using a food delivery app. This operation includes selecting a specific food menu item and confirming the order. Touchpoint coordinate data, a timestamp, and the order details (e.g., pizza) are collected as input. These event data are generated as output.

[0597] Step 2:

[0598] The terminal sends the collected event data (coordinate data, timestamp, and order details) to the server in real time. The input is the event data generated in step 1, and the output is the data sent to the server. The communication module is used to send the data quickly and accurately.

[0599] Step 3:

[0600] The server analyzes the received event data to understand the user's operation. This analysis includes extracting the meal order details from the event data. The input is the event data sent from the device, and the output is the order details data as the analysis result.

[0601] Step 4:

[0602] The server uses the generative AI model to generate the movements and expressions of the virtual character according to the user's order. Specifically, the prompt statement "The user has ordered a pizza. Please generate a reaction that will please the pet." is input into the generative AI model, and animation data is generated based on that. The order data and prompt statement from the analysis results are used as input, and the generated animation data is obtained as output.

[0603] Step 5:

[0604] The generated animation data is sent from the server to the user's device. The input is the animation data output from the generative AI model, and the output is the data sent to the device. The animation data is sent in real time using a communication module.

[0605] Step 6:

[0606] The user device displays the received animation data on a display in real time. Specifically, the virtual character displays movements such as a happy expression or a wagging tail. The input is the animation data sent from the server, and the output is the animation visually displayed to the user.

[0607] This series of processes allows users to enjoy an interactive experience with virtual characters through the food delivery app, making the waiting time for their order more enjoyable.

[0608] 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.

[0609] As one embodiment of the present invention, a system that combines a virtual pet interaction system using a smartphone with an emotion engine that analyzes the user's emotions will be described in detail.

[0610] System configuration

[0611] The system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to sense the user's operations and an emotion engine that analyzes emotions, as well as a communication module that collects this data and transmits it to the server. The server uses generative AI to analyze the user's operation data and emotion data and generates virtual pet animations in real time.

[0612] Program processing (natural language explanation)

[0613] Sensing user actions and emotions

[0614] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[0615] Sending operational and emotional data

[0616] The device sends the collected coordinate data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0617] Analysis and movement generation by the server

[0618] The server analyzes the received event data and emotion data. At this time, a generation AI is used to determine the type of user operation and the user's emotional state at the time. For example, if the user is stroking the pet and has a happy expression, it is determined that the pet should be more active and happy, wagging its tail. Based on this judgment, the generation AI generates the virtual pet's movements and expressions and compiles them as animation data.

[0619] Sending interaction data

[0620] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[0621] Specific examples

[0622] When the user pets the pet, the following steps are performed.

[0623] 1. Sensing user actions and emotions

[0624] The user strokes the image of the pet with their finger.

[0625] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[0626] The emotion engine analyzes the user's facial expressions and voice to collect data on happy emotions.

[0627] 2. Transmission of operational and emotional data

[0628] The terminal transmits this data to the server.

[0629] 3. Analysis and movement generation by the server

[0630] The server analyzes the received data and recognizes that the user is enjoying the stroking action.

[0631] The generative AI responds to the user's operations and emotions to generate more lively, happy expressions and tail-wagging movements for the pet.

[0632] 4. Sending Interaction Data

[0633] The server transmits the generated animation data to the terminal.

[0634] 5. Real-time updates

[0635] The device displays the received animation data and plays back the pet's active tail-wagging action in real time.

[0636] Users can visually see their pet's joy on the screen, and their own emotions will be elevated along with it.

[0637] This system allows users to have an experience that feels like interacting with a real pet, which helps to alleviate feelings of loneliness and relieve stress, and provides responses based on the user's emotions, allowing for a more intimate experience.It serves as a new means of solving traditional problems of pet ownership, such as allergies, odors, and the burden of caring for them.

[0638] The processing flow will be explained below.

[0639] Step 1:

[0640] The user touches or swipes the smartphone screen.

[0641] The user strokes the image of the pet with his / her finger.

[0642] Step 2:

[0643] The terminal senses the user's operation and records the coordinate data and a timestamp.

[0644] The device collects touch point start and end points and swipe trajectory data.

[0645] The time information when the operation was performed is obtained as a timestamp.

[0646] Step 3:

[0647] An emotion engine within the device analyzes the user's emotional state.

[0648] The device analyzes the user's facial expressions and voice and collects emotional data in real time.

[0649] Step 4:

[0650] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[0651] The terminal assembles this data into data packets and transmits them to the server in real time.

[0652] Step 5:

[0653] The server analyzes the received event data and emotion data.

[0654] The server analyzes the coordinate data and timestamp and identifies the type of user operation (for example, stroking).

[0655] The server analyzes the emotion data sent from the emotion engine and determines the user's emotional state.

[0656] Step 6:

[0657] The server uses generative AI to generate animal movements and expressions based on the user's actions and emotions.

[0658] The generative AI determines the virtual pet's behavior (e.g., wagging its tail happily, jumping, etc.) based on the user's actions and emotional state.

[0659] The server packages the generated animation data into data packets.

[0660] Step 7:

[0661] The server transmits the generated interaction data to the terminal.

[0662] The server collects animation data into packets and sends them to the terminal.

[0663] Step 8:

[0664] The terminal displays the received animation data in real time.

[0665] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[0666] Users can instantly see their pet wagging its tail and bouncing on the screen.

[0667] Specific examples

[0668] The process flow when the user is enjoying petting a pet is as follows.

[0669] 1. Step 1:

[0670] The user strokes the image of the pet with their finger.

[0671] 2. Step 2:

[0672] The device detects touch events on the screen and records the coordinate data of the touch point and the trajectory data of the swipe.

[0673] Record the timestamp of the operation.

[0674] 3. Step 3:

[0675] The device's emotion engine analyzes the user's facial expressions and voice to determine their feelings of enjoyment.

[0676] 4. Step 4:

[0677] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[0678] 5. Step 5:

[0679] The server analyzes the coordinate data and timestamp and recognizes that a stroking action has been performed.

[0680] The server analyzes the received emotional data and determines that the user is enjoying themselves.

[0681] 6. Step 6:

[0682] The generating AI responds to the user's operations and emotions to generate a lively and happy tail-wagging behavior for the pet.

[0683] The server packages the generated animation data into packets.

[0684] 7. Step 7:

[0685] The server transmits this data to the terminal.

[0686] 8. Step 8:

[0687] The device displays the received animation data in real time, recreating the action of your pet happily wagging its tail.

[0688] Users can visually see their pets' happy expressions and enjoy the experience even more.

[0689] This system allows users to have an experience similar to interacting with a real pet, which helps to alleviate feelings of loneliness and stress. Furthermore, by providing responses according to the user's emotional state, it allows for a more intimate and fulfilling interaction.

[0690] Example 2

[0691] 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."

[0692] Conventional virtual pet systems have limited response to user input and are unable to fully reflect the user's emotions. Real-time responses are also insufficient, making it difficult to improve the user experience. Furthermore, there is a lack of means to analyze the user's emotions, making it difficult to provide a more intimate experience.

[0693] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing event data and emotion data input by the user and generating appropriate virtual pet movements using a generation AI, means for determining the virtual pet's movements and facial expressions based on the received data, and means for transmitting the generated virtual pet movements to the terminal. This enables the virtual pet to move in a way that reflects the user's operations and emotions in real time.

[0694] "User" refers to the person who operates the system and interacts with the virtual pet.

[0695] "Event data" refers to input information such as touch points and swipe trajectories generated when a user operates a device such as a smartphone.

[0696] "Emotion data" refers to data analyzed by the emotion engine based on the user's facial expressions, voice, etc.

[0697] "Server" refers to a computer system that analyzes collected event data and emotion data and generates appropriate virtual pet movements.

[0698] "Generative AI" refers to artificial intelligence technology that analyzes user operations and emotional data to generate the movements and facial expressions of a virtual pet.

[0699] "Virtual pet" refers to a digital pet character that operates on a display device such as a smartphone.

[0700] A "timestamp" refers to data that records the time when a user performs an operation.

[0701] "Real-time" refers to processing that responds immediately to user operations and emotions.

[0702] "Coordinate data" refers to data that records the position information of operations performed by a user on a touch screen.

[0703] "Display Device" means a device, such as a smartphone or tablet, that visually displays the movements and reactions of a virtual pet.

[0704] This invention is a system that senses user operations and emotions, and generates and displays the movements of a virtual pet in real time based on those operations. This system consists of a "terminal" that senses user operations, a "server" that analyzes the operation and emotion data and generates appropriate movements, and a "terminal" that displays the generated movements.

[0705] Hardware and software used

[0706] Terminal

[0707] A device is a mobile device such as a smartphone or tablet, and includes the following elements:

[0708] Touchscreen sensor: Detects user touch and swipe actions.

[0709] Camera and microphone: Captures the user's facial expressions and voice, providing data for analysis by the emotion engine.

[0710] Emotion engine: A software module that analyzes emotions from the user's facial expressions and voice.

[0711] Communication module: Sends collected operation and emotion data to the server.

[0712] server

[0713] A server is a powerful computer system that includes the following components:

[0714] Data analysis module: Analyzes the operation data and emotion data sent from the terminal.

[0715] Generative AI: Artificial intelligence that generates appropriate movements and facial expressions for a virtual pet based on analysis results.

[0716] Communication module: Sends the generated animation data to the terminal.

[0717] Specific actions

[0718] Here's a concrete example of how this system works:

[0719] Sensing user actions and emotions

[0720] When a user touches or swipes the smartphone screen, the device detects the action. For example, if the user strokes the image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the device's built-in emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[0721] Sending operational and emotional data

[0722] The device sends the collected touch point coordinate data, swipe trajectory data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0723] Analysis and movement generation by the server

[0724] The server analyzes the received operation data and emotional data. Using a generation AI, it determines what the user's operation was and what their emotional state was at the time. For example, when a petting operation and a happy facial expression are detected, the generation AI determines that the pet's behavior is appropriate for making the pet happy. Based on this judgment, the server generates the virtual pet's movements and facial expressions and compiles them as animation data.

[0725] Sending interaction data and updating it in real time

[0726] The server sends the generated animation data to the device, which then receives the animation data and displays it in real time. For example, immediately after a user strokes a pet, the pet's tail wagging motion on the screen is reproduced in real time.

[0727] Prompt Sentence Examples

[0728] The user pets the pet using a smartphone. The emotion engine analyzes the user's happy facial expression and generates how the virtual pet will react based on that data.

[0729] Using this prompt, the generative AI model can generate specific actions.

[0730] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0731] Step 1: Sensing user actions and emotions

[0732] When a user touches or swipes the smartphone screen, the device's touchscreen sensor detects and records the coordinate data of the touch point and the swipe trajectory data as input. At the same time, the device's camera and microphone capture the user's facial expressions and voice and provide this data as input to the emotion engine. The emotion engine analyzes this data and generates the user's emotional state as output. Specifically, if a user strokes the image of a pet and says "cute" with a smile, the emotion engine will collect happy emotion data.

