system

Abstract

We provide the system. [Solution] A device that receives user input, A processing device that generates multilingual information using an information generation module based on user input, A display device that presents multiple options from the generated information, Information processing means that generates final information based on the option selected by the user from among the multiple options presented, A communication device that publishes the final information on the network, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the tourism industry, information dissemination corresponding to multiple languages is very important. However, it is difficult for elderly workers or those unfamiliar with website production to create an effective and convenient multilingual website. In the existing systems, specialized knowledge and technology are required and they are not easily available at present. Therefore, there is a need for a system that can easily generate and publish a visually attractive and multilingual website.

Means for Solving the Problems

[0005] The present invention provides a system that automatically generates multilingual information based on information entered by a user and presents it as multiple design options. The system generates final information, including visual elements, by allowing the user to select their preferred option. Furthermore, it enables the easy publication of this final information on a network, making it possible to quickly and easily create multilingual websites without requiring specialized knowledge.

[0006] "User input" refers to data used to receive information and requests from users within a system.

[0007] A "device" is a piece of hardware or software that a user uses to input information.

[0008] An "information generation module" is a software component used to generate predetermined information based on user input received.

[0009] "Multilingual support" refers to a function or state that allows equivalent content to be provided and displayed in multiple languages.

[0010] A "processing device" is a computing device that includes hardware or software for processing information.

[0011] A "display device" is a device that presents information to a user in a visually recognizable format.

[0012] An "information processing means" is a function that processes information based on selected options or instructions and generates a final conclusion or result.

[0013] A "communication device" is a device that has network connectivity capabilities for sharing generated information with other devices or users.

[0014] "Media data" refers to content data such as images, audio, and video provided by the user.

[0015] "Visual elements" refer to images and design elements visually represented on websites and applications.

Brief Explanation of Drawings

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

Embodiments for Carrying out the Invention

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

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

[0019] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

[0021] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention provides a system that allows users to easily create and publish multilingual websites. The system includes a process in which the user inputs information via a terminal, and the server automatically generates the website based on that information.

[0038] The user can first use an application on their device to input the necessary theme and image information for the website. The device then sends the entered information to the server and generates a request.

[0039] The server processes incoming requests and uses an information generation module to create a multilingual website based on the user's requirements. The server considers images and other visual elements provided by the user and generates multiple design options. This allows the user to visualize the specific website they want to create.

[0040] The server sends the generated design proposals back to the terminal, providing the user with multiple options. The user then uses the terminal to review the presented design images and selects the one they like best.

[0041] The design selected by the user is generated as the final website by the server. The server integrates the specified content and multilingual support features based on the selected design. Finally, the generated website is published on the internet, and the user can manage it through a dedicated URL.

[0042] Users can easily utilize multilingual websites without requiring specialized knowledge, significantly reducing the effort required to create new websites. This system is expected to be used in many fields, including tourism, and will contribute to the efficiency of information dissemination.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user launches the application using their device and enters the theme, images, and corresponding languages ​​for the website they want to create. This allows the system to specifically communicate the user's wishes.

[0046] Step 2:

[0047] The terminal collects user input information, forms data packets, and sends them to the server. The terminal delivers this information to the server according to a secure protocol.

[0048] Step 3:

[0049] The server analyzes the received user information and calls an information generation module to generate multiple website design proposals that meet the required specifications. In this process, it applies the specified language and provided images to numerous templates.

[0050] Step 4:

[0051] The server generates design proposals, which are then returned to the terminal and presented to the user. These are provided as preview images or live links so that the user can visually compare each design proposal.

[0052] Step 5:

[0053] The user reviews several design options presented through the device and selects the one they like best. The selection is made via the device's interface, and the user's instructions are sent to the server.

[0054] Step 6:

[0055] The server generates the final website based on the design selected by the user. It makes necessary changes to the selected design and incorporates multilingual support.

[0056] Step 7:

[0057] The server publishes the final generated website to the network. It sends domain settings and host information to the terminal, allowing the user to manage the website.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] Creating a multilingual website requires a great deal of specialized knowledge and effort, and dealing with different languages ​​and cultures is particularly challenging. Furthermore, providing users with a wide range of options during the design and translation process presents another challenge.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes means for acquiring information through a terminal device that receives user input, means for using a computer device that generates multilingual information using a generative AI model, and data display means for presenting multiple design options from the generated information. This makes it possible for users to easily create multilingual websites without specialized knowledge and to efficiently build sites while expanding their design and translation options.

[0063] A "terminal device" is a device used by users to input information and transmit it to a processing unit.

[0064] A "generative AI model" is an artificial intelligence algorithm used to automatically generate multilingual information based on information provided by users.

[0065] A "computer device" is a computing device that uses generative AI models to perform processing and generate multilingual information.

[0066] A "data display means" is a display mechanism for presenting multiple design options to the user based on the generated information.

[0067] A "data processing means" is a processing mechanism for generating final information based on the design proposal selected by the user.

[0068] A "communication mechanism" is a means used to publish the final generated information over a network.

[0069] This system allows users to easily create and publish multilingual websites using their devices. Users operate a dedicated application on their devices to input website themes, visual elements, text information, and other details. The device collects this information and sends it to the server. The server processes the received information using a generative AI model and generates multilingual content based on the user's requests.

[0070] Specifically, the server automatically translates text entered by the user into different languages ​​and creates multiple design options for the website using appropriate design templates. This generation process preferably utilizes large-scale language models and text generation algorithms (e.g., Transformer models). The generated design options are sent back to the terminal for the user to review and select.

[0071] Ultimately, based on the design chosen by the user, the server builds a complete website and publishes it on the network. This allows the user to manage and operate the site through a dedicated URL.

[0072] As a concrete example, consider a scenario where a user wants to create a tourism website. The user inputs photos and descriptions of tourist destinations into their device and requests support in Japanese, English, and French. The server generates content in these three languages ​​based on this information and provides different design proposals. The user can then select their preferred design and publish it, utilizing prompts such as, "Please propose design proposals needed to create a tourism guide website in English, French, and Chinese."

[0073] This system enables users to create highly multilingual websites without requiring IT expertise, providing them with a means to effectively deliver information to users from different cultural backgrounds.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] Users launch a dedicated application on their device and input information necessary for creating a website, such as themes, text, images, and target languages. The input data is stored in a structured format (e.g., JSON). This allows information about the type of website the user desires to be collected.

[0077] Step 2:

[0078] The device collects information entered by the user, generates a request, and sends it to the server. Specifically, it compiles the information into JSON format and sends an HTTP request to the server's API endpoint. This allows the server to analyze the information.

[0079] Step 3:

[0080] The server analyzes the received request and uses a generative AI model to generate multilingual content tailored to the user's needs. The generative AI model translates the input text into multiple languages ​​and generates text suitable for web templates. This results in the output of multilingual web content.

[0081] Step 4:

[0082] The server uses the generated multilingual content to construct multiple design options. Specifically, it generates design patterns based on the selected template, taking into account different layouts and color schemes. Multiple design options are output.

[0083] Step 5:

[0084] The server sends the generated design proposals back to the terminal. The terminal's application receives these and displays them for the user to review. From the displayed design proposals, the user selects their preferred design.

[0085] Step 6:

[0086] The user reviews several design options presented on the device and selects the best one. This selection information is sent to the server, which then receives it.

[0087] Step 7:

[0088] The server generates the final website based on the selected design proposal and integrates multilingual support functionality. The final output is a set of HTML / CSS files for the complete website.

[0089] Step 8:

[0090] The server publishes the completed website on the network and provides users with access rights via a dedicated URL. This URL is reliably communicated to users by email or other means.

[0091] (Application Example 1)

[0092] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0093] In modern commerce, building a multilingual e-commerce site that can quickly and easily serve international customers is important, but conventional methods require specialized technical knowledge and are time-consuming and labor-intensive. This invention aims to solve this problem.

[0094] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0095] In this invention, the server includes a device for receiving user input, an information generation device for generating multilingual commercial transaction information, and means for generating an e-commerce site based on the final commercial transaction information. This makes it possible for users to easily and quickly build a multilingual e-commerce site that can serve international customers, even without specialized knowledge.

[0096] "User input" refers to data and information provided by users through the system.

[0097] A "device" is a mechanical or electronic mechanism built to perform a specific function.

[0098] "Multilingual support" refers to the ability to display and process information in multiple different languages.

[0099] "Commercial transaction information" refers to information related to commercial transactions, including product descriptions and pricing information.

[0100] An "information generation device" is a device that automatically generates information in a specific format based on received data.

[0101] A "design proposal" is a proposal that shows the visual or functional structure of the final product or service.

[0102] An "output device" is a device used to present information visually or physically.

[0103] "Information processing means" refers to methods or processes for receiving data, processing it, and obtaining specific results.

[0104] An "online shopping site" is an e-commerce platform used to sell goods and services over the internet.

[0105] A "communication device" is a device used to send and receive digital or analog signals.

[0106] "Product data" refers to information about a product, such as its features, price, and availability.

[0107] "Visual elements" refer to content that is perceived visually, such as images and designs.

[0108] "Automatic translation" is the process of converting text from one language to another using a mechanical process.

[0109] The system used to implement this application primarily consists of a server and a user terminal. First, the user uses an application on their terminal to input product information and image data required for the e-commerce site. The terminal then sends this information to the server. In this case, an application using React Native is used to build the user interface.

[0110] The server operates an information generation device to generate multilingual commercial transaction information based on received product information. This information is translated into multiple languages ​​via a machine translation API (e.g., Google® Translate API). This prepares data that can be used in multiple languages. Cloud platforms such as AWS® are used as the underlying technology for this information processing and translation work.

[0111] The server then generates a series of visual design templates and presents them to the user as multiple design options. The design selected by the user is automatically generated by the server as the final e-commerce site. The generated site is then published on the internet using a communication device.

[0112] As a concrete example, if a user wants to sell traditional Japanese crafts, they would input product descriptions, images, and prices through the app. Once the input is complete, the system instantly generates a website written in English, French, Chinese, and other languages, enabling them to reach international customers. This is how the system supports users in entering the international market.

[0113] An example of a prompt message is: "Please enter information about your new product. Enter the product name, description, price, and image files. Then, select your translation language and choose your preferred style from the design templates. Please review the site once it has been automatically generated."

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The device (the user's smartphone) accepts product information, price, description, and images as input through its user interface. This information is temporarily stored on the device and prepared for transmission to the server.

[0117] Step 2:

[0118] The terminal packages the product information received from the user and sends it to the server as a structured request. Here, product data is sent to the server as input.

[0119] Step 3:

[0120] The server processes the received product information using an information generation device. At this stage, the product information is stored in a database, and the product information is translated into multiple languages ​​using the Google Translate API. The output is translated commercial transaction information.

[0121] Step 4:

[0122] The server uses the translated data to generate multiple e-commerce site design proposals that users can visually select from. These proposals include different templates and styles. The output here is a list of selectable design proposals.

