System

Abstract

A system is provided.SOLUTION: A system, comprising: means for generating a response to a question of a user using a generative artificial intelligence model; means for sending the question input by the user to the generative artificial intelligence model; means for displaying the generated response to the user; and means for adding a product that the user wishes to purchase to a cart.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 today's online shopping environment, people with disabilities and general consumers face the problem of spending a lot of time and effort checking product information and operation instructions. It is particularly difficult for people with disabilities to obtain product information and operation instructions in an accessible format. Furthermore, the process of obtaining detailed product information or asking additional questions is cumbersome, making the purchasing decision process inefficient. This creates an inconvenient online shopping experience. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system that generates responses to user questions using a generative artificial intelligence model. Specifically, the system includes a means for sending a question entered by the user to the generative artificial intelligence model and displaying the generated response to the user. The system also includes a means for adding products the user wishes to purchase to a cart. This allows users to efficiently obtain product information, purchase the product, and understand how to use it. Furthermore, the system allows people with disabilities to perform input operations using a brain-controlled interface, improving ease of use.

[0006] A "generative artificial intelligence model" includes machine learning algorithms for generating responses in natural language to user input.

[0007] "User questions" refer to inquiries about product information and operation methods that users input to the system.

[0008] "Response" refers to an answer or information provided by a generative artificial intelligence model based on a user's question.

[0009] "Cart addition means" refers to a function that allows a user to select products they wish to purchase and add them to a virtual shopping cart on the system.

[0010] "Brain-controlled interfaces" refer to technology that uses a user's brain waves or neural signals to provide input to a computer system. [Brief explanation of the drawings]

[0011] [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

[0012] 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.

[0013] First, the terms used in the following description will be explained.

[0014] 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).

[0015] 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.

[0016] 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.

[0017] 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.

[0018] 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."

[0019] [First embodiment]

[0020] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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."

[0032] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for adding products that the user wishes to purchase to a cart.

[0033] System Configuration

[0034] server

[0035] The server is the core component that operates the generative artificial intelligence model. The server has the following functions:

[0036] 1. Request received:

[0037] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[0038] 2. Generative AI processing:

[0039] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[0040] 3. Database integration:

[0041] The server retrieves the necessary product information and user data from the database along with the response from the generative AI model and adds it to the response.

[0042] 4. Response generation:

[0043] The server formats the generated response and sends it back to the user or terminal.

[0044] 5. Cart Management:

[0045] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[0046] Terminal

[0047] The terminal functions as an interface with the user and has the following functions:

[0048] 1. User Interface:

[0049] It provides an interface where users can enter and submit questions, either through text input or voice input.

[0050] 2. Submit your request:

[0051] The entered question is sent to the server.

[0052] 3. Response display:

[0053] The response received from the server is displayed in the user interface.

[0054] 4. Cart function:

[0055] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[0056] User

[0057] The user performs the following operations:

[0058] 1. Enter your question:

[0059] Enter product-related questions into the device using text or voice.

[0060] For example: "Teach me how to use this smartphone."

[0061] 2. Response confirmation:

[0062] Check the response from the server displayed on the terminal.

[0063] 3. Purchase decision:

[0064] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[0065] Specific examples

[0066] Next, an embodiment of the present invention will be described with specific examples.

[0067] 1. Enter your question

[0068] If a user has a question about how to use their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[0069] 2. Submit your question

[0070] The device sends this question to the server, which receives the question and sends it to the generating AI.

[0071] 3. Generative AI Processing

[0072] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[0073] 4. Data Formatting

[0074] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0075] 5. Sending and Displaying Responses

[0076] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[0077] 6. Add to Cart

[0078] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0079] The system configured in this way allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. The system of the present invention makes it easy for people with disabilities to shop online, improving the user experience.

[0080] The processing flow will be explained below.

[0081] Step 1:

[0082] The user enters a question by text or voice into a user interface on the device.

[0083] Step 2:

[0084] The device receives the user's question and sends the question and the user's ID to the server. The data sent is often in text format, JSON.

[0085] Step 3:

[0086] The server receives the question sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[0087] Step 4:

[0088] The server sends the converted question to the generative AI model, which then generates a response based on the user's question.

[0089] Step 5:

[0090] The generation AI generates a response to the question received from the server and returns the response to the server. The generated response is created in detail based on the content of the question.

[0091] Step 6:

[0092] The server formats the response received from the generation AI, and if necessary, retrieves additional information from the database (e.g., product specifications or the user's past purchase history) and incorporates it into the response.

[0093] Step 7:

[0094] The server converts the formatted response into JSON format and sends it to the device, which includes the generated AI's response and additional information.

[0095] Step 8:

[0096] The terminal analyzes the response received from the server and displays it on the user interface. The displayed content is the answer to the question asked by the user.

[0097] Step 9:

[0098] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[0099] Step 10:

[0100] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[0101] Step 11:

[0102] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[0103] Step 12:

[0104] The server sends the cart update status (success or failure) to the device.

[0105] Step 13:

[0106] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[0107] In this way, the program's processing is clearly divided into steps, allowing users to smoothly progress from asking questions to completing the purchase process.

[0108] Example 1

[0109] 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."

[0110] Conventional online shopping systems require users to use multiple different platforms to answer questions about products and complete purchase procedures, which is time-consuming. Furthermore, the process from obtaining information to making a purchase decision is fragmented, making it difficult to improve the user experience. Furthermore, insufficient or inaccurate information can discourage users from making a purchase.

[0111] 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.

[0112] In this invention, the server includes means for receiving a user's question, means for sending the question to a generative AI model, means for generating a response from the generative AI model, means for retrieving product information and user information from a database, means for formatting the generated response, means for displaying the formatted response to the user, and means for adding products the user wishes to purchase to a cart. This allows users to complete the entire process from asking a question to completing the purchase procedure within a single platform, improving the user experience and increasing their willingness to purchase.

[0113] A "user" is an entity that uses this system to input questions, receive responses, and purchase products.

[0114] A "generative AI model" is an artificial intelligence model that receives a question from a user and generates an appropriate response to it.

[0115] The "server" is a central facility that receives user questions, sends them to the generative AI model, generates responses, connects with the database, considers the final response, and sends it to the terminal.

[0116] A "terminal" is a device that provides an interface for a user to enter questions, interact with the server, display generated responses, and add items to a cart.

[0117] A "database" is an information management system that stores information such as product information and user information, and allows the server to refer to and retrieve information as needed.

[0118] The "means for receiving a question" is a function for acquiring a question input by a user and inputting it into the server.

[0119] "Means for sending questions to the generative AI model" is a function that sends the questions received by the server to the generative AI model and obtains the response.

[0120] "Means for generating a response from a generative AI model" refers to the function of the generative AI model to create an appropriate response based on an input question.

[0121] The "means for linking with a database" is a function that enables the server to obtain additional information required for a response from a database and incorporate it into the response.

[0122] "Means for formatting responses" is a function that formats information obtained from the generative AI model and database into a format that is easy for users to view and understand.

[0123] The "means for displaying to the user" is a function for visually presenting the formatted response to the user via the terminal.

[0124] The "means for adding to cart" is a function for adding products that the user wishes to purchase to a virtual shopping cart.

[0125] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative AI model, and displays the response. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[0126] System Configuration

[0127] server

[0128] The server is the core component that operates the generative AI model and has the following functions:

[0129] 1. Request received:

[0130] The server receives a question sent from a user or a device, such as "How do I use this smartphone?"

[0131] 2. Generative AI processing:

[0132] The server sends the received question to a generative AI model (e.g., GPT-3), which generates an appropriate response based on the prompt.

[0133] 3. Database integration:

[0134] Based on the response from the generative AI model, the server retrieves additional product information and user data from the database, such as related accessory information and product page links.

[0135] 4. Response Formatting:

[0136] The server combines the acquired information with the response of the generating AI and formats it in a format that is easy for the user to understand.

[0137] 5. Send Response:

[0138] The server sends a formatted response back to the terminal for display to the user.

[0139] 6. Cart Management:

[0140] The server receives a cart add request from the user and adds the product to the user's cart.

[0141] Terminal

[0142] The terminal functions as an interface with the user. Its specific functions are as follows:

[0143] 1. User Interface:

[0144] It provides an interface for users to enter and submit questions, either by text input or by voice input.

[0145] 2. Submit your request:

[0146] The entered question is sent to the server. For example, a question such as "Teach me how to use this smartphone" is sent.

[0147] 3. Response display:

[0148] Display the response received from the server in the user interface. For example, the response might look like this: "To use your smartphone, power it on, then access the settings menu..."

[0149] 4. Cart function:

[0150] An interface is provided for users to add desired products to their cart. For example, a user can add a product to their cart by pressing an "Add to cart" button.

[0151] User

[0152] The user performs the following operations:

[0153] 1. Enter your question:

[0154] Enter a question about the product into the device using text or voice. For example, enter the question "How do I use this smartphone?"

[0155] 2. Response confirmation:

[0156] Check the response from the server that is displayed on the device, such as "To use your smartphone, turn it on, then access the settings menu..."

[0157] 3. Purchase decision:

[0158] If there is an item you would like to add to your cart, press the "Add to Cart" button. For example, if you decide to purchase a smartphone, press the "Add to Cart" button.

[0159] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision, thereby improving the user experience and increasing their willingness to buy.

[0160] Specific examples

[0161] Specific usage scenarios are shown below.

[0162] 1. Enter your question

[0163] If a user has a question about how to operate their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[0164] 2. Submit your question

[0165] The device sends this question to the server, which receives the question and sends it to the generating AI.

[0166] 3. Generative AI Processing

[0167] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[0168] 4. Data Formatting

[0169] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0170] 5. Sending and Displaying Responses

[0171] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[0172] 6. Add to Cart

[0173] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0174] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0175] The flow of this system's program processing

[0176] Step 1:

[0177] The user enters a question.

[0178] Input: The user types a question into the device using text or voice, for example, "Teach me how to use this phone."

[0179] Processing: The device receives the input and converts it to text form. If it is voice input, it converts it to text using speech recognition software (e.g., Google Speech-to-Text).

[0180] Output: A textual question is prepared on the terminal.

[0181] Step 2:

[0182] The terminal sends a question to the server.

[0183] Input: A text question entered by the user. For example, "Teach me how to use this phone."

[0184] Process: The device sends a question to the server using an HTTP request.

[0185] Output: The server receives the query.

[0186] Step 3:

[0187] The server sends the question to the generative AI model.

[0188] Input: A text question sent from the device, for example, "Teach me how to use this phone."

[0189] Processing: The server sends an API request to the generative AI model and inputs the prompt sentence into the generative AI model.

[0190] Output: The generative AI model begins processing.

[0191] Step 4:

[0192] A generative AI model generates a response.

[0193] Input: The prompt sent by the server. For example, "Teach me how to use this phone."

[0194] Processing: A generative AI model (e.g., GPT-3) generates a response based on the prompt.

[0195] Output: A response such as "To use your smartphone, power it on, then access the settings menu..." is generated and sent back to the server.

[0196] Step 5:

[0197] The server retrieves the additional information from the database.

[0198] Input: The response received from the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..."

[0199] Action: The server executes a database query to retrieve relevant product and user information.

[0200] Output: Retrieved product and user information, such as "related accessory information" and "product page link."

[0201] Step 6:

[0202] The server formats the response.

[0203] Input: The response of the generative AI model and additional information retrieved from the database.

[0204] Processing: The server combines the generated AI model's response with additional information and formats it in a user-friendly format.

[0205] Output: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]".

[0206] Step 7:

[0207] The server sends the formatted response to the terminal.

[0208] Input: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]."

[0209] Processing: The server uses the HTTP response to format the response and sends it to the terminal.

[0210] Output: The response arrives at the terminal.

[0211] Step 8:

[0212] The terminal displays the response to the user.

[0213] Input: The formatted response received from the server, for example, "To learn how to use your smartphone, power it on, then access the settings menu.... For related accessories, see the following link: [LINK]".

[0214] Processing: The terminal displays the formatted response in its user interface.

[0215] Output: The user sees the response on the screen.

[0216] Step 9:

[0217] A user adds a product to their cart.

[0218] Input: The product selected by the user to add to cart. For example, a specific smartphone.

[0219] Action: The user presses the "Add to Cart" button. The device records this action.

[0220] Output: An add to cart request is prepared on the terminal.

[0221] Step 10:

[0222] The terminal sends a cart add request to the server.

[0223] Input: User's add-to-cart request, for example, the product ID of a smartphone.

[0224] Processing: The terminal sends an add-to-cart request to the server as an HTTP request.

[0225] Output: The server receives the add to cart request.

[0226] Step 11:

[0227] The server updates the cart.

[0228] Input: User add-to-cart request, for example, smartphone product ID.

[0229] Processing: The server adds the item to the user's cart and updates the database.

[0230] Output: The cart is updated and the user sees the message "Product added to cart."

[0231] (Application example 1)

[0232] 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."

[0233] Current online shopping systems require a lot of effort for users to input questions and receive responses. Furthermore, they lack efficient methods for providing product operation instructions and detailed product information, limiting the user experience. In particular, when shopping using virtual reality (VR), users need a way to ask questions and give instructions using a natural interface, but current systems are unable to adequately address this need.

[0234] 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.

[0235] In this invention, the server includes means for generating a response to a user's question using a generative artificial intelligence model, means for transmitting the question entered by the user to the generative artificial intelligence model, and means for displaying the generated response to the user. This allows the user to obtain product information and operation instructions through natural dialogue in a virtual space. Furthermore, by including means for providing a user experience using a head-mounted display and means for converting user input into text using voice recognition, the user can enjoy virtual shopping in an intuitive and natural way. Furthermore, by simplifying the process of adding products the user wishes to purchase to their cart, the efficiency of online shopping and the user experience can be improved.

[0236] "Generative artificial intelligence models" are artificial intelligence algorithms and systems for generating responses to user questions.

[0237] "User input" refers to operations such as questions and instructions given by the user to the system.

[0238] The "server" is the central component that operates the generative AI model, receives and processes requests from users, generates responses, and interacts with the database.

[0239] A "head-mounted display" is a display device worn on the user's head, allowing them to visually experience virtual reality (VR) and augmented reality (AR).

[0240] "Speech recognition" is a technology that analyzes a user's voice and converts it into text format.

[0241] A "virtual space" is a computer-generated virtual space in which users can have an interactive experience.

[0242] A "cart" is an electronic list or function that temporarily holds items that a user wishes to purchase.

[0243] "User experience" refers to the overall feeling and impression a user gets while using a product or service.

[0244] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for a user to experience products in a virtual space and add desired products to a cart.

[0245] System Configuration

[0246] server

[0247] The server is the central component of the invention and has the following functions:

[0248] 1. Request reception: Receives a question sent by the user or device in voice or text format.

[0249] 2. Generative AI processing: The received question is sent to a generative AI model (e.g., GPT-4) to generate a response.

[0250] 3. Database integration: Retrieve the necessary product information and user data from the database and add it to the generated response.

[0251] 4. Response generation: The generated response is formatted and sent back to the user or device.

[0252] 5. Cart management: Receives cart addition requests from users and adds the corresponding products to the user's cart.

[0253] Hardware and software used

[0254] Head-mounted display (HMD): A display device that allows users to experience shopping in a virtual space.

[0255] Speech Recognition Software: Technology that converts user voice input into text, using Google Cloud Speech-to-Text as an example.

[0256] Generative AI model (GPT-4): Artificial intelligence for generating responses to user questions.

[0257] Database system: A system that holds product information and user data.

[0258] Display module: A module that visually displays the generated responses within the head-mounted display.

[0259] Specific examples

[0260] Suppose a user wears a head-mounted display and asks a voice question like this:

[0261] "Tell me the features of this red dress."

[0262] This speech is converted into text by speech recognition software, and the textual question is then sent to a server where a generative AI model (GPT-4) generates a response like this:

[0263] "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[0264] Additionally, the server retrieves additional product information from its database and includes it in the response:

[0265] "Plus, this dress is available in all sizes for 49,800 yen."

[0266] The final response is displayed on the head-mounted display, allowing the user to intuitively obtain information about the product. If the user wants to purchase the product, they can use voice commands such as "add to cart" to add the product to their cart.

[0267] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0268] Step 1:

[0269] The terminal receives the user's voice input.

[0270] Specific behavior:

[0271] The user wears a head-mounted display and utters a question by voice, such as "What are the features of this red dress?" Speech recognition software captures this and converts it into text.

[0272] input:

[0273] User voice input: "What are the features of this red dress?"

[0274] output:

[0275] Text question: "What are the features of this red dress?"

[0276] Step 2:

[0277] The device sends a textual question to the server.

[0278] Specific behavior:

[0279] The question converted into text format is sent from the terminal to the server in the form of an HTTP request or the like.

[0280] input:

[0281] Text question: "What are the features of this red dress?"

[0282] output:

[0283] Text question sent to the server

[0284] Step 3:

[0285] The server receives the question and sends it to the generative AI model.

[0286] Specific behavior:

[0287] The server sends the received question as a prompt to a generative AI model (e.g., GPT-4), which generates a response based on it.

[0288] input:

[0289] A text question sent to the server: "What are the features of this red dress?"

[0290] output:

[0291] Response text from the generative AI model: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[0292] Step 4:

[0293] The server formats the response from the generative AI model and retrieves additional information from the database to incorporate into the response.

[0294] Specific behavior:

[0295] In addition to the response obtained from the generative AI model, we retrieve detailed information about the product from the database (price, size, etc.) and add it to the response.

[0296] input:

[0297] A database containing response text from the generative AI model and product information

[0298] output:

[0299] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[0300] Step 5:

[0301] The server sends the formatted response to the terminal.

[0302] Specific behavior:

[0303] The formatted response is sent to the terminal in the form of an HTTP response or the like.