[0733] Step 2: Sending Operation and Emotion Data

[0734] The device collects the touch point coordinate data, swipe trajectory data, timestamps, and emotion data collected in step 1 as input and sends them to the server. Using the communication module, this data is sent to the server in real time. For example, the coordinate data of the moment you stroke your pet and the voice analysis results, such as "cute," are sent to the server.

[0735] Step 3: Server analysis and motion generation

[0736] The server receives the operation data and emotion data sent in step 2 and analyzes them as input in the data analysis module. Based on the analysis results, the generation AI determines the user's operation and emotional state, and generates appropriate movements and facial expressions for the virtual pet as output. For example, if a stroking operation and a happy emotion are detected, the generation AI determines that the pet will happily wag its tail and generates this as animation data.

[0737] Step 4: Sending interaction data

[0738] The server organizes the animation data generated in step 3 as input and sends it to the terminal. Using a communication module, the generated animation data is sent to the terminal in real time. For example, animation data of a pet wagging its tail is sent to the terminal.

[0739] Step 5: Real-time updates

[0740] The terminal receives the animation data sent in step 4 and processes it as input. The terminal plays the received animation data in real time on a display device, providing the user with visual feedback as output. For example, immediately after the user pets the pet, the pet's tail wagging action is displayed on the screen in real time. As a result, the user can see the pet's reaction immediately.

[0741] (Application example 2)

[0742] 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."

[0743] Conventional food delivery services have faced problems such as stress and dissatisfaction from users due to delivery delays and order cancellations. Furthermore, there is a lack of systems that can respond to users' emotions, creating a need for an improved user experience. This invention aims to solve these problems by analyzing users' emotions and providing a delivery experience that is customized accordingly.

[0744] 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 including an emotion engine that collects and analyzes user emotion data, means for generating the movements and facial expressions of the pseudo-creature based on the emotion data, and means for providing customized information based on the user's emotions and operations. This makes it possible to reduce user stress caused by delivery delays, order cancellations, etc., and improve the user experience.

[0745] "Event data input by a user" is operation information generated when a user operates a terminal, and is data indicating input actions such as touching, swiping, and clicking.

[0746] "Emotion data" is data that indicates the emotional state of the user analyzed from the user's voice, facial expression, gestures, etc., and is information that reflects the user's psychological state.

[0747] An "emotion engine" is software for analyzing a user's emotions, and is a program with the function of generating emotion data through facial expression recognition, voice analysis, etc.

[0748] "Generative AI" is an artificial intelligence technology that analyzes user operation data and emotional data and generates appropriate responses and actions based on that data.

[0749] A "pseudo-creature" is a virtual creature designed to interact with users like a virtual pet, and is a character that displays movements and expressions on a display.

[0750] "The behavior of the generated pseudo-creature" refers to the actions and reactions of the pseudo-creature determined by the generating AI based on the user's operations and emotions.

[0751] This invention is a system for food delivery services that analyzes user emotions and provides a customized delivery experience. This system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate actions, and a "terminal" that displays the generated actions.

[0752] System configuration

[0753] 1. Terminal

[0754] Touchscreen: Used to sense user interaction.

[0755] Camera: Captures the user's facial expressions and collects emotional data.

[0756] Microphone: Captures the user's voice and analyzes emotional data.

[0757] Communication module: Sends collected operation data and emotion data to the server in real time.

[0758] 2. Server

[0759] Emotion engine (e.g., Affectiva API): Software that analyzes emotions from a user's facial expressions and voice.

[0760] Generative AI (e.g., GPT-4): Artificial intelligence that analyzes user actions and emotional data to generate appropriate behaviors and responses.

[0761] 3. Applications on the device

[0762] The behavior of the generated pseudo-creature is displayed in real time.

[0763] Program processing (natural language explanation)

[0764] Sensing user actions and emotions

[0765] When a user touches or swipes the smartphone screen, the corresponding device detects the action. For example, when a user places an order on a food delivery app, the operation data is recorded. Meanwhile, the user's face is captured by the camera and analyzed by the emotion engine. The user's voice is also collected by the microphone and analyzed as emotion data.

[0766] Sending operational and emotional data

[0767] The device sends the collected operation data, emotion data, and timestamps to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0768] Analysis and movement generation by the server

[0769] The server analyzes the received data using an emotion engine (Affectiva API) and a generative AI (GPT-4 model) to determine the user's actions and emotional state. For example, if a delivery is delayed, the emotion engine detects the user's dissatisfaction, and the generative AI generates actions of the simulated creature to comfort the user.

[0770] Sending and viewing interaction data

[0771] The server sends the generated animation data to the device, which receives the data and displays it to the user in real time, allowing the user to visually confirm the movements of the simulated creature and alleviate their emotions.

[0772] Specific examples

[0773] If delivery is delayed

[0774] 1. Sensing user actions and emotions

[0775] The user opens the delivery app to check the delivery status.

[0776] The camera captures the user's facial expressions and the emotion engine collects the displeased emotion data.

[0777] 2. Transmission of operational and emotional data

[0778] The terminal transmits this data to the server.

[0779] 3. Analysis and movement generation by the server

[0780] The server analyzes the delay notification and the displeased emotion data, and the generative AI (GPT-4) generates the behavior of a charming pseudo-creature that says, "Delicious food will arrive soon, so please be patient a little longer!"

[0781] 4. Sending and Displaying Interaction Data

[0782] The server transmits the generated data to the terminal and displays it to the user in real time.

[0783] Example prompts for generative AI models

[0784] User emotion: Sad

[0785] Delivery status: Delayed

[0786] Pet action: Generate an animation where the pet apologizes and says something funny to brighten the user's mood.

[0787] Using this prompt, the generative AI model generates an appropriate response and implements an action that corresponds to the user's emotions.

[0788] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0789] Step 1: Sensing user actions and emotions

[0790] A user places an order on a food delivery app. The device collects operation data through the touchscreen. It also uses a camera and microphone to capture the user's facial expressions and voice, obtaining emotion data. This data includes touch point coordinates, timestamps, and the analysis results (user's emotional state) by the emotion engine. The input is the operation data and emotion data, and the output is a data package.

[0791] Step 2: Sending Operation and Emotion Data

[0792] The terminal transmits the collected operation data and emotion data to the server in real time. Using the communication module, the operation data includes the coordinates of the touch points and a timestamp, and the emotion data includes the analysis results (for example, whether the user is happy or sad). The input is the operation data and emotion data, and the output is the state in which they are transmitted to the server.

[0793] Step 3: Server analysis and motion generation

[0794] The server analyzes the received operation data and emotional data. First, it examines the user's emotional state using an emotion engine (e.g., Affectiva API) and passes the results to a generation AI (e.g., GPT-4). The generation AI generates appropriate movements and facial expressions for the simulated creature based on the given prompts. For example, if a delivery is delayed or the user is in a bad mood, the simulated creature will generate movements to comfort the user. The input is operation data and emotional data, and the output is the movements (animation data) of the generated simulated creature.

[0795] Step 4: Sending interaction data

[0796] The server sends the generated motion data of the pseudo-creature to the terminal. When sent to the terminal, the animation data and an accompanying timestamp are included in the data package. The input is the generated animation data, and the output is the state of the transmitted data as it arrives at the terminal.

[0797] Step 5: Displaying the behavior of the mimic creature

[0798] The device interprets the received animation data and displays it to the user in real time. The animation engine renders the movements of the simulated creature and plays them on the screen, allowing the user to visually confirm how the simulated creature is behaving in accordance with their own emotions. The input is the animation data sent from the server, and the output is the movements played on the screen.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] [Third embodiment]

[0803] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0804] 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.

[0805] 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).

[0806] 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.

[0807] 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.

[0808] 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).

[0809] 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. 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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."

[0815] As one embodiment of the present invention, a virtual pet interaction system using a smartphone will be described in detail below.

[0816] System configuration

[0817] The system consists of a "terminal" that detects user operations, a "server" that analyzes the operation data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to detect user operations and a communication module that transmits event data to the server. The server uses generative AI to analyze the user's operation data and generate virtual pet animations in real time.

[0818] Program processing (natural language explanation)

[0819] User operation detection

[0820] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. Each action is also time-stamped, and the time information of the action is also collected.

[0821] Sending operation data

[0822] The device sends the collected coordinate data and timestamp to the server as event data. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[0823] Analysis and movement generation by the server

[0824] The server analyzes the received event data. At this time, a generation AI is used to determine what kind of operation the user performed. For example, if the operation was stroking, it is determined that the appropriate action would be for the pet to wag its tail in delight. Based on this determination, the generation AI generates the movements and expressions of the virtual pet and compiles them as animation data.

[0825] Sending interaction data

[0826] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[0827] Specific examples

[0828] When the user pets the pet, the following steps are performed.

[0829] 1. User operation detection

[0830] The user strokes the image of the pet with their finger.

[0831] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[0832] 2. Sending operation data

[0833] The terminal transmits this data to the server.

[0834] 3. Analysis and movement generation by the server

[0835] The server analyzes the received data and recognizes that the user has performed a stroking action.

[0836] The generating AI responds to user input by generating a happy expression and tail-wagging behavior for the pet.

[0837] 4. Sending Interaction Data

[0838] The server transmits the generated animation data to the terminal.

[0839] 5. Real-time updates

[0840] The device displays the received animation data and plays back the pet's tail-wagging action in real time.

[0841] Users can visually see their pet's joy on the screen.

[0842] This system allows users to have an experience that feels like interacting with a real pet, helping to alleviate feelings of loneliness and reduce stress. It also serves as a new means of solving traditional problems with pet ownership, such as allergies, odors, and the burden of caring for a pet.

[0843] The processing flow will be explained below.

[0844] Step 1:

[0845] The user touches or swipes the smartphone screen.

[0846] The user strokes the image of the pet with his / her finger.

[0847] Step 2:

[0848] The terminal senses the user's operation and records the coordinate data and a timestamp.

[0849] The device collects touch point start and end points and swipe trajectory data.

[0850] The time information when the operation was performed is obtained as a timestamp.

[0851] Step 3:

[0852] The terminal transmits the collected event data to the server.

[0853] The terminal assembles the coordinate data and timestamp into a data packet and transmits it to the server in real time.

[0854] Step 4:

[0855] The server analyzes the received event data.

[0856] The server analyzes the data and recognizes the type of user operation (for example, stroking).

[0857] Based on the analysis results, it is decided what reaction the pet will have.

[0858] Step 5:

[0859] The server uses generative AI to generate animal movements and expressions in response to user input.

[0860] Based on the analysis results, the generation AI generates animation data for the virtual pet's happy expression and tail wagging.

[0861] The server assembles the generated animal movements into data packets.

[0862] Step 6:

[0863] The server transmits the generated interaction data to the terminal.

[0864] The server collects animation data into packets and sends them to the terminal.

[0865] Step 7:

[0866] The terminal displays the received animation data in real time.

[0867] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[0868] Users can instantly watch their pet wag its tail and show signs of happiness on the screen.

[0869] Example 1

[0870] 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."

[0871] Conventional virtual pet systems suffer from delayed responses to user operations and a lack of real-time capabilities. Furthermore, the animals' reactions to various user operation patterns are limited, resulting in a lack of interactive experience. Furthermore, conventional systems have difficulty analyzing complex operations and generating movements, making it difficult to improve the user experience.

