System

Abstract

A system is provided.SOLUTION: A system includes a means for generating a reason why a customer selects a commodity or a service, a means for describing a specific scene in a novel form from a viewpoint of the customer based on the generated selection reason, and a means for visualizing the described scenario by a virtual reality or an augmented reality technology.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] For companies planning new businesses or developing new products, it is extremely difficult to understand the psychology behind customers' product and service selection. In particular, it is difficult to intuitively grasp differences in selection based on customer attributes such as cultural background, gender, and age group. Given this background, there is a need for effective methods to deeply understand the reasons for target customers' choices and their behavioral patterns. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for generating reasons why customers choose a product or service, a means for depicting a specific scenario from the customer's perspective in a novel format based on the generated reasons for selection, and a means for visualizing the depicted scenario using virtual reality or augmented reality technology. This system includes a means for generating reasons for selection taking into account customer attributes such as cultural background, gender, and age group, and further includes a means for visualizing a specific scenario from the customer's perspective in 360 degrees using virtual reality or augmented reality technology. This allows companies to intuitively and specifically understand the selection psychology and behavioral patterns of their target customers.

[0006] "Customers" or "Target Customers" refers to people who may purchase, use, or consider the subject product or service.

[0007] "Products" refers to tangible goods and intangible services that are intended for purchase by consumers.

[0008] "Reasons for choice" refers to the factors and motivations that influence customers when choosing a particular product or service.

[0009] "Generating means" refers to a method or process for producing new information or results based on specified input data.

[0010] "Fictionalized means" refers to the way events or scenes are presented in a narrative style written in writing.

[0011] "Virtual reality technology (VR)" refers to technology that allows users to visually experience a virtual environment created using computer technology.

[0012] "Augmented reality technology (AR)" refers to the technology of overlaying digital information onto real-world scenery.

[0013] "Visualization means" refers to a method of displaying information in a visual format (e.g., 3D models, graphics, animations, etc.).

[0014] "Cultural background" refers to customs, values, and behavioral patterns based on a particular culture or social environment.

[0015] "Customer attributes" refers to the characteristics and profile of customers (e.g., age, gender, occupation, preferences, etc.).

[0016] "360-degree visualization" refers to a method of displaying a particular scene or environment in a format that allows it to be viewed from all directions. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service. This system automatically generates reasons why customers choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology.

[0039] User Input Phase

[0040] Step 1: Enter product information and customer attributes

[0041] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[0042] AI model generation phase

[0043] Step 2: Generate reasons for selection

[0044] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0045] Scenario description phase

[0046] Step 3: Writing in fiction

[0047] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[0048] VR / AR visualization phase

[0049] Step 4: Visualize the scenario

[0050] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0051] Specific examples

[0052] The following process is performed on a newly developed sports sneaker.

[0053] 1. The user enters information into the device

[0054] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[0055] 2. The server generates the selection reason

[0056] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0057] 3. The server describes the scenario

[0058] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0059] 4. The server generates the VR / AR content

[0060] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0061] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions regarding new business ventures and product development.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The user inputs product information and customer attributes into the terminal. Product information includes the product name, features, price, etc., while customer attributes include age group, gender, cultural background, lifestyle, preferences, etc. This input data is sent from the terminal to the server.

[0065] Step 2:

[0066] The server receives the product information and customer attribute data sent from the terminal. It analyzes the received data and uses it as the basis for generating the customer's reasons for selection. At this time, it automatically checks for missing data or input errors.

[0067] Step 3:

[0068] The server launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why customers would choose a product. The model outputs multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0069] Step 4:

[0070] Based on the generated reasons for selection, the server creates a fictional scenario in which a customer uses a particular product. For example, it depicts a young sports enthusiast putting on new sneakers during a morning jog. At this time, the generated reasons for selection are appropriately incorporated into the scenario.

[0071] Step 5:

[0072] The server uses 3D modeling technology to convert the depicted scenario into VR / AR content. It generates detailed 3D models and their behavior based on the scenario, constructing a virtual reality or augmented reality scene.

[0073] Step 6:

[0074] The server then transmits the completed VR / AR content to the user's device, which includes compressing large amounts of data and optimizing the transmission route.

[0075] Step 7:

[0076] Users experience the visualized scenario using a terminal and necessary VR / AR devices (e.g., VR headsets). Users can see specific scenes in which customers use the product in a 360-degree field of view, thereby intuitively understanding the reasons for customers' choices and behavioral patterns.

[0077] Each of these steps allows companies to gain a deeper understanding of the psychology of their target customers, which can be used to develop new businesses and products.

[0078] Example 1

[0079] 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."

[0080] Conventional systems have difficulty intuitively understanding the psychological factors that customers use when selecting a product or service, making it difficult for companies to fully grasp the reasons for their choices and their behavioral patterns. This makes it difficult to develop products and formulate marketing strategies that accurately reflect the needs and preferences of target customers.

[0081] 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.

[0082] In this invention, the server includes: means for inputting information about a product or service and customer attribute data; means for automatically generating reasons why customers select a product or service using a generative AI model; means for describing specific scenes in which customers use the product in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario in virtual reality or augmented reality using 3D modeling technology; and means for users to experience the visualized scenario using a virtual reality or augmented reality device. This allows companies to intuitively understand the selection reasons and behavioral patterns of target customers and make effective decisions in new business and product development.

[0083] "Product or service information" refers to detailed data about a specific product or service, such as product name, features, and price.

[0084] "Customer attribute data" is information about the personal characteristics of target customers, such as age, gender, cultural background, lifestyle, and preferences.

[0085] A "generative AI model" is an algorithm that automatically generates reasons why a customer might choose a product or service based on input data.

[0086] "Reasons for choice" are the motivations or reasons why customers choose a particular product or service.

[0087] The "means of describing specific scenes in a novel format" is a process of creating a narrative-like concrete scene in which a customer uses a product based on the generated reasons for selection.

[0088] "3D modeling technology" is the technology of using a computer to generate and manipulate three-dimensional objects.

[0089] "Virtual reality technology" is a technology that provides users with a virtual environment generated using computer simulation.

[0090] "Augmented reality technology" is a technology that overlays computer-generated information onto images of the real world.

[0091] A "virtual reality or augmented reality device" is hardware, such as a headset or smartphone, that allows you to experience virtual reality or augmented reality content.

[0092] A "visualized scenario" is a scene that is visually recreated using 3D modeling techniques and virtual or augmented reality technologies.

[0093] This invention is a system that uses virtual reality (VR) and augmented reality (AR) technologies to intuitively understand the psychological factors that customers consider when selecting a product or service. This system involves a procedure in which a user inputs product information and customer attributes via a terminal, a server generates reasons for selection based on that data, depicts a specific scene, and visualizes the scene using virtual reality or augmented reality technology.

[0094] First, the user uses a terminal to input information about the product or service and target customer attribute data. For example, the terminal has a dedicated input form where the user can enter detailed product features such as "lightweight and breathable" and "modern design" as well as customer attributes such as "young people aged 18-25, sports enthusiasts, male." This data is then sent to a server via the Internet.

[0095] Next, the server uses a generative AI model (for example, OpenAI (registered trademark) GPT-4 (registered trademark)) to analyze the received product information and customer attribute data and automatically generate reasons why the target customer would choose the product. This generative AI model takes into account customer attributes such as cultural background, age, and gender, and generates reasons for selection such as "the design is modern and popular with friends," "it's comfortable when jogging," and "it's recommended by famous athletes."

[0096] The server then uses the generated reasons for selection to create a story in which the customer uses the product. For example, a scenario called "Morning Jogging Scene" could be created, depicting a young sports enthusiast enjoying a jog in their new sneakers, with comments of praise from friends. The created scenario is stored in the server's database.

[0097] The server then performs 3D modeling based on this scene and generates VR / AR content using a 3D modeling platform such as Unreal Engine or Unity. The created VR / AR content is visualized in a 360-degree field of view and can be experienced by users using a VR headset or AR-enabled device.

[0098] Finally, users can experience visualized scenarios using virtual or augmented reality devices, helping them intuitively understand the reasons and context behind customers' product or service choices.

[0099] As a concrete example, the process for a newly developed sports sneaker is as follows:

[0100] 1. The user enters details about the sports sneakers, such as "lightweight and breathable" and "modern design," into the input form on the device, and sets the target customers as "young people aged 18-25, sports enthusiasts, males."

[0101] 2. The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0102] 3. The server creates a novel-style depiction of a "morning jogging scene." The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of effortless running and complimentary comments from friends.

[0103] 4. The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, the user can intuitively understand the specific situation based on the reasons for their choice.

[0104] An example prompt is:

[0105] "Generate reasons why young people aged 18-25, sports enthusiasts, should choose a new lightweight, breathable sneaker. Consider the comfort they feel while jogging, the praise they get from friends, and endorsements by famous athletes."

[0106] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0107] Step 1: The user enters product information and customer attributes.

[0108] The user enters product information (e.g., product name, features, price) and customer attribute data (e.g., age, gender, cultural background, lifestyle, preferences) into a dedicated input form on the device. For example, the user might enter "lightweight and breathable" and "modern design" as product features, and set "young people aged 18-25, sports enthusiasts" as target customers. The input data is sent from the user's device to the server. The input here is basic information about the product or service and information based on the customer's attributes.

[0109] Step 2: The server generates the selection reasons using the generative AI model.

[0110] The server receives the product information and customer attribute data sent from the device. The received data is input into a generative AI model, which then performs analysis based on that data. The generative AI model (e.g., GPT-4) generates reasons why the target customer would choose the product, taking into account the customer's cultural background, age, gender, and other factors. The output of this step is a selection reason, such as "The design is modern and popular with friends," "It's comfortable for jogging," or "It's recommended by a famous athlete."

[0111] Step 3: The server describes the scene in novel form.

[0112] The server uses the generated reasons for selection to describe in a novel-like format a specific scene in which the customer uses the product. For example, it creates a scenario called "Morning Jogging Scene" and describes a story in which a young sports enthusiast puts on new sneakers and enjoys jogging, receiving praise from friends. This created scene is saved in a database on the server. The input is the generated reasons for selection, and the output is the described scenario in a novel-like format.

[0113] Step 4: The server visualizes the scenario using 3D modeling techniques.

[0114] The server performs 3D modeling based on the saved scenario. This task typically uses a 3D modeling platform such as Unreal Engine or Unity. The server models each element of the scenario in 3D and converts it into virtual reality (VR) or augmented reality (AR) content. The output is visualized VR / AR content with a 360-degree field of view.

[0115] Step 5: The user experiences the visualized scenario using the VR / AR device.

[0116] The user experiences the VR / AR content generated by the server using a VR headset or an AR-compatible device. For example, the user can wear the headset and experience a jogging scene with a 360-degree field of view. The visualized scene helps customers intuitively understand the reasons for selecting a product and the usage experience. The input of this step is the VR / AR content, and the output is the user's understanding as an experience.

[0117] Through these steps, the system extracts the reasons why customers choose a product or service, and based on that, it can depict specific scenes and visualize them using virtual reality and augmented reality technology, allowing companies to intuitively understand the reasons and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development.

[0118] (Application example 1)

[0119] 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."

[0120] In recent years, responding to the diversifying needs of consumers has required a deep understanding of the reasons for their product and service selection, and appropriate marketing. Traditional methods rely on surveys and data analysis, but these alone have the problem of not being able to fully grasp customers' psychological factors and purchasing motivations. Furthermore, physical stores have limited means of visually appealing products, and online shopping presents challenges, making it difficult for users to experience the texture and feel of a product. In response, a new system is needed that provides an intuitive, interactive purchasing experience and deeply understands the reasons for customers' choices.

[0121] 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.

[0122] In this invention, the server includes: a means for generating reasons for a customer's selection of a product or service; a means for describing a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; and a means for visualizing the described scenario using virtual reality or augmented reality technology and allowing the user to experience it in a virtual environment. This allows customers to intuitively and experientially understand their reasons for selecting a product or service and their purchasing motivations, making it easier for companies to understand customers' psychological factors. Furthermore, product experiences in a virtual environment allow users to simulate the texture and feel of the product, thereby solving challenges in online shopping.

[0123] "Customer" means any person who purchases or uses goods or services.

[0124] "Goods or services" means any item or activity that a consumer purchases or uses.

[0125] "Reasons for choice" are the factors and motivations behind a customer's selection of a particular product or service.

[0126] "Means for generating" refers to a system or method for generating information such as reasons for selection based on specific data or algorithms.

[0127] A "scene" is a representation or depiction of a particular situation or setting.

[0128] "Novel form" is a technique of describing specific scenes in the form of a narrative or story.

[0129] "Virtual reality technology" is a technology that allows users to experience a three-dimensional virtual environment generated by a computer.

[0130] "Augmented reality technology" is a technology that adds digital information to visual information from the real world and displays it.

[0131] A "visualization tool" is a system or method for converting information or data into a visible form and displaying it.

[0132] "Cultural background" refers to the totality of traditions, customs, values, etc. in a particular society or community.

[0133] "Gender" is the biological or social classification of male or female.

[0134] An "age group" is a group of people that falls into a particular age range.

[0135] "Customer attributes" are information or characteristics that categorize customers into specific groups.

[0136] "360-degree visualization" is a technology that provides visual information in all directions, allowing users to see in any direction.

[0137] A "virtual environment" is a computer-generated imaginary world or space.

[0138] "Means of experience" are methods and devices that allow users to actually experience the virtual environment.

[0139] "Checking out the details" is the act of gaining a more detailed understanding of a particular subject.

[0140] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers experience when selecting a product or service. This system operates as follows between a server, a terminal, and a user.

[0141] 1. System Configuration and Hardware / Software

[0142] Hardware:

[0143] VR-compatible head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0144] High-performance smartphone

[0145] software:

[0146] Unity Engine

[0147] OpenAI GPT-4 (generative AI model)

[0148] 3D modeling tools (e.g. Blender, Maya)

[0149] 2. Program Processing

[0150] User input phase:

[0151] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.), and this data is sent from the terminal to the server.

[0152] AI model generation phase:

[0153] Based on the received data, the server uses a generative AI model (OpenAI GPT-4) to automatically generate reasons why the target customer would select the product. The generative AI model takes into account customer attributes such as cultural background, gender, and age group to provide multiple reasons for selection. Examples of prompt sentences include the following:

[0154] Example prompt:

[0155] "Please tell us why young people aged 18-25 and sports enthusiasts choose sneakers."

[0156] Scenario Description Phase:

[0157] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer would use the product. The scenario is written in a narrative style and focuses on the customer's daily life and specific situations. For example, it could describe in detail a scene in which the customer enjoys a morning jog wearing new sneakers.

[0158] VR / AR visualization phase:

[0159] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0160] 3. Specific Examples

[0161] For example, if we were to look at a newly developed sports sneaker, the process would look something like this:

[0162] 1. User Input Phase

[0163] Users input information about sports sneakers, such as "lightweight and breathable" and "modern design," into the device, and set their target customers as "young people aged 18-25, sports enthusiasts."

[0164] 2. AI model generation phase

[0165] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0166] 3. Scenario description phase

[0167] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0168] 4. VR / AR visualization phase

[0169] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this scene through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0170] As described above, this invention is a system that deeply understands the psychological factors of customers and makes it possible to intuitively grasp the reasons for customers' choices through interactive experiences.

[0171] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0172] Step 1:

[0173] User Input Phase

[0174] The user uses a terminal to input product information (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This input data is sent from the terminal to the server. Specifically, the user fills in the necessary information in the application's input form and presses the "Submit" button, which transfers the data to the server.

[0175] Input: Product information, target customer attributes

[0176] Output: The input data sent to the server

[0177] Step 2:

[0178] AI model generation phase

[0179] The server receives the data sent in step 1 and uses a generative AI model (OpenAI GPT-4) to generate reasons why customers would select a product. The server creates a prompt based on the received customer attribute data and inputs the prompt into the generative AI model to generate reasons for selection. As a specific example, a prompt such as "Please tell us the reasons why young people aged 18-25 who are sports enthusiasts would choose these sneakers" is created and input into the AI ​​model.

[0180] Input: Customer attribute data, prompt statement

[0181] Output: Generated selection reasons

[0182] Step 3:

[0183] Scenario description phase

[0184] Based on the reasons for selection generated in step 2, the server creates a novel-style scenario in which the target customer would use the product. A narrative scenario is created based on the reasons for selection obtained from the generative AI model. The specific scenario is depicted focusing on the customer's daily life or a specific situation. For example, a scene in which a user puts on new sneakers and enjoys a morning jog can be depicted in novel form.

[0185] Input: Generated selection reasons

[0186] Output: Depicted scenario

[0187] Step 4:

[0188] VR / AR visualization phase

[0189] The server uses 3D modeling technology to convert the scenario depicted in step 3 into VR / AR content. Using the Unity engine, the server creates 3D models of each element of the depicted scenario and converts them into a format that can be displayed in the virtual environment. Finally, the visualized scenario can be experienced with a 360-degree field of view. The user puts on a VR headset and experiences the scenario in the virtual environment.

[0190] Input: Depicted scenario

[0191] Output: VR / AR content

[0192] Through this process, users can intuitively and experientially understand the reasons for choosing a product, and companies can gain a deeper understanding of the psychological factors behind their customers.

[0193] 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.

[0194] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers use when selecting a product or service with an emotion engine that recognizes the user's emotions. This system automatically generates reasons why a customer might choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology. The emotion engine also recognizes the user's emotions in real time, dynamically adjusting the content of the scenario and the VR / AR display based on the results.

[0195] User Input Phase

[0196] Step 1: Enter product information and customer attributes

[0197] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[0198] AI model generation phase

[0199] Step 2: Generate reasons for selection

[0200] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0201] Scenario description phase

[0202] Step 3: Writing in fiction

[0203] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[0204] VR / AR visualization phase

[0205] Step 4: Visualize the scenario

[0206] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0207] Introducing the Emotion Engine

[0208] Step 5: Activating the Emotion Engine

[0209] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions and tone of voice, and transmits the data in real time to the emotion engine, which then analyzes this data and recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.).