[0304] input:

[0305] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[0306] output:

[0307] The formatted response sent to the terminal

[0308] Step 6:

[0309] The terminal displays the received response on the user interface.

[0310] Specific behavior:

[0311] The terminal displays the received text on the head-mounted display so that the user can see it.

[0312] input:

[0313] The formatted response sent to the terminal

[0314] output:

[0315] The response displayed in the user interface was, "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[0316] Step 7:

[0317] The user gives the instruction to add an item to the cart.

[0318] Specific behavior:

[0319] The user speaks the command "add to cart," which is also converted into text by the speech recognition software and sent to the server.

[0320] input:

[0321] Voice input "Add to Cart"

[0322] output:

[0323] "Add to Cart" instructions converted to plain text

[0324] Step 8:

[0325] The server receives the request to add the product to the cart and adds the product to the cart.

[0326] Specific behavior:

[0327] The server updates the user's cart database based on the received request and adds the product to the cart.

[0328] input:

[0329] "Add to Cart" instructions converted to plain text

[0330] output:

[0331] The product is added to the user's cart and cart update information is generated.

[0332] Step 9:

[0333] The server notifies the terminal that the cart has been updated.

[0334] Specific behavior:

[0335] A notification that the cart has been updated is sent to the terminal in the form of an HTTP response or the like.

[0336] input:

[0337] Cart update information

[0338] output:

[0339] Cart update notifications sent to your device

[0340] Step 10:

[0341] The device displays a cart update notification to the user.

[0342] Specific behavior:

[0343] The terminal displays on the head-mounted display that the cart has been updated and provides the user with a message saying "Product added to cart."

[0344] input:

[0345] Cart update notifications sent to your device

[0346] output:

[0347] Cart update message displayed in the user interface: "Item added to cart"

[0348] The above process realizes a system that allows users to ask questions in a virtual space, receive responses using a generative AI model, and shop efficiently.

[0349] 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.

[0350] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[0351] System Configuration

[0352] server

[0353] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[0354] 1. Request received:

[0355] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[0356] 2. Generative AI processing:

[0357] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[0358] 3. Emotion recognition:

[0359] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[0360] 4. Database integration:

[0361] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and adds it to the response.

[0362] 5. Response Generation:

[0363] The server formats the generated response and sends it back to the user or terminal.

[0364] 6. Cart Management:

[0365] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[0366] Terminal

[0367] The terminal functions as an interface with the user and has the following functions:

[0368] 1. User Interface:

[0369] It provides an interface where users can enter and submit questions, either through text input or voice input.

[0370] 2. Submit your request:

[0371] The entered question is sent to the server.

[0372] 3. Response display:

[0373] The response received from the server is displayed in the user interface.

[0374] 4. Cart function:

[0375] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[0376] 5. Emotion information display:

[0377] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[0378] User

[0379] The user performs the following operations:

[0380] 1. Enter your question:

[0381] Enter product-related questions into the device using text or voice.

[0382] For example: "Teach me how to use this smartphone."

[0383] 2. Response confirmation:

[0384] Check the response from the server displayed on the terminal.

[0385] 3. Purchase decision:

[0386] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[0387] Specific examples

[0388] Next, an embodiment of the present invention will be described with specific examples.

[0389] 1. Enter your question

[0390] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[0391] 2. Submit your question

[0392] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[0393] 3. Generative AI Processing

[0394] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[0395] 4. Reflecting emotional information

[0396] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[0397] 5. Data Formatting

[0398] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0399] 6. Sending and Displaying Responses

[0400] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[0401] 7. Add to Cart

[0402] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0403] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[0404] The processing flow will be explained below.

[0405] Step 1:

[0406] The user enters a question via text or voice into the device's user interface. For example, "Please tell me how to use this smartphone."

[0407] Step 2:

[0408] The device captures the user's question, as well as the user's facial expression and voice data. This data is then sent to the server. The data sent is often in text format, JSON.

[0409] Step 3:

[0410] The server receives the question and emotion data sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[0411] Step 4:

[0412] The server sends the converted question to a generative AI model (e.g., GPT-3) to generate a response. The generative AI model generates a response based on the user's question.

[0413] Step 5:

[0414] The server then sends the user's emotion data to the emotion engine, which then analyzes the user's emotion. The emotion engine then analyzes facial expressions and voice to recognize the user's emotion (e.g., surprise, joy, stress).

[0415] Step 6:

[0416] The emotion engine returns the analysis results to the server, which are provided to the server as data containing the emotions the user was feeling when entering the information.

[0417] Step 7:

[0418] The server combines the response from the generative AI model with emotional data from the emotion engine. For example, if the user is feeling stressed, it may adjust the response to be more succinct. It may also retrieve additional product information or tutorial links from the database and incorporate them into the response.

[0419] Step 8:

[0420] The server formats the final response in JSON format and sends it to the device, which includes the generative AI's response, additional information, and adjustments based on emotion recognition.

[0421] Step 9:

[0422] The device analyzes the response received from the server and displays it on the user interface. The content displayed is the answer to the question asked by the user. For example, it might say, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[0423] Step 10:

[0424] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[0425] Step 11:

[0426] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[0427] Step 12:

[0428] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[0429] Step 13:

[0430] The server sends the cart update status (success or failure) to the device.

[0431] Step 14:

[0432] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[0433] In this way, the program's processing is clearly divided into steps, allowing users to smoothly proceed from inquiry to purchase. Emotion recognition makes it possible to provide optimal responses based on the user's emotions, making online shopping easier and more convenient for people with visual impairments in particular. This system aims to improve the user experience.

[0434] Example 2

[0435] 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."

[0436] In conventional online shopping systems, when users ask questions about products, they often do not receive an appropriate response, which can lead to a poor user experience. Furthermore, because the system does not take into account the user's feelings, it can be difficult to use, especially for users with disabilities. This can lead to problems such as a decrease in user satisfaction and a decrease in purchasing motivation.

[0437] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0438] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question input by the user to the generative AI model, means for recognizing the user's emotion based on the generated response, means for adjusting the response based on the recognized emotion information, means for displaying the generated response to the user, and means for adding products the user wishes to purchase to a cart. This provides an appropriate response to the user's question that takes emotion into consideration, and is easy to use, especially for users with disabilities, thereby improving the user experience and encouraging purchasing motivation.

[0439] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates responses in natural language to questions or commands entered by a user.

[0440] "User questions" are information or questions that users input to the system, including details about the product and how to use it.

[0441] An "emotion recognition engine" is an algorithm or software that analyzes user input data (voice and facial expressions) to identify the user's emotional state.

[0442] "Means for adding to cart" refers to the mechanism by which a user registers desired products in an online shopping cart.

[0443] The "database" is a repository of information that stores data from generative AI models and emotion recognition engines, product information, user data, etc.

[0444] "Means for displaying the generated response to the user" refers to a mechanism for presenting the response created by the generative artificial intelligence model on a user interface.

[0445] The "means for adjusting the response" refers to a mechanism for appropriately modifying the generated response based on the recognized emotional information of the user.

[0446] MODE FOR CARRYING OUT THE INVENTION

[0447] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[0448] System Configuration

[0449] server

[0450] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[0451] 1. Request reception: The server receives a question sent by a user or terminal. The received question can be in text or voice format.

[0452] 2. Generative AI processing: The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[0453] 3. Emotion Recognition: The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[0454] 4. Database integration: The server retrieves the necessary product information and user data from the database along with data from the generative AI model and emotion engine, and adds them to the response.

[0455] 5. Response generation: The server formats the generated response and sends it back to the user or device.

[0456] 6. Cart management: The server receives a cart addition request from the user and adds the corresponding item to the user's cart.

[0457] Terminal

[0458] The terminal functions as an interface with the user and has the following functions:

[0459] 1. User Interface: Provides an interface where users can input and submit questions. Input can be done via text input or voice input.

[0460] 2. Send request: Send the entered question to the server.

[0461] 3. Display response: Display the response received from the server in the user interface.

[0462] 4. Cart functionality: Provide an interface that allows users to add desired products to their cart (e.g., add to cart button).

[0463] 5. Emotional information display: Change the display of the user interface based on the emotional information obtained from the emotion engine (e.g., simplify the display if the user feels stressed).

[0464] User

[0465] The user performs the following operations:

[0466] 1. Question input: Enter a question about the product into the device using text or voice. For example, "Tell me how to use this smartphone."

[0467] 2. Check the response: Check the response from the server displayed on the terminal.

[0468] 3. Purchase decision: If there is an item you would like to add to your cart, press the "Add to cart" button.

[0469] Specific examples

[0470] Next, an embodiment of the present invention will be described with specific examples.

[0471] 1. Enter your question

[0472] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[0473] 2. Submit your question

[0474] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[0475] 3. Generative AI Processing

[0476] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. The prompt is, "The user wants to know how to use this smartphone." The response is, "To use the smartphone, power it on, then access the settings menu..."

[0477] 4. Reflecting emotional information

[0478] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[0479] 5. Data Formatting

[0480] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0481] 6. Sending and Displaying Responses

[0482] The server sends a formatted response back to the device, which displays the response in its user interface, for example, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[0483] 7. Add to Cart

[0484] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0485] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[0486] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0487] Step 1: User enters question

[0488] The user enters a question into the device's input box, such as "Teach me how to use this smartphone." The user can enter the question using text or voice. The entered data is sent directly to the next step by the device.

[0489] Step 2: Submit your question

[0490] The device sends the question entered by the user to the server. At this time, the user's emotional information (e.g., facial expressions and voice data) is also sent. The device receives the question and emotional data as input and sends them to the server. As output, data to be sent to the server is generated.

[0491] Step 3: Server receives query

[0492] The server receives the question and emotion information sent from the device. It receives the data sent from the device as input and analyzes the question text and emotion data. The analyzed text data and emotion data are obtained as output.

[0493] Step 4: Generative AI generates a response

[0494] The server sends the received question text to a generative AI model (e.g., GPT-3) as a prompt. The question text is provided as input, and a response is generated by the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..." The generated response is obtained as output.

[0495] Step 5: Emotion Recognition Engine Processing

[0496] The server sends the received emotion data to the emotion recognition engine to analyze the user's emotion. The emotion data is provided as input, and emotion analysis is performed. The output is the analyzed user's emotional state (e.g., joy, surprise, stress).

[0497] Step 6: Shaping the data

[0498] The server adjusts the response from the generation AI based on the emotional information obtained from the emotion recognition engine. It receives the response sentence and emotional data as input and modifies the response according to the emotion. For example, if the user is feeling stressed, it will make the response briefer. The modified response sentence is generated as output.

[0499] Step 7: Connect to the database

[0500] The server retrieves the necessary product information and user data from the database based on data from the generative AI model and emotion engine. As input, it sends queries to retrieve product information and user attribute information and retrieves the data. As output, additional product information and links are incorporated into the response.

[0501] Step 8: Formatting the response

[0502] The server formats the final response based on the retrieved product information. As input, it receives information from multiple data sources, integrates it, and formats it in a way that is optimal for the user. As output, a formatted response is generated.

[0503] Step 9: Sending a Response

[0504] The server sends a formatted response to the terminal. It receives a formatted response as input and sends it to the terminal. As output, it gets the data sent to the terminal.

[0505] Step 10: Displaying the response on the terminal

[0506] The terminal displays the response received from the server on the user interface. As input, it receives response data from the server and displays it in a format that is easy for the user to see. As output, it provides a response display that the user can confirm.

[0507] Step 11: User Add to Cart Operation

[0508] The user presses the "Add to Cart" button for the product they wish to purchase. The appropriate "Add to Cart" button event is generated as input, and that information is sent to the next step. The output is an add-to-cart request.

[0509] Step 12: Add to Cart Processing by Server

[0510] The server receives the user's add-to-cart request and adds the product to the cart. It takes the add-to-cart request as input and updates the cart database. It generates the updated cart data and a confirmation message as output.

[0511] Step 13: Displaying the Add to Cart message on the device

[0512] The terminal receives the cart addition confirmation message from the server and displays it to the user. It receives the message from the server as input and displays it in its user interface. As output, the user sees "Product added to cart."

[0513] (Application example 2)

[0514] 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."

[0515] Conventional online shopping systems have the problem that users may feel stressed during the process of obtaining product information and making a purchase decision, resulting in a poor user experience.In addition, because they are unable to respond or operate in accordance with the user's emotions, they can be difficult to understand and use, especially for first-time users, the elderly, and people with disabilities.

[0516] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0517] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question entered by the user to the generative AI model, means for displaying the generated response to the user, means for adding an item the user wishes to purchase to a cart, means including an emotion recognition engine for recognizing the user's emotion, and means for incorporating the recognized emotion information into the response generation process. This enables responses and operations to be performed in accordance with the user's emotion, thereby providing a particularly stress-free shopping experience.

[0518] A "generative artificial intelligence model" is an artificial intelligence system that automatically generates responses based on user input.

[0519] A "question" is a text or voice input about information or knowledge that a user seeks.

[0520] A "response" is an answer to a user's question generated by a generative artificial intelligence model.

[0521] An "emotion recognition engine" is a software technology that identifies emotions from user input, facial expressions, and voice.

[0522] The "cart" refers to an area where a user temporarily stores products that they wish to purchase.

[0523] "Emotion information" is data on the user's emotions identified by the emotion recognition engine.

[0524] "Product Information" means detailed data relating to a particular product, including price, description, reviews, and images.

[0525] "Instructions" are steps or guidelines for using a product.

[0526] A "brain-controlled interface" is a technology that uses brain waves and neural signals to operate computers and devices.

[0527] A "user interface" refers to input and display means such as a screen and operation buttons that allow a user to interact with a system.

[0528] This invention is a system that combines a generative AI model to generate and display a response to a user's question, an emotion engine that recognizes the user's emotions, and a series of procedures for adding products the user wishes to purchase to their cart.

[0529] System Configuration

[0530] server

[0531] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[0532] 1. Request received:

[0533] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[0534] 2. Generative AI processing:

[0535] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[0536] 3. Emotion recognition:

[0537] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[0538] 4. Database integration:

[0539] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and incorporates it into the response.

[0540] 5. Response Generation:

[0541] The server formats the generated response and sends it back to the user or terminal.

[0542] 6. Cart Management:

[0543] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[0544] Terminal

[0545] The terminal functions as an interface with the user and has the following functions:

[0546] 1. User Interface:

[0547] It provides an interface where users can enter and submit questions, either through text input or voice input.

[0548] 2. Submit your request:

[0549] The entered question is sent to the server.

[0550] 3. Response display:

[0551] The response received from the server is displayed in the user interface.

[0552] 4. Cart function:

[0553] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[0554] 5. Emotion information display:

[0555] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[0556] User

[0557] The user performs the following operations:

[0558] 1. Enter your question:

[0559] Enter product-related questions into the device using text or voice.

[0560] For example: "Teach me how to use my new smartphone."

[0561] 2. Response confirmation:

[0562] Check the response from the server displayed on the terminal.

[0563] 3. Purchase decision:

[0564] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[0565] Specific examples

[0566] Next, an embodiment of the present invention will be described with specific examples.

[0567] 1. Enter your question:

[0568] If a user has a question about how to use their new smartphone, they can type "Teach me how to use my new smartphone" into the input box on the device. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[0569] 2. Submit your question:

[0570] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[0571] 3. Generative AI processing:

[0572] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[0573] 4. Reflecting emotional information:

[0574] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[0575] 5. Data Formatting:

[0576] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0577] 6. Sending and displaying responses:

[0578] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[0579] 7. Add to Cart:

[0580] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0581] As an example, here is an example of a prompt sentence to be input to the generative AI model:

[0582] Example prompt sentence:

[0583] User input: I want to know how to use my new smartphone.

[0584] Emotion: Stress

[0585] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier and more convenient for people with disabilities and the elderly, thereby improving the user experience.

[0586] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0587] Step 1:

[0588] The user inputs a question into the device's interface. The input question can be in text or voice format. For example, the user might input "Teach me how to use my new smartphone." This is input data from the user.

[0589] Step 2:

[0590] The device receives the user's input data and first sends the data to an emotion recognition engine to analyze the user's emotions. The emotion recognition engine extracts features from the user's input (voice, text, facial expressions) and outputs an emotion label (e.g., stress, joy, etc.). In this example, we assume that the emotion label is determined to be "stress."

[0591] Step 3:

[0592] The device sends the user's input data and emotional information to the server. At this time, the input data is converted into text format, and the emotional information is sent as an emotional label. Specifically, the input data "Teach me how to use my new smartphone" and the emotional information "Stress" are sent to the server.

[0593] Step 4:

[0594] The server sends the received input data and emotion information to a generative AI model (e.g., GPT-3). The server sends the input data as a prompt to the generative AI model, which then generates a response. For example, the prompt might be "User input: I want to know how to use my new smartphone. Emotion: Stress." The generative AI model generates an answer based on this prompt and outputs the response text.

[0595] Step 5:

[0596] The server receives the generated response text, retrieves related product information (e.g., tutorial links) from the database, and adds detailed information related to the selected product from the database.

[0597] Step 6:

[0598] The server combines the generated response text with the acquired product information to generate the final response. It adjusts the response to be concise, taking into account emotional information. In this example, the final response generated is, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[0599] Step 7:

[0600] The server sends the final response to the device, which displays it to the user, who can then see the answer to their question by viewing the response displayed in the device's interface.

[0601] Step 8:

[0602] If the user is satisfied with the answers and decides to purchase the product, he or she presses the "Add to Cart" button on the terminal, which sends a request to add the product to the cart from the terminal to the server.

[0603] Step 9:

[0604] The server receives the cart addition request and updates the user's cart based on the product ID and user ID. If the update is successful, the server sends a message to the terminal stating "The product has been added to the cart."

[0605] Step 10:

[0606] The terminal receives the message from the server and displays the message "The product has been added to the cart" on the user interface. The user can confirm this message and continue the purchase procedure.