[0872] 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.

[0873] In this invention, the server includes a means for analyzing event data input by the user, a means for generating appropriate animal movements using a generation AI, and a means for transmitting the generated animal movements to the terminal, thereby providing a virtual pet system that responds to user operations in real time.

[0874] "Event data" is data that includes operation information input by the user.

[0875] The "server" is a computing device that analyzes the received event data and performs the processing to generate appropriate animal movements.

[0876] "Generative AI" is an artificial intelligence model that learns user operation data and generates appropriate animal movements and facial expressions based on the input.

[0877] "Coordinate data" is data that indicates a specific position on the screen that the user touched.

[0878] A "timestamp" is data that records the specific time at which a user operation was performed.

[0879] "Real-time update" means that data is received and displayed almost simultaneously, providing feedback to the user without delay.

[0880] The "screen" is a display device that allows the user to input operations and visually confirm the movements and expressions of the animals.

[0881] The present invention relates to a system that allows users to enjoy the real-time reactions of a virtual pet by operating a touch screen. The system includes a terminal that detects user operations, a server that analyzes the operation data and generates appropriate movements, and a terminal that displays the generated movements.

[0882] Hardware and Software Configuration

[0883] The main components of the system are:

[0884] Device:

[0885] Touchscreen: Sensitive to user touches and swipes.

[0886] Communication module: Provides a communication means for transmitting detected operation data to the server.

[0887] server:

[0888] Generative AI (e.g., OpenAI's GPT-4): Analyzes user operation data and generates the movements and expressions of a virtual pet based on that data.

[0889] Analysis device: Analyzes the event data sent from the device.

[0890] Data processing and calculation

[0891] User operation detection

[0892] When a user strokes or taps a virtual pet on the smartphone touchscreen, the device collects coordinate data of the operation position and swipe trajectory data, and assigns a timestamp to the data.

[0893] Sending operation data

[0894] The terminal assembles the collected coordinate data and timestamp into a packet as event data and sends it to the server via the communication module.

[0895] Analysis and movement generation by the server

[0896] The server uses a generative AI to analyze the received event data. Based on the analysis results, it determines whether the user's action is a stroking or tapping, and generates appropriate movements and expressions for the virtual pet. For example, if the user stroking the pet, the server generates a motion that makes the pet wag its tail in joy.

[0897] Sending interaction data

[0898] The generated animation data is sent from the server to the device, where it is displayed on the device's touch screen in real time.

[0899] Specific examples

[0900] The sequence of actions a user can take to pet a virtual pet is shown below.

[0901] 1. The user strokes the pet image for 2 seconds.

[0902] 2. The device records the coordinate data of the touch point (x1, y1) to (x2, y2) and the timestamp (t1, t2).

[0903] 3. The device collects this data into packets and sends them to the server.

[0904] 4. The server uses generative AI to analyze the data and generate an animation of your pet happily wagging its tail.

[0905] 5. The server assembles the generated animation data into packets and sends them to the device.

[0906] 6. The device analyzes the received animation data and displays the pet's tail-wagging motion in real time.

[0907] 7. Users can visually see their pets enjoying themselves.

[0908] Prompt Sentence Examples

[0909] Below is an example of a prompt sentence to the generative AI model to test the specific behavior of the system.

[0910] prompt:

[0911] The user stroked the virtual pet on the smartphone screen for two seconds. The device detected this action and recorded the coordinate data (x1, y1) to (x2, y2) and the timestamp (t1, t2). The data was sent to the server, which used a generative AI to generate an animation of the pet happily wagging its tail. The animation data was sent to the device in real time, allowing the user to observe the pet's happy behavior in real time on their smartphone.

[0912] This system allows users to enjoy real-time interactions with virtual pets, allowing them to experience the human touch while avoiding the problems of keeping a real pet.

[0913] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0914] Step 1:

[0915] User operation detection

[0916] Input: The user operates the smartphone's touchscreen.

[0917] Specific action: The user strokes the image of the virtual pet for 2 seconds.

[0918] Data processing: The device's touchscreen records the coordinate data of the operation position (x1, y1) to (x2, y2), the swipe trajectory data, and the timestamp (t1, t2).

[0919] Output: Touch point coordinate data, swipe trajectory data, timestamp.

[0920] Step 2:

[0921] Sending operation data

[0922] Input: Recorded coordinate data, swipe trajectory data, timestamp.

[0923] Specific operation: The terminal collects data and organizes it into packets.

[0924] Data processing: Packaging data into packets for transmission.

[0925] Output: Data packet to send to the server.

[0926] Step 3:

[0927] Analysis and movement generation by the server

[0928] Input: Data packets sent from the terminal.

[0929] Specific operation: The server receives the data packet and uses the generated AI to analyze the operational data.

[0930] Data processing: Through analysis, the system determines that the user's action is a stroking motion and generates the animal's movements accordingly.

[0931] Output: Animation data of a happy virtual pet wagging its tail.

[0932] Step 4:

[0933] Sending interaction data

[0934] Input: The generated animation data.

[0935] Specific operation: The server packs the animation data into packets.

[0936] Data processing: Packaging animation data into packets for transmission.

[0937] Output: Animation data packets for sending to the device.

[0938] Step 5:

[0939] Real-time updates

[0940] Input: Animation data packet sent by the server.

[0941] Specific operation: The device receives the animation data and displays it on the touch screen.

[0942] Data processing: Analyze animation data and reproduce the movements of your virtual pet.

[0943] Output: The user can observe the happy tail wagging of the virtual pet in real time on the device screen.

[0944] (Application example 1)

[0945] 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."

[0946] In today's food delivery services, users have limited ways to enjoy the waiting time for their order. Furthermore, systems that provide conversational and emotional interactions to increase engagement and reduce stress are lacking. Furthermore, there is a demand for services that can respond in real time to specific user actions.

[0947] 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.

[0948] In this invention, the server includes means for detecting event data input by a user, means for transmitting the event data to the server, means for analyzing the event data and generating appropriate movements of a virtual character in the server, means for transmitting the generated movements of the virtual character to the terminal, means for displaying the received movements of the virtual character in real time on a display of the terminal, and means for the virtual character to generate a reaction related to a meal order in response to a specific operation by the user, thereby allowing the user to enjoy the time while waiting for their order, increasing engagement and reducing stress.

[0949] "User-input event data" refers to information about touches, swipes, clicks, and other actions performed by a user on a device, including touch point coordinate data and timestamps.

[0950] "Means for transmitting to the server" refers to a communication module or protocol that allows the terminal to transmit user operation data to the server in real time.

[0951] "Virtual character" refers to a digital character that runs on a computer and can interact with users.

[0952] "Virtual character movements" refers to various animations and reactions displayed by a virtual character, including expressions and movements such as happiness, sadness, and surprise.

[0953] "Means for transmitting to the terminal" refers to a communication module or protocol for transmitting animation data generated by the server to the terminal.

[0954] "Means for displaying in real time on a display" refers to a combination of software and hardware for instantly displaying the movements of a virtual character on the screen of a terminal.

[0955] "Specific user operations" refer to specific actions or inputs made by the user, such as ordering food or information about special dates.

[0956] The "means for generating a reaction related to a meal order" refers to a means for analyzing the user's meal order data and generating corresponding movements and facial expressions of the virtual character.

[0957] This invention is an interactive system that generates the movements of a virtual character based on event data entered by a user and displays reactions related to food orders. This section describes the program used to realize this system and the processing of that program.

[0958] Explanation of program processing

[0959] The system operates using a user terminal, a server, and a generative AI model.

[0960] Hardware and Software

[0961] User terminal: A device such as a smartphone or tablet, which includes a touchscreen, a communication module, and a display device.

[0962] Server: Cloud-based computing resources that run data analytics and generative AI models.

[0963] Generative AI model: For example, generative AI such as GPT-4 or DALL-E is used to analyze user operation data and generate the movements and facial expressions of a virtual character.

[0964] Data processing and calculation

[0965] 1. User event detection

[0966] When a user touches, swipes, or clicks on the smartphone screen, the action is detected by the user device, for example, when the user orders food from a food delivery app.

[0967] The user terminal records the coordinate data of the touch point, a timestamp, and the operation content (order data, etc.).

[0968] 2. Sending operation data

[0969] The user terminal transmits the collected event data (coordinate data, timestamp, and order data) to the server in real time.

[0970] 3. Analysis and movement generation by the server

[0971] The server analyzes the received event data and uses a generative AI model to generate appropriate movements and facial expressions for the virtual character.

[0972] For example, if a user orders a pizza, the generative AI generates a happy expression and tail wagging motion for the virtual character.

[0973] 4. Sending Interaction Data

[0974] The generated animation data is transmitted from the server to the user terminal.

[0975] 5. Real-time display

[0976] The user terminal immediately displays the received animation data, and the virtual character moves in real time.

[0977] This allows users to see the reactions of the virtual characters within the food delivery app, allowing them to enjoy the time they have while waiting for their order.

[0978] Adding specific examples

[0979] Example 1: When a user orders a pizza on a touchscreen, the user device collects coordinate data and order data and sends them to the server. The server then inputs a prompt to the generative AI model: "The user has ordered a pizza. Please generate a reaction that will make the pet happy.", and generates an animation of the virtual character.

[0980] Prompt Sentence Examples

[0981] "A user orders a pizza. Generate a reaction that will make their pet happy."

[0982] In this way, the present invention realizes a system that can provide interactive reactions to operations performed by users within a food delivery app, thereby increasing engagement.

[0983] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0984] Step 1:

[0985] A user operates the touchscreen of a smartphone to order food using a food delivery app. This operation includes selecting a specific food menu item and confirming the order. Touchpoint coordinate data, a timestamp, and the order details (e.g., pizza) are collected as input. These event data are generated as output.

[0986] Step 2:

[0987] The terminal sends the collected event data (coordinate data, timestamp, and order details) to the server in real time. The input is the event data generated in step 1, and the output is the data sent to the server. The communication module is used to send the data quickly and accurately.

[0988] Step 3:

[0989] The server analyzes the received event data to understand the user's operation. This analysis includes extracting the meal order details from the event data. The input is the event data sent from the device, and the output is the order details data as the analysis result.

[0990] Step 4:

[0991] The server uses the generative AI model to generate the movements and expressions of the virtual character according to the user's order. Specifically, the prompt statement "The user has ordered a pizza. Please generate a reaction that will please the pet." is input into the generative AI model, and animation data is generated based on that. The order data and prompt statement from the analysis results are used as input, and the generated animation data is obtained as output.

[0992] Step 5:

[0993] The generated animation data is sent from the server to the user's device. The input is the animation data output from the generative AI model, and the output is the data sent to the device. The animation data is sent in real time using a communication module.

[0994] Step 6:

[0995] The user device displays the received animation data on a display in real time. Specifically, the virtual character displays movements such as a happy expression or a wagging tail. The input is the animation data sent from the server, and the output is the animation visually displayed to the user.

[0996] This series of processes allows users to enjoy an interactive experience with virtual characters through the food delivery app, making the waiting time for their order more enjoyable.

[0997] 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.

[0998] As one embodiment of the present invention, a system that combines a virtual pet interaction system using a smartphone with an emotion engine that analyzes the user's emotions will be described in detail.