[0210] Step 6: Dynamically adjust the scenario

[0211] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server will change the scenario to explain it more clearly. If the emotion of joy is recognized, the server will add more interesting scenes to enrich the user's experience.

[0212] Step 7: Optimize the user experience

[0213] Users can continuously enjoy tailored scenarios and VR / AR experiences, providing an experience optimized for their emotions and allowing users to gain a more intuitive and deeper understanding of customer psychology.

[0214] Specific examples

[0215] The following process is performed on a newly developed sports sneaker.

[0216] 1. The user enters information into the device

[0217] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[0218] 2. The server generates the selection reason

[0219] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0220] 3. The server describes the scenario

[0221] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0222] 4. The server generates the VR / AR content

[0223] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0224] 5. Introducing the Emotion Engine

[0225] While the user is experiencing the jogging scene using a VR headset, the device recognizes the user's emotions in real time. The emotion engine analyzes the user's reactions (e.g., surprise or satisfaction) and sends the analysis results to the server.

[0226] 6. Dynamically adjust scenarios and VR / AR experiences

[0227] Based on the results of the emotion engine, the server dynamically adjusts the scenario and VR / AR content to optimize the user experience. For example, if the user feels surprised, it adds more interesting information or scenes.

[0228] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development, and to provide optimal experiences based on user emotions.

[0229] The processing flow will be explained below.

[0230] Step 1:

[0231] The user inputs product and customer attribute information into the terminal. Product information includes the product name, features, and price, and customer attributes include age group, gender, cultural background, lifestyle, and preferences. This information is sent from the terminal to the server.

[0232] Step 2:

[0233] The server analyzes the product and customer attribute data received from the terminal, automatically checking for missing or incorrect data and establishing standards for accurate data analysis.

[0234] Step 3:

[0235] The server then launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why target customers would choose a product. For example, it generates reasons why young sports enthusiasts choose sneakers, such as "casual and modern design," "comfortable for jogging," and "recommended by friends and influencers."

[0236] Step 4:

[0237] Based on the generated reasons for selection, the server creates a narrative depiction of a specific scenario in which the target customer uses the product, such as a young sports enthusiast putting on a new pair of sneakers during a morning jog and feeling pleased with their comfort.

[0238] Step 5:

[0239] The server converts the depicted scenario into virtual reality (VR) or augmented reality (AR) content using 3D modeling technology. To realistically recreate the scene, it generates a 3D model based on the scenario and its behavior.

[0240] Step 6:

[0241] The server then transmits the completed VR / AR content to the user's device. The server compresses large amounts of data and optimizes the transmission route to deliver the data efficiently.

[0242] Step 7:

[0243] Users can use a terminal and a VR / AR device (e.g., a VR headset) to experience a visualized scenario, allowing them to experience specific scenes in which customers use the product in a 360-degree field of view and intuitively understand the reasons for their choices.

[0244] Step 8:

[0245] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions, tone of voice, and other data, and sends the data to the emotion engine in real time.

[0246] Step 9:

[0247] The emotion engine recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.) in real time and sends the analysis results to the server, where the user's emotions are classified in detail and the type of reaction is understood.

[0248] Step 10:

[0249] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server changes the scenario to make it easier to understand, and if the user is satisfied, the server adds more interesting scenes.

[0250] Step 11:

[0251] Users can enjoy tailored scenarios and VR / AR experiences continuously, and the emotionally optimized experience provides users with a deeper understanding.

[0252] Through all these steps, companies can accurately understand the reasons for target customers' choices and behavioral patterns, allowing them to make effective decisions in new business and product development. Furthermore, optimizing user experience based on emotions allows for more effective customer understanding.

[0253] Example 2

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

[0255] Today's consumers are diverse, and there are many psychological factors that influence their product and service choices. Traditional marketing methods make it difficult to accurately grasp consumer psychology and accurately analyze the reasons for product selection. Furthermore, there were limited ways to describe and visualize specific scenes from the customer's perspective, resulting in an insufficient user experience. Furthermore, there was a lack of a way to optimize the experience based on user emotions in real time. This made it difficult for companies to understand their customers' true needs and develop effective marketing strategies.

[0256] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for generating reasons why a customer selects a product or service; means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario using virtual reality or augmented reality technology; and means for dynamically adjusting the scenario and virtual reality or augmented reality content using an emotion engine that recognizes the user's emotions. This allows users to have a more intuitive and deeper understanding of customer psychology, and companies to gain a deeper understanding of the selection reasons and behavioral patterns of target customers, enabling them to make effective decisions in new business ventures and product development. It also allows for the provision of an optimal experience based on the user's emotions.

[0257] "Customer" means a person who purchases or uses goods or services.

[0258] "Goods" refers to tangible objects intended for purchase by consumers.

[0259] "Service" refers to an intangible provision intended for consumer enjoyment.

[0260] "Reasons for choice" refers to the reasons and motivations that customers have when choosing a particular product or service.

[0261] "Novel form" refers to a method of structuring text in a narrative style.

[0262] "Virtual reality technology" refers to technology that allows users to experience a virtual environment generated by a computer.

[0263] "Augmented reality technology" refers to technology that displays digital information overlaid on the real environment.

[0264] "Visualization" refers to displaying information in a visually easy-to-read manner.

[0265] "User" refers to a person who uses a system or service.

[0266] An "emotion engine" refers to technology that recognizes the user's emotional state and controls the system's behavior based on the results.

[0267] "Dynamic adjustment" refers to changing the content in real time according to the situation.

[0268] A "prompt" refers to the text of a question or instruction that is input into a generative AI model.

[0269] A "generative AI model" refers to an artificial intelligence model that generates an output for a specific input based on a large amount of data.

[0270] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service with an emotion engine that recognizes the user's emotions. This system is implemented using multiple hardware and software components.

[0271] First, the user uses a terminal to input information about the product or service (e.g., product name, features, price, etc.), as well as the attributes of the target customer (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server. At this stage, the user uses an input interface (e.g., a web form).

[0272] The server uses a generative AI model based on the received data to automatically generate reasons why the target customer would choose a product. This generative AI model is trained to provide multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0273] (Example of a prompt)

[0274] "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[0275] Next, the server uses the generated reasons for selection to create a story-like scenario in which the target customer would use the product, in a novel format. The scenario is then saved in a database using a text generation engine.

[0276] The server then converts the scenario described in the novel format into VR / AR content using 3D modeling tools (e.g., Blender, Unity). The visualized scenario can be experienced through devices such as headsets.

[0277] When a user experiences generated content using a VR / AR headset, the device uses its built-in cameras and sensors to recognize the user's emotions (e.g., joy, surprise, confusion, etc.) in real time. The emotion engine analyzes this data and recognizes the user's emotional state.

[0278] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server adds detailed explanations and changes the scene to make it easier to understand. The user can continue to enjoy the adjusted scenario and VR / AR experience.

[0279] As a concrete example, the following steps are performed for a newly developed pair of sports sneakers. The user enters product information into the device, such as "lightweight and breathable" and "modern design," and sets the target customer as "young people aged 18-25, sports enthusiasts." The server uses a generative AI model to automatically generate reasons why young sports enthusiasts would choose the sneakers, and based on the generated reasons, describes a "morning jogging scene" in novel form. The server models the scenario in 3D and visualizes it using virtual reality technology, which the user experiences through a VR headset. During the experience, the device analyzes the user's emotions in real time, and the emotion engine dynamically adjusts the scenario and VR / AR content based on the results. This system allows companies to deeply understand customer reasons for choice and behavioral patterns, allowing them to provide optimal experiences based on the user's emotions.

[0280] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0281] Step 1:

[0282] The user logs in to the device and enters product or service information. The input is sent from the device to the server. At this stage, the input data includes the product name, features, price, and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). The device converts the input data into JSON format and sends it to the server as a request.

[0283] Input: Product information and customer attribute information

[0284] Output: Send data to the server

[0285] Specific behavior:

[0286] Enter product information: Example: "Lightweight and breathable sports sneakers with a modern design. Price: 8,000 yen"

[0287] Enter customer attributes: e.g. "Young people aged 18-25, sports enthusiasts"

[0288] Data transmission: The device converts the data into JSON format and sends it to the server.

[0289] Step 2:

[0290] The server sends prompts to the generative AI model based on the received data. The generative AI model generates reasons why the target customer would choose the product based on a pre-trained dataset. The server receives the generated reasons and stores them in its internal database.

[0291] Input: JSON data of product information and customer attributes

[0292] Output: Reason for selection

[0293] Specific behavior:

[0294] Generate and send prompts: e.g., "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[0295] Receive responses from the generative AI model: e.g., "The design is modern and popular with friends," "It's comfortable for jogging," "It's recommended by famous athletes."

[0296] Step 3:

[0297] The server then depicts specific scenes in a novel format based on the generated reasons for the choices. The scenes are created using a text generation engine in a narrative style, focusing on the user's daily life or specific situations. The created scenarios are stored in the server's database.

[0298] Input: Reason for selection

[0299] Output: Novel-style scenario

[0300] Specific behavior:

[0301] Scenario generation: Using a text generation engine

[0302] Example: "A morning jogging scene. A young sports enthusiast enjoys jogging in lightweight, breathable sneakers. Includes comments of praise from friends."

[0303] Step 4:

[0304] The server generates VR / AR content using a 3D modeling tool based on the created scenario, constructs 3D models and action sequences based on the scenario, creates VR / AR content, and prepares it for transmission to the device.

[0305] Input: Novel-style scenario

[0306] Output: VR / AR content

[0307] Specific behavior:

[0308] Use of 3D modeling tools (e.g. Blender, Unity)

[0309] Model generation: jogging characters and jogging paths

[0310] Scene rendering: morning scenery and friend interaction scenes

[0311] Step 5:

[0312] While a user wears a VR / AR headset and experiences content, the device uses its built-in cameras and sensors to collect emotional data in real time. The emotion engine analyzes the collected data and recognizes the user's emotional state.

[0313] Input: User experience data (facial expressions, tone of voice, etc.)

[0314] Output: User's emotional state

[0315] Specific behavior:

[0316] Use of face recognition algorithms (e.g. OpenCV)

[0317] Use of voice tone analysis algorithms (e.g., Google® Cloud Speech-to-Text)

[0318] Step 6:

[0319] The server dynamically adjusts the scenario and VR / AR content based on the user's emotional state as recognized by the emotion engine. For example, if the user is confused, it adds detailed explanations and changes the scene to make it easier to understand. The adjusted scenario and content are then regenerated and sent to the device in real time.

[0320] Input: User's emotional state

[0321] Output: Adjusted scenarios and VR / AR content

[0322] Specific behavior:

[0323] Scenario change: Dynamic adjustment based on the analysis results of the emotion engine

[0324] For example, "If users are confused, add detailed explanations."

[0325] Step 7:

[0326] Users can continuously enjoy the tailored scenario and VR / AR experience. The device continuously collects emotional data and sends feedback to the server until the user experience ends, providing an experience optimized for the user's emotions.

[0327] Input: Tailored scenarios and VR / AR content

[0328] Output: Optimized user experience

[0329] Specific behavior:

[0330] Continuously monitoring user experience

[0331] Continued data collection: Emotion data is collected periodically until the end of the user experience and sent to the server

[0332] (Application example 2)

[0333] 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."

[0334] Conventional product or service selection support systems for autonomous vehicles have difficulty fully understanding the user's reasons for selection and psychological factors, and have been unable to provide an experience optimized for the user's emotions. As a result, it has been difficult for users to intuitively understand the value of products and services, and there have been issues in increasing their desire to purchase.

[0335] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating reasons why a customer selects a product or service, means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection, means for visualizing the depicted scenario using virtual reality or augmented reality technology, an emotion engine for recognizing the customer's emotions in real time, and means for dynamically adjusting the content of the scenario and the virtual reality or augmented reality display based on the customer's emotions recognized by the emotion engine. This makes it easier for the user to understand the reasons for their selection and provides an optimal experience based on their emotions.

[0336] "Reasons for choosing a product or service" refers to the motives and criteria that customers consider when choosing a particular product or service.

[0337] "Description in novel form" is a method of writing a story about a specific scene from the customer's perspective based on the reasons for their choice.

[0338] "Virtual reality or augmented reality visualization" refers to a technology that transforms a scenario depicted in a novel format into an experiential form in three-dimensional space and displays it through a virtual reality (VR) or augmented reality (AR) device.

[0339] The "emotion engine that recognizes customer emotions in real time" is a system that uses sensors and cameras to analyze the customer's facial expressions and voice to grasp the customer's emotional state in real time.

[0340] "Dynamic adjustment" refers to a method for changing scenarios and virtual or augmented reality content on the fly based on perceived customer sentiment.

[0341] "Customer attributes such as cultural background, gender, age group, etc." refers to individual characteristics that influence the reasons for a customer's choice, such as their cultural background, gender, age, and lifestyle.

[0342] This invention relates to a selection support system for autonomous vehicles, which generates reasons for customers to select a vehicle, describes specific scenes in a novel format based on those reasons, and visualizes them using virtual reality (VR) or augmented reality (AR) technology. Furthermore, it uses an emotion engine that recognizes customer emotions in real time, dynamically adjusting the scenario and VR / AR display.

[0343] To realize this system, the following hardware and software are used.

[0344] 1. Hardware

[0345] Autonomous vehicle console: The interface for receiving user input and operating the system.

[0346] VR headset (e.g., Oculus Quest 2): Used by users to experience virtual reality scenarios.

[0347] Built-in cameras and sensors (e.g., a vehicle's dashboard camera): Detects the user's facial expressions and voice and sends data to the emotion engine.

[0348] 2. Software

[0349] Emotion recognition software (e.g., Affectiva SDK): Analyzes and recognizes the user's emotional state in real time.

[0350] Generative AI models (e.g., GPT-4): Automatically generate reasons for choosing a vehicle based on customer attributes and input data.

[0351] 3D modeling software (e.g. Blender): Convert the generated scenario into a 3D model and create VR / AR content.

[0352] Program processing and its explanation

[0353] User Input Phase

[0354] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal, and this data is sent to the server.

[0355] AI model generation phase

[0356] Based on the data sent, the server uses a generative AI model such as GPT-4 to automatically generate reasons why the customer chose the vehicle, such as "because it's environmentally friendly" or "because I want to try new technology."

[0357] Scenario description phase

[0358] Based on the generated reasons for selection, the server describes specific scenes from the customer's perspective in a novel format, such as "commuting in an urban area" or "driving with family."

[0359] VR / AR visualization phase

[0360] The depicted scenarios are converted into VR / AR content using 3D modeling software such as Blender, and users can experience the specific situations created through VR headsets such as the Oculus Quest 2.

[0361] Introducing the Emotion Engine

[0362] While a user is experiencing a scene using a VR headset, the built-in camera and sensors analyze the user's facial expressions and voice, and emotion recognition software such as the Affectiva SDK sends the data to an emotion engine, which then analyzes this data to understand the user's emotional state in real time.

[0363] Dynamically adjusting scenarios

[0364] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is surprised, it adds more interesting information. If the user has difficulty understanding, it adds detailed explanations.

[0365] Examples of prompt statements

[0366] For example, a prompt to generate a scenario for a new autonomous electric vehicle might look like this:

[0367] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[0368] These systems and prompts help users understand the reasons for their choices, providing an optimal emotional experience.

[0369] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0370] Step 1:

[0371] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal. The input data is sent to the server. Specifically, the user enters the data using an interface such as a touchscreen or keyboard, and then presses the send button, which sends the data to the server.

[0372] Step 2:

[0373] Based on the data received by the server, a generative AI model (e.g., GPT-4) is used to automatically generate reasons why a customer should choose a vehicle. The input is vehicle information and customer attributes, and the output is multiple reasons for selection. Specifically, the server analyzes the received data and generates reasons for selection by providing them as prompts to the generative AI model. In this case, the prompts are in the following format:

[0374] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[0375] Step 3:

[0376] Based on the generated reasons for selection, the server describes a specific scene in novel form from the customer's perspective. The input is the reason for selection, and the output is a novel-style text describing a specific scene. Specifically, the server uses an AI model to generate a story-like scenario from the reasons for selection. This scenario could be, for example, a "commuting scene in an urban area" or a "drive scene with family."

[0377] Step 4:

[0378] The server converts the depicted scenario into VR / AR content using 3D modeling software (e.g., Blender). The input is a novel-style scenario, and the output is VR / AR content. Specifically, the server analyzes the scenario and converts its contents into a 3D model. The user can experience this model through a VR headset.

[0379] Step 5:

[0380] While a user experiences a scenario using a VR headset, the built-in camera and sensors detect the user's facial expressions and voice and send the data to an emotion engine (e.g., Affectiva SDK). The input is the user's facial and voice data, and the output is an analyzed emotional state. Specifically, the camera and sensors collect data and send it to the emotion engine in real time for analysis.

[0381] Step 6:

[0382] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. The input is the analyzed emotional state, and the output is the adjusted content. Specifically, the server analyzes the emotional data and adjusts the scenario. For example, if the user is surprised, it adds more interesting information. Also, if the content is difficult to understand, it adds detailed explanations.

[0383] This helps users understand the reasons behind their choices and provides an optimal emotional experience.

[0384] 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.

[0385] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0386] 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.

[0387] [Second embodiment]

[0388] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0389] 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.

[0390] 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).

[0391] 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.

[0392] 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.

[0393] 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).

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0399] 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."

[0400] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service. This system automatically generates reasons why customers choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology.

[0401] User Input Phase

[0402] Step 1: Enter product information and customer attributes

[0403] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[0404] AI model generation phase

[0405] Step 2: Generate reasons for selection

[0406] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0407] Scenario description phase

[0408] Step 3: Writing in fiction

[0409] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[0410] VR / AR visualization phase

[0411] Step 4: Visualize the scenario

[0412] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0413] Specific examples

[0414] The following process is performed on a newly developed sports sneaker.