[0607] The above is a specific processing flow for carrying out the present invention, which allows the user to efficiently and stress-free go from obtaining product information to deciding on a purchase.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] [Second embodiment]

[0612] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0613] 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.

[0614] 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).

[0615] 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.

[0616] 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.

[0617] 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).

[0618] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] In the smart glasses 214, 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.

[0623] 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."

[0624] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for adding products that the user wishes to purchase to a cart.

[0625] System Configuration

[0626] server

[0627] The server is the core component that operates the generative artificial intelligence model. The server has the following functions:

[0628] 1. Request received:

[0629] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[0630] 2. Generative AI processing:

[0631] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[0632] 3. Database integration:

[0633] The server retrieves the necessary product information and user data from the database along with the response from the generative AI model and adds it to the response.

[0634] 4. Response generation:

[0635] The server formats the generated response and sends it back to the user or terminal.

[0636] 5. Cart Management:

[0637] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[0638] Terminal

[0639] The terminal functions as an interface with the user and has the following functions:

[0640] 1. User Interface:

[0641] It provides an interface where users can enter and submit questions, either through text input or voice input.

[0642] 2. Submit your request:

[0643] The entered question is sent to the server.

[0644] 3. Response display:

[0645] The response received from the server is displayed in the user interface.

[0646] 4. Cart function:

[0647] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[0648] User

[0649] The user performs the following operations:

[0650] 1. Enter your question:

[0651] Enter product-related questions into the device using text or voice.

[0652] For example: "Teach me how to use this smartphone."

[0653] 2. Response confirmation:

[0654] Check the response from the server displayed on the terminal.

[0655] 3. Purchase decision:

[0656] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[0657] Specific examples

[0658] Next, an embodiment of the present invention will be described with specific examples.

[0659] 1. Enter your question

[0660] If a user has a question about how to use their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[0661] 2. Submit your question

[0662] The device sends this question to the server, which receives the question and sends it to the generating AI.

[0663] 3. Generative AI Processing

[0664] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[0665] 4. Data Formatting

[0666] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0667] 5. Sending and Displaying Responses

[0668] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[0669] 6. Add to Cart

[0670] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0671] The system configured in this way allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. The system of the present invention makes it easy for people with disabilities to shop online, improving the user experience.

[0672] The processing flow will be explained below.

[0673] Step 1:

[0674] The user enters a question by text or voice into a user interface on the device.

[0675] Step 2:

[0676] The device receives the user's question and sends the question and the user's ID to the server. The data sent is often in text format, JSON.

[0677] Step 3:

[0678] The server receives the question sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[0679] Step 4:

[0680] The server sends the converted question to the generative AI model, which then generates a response based on the user's question.

[0681] Step 5:

[0682] The generation AI generates a response to the question received from the server and returns the response to the server. The generated response is created in detail based on the content of the question.

[0683] Step 6:

[0684] The server formats the response received from the generation AI, and if necessary, retrieves additional information from the database (e.g., product specifications or the user's past purchase history) and incorporates it into the response.

[0685] Step 7:

[0686] The server converts the formatted response into JSON format and sends it to the device, which includes the generated AI's response and additional information.

[0687] Step 8:

[0688] The terminal analyzes the response received from the server and displays it on the user interface. The displayed content is the answer to the question asked by the user.

[0689] Step 9:

[0690] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[0691] Step 10:

[0692] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[0693] Step 11:

[0694] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[0695] Step 12:

[0696] The server sends the cart update status (success or failure) to the device.

[0697] Step 13:

[0698] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[0699] In this way, the program's processing is clearly divided into steps, allowing users to smoothly progress from asking questions to completing the purchase process.

[0700] Example 1

[0701] 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."

[0702] Conventional online shopping systems require users to use multiple different platforms to answer questions about products and complete purchase procedures, which is time-consuming. Furthermore, the process from obtaining information to making a purchase decision is fragmented, making it difficult to improve the user experience. Furthermore, insufficient or inaccurate information can discourage users from making a purchase.

[0703] 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.

[0704] In this invention, the server includes means for receiving a user's question, means for sending the question to a generative AI model, means for generating a response from the generative AI model, means for retrieving product information and user information from a database, means for formatting the generated response, means for displaying the formatted response to the user, and means for adding products the user wishes to purchase to a cart. This allows users to complete the entire process from asking a question to completing the purchase procedure within a single platform, improving the user experience and increasing their willingness to purchase.

[0705] A "user" is an entity that uses this system to input questions, receive responses, and purchase products.

[0706] A "generative AI model" is an artificial intelligence model that receives a question from a user and generates an appropriate response to it.

[0707] The "server" is a central facility that receives user questions, sends them to the generative AI model, generates responses, connects with the database, considers the final response, and sends it to the terminal.

[0708] A "terminal" is a device that provides an interface for a user to enter questions, interact with the server, display generated responses, and add items to a cart.

[0709] A "database" is an information management system that stores information such as product information and user information, and allows the server to refer to and retrieve information as needed.

[0710] The "means for receiving a question" is a function for acquiring a question input by a user and inputting it into the server.

[0711] "Means for sending questions to the generative AI model" is a function that sends the questions received by the server to the generative AI model and obtains the response.

[0712] "Means for generating a response from a generative AI model" refers to the function of the generative AI model to create an appropriate response based on an input question.

[0713] The "means for linking with a database" is a function that enables the server to obtain additional information required for a response from a database and incorporate it into the response.

[0714] "Means for formatting responses" is a function that formats information obtained from the generative AI model and database into a format that is easy for users to view and understand.

[0715] The "means for displaying to the user" is a function for visually presenting the formatted response to the user via the terminal.

[0716] The "means for adding to cart" is a function for adding products that the user wishes to purchase to a virtual shopping cart.

[0717] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative AI model, and displays the response. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[0718] System Configuration

[0719] server

[0720] The server is the core component that operates the generative AI model and has the following functions:

[0721] 1. Request received:

[0722] The server receives a question sent from a user or a device, such as "How do I use this smartphone?"

[0723] 2. Generative AI processing:

[0724] The server sends the received question to a generative AI model (e.g., GPT-3), which generates an appropriate response based on the prompt.

[0725] 3. Database integration:

[0726] Based on the response from the generative AI model, the server retrieves additional product information and user data from the database, such as related accessory information and product page links.

[0727] 4. Response Formatting:

[0728] The server combines the acquired information with the response of the generating AI and formats it in a format that is easy for the user to understand.

[0729] 5. Send Response:

[0730] The server sends a formatted response back to the terminal for display to the user.

[0731] 6. Cart Management:

[0732] The server receives a cart add request from the user and adds the product to the user's cart.

[0733] Terminal

[0734] The terminal functions as an interface with the user. Its specific functions are as follows:

[0735] 1. User Interface:

[0736] It provides an interface for users to enter and submit questions, either by text input or by voice input.

[0737] 2. Submit your request:

[0738] The entered question is sent to the server. For example, a question such as "Teach me how to use this smartphone" is sent.

[0739] 3. Response display:

[0740] Display the response received from the server in the user interface. For example, the response might look like this: "To use your smartphone, power it on, then access the settings menu..."

[0741] 4. Cart function:

[0742] An interface is provided for users to add desired products to their cart. For example, a user can add a product to their cart by pressing an "Add to cart" button.

[0743] User

[0744] The user performs the following operations:

[0745] 1. Enter your question:

[0746] Enter a question about the product into the device using text or voice. For example, enter the question "How do I use this smartphone?"

[0747] 2. Response confirmation:

[0748] Check the response from the server that is displayed on the device, such as "To use your smartphone, turn it on, then access the settings menu..."

[0749] 3. Purchase decision:

[0750] If there is an item you would like to add to your cart, press the "Add to Cart" button. For example, if you decide to purchase a smartphone, press the "Add to Cart" button.

[0751] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision, thereby improving the user experience and increasing their willingness to buy.

[0752] Specific examples

[0753] Specific usage scenarios are shown below.

[0754] 1. Enter your question

[0755] If a user has a question about how to operate their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[0756] 2. Submit your question

[0757] The device sends this question to the server, which receives the question and sends it to the generating AI.

[0758] 3. Generative AI Processing

[0759] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[0760] 4. Data Formatting

[0761] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0762] 5. Sending and Displaying Responses

[0763] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[0764] 6. Add to Cart

[0765] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0766] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0767] The flow of this system's program processing

[0768] Step 1:

[0769] The user enters a question.

[0770] Input: The user types a question into the device using text or voice, for example, "Teach me how to use this phone."

[0771] Processing: The device receives the input and converts it to text form. If it is voice input, it converts it to text using speech recognition software (e.g., Google Speech-to-Text).

[0772] Output: A textual question is prepared on the terminal.

[0773] Step 2:

[0774] The terminal sends a question to the server.

[0775] Input: A text question entered by the user. For example, "Teach me how to use this phone."

[0776] Process: The device sends a question to the server using an HTTP request.

[0777] Output: The server receives the query.

[0778] Step 3:

[0779] The server sends the question to the generative AI model.

[0780] Input: A text question sent from the device, for example, "Teach me how to use this phone."

[0781] Processing: The server sends an API request to the generative AI model and inputs the prompt sentence into the generative AI model.

[0782] Output: The generative AI model begins processing.

[0783] Step 4:

[0784] A generative AI model generates a response.

[0785] Input: The prompt sent by the server. For example, "Teach me how to use this phone."

[0786] Processing: A generative AI model (e.g., GPT-3) generates a response based on the prompt.

[0787] Output: A response such as "To use your smartphone, power it on, then access the settings menu..." is generated and sent back to the server.

[0788] Step 5:

[0789] The server retrieves the additional information from the database.

[0790] Input: The response received from the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..."

[0791] Action: The server executes a database query to retrieve relevant product and user information.

[0792] Output: Retrieved product and user information, such as "related accessory information" and "product page link."

[0793] Step 6:

[0794] The server formats the response.

[0795] Input: The response of the generative AI model and additional information retrieved from the database.

[0796] Processing: The server combines the generated AI model's response with additional information and formats it in a user-friendly format.

[0797] Output: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]".

[0798] Step 7:

[0799] The server sends the formatted response to the terminal.

[0800] Input: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]."

[0801] Processing: The server uses the HTTP response to format the response and sends it to the terminal.

[0802] Output: The response arrives at the terminal.

[0803] Step 8:

[0804] The terminal displays the response to the user.

[0805] Input: The formatted response received from the server, for example, "To learn how to use your smartphone, power it on, then access the settings menu.... For related accessories, see the following link: [LINK]".

[0806] Processing: The terminal displays the formatted response in its user interface.

[0807] Output: The user sees the response on the screen.

[0808] Step 9:

[0809] A user adds a product to their cart.

[0810] Input: The product selected by the user to add to cart. For example, a specific smartphone.

[0811] Action: The user presses the "Add to Cart" button. The device records this action.

[0812] Output: An add to cart request is prepared on the terminal.

[0813] Step 10:

[0814] The terminal sends a cart add request to the server.

[0815] Input: User's add-to-cart request, for example, the product ID of a smartphone.

[0816] Processing: The terminal sends an add-to-cart request to the server as an HTTP request.

[0817] Output: The server receives the add to cart request.

[0818] Step 11:

[0819] The server updates the cart.

[0820] Input: User add-to-cart request, for example, smartphone product ID.

[0821] Processing: The server adds the item to the user's cart and updates the database.

[0822] Output: The cart is updated and the user sees the message "Product added to cart."

[0823] (Application example 1)

[0824] 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."

[0825] Current online shopping systems require a lot of effort for users to input questions and receive responses. Furthermore, they lack efficient methods for providing product operation instructions and detailed product information, limiting the user experience. In particular, when shopping using virtual reality (VR), users need a way to ask questions and give instructions using a natural interface, but current systems are unable to adequately address this need.

[0826] 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.

[0827] In this invention, the server includes means for generating a response to a user's question using a generative artificial intelligence model, means for transmitting the question entered by the user to the generative artificial intelligence model, and means for displaying the generated response to the user. This allows the user to obtain product information and operation instructions through natural dialogue in a virtual space. Furthermore, by including means for providing a user experience using a head-mounted display and means for converting user input into text using voice recognition, the user can enjoy virtual shopping in an intuitive and natural way. Furthermore, by simplifying the process of adding products the user wishes to purchase to their cart, the efficiency of online shopping and the user experience can be improved.

[0828] "Generative artificial intelligence models" are artificial intelligence algorithms and systems for generating responses to user questions.

[0829] "User input" refers to operations such as questions and instructions given by the user to the system.

[0830] The "server" is the central component that operates the generative AI model, receives and processes requests from users, generates responses, and interacts with the database.

[0831] A "head-mounted display" is a display device worn on the user's head, allowing them to visually experience virtual reality (VR) and augmented reality (AR).

[0832] "Speech recognition" is a technology that analyzes a user's voice and converts it into text format.

[0833] A "virtual space" is a computer-generated virtual space in which users can have an interactive experience.

[0834] A "cart" is an electronic list or function that temporarily holds items that a user wishes to purchase.

[0835] "User experience" refers to the overall feeling and impression a user gets while using a product or service.

[0836] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for a user to experience products in a virtual space and add desired products to a cart.

[0837] System Configuration

[0838] server

[0839] The server is the central component of the invention and has the following functions:

[0840] 1. Request reception: Receives a question sent by the user or device in voice or text format.

[0841] 2. Generative AI processing: The received question is sent to a generative AI model (e.g., GPT-4) to generate a response.

[0842] 3. Database integration: Retrieve the necessary product information and user data from the database and add it to the generated response.

[0843] 4. Response generation: The generated response is formatted and sent back to the user or device.

[0844] 5. Cart management: Receives cart addition requests from users and adds the corresponding products to the user's cart.

[0845] Hardware and software used

[0846] Head-mounted display (HMD): A display device that allows users to experience shopping in a virtual space.

[0847] Speech Recognition Software: Technology that converts user voice input into text, using Google Cloud Speech-to-Text as an example.

[0848] Generative AI model (GPT-4): Artificial intelligence for generating responses to user questions.

[0849] Database system: A system that holds product information and user data.

[0850] Display module: A module that visually displays the generated responses within the head-mounted display.

[0851] Specific examples

[0852] Suppose a user wears a head-mounted display and asks a voice question like this:

[0853] "Tell me the features of this red dress."

[0854] This speech is converted into text by speech recognition software, and the textual question is then sent to a server where a generative AI model (GPT-4) generates a response like this:

[0855] "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[0856] Additionally, the server retrieves additional product information from its database and includes it in the response:

[0857] "Plus, this dress is available in all sizes for 49,800 yen."

[0858] The final response is displayed on the head-mounted display, allowing the user to intuitively obtain information about the product. If the user wants to purchase the product, they can use voice commands such as "add to cart" to add the product to their cart.

[0859] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0860] Step 1:

[0861] The terminal receives the user's voice input.

[0862] Specific behavior:

[0863] The user wears a head-mounted display and utters a question by voice, such as "What are the features of this red dress?" Speech recognition software captures this and converts it into text.

[0864] input:

[0865] User voice input: "What are the features of this red dress?"

[0866] output:

[0867] Text question: "What are the features of this red dress?"

[0868] Step 2:

[0869] The device sends a textual question to the server.

[0870] Specific behavior:

[0871] The question converted into text format is sent from the terminal to the server in the form of an HTTP request or the like.

[0872] input:

[0873] Text question: "What are the features of this red dress?"

[0874] output:

[0875] Text question sent to the server

[0876] Step 3:

[0877] The server receives the question and sends it to the generative AI model.

[0878] Specific behavior:

[0879] The server sends the received question as a prompt to a generative AI model (e.g., GPT-4), which generates a response based on it.

[0880] input:

[0881] A text question sent to the server: "What are the features of this red dress?"

[0882] output:

[0883] Response text from the generative AI model: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[0884] Step 4:

[0885] The server formats the response from the generative AI model and retrieves additional information from the database to incorporate into the response.

[0886] Specific behavior:

[0887] In addition to the response obtained from the generative AI model, we retrieve detailed information about the product from the database (price, size, etc.) and add it to the response.

[0888] input:

[0889] A database containing response text from the generative AI model and product information

[0890] output:

[0891] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[0892] Step 5:

[0893] The server sends the formatted response to the terminal.

[0894] Specific behavior:

[0895] The formatted response is sent to the terminal in the form of an HTTP response or the like.

[0896] input:

[0897] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[0898] output:

[0899] The formatted response sent to the terminal

[0900] Step 6:

[0901] The terminal displays the received response on the user interface.

[0902] Specific behavior:

[0903] The terminal displays the received text on the head-mounted display so that the user can see it.

[0904] input:

[0905] The formatted response sent to the terminal

[0906] output:

[0907] The response displayed in the user interface was, "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[0908] Step 7:

[0909] The user gives the instruction to add an item to the cart.

[0910] Specific behavior:

[0911] The user speaks the command "add to cart," which is also converted into text by the speech recognition software and sent to the server.

[0912] input:

[0913] Voice input "Add to Cart"

[0914] output:

[0915] "Add to Cart" instructions converted to plain text

[0916] Step 8:

[0917] The server receives the request to add the product to the cart and adds the product to the cart.

[0918] Specific behavior:

[0919] The server updates the user's cart database based on the received request and adds the product to the cart.

[0920] input:

[0921] "Add to Cart" instructions converted to plain text

[0922] output:

[0923] The product is added to the user's cart and cart update information is generated.

[0924] Step 9:

[0925] The server notifies the terminal that the cart has been updated.

[0926] Specific behavior:

[0927] A notification that the cart has been updated is sent to the terminal in the form of an HTTP response or the like.

[0928] input:

[0929] Cart update information

[0930] output:

[0931] Cart update notifications sent to your device

[0932] Step 10:

[0933] The device displays a cart update notification to the user.

[0934] Specific behavior:

[0935] The terminal displays on the head-mounted display that the cart has been updated and provides the user with a message saying "Product added to cart."

