system

Abstract

We provide the system. [Solution] A means of receiving project information, converting it into multiple languages, and generating a funding page, A means to automatically submit applications to the crowdfunding platform in the target country, A means of generating public relations materials based on progress information and sending them to multiple communication media, 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, 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 modern global market, for venture companies to grow by utilizing crowdfunding, entering overseas markets is important. However, there are language barriers and different platform requirements in each country, and relying on specialized consulting incurs high costs, so these factors have become major hurdles preventing companies from entering. There is a need for a system that can address such problems.

Means for Solving the Problems

[0005] This invention provides a system that receives project information, translates it into multiple languages, and generates funding pages for each country. Furthermore, by automating the application process to crowdfunding platforms in each country, it simplifies procedures and supports companies' overseas market entry by generating promotional materials based on progress and effectively distributing them through social media and other communication channels. This overcomes language barriers, reduces consulting costs, and makes it easier for more companies to explore overseas markets.

[0006] "Project information" refers to information that describes the purpose, content, and target amount of a crowdfunding campaign.

[0007] "Translating into another language" means translating text written in one language into another language.

[0008] A "funding page" is a webpage created for crowdfunding, which presents project information to potential supporters.

[0009] "Automatically executing an application" means that a program will fill in the necessary information without human intervention and submit it via an online form or similar system.

[0010] "Progress information" refers to information that shows the progress of a project, the results achieved, and future plans.

[0011] "Public relations materials" are documents and graphic content created to effectively communicate information about a project.

[0012] "Communication media" refers to means or channels for transmitting information, and examples include social media, email, and websites.

[0013] "Image and video content" refers to digital data such as still images and videos that contain visual information.

[0014] "Social media analysis" is the process of analyzing user behavior and trends on social media, collecting data, and deriving useful information.

[0015] "Optimizing according to market trends" means adjusting strategies and processes based on the current market situation and forecasts, aiming for the most effective results. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This 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 Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

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

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

[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 relates to a system in which users input project information via a terminal, which is then processed by a server in multiple languages ​​for each country, and a crowdfunding campaign page is generated. This system has multiple functions and supports the international expansion of projects.

[0038] First, the user enters necessary information such as the project title, description, target amount, images, and videos using their own device. This input information is sent from the user's device to the server. Based on the received information, the server executes a program to perform multilingual translation. Natural language processing (NLP) technology is used for translation, and image recognition technology can also be used to translate text information contained within images and videos.

[0039] After the translation is complete, the server incorporates the translation results into templates tailored to each language, generating appropriate funding pages for each. For example, it might translate a Japanese project description into English and French, and then apply a page design that is appropriate for the culture and customs of each language.

[0040] Next, the server executes the application process on behalf of the user. It accesses the APIs or web pages of crowdfunding platforms in each country and automatically fills in the required application fields. If legal documents or platform-specific information are required, the server may translate them and present them to the user, requesting any necessary action.

[0041] In addition, project progress information is continuously collected, and drafts for social media posts and newsletters are generated as promotional materials. These promotional materials are created in multiple languages ​​by the server and delivered according to user-defined timings. The server analyzes the feedback received after delivery and incorporates the results into future content generation to ensure more effective information dissemination.

[0042] For example, when a Japanese startup company attempts to crowdfund a new product overseas, this system allows them to quickly and easily create pages for supporters in English-speaking and French-speaking regions, enabling effective promotion. In this way, the present invention removes language and cultural barriers, supporting easy entry into the global market.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user enters project information (title, description, target amount, images, videos, etc.) via their device and sends it to the server.

[0046] Step 2:

[0047] The server analyzes the received project information and identifies the languages ​​corresponding to each country. Natural language processing (NLP) is used to prepare the text for translation into the target language.

[0048] Step 3:

[0049] The server extracts text information from images and videos using image recognition technology and translates it as well. It understands the content and generates translations appropriate to the cultural context.

[0050] Step 4:

[0051] The server incorporates translated content in each language into templates and generates fundraising pages adapted for each country. The design and layout are also adjusted to suit each region.

[0052] Step 5:

[0053] The server initiates the application process in each country via the crowdfunding platform's API or webpage. It automatically fills in the necessary forms and submits the information, taking legal requirements into consideration.