[0999] System configuration

[1000] The system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to sense the user's operations and an emotion engine that analyzes emotions, as well as a communication module that collects this data and transmits it to the server. The server uses generative AI to analyze the user's operation data and emotion data and generates virtual pet animations in real time.

[1001] Program processing (natural language explanation)

[1002] Sensing user actions and emotions

[1003] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[1004] Sending operational and emotional data

[1005] The device sends the collected coordinate data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[1006] Analysis and movement generation by the server

[1007] The server analyzes the received event data and emotion data. At this time, a generation AI is used to determine the type of user operation and the user's emotional state at the time. For example, if the user is stroking the pet and has a happy expression, it is determined that the pet should be more active and happy, wagging its tail. Based on this judgment, the generation AI generates the virtual pet's movements and expressions and compiles them as animation data.

[1008] Sending interaction data

[1009] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[1010] Specific examples

[1011] When the user pets the pet, the following steps are performed.

[1012] 1. Sensing user actions and emotions

[1013] The user strokes the image of the pet with their finger.

[1014] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[1015] The emotion engine analyzes the user's facial expressions and voice to collect data on happy emotions.

[1016] 2. Transmission of operational and emotional data

[1017] The terminal transmits this data to the server.

[1018] 3. Analysis and movement generation by the server

[1019] The server analyzes the received data and recognizes that the user is enjoying the stroking action.

[1020] The generative AI responds to the user's operations and emotions to generate more lively, happy expressions and tail-wagging movements for the pet.

[1021] 4. Sending Interaction Data

[1022] The server transmits the generated animation data to the terminal.

[1023] 5. Real-time updates

[1024] The device displays the received animation data and plays back the pet's active tail-wagging action in real time.

[1025] Users can visually see their pet's joy on the screen, and their own emotions will be elevated along with it.

[1026] This system allows users to have an experience that feels like interacting with a real pet, which helps to alleviate feelings of loneliness and relieve stress, and provides responses based on the user's emotions, allowing for a more intimate experience.It serves as a new means of solving traditional problems of pet ownership, such as allergies, odors, and the burden of caring for them.

[1027] The processing flow will be explained below.

[1028] Step 1:

[1029] The user touches or swipes the smartphone screen.

[1030] The user strokes the image of the pet with his / her finger.

[1031] Step 2:

[1032] The terminal senses the user's operation and records the coordinate data and a timestamp.

[1033] The device collects touch point start and end points and swipe trajectory data.

[1034] The time information when the operation was performed is obtained as a timestamp.

[1035] Step 3:

[1036] An emotion engine within the device analyzes the user's emotional state.

[1037] The device analyzes the user's facial expressions and voice and collects emotional data in real time.

[1038] Step 4:

[1039] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[1040] The terminal assembles this data into data packets and transmits them to the server in real time.

[1041] Step 5:

[1042] The server analyzes the received event data and emotion data.

[1043] The server analyzes the coordinate data and timestamp and identifies the type of user operation (for example, stroking).

[1044] The server analyzes the emotion data sent from the emotion engine and determines the user's emotional state.

[1045] Step 6:

[1046] The server uses generative AI to generate animal movements and expressions based on the user's actions and emotions.

[1047] The generative AI determines the virtual pet's behavior (e.g., wagging its tail happily, jumping, etc.) based on the user's actions and emotional state.

[1048] The server packages the generated animation data into data packets.

[1049] Step 7:

[1050] The server transmits the generated interaction data to the terminal.

[1051] The server collects animation data into packets and sends them to the terminal.

[1052] Step 8:

[1053] The terminal displays the received animation data in real time.

[1054] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[1055] Users can instantly see their pet wagging its tail and bouncing on the screen.

[1056] Specific examples

[1057] The process flow when the user is enjoying petting a pet is as follows.

[1058] 1. Step 1:

[1059] The user strokes the image of the pet with their finger.

[1060] 2. Step 2:

[1061] The device detects touch events on the screen and records the coordinate data of the touch point and the trajectory data of the swipe.

[1062] Record the timestamp of the operation.

[1063] 3. Step 3:

[1064] The device's emotion engine analyzes the user's facial expressions and voice to determine their feelings of enjoyment.

[1065] 4. Step 4:

[1066] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[1067] 5. Step 5:

[1068] The server analyzes the coordinate data and timestamp and recognizes that a stroking action has been performed.

[1069] The server analyzes the received emotional data and determines that the user is enjoying themselves.

[1070] 6. Step 6:

[1071] The generating AI responds to the user's operations and emotions to generate a lively and happy tail-wagging behavior for the pet.

[1072] The server packages the generated animation data into packets.

[1073] 7. Step 7:

[1074] The server transmits this data to the terminal.

[1075] 8. Step 8:

[1076] The device displays the received animation data in real time, recreating the action of your pet happily wagging its tail.

[1077] Users can visually see their pets' happy expressions and enjoy the experience even more.

[1078] This system allows users to have an experience similar to interacting with a real pet, which helps to alleviate feelings of loneliness and stress. Furthermore, by providing responses according to the user's emotional state, it allows for a more intimate and fulfilling interaction.

[1079] Example 2

[1080] 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."

[1081] Conventional virtual pet systems have limited response to user input and are unable to fully reflect the user's emotions. Real-time responses are also insufficient, making it difficult to improve the user experience. Furthermore, there is a lack of means to analyze the user's emotions, making it difficult to provide a more intimate experience.

[1082] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing event data and emotion data input by the user and generating appropriate virtual pet movements using a generation AI, means for determining the virtual pet's movements and facial expressions based on the received data, and means for transmitting the generated virtual pet movements to the terminal. This enables the virtual pet to move in a way that reflects the user's operations and emotions in real time.

[1083] "User" refers to the person who operates the system and interacts with the virtual pet.

[1084] "Event data" refers to input information such as touch points and swipe trajectories generated when a user operates a device such as a smartphone.

[1085] "Emotion data" refers to data analyzed by the emotion engine based on the user's facial expressions, voice, etc.

[1086] "Server" refers to a computer system that analyzes collected event data and emotion data and generates appropriate virtual pet movements.

[1087] "Generative AI" refers to artificial intelligence technology that analyzes user operations and emotional data to generate the movements and facial expressions of a virtual pet.

[1088] "Virtual pet" refers to a digital pet character that operates on a display device such as a smartphone.

[1089] A "timestamp" refers to data that records the time when a user performs an operation.

[1090] "Real-time" refers to processing that responds immediately to user operations and emotions.

[1091] "Coordinate data" refers to data that records the position information of operations performed by a user on a touch screen.

[1092] "Display Device" means a device, such as a smartphone or tablet, that visually displays the movements and reactions of a virtual pet.

[1093] This invention is a system that senses user operations and emotions, and generates and displays the movements of a virtual pet in real time based on those operations. This system consists of a "terminal" that senses user operations, a "server" that analyzes the operation and emotion data and generates appropriate movements, and a "terminal" that displays the generated movements.

[1094] Hardware and software used

[1095] Terminal

[1096] A device is a mobile device such as a smartphone or tablet, and includes the following elements:

[1097] Touchscreen sensor: Detects user touch and swipe actions.

[1098] Camera and microphone: Captures the user's facial expressions and voice, providing data for analysis by the emotion engine.

[1099] Emotion engine: A software module that analyzes emotions from the user's facial expressions and voice.

[1100] Communication module: Sends collected operation and emotion data to the server.

[1101] server

[1102] A server is a powerful computer system that includes the following components:

[1103] Data analysis module: Analyzes the operation data and emotion data sent from the terminal.

[1104] Generative AI: Artificial intelligence that generates appropriate movements and facial expressions for a virtual pet based on analysis results.

[1105] Communication module: Sends the generated animation data to the terminal.

[1106] Specific actions

[1107] Here's a concrete example of how this system works:

[1108] Sensing user actions and emotions

[1109] When a user touches or swipes the smartphone screen, the device detects the action. For example, if the user strokes the image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the device's built-in emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[1110] Sending operational and emotional data

[1111] The device sends the collected touch point coordinate data, swipe trajectory data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[1112] Analysis and movement generation by the server

[1113] The server analyzes the received operation data and emotional data. Using a generation AI, it determines what the user's operation was and what their emotional state was at the time. For example, when a petting operation and a happy facial expression are detected, the generation AI determines that the pet's behavior is appropriate for making the pet happy. Based on this judgment, the server generates the virtual pet's movements and facial expressions and compiles them as animation data.

[1114] Sending interaction data and updating it in real time

[1115] The server sends the generated animation data to the device, which then receives the animation data and displays it in real time. For example, immediately after a user strokes a pet, the pet's tail wagging motion on the screen is reproduced in real time.

[1116] Prompt Sentence Examples

[1117] The user pets the pet using a smartphone. The emotion engine analyzes the user's happy facial expression and generates how the virtual pet will react based on that data.

[1118] Using this prompt, the generative AI model can generate specific actions.

[1119] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1120] Step 1: Sensing user actions and emotions

[1121] When a user touches or swipes the smartphone screen, the device's touchscreen sensor detects and records the coordinate data of the touch point and the swipe trajectory data as input. At the same time, the device's camera and microphone capture the user's facial expressions and voice and provide this data as input to the emotion engine. The emotion engine analyzes this data and generates the user's emotional state as output. Specifically, if a user strokes the image of a pet and says "cute" with a smile, the emotion engine will collect happy emotion data.

[1122] Step 2: Sending Operation and Emotion Data

[1123] The device collects the touch point coordinate data, swipe trajectory data, timestamps, and emotion data collected in step 1 as input and sends them to the server. Using the communication module, this data is sent to the server in real time. For example, the coordinate data of the moment you stroke your pet and the voice analysis results, such as "cute," are sent to the server.

[1124] Step 3: Server analysis and motion generation

[1125] The server receives the operation data and emotion data sent in step 2 and analyzes them as input in the data analysis module. Based on the analysis results, the generation AI determines the user's operation and emotional state, and generates appropriate movements and facial expressions for the virtual pet as output. For example, if a stroking operation and a happy emotion are detected, the generation AI determines that the pet will happily wag its tail and generates this as animation data.

[1126] Step 4: Sending interaction data

[1127] The server organizes the animation data generated in step 3 as input and sends it to the terminal. Using a communication module, the generated animation data is sent to the terminal in real time. For example, animation data of a pet wagging its tail is sent to the terminal.

[1128] Step 5: Real-time updates

[1129] The terminal receives the animation data sent in step 4 and processes it as input. The terminal plays the received animation data in real time on a display device, providing the user with visual feedback as output. For example, immediately after the user pets the pet, the pet's tail wagging action is displayed on the screen in real time. As a result, the user can see the pet's reaction immediately.

[1130] (Application example 2)

[1131] 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."

[1132] Conventional food delivery services have faced problems such as stress and dissatisfaction from users due to delivery delays and order cancellations. Furthermore, there is a lack of systems that can respond to users' emotions, creating a need for an improved user experience. This invention aims to solve these problems by analyzing users' emotions and providing a delivery experience that is customized accordingly.