[0415] 1. The user enters information into the device

[0416] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[0417] 2. The server generates the selection reason

[0418] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0419] 3. The server describes the scenario

[0420] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0421] 4. The server generates the VR / AR content

[0422] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0423] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions regarding new business ventures and product development.

[0424] The processing flow will be explained below.

[0425] Step 1:

[0426] The user inputs product information and customer attributes into the terminal. Product information includes the product name, features, price, etc., while customer attributes include age group, gender, cultural background, lifestyle, preferences, etc. This input data is sent from the terminal to the server.

[0427] Step 2:

[0428] The server receives the product information and customer attribute data sent from the terminal. It analyzes the received data and uses it as the basis for generating the customer's reasons for selection. At this time, it automatically checks for missing data or input errors.

[0429] Step 3:

[0430] The server launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why customers would choose a product. The model outputs multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0431] Step 4:

[0432] Based on the generated reasons for selection, the server creates a fictional scenario in which a customer uses a particular product. For example, it depicts a young sports enthusiast putting on new sneakers during a morning jog. At this time, the generated reasons for selection are appropriately incorporated into the scenario.

[0433] Step 5:

[0434] The server uses 3D modeling technology to convert the depicted scenario into VR / AR content. It generates detailed 3D models and their behavior based on the scenario, constructing a virtual reality or augmented reality scene.

[0435] Step 6:

[0436] The server then transmits the completed VR / AR content to the user's device, which includes compressing large amounts of data and optimizing the transmission route.

[0437] Step 7:

[0438] Users experience the visualized scenario using a terminal and necessary VR / AR devices (e.g., VR headsets). Users can see specific scenes in which customers use the product in a 360-degree field of view, thereby intuitively understanding the reasons for customers' choices and behavioral patterns.

[0439] Each of these steps allows companies to gain a deeper understanding of the psychology of their target customers, which can be used to develop new businesses and products.

[0440] Example 1

[0441] 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."

[0442] Conventional systems have difficulty intuitively understanding the psychological factors that customers use when selecting a product or service, making it difficult for companies to fully grasp the reasons for their choices and their behavioral patterns. This makes it difficult to develop products and formulate marketing strategies that accurately reflect the needs and preferences of target customers.

[0443] 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.

[0444] In this invention, the server includes: means for inputting information about a product or service and customer attribute data; means for automatically generating reasons why customers select a product or service using a generative AI model; means for describing specific scenes in which customers use the product in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario in virtual reality or augmented reality using 3D modeling technology; and means for users to experience the visualized scenario using a virtual reality or augmented reality device. This allows companies to intuitively understand the selection reasons and behavioral patterns of target customers and make effective decisions in new business and product development.

[0445] "Product or service information" refers to detailed data about a specific product or service, such as product name, features, and price.

[0446] "Customer attribute data" is information about the personal characteristics of target customers, such as age, gender, cultural background, lifestyle, and preferences.

[0447] A "generative AI model" is an algorithm that automatically generates reasons why a customer might choose a product or service based on input data.

[0448] "Reasons for choice" are the motivations or reasons why customers choose a particular product or service.

[0449] The "means of describing specific scenes in a novel format" is a process of creating a narrative-like concrete scene in which a customer uses a product based on the generated reasons for selection.

[0450] "3D modeling technology" is the technology of using a computer to generate and manipulate three-dimensional objects.

[0451] "Virtual reality technology" is a technology that provides users with a virtual environment generated using computer simulation.

[0452] "Augmented reality technology" is a technology that overlays computer-generated information onto images of the real world.

[0453] A "virtual reality or augmented reality device" is hardware, such as a headset or smartphone, that allows you to experience virtual reality or augmented reality content.

[0454] A "visualized scenario" is a scene that is visually recreated using 3D modeling techniques and virtual or augmented reality technologies.

[0455] This invention is a system that uses virtual reality (VR) and augmented reality (AR) technologies to intuitively understand the psychological factors that customers consider when selecting a product or service. This system involves a procedure in which a user inputs product information and customer attributes via a terminal, a server generates reasons for selection based on that data, depicts a specific scene, and visualizes the scene using virtual reality or augmented reality technology.

[0456] First, the user uses a terminal to input information about the product or service and target customer attribute data. For example, the terminal has a dedicated input form where the user can enter detailed product features such as "lightweight and breathable" and "modern design" as well as customer attributes such as "young people aged 18-25, sports enthusiasts, male." This data is then sent to a server via the Internet.

[0457] Next, the server uses a generative AI model (e.g., OpenAI GPT-4) to analyze the received product information and customer attribute data and automatically generate reasons why the target customer would choose the product. This generative AI model takes into account customer attributes such as cultural background, age, and gender, and generates reasons for selection such as "the design is modern and popular with friends," "it's comfortable when jogging," and "it's recommended by famous athletes."

[0458] The server then uses the generated reasons for selection to create a story in which the customer uses the product. For example, a scenario called "Morning Jogging Scene" could be created, depicting a young sports enthusiast enjoying a jog in their new sneakers, with comments of praise from friends. The created scenario is stored in the server's database.

[0459] The server then performs 3D modeling based on this scene and generates VR / AR content using a 3D modeling platform such as Unreal Engine or Unity. The created VR / AR content is visualized in a 360-degree field of view and can be experienced by users using a VR headset or AR-enabled device.

[0460] Finally, users can experience visualized scenarios using virtual or augmented reality devices, helping them intuitively understand the reasons and context behind customers' product or service choices.

[0461] As a concrete example, the process for a newly developed sports sneaker is as follows:

[0462] 1. The user enters details about the sports sneakers, such as "lightweight and breathable" and "modern design," into the input form on the device, and sets the target customers as "young people aged 18-25, sports enthusiasts, males."

[0463] 2. The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0464] 3. The server creates a novel-style depiction of a "morning jogging scene." The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of effortless running and complimentary comments from friends.

[0465] 4. The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, the user can intuitively understand the specific situation based on the reasons for their choice.

[0466] An example prompt is:

[0467] "Generate reasons why young people aged 18-25, sports enthusiasts, should choose a new lightweight, breathable sneaker. Consider the comfort they feel while jogging, the praise they get from friends, and endorsements by famous athletes."

[0468] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0469] Step 1: The user enters product information and customer attributes.

[0470] The user enters product information (e.g., product name, features, price) and customer attribute data (e.g., age, gender, cultural background, lifestyle, preferences) into a dedicated input form on the device. For example, the user might enter "lightweight and breathable" and "modern design" as product features, and set "young people aged 18-25, sports enthusiasts" as target customers. The input data is sent from the user's device to the server. The input here is basic information about the product or service and information based on the customer's attributes.

[0471] Step 2: The server generates the selection reasons using the generative AI model.

[0472] The server receives the product information and customer attribute data sent from the device. The received data is input into a generative AI model, which then performs analysis based on that data. The generative AI model (e.g., GPT-4) generates reasons why the target customer would choose the product, taking into account the customer's cultural background, age, gender, and other factors. The output of this step is a selection reason, such as "The design is modern and popular with friends," "It's comfortable for jogging," or "It's recommended by a famous athlete."

[0473] Step 3: The server describes the scene in novel form.

[0474] The server uses the generated reasons for selection to describe in a novel-like format a specific scene in which the customer uses the product. For example, it creates a scenario called "Morning Jogging Scene" and describes a story in which a young sports enthusiast puts on new sneakers and enjoys jogging, receiving praise from friends. This created scene is saved in a database on the server. The input is the generated reasons for selection, and the output is the described scenario in a novel-like format.

[0475] Step 4: The server visualizes the scenario using 3D modeling techniques.

[0476] The server performs 3D modeling based on the saved scenario. This task typically uses a 3D modeling platform such as Unreal Engine or Unity. The server models each element of the scenario in 3D and converts it into virtual reality (VR) or augmented reality (AR) content. The output is visualized VR / AR content with a 360-degree field of view.

[0477] Step 5: The user experiences the visualized scenario using the VR / AR device.

[0478] The user experiences the VR / AR content generated by the server using a VR headset or an AR-compatible device. For example, the user can wear the headset and experience a jogging scene with a 360-degree field of view. The visualized scene helps customers intuitively understand the reasons for selecting a product and the usage experience. The input of this step is the VR / AR content, and the output is the user's understanding as an experience.

[0479] Through these steps, the system extracts the reasons why customers choose a product or service, and based on that, it can depict specific scenes and visualize them using virtual reality and augmented reality technology, allowing companies to intuitively understand the reasons and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development.

[0480] (Application example 1)

[0481] 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."

[0482] In recent years, responding to the diversifying needs of consumers has required a deep understanding of the reasons for their product and service selection, and appropriate marketing. Traditional methods rely on surveys and data analysis, but these alone have the problem of not being able to fully grasp customers' psychological factors and purchasing motivations. Furthermore, physical stores have limited means of visually appealing products, and online shopping presents challenges, making it difficult for users to experience the texture and feel of a product. In response, a new system is needed that provides an intuitive, interactive purchasing experience and deeply understands the reasons for customers' choices.

[0483] 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.

[0484] In this invention, the server includes: a means for generating reasons for a customer's selection of a product or service; a means for describing a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; and a means for visualizing the described scenario using virtual reality or augmented reality technology and allowing the user to experience it in a virtual environment. This allows customers to intuitively and experientially understand their reasons for selecting a product or service and their purchasing motivations, making it easier for companies to understand customers' psychological factors. Furthermore, product experiences in a virtual environment allow users to simulate the texture and feel of the product, thereby solving challenges in online shopping.

[0485] "Customer" means any person who purchases or uses goods or services.

[0486] "Goods or services" means any item or activity that a consumer purchases or uses.

[0487] "Reasons for choice" are the factors and motivations behind a customer's selection of a particular product or service.

[0488] "Means for generating" refers to a system or method for generating information such as reasons for selection based on specific data or algorithms.

[0489] A "scene" is a representation or depiction of a particular situation or setting.

[0490] "Novel form" is a technique of describing specific scenes in the form of a narrative or story.

[0491] "Virtual reality technology" is a technology that allows users to experience a three-dimensional virtual environment generated by a computer.

[0492] "Augmented reality technology" is a technology that adds digital information to visual information from the real world and displays it.

[0493] A "visualization tool" is a system or method for converting information or data into a visible form and displaying it.

[0494] "Cultural background" refers to the totality of traditions, customs, values, etc. in a particular society or community.

[0495] "Gender" is the biological or social classification of male or female.

[0496] An "age group" is a group of people that falls into a particular age range.

[0497] "Customer attributes" are information or characteristics that categorize customers into specific groups.

[0498] "360-degree visualization" is a technology that provides visual information in all directions, allowing users to see in any direction.

[0499] A "virtual environment" is a computer-generated imaginary world or space.

[0500] "Means of experience" are methods and devices that allow users to actually experience the virtual environment.

[0501] "Checking out the details" is the act of gaining a more detailed understanding of a particular subject.

[0502] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers experience when selecting a product or service. This system operates as follows between a server, a terminal, and a user.

[0503] 1. System Configuration and Hardware / Software

[0504] Hardware:

[0505] VR-compatible head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0506] High-performance smartphone

[0507] software:

[0508] Unity Engine

[0509] OpenAI GPT-4 (generative AI model)

[0510] 3D modeling tools (e.g. Blender, Maya)

[0511] 2. Program Processing

[0512] User input phase:

[0513] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.), and this data is sent from the terminal to the server.

[0514] AI model generation phase:

[0515] Based on the received data, the server uses a generative AI model (OpenAI GPT-4) to automatically generate reasons why the target customer would select the product. The generative AI model takes into account customer attributes such as cultural background, gender, and age group to provide multiple reasons for selection. Examples of prompt sentences include the following:

[0516] Example prompt:

[0517] "Please tell us why young people aged 18-25 and sports enthusiasts choose sneakers."

[0518] Scenario Description Phase:

[0519] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer would use the product. The scenario is written in a narrative style and focuses on the customer's daily life and specific situations. For example, it could describe in detail a scene in which the customer enjoys a morning jog wearing new sneakers.

[0520] VR / AR visualization phase:

[0521] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0522] 3. Specific Examples

[0523] For example, if we were to look at a newly developed sports sneaker, the process would look something like this:

[0524] 1. User Input Phase

[0525] Users input information about sports sneakers, such as "lightweight and breathable" and "modern design," into the device, and set their target customers as "young people aged 18-25, sports enthusiasts."

[0526] 2. AI model generation phase

[0527] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0528] 3. Scenario description phase

[0529] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0530] 4. VR / AR visualization phase

[0531] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this scene through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0532] As described above, this invention is a system that deeply understands the psychological factors of customers and makes it possible to intuitively grasp the reasons for customers' choices through interactive experiences.

[0533] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0534] Step 1:

[0535] User Input Phase

[0536] The user uses a terminal to input product information (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This input data is sent from the terminal to the server. Specifically, the user fills in the necessary information in the application's input form and presses the "Submit" button, which transfers the data to the server.

[0537] Input: Product information, target customer attributes

[0538] Output: The input data sent to the server

[0539] Step 2:

[0540] AI model generation phase

[0541] The server receives the data sent in step 1 and uses a generative AI model (OpenAI GPT-4) to generate reasons why customers would select a product. The server creates a prompt based on the received customer attribute data and inputs the prompt into the generative AI model to generate reasons for selection. As a specific example, a prompt such as "Please tell us the reasons why young people aged 18-25 who are sports enthusiasts would choose these sneakers" is created and input into the AI ​​model.

[0542] Input: Customer attribute data, prompt statement

[0543] Output: Generated selection reasons

[0544] Step 3:

[0545] Scenario description phase

[0546] Based on the reasons for selection generated in step 2, the server creates a novel-style scenario in which the target customer would use the product. A narrative scenario is created based on the reasons for selection obtained from the generative AI model. The specific scenario is depicted focusing on the customer's daily life or a specific situation. For example, a scene in which a user puts on new sneakers and enjoys a morning jog can be depicted in novel form.

[0547] Input: Generated selection reasons

[0548] Output: Depicted scenario

[0549] Step 4:

[0550] VR / AR visualization phase

[0551] The server uses 3D modeling technology to convert the scenario depicted in step 3 into VR / AR content. Using the Unity engine, the server creates 3D models of each element of the depicted scenario and converts them into a format that can be displayed in the virtual environment. Finally, the visualized scenario can be experienced with a 360-degree field of view. The user puts on a VR headset and experiences the scenario in the virtual environment.

[0552] Input: Depicted scenario

[0553] Output: VR / AR content

[0554] Through this process, users can intuitively and experientially understand the reasons for choosing a product, and companies can gain a deeper understanding of the psychological factors behind their customers.

[0555] 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.

[0556] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers use when selecting a product or service with an emotion engine that recognizes the user's emotions. This system automatically generates reasons why a customer might choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology. The emotion engine also recognizes the user's emotions in real time, dynamically adjusting the content of the scenario and the VR / AR display based on the results.

[0557] User Input Phase

[0558] Step 1: Enter product information and customer attributes

[0559] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[0560] AI model generation phase

[0561] Step 2: Generate reasons for selection

[0562] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0563] Scenario description phase

[0564] Step 3: Writing in fiction

[0565] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[0566] VR / AR visualization phase

[0567] Step 4: Visualize the scenario

[0568] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0569] Introducing the Emotion Engine

[0570] Step 5: Activating the Emotion Engine

[0571] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions and tone of voice, and transmits the data in real time to the emotion engine, which then analyzes this data and recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.).

[0572] Step 6: Dynamically adjust the scenario

[0573] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server will change the scenario to explain it more clearly. If the emotion of joy is recognized, the server will add more interesting scenes to enrich the user's experience.

[0574] Step 7: Optimize the user experience

[0575] Users can continuously enjoy tailored scenarios and VR / AR experiences, providing an experience optimized for their emotions and allowing users to gain a more intuitive and deeper understanding of customer psychology.

[0576] Specific examples

[0577] The following process is performed on a newly developed sports sneaker.

[0578] 1. The user enters information into the device

[0579] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[0580] 2. The server generates the selection reason

[0581] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0582] 3. The server describes the scenario

[0583] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0584] 4. The server generates the VR / AR content

[0585] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0586] 5. Introducing the Emotion Engine

[0587] While the user is experiencing the jogging scene using a VR headset, the device recognizes the user's emotions in real time. The emotion engine analyzes the user's reactions (e.g., surprise or satisfaction) and sends the analysis results to the server.

[0588] 6. Dynamically adjust scenarios and VR / AR experiences

[0589] Based on the results of the emotion engine, the server dynamically adjusts the scenario and VR / AR content to optimize the user experience. For example, if the user feels surprised, it adds more interesting information or scenes.

[0590] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development, and to provide optimal experiences based on user emotions.

[0591] The processing flow will be explained below.

[0592] Step 1:

[0593] The user inputs product and customer attribute information into the terminal. Product information includes the product name, features, and price, and customer attributes include age group, gender, cultural background, lifestyle, and preferences. This information is sent from the terminal to the server.

[0594] Step 2:

[0595] The server analyzes the product and customer attribute data received from the terminal, automatically checking for missing or incorrect data and establishing standards for accurate data analysis.

[0596] Step 3:

[0597] The server then launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why target customers would choose a product. For example, it generates reasons why young sports enthusiasts choose sneakers, such as "casual and modern design," "comfortable for jogging," and "recommended by friends and influencers."

[0598] Step 4:

[0599] Based on the generated reasons for selection, the server creates a narrative depiction of a specific scenario in which the target customer uses the product, such as a young sports enthusiast putting on a new pair of sneakers during a morning jog and feeling pleased with their comfort.

[0600] Step 5:

[0601] The server converts the depicted scenario into virtual reality (VR) or augmented reality (AR) content using 3D modeling technology. To realistically recreate the scene, it generates a 3D model based on the scenario and its behavior.