[0054] Step 6:

[0055] The server periodically checks the project's progress and generates promotional materials (SNS posts, newsletters, etc.) in various languages.

[0056] Step 7:

[0057] The server distributes public relations materials to various communication channels at the scheduled time. After distribution, feedback and engagement data are collected and used to improve future public relations activities.

[0058] Step 8:

[0059] Users monitor server results via their terminals and modify or add project information as needed. The server receives these updates and reprocesses the data.

[0060] (Example 1)

[0061] 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."

[0062] In today's global market environment, it is essential to widely publicize projects in multiple languages ​​and efficiently submit applications to crowdfunding platforms in each region. However, traditional methods have faced difficulties in multilingualizing project information and conducting appropriate marketing in each region due to language barriers and cultural differences. To address this challenge, there is a need to establish effective public relations methods based on project progress information.

[0063] 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.

[0064] This invention includes a server that receives project information from a user, translates the information into multiple different languages ​​using natural language processing technology to generate publicly available documents, automatically constructs recruitment pages using templates corresponding to each language based on the translated information, and automatically performs the application process to regional fundraising platforms. This enables smooth international expansion of the project and allows for effective public relations and marketing activities.

[0065] "Receiving project information from the user" refers to the server retrieving detailed project data entered by the user via their device.

[0066] "Natural language processing technology" refers to the technology that allows computers to understand, analyze, and generate natural human language, and is used for translation and text analysis.

[0067] "Translating into multiple different languages" refers to accurately and culturally appropriate rephrasing from the original language into two or more other languages.

[0068] "Generating publicly available materials" refers to creating informational content based on collected information and data, to be provided to relevant markets and target customers.

[0069] "Automatically building fundraising pages using templates" refers to generating web pages for fundraising and donations without manual intervention, by using pre-defined templates with standardized structures and designs.

[0070] "Automating the application process to regional fundraising platforms" means that the server automatically submits the necessary information and handles the application process for crowdfunding and other fundraising systems that differ from region to region.

[0071] "Collecting progress data" refers to gathering and managing information about the progress of a project during its execution.

[0072] "Generating and sending promotional materials via multiple communication channels" refers to creating content for advertising and information dissemination and distributing it through various communication channels such as email and social media.

[0073] "Analyzing the feedback received after transmission and reflecting the analysis results in the creation of future materials" means analyzing the feedback received on the distributed information and using that insight to improve the effectiveness of future information content.

[0074] This invention is a system that enables users to efficiently and effectively expand their projects internationally. It begins with the user inputting project information via a terminal and sending it to a server. Project information includes title, description, target amount, images, videos, and more.

[0075] The server uses natural language processing technology to perform multilingual translation based on the received information. A generative AI model is used for translation, translating from Japanese to English, French, and other languages. Furthermore, image recognition technology is utilized to detect text within visual content and convert it to the required language. This ensures the creation of accurate and culturally appropriate project documents.

[0076] Next, the server automatically constructs the recruitment page using templates corresponding to each language based on the translated information. In this process, a design and layout that is appropriate for the culture and customs of each country is applied, resulting in a more user-friendly page.

[0077] The server also automatically submits applications to local crowdfunding platforms. If specific legal documents or information are required, it can provide users with translated materials and request their cooperation. This reduces manual work for users and allows them to complete project applications quickly in each country.

[0078] Once a project begins, the server automatically collects progress information and generates promotional materials. Here too, AI modeling technology is utilized to create social media posts and newsletters in multiple languages. These materials are distributed to multiple communication channels at user-defined timings. Feedback received after distribution is analyzed and incorporated into future promotional activities.

[0079] For example, when a Japanese startup seeks to raise international funds for a new product, this system can be used to quickly create campaign pages for English-speaking and French-speaking supporters and effectively promote the product. An example of a prompt would be: "Translate the project description written in Japanese into English and French, and create crowdfunding pages that reflect the cultural and design differences of each language."

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The user uses a terminal to enter information about the project. This data includes title, description, target amount, images, and videos. The user's input actions send this data from the terminal to the server. As output, the terminal provides the server with a set of the input data.