[1133] 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 including an emotion engine that collects and analyzes user emotion data, means for generating the movements and facial expressions of the pseudo-creature based on the emotion data, and means for providing customized information based on the user's emotions and operations. This makes it possible to reduce user stress caused by delivery delays, order cancellations, etc., and improve the user experience.

[1134] "Event data input by a user" is operation information generated when a user operates a terminal, and is data indicating input actions such as touching, swiping, and clicking.

[1135] "Emotion data" is data that indicates the emotional state of the user analyzed from the user's voice, facial expression, gestures, etc., and is information that reflects the user's psychological state.

[1136] An "emotion engine" is software for analyzing a user's emotions, and is a program with the function of generating emotion data through facial expression recognition, voice analysis, etc.

[1137] "Generative AI" is an artificial intelligence technology that analyzes user operation data and emotional data and generates appropriate responses and actions based on that data.

[1138] A "pseudo-creature" is a virtual creature designed to interact with users like a virtual pet, and is a character that displays movements and expressions on a display.

[1139] "The behavior of the generated pseudo-creature" refers to the actions and reactions of the pseudo-creature determined by the generating AI based on the user's operations and emotions.

[1140] This invention is a system for food delivery services that analyzes user emotions and provides a customized delivery experience. This system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate actions, and a "terminal" that displays the generated actions.

[1141] System configuration

[1142] 1. Terminal

[1143] Touchscreen: Used to sense user interaction.

[1144] Camera: Captures the user's facial expressions and collects emotional data.

[1145] Microphone: Captures the user's voice and analyzes emotional data.

[1146] Communication module: Sends collected operation data and emotion data to the server in real time.

[1147] 2. Server

[1148] Emotion engine (e.g., Affectiva API): Software that analyzes emotions from a user's facial expressions and voice.

[1149] Generative AI (e.g., GPT-4): Artificial intelligence that analyzes user actions and emotional data to generate appropriate behaviors and responses.

[1150] 3. Applications on the device

[1151] The behavior of the generated pseudo-creature is displayed in real time.

[1152] Program processing (natural language explanation)

[1153] Sensing user actions and emotions

[1154] When a user touches or swipes the smartphone screen, the corresponding device detects the action. For example, when a user places an order on a food delivery app, the operation data is recorded. Meanwhile, the user's face is captured by the camera and analyzed by the emotion engine. The user's voice is also collected by the microphone and analyzed as emotion data.

[1155] Sending operational and emotional data

[1156] The device sends the collected operation data, emotion data, and timestamps to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[1157] Analysis and movement generation by the server

[1158] The server analyzes the received data using an emotion engine (Affectiva API) and a generative AI (GPT-4 model) to determine the user's actions and emotional state. For example, if a delivery is delayed, the emotion engine detects the user's dissatisfaction, and the generative AI generates actions of the simulated creature to comfort the user.

[1159] Sending and viewing interaction data

[1160] The server sends the generated animation data to the device, which receives the data and displays it to the user in real time, allowing the user to visually confirm the movements of the simulated creature and alleviate their emotions.

[1161] Specific examples

[1162] If delivery is delayed

[1163] 1. Sensing user actions and emotions

[1164] The user opens the delivery app to check the delivery status.

[1165] The camera captures the user's facial expressions and the emotion engine collects the displeased emotion data.

[1166] 2. Transmission of operational and emotional data

[1167] The terminal transmits this data to the server.

[1168] 3. Analysis and movement generation by the server

[1169] The server analyzes the delay notification and the displeased emotion data, and the generative AI (GPT-4) generates the behavior of a charming pseudo-creature that says, "Delicious food will arrive soon, so please be patient a little longer!"

[1170] 4. Sending and Displaying Interaction Data

[1171] The server transmits the generated data to the terminal and displays it to the user in real time.

[1172] Example prompts for generative AI models

[1173] User emotion: Sad

[1174] Delivery status: Delayed

[1175] Pet action: Generate an animation where the pet apologizes and says something funny to brighten the user's mood.

[1176] Using this prompt, the generative AI model generates an appropriate response and implements an action that corresponds to the user's emotions.

[1177] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1178] Step 1: Sensing user actions and emotions

[1179] A user places an order on a food delivery app. The device collects operation data through the touchscreen. It also uses a camera and microphone to capture the user's facial expressions and voice, obtaining emotion data. This data includes touch point coordinates, timestamps, and the analysis results (user's emotional state) by the emotion engine. The input is the operation data and emotion data, and the output is a data package.

[1180] Step 2: Sending Operation and Emotion Data

[1181] The terminal transmits the collected operation data and emotion data to the server in real time. Using the communication module, the operation data includes the coordinates of the touch points and a timestamp, and the emotion data includes the analysis results (for example, whether the user is happy or sad). The input is the operation data and emotion data, and the output is the state in which they are transmitted to the server.

[1182] Step 3: Server analysis and motion generation

[1183] The server analyzes the received operation data and emotional data. First, it examines the user's emotional state using an emotion engine (e.g., Affectiva API) and passes the results to a generation AI (e.g., GPT-4). The generation AI generates appropriate movements and facial expressions for the simulated creature based on the given prompts. For example, if a delivery is delayed or the user is in a bad mood, the simulated creature will generate movements to comfort the user. The input is operation data and emotional data, and the output is the movements (animation data) of the generated simulated creature.

[1184] Step 4: Sending interaction data

[1185] The server sends the generated motion data of the pseudo-creature to the terminal. When sent to the terminal, the animation data and an accompanying timestamp are included in the data package. The input is the generated animation data, and the output is the state of the transmitted data as it arrives at the terminal.

[1186] Step 5: Displaying the behavior of the mimic creature

[1187] The device interprets the received animation data and displays it to the user in real time. The animation engine renders the movements of the simulated creature and plays them on the screen, allowing the user to visually confirm how the simulated creature is behaving in accordance with their own emotions. The input is the animation data sent from the server, and the output is the movements played on the screen.

[1188] 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.

[1189] 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.

[1190] 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.

[1191] [Fourth embodiment]

[1192] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1193] 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.

[1194] 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).

[1195] 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.

[1196] 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.

[1197] 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).

[1198] 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. 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.

[1199] 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.

[1200] 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.

[1201] 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.

[1202] 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.

[1203] 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.

[1204] 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."

[1205] As one embodiment of the present invention, a virtual pet interaction system using a smartphone will be described in detail below.

[1206] System configuration

[1207] The system consists of a "terminal" that detects user operations, a "server" that analyzes the operation data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to detect user operations and a communication module that transmits event data to the server. The server uses generative AI to analyze the user's operation data and generate virtual pet animations in real time.

[1208] Program processing (natural language explanation)

[1209] User operation detection

[1210] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. Each action is also time-stamped, and the time information of the action is also collected.

[1211] Sending operation data

[1212] The device sends the collected coordinate data and timestamp to the server as event data. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[1213] Analysis and movement generation by the server

[1214] The server analyzes the received event data. At this time, a generation AI is used to determine what kind of operation the user performed. For example, if the operation was stroking, it is determined that the appropriate action would be for the pet to wag its tail in delight. Based on this determination, the generation AI generates the movements and expressions of the virtual pet and compiles them as animation data.

[1215] Sending interaction data

[1216] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[1217] Specific examples

[1218] When the user pets the pet, the following steps are performed.

[1219] 1. User operation detection

[1220] The user strokes the image of the pet with their finger.

[1221] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[1222] 2. Sending operation data

[1223] The terminal transmits this data to the server.

[1224] 3. Analysis and movement generation by the server

[1225] The server analyzes the received data and recognizes that the user has performed a stroking action.

[1226] The generating AI responds to user input by generating a happy expression and tail-wagging behavior for the pet.

[1227] 4. Sending Interaction Data

[1228] The server transmits the generated animation data to the terminal.

[1229] 5. Real-time updates

[1230] The device displays the received animation data and plays back the pet's tail-wagging action in real time.

[1231] Users can visually see their pet's joy on the screen.

[1232] This system allows users to have an experience that feels like interacting with a real pet, helping to alleviate feelings of loneliness and reduce stress. It also serves as a new means of solving traditional problems with pet ownership, such as allergies, odors, and the burden of caring for a pet.

[1233] The processing flow will be explained below.

[1234] Step 1:

[1235] The user touches or swipes the smartphone screen.

[1236] The user strokes the image of the pet with his / her finger.

[1237] Step 2:

[1238] The terminal senses the user's operation and records the coordinate data and a timestamp.

[1239] The device collects touch point start and end points and swipe trajectory data.

[1240] The time information when the operation was performed is obtained as a timestamp.

[1241] Step 3:

[1242] The terminal transmits the collected event data to the server.

[1243] The terminal assembles the coordinate data and timestamp into a data packet and transmits it to the server in real time.

[1244] Step 4:

[1245] The server analyzes the received event data.

[1246] The server analyzes the data and recognizes the type of user operation (for example, stroking).

[1247] Based on the analysis results, it is decided what reaction the pet will have.

[1248] Step 5:

[1249] The server uses generative AI to generate animal movements and expressions in response to user input.

[1250] Based on the analysis results, the generation AI generates animation data for the virtual pet's happy expression and tail wagging.

[1251] The server assembles the generated animal movements into data packets.

[1252] Step 6:

[1253] The server transmits the generated interaction data to the terminal.

[1254] The server collects animation data into packets and sends them to the terminal.

[1255] Step 7:

[1256] The terminal displays the received animation data in real time.

[1257] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[1258] Users can instantly watch their pet wag its tail and show signs of happiness on the screen.

[1259] Example 1

[1260] 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."

[1261] Conventional virtual pet systems suffer from delayed responses to user operations and a lack of real-time capabilities. Furthermore, the animals' reactions to various user operation patterns are limited, resulting in a lack of interactive experience. Furthermore, conventional systems have difficulty analyzing complex operations and generating movements, making it difficult to improve the user experience.

[1262] 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.

[1263] In this invention, the server includes a means for analyzing event data input by the user, a means for generating appropriate animal movements using a generation AI, and a means for transmitting the generated animal movements to the terminal, thereby providing a virtual pet system that responds to user operations in real time.

[1264] "Event data" is data that includes operation information input by the user.

[1265] The "server" is a computing device that analyzes the received event data and performs the processing to generate appropriate animal movements.

[1266] "Generative AI" is an artificial intelligence model that learns user operation data and generates appropriate animal movements and facial expressions based on the input.

[1267] "Coordinate data" is data that indicates a specific position on the screen that the user touched.

[1268] A "timestamp" is data that records the specific time at which a user operation was performed.

[1269] "Real-time update" means that data is received and displayed almost simultaneously, providing feedback to the user without delay.

[1270] The "screen" is a display device that allows the user to input operations and visually confirm the movements and expressions of the animals.

[1271] The present invention relates to a system that allows users to enjoy the real-time reactions of a virtual pet by operating a touch screen. The system includes a terminal that detects user operations, a server that analyzes the operation data and generates appropriate movements, and a terminal that displays the generated movements.

[1272] Hardware and Software Configuration

[1273] The main components of the system are:

[1274] Device:

[1275] Touchscreen: Sensitive to user touches and swipes.

[1276] Communication module: Provides a communication means for transmitting detected operation data to the server.