[0123] Step 5:

[0124] The terminal presents the user with design proposals received from the server. The user selects their preferred design from these proposals and returns that selection to the server. The input is the user's selection, which is then sent to the server.

[0125] Step 6:

[0126] The server generates the final e-commerce website based on the design selected by the user. This process involves integrating commercial information into the chosen design template. The output is a completed, multilingual e-commerce website.

[0127] Step 7:

[0128] The server publishes the generated e-commerce site on the internet, making it accessible to users and international customers via communication devices. The output is the URL of the published site.

[0129] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0130] This invention provides a system for further personalizing multilingual websites by combining it with an emotion engine that recognizes user emotions. This system dynamically adjusts the information generated and presented according to the user's emotions.

[0131] The user launches the application using the device and inputs themes related to the website and image information they wish to use. The device is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions as emotion data. For example, if the user has a happy expression, the device recognizes this emotion as "joy" and takes it into consideration when generating information.

[0132] The results analyzed by the emotion engine are included in the input information sent from the terminal to the server. The server adjusts the information generation module based on the user's emotions, customizing the tone and theme of the generated website to match those emotions. For example, if it is suggested that the user wants to relax, the site design will be adjusted to have calmer and softer colors.

[0133] The server generates multiple design options and sorts them based on a priority system that takes emotional data into account. This allows users to make better choices because designs that match their current emotions are presented at the top of the list.

[0134] Once the user selects their favorite design through their device, the server generates the final website based on the selected design. Emotion-based adjustments are also applied here, providing a more personalized user experience when the website is published.

[0135] This system allows users to easily create and publish websites optimized according to their emotional state, leading to higher user satisfaction.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] The user launches a website creation application using their device and inputs the necessary theme and image information. The device is equipped with a camera and microphone, which are used to capture and record the user's facial expressions and voice, and an emotion engine analyzes their emotions in real time.

[0139] Step 2:

[0140] The terminal composes the user's input information and sentiment analysis results into data packets and sends them to the server. This data also includes metadata based on the sentiment recognition results.

[0141] Step 3:

[0142] The server analyzes the received data and calls an information generation module. The server considers the emotional data and sets the website's tone and design to match the user's emotions. At this stage, the content's color scheme, layout, and image selection are optimized to match the emotions.

[0143] Step 4:

[0144] The server generates multiple website design options based on the user's requests and emotions. For example, if the user indicates "fun," designs with brighter colors and more dynamic elements will be suggested.

[0145] Step 5:

[0146] The server generates multiple design options, which are then sent to the user's device and presented to them. At this stage, emotional data is used to ensure that the design that best matches the user's emotions at the time is displayed at the top.

[0147] Step 6:

[0148] The user reviews the design proposals presented through their device and selects the one that best matches their feelings and preferences. The device then sends the selection information to the server.

[0149] Step 7:

[0150] The server generates the final website based on the design selected by the user. Here too, sentiment data is used to make final adjustments to the content to maximize the user experience.

[0151] Step 8:

[0152] The server publishes the completed website to the internet and notifies the user of the publication status. Users can then check and manage the site's status via the provided link. In this way, personalized websites tailored to user emotions are efficiently published.

[0153] (Example 2)

[0154] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0155] Providing personalized information based on user emotions is something that existing systems are not adequately capable of. In particular, for web pages requiring multilingual support, it is difficult to provide visual elements and information that reflect the user's emotions and state, which can impair the quality of the user experience. This results in a challenge in meeting the true needs of information recipients and making it difficult to provide optimal information.

[0156] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0157] In this invention, the server includes analysis means for analyzing the user's behavior and recognizing their emotional state; processing means for dynamically adjusting the settings of an information generation module based on the emotional state and generating personalized information; and display means for presenting multiple suggestions from the generated personalized information and prioritizing them. This enables the dynamic provision of information according to the user's emotional state and allows for multilingual customization.

[0158] "Analysis tools" are means for analyzing user behavior and recognizing their emotional state.

[0159] An "information generation module" is a component that dynamically adjusts settings based on the user's emotional state to generate personalized information.

[0160] A "processing means" is a device or program that performs processing based on generated information and has the function of solving a specific problem.

[0161] A "display means" is a device or module that has the function of presenting generated personalized information as multiple suggestions and prioritizing them.

[0162] "Communication means" refers to a device or protocol equipped with the functionality to publish the final generated information over a network.

[0163] The system of this invention enables users to generate and provide personalized information based on their emotions using a terminal. The terminal is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions in real time. This engine collects data using a microphone and camera and has the function of classifying emotional states as "joy" or "sadness."

[0164] Emotional data is transmitted from the device to the server. A secure protocol (e.g., HTTPS) is used for communication, ensuring user privacy and data security. The server dynamically adjusts an information generation module based on the emotional data to generate personalized information. This module includes algorithms for customizing tone and themes according to the user's emotions.

[0165] The generated information is provided by the server as multiple suggestions. Each suggestion is created by a generative AI model and prioritized in an order that best suits the user's emotions. The user can review these suggestions on their device and select the design they like best. Based on this selection, the server builds the final website and publishes it on the network via communication.

[0166] For example, a user might want to create a website with the theme of a "fun barbecue event." In this case, the server automatically recognizes the user's emotion as "fun," and prioritizes suggesting bright and lively designs. The prompt could be, "Please suggest a fun design for a barbecue event. Please use warm colors for the theme." This enables emotion-based personalization, allowing the user to receive highly satisfying information.

[0167] This system also features multilingual capabilities, allowing it to automatically provide information in different languages ​​based on user selection. The generated websites offer a more personalized user experience through emotion and language-based customization.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user launches a dedicated application on their device. They input the website's theme and desired image information into the application's interface. This information represents the user's design intent, and the device receives it as initial data, preparing it for transmission to the server.

[0171] Step 2:

[0172] The device utilizes an emotion recognition engine to analyze the user's voice tone and facial expressions in real time. The input data consists of the user's voice and video data, which are used to determine their emotional state. For example, if the user is laughing, "joy" emotion data is generated. This emotional information is then used for subsequent personalization processes.

[0173] Step 3:

[0174] The terminal combines the analyzed emotion data and user input information into data packets and sends them to the server. HTTPS is used as the transmission protocol for security reasons. The terminal's role is not limited to information transmission, but also to ensuring the security of the communication.

[0175] Step 4:

[0176] The server dynamically adjusts the parameters of the information generation module based on the received sentiment data and user information. The input consists of theme information and emotional state from the user, which determines the website's design tone and theme. A generative AI model is utilized to generate optimal information that aligns with the user's emotions.

[0177] Step 5:

[0178] The server generates multiple design proposals from the generated information and presents them in order of priority. The design proposal generation is performed by a generation AI model that considers user sentiment data to select the most appropriate design. The output is a list of design proposals sorted by priority.

[0179] Step 6:

[0180] The user selects their favorite design from several options presented on the device. The user makes their selection using a selection button within the application, and the chosen design becomes the input for the next step.

[0181] Step 7:

[0182] The server builds the final website based on the design selected by the user. Using the selected design as input data, it prepares for publication on the network via communication methods. Thus, the personalized website is published online as the final deliverable.

[0183] (Application Example 2)

[0184] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0185] In existing brick-and-mortar stores, it is difficult to offer personalized services and products that respond to customers' emotions, and immediate and appropriate responses are required to improve customer satisfaction. Furthermore, when multilingual information is needed, there is the challenge of simultaneously performing language translation and emotion-based personalization, which is complex.

[0186] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0187] In this invention, the server includes terminal means for receiving user input, a recognition engine for recognizing the user's emotions, and processing means for generating multilingual and personalized information using an information generation module based on the recognized emotions. This enables the provision of appropriate information according to emotions, and is expected to improve customer satisfaction.

[0188] A "terminal means for receiving user input" is a device for receiving information and instructions from users, and is used to acquire initial data for emotion recognition and information generation.

[0189] A "recognition engine" is a device or program that analyzes data such as the user's voice tone and facial expressions to identify their emotional state.

[0190] An "information generation module" is a processing device that creates optimal information based on user sentiment data, and generates multilingual and personalized content.

[0191] A "display means" is a device for visually presenting generated information or multiple options to the user.

[0192] An "information processing device" is a processing device that constructs final information based on a proposal selected by the user, thereby realizing personalized information provision.

[0193] "Communication means" refers to a device or system for making final information publicly available on a network and widely accessible.

[0194] A system for realizing this invention includes a terminal for receiving user input, a recognition engine for recognizing emotions, a multilingual information generation module, a display device for presenting information, information processing means for processing information, and communication means for disclosing the final information.

[0195] The device is equipped with a camera and microphone to acquire voice and image data from the user. This data is analyzed by a recognition engine to identify the user's emotional state. Specifically, commercially available facial recognition software and voice analysis technologies (for example, Google Cloud Vision API or Microsoft® Azure® emotion recognition tools) can be used as the emotion recognition engine. This engine converts the user's facial expressions and voice tone into emotion data.

[0196] Next, the server uses the acquired sentiment data to create multilingual content tailored to the user using an information generation module. This module utilizes a generative AI model to customize information according to the user's needs and emotions. For example, it can use Python's Natural Language Toolkit (NLTK) to perform natural language processing and generate multilingual text data.

[0197] Subsequently, the multiple proposals created are displayed on a storefront screen for the user to select. The selected proposal is integrated by an information processing system to generate final information. This information is transmitted to the user in real time by a display device and can also be shared over a network via a communication system.

[0198] As a concrete example, in a fashion store, visitors can view their own image on a display along with selectable outfit examples in real time. This information is selected based on the customer's current emotions, providing a more personalized experience. An example of a prompt for a generative AI model would be, "Design a logic that analyzes the emotions of customers from their facial expressions and displays product information tailored to those emotions in real time."

[0199] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0200] Step 1:

[0201] The device uses its camera and microphone to acquire images of the user's face and audio data. This data becomes input and is sent to the recognition engine.

[0202] Step 2:

[0203] The recognition engine analyzes the received image and audio data to recognize the user's emotional state. For example, it uses an image processing algorithm to analyze the user's facial expressions and audio analysis software to analyze the tone of their voice. The output of this process is data indicating the user's emotions.

[0204] Step 3:

[0205] The server drives an information generation module based on recognized emotion data to generate multilingual content. It receives emotion data as input and uses a generation AI model to produce information that resonates with the user's emotions. The output is content customized to match the emotions.

[0206] Step 4:

[0207] The server sends several generated content options to the terminal's display device. The user visually reviews the displayed content options and selects the one they like best. This selection becomes the input for the next processing step.

[0208] Step 5:

[0209] The information processing system constructs the final information based on the user's selection. It receives the user's selected proposal as input and generates the final output by integrating and formatting the data.

[0210] Step 6:

[0211] The final information is presented to the user in real time via the terminal's display device. Furthermore, the information can be made publicly available on the network through communication means, allowing other users and systems to access it.