[0602] Step 6:

[0603] The server then transmits the completed VR / AR content to the user's device. The server compresses large amounts of data and optimizes the transmission route to deliver the data efficiently.

[0604] Step 7:

[0605] Users can use a terminal and a VR / AR device (e.g., a VR headset) to experience a visualized scenario, allowing them to experience specific scenes in which customers use the product in a 360-degree field of view and intuitively understand the reasons for their choices.

[0606] Step 8:

[0607] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions, tone of voice, and other data, and sends the data to the emotion engine in real time.

[0608] Step 9:

[0609] The emotion engine recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.) in real time and sends the analysis results to the server, where the user's emotions are classified in detail and the type of reaction is understood.

[0610] Step 10:

[0611] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server changes the scenario to make it easier to understand, and if the user is satisfied, the server adds more interesting scenes.

[0612] Step 11:

[0613] Users can enjoy tailored scenarios and VR / AR experiences continuously, and the emotionally optimized experience provides users with a deeper understanding.

[0614] Through all these steps, companies can accurately understand the reasons for target customers' choices and behavioral patterns, allowing them to make effective decisions in new business and product development. Furthermore, optimizing user experience based on emotions allows for more effective customer understanding.

[0615] Example 2

[0616] 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."

[0617] Today's consumers are diverse, and there are many psychological factors that influence their product and service choices. Traditional marketing methods make it difficult to accurately grasp consumer psychology and accurately analyze the reasons for product selection. Furthermore, there were limited ways to describe and visualize specific scenes from the customer's perspective, resulting in an insufficient user experience. Furthermore, there was a lack of a way to optimize the experience based on user emotions in real time. This made it difficult for companies to understand their customers' true needs and develop effective marketing strategies.

[0618] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for generating reasons why a customer selects a product or service; means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario using virtual reality or augmented reality technology; and means for dynamically adjusting the scenario and virtual reality or augmented reality content using an emotion engine that recognizes the user's emotions. This allows users to have a more intuitive and deeper understanding of customer psychology, and companies to gain a deeper understanding of the selection reasons and behavioral patterns of target customers, enabling them to make effective decisions in new business ventures and product development. It also allows for the provision of an optimal experience based on the user's emotions.

[0619] "Customer" means a person who purchases or uses goods or services.

[0620] "Goods" refers to tangible objects intended for purchase by consumers.

[0621] "Service" refers to an intangible provision intended for consumer enjoyment.

[0622] "Reasons for choice" refers to the reasons and motivations that customers have when choosing a particular product or service.

[0623] "Novel form" refers to a method of structuring text in a narrative style.

[0624] "Virtual reality technology" refers to technology that allows users to experience a virtual environment generated by a computer.

[0625] "Augmented reality technology" refers to technology that displays digital information overlaid on the real environment.

[0626] "Visualization" refers to displaying information in a visually easy-to-read manner.

[0627] "User" refers to a person who uses a system or service.

[0628] An "emotion engine" refers to technology that recognizes the user's emotional state and controls the system's behavior based on the results.

[0629] "Dynamic adjustment" refers to changing the content in real time according to the situation.

[0630] A "prompt" refers to the text of a question or instruction that is input into a generative AI model.

[0631] A "generative AI model" refers to an artificial intelligence model that generates an output for a specific input based on a large amount of data.

[0632] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service with an emotion engine that recognizes the user's emotions. This system is implemented using multiple hardware and software components.

[0633] First, the user uses a terminal to input information about the product or service (e.g., product name, features, price, etc.), as well as the attributes of the target customer (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server. At this stage, the user uses an input interface (e.g., a web form).

[0634] The server uses a generative AI model based on the received data to automatically generate reasons why the target customer would choose a product. This generative AI model is trained to provide multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0635] (Example of a prompt)

[0636] "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[0637] Next, the server uses the generated reasons for selection to create a story-like scenario in which the target customer would use the product, in a novel format. The scenario is then saved in a database using a text generation engine.

[0638] The server then converts the scenario described in the novel format into VR / AR content using 3D modeling tools (e.g., Blender, Unity). The visualized scenario can be experienced through devices such as headsets.

[0639] When a user experiences generated content using a VR / AR headset, the device uses its built-in cameras and sensors to recognize the user's emotions (e.g., joy, surprise, confusion, etc.) in real time. The emotion engine analyzes this data and recognizes the user's emotional state.

[0640] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server adds detailed explanations and changes the scene to make it easier to understand. The user can continue to enjoy the adjusted scenario and VR / AR experience.

[0641] As a concrete example, the following steps are performed for a newly developed pair of sports sneakers. The user enters product information into the device, such as "lightweight and breathable" and "modern design," and sets the target customer as "young people aged 18-25, sports enthusiasts." The server uses a generative AI model to automatically generate reasons why young sports enthusiasts would choose the sneakers, and based on the generated reasons, describes a "morning jogging scene" in novel form. The server models the scenario in 3D and visualizes it using virtual reality technology, which the user experiences through a VR headset. During the experience, the device analyzes the user's emotions in real time, and the emotion engine dynamically adjusts the scenario and VR / AR content based on the results. This system allows companies to deeply understand customer reasons for choice and behavioral patterns, allowing them to provide optimal experiences based on the user's emotions.

[0642] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0643] Step 1:

[0644] The user logs in to the device and enters product or service information. The input is sent from the device to the server. At this stage, the input data includes the product name, features, price, and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). The device converts the input data into JSON format and sends it to the server as a request.

[0645] Input: Product information and customer attribute information

[0646] Output: Send data to the server

[0647] Specific behavior:

[0648] Enter product information: Example: "Lightweight and breathable sports sneakers with a modern design. Price: 8,000 yen"

[0649] Enter customer attributes: e.g. "Young people aged 18-25, sports enthusiasts"

[0650] Data transmission: The device converts the data into JSON format and sends it to the server.

[0651] Step 2:

[0652] The server sends prompts to the generative AI model based on the received data. The generative AI model generates reasons why the target customer would choose the product based on a pre-trained dataset. The server receives the generated reasons and stores them in its internal database.

[0653] Input: JSON data of product information and customer attributes

[0654] Output: Reason for selection

[0655] Specific behavior:

[0656] Generate and send prompts: e.g., "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[0657] Receive responses from the generative AI model: e.g., "The design is modern and popular with friends," "It's comfortable for jogging," "It's recommended by famous athletes."

[0658] Step 3:

[0659] The server then depicts specific scenes in a novel format based on the generated reasons for the choices. The scenes are created using a text generation engine in a narrative style, focusing on the user's daily life or specific situations. The created scenarios are stored in the server's database.

[0660] Input: Reason for selection

[0661] Output: Novel-style scenario

[0662] Specific behavior:

[0663] Scenario generation: Using a text generation engine

[0664] Example: "A morning jogging scene. A young sports enthusiast enjoys jogging in lightweight, breathable sneakers. Includes comments of praise from friends."

[0665] Step 4:

[0666] The server generates VR / AR content using a 3D modeling tool based on the created scenario, constructs 3D models and action sequences based on the scenario, creates VR / AR content, and prepares it for transmission to the device.

[0667] Input: Novel-style scenario

[0668] Output: VR / AR content

[0669] Specific behavior:

[0670] Use of 3D modeling tools (e.g. Blender, Unity)

[0671] Model generation: jogging characters and jogging paths

[0672] Scene rendering: morning scenery and friend interaction scenes

[0673] Step 5:

[0674] While a user wears a VR / AR headset and experiences content, the device uses its built-in cameras and sensors to collect emotional data in real time. The emotion engine analyzes the collected data and recognizes the user's emotional state.

[0675] Input: User experience data (facial expressions, tone of voice, etc.)

[0676] Output: User's emotional state

[0677] Specific behavior:

[0678] Use of face recognition algorithms (e.g. OpenCV)

[0679] Use of voice tone analysis algorithms (e.g., Google Cloud Speech-to-Text)

[0680] Step 6:

[0681] The server dynamically adjusts the scenario and VR / AR content based on the user's emotional state as recognized by the emotion engine. For example, if the user is confused, it adds detailed explanations and changes the scene to make it easier to understand. The adjusted scenario and content are then regenerated and sent to the device in real time.

[0682] Input: User's emotional state

[0683] Output: Adjusted scenarios and VR / AR content

[0684] Specific behavior:

[0685] Scenario change: Dynamic adjustment based on the analysis results of the emotion engine

[0686] For example, "If users are confused, add detailed explanations."

[0687] Step 7:

[0688] Users can continuously enjoy the tailored scenario and VR / AR experience. The device continuously collects emotional data and sends feedback to the server until the user experience ends, providing an experience optimized for the user's emotions.

[0689] Input: Tailored scenarios and VR / AR content

[0690] Output: Optimized user experience

[0691] Specific behavior:

[0692] Continuously monitoring user experience

[0693] Continued data collection: Emotion data is collected periodically until the end of the user experience and sent to the server

[0694] (Application example 2)

[0695] 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."

[0696] Conventional product or service selection support systems for autonomous vehicles have difficulty fully understanding the user's reasons for selection and psychological factors, and have been unable to provide an experience optimized for the user's emotions. As a result, it has been difficult for users to intuitively understand the value of products and services, and there have been issues in increasing their desire to purchase.

[0697] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating reasons why a customer selects a product or service, means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection, means for visualizing the depicted scenario using virtual reality or augmented reality technology, an emotion engine for recognizing the customer's emotions in real time, and means for dynamically adjusting the content of the scenario and the virtual reality or augmented reality display based on the customer's emotions recognized by the emotion engine. This makes it easier for the user to understand the reasons for their selection and provides an optimal experience based on their emotions.

[0698] "Reasons for choosing a product or service" refers to the motives and criteria that customers consider when choosing a particular product or service.

[0699] "Description in novel form" is a method of writing a story about a specific scene from the customer's perspective based on the reasons for their choice.

[0700] "Virtual reality or augmented reality visualization" refers to a technology that transforms a scenario depicted in a novel format into an experiential form in three-dimensional space and displays it through a virtual reality (VR) or augmented reality (AR) device.

[0701] The "emotion engine that recognizes customer emotions in real time" is a system that uses sensors and cameras to analyze the customer's facial expressions and voice to grasp the customer's emotional state in real time.

[0702] "Dynamic adjustment" refers to a method for changing scenarios and virtual or augmented reality content on the fly based on perceived customer sentiment.

[0703] "Customer attributes such as cultural background, gender, age group, etc." refers to individual characteristics that influence the reasons for a customer's choice, such as their cultural background, gender, age, and lifestyle.

[0704] This invention relates to a selection support system for autonomous vehicles, which generates reasons for customers to select a vehicle, describes specific scenes in a novel format based on those reasons, and visualizes them using virtual reality (VR) or augmented reality (AR) technology. Furthermore, it uses an emotion engine that recognizes customer emotions in real time, dynamically adjusting the scenario and VR / AR display.

[0705] To realize this system, the following hardware and software are used.

[0706] 1. Hardware

[0707] Autonomous vehicle console: The interface for receiving user input and operating the system.

[0708] VR headset (e.g., Oculus Quest 2): Used by users to experience virtual reality scenarios.

[0709] Built-in cameras and sensors (e.g., a vehicle's dashboard camera): Detects the user's facial expressions and voice and sends data to the emotion engine.

[0710] 2. Software

[0711] Emotion recognition software (e.g., Affectiva SDK): Analyzes and recognizes the user's emotional state in real time.

[0712] Generative AI models (e.g., GPT-4): Automatically generate reasons for choosing a vehicle based on customer attributes and input data.

[0713] 3D modeling software (e.g. Blender): Convert the generated scenario into a 3D model and create VR / AR content.

[0714] Program processing and its explanation

[0715] User Input Phase

[0716] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal, and this data is sent to the server.

[0717] AI model generation phase

[0718] Based on the data sent, the server uses a generative AI model such as GPT-4 to automatically generate reasons why the customer chose the vehicle, such as "because it's environmentally friendly" or "because I want to try new technology."

[0719] Scenario description phase

[0720] Based on the generated reasons for selection, the server describes specific scenes from the customer's perspective in a novel format, such as "commuting in an urban area" or "driving with family."

[0721] VR / AR visualization phase

[0722] The depicted scenarios are converted into VR / AR content using 3D modeling software such as Blender, and users can experience the specific situations created through VR headsets such as the Oculus Quest 2.

[0723] Introducing the Emotion Engine

[0724] While a user is experiencing a scene using a VR headset, the built-in camera and sensors analyze the user's facial expressions and voice, and emotion recognition software such as the Affectiva SDK sends the data to an emotion engine, which then analyzes this data to understand the user's emotional state in real time.

[0725] Dynamically adjusting scenarios

[0726] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is surprised, it adds more interesting information. If the user has difficulty understanding, it adds detailed explanations.

[0727] Examples of prompt statements

[0728] For example, a prompt to generate a scenario for a new autonomous electric vehicle might look like this:

[0729] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[0730] These systems and prompts help users understand the reasons for their choices, providing an optimal emotional experience.

[0731] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0732] Step 1:

[0733] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal. The input data is sent to the server. Specifically, the user enters the data using an interface such as a touchscreen or keyboard, and then presses the send button, which sends the data to the server.

[0734] Step 2:

[0735] Based on the data received by the server, a generative AI model (e.g., GPT-4) is used to automatically generate reasons why a customer should choose a vehicle. The input is vehicle information and customer attributes, and the output is multiple reasons for selection. Specifically, the server analyzes the received data and generates reasons for selection by providing them as prompts to the generative AI model. In this case, the prompts are in the following format:

[0736] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[0737] Step 3:

[0738] Based on the generated reasons for selection, the server describes a specific scene in novel form from the customer's perspective. The input is the reason for selection, and the output is a novel-style text describing a specific scene. Specifically, the server uses an AI model to generate a story-like scenario from the reasons for selection. This scenario could be, for example, a "commuting scene in an urban area" or a "drive scene with family."

[0739] Step 4:

[0740] The server converts the depicted scenario into VR / AR content using 3D modeling software (e.g., Blender). The input is a novel-style scenario, and the output is VR / AR content. Specifically, the server analyzes the scenario and converts its contents into a 3D model. The user can experience this model through a VR headset.

[0741] Step 5:

[0742] While a user experiences a scenario using a VR headset, the built-in camera and sensors detect the user's facial expressions and voice and send the data to an emotion engine (e.g., Affectiva SDK). The input is the user's facial and voice data, and the output is an analyzed emotional state. Specifically, the camera and sensors collect data and send it to the emotion engine in real time for analysis.

[0743] Step 6:

[0744] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. The input is the analyzed emotional state, and the output is the adjusted content. Specifically, the server analyzes the emotional data and adjusts the scenario. For example, if the user is surprised, it adds more interesting information. Also, if the content is difficult to understand, it adds detailed explanations.

[0745] This helps users understand the reasons behind their choices and provides an optimal emotional experience.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] [Third embodiment]

[0750] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0751] 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.

[0752] 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).

[0753] 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.

[0754] 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.

[0755] 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).

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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."

[0762] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service. This system automatically generates reasons why customers choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology.

[0763] User Input Phase

[0764] Step 1: Enter product information and customer attributes

[0765] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[0766] AI model generation phase

[0767] Step 2: Generate reasons for selection

[0768] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0769] Scenario description phase

[0770] Step 3: Writing in fiction

[0771] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[0772] VR / AR visualization phase

[0773] Step 4: Visualize the scenario

[0774] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0775] Specific examples

[0776] The following process is performed on a newly developed sports sneaker.

[0777] 1. The user enters information into the device

[0778] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[0779] 2. The server generates the selection reason

[0780] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0781] 3. The server describes the scenario

[0782] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0783] 4. The server generates the VR / AR content

[0784] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0785] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions regarding new business ventures and product development.

[0786] The processing flow will be explained below.

[0787] Step 1:

[0788] The user inputs product information and customer attributes into the terminal. Product information includes the product name, features, price, etc., while customer attributes include age group, gender, cultural background, lifestyle, preferences, etc. This input data is sent from the terminal to the server.

[0789] Step 2:

[0790] The server receives the product information and customer attribute data sent from the terminal. It analyzes the received data and uses it as the basis for generating the customer's reasons for selection. At this time, it automatically checks for missing data or input errors.

[0791] Step 3:

[0792] The server launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why customers would choose a product. The model outputs multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0793] Step 4:

[0794] Based on the generated reasons for selection, the server creates a fictional scenario in which a customer uses a particular product. For example, it depicts a young sports enthusiast putting on new sneakers during a morning jog. At this time, the generated reasons for selection are appropriately incorporated into the scenario.

[0795] Step 5:

[0796] The server uses 3D modeling technology to convert the depicted scenario into VR / AR content. It generates detailed 3D models and their behavior based on the scenario, constructing a virtual reality or augmented reality scene.

[0797] Step 6:

[0798] The server then transmits the completed VR / AR content to the user's device, which includes compressing large amounts of data and optimizing the transmission route.

[0799] Step 7:

[0800] Users experience the visualized scenario using a terminal and necessary VR / AR devices (e.g., VR headsets). Users can see specific scenes in which customers use the product in a 360-degree field of view, thereby intuitively understanding the reasons for customers' choices and behavioral patterns.

[0801] Each of these steps allows companies to gain a deeper understanding of the psychology of their target customers, which can be used to develop new businesses and products.

[0802] Example 1

[0803] 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."

[0804] Conventional systems have difficulty intuitively understanding the psychological factors that customers use when selecting a product or service, making it difficult for companies to fully grasp the reasons for their choices and their behavioral patterns. This makes it difficult to develop products and formulate marketing strategies that accurately reflect the needs and preferences of target customers.

[0805] 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.