[1277] server:

[1278] Generative AI (e.g., OpenAI's GPT-4): Analyzes user operation data and generates the movements and expressions of a virtual pet based on that data.

[1279] Analysis device: Analyzes the event data sent from the device.

[1280] Data processing and calculation

[1281] User operation detection

[1282] When a user strokes or taps a virtual pet on the smartphone touchscreen, the device collects coordinate data of the operation position and swipe trajectory data, and assigns a timestamp to the data.

[1283] Sending operation data

[1284] The terminal assembles the collected coordinate data and timestamp into a packet as event data and sends it to the server via the communication module.

[1285] Analysis and movement generation by the server

[1286] The server uses a generative AI to analyze the received event data. Based on the analysis results, it determines whether the user's action is a stroking or tapping, and generates appropriate movements and expressions for the virtual pet. For example, if the user stroking the pet, the server generates a motion that makes the pet wag its tail in joy.

[1287] Sending interaction data

[1288] The generated animation data is sent from the server to the device, where it is displayed on the device's touch screen in real time.

[1289] Specific examples

[1290] The sequence of actions a user can take to pet a virtual pet is shown below.

[1291] 1. The user strokes the pet image for 2 seconds.

[1292] 2. The device records the coordinate data of the touch point (x1, y1) to (x2, y2) and the timestamp (t1, t2).

[1293] 3. The device collects this data into packets and sends them to the server.

[1294] 4. The server uses generative AI to analyze the data and generate an animation of your pet happily wagging its tail.

[1295] 5. The server assembles the generated animation data into packets and sends them to the device.

[1296] 6. The device analyzes the received animation data and displays the pet's tail-wagging motion in real time.

[1297] 7. Users can visually see their pets enjoying themselves.

[1298] Prompt Sentence Examples

[1299] Below is an example of a prompt sentence to the generative AI model to test the specific behavior of the system.

[1300] prompt:

[1301] The user stroked the virtual pet on the smartphone screen for two seconds. The device detected this action and recorded the coordinate data (x1, y1) to (x2, y2) and the timestamp (t1, t2). The data was sent to the server, which used a generative AI to generate an animation of the pet happily wagging its tail. The animation data was sent to the device in real time, allowing the user to observe the pet's happy behavior in real time on their smartphone.

[1302] This system allows users to enjoy real-time interactions with virtual pets, allowing them to experience the human touch while avoiding the problems of keeping a real pet.

[1303] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1304] Step 1:

[1305] User operation detection

[1306] Input: The user operates the smartphone's touchscreen.

[1307] Specific action: The user strokes the image of the virtual pet for 2 seconds.

[1308] Data processing: The device's touchscreen records the coordinate data of the operation position (x1, y1) to (x2, y2), the swipe trajectory data, and the timestamp (t1, t2).

[1309] Output: Touch point coordinate data, swipe trajectory data, timestamp.

[1310] Step 2:

[1311] Sending operation data

[1312] Input: Recorded coordinate data, swipe trajectory data, timestamp.

[1313] Specific operation: The terminal collects data and organizes it into packets.

[1314] Data processing: Packaging data into packets for transmission.

[1315] Output: Data packet to send to the server.

[1316] Step 3:

[1317] Analysis and movement generation by the server

[1318] Input: Data packets sent from the terminal.

[1319] Specific operation: The server receives the data packet and uses the generated AI to analyze the operational data.

[1320] Data processing: Through analysis, the system determines that the user's action is a stroking motion and generates the animal's movements accordingly.

[1321] Output: Animation data of a happy virtual pet wagging its tail.

[1322] Step 4:

[1323] Sending interaction data

[1324] Input: The generated animation data.

[1325] Specific operation: The server packs the animation data into packets.

[1326] Data processing: Packaging animation data into packets for transmission.

[1327] Output: Animation data packets for sending to the device.

[1328] Step 5:

[1329] Real-time updates

[1330] Input: Animation data packet sent by the server.

[1331] Specific operation: The device receives the animation data and displays it on the touch screen.

[1332] Data processing: Analyze animation data and reproduce the movements of your virtual pet.

[1333] Output: The user can observe the happy tail wagging of the virtual pet in real time on the device screen.

[1334] (Application example 1)

[1335] 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."

[1336] In today's food delivery services, users have limited ways to enjoy the waiting time for their order. Furthermore, systems that provide conversational and emotional interactions to increase engagement and reduce stress are lacking. Furthermore, there is a demand for services that can respond in real time to specific user actions.

[1337] 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.

[1338] In this invention, the server includes means for detecting event data input by a user, means for transmitting the event data to the server, means for analyzing the event data and generating appropriate movements of a virtual character in the server, means for transmitting the generated movements of the virtual character to the terminal, means for displaying the received movements of the virtual character in real time on a display of the terminal, and means for the virtual character to generate a reaction related to a meal order in response to a specific operation by the user, thereby allowing the user to enjoy the time while waiting for their order, increasing engagement and reducing stress.

[1339] "User-input event data" refers to information about touches, swipes, clicks, and other actions performed by a user on a device, including touch point coordinate data and timestamps.

[1340] "Means for transmitting to the server" refers to a communication module or protocol that allows the terminal to transmit user operation data to the server in real time.

[1341] "Virtual character" refers to a digital character that runs on a computer and can interact with users.

[1342] "Virtual character movements" refers to various animations and reactions displayed by a virtual character, including expressions and movements such as happiness, sadness, and surprise.

[1343] "Means for transmitting to the terminal" refers to a communication module or protocol for transmitting animation data generated by the server to the terminal.

[1344] "Means for displaying in real time on a display" refers to a combination of software and hardware for instantly displaying the movements of a virtual character on the screen of a terminal.

[1345] "Specific user operations" refer to specific actions or inputs made by the user, such as ordering food or information about special dates.

[1346] The "means for generating a reaction related to a meal order" refers to a means for analyzing the user's meal order data and generating corresponding movements and facial expressions of the virtual character.

[1347] This invention is an interactive system that generates the movements of a virtual character based on event data entered by a user and displays reactions related to food orders. This section describes the program used to realize this system and the processing of that program.

[1348] Explanation of program processing

[1349] The system operates using a user terminal, a server, and a generative AI model.

[1350] Hardware and Software

[1351] User terminal: A device such as a smartphone or tablet, which includes a touchscreen, a communication module, and a display device.

[1352] Server: Cloud-based computing resources that run data analytics and generative AI models.

[1353] Generative AI model: For example, generative AI such as GPT-4 or DALL-E is used to analyze user operation data and generate the movements and facial expressions of a virtual character.

[1354] Data processing and calculation

[1355] 1. User event detection

[1356] When a user touches, swipes, or clicks on the smartphone screen, the action is detected by the user device, for example, when the user orders food from a food delivery app.

[1357] The user terminal records the coordinate data of the touch point, a timestamp, and the operation content (order data, etc.).

[1358] 2. Sending operation data

[1359] The user terminal transmits the collected event data (coordinate data, timestamp, and order data) to the server in real time.

[1360] 3. Analysis and movement generation by the server

[1361] The server analyzes the received event data and uses a generative AI model to generate appropriate movements and facial expressions for the virtual character.

[1362] For example, if a user orders a pizza, the generative AI generates a happy expression and tail wagging motion for the virtual character.

[1363] 4. Sending Interaction Data

[1364] The generated animation data is transmitted from the server to the user terminal.

[1365] 5. Real-time display

[1366] The user terminal immediately displays the received animation data, and the virtual character moves in real time.

[1367] This allows users to see the reactions of the virtual characters within the food delivery app, allowing them to enjoy the time they have while waiting for their order.

[1368] Adding specific examples

[1369] Example 1: When a user orders a pizza on a touchscreen, the user device collects coordinate data and order data and sends them to the server. The server then inputs a prompt to the generative AI model: "The user has ordered a pizza. Please generate a reaction that will make the pet happy.", and generates an animation of the virtual character.

[1370] Prompt Sentence Examples

[1371] "A user orders a pizza. Generate a reaction that will make their pet happy."

[1372] In this way, the present invention realizes a system that can provide interactive reactions to operations performed by users within a food delivery app, thereby increasing engagement.

[1373] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1374] Step 1:

[1375] A user operates the touchscreen of a smartphone to order food using a food delivery app. This operation includes selecting a specific food menu item and confirming the order. Touchpoint coordinate data, a timestamp, and the order details (e.g., pizza) are collected as input. These event data are generated as output.

[1376] Step 2:

[1377] The terminal sends the collected event data (coordinate data, timestamp, and order details) to the server in real time. The input is the event data generated in step 1, and the output is the data sent to the server. The communication module is used to send the data quickly and accurately.

[1378] Step 3:

[1379] The server analyzes the received event data to understand the user's operation. This analysis includes extracting the meal order details from the event data. The input is the event data sent from the device, and the output is the order details data as the analysis result.

[1380] Step 4:

[1381] The server uses the generative AI model to generate the movements and expressions of the virtual character according to the user's order. Specifically, the prompt statement "The user has ordered a pizza. Please generate a reaction that will please the pet." is input into the generative AI model, and animation data is generated based on that. The order data and prompt statement from the analysis results are used as input, and the generated animation data is obtained as output.

[1382] Step 5:

[1383] The generated animation data is sent from the server to the user's device. The input is the animation data output from the generative AI model, and the output is the data sent to the device. The animation data is sent in real time using a communication module.

[1384] Step 6:

[1385] The user device displays the received animation data on a display in real time. Specifically, the virtual character displays movements such as a happy expression or a wagging tail. The input is the animation data sent from the server, and the output is the animation visually displayed to the user.

[1386] This series of processes allows users to enjoy an interactive experience with virtual characters through the food delivery app, making the waiting time for their order more enjoyable.

[1387] 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.

[1388] As one embodiment of the present invention, a system that combines a virtual pet interaction system using a smartphone with an emotion engine that analyzes the user's emotions will be described in detail.

[1389] System configuration

[1390] The system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate movements, and another "terminal" that displays the generated movements. The terminal includes a touch screen to sense the user's operations and an emotion engine that analyzes emotions, as well as a communication module that collects this data and transmits it to the server. The server uses generative AI to analyze the user's operation data and emotion data and generates virtual pet animations in real time.

[1391] Program processing (natural language explanation)

[1392] Sensing user actions and emotions

[1393] When a user touches or swipes the smartphone screen, the device detects the action. For example, if a user strokes an image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[1394] Sending operational and emotional data

[1395] The device sends the collected coordinate data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[1396] Analysis and movement generation by the server

[1397] The server analyzes the received event data and emotion data. At this time, a generation AI is used to determine the type of user operation and the user's emotional state at the time. For example, if the user is stroking the pet and has a happy expression, it is determined that the pet should be more active and happy, wagging its tail. Based on this judgment, the generation AI generates the virtual pet's movements and expressions and compiles them as animation data.

[1398] Sending interaction data

[1399] The generated animation data is sent from the server to the device, where it is received by the application on the device and displayed in real time, allowing the user to instantly see their pet's reactions visually.

[1400] Specific examples

[1401] When the user pets the pet, the following steps are performed.

[1402] 1. Sensing user actions and emotions

[1403] The user strokes the image of the pet with their finger.