[0212] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0213] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0214] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0218] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0219] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0220] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0221] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0222] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0223] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0224] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0225] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0226] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0227] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0228] This invention provides a system that allows users to easily create and publish multilingual websites. The system includes a process in which the user inputs information via a terminal, and the server automatically generates the website based on that information.

[0229] The user can first use an application on their device to input the necessary theme and image information for the website. The device then sends the entered information to the server and generates a request.

[0230] The server processes incoming requests and uses an information generation module to create a multilingual website based on the user's requirements. The server considers images and other visual elements provided by the user and generates multiple design options. This allows the user to visualize the specific website they want to create.

[0231] The server sends the generated design proposals back to the terminal, providing the user with multiple options. The user then uses the terminal to review the presented design images and selects the one they like best.

[0232] The design selected by the user is generated as the final website by the server. The server integrates the specified content and multilingual support features based on the selected design. Finally, the generated website is published on the internet, and the user can manage it through a dedicated URL.

[0233] Users can easily utilize multilingual websites without requiring specialized knowledge, significantly reducing the effort required to create new websites. This system is expected to be used in many fields, including tourism, and will contribute to the efficiency of information dissemination.

[0234] The following describes the processing flow.

[0235] Step 1:

[0236] The user launches the application using their device and enters the theme, images, and corresponding languages ​​for the website they want to create. This allows the system to specifically communicate the user's wishes.

[0237] Step 2:

[0238] The terminal collects user input information, forms data packets, and sends them to the server. The terminal delivers this information to the server according to a secure protocol.

[0239] Step 3:

[0240] The server analyzes the received user information and calls an information generation module to generate multiple website design proposals that meet the required specifications. In this process, it applies the specified language and provided images to numerous templates.

[0241] Step 4:

[0242] The server generates design proposals, which are then returned to the terminal and presented to the user. These are provided as preview images or live links so that the user can visually compare each design proposal.

[0243] Step 5:

[0244] The user reviews several design options presented through the device and selects the one they like best. The selection is made via the device's interface, and the user's instructions are sent to the server.

[0245] Step 6:

[0246] The server generates the final website based on the design selected by the user. It makes necessary changes to the selected design and incorporates multilingual support.

[0247] Step 7:

[0248] The server publishes the final generated website to the network. It sends domain settings and host information to the terminal, allowing the user to manage the website.

[0249] (Example 1)

[0250] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0251] Creating a multilingual website requires a great deal of specialized knowledge and effort, and dealing with different languages ​​and cultures is particularly challenging. Furthermore, providing users with a wide range of options during the design and translation process presents another challenge.

[0252] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0253] In this invention, the server includes means for acquiring information through a terminal device that receives user input, means for using a computer device that generates multilingual information using a generative AI model, and data display means for presenting multiple design options from the generated information. This makes it possible for users to easily create multilingual websites without specialized knowledge and to efficiently build sites while expanding their design and translation options.

[0254] A "terminal device" is a device used by users to input information and transmit it to a processing unit.

[0255] A "generative AI model" is an artificial intelligence algorithm used to automatically generate multilingual information based on information provided by users.

[0256] A "computer device" is a computing device that uses generative AI models to perform processing and generate multilingual information.

[0257] A "data display means" is a display mechanism for presenting multiple design options to the user based on the generated information.

[0258] A "data processing means" is a processing mechanism for generating final information based on the design proposal selected by the user.

[0259] A "communication mechanism" is a means used to publish the final generated information over a network.

[0260] This system allows users to easily create and publish multilingual websites using their devices. Users operate a dedicated application on their devices to input website themes, visual elements, text information, and other details. The device collects this information and sends it to the server. The server processes the received information using a generative AI model and generates multilingual content based on the user's requests.

[0261] Specifically, the server automatically translates text entered by the user into different languages ​​and creates multiple design options for the website using appropriate design templates. This generation process preferably utilizes large-scale language models and text generation algorithms (e.g., Transformer models). The generated design options are sent back to the terminal for the user to review and select.

[0262] Ultimately, based on the design chosen by the user, the server builds a complete website and publishes it on the network. This allows the user to manage and operate the site through a dedicated URL.

[0263] As a concrete example, consider a scenario where a user wants to create a tourism website. The user inputs photos and descriptions of tourist destinations into their device and requests support in Japanese, English, and French. The server generates content in these three languages ​​based on this information and provides different design proposals. The user can then select their preferred design and publish it, utilizing prompts such as, "Please propose design proposals needed to create a tourism guide website in English, French, and Chinese."

[0264] This system enables users to create highly multilingual websites without requiring IT expertise, providing them with a means to effectively deliver information to users from different cultural backgrounds.

[0265] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0266] Step 1:

[0267] Users launch a dedicated application on their device and input information necessary for creating a website, such as themes, text, images, and target languages. The input data is stored in a structured format (e.g., JSON). This allows information about the type of website the user desires to be collected.

[0268] Step 2:

[0269] The device collects information entered by the user, generates a request, and sends it to the server. Specifically, it compiles the information into JSON format and sends an HTTP request to the server's API endpoint. This allows the server to analyze the information.

[0270] Step 3:

[0271] The server analyzes the received request and uses a generative AI model to generate multilingual content tailored to the user's needs. The generative AI model translates the input text into multiple languages ​​and generates text suitable for web templates. This results in the output of multilingual web content.

[0272] Step 4:

[0273] The server uses the generated multilingual content to construct multiple design options. Specifically, it generates design patterns based on the selected template, taking into account different layouts and color schemes. Multiple design options are output.

[0274] Step 5:

[0275] The server sends back the generated design proposals to the terminal. The terminal application receives these and displays them for the user to view. From the displayed design proposals, the user selects the preferred design.

[0276] Step 6:

[0277] The user examines the multiple design proposals presented on the terminal and selects the optimal design. This selection information is sent to the server, and the server receives it.

[0278] Step 7:

[0279] Based on the selected design proposal, the server generates the final website and integrates the multilingual support function into it. The final product is output as a group of HTML / CSS files of a complete website.

[0280] Step 8:

[0281] The server publishes the completed website on the network and provides the user with access rights through a dedicated URL. This URL is reliably transmitted by notifying the user via email or the like.

[0282] (Application Example 1)

[0283] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0284] In modern commercial transactions, it is important to build a multilingual communication sales website that can respond quickly and easily to international customers. However, the conventional methods have problems such as requiring specialized technical knowledge and taking time and effort. The purpose of the present invention is to solve this problem.

[0285] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means.

[0286] In this invention, the server includes a device that receives user input, an information generation device that generates multilingual business quotation information, and means for generating an e-commerce site based on the final business quotation information. Thereby, even without specialized knowledge, the user can easily and quickly construct a multilingual e-commerce site that can respond to international customers.

[0287] "User input" refers to data and information provided by the user through the system.

[0288] "Device" refers to a mechanical or electronic mechanism constructed to execute a specific function.

[0289] "Multilingual support" means that information display and processing in multiple different languages are possible.

[0290] "Business quotation information" refers to information related to commercial transactions and includes product descriptions and price information.

[0291] "Information generation device" is a device for automatically generating information in a specific format based on the received data.

[0292] "Design proposal" refers to a proposal showing the visual or functional structure of the final product or service.

[0293] "Output device" is a device for presenting information visually or physically.

[0294] "Information processing means" refers to a method or process for receiving data, processing it, and obtaining a specific result.

[0295] "E-commerce site" is an e-commerce platform for selling goods and services on the Internet.

[0296] A "communication device" is a device used to send and receive digital or analog signals.

[0297] "Product data" refers to information about a product, such as its features, price, and availability.

[0298] "Visual elements" refer to content that is perceived visually, such as images and designs.

[0299] "Automatic translation" is the process of converting text from one language to another using a mechanical process.

[0300] The system used to implement this application primarily consists of a server and a user terminal. First, the user uses an application on their terminal to input product information and image data required for the e-commerce site. The terminal then sends this information to the server. In this case, an application using React Native is used to build the user interface.

[0301] The server operates an information generation device to generate multilingual commercial transaction information based on received product information. This information is translated into multiple languages ​​via a machine translation API (e.g., Google Translate API). This prepares data that can be used in multiple languages. Cloud platforms such as AWS are used as the underlying technology for this information processing and translation work.

[0302] The server then generates a series of visual design templates and presents them to the user as multiple design options. The design selected by the user is automatically generated by the server as the final e-commerce site. The generated site is then published on the internet using a communication device.

[0303] As a specific example, when a user wants to sell traditional Japanese handicrafts, they input the product description, image, and price through the app. Once the input is complete, the system immediately generates a website written in English, French, Chinese, etc., enabling access to international customers. This is a mechanism to assist users in entering the international market.

[0304] Examples of prompt sentences are as follows. "Please enter information about the new product. Enter the product name, description, price, and image file. Then, select the translation language and choose your favorite style from the design templates. Please check after the site is automatically generated."

[0305] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0306] Step 1:

[0307] The terminal (the user's smartphone) receives product information, price, description, and image as input through the user interface. This information is temporarily stored on the terminal and prepared for transmission to the server.

[0308] Step 2:

[0309] The terminal packages the product information received from the user and sends it to the server as a structured request. Here, the product data is sent to the server as input.

[0310] Step 3:

[0311] The server performs data processing using the information generation device based on the received product information. At this stage, the product information is stored in the database, and the Google Translate API is used to translate the product information into multiple languages. As output, the translated product information is obtained.

[0312] Step 4:

[0313] The server uses the translated data to generate multiple e-commerce site design proposals that users can visually select from. These proposals include different templates and styles. The output here is a list of selectable design proposals.

[0314] Step 5:

[0315] The terminal presents the user with design proposals received from the server. The user selects their preferred design from these proposals and returns that selection to the server. The input is the user's selection, which is then sent to the server.

[0316] Step 6:

[0317] The server generates the final e-commerce website based on the design selected by the user. This process involves integrating commercial information into the chosen design template. The output is a completed, multilingual e-commerce website.

[0318] Step 7:

[0319] The server publishes the generated e-commerce site on the internet, making it accessible to users and international customers via communication devices. The output is the URL of the published site.

[0320] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0321] This invention provides a system for further personalizing multilingual websites by combining it with an emotion engine that recognizes user emotions. This system dynamically adjusts the information generated and presented according to the user's emotions.

[0322] The user launches the application using the device and inputs themes related to the website and image information they wish to use. The device is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions as emotion data. For example, if the user has a happy expression, the device recognizes this emotion as "joy" and takes it into consideration when generating information.

[0323] The results analyzed by the emotion engine are included in the input information sent from the terminal to the server. The server adjusts the information generation module based on the user's emotions, customizing the tone and theme of the generated website to match those emotions. For example, if it is suggested that the user wants to relax, the site design will be adjusted to have calmer and softer colors.

[0324] The server generates multiple design options and sorts them based on a priority system that takes emotional data into account. This allows users to make better choices because designs that match their current emotions are presented at the top of the list.