[0806] In this invention, the server includes: means for inputting information about a product or service and customer attribute data; means for automatically generating reasons why customers select a product or service using a generative AI model; means for describing specific scenes in which customers use the product in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario in virtual reality or augmented reality using 3D modeling technology; and means for users to experience the visualized scenario using a virtual reality or augmented reality device. This allows companies to intuitively understand the selection reasons and behavioral patterns of target customers and make effective decisions in new business and product development.

[0807] "Product or service information" refers to detailed data about a specific product or service, such as product name, features, and price.

[0808] "Customer attribute data" is information about the personal characteristics of target customers, such as age, gender, cultural background, lifestyle, and preferences.

[0809] A "generative AI model" is an algorithm that automatically generates reasons why a customer might choose a product or service based on input data.

[0810] "Reasons for choice" are the motivations or reasons why customers choose a particular product or service.

[0811] The "means of describing specific scenes in a novel format" is a process of creating a narrative-like concrete scene in which a customer uses a product based on the generated reasons for selection.

[0812] "3D modeling technology" is the technology of using a computer to generate and manipulate three-dimensional objects.

[0813] "Virtual reality technology" is a technology that provides users with a virtual environment generated using computer simulation.

[0814] "Augmented reality technology" is a technology that overlays computer-generated information onto images of the real world.

[0815] A "virtual reality or augmented reality device" is hardware, such as a headset or smartphone, that allows you to experience virtual reality or augmented reality content.

[0816] A "visualized scenario" is a scene that is visually recreated using 3D modeling techniques and virtual or augmented reality technologies.

[0817] This invention is a system that uses virtual reality (VR) and augmented reality (AR) technologies to intuitively understand the psychological factors that customers consider when selecting a product or service. This system involves a procedure in which a user inputs product information and customer attributes via a terminal, a server generates reasons for selection based on that data, depicts a specific scene, and visualizes the scene using virtual reality or augmented reality technology.

[0818] First, the user uses a terminal to input information about the product or service and target customer attribute data. For example, the terminal has a dedicated input form where the user can enter detailed product features such as "lightweight and breathable" and "modern design" as well as customer attributes such as "young people aged 18-25, sports enthusiasts, male." This data is then sent to a server via the Internet.

[0819] Next, the server uses a generative AI model (e.g., OpenAI GPT-4) to analyze the received product information and customer attribute data and automatically generate reasons why the target customer would choose the product. This generative AI model takes into account customer attributes such as cultural background, age, and gender, and generates reasons for selection such as "the design is modern and popular with friends," "it's comfortable when jogging," and "it's recommended by famous athletes."

[0820] The server then uses the generated reasons for selection to create a story in which the customer uses the product. For example, a scenario called "Morning Jogging Scene" could be created, depicting a young sports enthusiast enjoying a jog in their new sneakers, with comments of praise from friends. The created scenario is stored in the server's database.

[0821] The server then performs 3D modeling based on this scene and generates VR / AR content using a 3D modeling platform such as Unreal Engine or Unity. The created VR / AR content is visualized in a 360-degree field of view and can be experienced by users using a VR headset or AR-enabled device.

[0822] Finally, users can experience visualized scenarios using virtual or augmented reality devices, helping them intuitively understand the reasons and context behind customers' product or service choices.

[0823] As a concrete example, the process for a newly developed sports sneaker is as follows:

[0824] 1. The user enters details about the sports sneakers, such as "lightweight and breathable" and "modern design," into the input form on the device, and sets the target customers as "young people aged 18-25, sports enthusiasts, males."

[0825] 2. The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0826] 3. The server creates a novel-style depiction of a "morning jogging scene." The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of effortless running and complimentary comments from friends.

[0827] 4. The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, the user can intuitively understand the specific situation based on the reasons for their choice.

[0828] An example prompt is:

[0829] "Generate reasons why young people aged 18-25, sports enthusiasts, should choose a new lightweight, breathable sneaker. Consider the comfort they feel while jogging, the praise they get from friends, and endorsements by famous athletes."

[0830] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0831] Step 1: The user enters product information and customer attributes.

[0832] The user enters product information (e.g., product name, features, price) and customer attribute data (e.g., age, gender, cultural background, lifestyle, preferences) into a dedicated input form on the device. For example, the user might enter "lightweight and breathable" and "modern design" as product features, and set "young people aged 18-25, sports enthusiasts" as target customers. The input data is sent from the user's device to the server. The input here is basic information about the product or service and information based on the customer's attributes.

[0833] Step 2: The server generates the selection reasons using the generative AI model.

[0834] The server receives the product information and customer attribute data sent from the device. The received data is input into a generative AI model, which then performs analysis based on that data. The generative AI model (e.g., GPT-4) generates reasons why the target customer would choose the product, taking into account the customer's cultural background, age, gender, and other factors. The output of this step is a selection reason, such as "The design is modern and popular with friends," "It's comfortable for jogging," or "It's recommended by a famous athlete."

[0835] Step 3: The server describes the scene in novel form.

[0836] The server uses the generated reasons for selection to describe in a novel-like format a specific scene in which the customer uses the product. For example, it creates a scenario called "Morning Jogging Scene" and describes a story in which a young sports enthusiast puts on new sneakers and enjoys jogging, receiving praise from friends. This created scene is saved in a database on the server. The input is the generated reasons for selection, and the output is the described scenario in a novel-like format.

[0837] Step 4: The server visualizes the scenario using 3D modeling techniques.

[0838] The server performs 3D modeling based on the saved scenario. This task typically uses a 3D modeling platform such as Unreal Engine or Unity. The server models each element of the scenario in 3D and converts it into virtual reality (VR) or augmented reality (AR) content. The output is visualized VR / AR content with a 360-degree field of view.

[0839] Step 5: The user experiences the visualized scenario using the VR / AR device.

[0840] The user experiences the VR / AR content generated by the server using a VR headset or an AR-compatible device. For example, the user can wear the headset and experience a jogging scene with a 360-degree field of view. The visualized scene helps customers intuitively understand the reasons for selecting a product and the usage experience. The input of this step is the VR / AR content, and the output is the user's understanding as an experience.

[0841] Through these steps, the system extracts the reasons why customers choose a product or service, and based on that, it can depict specific scenes and visualize them using virtual reality and augmented reality technology, allowing companies to intuitively understand the reasons and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development.

[0842] (Application example 1)

[0843] 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."

[0844] In recent years, responding to the diversifying needs of consumers has required a deep understanding of the reasons for their product and service selection, and appropriate marketing. Traditional methods rely on surveys and data analysis, but these alone have the problem of not being able to fully grasp customers' psychological factors and purchasing motivations. Furthermore, physical stores have limited means of visually appealing products, and online shopping presents challenges, making it difficult for users to experience the texture and feel of a product. In response, a new system is needed that provides an intuitive, interactive purchasing experience and deeply understands the reasons for customers' choices.

[0845] 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.

[0846] In this invention, the server includes: a means for generating reasons for a customer's selection of a product or service; a means for describing a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; and a means for visualizing the described scenario using virtual reality or augmented reality technology and allowing the user to experience it in a virtual environment. This allows customers to intuitively and experientially understand their reasons for selecting a product or service and their purchasing motivations, making it easier for companies to understand customers' psychological factors. Furthermore, product experiences in a virtual environment allow users to simulate the texture and feel of the product, thereby solving challenges in online shopping.

[0847] "Customer" means any person who purchases or uses goods or services.

[0848] "Goods or services" means any item or activity that a consumer purchases or uses.

[0849] "Reasons for choice" are the factors and motivations behind a customer's selection of a particular product or service.

[0850] "Means for generating" refers to a system or method for generating information such as reasons for selection based on specific data or algorithms.

[0851] A "scene" is a representation or depiction of a particular situation or setting.

[0852] "Novel form" is a technique of describing specific scenes in the form of a narrative or story.

[0853] "Virtual reality technology" is a technology that allows users to experience a three-dimensional virtual environment generated by a computer.

[0854] "Augmented reality technology" is a technology that adds digital information to visual information from the real world and displays it.

[0855] A "visualization tool" is a system or method for converting information or data into a visible form and displaying it.

[0856] "Cultural background" refers to the totality of traditions, customs, values, etc. in a particular society or community.

[0857] "Gender" is the biological or social classification of male or female.

[0858] An "age group" is a group of people that falls into a particular age range.

[0859] "Customer attributes" are information or characteristics that categorize customers into specific groups.

[0860] "360-degree visualization" is a technology that provides visual information in all directions, allowing users to see in any direction.

[0861] A "virtual environment" is a computer-generated imaginary world or space.

[0862] "Means of experience" are methods and devices that allow users to actually experience the virtual environment.

[0863] "Checking out the details" is the act of gaining a more detailed understanding of a particular subject.

[0864] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers experience when selecting a product or service. This system operates as follows between a server, a terminal, and a user.

[0865] 1. System Configuration and Hardware / Software

[0866] Hardware:

[0867] VR-compatible head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0868] High-performance smartphone

[0869] software:

[0870] Unity Engine

[0871] OpenAI GPT-4 (generative AI model)

[0872] 3D modeling tools (e.g. Blender, Maya)

[0873] 2. Program Processing

[0874] User input phase:

[0875] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.), and this data is sent from the terminal to the server.

[0876] AI model generation phase:

[0877] Based on the received data, the server uses a generative AI model (OpenAI GPT-4) to automatically generate reasons why the target customer would select the product. The generative AI model takes into account customer attributes such as cultural background, gender, and age group to provide multiple reasons for selection. Examples of prompt sentences include the following:

[0878] Example prompt:

[0879] "Please tell us why young people aged 18-25 and sports enthusiasts choose sneakers."

[0880] Scenario Description Phase:

[0881] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer would use the product. The scenario is written in a narrative style and focuses on the customer's daily life and specific situations. For example, it could describe in detail a scene in which the customer enjoys a morning jog wearing new sneakers.

[0882] VR / AR visualization phase:

[0883] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0884] 3. Specific Examples

[0885] For example, if we were to look at a newly developed sports sneaker, the process would look something like this:

[0886] 1. User Input Phase

[0887] Users input information about sports sneakers, such as "lightweight and breathable" and "modern design," into the device, and set their target customers as "young people aged 18-25, sports enthusiasts."

[0888] 2. AI model generation phase

[0889] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0890] 3. Scenario description phase

[0891] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0892] 4. VR / AR visualization phase

[0893] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this scene through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0894] As described above, this invention is a system that deeply understands the psychological factors of customers and makes it possible to intuitively grasp the reasons for customers' choices through interactive experiences.

[0895] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0896] Step 1:

[0897] User Input Phase

[0898] The user uses a terminal to input product information (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This input data is sent from the terminal to the server. Specifically, the user fills in the necessary information in the application's input form and presses the "Submit" button, which transfers the data to the server.

[0899] Input: Product information, target customer attributes

[0900] Output: The input data sent to the server

[0901] Step 2:

[0902] AI model generation phase

[0903] The server receives the data sent in step 1 and uses a generative AI model (OpenAI GPT-4) to generate reasons why customers would select a product. The server creates a prompt based on the received customer attribute data and inputs the prompt into the generative AI model to generate reasons for selection. As a specific example, a prompt such as "Please tell us the reasons why young people aged 18-25 who are sports enthusiasts would choose these sneakers" is created and input into the AI ​​model.

[0904] Input: Customer attribute data, prompt statement

[0905] Output: Generated selection reasons

[0906] Step 3:

[0907] Scenario description phase

[0908] Based on the reasons for selection generated in step 2, the server creates a novel-style scenario in which the target customer would use the product. A narrative scenario is created based on the reasons for selection obtained from the generative AI model. The specific scenario is depicted focusing on the customer's daily life or a specific situation. For example, a scene in which a user puts on new sneakers and enjoys a morning jog can be depicted in novel form.

[0909] Input: Generated selection reasons

[0910] Output: Depicted scenario

[0911] Step 4:

[0912] VR / AR visualization phase

[0913] The server uses 3D modeling technology to convert the scenario depicted in step 3 into VR / AR content. Using the Unity engine, the server creates 3D models of each element of the depicted scenario and converts them into a format that can be displayed in the virtual environment. Finally, the visualized scenario can be experienced with a 360-degree field of view. The user puts on a VR headset and experiences the scenario in the virtual environment.

[0914] Input: Depicted scenario

[0915] Output: VR / AR content

[0916] Through this process, users can intuitively and experientially understand the reasons for choosing a product, and companies can gain a deeper understanding of the psychological factors behind their customers.

[0917] 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.

[0918] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers use when selecting a product or service with an emotion engine that recognizes the user's emotions. This system automatically generates reasons why a customer might choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology. The emotion engine also recognizes the user's emotions in real time, dynamically adjusting the content of the scenario and the VR / AR display based on the results.

[0919] User Input Phase

[0920] Step 1: Enter product information and customer attributes

[0921] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[0922] AI model generation phase

[0923] Step 2: Generate reasons for selection

[0924] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0925] Scenario description phase

[0926] Step 3: Writing in fiction

[0927] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[0928] VR / AR visualization phase

[0929] Step 4: Visualize the scenario

[0930] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[0931] Introducing the Emotion Engine

[0932] Step 5: Activating the Emotion Engine

[0933] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions and tone of voice, and transmits the data in real time to the emotion engine, which then analyzes this data and recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.).

[0934] Step 6: Dynamically adjust the scenario

[0935] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server will change the scenario to explain it more clearly. If the emotion of joy is recognized, the server will add more interesting scenes to enrich the user's experience.

[0936] Step 7: Optimize the user experience

[0937] Users can continuously enjoy tailored scenarios and VR / AR experiences, providing an experience optimized for their emotions and allowing users to gain a more intuitive and deeper understanding of customer psychology.

[0938] Specific examples

[0939] The following process is performed on a newly developed sports sneaker.

[0940] 1. The user enters information into the device

[0941] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[0942] 2. The server generates the selection reason

[0943] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[0944] 3. The server describes the scenario

[0945] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[0946] 4. The server generates the VR / AR content

[0947] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[0948] 5. Introducing the Emotion Engine

[0949] While the user is experiencing the jogging scene using a VR headset, the device recognizes the user's emotions in real time. The emotion engine analyzes the user's reactions (e.g., surprise or satisfaction) and sends the analysis results to the server.

[0950] 6. Dynamically adjust scenarios and VR / AR experiences

[0951] Based on the results of the emotion engine, the server dynamically adjusts the scenario and VR / AR content to optimize the user experience. For example, if the user feels surprised, it adds more interesting information or scenes.

[0952] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development, and to provide optimal experiences based on user emotions.

[0953] The processing flow will be explained below.

[0954] Step 1:

[0955] The user inputs product and customer attribute information into the terminal. Product information includes the product name, features, and price, and customer attributes include age group, gender, cultural background, lifestyle, and preferences. This information is sent from the terminal to the server.

[0956] Step 2:

[0957] The server analyzes the product and customer attribute data received from the terminal, automatically checking for missing or incorrect data and establishing standards for accurate data analysis.

[0958] Step 3:

[0959] The server then launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why target customers would choose a product. For example, it generates reasons why young sports enthusiasts choose sneakers, such as "casual and modern design," "comfortable for jogging," and "recommended by friends and influencers."

[0960] Step 4:

[0961] Based on the generated reasons for selection, the server creates a narrative depiction of a specific scenario in which the target customer uses the product, such as a young sports enthusiast putting on a new pair of sneakers during a morning jog and feeling pleased with their comfort.

[0962] Step 5:

[0963] The server converts the depicted scenario into virtual reality (VR) or augmented reality (AR) content using 3D modeling technology. To realistically recreate the scene, it generates a 3D model based on the scenario and its behavior.

[0964] Step 6:

[0965] The server then transmits the completed VR / AR content to the user's device. The server compresses large amounts of data and optimizes the transmission route to deliver the data efficiently.

[0966] Step 7:

[0967] Users can use a terminal and a VR / AR device (e.g., a VR headset) to experience a visualized scenario, allowing them to experience specific scenes in which customers use the product in a 360-degree field of view and intuitively understand the reasons for their choices.

[0968] Step 8:

[0969] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions, tone of voice, and other data, and sends the data to the emotion engine in real time.

[0970] Step 9:

[0971] The emotion engine recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.) in real time and sends the analysis results to the server, where the user's emotions are classified in detail and the type of reaction is understood.

[0972] Step 10:

[0973] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server changes the scenario to make it easier to understand, and if the user is satisfied, the server adds more interesting scenes.

[0974] Step 11:

[0975] Users can enjoy tailored scenarios and VR / AR experiences continuously, and the emotionally optimized experience provides users with a deeper understanding.

[0976] Through all these steps, companies can accurately understand the reasons for target customers' choices and behavioral patterns, allowing them to make effective decisions in new business and product development. Furthermore, optimizing user experience based on emotions allows for more effective customer understanding.

[0977] Example 2

[0978] 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."

[0979] Today's consumers are diverse, and there are many psychological factors that influence their product and service choices. Traditional marketing methods make it difficult to accurately grasp consumer psychology and accurately analyze the reasons for product selection. Furthermore, there were limited ways to describe and visualize specific scenes from the customer's perspective, resulting in an insufficient user experience. Furthermore, there was a lack of a way to optimize the experience based on user emotions in real time. This made it difficult for companies to understand their customers' true needs and develop effective marketing strategies.

[0980] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for generating reasons why a customer selects a product or service; means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario using virtual reality or augmented reality technology; and means for dynamically adjusting the scenario and virtual reality or augmented reality content using an emotion engine that recognizes the user's emotions. This allows users to have a more intuitive and deeper understanding of customer psychology, and companies to gain a deeper understanding of the selection reasons and behavioral patterns of target customers, enabling them to make effective decisions in new business ventures and product development. It also allows for the provision of an optimal experience based on the user's emotions.

[0981] "Customer" means a person who purchases or uses goods or services.

[0982] "Goods" refers to tangible objects intended for purchase by consumers.

[0983] "Service" refers to an intangible provision intended for consumer enjoyment.

[0984] "Reasons for choice" refers to the reasons and motivations that customers have when choosing a particular product or service.