[0936] input:

[0937] Cart update notifications sent to your device

[0938] output:

[0939] Cart update message displayed in the user interface: "Item added to cart"

[0940] The above process realizes a system that allows users to ask questions in a virtual space, receive responses using a generative AI model, and shop efficiently.

[0941] 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.

[0942] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[0943] System Configuration

[0944] server

[0945] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[0946] 1. Request received:

[0947] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[0948] 2. Generative AI processing:

[0949] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[0950] 3. Emotion recognition:

[0951] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[0952] 4. Database integration:

[0953] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and adds it to the response.

[0954] 5. Response Generation:

[0955] The server formats the generated response and sends it back to the user or terminal.

[0956] 6. Cart Management:

[0957] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[0958] Terminal

[0959] The terminal functions as an interface with the user and has the following functions:

[0960] 1. User Interface:

[0961] It provides an interface where users can enter and submit questions, either through text input or voice input.

[0962] 2. Submit your request:

[0963] The entered question is sent to the server.

[0964] 3. Response display:

[0965] The response received from the server is displayed in the user interface.

[0966] 4. Cart function:

[0967] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[0968] 5. Emotion information display:

[0969] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[0970] User

[0971] The user performs the following operations:

[0972] 1. Enter your question:

[0973] Enter product-related questions into the device using text or voice.

[0974] For example: "Teach me how to use this smartphone."

[0975] 2. Response confirmation:

[0976] Check the response from the server displayed on the terminal.

[0977] 3. Purchase decision:

[0978] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[0979] Specific examples

[0980] Next, an embodiment of the present invention will be described with specific examples.

[0981] 1. Enter your question

[0982] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[0983] 2. Submit your question

[0984] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[0985] 3. Generative AI Processing

[0986] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[0987] 4. Reflecting emotional information

[0988] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[0989] 5. Data Formatting

[0990] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[0991] 6. Sending and Displaying Responses

[0992] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[0993] 7. Add to Cart

[0994] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[0995] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[0996] The processing flow will be explained below.

[0997] Step 1:

[0998] The user enters a question via text or voice into the device's user interface. For example, "Please tell me how to use this smartphone."

[0999] Step 2:

[1000] The device captures the user's question, as well as the user's facial expression and voice data. This data is then sent to the server. The data sent is often in text format, JSON.

[1001] Step 3:

[1002] The server receives the question and emotion data sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[1003] Step 4:

[1004] The server sends the converted question to a generative AI model (e.g., GPT-3) to generate a response. The generative AI model generates a response based on the user's question.

[1005] Step 5:

[1006] The server then sends the user's emotion data to the emotion engine, which then analyzes the user's emotion. The emotion engine then analyzes facial expressions and voice to recognize the user's emotion (e.g., surprise, joy, stress).

[1007] Step 6:

[1008] The emotion engine returns the analysis results to the server, which are provided to the server as data containing the emotions the user was feeling when entering the information.

[1009] Step 7:

[1010] The server combines the response from the generative AI model with emotional data from the emotion engine. For example, if the user is feeling stressed, it may adjust the response to be more succinct. It may also retrieve additional product information or tutorial links from the database and incorporate them into the response.

[1011] Step 8:

[1012] The server formats the final response in JSON format and sends it to the device, which includes the generative AI's response, additional information, and adjustments based on emotion recognition.

[1013] Step 9:

[1014] The device analyzes the response received from the server and displays it on the user interface. The content displayed is the answer to the question asked by the user. For example, it might say, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1015] Step 10:

[1016] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[1017] Step 11:

[1018] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[1019] Step 12:

[1020] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[1021] Step 13:

[1022] The server sends the cart update status (success or failure) to the device.

[1023] Step 14:

[1024] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[1025] In this way, the program's processing is clearly divided into steps, allowing users to smoothly proceed from inquiry to purchase. Emotion recognition makes it possible to provide optimal responses based on the user's emotions, making online shopping easier and more convenient for people with visual impairments in particular. This system aims to improve the user experience.

[1026] Example 2

[1027] 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."

[1028] In conventional online shopping systems, when users ask questions about products, they often do not receive an appropriate response, which can lead to a poor user experience. Furthermore, because the system does not take into account the user's feelings, it can be difficult to use, especially for users with disabilities. This can lead to problems such as a decrease in user satisfaction and a decrease in purchasing motivation.

[1029] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1030] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question input by the user to the generative AI model, means for recognizing the user's emotion based on the generated response, means for adjusting the response based on the recognized emotion information, means for displaying the generated response to the user, and means for adding products the user wishes to purchase to a cart. This provides an appropriate response to the user's question that takes emotion into consideration, and is easy to use, especially for users with disabilities, thereby improving the user experience and encouraging purchasing motivation.

[1031] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates responses in natural language to questions or commands entered by a user.

[1032] "User questions" are information or questions that users input to the system, including details about the product and how to use it.

[1033] An "emotion recognition engine" is an algorithm or software that analyzes user input data (voice and facial expressions) to identify the user's emotional state.

[1034] "Means for adding to cart" refers to the mechanism by which a user registers desired products in an online shopping cart.

[1035] The "database" is a repository of information that stores data from generative AI models and emotion recognition engines, product information, user data, etc.

[1036] "Means for displaying the generated response to the user" refers to a mechanism for presenting the response created by the generative artificial intelligence model on a user interface.

[1037] The "means for adjusting the response" refers to a mechanism for appropriately modifying the generated response based on the recognized emotional information of the user.

[1038] MODE FOR CARRYING OUT THE INVENTION

[1039] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[1040] System Configuration

[1041] server

[1042] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[1043] 1. Request reception: The server receives a question sent by a user or terminal. The received question can be in text or voice format.

[1044] 2. Generative AI processing: The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[1045] 3. Emotion Recognition: The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[1046] 4. Database integration: The server retrieves the necessary product information and user data from the database along with data from the generative AI model and emotion engine, and adds them to the response.

[1047] 5. Response generation: The server formats the generated response and sends it back to the user or device.

[1048] 6. Cart management: The server receives a cart addition request from the user and adds the corresponding item to the user's cart.

[1049] Terminal

[1050] The terminal functions as an interface with the user and has the following functions:

[1051] 1. User Interface: Provides an interface where users can input and submit questions. Input can be done via text input or voice input.

[1052] 2. Send request: Send the entered question to the server.

[1053] 3. Display response: Display the response received from the server in the user interface.

[1054] 4. Cart functionality: Provide an interface that allows users to add desired products to their cart (e.g., add to cart button).

[1055] 5. Emotional information display: Change the display of the user interface based on the emotional information obtained from the emotion engine (e.g., simplify the display if the user feels stressed).

[1056] User

[1057] The user performs the following operations:

[1058] 1. Question input: Enter a question about the product into the device using text or voice. For example, "Tell me how to use this smartphone."

[1059] 2. Check the response: Check the response from the server displayed on the terminal.

[1060] 3. Purchase decision: If there is an item you would like to add to your cart, press the "Add to cart" button.

[1061] Specific examples

[1062] Next, an embodiment of the present invention will be described with specific examples.

[1063] 1. Enter your question

[1064] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[1065] 2. Submit your question

[1066] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[1067] 3. Generative AI Processing

[1068] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. The prompt is, "The user wants to know how to use this smartphone." The response is, "To use the smartphone, power it on, then access the settings menu..."

[1069] 4. Reflecting emotional information

[1070] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[1071] 5. Data Formatting

[1072] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1073] 6. Sending and Displaying Responses

[1074] The server sends a formatted response back to the device, which displays the response in its user interface, for example, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1075] 7. Add to Cart

[1076] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1077] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[1078] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1079] Step 1: User enters question

[1080] The user enters a question into the device's input box, such as "Teach me how to use this smartphone." The user can enter the question using text or voice. The entered data is sent directly to the next step by the device.

[1081] Step 2: Submit your question

[1082] The device sends the question entered by the user to the server. At this time, the user's emotional information (e.g., facial expressions and voice data) is also sent. The device receives the question and emotional data as input and sends them to the server. As output, data to be sent to the server is generated.

[1083] Step 3: Server receives query

[1084] The server receives the question and emotion information sent from the device. It receives the data sent from the device as input and analyzes the question text and emotion data. The analyzed text data and emotion data are obtained as output.

[1085] Step 4: Generative AI generates a response

[1086] The server sends the received question text to a generative AI model (e.g., GPT-3) as a prompt. The question text is provided as input, and a response is generated by the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..." The generated response is obtained as output.

[1087] Step 5: Emotion Recognition Engine Processing

[1088] The server sends the received emotion data to the emotion recognition engine to analyze the user's emotion. The emotion data is provided as input, and emotion analysis is performed. The output is the analyzed user's emotional state (e.g., joy, surprise, stress).

[1089] Step 6: Shaping the data

[1090] The server adjusts the response from the generation AI based on the emotional information obtained from the emotion recognition engine. It receives the response sentence and emotional data as input and modifies the response according to the emotion. For example, if the user is feeling stressed, it will make the response briefer. The modified response sentence is generated as output.

[1091] Step 7: Connect to the database

[1092] The server retrieves the necessary product information and user data from the database based on data from the generative AI model and emotion engine. As input, it sends queries to retrieve product information and user attribute information and retrieves the data. As output, additional product information and links are incorporated into the response.

[1093] Step 8: Formatting the response

[1094] The server formats the final response based on the retrieved product information. As input, it receives information from multiple data sources, integrates it, and formats it in a way that is optimal for the user. As output, a formatted response is generated.

[1095] Step 9: Sending a Response

[1096] The server sends a formatted response to the terminal. It receives a formatted response as input and sends it to the terminal. As output, it gets the data sent to the terminal.

[1097] Step 10: Displaying the response on the terminal

[1098] The terminal displays the response received from the server on the user interface. As input, it receives response data from the server and displays it in a format that is easy for the user to see. As output, it provides a response display that the user can confirm.

[1099] Step 11: User Add to Cart Operation

[1100] The user presses the "Add to Cart" button for the product they wish to purchase. The appropriate "Add to Cart" button event is generated as input, and that information is sent to the next step. The output is an add-to-cart request.

[1101] Step 12: Add to Cart Processing by Server

[1102] The server receives the user's add-to-cart request and adds the product to the cart. It takes the add-to-cart request as input and updates the cart database. It generates the updated cart data and a confirmation message as output.

[1103] Step 13: Displaying the Add to Cart message on the device

[1104] The terminal receives the cart addition confirmation message from the server and displays it to the user. It receives the message from the server as input and displays it in its user interface. As output, the user sees "Product added to cart."

[1105] (Application example 2)

[1106] 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."

[1107] Conventional online shopping systems have the problem that users may feel stressed during the process of obtaining product information and making a purchase decision, resulting in a poor user experience.In addition, because they are unable to respond or operate in accordance with the user's emotions, they can be difficult to understand and use, especially for first-time users, the elderly, and people with disabilities.

[1108] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1109] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question entered by the user to the generative AI model, means for displaying the generated response to the user, means for adding an item the user wishes to purchase to a cart, means including an emotion recognition engine for recognizing the user's emotion, and means for incorporating the recognized emotion information into the response generation process. This enables responses and operations to be performed in accordance with the user's emotion, thereby providing a particularly stress-free shopping experience.

[1110] A "generative artificial intelligence model" is an artificial intelligence system that automatically generates responses based on user input.

[1111] A "question" is a text or voice input about information or knowledge that a user seeks.

[1112] A "response" is an answer to a user's question generated by a generative artificial intelligence model.

[1113] An "emotion recognition engine" is a software technology that identifies emotions from user input, facial expressions, and voice.

[1114] The "cart" refers to an area where a user temporarily stores products that they wish to purchase.

[1115] "Emotion information" is data on the user's emotions identified by the emotion recognition engine.

[1116] "Product Information" means detailed data relating to a particular product, including price, description, reviews, and images.

[1117] "Instructions" are steps or guidelines for using a product.

[1118] A "brain-controlled interface" is a technology that uses brain waves and neural signals to operate computers and devices.

[1119] A "user interface" refers to input and display means such as a screen and operation buttons that allow a user to interact with a system.

[1120] This invention is a system that combines a generative AI model to generate and display a response to a user's question, an emotion engine that recognizes the user's emotions, and a series of procedures for adding products the user wishes to purchase to their cart.

[1121] System Configuration

[1122] server

[1123] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[1124] 1. Request received:

[1125] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[1126] 2. Generative AI processing:

[1127] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[1128] 3. Emotion recognition:

[1129] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[1130] 4. Database integration:

[1131] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and incorporates it into the response.

[1132] 5. Response Generation:

[1133] The server formats the generated response and sends it back to the user or terminal.

[1134] 6. Cart Management:

[1135] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[1136] Terminal

[1137] The terminal functions as an interface with the user and has the following functions:

[1138] 1. User Interface:

[1139] It provides an interface where users can enter and submit questions, either through text input or voice input.

[1140] 2. Submit your request:

[1141] The entered question is sent to the server.

[1142] 3. Response display:

[1143] The response received from the server is displayed in the user interface.

[1144] 4. Cart function:

[1145] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[1146] 5. Emotion information display:

[1147] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[1148] User

[1149] The user performs the following operations:

[1150] 1. Enter your question:

[1151] Enter product-related questions into the device using text or voice.

[1152] For example: "Teach me how to use my new smartphone."

[1153] 2. Response confirmation:

[1154] Check the response from the server displayed on the terminal.

[1155] 3. Purchase decision:

[1156] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[1157] Specific examples

[1158] Next, an embodiment of the present invention will be described with specific examples.

[1159] 1. Enter your question:

[1160] If a user has a question about how to use their new smartphone, they can type "Teach me how to use my new smartphone" into the input box on the device. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[1161] 2. Submit your question:

[1162] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[1163] 3. Generative AI processing:

[1164] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[1165] 4. Reflecting emotional information:

[1166] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[1167] 5. Data Formatting:

[1168] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1169] 6. Sending and displaying responses:

[1170] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1171] 7. Add to Cart:

[1172] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1173] As an example, here is an example of a prompt sentence to be input to the generative AI model:

[1174] Example prompt sentence:

[1175] User input: I want to know how to use my new smartphone.

[1176] Emotion: Stress

[1177] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier and more convenient for people with disabilities and the elderly, thereby improving the user experience.

[1178] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1179] Step 1:

[1180] The user inputs a question into the device's interface. The input question can be in text or voice format. For example, the user might input "Teach me how to use my new smartphone." This is input data from the user.

[1181] Step 2:

[1182] The device receives the user's input data and first sends the data to an emotion recognition engine to analyze the user's emotions. The emotion recognition engine extracts features from the user's input (voice, text, facial expressions) and outputs an emotion label (e.g., stress, joy, etc.). In this example, we assume that the emotion label is determined to be "stress."

[1183] Step 3:

[1184] The device sends the user's input data and emotional information to the server. At this time, the input data is converted into text format, and the emotional information is sent as an emotional label. Specifically, the input data "Teach me how to use my new smartphone" and the emotional information "Stress" are sent to the server.

[1185] Step 4:

[1186] The server sends the received input data and emotion information to a generative AI model (e.g., GPT-3). The server sends the input data as a prompt to the generative AI model, which then generates a response. For example, the prompt might be "User input: I want to know how to use my new smartphone. Emotion: Stress." The generative AI model generates an answer based on this prompt and outputs the response text.

[1187] Step 5:

[1188] The server receives the generated response text, retrieves related product information (e.g., tutorial links) from the database, and adds detailed information related to the selected product from the database.

[1189] Step 6:

[1190] The server combines the generated response text with the acquired product information to generate the final response. It adjusts the response to be concise, taking into account emotional information. In this example, the final response generated is, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1191] Step 7:

[1192] The server sends the final response to the device, which displays it to the user, who can then see the answer to their question by viewing the response displayed in the device's interface.

[1193] Step 8:

[1194] If the user is satisfied with the answers and decides to purchase the product, he or she presses the "Add to Cart" button on the terminal, which sends a request to add the product to the cart from the terminal to the server.

[1195] Step 9:

[1196] The server receives the cart addition request and updates the user's cart based on the product ID and user ID. If the update is successful, the server sends a message to the terminal stating "The product has been added to the cart."

[1197] Step 10:

[1198] The terminal receives the message from the server and displays the message "The product has been added to the cart" on the user interface. The user can confirm this message and continue the purchase procedure.

[1199] The above is a specific processing flow for carrying out the present invention, which allows the user to efficiently and stress-free go from obtaining product information to deciding on a purchase.

[1200] 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.

[1201] 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.

[1202] 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.

[1203] [Third embodiment]

[1204] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1205] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1206] 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).

[1207] 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.

[1208] 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.

[1209] 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).

[1210] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1211] 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.

[1212] 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.

[1213] 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.

[1214] 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.

[1215] 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."

[1216] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for adding products that the user wishes to purchase to a cart.

[1217] System Configuration

[1218] server

[1219] The server is the core component that operates the generative artificial intelligence model. The server has the following functions:

[1220] 1. Request received:

[1221] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[1222] 2. Generative AI processing:

[1223] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[1224] 3. Database integration:

[1225] The server retrieves the necessary product information and user data from the database along with the response from the generative AI model and adds it to the response.

[1226] 4. Response generation:

[1227] The server formats the generated response and sends it back to the user or terminal.

[1228] 5. Cart Management:

[1229] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[1230] Terminal

[1231] The terminal functions as an interface with the user and has the following functions:

[1232] 1. User Interface:

[1233] It provides an interface where users can enter and submit questions, either through text input or voice input.

[1234] 2. Submit your request:

[1235] The entered question is sent to the server.

[1236] 3. Response display:

[1237] The response received from the server is displayed in the user interface.

[1238] 4. Cart function:

[1239] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[1240] User

[1241] The user performs the following operations:

[1242] 1. Enter your question:

[1243] Enter product-related questions into the device using text or voice.