[0325] Once the user selects their favorite design through their device, the server generates the final website based on the selected design. Emotion-based adjustments are also applied here, providing a more personalized user experience when the website is published.

[0326] This system allows users to easily create and publish websites optimized according to their emotional state, leading to higher user satisfaction.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] The user launches a website creation application using their device and inputs the necessary theme and image information. The device is equipped with a camera and microphone, which are used to capture and record the user's facial expressions and voice, and an emotion engine analyzes their emotions in real time.

[0330] Step 2:

[0331] The terminal composes the user's input information and sentiment analysis results into data packets and sends them to the server. This data also includes metadata based on the sentiment recognition results.

[0332] Step 3:

[0333] The server analyzes the received data and calls an information generation module. The server considers the emotional data and sets the website's tone and design to match the user's emotions. At this stage, the content's color scheme, layout, and image selection are optimized to match the emotions.

[0334] Step 4:

[0335] The server generates multiple website design options based on the user's requests and emotions. For example, if the user indicates "fun," designs with brighter colors and more dynamic elements will be suggested.

[0336] Step 5:

[0337] The server generates multiple design options, which are then sent to the user's device and presented to them. At this stage, emotional data is used to ensure that the design that best matches the user's emotions at the time is displayed at the top.

[0338] Step 6:

[0339] The user reviews the design proposals presented through their device and selects the one that best matches their feelings and preferences. The device then sends the selection information to the server.

[0340] Step 7:

[0341] The server generates the final website based on the design selected by the user. Here too, sentiment data is used to make final adjustments to the content to maximize the user experience.

[0342] Step 8:

[0343] The server publishes the completed website to the internet and notifies the user of the publication status. Users can then check and manage the site's status via the provided link. In this way, personalized websites tailored to user emotions are efficiently published.

[0344] (Example 2)

[0345] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0346] Providing personalized information based on user emotions is something that existing systems are not adequately capable of. In particular, for web pages requiring multilingual support, it is difficult to provide visual elements and information that reflect the user's emotions and state, which can impair the quality of the user experience. This results in a challenge in meeting the true needs of information recipients and making it difficult to provide optimal information.

[0347] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0348] In this invention, the server includes analysis means for analyzing the user's behavior and recognizing their emotional state; processing means for dynamically adjusting the settings of an information generation module based on the emotional state and generating personalized information; and display means for presenting multiple suggestions from the generated personalized information and prioritizing them. This enables the dynamic provision of information according to the user's emotional state and allows for multilingual customization.

[0349] "Analysis tools" are means for analyzing user behavior and recognizing their emotional state.

[0350] An "information generation module" is a component that dynamically adjusts settings based on the user's emotional state to generate personalized information.

[0351] A "processing means" is a device or program that performs processing based on generated information and has the function of solving a specific problem.

[0352] A "display means" is a device or module that has the function of presenting generated personalized information as multiple suggestions and prioritizing them.

[0353] "Communication means" refers to a device or protocol equipped with the functionality to publish the final generated information over a network.

[0354] The system of this invention enables users to generate and provide personalized information based on their emotions using a terminal. The terminal is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions in real time. This engine collects data using a microphone and camera and has the function of classifying emotional states as "joy" or "sadness."

[0355] Emotional data is transmitted from the device to the server. A secure protocol (e.g., HTTPS) is used for communication, ensuring user privacy and data security. The server dynamically adjusts an information generation module based on the emotional data to generate personalized information. This module includes algorithms for customizing tone and themes according to the user's emotions.

[0356] The generated information is provided by the server as multiple suggestions. Each suggestion is created by a generative AI model and prioritized in an order that best suits the user's emotions. The user can review these suggestions on their device and select the design they like best. Based on this selection, the server builds the final website and publishes it on the network via communication.

[0357] For example, a user might want to create a website with the theme of a "fun barbecue event." In this case, the server automatically recognizes the user's emotion as "fun," and prioritizes suggesting bright and lively designs. The prompt could be, "Please suggest a fun design for a barbecue event. Please use warm colors for the theme." This enables emotion-based personalization, allowing the user to receive highly satisfying information.

[0358] This system also features multilingual capabilities, allowing it to automatically provide information in different languages ​​based on user selection. The generated websites offer a more personalized user experience through emotion and language-based customization.

[0359] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0360] Step 1:

[0361] The user launches a dedicated application on their device. They input the website's theme and desired image information into the application's interface. This information represents the user's design intent, and the device receives it as initial data, preparing it for transmission to the server.

[0362] Step 2:

[0363] The device utilizes an emotion recognition engine to analyze the user's voice tone and facial expressions in real time. The input data consists of the user's voice and video data, which are used to determine their emotional state. For example, if the user is laughing, "joy" emotion data is generated. This emotional information is then used for subsequent personalization processes.

[0364] Step 3:

[0365] The terminal combines the analyzed emotion data and user input information into data packets and sends them to the server. HTTPS is used as the transmission protocol for security reasons. The terminal's role is not limited to information transmission, but also to ensuring the security of the communication.

[0366] Step 4:

[0367] The server dynamically adjusts the parameters of the information generation module based on the received sentiment data and user information. The input consists of theme information and emotional state from the user, which determines the website's design tone and theme. A generative AI model is utilized to generate optimal information that aligns with the user's emotions.

[0368] Step 5:

[0369] The server generates multiple design proposals from the generated information and presents them in order of priority. The design proposal generation is performed by a generation AI model that considers user sentiment data to select the most appropriate design. The output is a list of design proposals sorted by priority.

[0370] Step 6:

[0371] The user selects their favorite design from several options presented on the device. The user makes their selection using a selection button within the application, and the chosen design becomes the input for the next step.

[0372] Step 7:

[0373] The server builds the final website based on the design selected by the user. Using the selected design as input data, it prepares for publication on the network via communication methods. Thus, the personalized website is published online as the final deliverable.

[0374] (Application Example 2)

[0375] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0376] In existing brick-and-mortar stores, it is difficult to offer personalized services and products that respond to customers' emotions, and immediate and appropriate responses are required to improve customer satisfaction. Furthermore, when multilingual information is needed, there is the challenge of simultaneously performing language translation and emotion-based personalization, which is complex.

[0377] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0378] In this invention, the server includes terminal means for receiving user input, a recognition engine for recognizing the user's emotions, and processing means for generating multilingual and personalized information using an information generation module based on the recognized emotions. This enables the provision of appropriate information according to emotions, and is expected to improve customer satisfaction.

[0379] A "terminal means for receiving user input" is a device for receiving information and instructions from users, and is used to acquire initial data for emotion recognition and information generation.

[0380] A "recognition engine" is a device or program that analyzes data such as the user's voice tone and facial expressions to identify their emotional state.

[0381] An "information generation module" is a processing device that creates optimal information based on user sentiment data, and generates multilingual and personalized content.

[0382] A "display means" is a device for visually presenting generated information or multiple options to the user.

[0383] An "information processing device" is a processing device that constructs final information based on a proposal selected by the user, thereby realizing personalized information provision.

[0384] "Communication means" refers to a device or system for making final information publicly available on a network and widely accessible.

[0385] A system for realizing this invention includes a terminal for receiving user input, a recognition engine for recognizing emotions, a multilingual information generation module, a display device for presenting information, information processing means for processing information, and communication means for disclosing the final information.

[0386] The device is equipped with a camera and microphone to acquire voice and image data from the user. This data is analyzed by a recognition engine to identify the user's emotional state. Specifically, commercially available facial recognition software and voice analysis technologies (for example, Google Cloud Vision API or Microsoft Azure's emotion recognition tools) can be used as the emotion recognition engine. This engine converts the user's facial expressions and voice tone into emotion data.

[0387] Next, the server uses the acquired sentiment data to create multilingual content tailored to the user using an information generation module. This module utilizes a generative AI model to customize information according to the user's needs and emotions. For example, it can use Python's Natural Language Toolkit (NLTK) to perform natural language processing and generate multilingual text data.

[0388] Subsequently, the multiple proposals created are displayed on a storefront screen for the user to select. The selected proposal is integrated by an information processing system to generate final information. This information is transmitted to the user in real time by a display device and can also be shared over a network via a communication system.

[0389] As a concrete example, in a fashion store, visitors can view their own image on a display along with selectable outfit examples in real time. This information is selected based on the customer's current emotions, providing a more personalized experience. An example of a prompt for a generative AI model would be, "Design a logic that analyzes the emotions of customers from their facial expressions and displays product information tailored to those emotions in real time."

[0390] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0391] Step 1:

[0392] The device uses its camera and microphone to acquire images of the user's face and audio data. This data becomes input and is sent to the recognition engine.

[0393] Step 2:

[0394] The recognition engine analyzes the received image and audio data to recognize the user's emotional state. For example, it uses an image processing algorithm to analyze the user's facial expressions and audio analysis software to analyze the tone of their voice. The output of this process is data indicating the user's emotions.

[0395] Step 3:

[0396] The server drives an information generation module based on recognized emotion data to generate multilingual content. It receives emotion data as input and uses a generation AI model to produce information that resonates with the user's emotions. The output is content customized to match the emotions.

[0397] Step 4:

[0398] The server sends several generated content options to the terminal's display device. The user visually reviews the displayed content options and selects the one they like best. This selection becomes the input for the next processing step.

[0399] Step 5:

[0400] The information processing system constructs the final information based on the user's selection. It receives the user's selected proposal as input and generates the final output by integrating and formatting the data.

[0401] Step 6:

[0402] The final information is presented to the user in real time via the terminal's display device. Furthermore, the information can be made publicly available on the network through communication means, allowing other users and systems to access it.

[0403] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0404] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0405] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0406] [Third Embodiment]

[0407] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0408] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0409] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0410] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0411] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0412] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0413] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0414] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0415] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0416] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0417] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0418] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0419] This invention provides a system that allows users to easily create and publish multilingual websites. The system includes a process in which the user inputs information via a terminal, and the server automatically generates the website based on that information.

[0420] The user can first use an application on their device to input the necessary theme and image information for the website. The device then sends the entered information to the server and generates a request.

[0421] The server processes incoming requests and uses an information generation module to create a multilingual website based on the user's requirements. The server considers images and other visual elements provided by the user and generates multiple design options. This allows the user to visualize the specific website they want to create.

[0422] The server sends the generated design proposals back to the terminal, providing the user with multiple options. The user then uses the terminal to review the presented design images and selects the one they like best.

[0423] The design selected by the user is generated as the final website by the server. The server integrates the specified content and multilingual support features based on the selected design. Finally, the generated website is published on the internet, and the user can manage it through a dedicated URL.

[0424] Users can easily utilize multilingual websites without requiring specialized knowledge, significantly reducing the effort required to create new websites. This system is expected to be used in many fields, including tourism, and will contribute to the efficiency of information dissemination.

[0425] The following describes the processing flow.

[0426] Step 1:

[0427] The user launches the application using their device and enters the theme, images, and corresponding languages ​​for the website they want to create. This allows the system to specifically communicate the user's wishes.