[0985] "Novel form" refers to a method of structuring text in a narrative style.

[0986] "Virtual reality technology" refers to technology that allows users to experience a virtual environment generated by a computer.

[0987] "Augmented reality technology" refers to technology that displays digital information overlaid on the real environment.

[0988] "Visualization" refers to displaying information in a visually easy-to-read manner.

[0989] "User" refers to a person who uses a system or service.

[0990] An "emotion engine" refers to technology that recognizes the user's emotional state and controls the system's behavior based on the results.

[0991] "Dynamic adjustment" refers to changing the content in real time according to the situation.

[0992] A "prompt" refers to the text of a question or instruction that is input into a generative AI model.

[0993] A "generative AI model" refers to an artificial intelligence model that generates an output for a specific input based on a large amount of data.

[0994] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service with an emotion engine that recognizes the user's emotions. This system is implemented using multiple hardware and software components.

[0995] First, the user uses a terminal to input information about the product or service (e.g., product name, features, price, etc.), as well as the attributes of the target customer (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server. At this stage, the user uses an input interface (e.g., a web form).

[0996] The server uses a generative AI model based on the received data to automatically generate reasons why the target customer would choose a product. This generative AI model is trained to provide multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[0997] (Example of a prompt)

[0998] "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[0999] Next, the server uses the generated reasons for selection to create a story-like scenario in which the target customer would use the product, in a novel format. The scenario is then saved in a database using a text generation engine.

[1000] The server then converts the scenario described in the novel format into VR / AR content using 3D modeling tools (e.g., Blender, Unity). The visualized scenario can be experienced through devices such as headsets.

[1001] When a user experiences generated content using a VR / AR headset, the device uses its built-in cameras and sensors to recognize the user's emotions (e.g., joy, surprise, confusion, etc.) in real time. The emotion engine analyzes this data and recognizes the user's emotional state.

[1002] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server adds detailed explanations and changes the scene to make it easier to understand. The user can continue to enjoy the adjusted scenario and VR / AR experience.

[1003] As a concrete example, the following steps are performed for a newly developed pair of sports sneakers. The user enters product information into the device, such as "lightweight and breathable" and "modern design," and sets the target customer as "young people aged 18-25, sports enthusiasts." The server uses a generative AI model to automatically generate reasons why young sports enthusiasts would choose the sneakers, and based on the generated reasons, describes a "morning jogging scene" in novel form. The server models the scenario in 3D and visualizes it using virtual reality technology, which the user experiences through a VR headset. During the experience, the device analyzes the user's emotions in real time, and the emotion engine dynamically adjusts the scenario and VR / AR content based on the results. This system allows companies to deeply understand customer reasons for choice and behavioral patterns, allowing them to provide optimal experiences based on the user's emotions.

[1004] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1005] Step 1:

[1006] The user logs in to the device and enters product or service information. The input is sent from the device to the server. At this stage, the input data includes the product name, features, price, and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). The device converts the input data into JSON format and sends it to the server as a request.

[1007] Input: Product information and customer attribute information

[1008] Output: Send data to the server

[1009] Specific behavior:

[1010] Enter product information: Example: "Lightweight and breathable sports sneakers with a modern design. Price: 8,000 yen"

[1011] Enter customer attributes: e.g. "Young people aged 18-25, sports enthusiasts"

[1012] Data transmission: The device converts the data into JSON format and sends it to the server.

[1013] Step 2:

[1014] The server sends prompts to the generative AI model based on the received data. The generative AI model generates reasons why the target customer would choose the product based on a pre-trained dataset. The server receives the generated reasons and stores them in its internal database.

[1015] Input: JSON data of product information and customer attributes

[1016] Output: Reason for selection

[1017] Specific behavior:

[1018] Generate and send prompts: e.g., "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[1019] Receive responses from the generative AI model: e.g., "The design is modern and popular with friends," "It's comfortable for jogging," "It's recommended by famous athletes."

[1020] Step 3:

[1021] The server then depicts specific scenes in a novel format based on the generated reasons for the choices. The scenes are created using a text generation engine in a narrative style, focusing on the user's daily life or specific situations. The created scenarios are stored in the server's database.

[1022] Input: Reason for selection

[1023] Output: Novel-style scenario

[1024] Specific behavior:

[1025] Scenario generation: Using a text generation engine

[1026] Example: "A morning jogging scene. A young sports enthusiast enjoys jogging in lightweight, breathable sneakers. Includes comments of praise from friends."

[1027] Step 4:

[1028] The server generates VR / AR content using a 3D modeling tool based on the created scenario, constructs 3D models and action sequences based on the scenario, creates VR / AR content, and prepares it for transmission to the device.

[1029] Input: Novel-style scenario

[1030] Output: VR / AR content

[1031] Specific behavior:

[1032] Use of 3D modeling tools (e.g. Blender, Unity)

[1033] Model generation: jogging characters and jogging paths

[1034] Scene rendering: morning scenery and friend interaction scenes

[1035] Step 5:

[1036] While a user wears a VR / AR headset and experiences content, the device uses its built-in cameras and sensors to collect emotional data in real time. The emotion engine analyzes the collected data and recognizes the user's emotional state.

[1037] Input: User experience data (facial expressions, tone of voice, etc.)

[1038] Output: User's emotional state

[1039] Specific behavior:

[1040] Use of face recognition algorithms (e.g. OpenCV)

[1041] Use of voice tone analysis algorithms (e.g., Google Cloud Speech-to-Text)

[1042] Step 6:

[1043] The server dynamically adjusts the scenario and VR / AR content based on the user's emotional state as recognized by the emotion engine. For example, if the user is confused, it adds detailed explanations and changes the scene to make it easier to understand. The adjusted scenario and content are then regenerated and sent to the device in real time.

[1044] Input: User's emotional state

[1045] Output: Adjusted scenarios and VR / AR content

[1046] Specific behavior:

[1047] Scenario change: Dynamic adjustment based on the analysis results of the emotion engine

[1048] For example, "If users are confused, add detailed explanations."

[1049] Step 7:

[1050] Users can continuously enjoy the tailored scenario and VR / AR experience. The device continuously collects emotional data and sends feedback to the server until the user experience ends, providing an experience optimized for the user's emotions.

[1051] Input: Tailored scenarios and VR / AR content

[1052] Output: Optimized user experience

[1053] Specific behavior:

[1054] Continuously monitoring user experience

[1055] Continued data collection: Emotion data is collected periodically until the end of the user experience and sent to the server

[1056] (Application example 2)

[1057] 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."

[1058] Conventional product or service selection support systems for autonomous vehicles have difficulty fully understanding the user's reasons for selection and psychological factors, and have been unable to provide an experience optimized for the user's emotions. As a result, it has been difficult for users to intuitively understand the value of products and services, and there have been issues in increasing their desire to purchase.

[1059] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating reasons why a customer selects a product or service, means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection, means for visualizing the depicted scenario using virtual reality or augmented reality technology, an emotion engine for recognizing the customer's emotions in real time, and means for dynamically adjusting the content of the scenario and the virtual reality or augmented reality display based on the customer's emotions recognized by the emotion engine. This makes it easier for the user to understand the reasons for their selection and provides an optimal experience based on their emotions.

[1060] "Reasons for choosing a product or service" refers to the motives and criteria that customers consider when choosing a particular product or service.

[1061] "Description in novel form" is a method of writing a story about a specific scene from the customer's perspective based on the reasons for their choice.

[1062] "Virtual reality or augmented reality visualization" refers to a technology that transforms a scenario depicted in a novel format into an experiential form in three-dimensional space and displays it through a virtual reality (VR) or augmented reality (AR) device.

[1063] The "emotion engine that recognizes customer emotions in real time" is a system that uses sensors and cameras to analyze the customer's facial expressions and voice to grasp the customer's emotional state in real time.

[1064] "Dynamic adjustment" refers to a method for changing scenarios and virtual or augmented reality content on the fly based on perceived customer sentiment.

[1065] "Customer attributes such as cultural background, gender, age group, etc." refers to individual characteristics that influence the reasons for a customer's choice, such as their cultural background, gender, age, and lifestyle.

[1066] This invention relates to a selection support system for autonomous vehicles, which generates reasons for customers to select a vehicle, describes specific scenes in a novel format based on those reasons, and visualizes them using virtual reality (VR) or augmented reality (AR) technology. Furthermore, it uses an emotion engine that recognizes customer emotions in real time, dynamically adjusting the scenario and VR / AR display.

[1067] To realize this system, the following hardware and software are used.

[1068] 1. Hardware

[1069] Autonomous vehicle console: The interface for receiving user input and operating the system.

[1070] VR headset (e.g., Oculus Quest 2): Used by users to experience virtual reality scenarios.

[1071] Built-in cameras and sensors (e.g., a vehicle's dashboard camera): Detects the user's facial expressions and voice and sends data to the emotion engine.

[1072] 2. Software

[1073] Emotion recognition software (e.g., Affectiva SDK): Analyzes and recognizes the user's emotional state in real time.

[1074] Generative AI models (e.g., GPT-4): Automatically generate reasons for choosing a vehicle based on customer attributes and input data.

[1075] 3D modeling software (e.g. Blender): Convert the generated scenario into a 3D model and create VR / AR content.

[1076] Program processing and its explanation

[1077] User Input Phase

[1078] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal, and this data is sent to the server.

[1079] AI model generation phase

[1080] Based on the data sent, the server uses a generative AI model such as GPT-4 to automatically generate reasons why the customer chose the vehicle, such as "because it's environmentally friendly" or "because I want to try new technology."

[1081] Scenario description phase

[1082] Based on the generated reasons for selection, the server describes specific scenes from the customer's perspective in a novel format, such as "commuting in an urban area" or "driving with family."

[1083] VR / AR visualization phase

[1084] The depicted scenarios are converted into VR / AR content using 3D modeling software such as Blender, and users can experience the specific situations created through VR headsets such as the Oculus Quest 2.

[1085] Introducing the Emotion Engine

[1086] While a user is experiencing a scene using a VR headset, the built-in camera and sensors analyze the user's facial expressions and voice, and emotion recognition software such as the Affectiva SDK sends the data to an emotion engine, which then analyzes this data to understand the user's emotional state in real time.

[1087] Dynamically adjusting scenarios

[1088] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is surprised, it adds more interesting information. If the user has difficulty understanding, it adds detailed explanations.

[1089] Examples of prompt statements

[1090] For example, a prompt to generate a scenario for a new autonomous electric vehicle might look like this:

[1091] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[1092] These systems and prompts help users understand the reasons for their choices, providing an optimal emotional experience.

[1093] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1094] Step 1:

[1095] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal. The input data is sent to the server. Specifically, the user enters the data using an interface such as a touchscreen or keyboard, and then presses the send button, which sends the data to the server.

[1096] Step 2:

[1097] Based on the data received by the server, a generative AI model (e.g., GPT-4) is used to automatically generate reasons why a customer should choose a vehicle. The input is vehicle information and customer attributes, and the output is multiple reasons for selection. Specifically, the server analyzes the received data and generates reasons for selection by providing them as prompts to the generative AI model. In this case, the prompts are in the following format:

[1098] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[1099] Step 3:

[1100] Based on the generated reasons for selection, the server describes a specific scene in novel form from the customer's perspective. The input is the reason for selection, and the output is a novel-style text describing a specific scene. Specifically, the server uses an AI model to generate a story-like scenario from the reasons for selection. This scenario could be, for example, a "commuting scene in an urban area" or a "drive scene with family."

[1101] Step 4:

[1102] The server converts the depicted scenario into VR / AR content using 3D modeling software (e.g., Blender). The input is a novel-style scenario, and the output is VR / AR content. Specifically, the server analyzes the scenario and converts its contents into a 3D model. The user can experience this model through a VR headset.

[1103] Step 5:

[1104] While a user experiences a scenario using a VR headset, the built-in camera and sensors detect the user's facial expressions and voice and send the data to an emotion engine (e.g., Affectiva SDK). The input is the user's facial and voice data, and the output is an analyzed emotional state. Specifically, the camera and sensors collect data and send it to the emotion engine in real time for analysis.

[1105] Step 6:

[1106] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. The input is the analyzed emotional state, and the output is the adjusted content. Specifically, the server analyzes the emotional data and adjusts the scenario. For example, if the user is surprised, it adds more interesting information. Also, if the content is difficult to understand, it adds detailed explanations.

[1107] This helps users understand the reasons behind their choices and provides an optimal emotional experience.

[1108] 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.

[1109] 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.

[1110] 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.

[1111] [Fourth embodiment]

[1112] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1113] 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.

[1114] 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).

[1115] 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.

[1116] 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.

[1117] 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).

[1118] 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.

[1119] 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.

[1120] 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.

[1121] 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.

[1122] 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.

[1123] 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.

[1124] 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."

[1125] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service. This system automatically generates reasons why customers choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology.

[1126] User Input Phase

[1127] Step 1: Enter product information and customer attributes

[1128] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[1129] AI model generation phase

[1130] Step 2: Generate reasons for selection

[1131] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[1132] Scenario description phase

[1133] Step 3: Writing in fiction

[1134] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[1135] VR / AR visualization phase

[1136] Step 4: Visualize the scenario

[1137] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[1138] Specific examples

[1139] The following process is performed on a newly developed sports sneaker.

[1140] 1. The user enters information into the device

[1141] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[1142] 2. The server generates the selection reason

[1143] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[1144] 3. The server describes the scenario

[1145] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[1146] 4. The server generates the VR / AR content

[1147] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[1148] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions regarding new business ventures and product development.

[1149] The processing flow will be explained below.

[1150] Step 1:

[1151] The user inputs product information and customer attributes into the terminal. Product information includes the product name, features, price, etc., while customer attributes include age group, gender, cultural background, lifestyle, preferences, etc. This input data is sent from the terminal to the server.

[1152] Step 2:

[1153] The server receives the product information and customer attribute data sent from the terminal. It analyzes the received data and uses it as the basis for generating the customer's reasons for selection. At this time, it automatically checks for missing data or input errors.

[1154] Step 3:

[1155] The server launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why customers would choose a product. The model outputs multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[1156] Step 4:

[1157] Based on the generated reasons for selection, the server creates a fictional scenario in which a customer uses a particular product. For example, it depicts a young sports enthusiast putting on new sneakers during a morning jog. At this time, the generated reasons for selection are appropriately incorporated into the scenario.

[1158] Step 5:

[1159] The server uses 3D modeling technology to convert the depicted scenario into VR / AR content. It generates detailed 3D models and their behavior based on the scenario, constructing a virtual reality or augmented reality scene.

[1160] Step 6:

[1161] The server then transmits the completed VR / AR content to the user's device, which includes compressing large amounts of data and optimizing the transmission route.

[1162] Step 7:

[1163] Users experience the visualized scenario using a terminal and necessary VR / AR devices (e.g., VR headsets). Users can see specific scenes in which customers use the product in a 360-degree field of view, thereby intuitively understanding the reasons for customers' choices and behavioral patterns.

[1164] Each of these steps allows companies to gain a deeper understanding of the psychology of their target customers, which can be used to develop new businesses and products.

[1165] Example 1

[1166] 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."

[1167] Conventional systems have difficulty intuitively understanding the psychological factors that customers use when selecting a product or service, making it difficult for companies to fully grasp the reasons for their choices and their behavioral patterns. This makes it difficult to develop products and formulate marketing strategies that accurately reflect the needs and preferences of target customers.

[1168] 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.

[1169] In this invention, the server includes: means for inputting information about a product or service and customer attribute data; means for automatically generating reasons why customers select a product or service using a generative AI model; means for describing specific scenes in which customers use the product in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario in virtual reality or augmented reality using 3D modeling technology; and means for users to experience the visualized scenario using a virtual reality or augmented reality device. This allows companies to intuitively understand the selection reasons and behavioral patterns of target customers and make effective decisions in new business and product development.

[1170] "Product or service information" refers to detailed data about a specific product or service, such as product name, features, and price.

[1171] "Customer attribute data" is information about the personal characteristics of target customers, such as age, gender, cultural background, lifestyle, and preferences.

[1172] A "generative AI model" is an algorithm that automatically generates reasons why a customer might choose a product or service based on input data.

[1173] "Reasons for choice" are the motivations or reasons why customers choose a particular product or service.

[1174] The "means of describing specific scenes in a novel format" is a process of creating a narrative-like concrete scene in which a customer uses a product based on the generated reasons for selection.

[1175] "3D modeling technology" is the technology of using a computer to generate and manipulate three-dimensional objects.

[1176] "Virtual reality technology" is a technology that provides users with a virtual environment generated using computer simulation.

[1177] "Augmented reality technology" is a technology that overlays computer-generated information onto images of the real world.

[1178] A "virtual reality or augmented reality device" is hardware, such as a headset or smartphone, that allows you to experience virtual reality or augmented reality content.

[1179] A "visualized scenario" is a scene that is visually recreated using 3D modeling techniques and virtual or augmented reality technologies.

[1180] This invention is a system that uses virtual reality (VR) and augmented reality (AR) technologies to intuitively understand the psychological factors that customers consider when selecting a product or service. This system involves a procedure in which a user inputs product information and customer attributes via a terminal, a server generates reasons for selection based on that data, depicts a specific scene, and visualizes the scene using virtual reality or augmented reality technology.

[1181] First, the user uses a terminal to input information about the product or service and target customer attribute data. For example, the terminal has a dedicated input form where the user can enter detailed product features such as "lightweight and breathable" and "modern design" as well as customer attributes such as "young people aged 18-25, sports enthusiasts, male." This data is then sent to a server via the Internet.

[1182] Next, the server uses a generative AI model (e.g., OpenAI GPT-4) to analyze the received product information and customer attribute data and automatically generate reasons why the target customer would choose the product. This generative AI model takes into account customer attributes such as cultural background, age, and gender, and generates reasons for selection such as "the design is modern and popular with friends," "it's comfortable when jogging," and "it's recommended by famous athletes."