[1244] For example: "Teach me how to use this smartphone."

[1245] 2. Response confirmation:

[1246] Check the response from the server displayed on the terminal.

[1247] 3. Purchase decision:

[1248] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[1249] Specific examples

[1250] Next, an embodiment of the present invention will be described with specific examples.

[1251] 1. Enter your question

[1252] If a user has a question about how to use their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[1253] 2. Submit your question

[1254] The device sends this question to the server, which receives the question and sends it to the generating AI.

[1255] 3. Generative AI Processing

[1256] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[1257] 4. Data Formatting

[1258] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1259] 5. Sending and Displaying Responses

[1260] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[1261] 6. Add to Cart

[1262] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1263] The system configured in this way allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. The system of the present invention makes it easy for people with disabilities to shop online, improving the user experience.

[1264] The processing flow will be explained below.

[1265] Step 1:

[1266] The user enters a question by text or voice into a user interface on the device.

[1267] Step 2:

[1268] The device receives the user's question and sends the question and the user's ID to the server. The data sent is often in text format, JSON.

[1269] Step 3:

[1270] The server receives the question sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[1271] Step 4:

[1272] The server sends the converted question to the generative AI model, which then generates a response based on the user's question.

[1273] Step 5:

[1274] The generation AI generates a response to the question received from the server and returns the response to the server. The generated response is created in detail based on the content of the question.

[1275] Step 6:

[1276] The server formats the response received from the generation AI, and if necessary, retrieves additional information from the database (e.g., product specifications or the user's past purchase history) and incorporates it into the response.

[1277] Step 7:

[1278] The server converts the formatted response into JSON format and sends it to the device, which includes the generated AI's response and additional information.

[1279] Step 8:

[1280] The terminal analyzes the response received from the server and displays it on the user interface. The displayed content is the answer to the question asked by the user.

[1281] Step 9:

[1282] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[1283] Step 10:

[1284] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[1285] Step 11:

[1286] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[1287] Step 12:

[1288] The server sends the cart update status (success or failure) to the device.

[1289] Step 13:

[1290] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[1291] In this way, the program's processing is clearly divided into steps, allowing users to smoothly progress from asking questions to completing the purchase process.

[1292] Example 1

[1293] 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."

[1294] Conventional online shopping systems require users to use multiple different platforms to answer questions about products and complete purchase procedures, which is time-consuming. Furthermore, the process from obtaining information to making a purchase decision is fragmented, making it difficult to improve the user experience. Furthermore, insufficient or inaccurate information can discourage users from making a purchase.

[1295] 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.

[1296] In this invention, the server includes means for receiving a user's question, means for sending the question to a generative AI model, means for generating a response from the generative AI model, means for retrieving product information and user information from a database, means for formatting the generated response, means for displaying the formatted response to the user, and means for adding products the user wishes to purchase to a cart. This allows users to complete the entire process from asking a question to completing the purchase procedure within a single platform, improving the user experience and increasing their willingness to purchase.

[1297] A "user" is an entity that uses this system to input questions, receive responses, and purchase products.

[1298] A "generative AI model" is an artificial intelligence model that receives a question from a user and generates an appropriate response to it.

[1299] The "server" is a central facility that receives user questions, sends them to the generative AI model, generates responses, connects with the database, considers the final response, and sends it to the terminal.

[1300] A "terminal" is a device that provides an interface for a user to enter questions, interact with the server, display generated responses, and add items to a cart.

[1301] A "database" is an information management system that stores information such as product information and user information, and allows the server to refer to and retrieve information as needed.

[1302] The "means for receiving a question" is a function for acquiring a question input by a user and inputting it into the server.

[1303] "Means for sending questions to the generative AI model" is a function that sends the questions received by the server to the generative AI model and obtains the response.

[1304] "Means for generating a response from a generative AI model" refers to the function of the generative AI model to create an appropriate response based on an input question.

[1305] The "means for linking with a database" is a function that enables the server to obtain additional information required for a response from a database and incorporate it into the response.

[1306] "Means for formatting responses" is a function that formats information obtained from the generative AI model and database into a format that is easy for users to view and understand.

[1307] The "means for displaying to the user" is a function for visually presenting the formatted response to the user via the terminal.

[1308] The "means for adding to cart" is a function for adding products that the user wishes to purchase to a virtual shopping cart.

[1309] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative AI model, and displays the response. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[1310] System Configuration

[1311] server

[1312] The server is the core component that operates the generative AI model and has the following functions:

[1313] 1. Request received:

[1314] The server receives a question sent from a user or a device, such as "How do I use this smartphone?"

[1315] 2. Generative AI processing:

[1316] The server sends the received question to a generative AI model (e.g., GPT-3), which generates an appropriate response based on the prompt.

[1317] 3. Database integration:

[1318] Based on the response from the generative AI model, the server retrieves additional product information and user data from the database, such as related accessory information and product page links.

[1319] 4. Response Formatting:

[1320] The server combines the acquired information with the response of the generating AI and formats it in a format that is easy for the user to understand.

[1321] 5. Send Response:

[1322] The server sends a formatted response back to the terminal for display to the user.

[1323] 6. Cart Management:

[1324] The server receives a cart add request from the user and adds the product to the user's cart.

[1325] Terminal

[1326] The terminal functions as an interface with the user. Its specific functions are as follows:

[1327] 1. User Interface:

[1328] It provides an interface for users to enter and submit questions, either by text input or by voice input.

[1329] 2. Submit your request:

[1330] The entered question is sent to the server. For example, a question such as "Teach me how to use this smartphone" is sent.

[1331] 3. Response display:

[1332] Display the response received from the server in the user interface. For example, the response might look like this: "To use your smartphone, power it on, then access the settings menu..."

[1333] 4. Cart function:

[1334] An interface is provided for users to add desired products to their cart. For example, a user can add a product to their cart by pressing an "Add to cart" button.

[1335] User

[1336] The user performs the following operations:

[1337] 1. Enter your question:

[1338] Enter a question about the product into the device using text or voice. For example, enter the question "How do I use this smartphone?"

[1339] 2. Response confirmation:

[1340] Check the response from the server that is displayed on the device, such as "To use your smartphone, turn it on, then access the settings menu..."

[1341] 3. Purchase decision:

[1342] If there is an item you would like to add to your cart, press the "Add to Cart" button. For example, if you decide to purchase a smartphone, press the "Add to Cart" button.

[1343] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision, thereby improving the user experience and increasing their willingness to buy.

[1344] Specific examples

[1345] Specific usage scenarios are shown below.

[1346] 1. Enter your question

[1347] If a user has a question about how to operate their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[1348] 2. Submit your question

[1349] The device sends this question to the server, which receives the question and sends it to the generating AI.

[1350] 3. Generative AI Processing

[1351] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[1352] 4. Data Formatting

[1353] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1354] 5. Sending and Displaying Responses

[1355] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[1356] 6. Add to Cart

[1357] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1358] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1359] The flow of this system's program processing

[1360] Step 1:

[1361] The user enters a question.

[1362] Input: The user types a question into the device using text or voice, for example, "Teach me how to use this phone."

[1363] Processing: The device receives the input and converts it to text form. If it is voice input, it converts it to text using speech recognition software (e.g., Google Speech-to-Text).

[1364] Output: A textual question is prepared on the terminal.

[1365] Step 2:

[1366] The terminal sends a question to the server.

[1367] Input: A text question entered by the user. For example, "Teach me how to use this phone."

[1368] Process: The device sends a question to the server using an HTTP request.

[1369] Output: The server receives the query.

[1370] Step 3:

[1371] The server sends the question to the generative AI model.

[1372] Input: A text question sent from the device, for example, "Teach me how to use this phone."

[1373] Processing: The server sends an API request to the generative AI model and inputs the prompt sentence into the generative AI model.

[1374] Output: The generative AI model begins processing.

[1375] Step 4:

[1376] A generative AI model generates a response.

[1377] Input: The prompt sent by the server. For example, "Teach me how to use this phone."

[1378] Processing: A generative AI model (e.g., GPT-3) generates a response based on the prompt.

[1379] Output: A response such as "To use your smartphone, power it on, then access the settings menu..." is generated and sent back to the server.

[1380] Step 5:

[1381] The server retrieves the additional information from the database.

[1382] Input: The response received from the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..."

[1383] Action: The server executes a database query to retrieve relevant product and user information.

[1384] Output: Retrieved product and user information, such as "related accessory information" and "product page link."

[1385] Step 6:

[1386] The server formats the response.

[1387] Input: The response of the generative AI model and additional information retrieved from the database.

[1388] Processing: The server combines the generated AI model's response with additional information and formats it in a user-friendly format.

[1389] Output: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]".

[1390] Step 7:

[1391] The server sends the formatted response to the terminal.

[1392] Input: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]."

[1393] Processing: The server uses the HTTP response to format the response and sends it to the terminal.

[1394] Output: The response arrives at the terminal.

[1395] Step 8:

[1396] The terminal displays the response to the user.

[1397] Input: The formatted response received from the server, for example, "To learn how to use your smartphone, power it on, then access the settings menu.... For related accessories, see the following link: [LINK]".

[1398] Processing: The terminal displays the formatted response in its user interface.

[1399] Output: The user sees the response on the screen.

[1400] Step 9:

[1401] A user adds a product to their cart.

[1402] Input: The product selected by the user to add to cart. For example, a specific smartphone.

[1403] Action: The user presses the "Add to Cart" button. The device records this action.

[1404] Output: An add to cart request is prepared on the terminal.

[1405] Step 10:

[1406] The terminal sends a cart add request to the server.

[1407] Input: User's add-to-cart request, for example, the product ID of a smartphone.

[1408] Processing: The terminal sends an add-to-cart request to the server as an HTTP request.

[1409] Output: The server receives the add to cart request.

[1410] Step 11:

[1411] The server updates the cart.

[1412] Input: User add-to-cart request, for example, smartphone product ID.

[1413] Processing: The server adds the item to the user's cart and updates the database.

[1414] Output: The cart is updated and the user sees the message "Product added to cart."

[1415] (Application example 1)

[1416] 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."

[1417] Current online shopping systems require a lot of effort for users to input questions and receive responses. Furthermore, they lack efficient methods for providing product operation instructions and detailed product information, limiting the user experience. In particular, when shopping using virtual reality (VR), users need a way to ask questions and give instructions using a natural interface, but current systems are unable to adequately address this need.

[1418] 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.

[1419] In this invention, the server includes means for generating a response to a user's question using a generative artificial intelligence model, means for transmitting the question entered by the user to the generative artificial intelligence model, and means for displaying the generated response to the user. This allows the user to obtain product information and operation instructions through natural dialogue in a virtual space. Furthermore, by including means for providing a user experience using a head-mounted display and means for converting user input into text using voice recognition, the user can enjoy virtual shopping in an intuitive and natural way. Furthermore, by simplifying the process of adding products the user wishes to purchase to their cart, the efficiency of online shopping and the user experience can be improved.

[1420] "Generative artificial intelligence models" are artificial intelligence algorithms and systems for generating responses to user questions.

[1421] "User input" refers to operations such as questions and instructions given by the user to the system.

[1422] The "server" is the central component that operates the generative AI model, receives and processes requests from users, generates responses, and interacts with the database.

[1423] A "head-mounted display" is a display device worn on the user's head, allowing them to visually experience virtual reality (VR) and augmented reality (AR).

[1424] "Speech recognition" is a technology that analyzes a user's voice and converts it into text format.

[1425] A "virtual space" is a computer-generated virtual space in which users can have an interactive experience.

[1426] A "cart" is an electronic list or function that temporarily holds items that a user wishes to purchase.

[1427] "User experience" refers to the overall feeling and impression a user gets while using a product or service.

[1428] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for a user to experience products in a virtual space and add desired products to a cart.

[1429] System Configuration

[1430] server

[1431] The server is the central component of the invention and has the following functions:

[1432] 1. Request reception: Receives a question sent by the user or device in voice or text format.

[1433] 2. Generative AI processing: The received question is sent to a generative AI model (e.g., GPT-4) to generate a response.

[1434] 3. Database integration: Retrieve the necessary product information and user data from the database and add it to the generated response.

[1435] 4. Response generation: The generated response is formatted and sent back to the user or device.

[1436] 5. Cart management: Receives cart addition requests from users and adds the corresponding products to the user's cart.

[1437] Hardware and software used

[1438] Head-mounted display (HMD): A display device that allows users to experience shopping in a virtual space.

[1439] Speech Recognition Software: Technology that converts user voice input into text, using Google Cloud Speech-to-Text as an example.

[1440] Generative AI model (GPT-4): Artificial intelligence for generating responses to user questions.

[1441] Database system: A system that holds product information and user data.

[1442] Display module: A module that visually displays the generated responses within the head-mounted display.

[1443] Specific examples

[1444] Suppose a user wears a head-mounted display and asks a voice question like this:

[1445] "Tell me the features of this red dress."

[1446] This speech is converted into text by speech recognition software, and the textual question is then sent to a server where a generative AI model (GPT-4) generates a response like this:

[1447] "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[1448] Additionally, the server retrieves additional product information from its database and includes it in the response:

[1449] "Plus, this dress is available in all sizes for 49,800 yen."

[1450] The final response is displayed on the head-mounted display, allowing the user to intuitively obtain information about the product. If the user wants to purchase the product, they can use voice commands such as "add to cart" to add the product to their cart.

[1451] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1452] Step 1:

[1453] The terminal receives the user's voice input.

[1454] Specific behavior:

[1455] The user wears a head-mounted display and utters a question by voice, such as "What are the features of this red dress?" Speech recognition software captures this and converts it into text.

[1456] input:

[1457] User voice input: "What are the features of this red dress?"

[1458] output:

[1459] Text question: "What are the features of this red dress?"

[1460] Step 2:

[1461] The device sends a textual question to the server.

[1462] Specific behavior:

[1463] The question converted into text format is sent from the terminal to the server in the form of an HTTP request or the like.

[1464] input:

[1465] Text question: "What are the features of this red dress?"

[1466] output:

[1467] Text question sent to the server

[1468] Step 3:

[1469] The server receives the question and sends it to the generative AI model.

[1470] Specific behavior:

[1471] The server sends the received question as a prompt to a generative AI model (e.g., GPT-4), which generates a response based on it.

[1472] input:

[1473] A text question sent to the server: "What are the features of this red dress?"

[1474] output:

[1475] Response text from the generative AI model: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[1476] Step 4:

[1477] The server formats the response from the generative AI model and retrieves additional information from the database to incorporate into the response.

[1478] Specific behavior:

[1479] In addition to the response obtained from the generative AI model, we retrieve detailed information about the product from the database (price, size, etc.) and add it to the response.

[1480] input:

[1481] A database containing response text from the generative AI model and product information

[1482] output:

[1483] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[1484] Step 5:

[1485] The server sends the formatted response to the terminal.

[1486] Specific behavior:

[1487] The formatted response is sent to the terminal in the form of an HTTP response or the like.

[1488] input:

[1489] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[1490] output:

[1491] The formatted response sent to the terminal

[1492] Step 6:

[1493] The terminal displays the received response on the user interface.

[1494] Specific behavior:

[1495] The terminal displays the received text on the head-mounted display so that the user can see it.

[1496] input:

[1497] The formatted response sent to the terminal

[1498] output:

[1499] The response displayed in the user interface was, "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[1500] Step 7:

[1501] The user gives the instruction to add an item to the cart.

[1502] Specific behavior:

[1503] The user speaks the command "add to cart," which is also converted into text by the speech recognition software and sent to the server.

[1504] input:

[1505] Voice input "Add to Cart"

[1506] output:

[1507] "Add to Cart" instructions converted to plain text

[1508] Step 8:

[1509] The server receives the request to add the product to the cart and adds the product to the cart.

[1510] Specific behavior:

[1511] The server updates the user's cart database based on the received request and adds the product to the cart.

[1512] input:

[1513] "Add to Cart" instructions converted to plain text

[1514] output:

[1515] The product is added to the user's cart and cart update information is generated.

[1516] Step 9:

[1517] The server notifies the terminal that the cart has been updated.

[1518] Specific behavior:

[1519] A notification that the cart has been updated is sent to the terminal in the form of an HTTP response or the like.

[1520] input:

[1521] Cart update information

[1522] output:

[1523] Cart update notifications sent to your device

[1524] Step 10:

[1525] The device displays a cart update notification to the user.

[1526] Specific behavior:

[1527] The terminal displays on the head-mounted display that the cart has been updated and provides the user with a message saying "Product added to cart."

[1528] input:

[1529] Cart update notifications sent to your device

[1530] output:

[1531] Cart update message displayed in the user interface: "Item added to cart"

[1532] The above process realizes a system that allows users to ask questions in a virtual space, receive responses using a generative AI model, and shop efficiently.

[1533] 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.

[1534] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[1535] System Configuration

[1536] server

[1537] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[1538] 1. Request received:

[1539] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[1540] 2. Generative AI processing:

[1541] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[1542] 3. Emotion recognition:

[1543] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[1544] 4. Database integration:

[1545] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and adds it to the response.

[1546] 5. Response Generation:

[1547] The server formats the generated response and sends it back to the user or terminal.

[1548] 6. Cart Management:

[1549] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[1550] Terminal

[1551] The terminal functions as an interface with the user and has the following functions:

[1552] 1. User Interface:

[1553] It provides an interface where users can enter and submit questions, either through text input or voice input.

[1554] 2. Submit your request:

[1555] The entered question is sent to the server.

[1556] 3. Response display:

[1557] The response received from the server is displayed in the user interface.

[1558] 4. Cart function:

[1559] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[1560] 5. Emotion information display:

[1561] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[1562] User

[1563] The user performs the following operations:

[1564] 1. Enter your question:

[1565] Enter product-related questions into the device using text or voice.

[1566] For example: "Teach me how to use this smartphone."