[0428] Step 2:

[0429] The terminal collects user input information, forms data packets, and sends them to the server. The terminal delivers this information to the server according to a secure protocol.

[0430] Step 3:

[0431] The server analyzes the received user information and calls an information generation module to generate multiple website design proposals that meet the required specifications. In this process, it applies the specified language and provided images to numerous templates.

[0432] Step 4:

[0433] The server generates design proposals, which are then returned to the terminal and presented to the user. These are provided as preview images or live links so that the user can visually compare each design proposal.

[0434] Step 5:

[0435] The user reviews several design options presented through the device and selects the one they like best. The selection is made via the device's interface, and the user's instructions are sent to the server.

[0436] Step 6:

[0437] The server generates the final website based on the design selected by the user. It makes necessary changes to the selected design and incorporates multilingual support.

[0438] Step 7:

[0439] The server publishes the final generated website to the network. It sends domain settings and host information to the terminal, allowing the user to manage the website.

[0440] (Example 1)

[0441] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0442] Creating a multilingual website requires a great deal of specialized knowledge and effort, and dealing with different languages ​​and cultures is particularly challenging. Furthermore, providing users with a wide range of options during the design and translation process presents another challenge.

[0443] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0444] In this invention, the server includes means for acquiring information through a terminal device that receives user input, means for using a computer device that generates multilingual information using a generative AI model, and data display means for presenting multiple design options from the generated information. This makes it possible for users to easily create multilingual websites without specialized knowledge and to efficiently build sites while expanding their design and translation options.

[0445] A "terminal device" is a device used by users to input information and transmit it to a processing unit.

[0446] A "generative AI model" is an artificial intelligence algorithm used to automatically generate multilingual information based on information provided by users.

[0447] A "computer device" is a computing device that uses generative AI models to perform processing and generate multilingual information.

[0448] A "data display means" is a display mechanism for presenting multiple design options to the user based on the generated information.

[0449] A "data processing means" is a processing mechanism for generating final information based on the design proposal selected by the user.

[0450] A "communication mechanism" is a means used to publish the final generated information over a network.

[0451] This system allows users to easily create and publish multilingual websites using their devices. Users operate a dedicated application on their devices to input website themes, visual elements, text information, and other details. The device collects this information and sends it to the server. The server processes the received information using a generative AI model and generates multilingual content based on the user's requests.

[0452] Specifically, the server automatically translates text entered by the user into different languages ​​and creates multiple design options for the website using appropriate design templates. This generation process preferably utilizes large-scale language models and text generation algorithms (e.g., Transformer models). The generated design options are sent back to the terminal for the user to review and select.

[0453] Ultimately, based on the design chosen by the user, the server builds a complete website and publishes it on the network. This allows the user to manage and operate the site through a dedicated URL.

[0454] As a concrete example, consider a scenario where a user wants to create a tourism website. The user inputs photos and descriptions of tourist destinations into their device and requests support in Japanese, English, and French. The server generates content in these three languages ​​based on this information and provides different design proposals. The user can then select their preferred design and publish it, utilizing prompts such as, "Please propose design proposals needed to create a tourism guide website in English, French, and Chinese."

[0455] This system enables users to create highly multilingual websites without requiring IT expertise, providing them with a means to effectively deliver information to users from different cultural backgrounds.

[0456] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0457] Step 1:

[0458] Users launch a dedicated application on their device and input information necessary for creating a website, such as themes, text, images, and target languages. The input data is stored in a structured format (e.g., JSON). This allows information about the type of website the user desires to be collected.

[0459] Step 2:

[0460] The device collects information entered by the user, generates a request, and sends it to the server. Specifically, it compiles the information into JSON format and sends an HTTP request to the server's API endpoint. This allows the server to analyze the information.

[0461] Step 3:

[0462] The server analyzes the received request and uses a generative AI model to generate multilingual content tailored to the user's needs. The generative AI model translates the input text into multiple languages ​​and generates text suitable for web templates. This results in the output of multilingual web content.

[0463] Step 4:

[0464] The server uses the generated multilingual content to construct multiple design options. Specifically, it generates design patterns based on the selected template, taking into account different layouts and color schemes. Multiple design options are output.

[0465] Step 5:

[0466] The server sends the generated design proposals back to the terminal. The terminal's application receives these and displays them for the user to review. From the displayed design proposals, the user selects their preferred design.

[0467] Step 6:

[0468] The user reviews several design options presented on the device and selects the best one. This selection information is sent to the server, which then receives it.

[0469] Step 7:

[0470] The server generates the final website based on the selected design proposal and integrates multilingual support functionality. The final output is a set of HTML / CSS files for the complete website.

[0471] Step 8:

[0472] The server publishes the completed website on the network and provides users with access rights via a dedicated URL. This URL is reliably communicated to users by email or other means.

[0473] (Application Example 1)

[0474] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0475] In modern commerce, building a multilingual e-commerce site that can quickly and easily serve international customers is important, but conventional methods require specialized technical knowledge and are time-consuming and labor-intensive. This invention aims to solve this problem.

[0476] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0477] In this invention, the server includes a device for receiving user input, an information generation device for generating multilingual commercial transaction information, and means for generating an e-commerce site based on the final commercial transaction information. This makes it possible for users to easily and quickly build a multilingual e-commerce site that can serve international customers, even without specialized knowledge.

[0478] "User input" refers to data and information provided by users through the system.

[0479] A "device" is a mechanical or electronic mechanism built to perform a specific function.

[0480] "Multilingual support" refers to the ability to display and process information in multiple different languages.

[0481] "Commercial transaction information" refers to information related to commercial transactions, including product descriptions and pricing information.

[0482] An "information generation device" is a device that automatically generates information in a specific format based on received data.

[0483] A "design proposal" is a proposal that shows the visual or functional structure of the final product or service.

[0484] An "output device" is a device used to present information visually or physically.

[0485] "Information processing means" refers to methods or processes for receiving data, processing it, and obtaining specific results.

[0486] An "online shopping site" is an e-commerce platform used to sell goods and services over the internet.

[0487] A "communication device" is a device used to send and receive digital or analog signals.

[0488] "Product data" refers to information about a product, such as its features, price, and availability.

[0489] "Visual elements" refer to content that is perceived visually, such as images and designs.

[0490] "Automatic translation" is the process of converting text from one language to another using a mechanical process.

[0491] The system used to implement this application primarily consists of a server and a user terminal. First, the user uses an application on their terminal to input product information and image data required for the e-commerce site. The terminal then sends this information to the server. In this case, an application using React Native is used to build the user interface.

[0492] The server operates an information generation device to generate multilingual commercial transaction information based on received product information. This information is translated into multiple languages ​​via a machine translation API (e.g., Google Translate API). This prepares data that can be used in multiple languages. Cloud platforms such as AWS are used as the underlying technology for this information processing and translation work.

[0493] The server then generates a series of visual design templates and presents them to the user as multiple design options. The design selected by the user is automatically generated by the server as the final e-commerce site. The generated site is then published on the internet using a communication device.

[0494] As a concrete example, if a user wants to sell traditional Japanese crafts, they would input product descriptions, images, and prices through the app. Once the input is complete, the system instantly generates a website written in English, French, Chinese, and other languages, enabling them to reach international customers. This is how the system supports users in entering the international market.

[0495] An example of a prompt message is: "Please enter information about your new product. Enter the product name, description, price, and image files. Then, select your translation language and choose your preferred style from the design templates. Please review the site once it has been automatically generated."

[0496] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0497] Step 1:

[0498] The device (the user's smartphone) accepts product information, price, description, and images as input through its user interface. This information is temporarily stored on the device and prepared for transmission to the server.

[0499] Step 2:

[0500] The terminal packages the product information received from the user and sends it to the server as a structured request. Here, product data is sent to the server as input.

[0501] Step 3:

[0502] The server processes the received product information using an information generation device. At this stage, the product information is stored in a database, and the product information is translated into multiple languages ​​using the Google Translate API. The output is translated commercial transaction information.

[0503] Step 4:

[0504] The server uses the translated data to generate multiple e-commerce site design proposals that users can visually select from. These proposals include different templates and styles. The output here is a list of selectable design proposals.

[0505] Step 5:

[0506] The terminal presents the user with design proposals received from the server. The user selects their preferred design from these proposals and returns that selection to the server. The input is the user's selection, which is then sent to the server.

[0507] Step 6:

[0508] The server generates the final e-commerce website based on the design selected by the user. This process involves integrating commercial information into the chosen design template. The output is a completed, multilingual e-commerce website.

[0509] Step 7:

[0510] The server publishes the generated e-commerce site on the internet, making it accessible to users and international customers via communication devices. The output is the URL of the published site.

[0511] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0512] This invention provides a system for further personalizing multilingual websites by combining it with an emotion engine that recognizes user emotions. This system dynamically adjusts the information generated and presented according to the user's emotions.

[0513] The user launches the application using the device and inputs themes related to the website and image information they wish to use. The device is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions as emotion data. For example, if the user has a happy expression, the device recognizes this emotion as "joy" and takes it into consideration when generating information.

[0514] The results analyzed by the emotion engine are included in the input information sent from the terminal to the server. The server adjusts the information generation module based on the user's emotions, customizing the tone and theme of the generated website to match those emotions. For example, if it is suggested that the user wants to relax, the site design will be adjusted to have calmer and softer colors.

[0515] The server generates multiple design options and sorts them based on a priority system that takes emotional data into account. This allows users to make better choices because designs that match their current emotions are presented at the top of the list.

[0516] Once the user selects their favorite design through their device, the server generates the final website based on the selected design. Emotion-based adjustments are also applied here, providing a more personalized user experience when the website is published.

[0517] This system allows users to easily create and publish websites optimized according to their emotional state, leading to higher user satisfaction.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] The user launches a website creation application using their device and inputs the necessary theme and image information. The device is equipped with a camera and microphone, which are used to capture and record the user's facial expressions and voice, and an emotion engine analyzes their emotions in real time.

[0521] Step 2:

[0522] The terminal composes the user's input information and sentiment analysis results into data packets and sends them to the server. This data also includes metadata based on the sentiment recognition results.

[0523] Step 3:

[0524] The server analyzes the received data and calls an information generation module. The server considers the emotional data and sets the website's tone and design to match the user's emotions. At this stage, the content's color scheme, layout, and image selection are optimized to match the emotions.

[0525] Step 4:

[0526] The server generates multiple website design options based on the user's requests and emotions. For example, if the user indicates "fun," designs with brighter colors and more dynamic elements will be suggested.

[0527] Step 5:

[0528] The server generates multiple design options, which are then sent to the user's device and presented to them. At this stage, emotional data is used to ensure that the design that best matches the user's emotions at the time is displayed at the top.

[0529] Step 6:

[0530] The user reviews the design proposals presented through their device and selects the one that best matches their feelings and preferences. The device then sends the selection information to the server.

[0531] Step 7:

[0532] The server generates the final website based on the design selected by the user. Here too, sentiment data is used to make final adjustments to the content to maximize the user experience.