[1404] The device records the coordinate data of the touch point and the trajectory data of the swipe and adds a timestamp.

[1405] The emotion engine analyzes the user's facial expressions and voice to collect data on happy emotions.

[1406] 2. Transmission of operational and emotional data

[1407] The terminal transmits this data to the server.

[1408] 3. Analysis and movement generation by the server

[1409] The server analyzes the received data and recognizes that the user is enjoying the stroking action.

[1410] The generative AI responds to the user's operations and emotions to generate more lively, happy expressions and tail-wagging movements for the pet.

[1411] 4. Sending Interaction Data

[1412] The server transmits the generated animation data to the terminal.

[1413] 5. Real-time updates

[1414] The device displays the received animation data and plays back the pet's active tail-wagging action in real time.

[1415] Users can visually see their pet's joy on the screen, and their own emotions will be elevated along with it.

[1416] This system allows users to have an experience that feels like interacting with a real pet, which helps to alleviate feelings of loneliness and relieve stress, and provides responses based on the user's emotions, allowing for a more intimate experience.It serves as a new means of solving traditional problems of pet ownership, such as allergies, odors, and the burden of caring for them.

[1417] The processing flow will be explained below.

[1418] Step 1:

[1419] The user touches or swipes the smartphone screen.

[1420] The user strokes the image of the pet with his / her finger.

[1421] Step 2:

[1422] The terminal senses the user's operation and records the coordinate data and a timestamp.

[1423] The device collects touch point start and end points and swipe trajectory data.

[1424] The time information when the operation was performed is obtained as a timestamp.

[1425] Step 3:

[1426] An emotion engine within the device analyzes the user's emotional state.

[1427] The device analyzes the user's facial expressions and voice and collects emotional data in real time.

[1428] Step 4:

[1429] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[1430] The terminal assembles this data into data packets and transmits them to the server in real time.

[1431] Step 5:

[1432] The server analyzes the received event data and emotion data.

[1433] The server analyzes the coordinate data and timestamp and identifies the type of user operation (for example, stroking).

[1434] The server analyzes the emotion data sent from the emotion engine and determines the user's emotional state.

[1435] Step 6:

[1436] The server uses generative AI to generate animal movements and expressions based on the user's actions and emotions.

[1437] The generative AI determines the virtual pet's behavior (e.g., wagging its tail happily, jumping, etc.) based on the user's actions and emotional state.

[1438] The server packages the generated animation data into data packets.

[1439] Step 7:

[1440] The server transmits the generated interaction data to the terminal.

[1441] The server collects animation data into packets and sends them to the terminal.

[1442] Step 8:

[1443] The terminal displays the received animation data in real time.

[1444] The device analyzes the animation data and reflects it on the virtual pet on the screen.

[1445] Users can instantly see their pet wagging its tail and bouncing on the screen.

[1446] Specific examples

[1447] The process flow when the user is enjoying petting a pet is as follows.

[1448] 1. Step 1:

[1449] The user strokes the image of the pet with their finger.

[1450] 2. Step 2:

[1451] The device detects touch events on the screen and records the coordinate data of the touch point and the trajectory data of the swipe.

[1452] Record the timestamp of the operation.

[1453] 3. Step 3:

[1454] The device's emotion engine analyzes the user's facial expressions and voice to determine their feelings of enjoyment.

[1455] 4. Step 4:

[1456] The terminal transmits the collected coordinate data, timestamp, and emotion data to the server.

[1457] 5. Step 5:

[1458] The server analyzes the coordinate data and timestamp and recognizes that a stroking action has been performed.

[1459] The server analyzes the received emotional data and determines that the user is enjoying themselves.

[1460] 6. Step 6:

[1461] The generating AI responds to the user's operations and emotions to generate a lively and happy tail-wagging behavior for the pet.

[1462] The server packages the generated animation data into packets.

[1463] 7. Step 7:

[1464] The server transmits this data to the terminal.

[1465] 8. Step 8:

[1466] The device displays the received animation data in real time, recreating the action of your pet happily wagging its tail.

[1467] Users can visually see their pets' happy expressions and enjoy the experience even more.

[1468] This system allows users to have an experience similar to interacting with a real pet, which helps to alleviate feelings of loneliness and stress. Furthermore, by providing responses according to the user's emotional state, it allows for a more intimate and fulfilling interaction.

[1469] Example 2

[1470] 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."

[1471] Conventional virtual pet systems have limited response to user input and are unable to fully reflect the user's emotions. Real-time responses are also insufficient, making it difficult to improve the user experience. Furthermore, there is a lack of means to analyze the user's emotions, making it difficult to provide a more intimate experience.

[1472] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing event data and emotion data input by the user and generating appropriate virtual pet movements using a generation AI, means for determining the virtual pet's movements and facial expressions based on the received data, and means for transmitting the generated virtual pet movements to the terminal. This enables the virtual pet to move in a way that reflects the user's operations and emotions in real time.

[1473] "User" refers to the person who operates the system and interacts with the virtual pet.

[1474] "Event data" refers to input information such as touch points and swipe trajectories generated when a user operates a device such as a smartphone.

[1475] "Emotion data" refers to data analyzed by the emotion engine based on the user's facial expressions, voice, etc.

[1476] "Server" refers to a computer system that analyzes collected event data and emotion data and generates appropriate virtual pet movements.

[1477] "Generative AI" refers to artificial intelligence technology that analyzes user operations and emotional data to generate the movements and facial expressions of a virtual pet.

[1478] "Virtual pet" refers to a digital pet character that operates on a display device such as a smartphone.

[1479] A "timestamp" refers to data that records the time when a user performs an operation.

[1480] "Real-time" refers to processing that responds immediately to user operations and emotions.

[1481] "Coordinate data" refers to data that records the position information of operations performed by a user on a touch screen.

[1482] "Display Device" means a device, such as a smartphone or tablet, that visually displays the movements and reactions of a virtual pet.

[1483] This invention is a system that senses user operations and emotions, and generates and displays the movements of a virtual pet in real time based on those operations. This system consists of a "terminal" that senses user operations, a "server" that analyzes the operation and emotion data and generates appropriate movements, and a "terminal" that displays the generated movements.

[1484] Hardware and software used

[1485] Terminal

[1486] A device is a mobile device such as a smartphone or tablet, and includes the following elements:

[1487] Touchscreen sensor: Detects user touch and swipe actions.

[1488] Camera and microphone: Captures the user's facial expressions and voice, providing data for analysis by the emotion engine.

[1489] Emotion engine: A software module that analyzes emotions from the user's facial expressions and voice.

[1490] Communication module: Sends collected operation and emotion data to the server.

[1491] server

[1492] A server is a powerful computer system that includes the following components:

[1493] Data analysis module: Analyzes the operation data and emotion data sent from the terminal.

[1494] Generative AI: Artificial intelligence that generates appropriate movements and facial expressions for a virtual pet based on analysis results.

[1495] Communication module: Sends the generated animation data to the terminal.

[1496] Specific actions

[1497] Here's a concrete example of how this system works:

[1498] Sensing user actions and emotions

[1499] When a user touches or swipes the smartphone screen, the device detects the action. For example, if the user strokes the image of a pet on the screen, the coordinate data of the touch point and the swipe trajectory data are recorded. At the same time, the device's built-in emotion engine analyzes the user's emotions from their facial expressions and voice and collects current emotion data.

[1500] Sending operational and emotional data

[1501] The device sends the collected touch point coordinate data, swipe trajectory data, timestamp, and emotion data to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[1502] Analysis and movement generation by the server

[1503] The server analyzes the received operation data and emotional data. Using a generation AI, it determines what the user's operation was and what their emotional state was at the time. For example, when a petting operation and a happy facial expression are detected, the generation AI determines that the pet's behavior is appropriate for making the pet happy. Based on this judgment, the server generates the virtual pet's movements and facial expressions and compiles them as animation data.

[1504] Sending interaction data and updating it in real time

[1505] The server sends the generated animation data to the device, which then receives the animation data and displays it in real time. For example, immediately after a user strokes a pet, the pet's tail wagging motion on the screen is reproduced in real time.

[1506] Prompt Sentence Examples

[1507] The user pets the pet using a smartphone. The emotion engine analyzes the user's happy facial expression and generates how the virtual pet will react based on that data.

[1508] Using this prompt, the generative AI model can generate specific actions.

[1509] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1510] Step 1: Sensing user actions and emotions

[1511] When a user touches or swipes the smartphone screen, the device's touchscreen sensor detects and records the coordinate data of the touch point and the swipe trajectory data as input. At the same time, the device's camera and microphone capture the user's facial expressions and voice and provide this data as input to the emotion engine. The emotion engine analyzes this data and generates the user's emotional state as output. Specifically, if a user strokes the image of a pet and says "cute" with a smile, the emotion engine will collect happy emotion data.

[1512] Step 2: Sending Operation and Emotion Data

[1513] The device collects the touch point coordinate data, swipe trajectory data, timestamps, and emotion data collected in step 1 as input and sends them to the server. Using the communication module, this data is sent to the server in real time. For example, the coordinate data of the moment you stroke your pet and the voice analysis results, such as "cute," are sent to the server.

[1514] Step 3: Server analysis and motion generation

[1515] The server receives the operation data and emotion data sent in step 2 and analyzes them as input in the data analysis module. Based on the analysis results, the generation AI determines the user's operation and emotional state, and generates appropriate movements and facial expressions for the virtual pet as output. For example, if a stroking operation and a happy emotion are detected, the generation AI determines that the pet will happily wag its tail and generates this as animation data.

[1516] Step 4: Sending interaction data

[1517] The server organizes the animation data generated in step 3 as input and sends it to the terminal. Using a communication module, the generated animation data is sent to the terminal in real time. For example, animation data of a pet wagging its tail is sent to the terminal.

[1518] Step 5: Real-time updates

[1519] The terminal receives the animation data sent in step 4 and processes it as input. The terminal plays the received animation data in real time on a display device, providing the user with visual feedback as output. For example, immediately after the user pets the pet, the pet's tail wagging action is displayed on the screen in real time. As a result, the user can see the pet's reaction immediately.

[1520] (Application example 2)

[1521] 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."

[1522] Conventional food delivery services have faced problems such as stress and dissatisfaction from users due to delivery delays and order cancellations. Furthermore, there is a lack of systems that can respond to users' emotions, creating a need for an improved user experience. This invention aims to solve these problems by analyzing users' emotions and providing a delivery experience that is customized accordingly.

[1523] 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 including an emotion engine that collects and analyzes user emotion data, means for generating the movements and facial expressions of the pseudo-creature based on the emotion data, and means for providing customized information based on the user's emotions and operations. This makes it possible to reduce user stress caused by delivery delays, order cancellations, etc., and improve the user experience.

[1524] "Event data input by a user" is operation information generated when a user operates a terminal, and is data indicating input actions such as touching, swiping, and clicking.

[1525] "Emotion data" is data that indicates the emotional state of the user analyzed from the user's voice, facial expression, gestures, etc., and is information that reflects the user's psychological state.

[1526] An "emotion engine" is software for analyzing a user's emotions, and is a program with the function of generating emotion data through facial expression recognition, voice analysis, etc.