[1567] 2. Response confirmation:

[1568] Check the response from the server displayed on the terminal.

[1569] 3. Purchase decision:

[1570] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[1571] Specific examples

[1572] Next, an embodiment of the present invention will be described with specific examples.

[1573] 1. Enter your question

[1574] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[1575] 2. Submit your question

[1576] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[1577] 3. Generative AI Processing

[1578] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[1579] 4. Reflecting emotional information

[1580] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[1581] 5. Data Formatting

[1582] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1583] 6. Sending and Displaying Responses

[1584] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1585] 7. Add to Cart

[1586] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1587] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[1588] The processing flow will be explained below.

[1589] Step 1:

[1590] The user enters a question via text or voice into the device's user interface. For example, "Please tell me how to use this smartphone."

[1591] Step 2:

[1592] The device captures the user's question, as well as the user's facial expression and voice data. This data is then sent to the server. The data sent is often in text format, JSON.

[1593] Step 3:

[1594] The server receives the question and emotion data sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[1595] Step 4:

[1596] The server sends the converted question to a generative AI model (e.g., GPT-3) to generate a response. The generative AI model generates a response based on the user's question.

[1597] Step 5:

[1598] The server then sends the user's emotion data to the emotion engine, which then analyzes the user's emotion. The emotion engine then analyzes facial expressions and voice to recognize the user's emotion (e.g., surprise, joy, stress).

[1599] Step 6:

[1600] The emotion engine returns the analysis results to the server, which are provided to the server as data containing the emotions the user was feeling when entering the information.

[1601] Step 7:

[1602] The server combines the response from the generative AI model with emotional data from the emotion engine. For example, if the user is feeling stressed, it may adjust the response to be more succinct. It may also retrieve additional product information or tutorial links from the database and incorporate them into the response.

[1603] Step 8:

[1604] The server formats the final response in JSON format and sends it to the device, which includes the generative AI's response, additional information, and adjustments based on emotion recognition.

[1605] Step 9:

[1606] The device analyzes the response received from the server and displays it on the user interface. The content displayed is the answer to the question asked by the user. For example, it might say, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1607] Step 10:

[1608] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[1609] Step 11:

[1610] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[1611] Step 12:

[1612] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[1613] Step 13:

[1614] The server sends the cart update status (success or failure) to the device.

[1615] Step 14:

[1616] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[1617] In this way, the program's processing is clearly divided into steps, allowing users to smoothly proceed from inquiry to purchase. Emotion recognition makes it possible to provide optimal responses based on the user's emotions, making online shopping easier and more convenient for people with visual impairments in particular. This system aims to improve the user experience.

[1618] Example 2

[1619] 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."

[1620] In conventional online shopping systems, when users ask questions about products, they often do not receive an appropriate response, which can lead to a poor user experience. Furthermore, because the system does not take into account the user's feelings, it can be difficult to use, especially for users with disabilities. This can lead to problems such as a decrease in user satisfaction and a decrease in purchasing motivation.

[1621] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1622] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question input by the user to the generative AI model, means for recognizing the user's emotion based on the generated response, means for adjusting the response based on the recognized emotion information, means for displaying the generated response to the user, and means for adding products the user wishes to purchase to a cart. This provides an appropriate response to the user's question that takes emotion into consideration, and is easy to use, especially for users with disabilities, thereby improving the user experience and encouraging purchasing motivation.

[1623] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates responses in natural language to questions or commands entered by a user.

[1624] "User questions" are information or questions that users input to the system, including details about the product and how to use it.

[1625] An "emotion recognition engine" is an algorithm or software that analyzes user input data (voice and facial expressions) to identify the user's emotional state.

[1626] "Means for adding to cart" refers to the mechanism by which a user registers desired products in an online shopping cart.

[1627] The "database" is a repository of information that stores data from generative AI models and emotion recognition engines, product information, user data, etc.

[1628] "Means for displaying the generated response to the user" refers to a mechanism for presenting the response created by the generative artificial intelligence model on a user interface.

[1629] The "means for adjusting the response" refers to a mechanism for appropriately modifying the generated response based on the recognized emotional information of the user.

[1630] MODE FOR CARRYING OUT THE INVENTION

[1631] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[1632] System Configuration

[1633] server

[1634] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[1635] 1. Request reception: The server receives a question sent by a user or terminal. The received question can be in text or voice format.

[1636] 2. Generative AI processing: The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[1637] 3. Emotion Recognition: The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[1638] 4. Database integration: The server retrieves the necessary product information and user data from the database along with data from the generative AI model and emotion engine, and adds them to the response.

[1639] 5. Response generation: The server formats the generated response and sends it back to the user or device.

[1640] 6. Cart management: The server receives a cart addition request from the user and adds the corresponding item to the user's cart.

[1641] Terminal

[1642] The terminal functions as an interface with the user and has the following functions:

[1643] 1. User Interface: Provides an interface where users can input and submit questions. Input can be done via text input or voice input.

[1644] 2. Send request: Send the entered question to the server.

[1645] 3. Display response: Display the response received from the server in the user interface.

[1646] 4. Cart functionality: Provide an interface that allows users to add desired products to their cart (e.g., add to cart button).

[1647] 5. Emotional information display: Change the display of the user interface based on the emotional information obtained from the emotion engine (e.g., simplify the display if the user feels stressed).

[1648] User

[1649] The user performs the following operations:

[1650] 1. Question input: Enter a question about the product into the device using text or voice. For example, "Tell me how to use this smartphone."

[1651] 2. Check the response: Check the response from the server displayed on the terminal.

[1652] 3. Purchase decision: If there is an item you would like to add to your cart, press the "Add to cart" button.

[1653] Specific examples

[1654] Next, an embodiment of the present invention will be described with specific examples.

[1655] 1. Enter your question

[1656] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[1657] 2. Submit your question

[1658] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[1659] 3. Generative AI Processing

[1660] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. The prompt is, "The user wants to know how to use this smartphone." The response is, "To use the smartphone, power it on, then access the settings menu..."

[1661] 4. Reflecting emotional information

[1662] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[1663] 5. Data Formatting

[1664] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1665] 6. Sending and Displaying Responses

[1666] The server sends a formatted response back to the device, which displays the response in its user interface, for example, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1667] 7. Add to Cart

[1668] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1669] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[1670] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1671] Step 1: User enters question

[1672] The user enters a question into the device's input box, such as "Teach me how to use this smartphone." The user can enter the question using text or voice. The entered data is sent directly to the next step by the device.

[1673] Step 2: Submit your question

[1674] The device sends the question entered by the user to the server. At this time, the user's emotional information (e.g., facial expressions and voice data) is also sent. The device receives the question and emotional data as input and sends them to the server. As output, data to be sent to the server is generated.

[1675] Step 3: Server receives query

[1676] The server receives the question and emotion information sent from the device. It receives the data sent from the device as input and analyzes the question text and emotion data. The analyzed text data and emotion data are obtained as output.

[1677] Step 4: Generative AI generates a response

[1678] The server sends the received question text to a generative AI model (e.g., GPT-3) as a prompt. The question text is provided as input, and a response is generated by the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..." The generated response is obtained as output.

[1679] Step 5: Emotion Recognition Engine Processing

[1680] The server sends the received emotion data to the emotion recognition engine to analyze the user's emotion. The emotion data is provided as input, and emotion analysis is performed. The output is the analyzed user's emotional state (e.g., joy, surprise, stress).

[1681] Step 6: Shaping the data

[1682] The server adjusts the response from the generation AI based on the emotional information obtained from the emotion recognition engine. It receives the response sentence and emotional data as input and modifies the response according to the emotion. For example, if the user is feeling stressed, it will make the response briefer. The modified response sentence is generated as output.

[1683] Step 7: Connect to the database

[1684] The server retrieves the necessary product information and user data from the database based on data from the generative AI model and emotion engine. As input, it sends queries to retrieve product information and user attribute information and retrieves the data. As output, additional product information and links are incorporated into the response.

[1685] Step 8: Formatting the response

[1686] The server formats the final response based on the retrieved product information. As input, it receives information from multiple data sources, integrates it, and formats it in a way that is optimal for the user. As output, a formatted response is generated.

[1687] Step 9: Sending a Response

[1688] The server sends a formatted response to the terminal. It receives a formatted response as input and sends it to the terminal. As output, it gets the data sent to the terminal.

[1689] Step 10: Displaying the response on the terminal

[1690] The terminal displays the response received from the server on the user interface. As input, it receives response data from the server and displays it in a format that is easy for the user to see. As output, it provides a response display that the user can confirm.

[1691] Step 11: User Add to Cart Operation

[1692] The user presses the "Add to Cart" button for the product they wish to purchase. The appropriate "Add to Cart" button event is generated as input, and that information is sent to the next step. The output is an add-to-cart request.

[1693] Step 12: Add to Cart Processing by Server

[1694] The server receives the user's add-to-cart request and adds the product to the cart. It takes the add-to-cart request as input and updates the cart database. It generates the updated cart data and a confirmation message as output.

[1695] Step 13: Displaying the Add to Cart message on the device

[1696] The terminal receives the cart addition confirmation message from the server and displays it to the user. It receives the message from the server as input and displays it in its user interface. As output, the user sees "Product added to cart."

[1697] (Application example 2)

[1698] 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."

[1699] Conventional online shopping systems have the problem that users may feel stressed during the process of obtaining product information and making a purchase decision, resulting in a poor user experience.In addition, because they are unable to respond or operate in accordance with the user's emotions, they can be difficult to understand and use, especially for first-time users, the elderly, and people with disabilities.

[1700] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1701] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question entered by the user to the generative AI model, means for displaying the generated response to the user, means for adding an item the user wishes to purchase to a cart, means including an emotion recognition engine for recognizing the user's emotion, and means for incorporating the recognized emotion information into the response generation process. This enables responses and operations to be performed in accordance with the user's emotion, thereby providing a particularly stress-free shopping experience.

[1702] A "generative artificial intelligence model" is an artificial intelligence system that automatically generates responses based on user input.

[1703] A "question" is a text or voice input about information or knowledge that a user seeks.

[1704] A "response" is an answer to a user's question generated by a generative artificial intelligence model.

[1705] An "emotion recognition engine" is a software technology that identifies emotions from user input, facial expressions, and voice.

[1706] The "cart" refers to an area where a user temporarily stores products that they wish to purchase.

[1707] "Emotion information" is data on the user's emotions identified by the emotion recognition engine.

[1708] "Product Information" means detailed data relating to a particular product, including price, description, reviews, and images.

[1709] "Instructions" are steps or guidelines for using a product.

[1710] A "brain-controlled interface" is a technology that uses brain waves and neural signals to operate computers and devices.

[1711] A "user interface" refers to input and display means such as a screen and operation buttons that allow a user to interact with a system.

[1712] This invention is a system that combines a generative AI model to generate and display a response to a user's question, an emotion engine that recognizes the user's emotions, and a series of procedures for adding products the user wishes to purchase to their cart.

[1713] System Configuration

[1714] server

[1715] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[1716] 1. Request received:

[1717] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[1718] 2. Generative AI processing:

[1719] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[1720] 3. Emotion recognition:

[1721] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[1722] 4. Database integration:

[1723] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and incorporates it into the response.

[1724] 5. Response Generation:

[1725] The server formats the generated response and sends it back to the user or terminal.

[1726] 6. Cart Management:

[1727] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[1728] Terminal

[1729] The terminal functions as an interface with the user and has the following functions:

[1730] 1. User Interface:

[1731] It provides an interface where users can enter and submit questions, either through text input or voice input.

[1732] 2. Submit your request:

[1733] The entered question is sent to the server.

[1734] 3. Response display:

[1735] The response received from the server is displayed in the user interface.

[1736] 4. Cart function:

[1737] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[1738] 5. Emotion information display:

[1739] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[1740] User

[1741] The user performs the following operations:

[1742] 1. Enter your question:

[1743] Enter product-related questions into the device using text or voice.

[1744] For example: "Teach me how to use my new smartphone."

[1745] 2. Response confirmation:

[1746] Check the response from the server displayed on the terminal.

[1747] 3. Purchase decision:

[1748] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[1749] Specific examples

[1750] Next, an embodiment of the present invention will be described with specific examples.

[1751] 1. Enter your question:

[1752] If a user has a question about how to use their new smartphone, they can type "Teach me how to use my new smartphone" into the input box on the device. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[1753] 2. Submit your question:

[1754] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[1755] 3. Generative AI processing:

[1756] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[1757] 4. Reflecting emotional information:

[1758] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[1759] 5. Data Formatting:

[1760] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1761] 6. Sending and displaying responses:

[1762] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1763] 7. Add to Cart:

[1764] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1765] As an example, here is an example of a prompt sentence to be input to the generative AI model:

[1766] Example prompt sentence:

[1767] User input: I want to know how to use my new smartphone.

[1768] Emotion: Stress

[1769] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier and more convenient for people with disabilities and the elderly, thereby improving the user experience.

[1770] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1771] Step 1:

[1772] The user inputs a question into the device's interface. The input question can be in text or voice format. For example, the user might input "Teach me how to use my new smartphone." This is input data from the user.

[1773] Step 2:

[1774] The device receives the user's input data and first sends the data to an emotion recognition engine to analyze the user's emotions. The emotion recognition engine extracts features from the user's input (voice, text, facial expressions) and outputs an emotion label (e.g., stress, joy, etc.). In this example, we assume that the emotion label is determined to be "stress."

[1775] Step 3:

[1776] The device sends the user's input data and emotional information to the server. At this time, the input data is converted into text format, and the emotional information is sent as an emotional label. Specifically, the input data "Teach me how to use my new smartphone" and the emotional information "Stress" are sent to the server.

[1777] Step 4:

[1778] The server sends the received input data and emotion information to a generative AI model (e.g., GPT-3). The server sends the input data as a prompt to the generative AI model, which then generates a response. For example, the prompt might be "User input: I want to know how to use my new smartphone. Emotion: Stress." The generative AI model generates an answer based on this prompt and outputs the response text.

[1779] Step 5:

[1780] The server receives the generated response text, retrieves related product information (e.g., tutorial links) from the database, and adds detailed information related to the selected product from the database.

[1781] Step 6:

[1782] The server combines the generated response text with the acquired product information to generate the final response. It adjusts the response to be concise, taking into account emotional information. In this example, the final response generated is, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[1783] Step 7:

[1784] The server sends the final response to the device, which displays it to the user, who can then see the answer to their question by viewing the response displayed in the device's interface.

[1785] Step 8:

[1786] If the user is satisfied with the answers and decides to purchase the product, he or she presses the "Add to Cart" button on the terminal, which sends a request to add the product to the cart from the terminal to the server.

[1787] Step 9:

[1788] The server receives the cart addition request and updates the user's cart based on the product ID and user ID. If the update is successful, the server sends a message to the terminal stating "The product has been added to the cart."

[1789] Step 10:

[1790] The terminal receives the message from the server and displays the message "The product has been added to the cart" on the user interface. The user can confirm this message and continue the purchase procedure.

[1791] The above is a specific processing flow for carrying out the present invention, which allows the user to efficiently and stress-free go from obtaining product information to deciding on a purchase.

[1792] 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.

[1793] 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.

[1794] 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.

[1795] [Fourth embodiment]

[1796] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1797] 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.

[1798] 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).

[1799] 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.

[1800] 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.

[1801] 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).

[1802] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1803] 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.

[1804] 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.

[1805] 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.

[1806] 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.

[1807] 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.

[1808] 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."

[1809] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for adding products that the user wishes to purchase to a cart.

[1810] System Configuration

[1811] server

[1812] The server is the core component that operates the generative artificial intelligence model. The server has the following functions:

[1813] 1. Request received:

[1814] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[1815] 2. Generative AI processing:

[1816] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[1817] 3. Database integration:

[1818] The server retrieves the necessary product information and user data from the database along with the response from the generative AI model and adds it to the response.

[1819] 4. Response generation:

[1820] The server formats the generated response and sends it back to the user or terminal.

[1821] 5. Cart Management:

[1822] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[1823] Terminal

[1824] The terminal functions as an interface with the user and has the following functions:

[1825] 1. User Interface:

[1826] It provides an interface where users can enter and submit questions, either through text input or voice input.

[1827] 2. Submit your request:

[1828] The entered question is sent to the server.

[1829] 3. Response display:

[1830] The response received from the server is displayed in the user interface.

[1831] 4. Cart function:

[1832] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[1833] User

[1834] The user performs the following operations:

[1835] 1. Enter your question:

[1836] Enter product-related questions into the device using text or voice.

[1837] For example: "Teach me how to use this smartphone."

[1838] 2. Response confirmation:

[1839] Check the response from the server displayed on the terminal.

[1840] 3. Purchase decision:

[1841] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[1842] Specific examples

[1843] Next, an embodiment of the present invention will be described with specific examples.

[1844] 1. Enter your question

[1845] If a user has a question about how to use their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[1846] 2. Submit your question

[1847] The device sends this question to the server, which receives the question and sends it to the generating AI.

[1848] 3. Generative AI Processing

[1849] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[1850] 4. Data Formatting

[1851] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1852] 5. Sending and Displaying Responses

[1853] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[1854] 6. Add to Cart

[1855] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1856] The system configured in this way allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. The system of the present invention makes it easy for people with disabilities to shop online, improving the user experience.

[1857] The processing flow will be explained below.

[1858] Step 1:

[1859] The user enters a question by text or voice into a user interface on the device.

[1860] Step 2:

[1861] The device receives the user's question and sends the question and the user's ID to the server. The data sent is often in text format, JSON.

[1862] Step 3:

[1863] The server receives the question sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[1864] Step 4:

[1865] The server sends the converted question to the generative AI model, which then generates a response based on the user's question.

[1866] Step 5:

[1867] The generation AI generates a response to the question received from the server and returns the response to the server. The generated response is created in detail based on the content of the question.