[0533] Step 8:

[0534] The server publishes the completed website to the internet and notifies the user of the publication status. Users can then check and manage the site's status via the provided link. In this way, personalized websites tailored to user emotions are efficiently published.

[0535] (Example 2)

[0536] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0537] Providing personalized information based on user emotions is something that existing systems are not adequately capable of. In particular, for web pages requiring multilingual support, it is difficult to provide visual elements and information that reflect the user's emotions and state, which can impair the quality of the user experience. This results in a challenge in meeting the true needs of information recipients and making it difficult to provide optimal information.

[0538] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0539] In this invention, the server includes analysis means for analyzing the user's behavior and recognizing their emotional state; processing means for dynamically adjusting the settings of an information generation module based on the emotional state and generating personalized information; and display means for presenting multiple suggestions from the generated personalized information and prioritizing them. This enables the dynamic provision of information according to the user's emotional state and allows for multilingual customization.

[0540] "Analysis tools" are means for analyzing user behavior and recognizing their emotional state.

[0541] An "information generation module" is a component that dynamically adjusts settings based on the user's emotional state to generate personalized information.

[0542] A "processing means" is a device or program that performs processing based on generated information and has the function of solving a specific problem.

[0543] A "display means" is a device or module that has the function of presenting generated personalized information as multiple suggestions and prioritizing them.

[0544] "Communication means" refers to a device or protocol equipped with the functionality to publish the final generated information over a network.

[0545] The system of this invention enables users to generate and provide personalized information based on their emotions using a terminal. The terminal is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions in real time. This engine collects data using a microphone and camera and has the function of classifying emotional states as "joy" or "sadness."

[0546] Emotional data is transmitted from the device to the server. A secure protocol (e.g., HTTPS) is used for communication, ensuring user privacy and data security. The server dynamically adjusts an information generation module based on the emotional data to generate personalized information. This module includes algorithms for customizing tone and themes according to the user's emotions.

[0547] The generated information is provided by the server as multiple suggestions. Each suggestion is created by a generative AI model and prioritized in an order that best suits the user's emotions. The user can review these suggestions on their device and select the design they like best. Based on this selection, the server builds the final website and publishes it on the network via communication.

[0548] For example, a user might want to create a website with the theme of a "fun barbecue event." In this case, the server automatically recognizes the user's emotion as "fun," and prioritizes suggesting bright and lively designs. The prompt could be, "Please suggest a fun design for a barbecue event. Please use warm colors for the theme." This enables emotion-based personalization, allowing the user to receive highly satisfying information.

[0549] This system also features multilingual capabilities, allowing it to automatically provide information in different languages ​​based on user selection. The generated websites offer a more personalized user experience through emotion and language-based customization.

[0550] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0551] Step 1:

[0552] The user launches a dedicated application on their device. They input the website's theme and desired image information into the application's interface. This information represents the user's design intent, and the device receives it as initial data, preparing it for transmission to the server.

[0553] Step 2:

[0554] The device utilizes an emotion recognition engine to analyze the user's voice tone and facial expressions in real time. The input data consists of the user's voice and video data, which are used to determine their emotional state. For example, if the user is laughing, "joy" emotion data is generated. This emotional information is then used for subsequent personalization processes.

[0555] Step 3:

[0556] The terminal combines the analyzed emotion data and user input information into data packets and sends them to the server. HTTPS is used as the transmission protocol for security reasons. The terminal's role is not limited to information transmission, but also to ensuring the security of the communication.

[0557] Step 4:

[0558] The server dynamically adjusts the parameters of the information generation module based on the received sentiment data and user information. The input consists of theme information and emotional state from the user, which determines the website's design tone and theme. A generative AI model is utilized to generate optimal information that aligns with the user's emotions.

[0559] Step 5:

[0560] The server generates multiple design proposals from the generated information and presents them in order of priority. The design proposal generation is performed by a generation AI model that considers user sentiment data to select the most appropriate design. The output is a list of design proposals sorted by priority.

[0561] Step 6:

[0562] The user selects their favorite design from several options presented on the device. The user makes their selection using a selection button within the application, and the chosen design becomes the input for the next step.

[0563] Step 7:

[0564] The server builds the final website based on the design selected by the user. Using the selected design as input data, it prepares for publication on the network via communication methods. Thus, the personalized website is published online as the final deliverable.

[0565] (Application Example 2)

[0566] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0567] In existing brick-and-mortar stores, it is difficult to offer personalized services and products that respond to customers' emotions, and immediate and appropriate responses are required to improve customer satisfaction. Furthermore, when multilingual information is needed, there is the challenge of simultaneously performing language translation and emotion-based personalization, which is complex.

[0568] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0569] In this invention, the server includes terminal means for receiving user input, a recognition engine for recognizing the user's emotions, and processing means for generating multilingual and personalized information using an information generation module based on the recognized emotions. This enables the provision of appropriate information according to emotions, and is expected to improve customer satisfaction.

[0570] A "terminal means for receiving user input" is a device for receiving information and instructions from users, and is used to acquire initial data for emotion recognition and information generation.

[0571] A "recognition engine" is a device or program that analyzes data such as the user's voice tone and facial expressions to identify their emotional state.

[0572] An "information generation module" is a processing device that creates optimal information based on user sentiment data, and generates multilingual and personalized content.

[0573] A "display means" is a device for visually presenting generated information or multiple options to the user.

[0574] An "information processing device" is a processing device that constructs final information based on a proposal selected by the user, thereby realizing personalized information provision.

[0575] "Communication means" refers to a device or system for making final information publicly available on a network and widely accessible.

[0576] A system for realizing this invention includes a terminal for receiving user input, a recognition engine for recognizing emotions, a multilingual information generation module, a display device for presenting information, information processing means for processing information, and communication means for disclosing the final information.

[0577] The device is equipped with a camera and microphone to acquire voice and image data from the user. This data is analyzed by a recognition engine to identify the user's emotional state. Specifically, commercially available facial recognition software and voice analysis technologies (for example, Google Cloud Vision API or Microsoft Azure's emotion recognition tools) can be used as the emotion recognition engine. This engine converts the user's facial expressions and voice tone into emotion data.

[0578] Next, the server uses the acquired sentiment data to create multilingual content tailored to the user using an information generation module. This module utilizes a generative AI model to customize information according to the user's needs and emotions. For example, it can use Python's Natural Language Toolkit (NLTK) to perform natural language processing and generate multilingual text data.

[0579] Subsequently, the multiple proposals created are displayed on a storefront screen for the user to select. The selected proposal is integrated by an information processing system to generate final information. This information is transmitted to the user in real time by a display device and can also be shared over a network via a communication system.

[0580] As a concrete example, in a fashion store, visitors can view their own image on a display along with selectable outfit examples in real time. This information is selected based on the customer's current emotions, providing a more personalized experience. An example of a prompt for a generative AI model would be, "Design a logic that analyzes the emotions of customers from their facial expressions and displays product information tailored to those emotions in real time."

[0581] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0582] Step 1:

[0583] The device uses its camera and microphone to acquire images of the user's face and audio data. This data becomes input and is sent to the recognition engine.

[0584] Step 2:

[0585] The recognition engine analyzes the received image and audio data to recognize the user's emotional state. For example, it uses an image processing algorithm to analyze the user's facial expressions and audio analysis software to analyze the tone of their voice. The output of this process is data indicating the user's emotions.

[0586] Step 3:

[0587] The server drives an information generation module based on recognized emotion data to generate multilingual content. It receives emotion data as input and uses a generation AI model to produce information that resonates with the user's emotions. The output is content customized to match the emotions.

[0588] Step 4:

[0589] The server sends several generated content options to the terminal's display device. The user visually reviews the displayed content options and selects the one they like best. This selection becomes the input for the next processing step.

[0590] Step 5:

[0591] The information processing system constructs the final information based on the user's selection. It receives the user's selected proposal as input and generates the final output by integrating and formatting the data.

[0592] Step 6:

[0593] The final information is presented to the user in real time via the terminal's display device. Furthermore, the information can be made publicly available on the network through communication means, allowing other users and systems to access it.

[0594] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0595] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0596] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0597] [Fourth Embodiment]

[0598] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0599] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0600] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0601] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0602] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0603] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0604] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0605] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0606] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0607] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0608] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0609] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0610] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0611] This invention provides a system that allows users to easily create and publish multilingual websites. The system includes a process in which the user inputs information via a terminal, and the server automatically generates the website based on that information.

[0612] The user can first use an application on their device to input the necessary theme and image information for the website. The device then sends the entered information to the server and generates a request.

[0613] The server processes incoming requests and uses an information generation module to create a multilingual website based on the user's requirements. The server considers images and other visual elements provided by the user and generates multiple design options. This allows the user to visualize the specific website they want to create.

[0614] The server sends the generated design proposals back to the terminal, providing the user with multiple options. The user then uses the terminal to review the presented design images and selects the one they like best.

[0615] The design selected by the user is generated as the final website by the server. The server integrates the specified content and multilingual support features based on the selected design. Finally, the generated website is published on the internet, and the user can manage it through a dedicated URL.

[0616] Users can easily utilize multilingual websites without requiring specialized knowledge, significantly reducing the effort required to create new websites. This system is expected to be used in many fields, including tourism, and will contribute to the efficiency of information dissemination.

[0617] The following describes the processing flow.

[0618] Step 1:

[0619] The user launches the application using their device and enters the theme, images, and corresponding languages ​​for the website they want to create. This allows the system to specifically communicate the user's wishes.

[0620] Step 2:

[0621] The terminal collects user input information, forms data packets, and sends them to the server. The terminal delivers this information to the server according to a secure protocol.

[0622] Step 3:

[0623] The server analyzes the received user information and calls an information generation module to generate multiple website design proposals that meet the required specifications. In this process, it applies the specified language and provided images to numerous templates.

[0624] Step 4:

[0625] The server generates design proposals, which are then returned to the terminal and presented to the user. These are provided as preview images or live links so that the user can visually compare each design proposal.

[0626] Step 5:

[0627] The user reviews several design options presented through the device and selects the one they like best. The selection is made via the device's interface, and the user's instructions are sent to the server.

[0628] Step 6:

[0629] The server generates the final website based on the design selected by the user. It makes necessary changes to the selected design and incorporates multilingual support.

[0630] Step 7:

[0631] The server publishes the final generated website to the network. It sends domain settings and host information to the terminal, allowing the user to manage the website.

[0632] (Example 1)

[0633] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0634] Creating a multilingual website requires a great deal of specialized knowledge and effort, and dealing with different languages ​​and cultures is particularly challenging. Furthermore, providing users with a wide range of options during the design and translation process presents another challenge.

[0635] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0636] In this invention, the server includes means for acquiring information through a terminal device that receives user input, means for using a computer device that generates multilingual information using a generative AI model, and data display means for presenting multiple design options from the generated information. This makes it possible for users to easily create multilingual websites without specialized knowledge and to efficiently build sites while expanding their design and translation options.