[1183] The server then uses the generated reasons for selection to create a story in which the customer uses the product. For example, a scenario called "Morning Jogging Scene" could be created, depicting a young sports enthusiast enjoying a jog in their new sneakers, with comments of praise from friends. The created scenario is stored in the server's database.

[1184] The server then performs 3D modeling based on this scene and generates VR / AR content using a 3D modeling platform such as Unreal Engine or Unity. The created VR / AR content is visualized in a 360-degree field of view and can be experienced by users using a VR headset or AR-enabled device.

[1185] Finally, users can experience visualized scenarios using virtual or augmented reality devices, helping them intuitively understand the reasons and context behind customers' product or service choices.

[1186] As a concrete example, the process for a newly developed sports sneaker is as follows:

[1187] 1. The user enters details about the sports sneakers, such as "lightweight and breathable" and "modern design," into the input form on the device, and sets the target customers as "young people aged 18-25, sports enthusiasts, males."

[1188] 2. The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[1189] 3. The server creates a novel-style depiction of a "morning jogging scene." The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of effortless running and complimentary comments from friends.

[1190] 4. The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, the user can intuitively understand the specific situation based on the reasons for their choice.

[1191] An example prompt is:

[1192] "Generate reasons why young people aged 18-25, sports enthusiasts, should choose a new lightweight, breathable sneaker. Consider the comfort they feel while jogging, the praise they get from friends, and endorsements by famous athletes."

[1193] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1194] Step 1: The user enters product information and customer attributes.

[1195] The user enters product information (e.g., product name, features, price) and customer attribute data (e.g., age, gender, cultural background, lifestyle, preferences) into a dedicated input form on the device. For example, the user might enter "lightweight and breathable" and "modern design" as product features, and set "young people aged 18-25, sports enthusiasts" as target customers. The input data is sent from the user's device to the server. The input here is basic information about the product or service and information based on the customer's attributes.

[1196] Step 2: The server generates the selection reasons using the generative AI model.

[1197] The server receives the product information and customer attribute data sent from the device. The received data is input into a generative AI model, which then performs analysis based on that data. The generative AI model (e.g., GPT-4) generates reasons why the target customer would choose the product, taking into account the customer's cultural background, age, gender, and other factors. The output of this step is a selection reason, such as "The design is modern and popular with friends," "It's comfortable for jogging," or "It's recommended by a famous athlete."

[1198] Step 3: The server describes the scene in novel form.

[1199] The server uses the generated reasons for selection to describe in a novel-like format a specific scene in which the customer uses the product. For example, it creates a scenario called "Morning Jogging Scene" and describes a story in which a young sports enthusiast puts on new sneakers and enjoys jogging, receiving praise from friends. This created scene is saved in a database on the server. The input is the generated reasons for selection, and the output is the described scenario in a novel-like format.

[1200] Step 4: The server visualizes the scenario using 3D modeling techniques.

[1201] The server performs 3D modeling based on the saved scenario. This task typically uses a 3D modeling platform such as Unreal Engine or Unity. The server models each element of the scenario in 3D and converts it into virtual reality (VR) or augmented reality (AR) content. The output is visualized VR / AR content with a 360-degree field of view.

[1202] Step 5: The user experiences the visualized scenario using the VR / AR device.

[1203] The user experiences the VR / AR content generated by the server using a VR headset or an AR-compatible device. For example, the user can wear the headset and experience a jogging scene with a 360-degree field of view. The visualized scene helps customers intuitively understand the reasons for selecting a product and the usage experience. The input of this step is the VR / AR content, and the output is the user's understanding as an experience.

[1204] Through these steps, the system extracts the reasons why customers choose a product or service, and based on that, it can depict specific scenes and visualize them using virtual reality and augmented reality technology, allowing companies to intuitively understand the reasons and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development.

[1205] (Application example 1)

[1206] 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."

[1207] In recent years, responding to the diversifying needs of consumers has required a deep understanding of the reasons for their product and service selection, and appropriate marketing. Traditional methods rely on surveys and data analysis, but these alone have the problem of not being able to fully grasp customers' psychological factors and purchasing motivations. Furthermore, physical stores have limited means of visually appealing products, and online shopping presents challenges, making it difficult for users to experience the texture and feel of a product. In response, a new system is needed that provides an intuitive, interactive purchasing experience and deeply understands the reasons for customers' choices.

[1208] 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.

[1209] In this invention, the server includes: a means for generating reasons for a customer's selection of a product or service; a means for describing a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; and a means for visualizing the described scenario using virtual reality or augmented reality technology and allowing the user to experience it in a virtual environment. This allows customers to intuitively and experientially understand their reasons for selecting a product or service and their purchasing motivations, making it easier for companies to understand customers' psychological factors. Furthermore, product experiences in a virtual environment allow users to simulate the texture and feel of the product, thereby solving challenges in online shopping.

[1210] "Customer" means any person who purchases or uses goods or services.

[1211] "Goods or services" means any item or activity that a consumer purchases or uses.

[1212] "Reasons for choice" are the factors and motivations behind a customer's selection of a particular product or service.

[1213] "Means for generating" refers to a system or method for generating information such as reasons for selection based on specific data or algorithms.

[1214] A "scene" is a representation or depiction of a particular situation or setting.

[1215] "Novel form" is a technique of describing specific scenes in the form of a narrative or story.

[1216] "Virtual reality technology" is a technology that allows users to experience a three-dimensional virtual environment generated by a computer.

[1217] "Augmented reality technology" is a technology that adds digital information to visual information from the real world and displays it.

[1218] A "visualization tool" is a system or method for converting information or data into a visible form and displaying it.

[1219] "Cultural background" refers to the totality of traditions, customs, values, etc. in a particular society or community.

[1220] "Gender" is the biological or social classification of male or female.

[1221] An "age group" is a group of people that falls into a particular age range.

[1222] "Customer attributes" are information or characteristics that categorize customers into specific groups.

[1223] "360-degree visualization" is a technology that provides visual information in all directions, allowing users to see in any direction.

[1224] A "virtual environment" is a computer-generated imaginary world or space.

[1225] "Means of experience" are methods and devices that allow users to actually experience the virtual environment.

[1226] "Checking out the details" is the act of gaining a more detailed understanding of a particular subject.

[1227] This invention is a system that uses VR / AR technology to intuitively understand the psychological factors that customers experience when selecting a product or service. This system operates as follows between a server, a terminal, and a user.

[1228] 1. System Configuration and Hardware / Software

[1229] Hardware:

[1230] VR-compatible head-mounted displays (e.g., Oculus Rift, HTC Vive)

[1231] High-performance smartphone

[1232] software:

[1233] Unity Engine

[1234] OpenAI GPT-4 (generative AI model)

[1235] 3D modeling tools (e.g. Blender, Maya)

[1236] 2. Program Processing

[1237] User input phase:

[1238] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.), and this data is sent from the terminal to the server.

[1239] AI model generation phase:

[1240] Based on the received data, the server uses a generative AI model (OpenAI GPT-4) to automatically generate reasons why the target customer would select the product. The generative AI model takes into account customer attributes such as cultural background, gender, and age group to provide multiple reasons for selection. Examples of prompt sentences include the following:

[1241] Example prompt:

[1242] "Please tell us why young people aged 18-25 and sports enthusiasts choose sneakers."

[1243] Scenario Description Phase:

[1244] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer would use the product. The scenario is written in a narrative style and focuses on the customer's daily life and specific situations. For example, it could describe in detail a scene in which the customer enjoys a morning jog wearing new sneakers.

[1245] VR / AR visualization phase:

[1246] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[1247] 3. Specific Examples

[1248] For example, if we were to look at a newly developed sports sneaker, the process would look something like this:

[1249] 1. User Input Phase

[1250] Users input information about sports sneakers, such as "lightweight and breathable" and "modern design," into the device, and set their target customers as "young people aged 18-25, sports enthusiasts."

[1251] 2. AI model generation phase

[1252] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[1253] 3. Scenario description phase

[1254] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[1255] 4. VR / AR visualization phase

[1256] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this scene through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[1257] As described above, this invention is a system that deeply understands the psychological factors of customers and makes it possible to intuitively grasp the reasons for customers' choices through interactive experiences.

[1258] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1259] Step 1:

[1260] User Input Phase

[1261] The user uses a terminal to input product information (e.g., product name, features, price, etc.) and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This input data is sent from the terminal to the server. Specifically, the user fills in the necessary information in the application's input form and presses the "Submit" button, which transfers the data to the server.

[1262] Input: Product information, target customer attributes

[1263] Output: The input data sent to the server

[1264] Step 2:

[1265] AI model generation phase

[1266] The server receives the data sent in step 1 and uses a generative AI model (OpenAI GPT-4) to generate reasons why customers would select a product. The server creates a prompt based on the received customer attribute data and inputs the prompt into the generative AI model to generate reasons for selection. As a specific example, a prompt such as "Please tell us the reasons why young people aged 18-25 who are sports enthusiasts would choose these sneakers" is created and input into the AI ​​model.

[1267] Input: Customer attribute data, prompt statement

[1268] Output: Generated selection reasons

[1269] Step 3:

[1270] Scenario description phase

[1271] Based on the reasons for selection generated in step 2, the server creates a novel-style scenario in which the target customer would use the product. A narrative scenario is created based on the reasons for selection obtained from the generative AI model. The specific scenario is depicted focusing on the customer's daily life or a specific situation. For example, a scene in which a user puts on new sneakers and enjoys a morning jog can be depicted in novel form.

[1272] Input: Generated selection reasons

[1273] Output: Depicted scenario

[1274] Step 4:

[1275] VR / AR visualization phase

[1276] The server uses 3D modeling technology to convert the scenario depicted in step 3 into VR / AR content. Using the Unity engine, the server creates 3D models of each element of the depicted scenario and converts them into a format that can be displayed in the virtual environment. Finally, the visualized scenario can be experienced with a 360-degree field of view. The user puts on a VR headset and experiences the scenario in the virtual environment.

[1277] Input: Depicted scenario

[1278] Output: VR / AR content

[1279] Through this process, users can intuitively and experientially understand the reasons for choosing a product, and companies can gain a deeper understanding of the psychological factors behind their customers.

[1280] 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.

[1281] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers use when selecting a product or service with an emotion engine that recognizes the user's emotions. This system automatically generates reasons why a customer might choose a product or service, depicts specific scenes based on those reasons, and provides a means to visualize them using virtual reality (VR) or augmented reality (AR) technology. The emotion engine also recognizes the user's emotions in real time, dynamically adjusting the content of the scenario and the VR / AR display based on the results.

[1282] User Input Phase

[1283] Step 1: Enter product information and customer attributes

[1284] The user uses the terminal to input information about the product or service (e.g., product name, features, price, etc.) and also input target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server.

[1285] AI model generation phase

[1286] Step 2: Generate reasons for selection

[1287] Based on the received data, the server uses a generative AI model to automatically generate reasons why the target customer would choose the product. The generative AI model provides multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[1288] Scenario description phase

[1289] Step 3: Writing in fiction

[1290] Based on the generated reasons for selection, the server creates a novel-style scenario in which the target customer uses the product. The scenario is written in a narrative style, focusing on the customer's daily life and specific situations.

[1291] VR / AR visualization phase

[1292] Step 4: Visualize the scenario

[1293] The depicted scenario is converted into VR / AR content by the server using 3D modeling technology. The visualized scenario is designed to be experienced in 360 degrees, allowing users to directly experience the scene through virtual reality or augmented reality devices.

[1294] Introducing the Emotion Engine

[1295] Step 5: Activating the Emotion Engine

[1296] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions and tone of voice, and transmits the data in real time to the emotion engine, which then analyzes this data and recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.).

[1297] Step 6: Dynamically adjust the scenario

[1298] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server will change the scenario to explain it more clearly. If the emotion of joy is recognized, the server will add more interesting scenes to enrich the user's experience.

[1299] Step 7: Optimize the user experience

[1300] Users can continuously enjoy tailored scenarios and VR / AR experiences, providing an experience optimized for their emotions and allowing users to gain a more intuitive and deeper understanding of customer psychology.

[1301] Specific examples

[1302] The following process is performed on a newly developed sports sneaker.

[1303] 1. The user enters information into the device

[1304] The user enters information about sports sneakers that are "lightweight and breathable" and "modern in design," and sets the target customers as "young people aged 18-25, sports enthusiasts."

[1305] 2. The server generates the selection reason

[1306] The server uses a generative AI model to automatically generate reasons why young sports enthusiasts choose sneakers, such as "their modern design is popular with friends," "they're comfortable when jogging," and "they're recommended by famous athletes."

[1307] 3. The server describes the scenario

[1308] Thurber describes a "morning jogging scene" in the form of a novel. The scenario details a young sports enthusiast putting on a new pair of sneakers and enjoying a jog. The scene includes a sense of light running and admiring comments from friends.

[1309] 4. The server generates the VR / AR content

[1310] The server creates a 3D model based on the scenario and visualizes the jogging scene in 360 degrees. By experiencing this through a VR headset, users can intuitively understand the specific situation based on the reasons for their choices.

[1311] 5. Introducing the Emotion Engine

[1312] While the user is experiencing the jogging scene using a VR headset, the device recognizes the user's emotions in real time. The emotion engine analyzes the user's reactions (e.g., surprise or satisfaction) and sends the analysis results to the server.

[1313] 6. Dynamically adjust scenarios and VR / AR experiences

[1314] Based on the results of the emotion engine, the server dynamically adjusts the scenario and VR / AR content to optimize the user experience. For example, if the user feels surprised, it adds more interesting information or scenes.

[1315] This system will enable companies to gain a deeper understanding of the choices and behavioral patterns of their target customers, enabling them to make effective decisions in new business and product development, and to provide optimal experiences based on user emotions.

[1316] The processing flow will be explained below.

[1317] Step 1:

[1318] The user inputs product and customer attribute information into the terminal. Product information includes the product name, features, and price, and customer attributes include age group, gender, cultural background, lifestyle, and preferences. This information is sent from the terminal to the server.

[1319] Step 2:

[1320] The server analyzes the product and customer attribute data received from the terminal, automatically checking for missing or incorrect data and establishing standards for accurate data analysis.

[1321] Step 3:

[1322] The server then launches a generative AI model, which uses the analyzed data as input to automatically generate reasons why target customers would choose a product. For example, it generates reasons why young sports enthusiasts choose sneakers, such as "casual and modern design," "comfortable for jogging," and "recommended by friends and influencers."

[1323] Step 4:

[1324] Based on the generated reasons for selection, the server creates a narrative depiction of a specific scenario in which the target customer uses the product, such as a young sports enthusiast putting on a new pair of sneakers during a morning jog and feeling pleased with their comfort.

[1325] Step 5:

[1326] The server converts the depicted scenario into virtual reality (VR) or augmented reality (AR) content using 3D modeling technology. To realistically recreate the scene, it generates a 3D model based on the scenario and its behavior.

[1327] Step 6:

[1328] The server then transmits the completed VR / AR content to the user's device. The server compresses large amounts of data and optimizes the transmission route to deliver the data efficiently.

[1329] Step 7:

[1330] Users can use a terminal and a VR / AR device (e.g., a VR headset) to experience a visualized scenario, allowing them to experience specific scenes in which customers use the product in a 360-degree field of view and intuitively understand the reasons for their choices.

[1331] Step 8:

[1332] While a user is experiencing VR / AR content, the device uses its built-in camera and sensors to analyze the user's facial expressions, tone of voice, and other data, and sends the data to the emotion engine in real time.

[1333] Step 9:

[1334] The emotion engine recognizes the user's emotional state (e.g., joy, surprise, confusion, etc.) in real time and sends the analysis results to the server, where the user's emotions are classified in detail and the type of reaction is understood.

[1335] Step 10:

[1336] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server changes the scenario to make it easier to understand, and if the user is satisfied, the server adds more interesting scenes.

[1337] Step 11:

[1338] Users can enjoy tailored scenarios and VR / AR experiences continuously, and the emotionally optimized experience provides users with a deeper understanding.

[1339] Through all these steps, companies can accurately understand the reasons for target customers' choices and behavioral patterns, allowing them to make effective decisions in new business and product development. Furthermore, optimizing user experience based on emotions allows for more effective customer understanding.

[1340] Example 2

[1341] 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."

[1342] Today's consumers are diverse, and there are many psychological factors that influence their product and service choices. Traditional marketing methods make it difficult to accurately grasp consumer psychology and accurately analyze the reasons for product selection. Furthermore, there were limited ways to describe and visualize specific scenes from the customer's perspective, resulting in an insufficient user experience. Furthermore, there was a lack of a way to optimize the experience based on user emotions in real time. This made it difficult for companies to understand their customers' true needs and develop effective marketing strategies.

[1343] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for generating reasons why a customer selects a product or service; means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection; means for visualizing the depicted scenario using virtual reality or augmented reality technology; and means for dynamically adjusting the scenario and virtual reality or augmented reality content using an emotion engine that recognizes the user's emotions. This allows users to have a more intuitive and deeper understanding of customer psychology, and companies to gain a deeper understanding of the selection reasons and behavioral patterns of target customers, enabling them to make effective decisions in new business ventures and product development. It also allows for the provision of an optimal experience based on the user's emotions.

[1344] "Customer" means a person who purchases or uses goods or services.

[1345] "Goods" refers to tangible objects intended for purchase by consumers.

[1346] "Service" refers to an intangible provision intended for consumer enjoyment.

[1347] "Reasons for choice" refers to the reasons and motivations that customers have when choosing a particular product or service.

[1348] "Novel form" refers to a method of structuring text in a narrative style.

[1349] "Virtual reality technology" refers to technology that allows users to experience a virtual environment generated by a computer.

[1350] "Augmented reality technology" refers to technology that displays digital information overlaid on the real environment.

[1351] "Visualization" refers to displaying information in a visually easy-to-read manner.