[1868] Step 6:

[1869] The server formats the response received from the generation AI, and if necessary, retrieves additional information from the database (e.g., product specifications or the user's past purchase history) and incorporates it into the response.

[1870] Step 7:

[1871] The server converts the formatted response into JSON format and sends it to the device, which includes the generated AI's response and additional information.

[1872] Step 8:

[1873] The terminal analyzes the response received from the server and displays it on the user interface. The displayed content is the answer to the question asked by the user.

[1874] Step 9:

[1875] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[1876] Step 10:

[1877] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[1878] Step 11:

[1879] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[1880] Step 12:

[1881] The server sends the cart update status (success or failure) to the device.

[1882] Step 13:

[1883] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[1884] In this way, the program's processing is clearly divided into steps, allowing users to smoothly progress from asking questions to completing the purchase process.

[1885] Example 1

[1886] 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."

[1887] Conventional online shopping systems require users to use multiple different platforms to answer questions about products and complete purchase procedures, which is time-consuming. Furthermore, the process from obtaining information to making a purchase decision is fragmented, making it difficult to improve the user experience. Furthermore, insufficient or inaccurate information can discourage users from making a purchase.

[1888] 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.

[1889] In this invention, the server includes means for receiving a user's question, means for sending the question to a generative AI model, means for generating a response from the generative AI model, means for retrieving product information and user information from a database, means for formatting the generated response, means for displaying the formatted response to the user, and means for adding products the user wishes to purchase to a cart. This allows users to complete the entire process from asking a question to completing the purchase procedure within a single platform, improving the user experience and increasing their willingness to purchase.

[1890] A "user" is an entity that uses this system to input questions, receive responses, and purchase products.

[1891] A "generative AI model" is an artificial intelligence model that receives a question from a user and generates an appropriate response to it.

[1892] The "server" is a central facility that receives user questions, sends them to the generative AI model, generates responses, connects with the database, considers the final response, and sends it to the terminal.

[1893] A "terminal" is a device that provides an interface for a user to enter questions, interact with the server, display generated responses, and add items to a cart.

[1894] A "database" is an information management system that stores information such as product information and user information, and allows the server to refer to and retrieve information as needed.

[1895] The "means for receiving a question" is a function for acquiring a question input by a user and inputting it into the server.

[1896] "Means for sending questions to the generative AI model" is a function that sends the questions received by the server to the generative AI model and obtains the response.

[1897] "Means for generating a response from a generative AI model" refers to the function of the generative AI model to create an appropriate response based on an input question.

[1898] The "means for linking with a database" is a function that enables the server to obtain additional information required for a response from a database and incorporate it into the response.

[1899] "Means for formatting responses" is a function that formats information obtained from the generative AI model and database into a format that is easy for users to view and understand.

[1900] The "means for displaying to the user" is a function for visually presenting the formatted response to the user via the terminal.

[1901] The "means for adding to cart" is a function for adding products that the user wishes to purchase to a virtual shopping cart.

[1902] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative AI model, and displays the response. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[1903] System Configuration

[1904] server

[1905] The server is the core component that operates the generative AI model and has the following functions:

[1906] 1. Request received:

[1907] The server receives a question sent from a user or a device, such as "How do I use this smartphone?"

[1908] 2. Generative AI processing:

[1909] The server sends the received question to a generative AI model (e.g., GPT-3), which generates an appropriate response based on the prompt.

[1910] 3. Database integration:

[1911] Based on the response from the generative AI model, the server retrieves additional product information and user data from the database, such as related accessory information and product page links.

[1912] 4. Response Formatting:

[1913] The server combines the acquired information with the response of the generating AI and formats it in a format that is easy for the user to understand.

[1914] 5. Send Response:

[1915] The server sends a formatted response back to the terminal for display to the user.

[1916] 6. Cart Management:

[1917] The server receives a cart add request from the user and adds the product to the user's cart.

[1918] Terminal

[1919] The terminal functions as an interface with the user. Its specific functions are as follows:

[1920] 1. User Interface:

[1921] It provides an interface for users to enter and submit questions, either by text input or by voice input.

[1922] 2. Submit your request:

[1923] The entered question is sent to the server. For example, a question such as "Teach me how to use this smartphone" is sent.

[1924] 3. Response display:

[1925] Display the response received from the server in the user interface. For example, the response might look like this: "To use your smartphone, power it on, then access the settings menu..."

[1926] 4. Cart function:

[1927] An interface is provided for users to add desired products to their cart. For example, a user can add a product to their cart by pressing an "Add to cart" button.

[1928] User

[1929] The user performs the following operations:

[1930] 1. Enter your question:

[1931] Enter a question about the product into the device using text or voice. For example, enter the question "How do I use this smartphone?"

[1932] 2. Response confirmation:

[1933] Check the response from the server that is displayed on the device, such as "To use your smartphone, turn it on, then access the settings menu..."

[1934] 3. Purchase decision:

[1935] If there is an item you would like to add to your cart, press the "Add to Cart" button. For example, if you decide to purchase a smartphone, press the "Add to Cart" button.

[1936] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision, thereby improving the user experience and increasing their willingness to buy.

[1937] Specific examples

[1938] Specific usage scenarios are shown below.

[1939] 1. Enter your question

[1940] If a user has a question about how to operate their new smartphone, they type "Teach me how to use this smartphone" into the device's input box.

[1941] 2. Submit your question

[1942] The device sends this question to the server, which receives the question and sends it to the generating AI.

[1943] 3. Generative AI Processing

[1944] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[1945] 4. Data Formatting

[1946] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[1947] 5. Sending and Displaying Responses

[1948] The server sends a formatted response back to the terminal, which displays the response in its user interface.

[1949] 6. Add to Cart

[1950] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[1951] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1952] The flow of this system's program processing

[1953] Step 1:

[1954] The user enters a question.

[1955] Input: The user types a question into the device using text or voice, for example, "Teach me how to use this phone."

[1956] Processing: The device receives the input and converts it to text form. If it is voice input, it converts it to text using speech recognition software (e.g., Google Speech-to-Text).

[1957] Output: A textual question is prepared on the terminal.

[1958] Step 2:

[1959] The terminal sends a question to the server.

[1960] Input: A text question entered by the user. For example, "Teach me how to use this phone."

[1961] Process: The device sends a question to the server using an HTTP request.

[1962] Output: The server receives the query.

[1963] Step 3:

[1964] The server sends the question to the generative AI model.

[1965] Input: A text question sent from the device, for example, "Teach me how to use this phone."

[1966] Processing: The server sends an API request to the generative AI model and inputs the prompt sentence into the generative AI model.

[1967] Output: The generative AI model begins processing.

[1968] Step 4:

[1969] A generative AI model generates a response.

[1970] Input: The prompt sent by the server. For example, "Teach me how to use this phone."

[1971] Processing: A generative AI model (e.g., GPT-3) generates a response based on the prompt.

[1972] Output: A response such as "To use your smartphone, power it on, then access the settings menu..." is generated and sent back to the server.

[1973] Step 5:

[1974] The server retrieves the additional information from the database.

[1975] Input: The response received from the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..."

[1976] Action: The server executes a database query to retrieve relevant product and user information.

[1977] Output: Retrieved product and user information, such as "related accessory information" and "product page link."

[1978] Step 6:

[1979] The server formats the response.

[1980] Input: The response of the generative AI model and additional information retrieved from the database.

[1981] Processing: The server combines the generated AI model's response with additional information and formats it in a user-friendly format.

[1982] Output: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]".

[1983] Step 7:

[1984] The server sends the formatted response to the terminal.

[1985] Input: A formatted response, for example, "To use your phone, power it on, then access the settings menu... For related accessories, see: [LINK]."

[1986] Processing: The server uses the HTTP response to format the response and sends it to the terminal.

[1987] Output: The response arrives at the terminal.

[1988] Step 8:

[1989] The terminal displays the response to the user.

[1990] Input: The formatted response received from the server, for example, "To learn how to use your smartphone, power it on, then access the settings menu.... For related accessories, see the following link: [LINK]".

[1991] Processing: The terminal displays the formatted response in its user interface.

[1992] Output: The user sees the response on the screen.

[1993] Step 9:

[1994] A user adds a product to their cart.

[1995] Input: The product selected by the user to add to cart. For example, a specific smartphone.

[1996] Action: The user presses the "Add to Cart" button. The device records this action.

[1997] Output: An add to cart request is prepared on the terminal.

[1998] Step 10:

[1999] The terminal sends a cart add request to the server.

[2000] Input: User's add-to-cart request, for example, the product ID of a smartphone.

[2001] Processing: The terminal sends an add-to-cart request to the server as an HTTP request.

[2002] Output: The server receives the add to cart request.

[2003] Step 11:

[2004] The server updates the cart.

[2005] Input: User add-to-cart request, for example, smartphone product ID.

[2006] Processing: The server adds the item to the user's cart and updates the database.

[2007] Output: The cart is updated and the user sees the message "Product added to cart."

[2008] (Application example 1)

[2009] 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."

[2010] Current online shopping systems require a lot of effort for users to input questions and receive responses. Furthermore, they lack efficient methods for providing product operation instructions and detailed product information, limiting the user experience. In particular, when shopping using virtual reality (VR), users need a way to ask questions and give instructions using a natural interface, but current systems are unable to adequately address this need.

[2011] 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.

[2012] In this invention, the server includes means for generating a response to a user's question using a generative artificial intelligence model, means for transmitting the question entered by the user to the generative artificial intelligence model, and means for displaying the generated response to the user. This allows the user to obtain product information and operation instructions through natural dialogue in a virtual space. Furthermore, by including means for providing a user experience using a head-mounted display and means for converting user input into text using voice recognition, the user can enjoy virtual shopping in an intuitive and natural way. Furthermore, by simplifying the process of adding products the user wishes to purchase to their cart, the efficiency of online shopping and the user experience can be improved.

[2013] "Generative artificial intelligence models" are artificial intelligence algorithms and systems for generating responses to user questions.

[2014] "User input" refers to operations such as questions and instructions given by the user to the system.

[2015] The "server" is the central component that operates the generative AI model, receives and processes requests from users, generates responses, and interacts with the database.

[2016] A "head-mounted display" is a display device worn on the user's head, allowing them to visually experience virtual reality (VR) and augmented reality (AR).

[2017] "Speech recognition" is a technology that analyzes a user's voice and converts it into text format.

[2018] A "virtual space" is a computer-generated virtual space in which users can have an interactive experience.

[2019] A "cart" is an electronic list or function that temporarily holds items that a user wishes to purchase.

[2020] "User experience" refers to the overall feeling and impression a user gets while using a product or service.

[2021] The present invention relates to a system that allows a user to input a question, generates a response to the question using a generative artificial intelligence model, and displays the response. It also includes a series of procedures for a user to experience products in a virtual space and add desired products to a cart.

[2022] System Configuration

[2023] server

[2024] The server is the central component of the invention and has the following functions:

[2025] 1. Request reception: Receives a question sent by the user or device in voice or text format.

[2026] 2. Generative AI processing: The received question is sent to a generative AI model (e.g., GPT-4) to generate a response.

[2027] 3. Database integration: Retrieve the necessary product information and user data from the database and add it to the generated response.

[2028] 4. Response generation: The generated response is formatted and sent back to the user or device.

[2029] 5. Cart management: Receives cart addition requests from users and adds the corresponding products to the user's cart.

[2030] Hardware and software used

[2031] Head-mounted display (HMD): A display device that allows users to experience shopping in a virtual space.

[2032] Speech Recognition Software: Technology that converts user voice input into text, using Google Cloud Speech-to-Text as an example.

[2033] Generative AI model (GPT-4): Artificial intelligence for generating responses to user questions.

[2034] Database system: A system that holds product information and user data.

[2035] Display module: A module that visually displays the generated responses within the head-mounted display.

[2036] Specific examples

[2037] Suppose a user wears a head-mounted display and asks a voice question like this:

[2038] "Tell me the features of this red dress."

[2039] This speech is converted into text by speech recognition software, and the textual question is then sent to a server where a generative AI model (GPT-4) generates a response like this:

[2040] "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[2041] Additionally, the server retrieves additional product information from its database and includes it in the response:

[2042] "Plus, this dress is available in all sizes for 49,800 yen."

[2043] The final response is displayed on the head-mounted display, allowing the user to intuitively obtain information about the product. If the user wants to purchase the product, they can use voice commands such as "add to cart" to add the product to their cart.

[2044] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2045] Step 1:

[2046] The terminal receives the user's voice input.

[2047] Specific behavior:

[2048] The user wears a head-mounted display and utters a question by voice, such as "What are the features of this red dress?" Speech recognition software captures this and converts it into text.

[2049] input:

[2050] User voice input: "What are the features of this red dress?"

[2051] output:

[2052] Text question: "What are the features of this red dress?"

[2053] Step 2:

[2054] The device sends a textual question to the server.

[2055] Specific behavior:

[2056] The question converted into text format is sent from the terminal to the server in the form of an HTTP request or the like.

[2057] input:

[2058] Text question: "What are the features of this red dress?"

[2059] output:

[2060] Text question sent to the server

[2061] Step 3:

[2062] The server receives the question and sends it to the generative AI model.

[2063] Specific behavior:

[2064] The server sends the received question as a prompt to a generative AI model (e.g., GPT-4), which generates a response based on it.

[2065] input:

[2066] A text question sent to the server: "What are the features of this red dress?"

[2067] output:

[2068] Response text from the generative AI model: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace."

[2069] Step 4:

[2070] The server formats the response from the generative AI model and retrieves additional information from the database to incorporate into the response.

[2071] Specific behavior:

[2072] In addition to the response obtained from the generative AI model, we retrieve detailed information about the product from the database (price, size, etc.) and add it to the response.

[2073] input:

[2074] A database containing response text from the generative AI model and product information

[2075] output:

[2076] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[2077] Step 5:

[2078] The server sends the formatted response to the terminal.

[2079] Specific behavior:

[2080] The formatted response is sent to the terminal in the form of an HTTP response or the like.

[2081] input:

[2082] Formatted Response: "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[2083] output:

[2084] The formatted response sent to the terminal

[2085] Step 6:

[2086] The terminal displays the received response on the user interface.

[2087] Specific behavior:

[2088] The terminal displays the received text on the head-mounted display so that the user can see it.

[2089] input:

[2090] The formatted response sent to the terminal

[2091] output:

[2092] The response displayed in the user interface was, "This red dress is made of silk and features an elegant design. The design especially features vintage-inspired lace. Furthermore, this dress is available in all sizes for 49,800 yen."

[2093] Step 7:

[2094] The user gives the instruction to add an item to the cart.

[2095] Specific behavior:

[2096] The user speaks the command "add to cart," which is also converted into text by the speech recognition software and sent to the server.

[2097] input:

[2098] Voice input "Add to Cart"

[2099] output:

[2100] "Add to Cart" instructions converted to plain text

[2101] Step 8:

[2102] The server receives the request to add the product to the cart and adds the product to the cart.

[2103] Specific behavior:

[2104] The server updates the user's cart database based on the received request and adds the product to the cart.

[2105] input:

[2106] "Add to Cart" instructions converted to plain text

[2107] output:

[2108] The product is added to the user's cart and cart update information is generated.

[2109] Step 9:

[2110] The server notifies the terminal that the cart has been updated.

[2111] Specific behavior:

[2112] A notification that the cart has been updated is sent to the terminal in the form of an HTTP response or the like.

[2113] input:

[2114] Cart update information

[2115] output:

[2116] Cart update notifications sent to your device

[2117] Step 10:

[2118] The device displays a cart update notification to the user.

[2119] Specific behavior:

[2120] The terminal displays on the head-mounted display that the cart has been updated and provides the user with a message saying "Product added to cart."

[2121] input:

[2122] Cart update notifications sent to your device

[2123] output:

[2124] Cart update message displayed in the user interface: "Item added to cart"

[2125] The above process realizes a system that allows users to ask questions in a virtual space, receive responses using a generative AI model, and shop efficiently.

[2126] 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.

[2127] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[2128] System Configuration

[2129] server

[2130] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[2131] 1. Request received:

[2132] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[2133] 2. Generative AI processing:

[2134] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[2135] 3. Emotion recognition:

[2136] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[2137] 4. Database integration:

[2138] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and adds it to the response.

[2139] 5. Response Generation:

[2140] The server formats the generated response and sends it back to the user or terminal.

[2141] 6. Cart Management:

[2142] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[2143] Terminal

[2144] The terminal functions as an interface with the user and has the following functions:

[2145] 1. User Interface:

[2146] It provides an interface where users can enter and submit questions, either through text input or voice input.

[2147] 2. Submit your request:

[2148] The entered question is sent to the server.

[2149] 3. Response display:

[2150] The response received from the server is displayed in the user interface.

[2151] 4. Cart function:

[2152] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[2153] 5. Emotion information display:

[2154] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[2155] User

[2156] The user performs the following operations:

[2157] 1. Enter your question:

[2158] Enter product-related questions into the device using text or voice.

[2159] For example: "Teach me how to use this smartphone."

[2160] 2. Response confirmation:

[2161] Check the response from the server displayed on the terminal.

[2162] 3. Purchase decision:

[2163] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[2164] Specific examples

[2165] Next, an embodiment of the present invention will be described with specific examples.

[2166] 1. Enter your question

[2167] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[2168] 2. Submit your question

[2169] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[2170] 3. Generative AI Processing

[2171] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[2172] 4. Reflecting emotional information

[2173] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[2174] 5. Data Formatting

[2175] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[2176] 6. Sending and Displaying Responses

[2177] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[2178] 7. Add to Cart

[2179] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[2180] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[2181] The processing flow will be explained below.

[2182] Step 1:

[2183] The user enters a question via text or voice into the device's user interface. For example, "Please tell me how to use this smartphone."

[2184] Step 2:

[2185] The device captures the user's question, as well as the user's facial expression and voice data. This data is then sent to the server. The data sent is often in text format, JSON.