[0637] A "terminal device" is a device used by users to input information and transmit it to a processing unit.

[0638] A "generative AI model" is an artificial intelligence algorithm used to automatically generate multilingual information based on information provided by users.

[0639] A "computer device" is a computing device that uses generative AI models to perform processing and generate multilingual information.

[0640] A "data display means" is a display mechanism for presenting multiple design options to the user based on the generated information.

[0641] A "data processing means" is a processing mechanism for generating final information based on the design proposal selected by the user.

[0642] A "communication mechanism" is a means used to publish the final generated information over a network.

[0643] This system allows users to easily create and publish multilingual websites using their devices. Users operate a dedicated application on their devices to input website themes, visual elements, text information, and other details. The device collects this information and sends it to the server. The server processes the received information using a generative AI model and generates multilingual content based on the user's requests.

[0644] Specifically, the server automatically translates text entered by the user into different languages ​​and creates multiple design options for the website using appropriate design templates. This generation process preferably utilizes large-scale language models and text generation algorithms (e.g., Transformer models). The generated design options are sent back to the terminal for the user to review and select.

[0645] Ultimately, based on the design chosen by the user, the server builds a complete website and publishes it on the network. This allows the user to manage and operate the site through a dedicated URL.

[0646] As a concrete example, consider a scenario where a user wants to create a tourism website. The user inputs photos and descriptions of tourist destinations into their device and requests support in Japanese, English, and French. The server generates content in these three languages ​​based on this information and provides different design proposals. The user can then select their preferred design and publish it, utilizing prompts such as, "Please propose design proposals needed to create a tourism guide website in English, French, and Chinese."

[0647] This system enables users to create highly multilingual websites without requiring IT expertise, providing them with a means to effectively deliver information to users from different cultural backgrounds.

[0648] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0649] Step 1:

[0650] Users launch a dedicated application on their device and input information necessary for creating a website, such as themes, text, images, and target languages. The input data is stored in a structured format (e.g., JSON). This allows information about the type of website the user desires to be collected.

[0651] Step 2:

[0652] The device collects information entered by the user, generates a request, and sends it to the server. Specifically, it compiles the information into JSON format and sends an HTTP request to the server's API endpoint. This allows the server to analyze the information.

[0653] Step 3:

[0654] The server analyzes the received request and uses a generative AI model to generate multilingual content tailored to the user's needs. The generative AI model translates the input text into multiple languages ​​and generates text suitable for web templates. This results in the output of multilingual web content.

[0655] Step 4:

[0656] The server uses the generated multilingual content to construct multiple design options. Specifically, it generates design patterns based on the selected template, taking into account different layouts and color schemes. Multiple design options are output.

[0657] Step 5:

[0658] The server sends the generated design proposals back to the terminal. The terminal's application receives these and displays them for the user to review. From the displayed design proposals, the user selects their preferred design.

[0659] Step 6:

[0660] The user reviews several design options presented on the device and selects the best one. This selection information is sent to the server, which then receives it.

[0661] Step 7:

[0662] The server generates the final website based on the selected design proposal and integrates multilingual support functionality. The final output is a set of HTML / CSS files for the complete website.

[0663] Step 8:

[0664] The server publishes the completed website on the network and provides users with access rights via a dedicated URL. This URL is reliably communicated to users by email or other means.

[0665] (Application Example 1)

[0666] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0667] In modern commerce, building a multilingual e-commerce site that can quickly and easily serve international customers is important, but conventional methods require specialized technical knowledge and are time-consuming and labor-intensive. This invention aims to solve this problem.

[0668] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0669] In this invention, the server includes a device for receiving user input, an information generation device for generating multilingual commercial transaction information, and means for generating an e-commerce site based on the final commercial transaction information. This makes it possible for users to easily and quickly build a multilingual e-commerce site that can serve international customers, even without specialized knowledge.

[0670] "User input" refers to data and information provided by users through the system.

[0671] A "device" is a mechanical or electronic mechanism built to perform a specific function.

[0672] "Multilingual support" refers to the ability to display and process information in multiple different languages.

[0673] "Commercial transaction information" refers to information related to commercial transactions, including product descriptions and pricing information.

[0674] An "information generation device" is a device that automatically generates information in a specific format based on received data.

[0675] A "design proposal" is a proposal that shows the visual or functional structure of the final product or service.

[0676] An "output device" is a device used to present information visually or physically.

[0677] "Information processing means" refers to methods or processes for receiving data, processing it, and obtaining specific results.

[0678] An "online shopping site" is an e-commerce platform used to sell goods and services over the internet.

[0679] A "communication device" is a device used to send and receive digital or analog signals.

[0680] "Product data" refers to information about a product, such as its features, price, and availability.

[0681] "Visual elements" refer to content that is perceived visually, such as images and designs.

[0682] "Automatic translation" is the process of converting text from one language to another using a mechanical process.

[0683] The system used to implement this application primarily consists of a server and a user terminal. First, the user uses an application on their terminal to input product information and image data required for the e-commerce site. The terminal then sends this information to the server. In this case, an application using React Native is used to build the user interface.

[0684] The server operates an information generation device to generate multilingual commercial transaction information based on received product information. This information is translated into multiple languages ​​via a machine translation API (e.g., Google Translate API). This prepares data that can be used in multiple languages. Cloud platforms such as AWS are used as the underlying technology for this information processing and translation work.

[0685] The server then generates a series of visual design templates and presents them to the user as multiple design options. The design selected by the user is automatically generated by the server as the final e-commerce site. The generated site is then published on the internet using a communication device.

[0686] As a concrete example, if a user wants to sell traditional Japanese crafts, they would input product descriptions, images, and prices through the app. Once the input is complete, the system instantly generates a website written in English, French, Chinese, and other languages, enabling them to reach international customers. This is how the system supports users in entering the international market.

[0687] An example of a prompt message is: "Please enter information about your new product. Enter the product name, description, price, and image files. Then, select your translation language and choose your preferred style from the design templates. Please review the site once it has been automatically generated."

[0688] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0689] Step 1:

[0690] The device (the user's smartphone) accepts product information, price, description, and images as input through its user interface. This information is temporarily stored on the device and prepared for transmission to the server.

[0691] Step 2:

[0692] The terminal packages the product information received from the user and sends it to the server as a structured request. Here, product data is sent to the server as input.

[0693] Step 3:

[0694] The server processes the received product information using an information generation device. At this stage, the product information is stored in a database, and the product information is translated into multiple languages ​​using the Google Translate API. The output is translated commercial transaction information.

[0695] Step 4:

[0696] The server uses the translated data to generate multiple e-commerce site design proposals that users can visually select from. These proposals include different templates and styles. The output here is a list of selectable design proposals.

[0697] Step 5:

[0698] The terminal presents the user with design proposals received from the server. The user selects their preferred design from these proposals and returns that selection to the server. The input is the user's selection, which is then sent to the server.

[0699] Step 6:

[0700] The server generates the final e-commerce website based on the design selected by the user. This process involves integrating commercial information into the chosen design template. The output is a completed, multilingual e-commerce website.

[0701] Step 7:

[0702] The server publishes the generated e-commerce site on the internet, making it accessible to users and international customers via communication devices. The output is the URL of the published site.

[0703] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0704] This invention provides a system for further personalizing multilingual websites by combining it with an emotion engine that recognizes user emotions. This system dynamically adjusts the information generated and presented according to the user's emotions.

[0705] The user launches the application using the device and inputs themes related to the website and image information they wish to use. The device is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions as emotion data. For example, if the user has a happy expression, the device recognizes this emotion as "joy" and takes it into consideration when generating information.

[0706] The results analyzed by the emotion engine are included in the input information sent from the terminal to the server. The server adjusts the information generation module based on the user's emotions, customizing the tone and theme of the generated website to match those emotions. For example, if it is suggested that the user wants to relax, the site design will be adjusted to have calmer and softer colors.

[0707] The server generates multiple design options and sorts them based on a priority system that takes emotional data into account. This allows users to make better choices because designs that match their current emotions are presented at the top of the list.

[0708] Once the user selects their favorite design through their device, the server generates the final website based on the selected design. Emotion-based adjustments are also applied here, providing a more personalized user experience when the website is published.

[0709] This system allows users to easily create and publish websites optimized according to their emotional state, leading to higher user satisfaction.

[0710] The following describes the processing flow.

[0711] Step 1:

[0712] The user launches a website creation application using their device and inputs the necessary theme and image information. The device is equipped with a camera and microphone, which are used to capture and record the user's facial expressions and voice, and an emotion engine analyzes their emotions in real time.

[0713] Step 2:

[0714] The terminal composes the user's input information and sentiment analysis results into data packets and sends them to the server. This data also includes metadata based on the sentiment recognition results.

[0715] Step 3:

[0716] The server analyzes the received data and calls an information generation module. The server considers the emotional data and sets the website's tone and design to match the user's emotions. At this stage, the content's color scheme, layout, and image selection are optimized to match the emotions.

[0717] Step 4:

[0718] The server generates multiple website design options based on the user's requests and emotions. For example, if the user indicates "fun," designs with brighter colors and more dynamic elements will be suggested.

[0719] Step 5:

[0720] The server generates multiple design options, which are then sent to the user's device and presented to them. At this stage, emotional data is used to ensure that the design that best matches the user's emotions at the time is displayed at the top.

[0721] Step 6:

[0722] The user reviews the design proposals presented through their device and selects the one that best matches their feelings and preferences. The device then sends the selection information to the server.

[0723] Step 7:

[0724] The server generates the final website based on the design selected by the user. Here too, sentiment data is used to make final adjustments to the content to maximize the user experience.

[0725] Step 8:

[0726] The server publishes the completed website to the internet and notifies the user of the publication status. Users can then check and manage the site's status via the provided link. In this way, personalized websites tailored to user emotions are efficiently published.

[0727] (Example 2)

[0728] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0729] Providing personalized information based on user emotions is something that existing systems are not adequately capable of. In particular, for web pages requiring multilingual support, it is difficult to provide visual elements and information that reflect the user's emotions and state, which can impair the quality of the user experience. This results in a challenge in meeting the true needs of information recipients and making it difficult to provide optimal information.

[0730] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0731] In this invention, the server includes analysis means for analyzing the user's behavior and recognizing their emotional state; processing means for dynamically adjusting the settings of an information generation module based on the emotional state and generating personalized information; and display means for presenting multiple suggestions from the generated personalized information and prioritizing them. This enables the dynamic provision of information according to the user's emotional state and allows for multilingual customization.

[0732] "Analysis tools" are means for analyzing user behavior and recognizing their emotional state.

[0733] An "information generation module" is a component that dynamically adjusts settings based on the user's emotional state to generate personalized information.

[0734] A "processing means" is a device or program that performs processing based on generated information and has the function of solving a specific problem.

[0735] A "display means" is a device or module that has the function of presenting generated personalized information as multiple suggestions and prioritizing them.