[1527] "Generative AI" is an artificial intelligence technology that analyzes user operation data and emotional data and generates appropriate responses and actions based on that data.

[1528] A "pseudo-creature" is a virtual creature designed to interact with users like a virtual pet, and is a character that displays movements and expressions on a display.

[1529] "The behavior of the generated pseudo-creature" refers to the actions and reactions of the pseudo-creature determined by the generating AI based on the user's operations and emotions.

[1530] This invention is a system for food delivery services that analyzes user emotions and provides a customized delivery experience. This system consists of a "terminal" that senses the user's operations and emotions, a "server" that analyzes the operation and emotion data and generates appropriate actions, and a "terminal" that displays the generated actions.

[1531] System configuration

[1532] 1. Terminal

[1533] Touchscreen: Used to sense user interaction.

[1534] Camera: Captures the user's facial expressions and collects emotional data.

[1535] Microphone: Captures the user's voice and analyzes emotional data.

[1536] Communication module: Sends collected operation data and emotion data to the server in real time.

[1537] 2. Server

[1538] Emotion engine (e.g., Affectiva API): Software that analyzes emotions from a user's facial expressions and voice.

[1539] Generative AI (e.g., GPT-4): Artificial intelligence that analyzes user actions and emotional data to generate appropriate behaviors and responses.

[1540] 3. Applications on the device

[1541] The behavior of the generated pseudo-creature is displayed in real time.

[1542] Program processing (natural language explanation)

[1543] Sensing user actions and emotions

[1544] When a user touches or swipes the smartphone screen, the corresponding device detects the action. For example, when a user places an order on a food delivery app, the operation data is recorded. Meanwhile, the user's face is captured by the camera and analyzed by the emotion engine. The user's voice is also collected by the microphone and analyzed as emotion data.

[1545] Sending operational and emotional data

[1546] The device sends the collected operation data, emotion data, and timestamps to the server. This communication is performed in real time, and the data is delivered to the server the moment the user performs an operation.

[1547] Analysis and movement generation by the server

[1548] The server analyzes the received data using an emotion engine (Affectiva API) and a generative AI (GPT-4 model) to determine the user's actions and emotional state. For example, if a delivery is delayed, the emotion engine detects the user's dissatisfaction, and the generative AI generates actions of the simulated creature to comfort the user.

[1549] Sending and viewing interaction data

[1550] The server sends the generated animation data to the device, which receives the data and displays it to the user in real time, allowing the user to visually confirm the movements of the simulated creature and alleviate their emotions.

[1551] Specific examples

[1552] If delivery is delayed

[1553] 1. Sensing user actions and emotions

[1554] The user opens the delivery app to check the delivery status.

[1555] The camera captures the user's facial expressions and the emotion engine collects the displeased emotion data.

[1556] 2. Transmission of operational and emotional data

[1557] The terminal transmits this data to the server.

[1558] 3. Analysis and movement generation by the server

[1559] The server analyzes the delay notification and the displeased emotion data, and the generative AI (GPT-4) generates the behavior of a charming pseudo-creature that says, "Delicious food will arrive soon, so please be patient a little longer!"

[1560] 4. Sending and Displaying Interaction Data

[1561] The server transmits the generated data to the terminal and displays it to the user in real time.

[1562] Example prompts for generative AI models

[1563] User emotion: Sad

[1564] Delivery status: Delayed

[1565] Pet action: Generate an animation where the pet apologizes and says something funny to brighten the user's mood.

[1566] Using this prompt, the generative AI model generates an appropriate response and implements an action that corresponds to the user's emotions.

[1567] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1568] Step 1: Sensing user actions and emotions

[1569] A user places an order on a food delivery app. The device collects operation data through the touchscreen. It also uses a camera and microphone to capture the user's facial expressions and voice, obtaining emotion data. This data includes touch point coordinates, timestamps, and the analysis results (user's emotional state) by the emotion engine. The input is the operation data and emotion data, and the output is a data package.

[1570] Step 2: Sending Operation and Emotion Data

[1571] The terminal transmits the collected operation data and emotion data to the server in real time. Using the communication module, the operation data includes the coordinates of the touch points and a timestamp, and the emotion data includes the analysis results (for example, whether the user is happy or sad). The input is the operation data and emotion data, and the output is the state in which they are transmitted to the server.

[1572] Step 3: Server analysis and motion generation

[1573] The server analyzes the received operation data and emotional data. First, it examines the user's emotional state using an emotion engine (e.g., Affectiva API) and passes the results to a generation AI (e.g., GPT-4). The generation AI generates appropriate movements and facial expressions for the simulated creature based on the given prompts. For example, if a delivery is delayed or the user is in a bad mood, the simulated creature will generate movements to comfort the user. The input is operation data and emotional data, and the output is the movements (animation data) of the generated simulated creature.

[1574] Step 4: Sending interaction data

[1575] The server sends the generated motion data of the pseudo-creature to the terminal. When sent to the terminal, the animation data and an accompanying timestamp are included in the data package. The input is the generated animation data, and the output is the state of the transmitted data as it arrives at the terminal.

[1576] Step 5: Displaying the behavior of the mimic creature

[1577] The device interprets the received animation data and displays it to the user in real time. The animation engine renders the movements of the simulated creature and plays them on the screen, allowing the user to visually confirm how the simulated creature is behaving in accordance with their own emotions. The input is the animation data sent from the server, and the output is the movements played on the screen.

[1578] 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.

[1579] 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.

[1580] 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.

[1581] 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.

[1582] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1583] 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.

[1584] 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).

[1585] 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.

[1586] 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."

[1587] 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.

[1588] 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).

[1589] 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.

[1590] 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.

[1591] 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.

[1592] 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.

[1593] 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.

[1594] 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.

[1595] 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.

[1596] 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.

[1597] 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.

[1598] 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.

[1599] The following is further disclosed regarding the above embodiment.

[1600] (Claim 1)

[1601] means for sensing user-entered event data;

[1602] means for transmitting the event data to a server;

[1603] means for analyzing the event data at a server and generating appropriate animal movements;

[1604] means for transmitting the generated animal movement to a terminal;

[1605] means for displaying the received animal movements on a screen of a terminal in real time;

[1606] A system including:

[1607] (Claim 2)

[1608] A means for using the generative AI to analyze the operational data entered by the user;

[1609] a means for updating the generated animal movements in real time;

[1610] 10. The system of claim 1, comprising:

[1611] (Claim 3)

[1612] means for analyzing the coordinate data and the time stamp to identify the type of operation performed by the user;

[1613] a means for determining the movement and facial expression of the animal based on the analysis results;

[1614] 10. The system of claim 1, comprising:

[1615] "Example 1"

[1616] (Claim 1)

[1617] means for sensing user-entered event data;

[1618] means for transmitting the event data to a server;

[1619] means for analyzing the event data at a server and generating appropriate animal movements;

[1620] means for transmitting the generated animal movement to a terminal;

[1621] means for displaying the received animal movements on a display of a terminal in real time;

[1622] A system including:

[1623] (Claim 2)

[1624] A means for using the generative AI to analyze the operational data entered by the user;

[1625] a means for updating the generated animal movements in real time;

[1626] 10. The system of claim 1, comprising:

[1627] (Claim 3)

[1628] means for analyzing the coordinate data and the time stamp to identify the type of operation performed by the user;

[1629] a means for determining the movement and facial expression of the animal based on the analysis results;

[1630] 10. The system of claim 1, comprising:

[1631] "Application Example 1"

[1632] (Claim 1)

[1633] means for sensing user-entered event data;

[1634] means for transmitting the event data to a server;

[1635] a means for analyzing the event data in a server and generating appropriate movements of the virtual character;

[1636] means for transmitting the movement of the generated virtual character to a terminal;

[1637] means for displaying the received movement of the virtual character on a display of the terminal in real time;

[1638] means for generating a reaction related to a meal order by the virtual character in response to a specific operation by the user;

[1639] A system including:

[1640] (Claim 2)

[1641] A means for using the generative AI to analyze the operational data entered by the user;

[1642] a means for updating the movement of the generated virtual character in real time;

[1643] A method for analyzing user order data to determine meal contents and special dates, and for virtual characters to react in a specific way;

[1644] 10. The system of claim 1, comprising:

[1645] (Claim 3)

[1646] means for analyzing the coordinate data and the time stamp to identify the type of operation performed by the user;

[1647] means for determining the movements and facial expressions of the virtual character based on the analysis results;

[1648] a means for using a generative AI model to generate reactions of a virtual character based on the user's order data;

[1649] 10. The system of claim 1, comprising:

[1650] "Example 2: Combining Emotion Engines"

[1651] (Claim 1)

[1652] means for sensing user-entered event data;

[1653] means for transmitting the event data and user emotion data to a server;

[1654] A means for analyzing the event data and emotion data in a server and generating appropriate movements of the virtual pet using a generation AI;

[1655] means for transmitting the generated movement of the virtual pet to a terminal;

[1656] means for displaying the received movement of the virtual pet in real time on a display device of the terminal;

[1657] A system including:

[1658] (Claim 2)

[1659] A means for using a generating AI to analyze event data and emotion data, and updating the movement of the generated virtual pet in real time based on the user's operation and emotion;

[1660] 10. The system of claim 1, comprising:

[1661] (Claim 3)

[1662] means for analyzing the coordinate data and the time stamp to identify the type of operation performed by the user;

[1663] means for determining the movements and expressions of the virtual pet based on the analysis results and the user's emotional data;

[1664] 10. The system of claim 1, comprising:

[1665] "Application example 2 when combining emotion engines"

[1666] (Claim 1)

[1667] means for sensing user-entered event data;

[1668] means for transmitting the event data to a server;

[1669] A means for analyzing the event data in a server and generating appropriate movements of the simulated creature;

[1670] means for transmitting the generated movement of the pseudo creature to a terminal;

[1671] means for displaying the received movements of the simulated creature on a screen of a terminal in real time;

[1672] means for collecting user emotion data and analyzing the data, the means including an emotion engine;

[1673] means for generating movements and facial expressions of a pseudo-creature based on emotion data;

[1674] A system including:

[1675] (Claim 2)

[1676] A means for using the generative AI to analyze the operational data entered by the user;

[1677] A means for updating the movement of the generated pseudo creature in real time;

[1678] A means for providing customized information based on the user's emotions and actions;

[1679] 10. The system of claim 1, comprising:

[1680] (Claim 3)

[1681] means for analyzing the coordinate data and the time stamp to identify the type of operation performed by the user;

[1682] means for determining the movements and facial expressions of the simulated creature based on the analysis results and the user's emotional data;

[1683] 10. The system of claim 1, comprising: [Explanation of symbols]

[1684] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for sensing user-entered event data; means for transmitting the event data to a server; means for analyzing the event data at a server and generating appropriate animal movements; means for transmitting the generated animal movement to a terminal; means for displaying the received animal movements on a screen of a terminal in real time; A system including:

2. A means for using the generative AI to analyze the operational data entered by the user; a means for updating the generated animal movements in real time; The system of claim 1 , comprising:

3. means for analyzing the coordinate data and the time stamp to identify the type of operation performed by the user; a means for determining the movement and facial expression of the animal based on the analysis results; The system of claim 1 , comprising:

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