[2186] Step 3:

[2187] The server receives the question and emotion data sent from the device, analyzes the received data, and converts it into a format (e.g., text) suitable for the generative AI model.

[2188] Step 4:

[2189] The server sends the converted question to a generative AI model (e.g., GPT-3) to generate a response. The generative AI model generates a response based on the user's question.

[2190] Step 5:

[2191] The server then sends the user's emotion data to the emotion engine, which then analyzes the user's emotion. The emotion engine then analyzes facial expressions and voice to recognize the user's emotion (e.g., surprise, joy, stress).

[2192] Step 6:

[2193] The emotion engine returns the analysis results to the server, which are provided to the server as data containing the emotions the user was feeling when entering the information.

[2194] Step 7:

[2195] The server combines the response from the generative AI model with emotional data from the emotion engine. For example, if the user is feeling stressed, it may adjust the response to be more succinct. It may also retrieve additional product information or tutorial links from the database and incorporate them into the response.

[2196] Step 8:

[2197] The server formats the final response in JSON format and sends it to the device, which includes the generative AI's response, additional information, and adjustments based on emotion recognition.

[2198] Step 9:

[2199] The device analyzes the response received from the server and displays it on the user interface. The content displayed is the answer to the question asked by the user. For example, it might say, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[2200] Step 10:

[2201] The user checks the displayed information and decides whether to purchase the product. If they decide to purchase, they press the "Add to Cart" button.

[2202] Step 11:

[2203] The device sends an "add to cart" request to the server, which includes the user's ID and the product ID.

[2204] Step 12:

[2205] The server receives the "add to cart" request, updates the database to add the product to the user's cart, and checks whether the update was successful.

[2206] Step 13:

[2207] The server sends the cart update status (success or failure) to the device.

[2208] Step 14:

[2209] The terminal displays the cart update status received from the server in the user interface, with a success message such as "Product added to cart."

[2210] In this way, the program's processing is clearly divided into steps, allowing users to smoothly proceed from inquiry to purchase. Emotion recognition makes it possible to provide optimal responses based on the user's emotions, making online shopping easier and more convenient for people with visual impairments in particular. This system aims to improve the user experience.

[2211] Example 2

[2212] 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."

[2213] In conventional online shopping systems, when users ask questions about products, they often do not receive an appropriate response, which can lead to a poor user experience. Furthermore, because the system does not take into account the user's feelings, it can be difficult to use, especially for users with disabilities. This can lead to problems such as a decrease in user satisfaction and a decrease in purchasing motivation.

[2214] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2215] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question input by the user to the generative AI model, means for recognizing the user's emotion based on the generated response, means for adjusting the response based on the recognized emotion information, means for displaying the generated response to the user, and means for adding products the user wishes to purchase to a cart. This provides an appropriate response to the user's question that takes emotion into consideration, and is easy to use, especially for users with disabilities, thereby improving the user experience and encouraging purchasing motivation.

[2216] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates responses in natural language to questions or commands entered by a user.

[2217] "User questions" are information or questions that users input to the system, including details about the product and how to use it.

[2218] An "emotion recognition engine" is an algorithm or software that analyzes user input data (voice and facial expressions) to identify the user's emotional state.

[2219] "Means for adding to cart" refers to the mechanism by which a user registers desired products in an online shopping cart.

[2220] The "database" is a repository of information that stores data from generative AI models and emotion recognition engines, product information, user data, etc.

[2221] "Means for displaying the generated response to the user" refers to a mechanism for presenting the response created by the generative artificial intelligence model on a user interface.

[2222] The "means for adjusting the response" refers to a mechanism for appropriately modifying the generated response based on the recognized emotional information of the user.

[2223] MODE FOR CARRYING OUT THE INVENTION

[2224] The present invention is a system that allows a user to input a question, generates and displays a response to the question using a generative AI model, and combines it with an emotion engine that recognizes the user's emotions. It also includes a series of procedures for adding products the user wishes to purchase to their cart.

[2225] System Configuration

[2226] server

[2227] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[2228] 1. Request reception: The server receives a question sent by a user or terminal. The received question can be in text or voice format.

[2229] 2. Generative AI processing: The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[2230] 3. Emotion Recognition: The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[2231] 4. Database integration: The server retrieves the necessary product information and user data from the database along with data from the generative AI model and emotion engine, and adds them to the response.

[2232] 5. Response generation: The server formats the generated response and sends it back to the user or device.

[2233] 6. Cart management: The server receives a cart addition request from the user and adds the corresponding item to the user's cart.

[2234] Terminal

[2235] The terminal functions as an interface with the user and has the following functions:

[2236] 1. User Interface: Provides an interface where users can input and submit questions. Input can be done via text input or voice input.

[2237] 2. Send request: Send the entered question to the server.

[2238] 3. Display response: Display the response received from the server in the user interface.

[2239] 4. Cart functionality: Provide an interface that allows users to add desired products to their cart (e.g., add to cart button).

[2240] 5. Emotional information display: Change the display of the user interface based on the emotional information obtained from the emotion engine (e.g., simplify the display if the user feels stressed).

[2241] User

[2242] The user performs the following operations:

[2243] 1. Question input: Enter a question about the product into the device using text or voice. For example, "Tell me how to use this smartphone."

[2244] 2. Check the response: Check the response from the server displayed on the terminal.

[2245] 3. Purchase decision: If there is an item you would like to add to your cart, press the "Add to cart" button.

[2246] Specific examples

[2247] Next, an embodiment of the present invention will be described with specific examples.

[2248] 1. Enter your question

[2249] If a user has a question about how to use a new smartphone, they can type "Teach me how to use this smartphone" into the device's input box. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[2250] 2. Submit your question

[2251] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[2252] 3. Generative AI Processing

[2253] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. The prompt is, "The user wants to know how to use this smartphone." The response is, "To use the smartphone, power it on, then access the settings menu..."

[2254] 4. Reflecting emotional information

[2255] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[2256] 5. Data Formatting

[2257] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[2258] 6. Sending and Displaying Responses

[2259] The server sends a formatted response back to the device, which displays the response in its user interface, for example, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[2260] 7. Add to Cart

[2261] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[2262] With a system configured in this way, users can efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier for people with disabilities in particular, and improving the user experience.

[2263] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2264] Step 1: User enters question

[2265] The user enters a question into the device's input box, such as "Teach me how to use this smartphone." The user can enter the question using text or voice. The entered data is sent directly to the next step by the device.

[2266] Step 2: Submit your question

[2267] The device sends the question entered by the user to the server. At this time, the user's emotional information (e.g., facial expressions and voice data) is also sent. The device receives the question and emotional data as input and sends them to the server. As output, data to be sent to the server is generated.

[2268] Step 3: Server receives query

[2269] The server receives the question and emotion information sent from the device. It receives the data sent from the device as input and analyzes the question text and emotion data. The analyzed text data and emotion data are obtained as output.

[2270] Step 4: Generative AI generates a response

[2271] The server sends the received question text to a generative AI model (e.g., GPT-3) as a prompt. The question text is provided as input, and a response is generated by the generative AI model. For example, "To use your smartphone, turn it on, then access the settings menu..." The generated response is obtained as output.

[2272] Step 5: Emotion Recognition Engine Processing

[2273] The server sends the received emotion data to the emotion recognition engine to analyze the user's emotion. The emotion data is provided as input, and emotion analysis is performed. The output is the analyzed user's emotional state (e.g., joy, surprise, stress).

[2274] Step 6: Shaping the data

[2275] The server adjusts the response from the generation AI based on the emotional information obtained from the emotion recognition engine. It receives the response sentence and emotional data as input and modifies the response according to the emotion. For example, if the user is feeling stressed, it will make the response briefer. The modified response sentence is generated as output.

[2276] Step 7: Connect to the database

[2277] The server retrieves the necessary product information and user data from the database based on data from the generative AI model and emotion engine. As input, it sends queries to retrieve product information and user attribute information and retrieves the data. As output, additional product information and links are incorporated into the response.

[2278] Step 8: Formatting the response

[2279] The server formats the final response based on the retrieved product information. As input, it receives information from multiple data sources, integrates it, and formats it in a way that is optimal for the user. As output, a formatted response is generated.

[2280] Step 9: Sending a Response

[2281] The server sends a formatted response to the terminal. It receives a formatted response as input and sends it to the terminal. As output, it gets the data sent to the terminal.

[2282] Step 10: Displaying the response on the terminal

[2283] The terminal displays the response received from the server on the user interface. As input, it receives response data from the server and displays it in a format that is easy for the user to see. As output, it provides a response display that the user can confirm.

[2284] Step 11: User Add to Cart Operation

[2285] The user presses the "Add to Cart" button for the product they wish to purchase. The appropriate "Add to Cart" button event is generated as input, and that information is sent to the next step. The output is an add-to-cart request.

[2286] Step 12: Add to Cart Processing by Server

[2287] The server receives the user's add-to-cart request and adds the product to the cart. It takes the add-to-cart request as input and updates the cart database. It generates the updated cart data and a confirmation message as output.

[2288] Step 13: Displaying the Add to Cart message on the device

[2289] The terminal receives the cart addition confirmation message from the server and displays it to the user. It receives the message from the server as input and displays it in its user interface. As output, the user sees "Product added to cart."

[2290] (Application example 2)

[2291] 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."

[2292] Conventional online shopping systems have the problem that users may feel stressed during the process of obtaining product information and making a purchase decision, resulting in a poor user experience.In addition, because they are unable to respond or operate in accordance with the user's emotions, they can be difficult to understand and use, especially for first-time users, the elderly, and people with disabilities.

[2293] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2294] In this invention, the server includes means for generating a response to a user's question using a generative AI model, means for sending a question entered by the user to the generative AI model, means for displaying the generated response to the user, means for adding an item the user wishes to purchase to a cart, means including an emotion recognition engine for recognizing the user's emotion, and means for incorporating the recognized emotion information into the response generation process. This enables responses and operations to be performed in accordance with the user's emotion, thereby providing a particularly stress-free shopping experience.

[2295] A "generative artificial intelligence model" is an artificial intelligence system that automatically generates responses based on user input.

[2296] A "question" is a text or voice input about information or knowledge that a user seeks.

[2297] A "response" is an answer to a user's question generated by a generative artificial intelligence model.

[2298] An "emotion recognition engine" is a software technology that identifies emotions from user input, facial expressions, and voice.

[2299] The "cart" refers to an area where a user temporarily stores products that they wish to purchase.

[2300] "Emotion information" is data on the user's emotions identified by the emotion recognition engine.

[2301] "Product Information" means detailed data relating to a particular product, including price, description, reviews, and images.

[2302] "Instructions" are steps or guidelines for using a product.

[2303] A "brain-controlled interface" is a technology that uses brain waves and neural signals to operate computers and devices.

[2304] A "user interface" refers to input and display means such as a screen and operation buttons that allow a user to interact with a system.

[2305] This invention is a system that combines a generative AI model to generate and display a response to a user's question, an emotion engine that recognizes the user's emotions, and a series of procedures for adding products the user wishes to purchase to their cart.

[2306] System Configuration

[2307] server

[2308] The server is the core component that operates the generative AI model and emotion engine. The server has the following functions:

[2309] 1. Request received:

[2310] The server receives a question sent from a user or a terminal, the question being in text or voice format.

[2311] 2. Generative AI processing:

[2312] The server sends the received question to a generative AI model (e.g., GPT-3) to generate a response.

[2313] 3. Emotion recognition:

[2314] The server uses an emotion engine to recognize emotions from the user's input and includes the emotion information in the response generation process.

[2315] 4. Database integration:

[2316] The server retrieves the necessary product information and user data from the database, along with data from the generative AI model and emotion engine, and incorporates it into the response.

[2317] 5. Response Generation:

[2318] The server formats the generated response and sends it back to the user or terminal.

[2319] 6. Cart Management:

[2320] The server receives a cart addition request from the user and adds the corresponding product to the user's cart.

[2321] Terminal

[2322] The terminal functions as an interface with the user and has the following functions:

[2323] 1. User Interface:

[2324] It provides an interface where users can enter and submit questions, either through text input or voice input.

[2325] 2. Submit your request:

[2326] The entered question is sent to the server.

[2327] 3. Response display:

[2328] The response received from the server is displayed in the user interface.

[2329] 4. Cart function:

[2330] Provide an interface that allows users to add the desired products to their cart (e.g., add to cart button).

[2331] 5. Emotion information display:

[2332] The display of the user interface is changed based on the emotional information obtained from the emotion engine (e.g., simplifying the display when the user feels stressed).

[2333] User

[2334] The user performs the following operations:

[2335] 1. Enter your question:

[2336] Enter product-related questions into the device using text or voice.

[2337] For example: "Teach me how to use my new smartphone."

[2338] 2. Response confirmation:

[2339] Check the response from the server displayed on the terminal.

[2340] 3. Purchase decision:

[2341] If there is an item you would like to add to your cart, click the "Add to Cart" button.

[2342] Specific examples

[2343] Next, an embodiment of the present invention will be described with specific examples.

[2344] 1. Enter your question:

[2345] If a user has a question about how to use their new smartphone, they can type "Teach me how to use my new smartphone" into the input box on the device. The device will then send emotional information from the user's facial expressions and voice to the emotion engine.

[2346] 2. Submit your question:

[2347] The device sends this question to the server, which receives the question and sends it to the generation AI. In parallel, the emotion engine recognizes the user's emotions.

[2348] 3. Generative AI processing:

[2349] The server sends the question to a generation AI (e.g., GPT-3), which then creates a response. An example response might be, "To use your smartphone, turn it on, then access the settings menu..."

[2350] 4. Reflecting emotional information:

[2351] The emotion engine analyzes the user's emotional information (e.g., surprise, joy, stress) and reflects that information in the generative AI's response. For example, if the user is feeling stressed, the response will be more concise.

[2352] 5. Data Formatting:

[2353] The server formats the response received from the generation AI and incorporates additional product information, tutorial links, etc. from the database into the response.

[2354] 6. Sending and displaying responses:

[2355] The server sends a formatted response back to the device, which displays the response in its user interface, such as "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[2356] 7. Add to Cart:

[2357] If the user decides to purchase the smartphone, they press the "Add to Cart" button. The device sends this request to the server, which updates the cart. Once the cart is updated, the user sees the message "Product added to cart."

[2358] As an example, here is an example of a prompt sentence to be input to the generative AI model:

[2359] Example prompt sentence:

[2360] User input: I want to know how to use my new smartphone.

[2361] Emotion: Stress

[2362] This system allows users to efficiently complete the entire process from obtaining product information to making a purchase decision. By incorporating an emotion engine into the system of the present invention, responses and operations can be made according to the user's emotions, making online shopping easier and more convenient for people with disabilities and the elderly, thereby improving the user experience.

[2363] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2364] Step 1:

[2365] The user inputs a question into the device's interface. The input question can be in text or voice format. For example, the user might input "Teach me how to use my new smartphone." This is input data from the user.

[2366] Step 2:

[2367] The device receives the user's input data and first sends the data to an emotion recognition engine to analyze the user's emotions. The emotion recognition engine extracts features from the user's input (voice, text, facial expressions) and outputs an emotion label (e.g., stress, joy, etc.). In this example, we assume that the emotion label is determined to be "stress."

[2368] Step 3:

[2369] The device sends the user's input data and emotional information to the server. At this time, the input data is converted into text format, and the emotional information is sent as an emotional label. Specifically, the input data "Teach me how to use my new smartphone" and the emotional information "Stress" are sent to the server.

[2370] Step 4:

[2371] The server sends the received input data and emotion information to a generative AI model (e.g., GPT-3). The server sends the input data as a prompt to the generative AI model, which then generates a response. For example, the prompt might be "User input: I want to know how to use my new smartphone. Emotion: Stress." The generative AI model generates an answer based on this prompt and outputs the response text.

[2372] Step 5:

[2373] The server receives the generated response text, retrieves related product information (e.g., tutorial links) from the database, and adds detailed information related to the selected product from the database.

[2374] Step 6:

[2375] The server combines the generated response text with the acquired product information to generate the final response. It adjusts the response to be concise, taking into account emotional information. In this example, the final response generated is, "To learn how to use your smartphone, turn it on and access the settings menu. If you have any questions, please see here."

[2376] Step 7:

[2377] The server sends the final response to the device, which displays it to the user, who can then see the answer to their question by viewing the response displayed in the device's interface.

[2378] Step 8:

[2379] If the user is satisfied with the answers and decides to purchase the product, he or she presses the "Add to Cart" button on the terminal, which sends a request to add the product to the cart from the terminal to the server.

[2380] Step 9:

[2381] The server receives the cart addition request and updates the user's cart based on the product ID and user ID. If the update is successful, the server sends a message to the terminal stating "The product has been added to the cart."

[2382] Step 10:

[2383] The terminal receives the message from the server and displays the message "The product has been added to the cart" on the user interface. The user can confirm this message and continue the purchase procedure.

[2384] The above is a specific processing flow for carrying out the present invention, which allows the user to efficiently and stress-free go from obtaining product information to deciding on a purchase.

[2385] 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.

[2386] 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.

[2387] 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.

[2388] 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.

[2389] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2390] 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.

[2391] 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).

[2392] 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.

[2393] 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."

[2394] 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.

[2395] 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).

[2396] 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.

[2397] 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.

[2398] 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.

[2399] 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.

[2400] 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.

[2401] 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). A...

Claims

1. means for generating responses to user questions using a generative artificial intelligence model; means for transmitting a user-entered question to a generative artificial intelligence model; means for displaying the generated response to a user; a means for the user to add items to their cart that they wish to purchase; A system including:

2. The system of claim 1 , further comprising means for providing product information and operating instructions using a generative artificial intelligence model.

3. The system of claim 1 further comprising means for receiving user input using a brain-controlled interface.

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