[0736] "Communication means" refers to a device or protocol equipped with the functionality to publish the final generated information over a network.

[0737] The system of this invention enables users to generate and provide personalized information based on their emotions using a terminal. The terminal is equipped with an emotion recognition engine that analyzes the user's voice tone and facial expressions in real time. This engine collects data using a microphone and camera and has the function of classifying emotional states as "joy" or "sadness."

[0738] Emotional data is transmitted from the device to the server. A secure protocol (e.g., HTTPS) is used for communication, ensuring user privacy and data security. The server dynamically adjusts an information generation module based on the emotional data to generate personalized information. This module includes algorithms for customizing tone and themes according to the user's emotions.

[0739] The generated information is provided by the server as multiple suggestions. Each suggestion is created by a generative AI model and prioritized in an order that best suits the user's emotions. The user can review these suggestions on their device and select the design they like best. Based on this selection, the server builds the final website and publishes it on the network via communication.

[0740] For example, a user might want to create a website with the theme of a "fun barbecue event." In this case, the server automatically recognizes the user's emotion as "fun," and prioritizes suggesting bright and lively designs. The prompt could be, "Please suggest a fun design for a barbecue event. Please use warm colors for the theme." This enables emotion-based personalization, allowing the user to receive highly satisfying information.

[0741] This system also features multilingual capabilities, allowing it to automatically provide information in different languages ​​based on user selection. The generated websites offer a more personalized user experience through emotion and language-based customization.

[0742] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0743] Step 1:

[0744] The user launches a dedicated application on their device. They input the website's theme and desired image information into the application's interface. This information represents the user's design intent, and the device receives it as initial data, preparing it for transmission to the server.

[0745] Step 2:

[0746] The device utilizes an emotion recognition engine to analyze the user's voice tone and facial expressions in real time. The input data consists of the user's voice and video data, which are used to determine their emotional state. For example, if the user is laughing, "joy" emotion data is generated. This emotional information is then used for subsequent personalization processes.

[0747] Step 3:

[0748] The terminal combines the analyzed emotion data and user input information into data packets and sends them to the server. HTTPS is used as the transmission protocol for security reasons. The terminal's role is not limited to information transmission, but also to ensuring the security of the communication.

[0749] Step 4:

[0750] The server dynamically adjusts the parameters of the information generation module based on the received sentiment data and user information. The input consists of theme information and emotional state from the user, which determines the website's design tone and theme. A generative AI model is utilized to generate optimal information that aligns with the user's emotions.

[0751] Step 5:

[0752] The server generates multiple design proposals from the generated information and presents them in order of priority. The design proposal generation is performed by a generation AI model that considers user sentiment data to select the most appropriate design. The output is a list of design proposals sorted by priority.

[0753] Step 6:

[0754] The user selects their favorite design from several options presented on the device. The user makes their selection using a selection button within the application, and the chosen design becomes the input for the next step.

[0755] Step 7:

[0756] The server builds the final website based on the design selected by the user. Using the selected design as input data, it prepares for publication on the network via communication methods. Thus, the personalized website is published online as the final deliverable.

[0757] (Application Example 2)

[0758] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0759] In existing brick-and-mortar stores, it is difficult to offer personalized services and products that respond to customers' emotions, and immediate and appropriate responses are required to improve customer satisfaction. Furthermore, when multilingual information is needed, there is the challenge of simultaneously performing language translation and emotion-based personalization, which is complex.

[0760] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0761] In this invention, the server includes terminal means for receiving user input, a recognition engine for recognizing the user's emotions, and processing means for generating multilingual and personalized information using an information generation module based on the recognized emotions. This enables the provision of appropriate information according to emotions, and is expected to improve customer satisfaction.

[0762] A "terminal means for receiving user input" is a device for receiving information and instructions from users, and is used to acquire initial data for emotion recognition and information generation.

[0763] A "recognition engine" is a device or program that analyzes data such as the user's voice tone and facial expressions to identify their emotional state.

[0764] An "information generation module" is a processing device that creates optimal information based on user sentiment data, and generates multilingual and personalized content.

[0765] A "display means" is a device for visually presenting generated information or multiple options to the user.

[0766] An "information processing device" is a processing device that constructs final information based on a proposal selected by the user, thereby realizing personalized information provision.

[0767] "Communication means" refers to a device or system for making final information publicly available on a network and widely accessible.

[0768] A system for realizing this invention includes a terminal for receiving user input, a recognition engine for recognizing emotions, a multilingual information generation module, a display device for presenting information, information processing means for processing information, and communication means for disclosing the final information.

[0769] The device is equipped with a camera and microphone to acquire voice and image data from the user. This data is analyzed by a recognition engine to identify the user's emotional state. Specifically, commercially available facial recognition software and voice analysis technologies (for example, Google Cloud Vision API or Microsoft Azure's emotion recognition tools) can be used as the emotion recognition engine. This engine converts the user's facial expressions and voice tone into emotion data.

[0770] Next, the server uses the acquired sentiment data to create multilingual content tailored to the user using an information generation module. This module utilizes a generative AI model to customize information according to the user's needs and emotions. For example, it can use Python's Natural Language Toolkit (NLTK) to perform natural language processing and generate multilingual text data.

[0771] Subsequently, the multiple proposals created are displayed on a storefront screen for the user to select. The selected proposal is integrated by an information processing system to generate final information. This information is transmitted to the user in real time by a display device and can also be shared over a network via a communication system.

[0772] As a concrete example, in a fashion store, visitors can view their own image on a display along with selectable outfit examples in real time. This information is selected based on the customer's current emotions, providing a more personalized experience. An example of a prompt for a generative AI model would be, "Design a logic that analyzes the emotions of customers from their facial expressions and displays product information tailored to those emotions in real time."

[0773] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0774] Step 1:

[0775] The device uses its camera and microphone to acquire images of the user's face and audio data. This data becomes input and is sent to the recognition engine.

[0776] Step 2:

[0777] The recognition engine analyzes the received image and audio data to recognize the user's emotional state. For example, it uses an image processing algorithm to analyze the user's facial expressions and audio analysis software to analyze the tone of their voice. The output of this process is data indicating the user's emotions.

[0778] Step 3:

[0779] The server drives an information generation module based on recognized emotion data to generate multilingual content. It receives emotion data as input and uses a generation AI model to produce information that resonates with the user's emotions. The output is content customized to match the emotions.

[0780] Step 4:

[0781] The server sends several generated content options to the terminal's display device. The user visually reviews the displayed content options and selects the one they like best. This selection becomes the input for the next processing step.

[0782] Step 5:

[0783] The information processing system constructs the final information based on the user's selection. It receives the user's selected proposal as input and generates the final output by integrating and formatting the data.

[0784] Step 6:

[0785] The final information is presented to the user in real time via the terminal's display device. Furthermore, the information can be made publicly available on the network through communication means, allowing other users and systems to access it.

[0786] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0787] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0788] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0789] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0790] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0791] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0792] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0793] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0794] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0795] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0796] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0797] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0798] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0799] 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.

[0800] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0801] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0802] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0803] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0804] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0805] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0806] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0807] The following is further disclosed regarding the embodiments described above.

[0808] (Claim 1)

[0809] A device that receives user input,

[0810] A processing device that generates multilingual information using an information generation module based on user input,

[0811] A display device that presents multiple options from the generated information,

[0812] Information processing means that generates final information based on the option selected by the user from among the multiple options presented,

[0813] A communication device that publishes the final information on the network,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, characterized in that the information generation module generates information including visual elements using media data provided by the user.

[0817] (Claim 3)

[0818] The system according to claim 1, characterized in that the processing device automatically provides information translated into multiple languages ​​selected by the user.

[0819] "Example 1"

[0820] (Claim 1)

[0821] A terminal device that receives user input,

[0822] A computer device that generates multilingual information using a generation AI model based on the user's input,

[0823] A data display means that presents multiple design proposals from the generated information,

[0824] A data processing means that generates final information based on the design proposal selected by the user,

[0825] A communication mechanism that publishes the final information on the network,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, characterized in that the generating AI model generates information including visual elements using media information provided by the user.

[0829] (Claim 3)

[0830] The system according to claim 1, characterized in that the computer device automatically provides information translated into multiple languages ​​selected by the user.

[0831] "Application Example 1"

[0832] (Claim 1)

[0833] A device that receives user input,

[0834] An information generation device that generates multilingual commercial transaction information based on user input,

[0835] An output device that presents multiple design proposals based on the generated commercial transaction information,

[0836] Information processing means for generating final commercial transaction information based on the design selected by the user from the presented design proposals,

[0837] A means for generating an internationally accessible, multilingual e-commerce site based on the final transaction information,

[0838] A communication device that publishes the e-commerce site on a network and provides it to the global market,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, characterized in that the information generation device generates commercial transaction information including visual elements using product data provided by a user.

[0842] (Claim 3)

[0843] The system according to claim 1, characterized in that the information generation device provides commercial transaction information that has been automatically translated into multiple languages ​​selected by the user.

[0844] "Example 2 of combining an emotion engine"

[0845] (Claim 1)

[0846] Analytical means for analyzing user behavior and recognizing emotional states,

[0847] A processing means that dynamically adjusts the settings of an information generation module based on the emotional state and generates personalized information,

[0848] A display means for presenting multiple suggestions from the generated personalized information and prioritizing them,

[0849] Information processing means that generates final information based on the proposal selected by the user from among the multiple proposals presented,

[0850] A means of communication for publishing the final information on the network,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, characterized in that the information generation module dynamically adjusts information including visual elements in consideration of the user's emotional state.

[0854] (Claim 3)

[0855] The system according to claim 1, characterized in that the processing means automatically provides information translated into multiple languages ​​selected by the user and performs emotion-based customization.

[0856] "Application example 2 when combining with an emotional engine"

[0857] (Claim 1)

[0858] A terminal means for receiving user input,

[0859] A recognition engine that recognizes the emotions of the user,

[0860] A processing means that generates multilingual and personalized information using an information generation module based on the recognized emotion,

[0861] A display means that presents multiple options from the generated information,

[0862] Information processing means that generates final information based on the option selected by the user from among the multiple options presented,

[0863] A means of communication for publishing the final information on the network,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, characterized in that the information generation module generates information in which visual elements are dynamically adjusted based on the user's emotional data.

[0867] (Claim 3)

[0868] The system according to claim 1, characterized in that the processing means analyzes the emotions of visitors and updates the information presented based on the results in real time. [Explanation of Symbols]

[0869] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A device that receives user input, A processing device that generates multilingual information using an information generation module based on user input, A display device that presents multiple options from the generated information, Information processing means that generates final information based on the option selected by the user from among the multiple options presented, A communication device that publishes the final information on the network, A system that includes this.

2. The system according to claim 1, characterized in that the information generation module generates information including visual elements using media data provided by the user.

3. The system according to claim 1, characterized in that the processing device automatically provides information translated into multiple languages ​​selected by the user.

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