[1352] "User" refers to a person who uses a system or service.

[1353] An "emotion engine" refers to technology that recognizes the user's emotional state and controls the system's behavior based on the results.

[1354] "Dynamic adjustment" refers to changing the content in real time according to the situation.

[1355] A "prompt" refers to the text of a question or instruction that is input into a generative AI model.

[1356] A "generative AI model" refers to an artificial intelligence model that generates an output for a specific input based on a large amount of data.

[1357] This invention combines a system that uses VR / AR technology to intuitively understand the psychological factors that customers consider when selecting a product or service with an emotion engine that recognizes the user's emotions. This system is implemented using multiple hardware and software components.

[1358] First, the user uses a terminal to input information about the product or service (e.g., product name, features, price, etc.), as well as the attributes of the target customer (e.g., age, gender, cultural background, lifestyle, preferences, etc.). This data is sent from the terminal to the server. At this stage, the user uses an input interface (e.g., a web form).

[1359] The server uses a generative AI model based on the received data to automatically generate reasons why the target customer would choose a product. This generative AI model is trained to provide multiple reasons for selection, taking into account customer attributes such as cultural background, gender, and age group.

[1360] (Example of a prompt)

[1361] "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[1362] Next, the server uses the generated reasons for selection to create a story-like scenario in which the target customer would use the product, in a novel format. The scenario is then saved in a database using a text generation engine.

[1363] The server then converts the scenario described in the novel format into VR / AR content using 3D modeling tools (e.g., Blender, Unity). The visualized scenario can be experienced through devices such as headsets.

[1364] When a user experiences generated content using a VR / AR headset, the device uses its built-in cameras and sensors to recognize the user's emotions (e.g., joy, surprise, confusion, etc.) in real time. The emotion engine analyzes this data and recognizes the user's emotional state.

[1365] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is confused, the server adds detailed explanations and changes the scene to make it easier to understand. The user can continue to enjoy the adjusted scenario and VR / AR experience.

[1366] As a concrete example, the following steps are performed for a newly developed pair of sports sneakers. The user enters product information into the device, such as "lightweight and breathable" and "modern design," and sets the target customer as "young people aged 18-25, sports enthusiasts." The server uses a generative AI model to automatically generate reasons why young sports enthusiasts would choose the sneakers, and based on the generated reasons, describes a "morning jogging scene" in novel form. The server models the scenario in 3D and visualizes it using virtual reality technology, which the user experiences through a VR headset. During the experience, the device analyzes the user's emotions in real time, and the emotion engine dynamically adjusts the scenario and VR / AR content based on the results. This system allows companies to deeply understand customer reasons for choice and behavioral patterns, allowing them to provide optimal experiences based on the user's emotions.

[1367] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1368] Step 1:

[1369] The user logs in to the device and enters product or service information. The input is sent from the device to the server. At this stage, the input data includes the product name, features, price, and target customer attributes (e.g., age, gender, cultural background, lifestyle, preferences, etc.). The device converts the input data into JSON format and sends it to the server as a request.

[1370] Input: Product information and customer attribute information

[1371] Output: Send data to the server

[1372] Specific behavior:

[1373] Enter product information: Example: "Lightweight and breathable sports sneakers with a modern design. Price: 8,000 yen"

[1374] Enter customer attributes: e.g. "Young people aged 18-25, sports enthusiasts"

[1375] Data transmission: The device converts the data into JSON format and sends it to the server.

[1376] Step 2:

[1377] The server sends prompts to the generative AI model based on the received data. The generative AI model generates reasons why the target customer would choose the product based on a pre-trained dataset. The server receives the generated reasons and stores them in its internal database.

[1378] Input: JSON data of product information and customer attributes

[1379] Output: Reason for selection

[1380] Specific behavior:

[1381] Generate and send prompts: e.g., "Why do young sports enthusiasts between the ages of 18-25 choose lightweight, breathable sports sneakers?"

[1382] Receive responses from the generative AI model: e.g., "The design is modern and popular with friends," "It's comfortable for jogging," "It's recommended by famous athletes."

[1383] Step 3:

[1384] The server then depicts specific scenes in a novel format based on the generated reasons for the choices. The scenes are created using a text generation engine in a narrative style, focusing on the user's daily life or specific situations. The created scenarios are stored in the server's database.

[1385] Input: Reason for selection

[1386] Output: Novel-style scenario

[1387] Specific behavior:

[1388] Scenario generation: Using a text generation engine

[1389] Example: "A morning jogging scene. A young sports enthusiast enjoys jogging in lightweight, breathable sneakers. Includes comments of praise from friends."

[1390] Step 4:

[1391] The server generates VR / AR content using a 3D modeling tool based on the created scenario, constructs 3D models and action sequences based on the scenario, creates VR / AR content, and prepares it for transmission to the device.

[1392] Input: Novel-style scenario

[1393] Output: VR / AR content

[1394] Specific behavior:

[1395] Use of 3D modeling tools (e.g. Blender, Unity)

[1396] Model generation: jogging characters and jogging paths

[1397] Scene rendering: morning scenery and friend interaction scenes

[1398] Step 5:

[1399] While a user wears a VR / AR headset and experiences content, the device uses its built-in cameras and sensors to collect emotional data in real time. The emotion engine analyzes the collected data and recognizes the user's emotional state.

[1400] Input: User experience data (facial expressions, tone of voice, etc.)

[1401] Output: User's emotional state

[1402] Specific behavior:

[1403] Use of face recognition algorithms (e.g. OpenCV)

[1404] Use of voice tone analysis algorithms (e.g., Google Cloud Speech-to-Text)

[1405] Step 6:

[1406] The server dynamically adjusts the scenario and VR / AR content based on the user's emotional state as recognized by the emotion engine. For example, if the user is confused, it adds detailed explanations and changes the scene to make it easier to understand. The adjusted scenario and content are then regenerated and sent to the device in real time.

[1407] Input: User's emotional state

[1408] Output: Adjusted scenarios and VR / AR content

[1409] Specific behavior:

[1410] Scenario change: Dynamic adjustment based on the analysis results of the emotion engine

[1411] For example, "If users are confused, add detailed explanations."

[1412] Step 7:

[1413] Users can continuously enjoy the tailored scenario and VR / AR experience. The device continuously collects emotional data and sends feedback to the server until the user experience ends, providing an experience optimized for the user's emotions.

[1414] Input: Tailored scenarios and VR / AR content

[1415] Output: Optimized user experience

[1416] Specific behavior:

[1417] Continuously monitoring user experience

[1418] Continued data collection: Emotion data is collected periodically until the end of the user experience and sent to the server

[1419] (Application example 2)

[1420] 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."

[1421] Conventional product or service selection support systems for autonomous vehicles have difficulty fully understanding the user's reasons for selection and psychological factors, and have been unable to provide an experience optimized for the user's emotions. As a result, it has been difficult for users to intuitively understand the value of products and services, and there have been issues in increasing their desire to purchase.

[1422] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating reasons why a customer selects a product or service, means for depicting a specific scene from the customer's perspective in a novel format based on the generated reasons for selection, means for visualizing the depicted scenario using virtual reality or augmented reality technology, an emotion engine for recognizing the customer's emotions in real time, and means for dynamically adjusting the content of the scenario and the virtual reality or augmented reality display based on the customer's emotions recognized by the emotion engine. This makes it easier for the user to understand the reasons for their selection and provides an optimal experience based on their emotions.

[1423] "Reasons for choosing a product or service" refers to the motives and criteria that customers consider when choosing a particular product or service.

[1424] "Description in novel form" is a method of writing a story about a specific scene from the customer's perspective based on the reasons for their choice.

[1425] "Virtual reality or augmented reality visualization" refers to a technology that transforms a scenario depicted in a novel format into an experiential form in three-dimensional space and displays it through a virtual reality (VR) or augmented reality (AR) device.

[1426] The "emotion engine that recognizes customer emotions in real time" is a system that uses sensors and cameras to analyze the customer's facial expressions and voice to grasp the customer's emotional state in real time.

[1427] "Dynamic adjustment" refers to a method for changing scenarios and virtual or augmented reality content on the fly based on perceived customer sentiment.

[1428] "Customer attributes such as cultural background, gender, age group, etc." refers to individual characteristics that influence the reasons for a customer's choice, such as their cultural background, gender, age, and lifestyle.

[1429] This invention relates to a selection support system for autonomous vehicles, which generates reasons for customers to select a vehicle, describes specific scenes in a novel format based on those reasons, and visualizes them using virtual reality (VR) or augmented reality (AR) technology. Furthermore, it uses an emotion engine that recognizes customer emotions in real time, dynamically adjusting the scenario and VR / AR display.

[1430] To realize this system, the following hardware and software are used.

[1431] 1. Hardware

[1432] Autonomous vehicle console: The interface for receiving user input and operating the system.

[1433] VR headset (e.g., Oculus Quest 2): Used by users to experience virtual reality scenarios.

[1434] Built-in cameras and sensors (e.g., a vehicle's dashboard camera): Detects the user's facial expressions and voice and sends data to the emotion engine.

[1435] 2. Software

[1436] Emotion recognition software (e.g., Affectiva SDK): Analyzes and recognizes the user's emotional state in real time.

[1437] Generative AI models (e.g., GPT-4): Automatically generate reasons for choosing a vehicle based on customer attributes and input data.

[1438] 3D modeling software (e.g. Blender): Convert the generated scenario into a 3D model and create VR / AR content.

[1439] Program processing and its explanation

[1440] User Input Phase

[1441] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal, and this data is sent to the server.

[1442] AI model generation phase

[1443] Based on the data sent, the server uses a generative AI model such as GPT-4 to automatically generate reasons why the customer chose the vehicle, such as "because it's environmentally friendly" or "because I want to try new technology."

[1444] Scenario description phase

[1445] Based on the generated reasons for selection, the server describes specific scenes from the customer's perspective in a novel format, such as "commuting in an urban area" or "driving with family."

[1446] VR / AR visualization phase

[1447] The depicted scenarios are converted into VR / AR content using 3D modeling software such as Blender, and users can experience the specific situations created through VR headsets such as the Oculus Quest 2.

[1448] Introducing the Emotion Engine

[1449] While a user is experiencing a scene using a VR headset, the built-in camera and sensors analyze the user's facial expressions and voice, and emotion recognition software such as the Affectiva SDK sends the data to an emotion engine, which then analyzes this data to understand the user's emotional state in real time.

[1450] Dynamically adjusting scenarios

[1451] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. For example, if the user is surprised, it adds more interesting information. If the user has difficulty understanding, it adds detailed explanations.

[1452] Examples of prompt statements

[1453] For example, a prompt to generate a scenario for a new autonomous electric vehicle might look like this:

[1454] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[1455] These systems and prompts help users understand the reasons for their choices, providing an optimal emotional experience.

[1456] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1457] Step 1:

[1458] The user uses the console of the autonomous vehicle to input information about the vehicle (e.g., model, features, price) and customer attributes (e.g., age, lifestyle, interests) into the terminal. The input data is sent to the server. Specifically, the user enters the data using an interface such as a touchscreen or keyboard, and then presses the send button, which sends the data to the server.

[1459] Step 2:

[1460] Based on the data received by the server, a generative AI model (e.g., GPT-4) is used to automatically generate reasons why a customer should choose a vehicle. The input is vehicle information and customer attributes, and the output is multiple reasons for selection. Specifically, the server analyzes the received data and generates reasons for selection by providing them as prompts to the generative AI model. In this case, the prompts are in the following format:

[1461] Think about the reasons for choosing a new autonomous electric vehicle. Generate reasons based on the following customer attributes: Age 25-35, Residence Urban, Occupation IT-related, Interests Latest technology, Lifestyle Green living.

[1462] Step 3:

[1463] Based on the generated reasons for selection, the server describes a specific scene in novel form from the customer's perspective. The input is the reason for selection, and the output is a novel-style text describing a specific scene. Specifically, the server uses an AI model to generate a story-like scenario from the reasons for selection. This scenario could be, for example, a "commuting scene in an urban area" or a "drive scene with family."

[1464] Step 4:

[1465] The server converts the depicted scenario into VR / AR content using 3D modeling software (e.g., Blender). The input is a novel-style scenario, and the output is VR / AR content. Specifically, the server analyzes the scenario and converts its contents into a 3D model. The user can experience this model through a VR headset.

[1466] Step 5:

[1467] While a user experiences a scenario using a VR headset, the built-in camera and sensors detect the user's facial expressions and voice and send the data to an emotion engine (e.g., Affectiva SDK). The input is the user's facial and voice data, and the output is an analyzed emotional state. Specifically, the camera and sensors collect data and send it to the emotion engine in real time for analysis.

[1468] Step 6:

[1469] The server dynamically adjusts the scenario and VR / AR content based on the user's emotions recognized by the emotion engine. The input is the analyzed emotional state, and the output is the adjusted content. Specifically, the server analyzes the emotional data and adjusts the scenario. For example, if the user is surprised, it adds more interesting information. Also, if the content is difficult to understand, it adds detailed explanations.

[1470] This helps users understand the reasons behind their choices and provides an optimal emotional experience.

[1471] 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.

[1472] 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.

[1473] 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.

[1474] 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.

[1475] 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.

[1476] 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.

[1477] 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).

[1478] 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.

[1479] 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."

[1480] 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.

[1481] 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).

[1482] 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.

[1483] 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.

[1484] 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.

[1485] 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.

[1486] 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.

[1487] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1488] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1489] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1490] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1491] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1492] The following is further disclosed regarding the above embodiment.

[1493] (Claim 1)

[1494] A means of generating reasons for customers to choose a product or service;

[1495] A means for describing specific scenes in a novel format from the customer's point of view based on the generated reasons for selection;

[1496] a means for visualizing the depicted scenario using virtual reality or augmented reality technology;

[1497] A system including:

[1498] (Claim 2)

[1499] The system according to claim 1, further comprising means for generating a reason for selection in consideration of customer attributes such as cultural background, gender, and age group.

[1500] (Claim 3)

[1501] 10. The system of claim 1, further comprising means for visualizing a particular scene in 360 degrees from a customer's perspective using virtual reality or augmented reality technology.

[1502] "Example 1"

[1503] (Claim 1)

[1504] a means for inputting product or service information and customer attribute data;

[1505] A means of automatically generating reasons why customers would choose a product or service using a generative AI model; and

[1506] A means of describing in novel form specific scenes in which customers use the product based on the generated reasons for selection;

[1507] means for visualizing the depicted scenario in virtual or augmented reality using 3D modeling techniques; and

[1508] a means for a user to experience the visualized scenario using a virtual reality or augmented reality device;

[1509] A system including:

[1510] (Claim 2)

[1511] The system according to claim 1, further comprising means for generating a reason for selection taking into consideration customer attributes such as cultural background, age, and gender.

[1512] (Claim 3)

[1513] 10. The system of claim 1, further comprising means for visualizing a specific scene in which a customer uses the product in 360 degrees using virtual reality or augmented reality technology.

[1514] "Application Example 1"

[1515] (Claim 1)

[1516] A means of generating reasons for customers to choose a product or service;

[1517] A means for describing specific scenes in a novel format from the customer's point of view based on the generated reasons for selection;

[1518] means for visualizing the depicted scenario using virtual reality or augmented reality technology to enable a user to experience the scenario in a virtual environment;

[1519] ...

[1520] A system including:

[1521] (Claim 2)

[1522] The system according to claim 1, further comprising means for generating a reason for selection in consideration of customer attributes such as cultural background, gender, and age group.

[1523] (Claim 3)

[1524] 10. The system of claim 1, further comprising means for visualizing a specific scene from a customer's perspective in 360 degrees using virtual reality or augmented reality technology, allowing a user to walk around the scene in a virtual environment and view product details.

[1525] "Example 2: Combining Emotion Engines"

[1526] (Claim 1)

[1527] A means of generating reasons for customers to choose a product or service;

[1528] A means for describing specific scenes in a novel format from the customer's point of view based on the generated reasons for selection;

[1529] a means for visualizing the depicted scenario using virtual reality or augmented reality technology;

[1530] means for dynamically adjusting the scenario and virtual or augmented reality content using an emotion engine that recognizes the user's emotions;

[1531] A system including:

[1532] (Claim 2)

[1533] The system according to claim 1, further comprising means for generating a reason for selection in consideration of customer attributes such as cultural background, gender, and age group.

[1534] (Claim 3)

[1535] 10. The system of claim 1, further comprising means for visualizing a particular scene in 360 degrees from a customer's perspective using virtual reality or augmented reality technology.

[1536] "Application example 2 when combining emotion engines"

[1537] (Claim 1)

[1538] A means of generating reasons for customers to choose a product or service;

[1539] A means for describing specific scenes in a novel format from the customer's point of view based on the generated reasons for selection;

[1540] a means for visualizing the depicted scenario using virtual reality or augmented reality technology;

[1541] An emotion engine that recognizes customer emotions in real time,

[1542] means for dynamically adjusting the content of the scenario and the virtual reality or augmented reality display based on the customer's emotions recognized by the emotion engine;

[1543] A system including:

[1544] (Claim 2)

[1545] The system according to claim 1, further comprising means for generating a reason for selection in consideration of customer attributes such as cultural background, gender, and age group.

[1546] (Claim 3)

[1547] 10. The system of claim 1, further comprising means for visualizing a particular scene in 360 degrees from a customer's perspective using virtual reality or augmented reality technology. [Explanation of symbols]

[1548] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of generating reasons for customers to choose a product or service; A means for describing specific scenes in a novel format from the customer's point of view based on the generated reasons for selection; a means for visualizing the depicted scenario using virtual reality or augmented reality technology; A system including:

2. The system according to claim 1 , further comprising means for generating a reason for selection in consideration of customer attributes such as cultural background, gender, and age group.

3. 10. The system of claim 1, further comprising means for 360-degree visualization of a particular scene from a customer's perspective using virtual reality or augmented reality technology.

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