[0083] Step 2:

[0084] The server analyzes project information received from the user. First, it extracts text data and translates it into multiple different languages ​​using natural language processing (NLP) techniques. Generative AI models are utilized in this process. The input is the received project information, and the output is the translated text data.

[0085] Step 3:

[0086] The server uses image recognition technology to identify text within images and videos. It analyzes image and video data as input, extracts text information, and then translates this extracted text into various languages, adding it to previously translated text. The output is an updated multilingual text set.

[0087] Step 4:

[0088] The server automatically generates crowdfunding campaign pages by selecting a template corresponding to each language based on the translated information. Here, template selection and construction are automated, and a design appropriate to cultural conventions is applied. The input is translated data, and the output is a completed multilingual web page.

[0089] Step 5:

[0090] The server submits applications to various crowdfunding platforms on behalf of the user. It automatically enters the necessary information using APIs and web interfaces, and proceeds with the application process. Inputs include data from the fundraising page and platform requirements, and output is application completion status information.

[0091] Step 6:

[0092] As the project progresses, the server continuously collects progress data and generates promotional materials. These materials are then organized into drafts for social media posts and newsletters. The input is collected progress data, and the output is multilingual promotional materials.

[0093] Step 7:

[0094] The server distributes public relations materials to multiple communication channels at scheduled times. It analyzes the feedback received after distribution and uses it to improve future content creation. The input is the public relations materials, and the output is the feedback received and its analysis results.

[0095] (Application Example 1)

[0096] 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."

[0097] In recent years, the e-commerce market has become increasingly globalized, requiring sales strategies that are tailored to the cultures and languages ​​of each country. In particular, in international markets, it is necessary to effectively appeal to multinational consumers with product ideas and to quickly generate sales and funding. However, achieving this using traditional methods requires considerable effort and cost, and continuously conducting optimal public relations activities in line with market trends presents significant challenges.

[0098] 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.

[0099] This invention includes a server that provides means for receiving project information, converting it into multiple languages, and generating an e-commerce solicitation page; means for automatically submitting applications to fundraising platforms in target countries; means for generating information dissemination materials based on progress information and transmitting them to multiple communication media; means for acquiring product ideas entered by users, transmitting this information to the cloud for translation; and means for automatically generating product pages optimized for the culture of each country based on the translation results, making them available for sale. This makes it possible to sell products and raise funds quickly and efficiently in the international market.

[0100] "Project information" refers to detailed information about products or services offered by users, such as the title, description, target amount, images, and videos.

[0101] An "e-commerce recruitment page" refers to an online page generated using translated multilingual information, intended for the sale of goods or fundraising.

[0102] A "fundraising platform" refers to an online service that showcases multiple projects or products and solicits support or purchases from consumers.

[0103] "Progress information" refers to data that shows the status of a project or product sales, including deadlines and target achievement rates.

[0104] "Information dissemination materials" refer to documents and digital content used to introduce products or projects to the market or consumers.

[0105] "Communication medium" refers to a means used to transmit information, including email, social media, and newsletters.

[0106] A "product idea" refers to a concept or plan for a new product or service devised by a user.

[0107] "Translation" refers to the process of converting information written in one language into another language.

[0108] "Cloud" refers to a service that provides resources on the internet for storing and processing data.

[0109] A "culture-optimized page" refers to a webpage whose design and content have been adjusted to take into account the culture and customs of the target country or region.

[0110] The system for realizing this invention consists of multiple computer programs. These programs operate by combining a user-owned terminal, server infrastructure, and cloud computing services.

[0111] First, users enter project information using a device such as a smartphone or tablet. This project information includes the title, description, target amount, images, and videos of the product or service. The entered information is then transmitted to the server via the network.

[0112] The server uses natural language processing technology to perform multilingual translation based on the received project information. The translation process utilizes Google® Translate API and Azure® Cognitive Services. Furthermore, it can translate text information within images and videos using image recognition technology.

[0113] After multilingual translation is complete, the server generates e-commerce recruitment pages with designs tailored to the culture and customs of each country. This process uses a template engine, and page generation is performed in a Node.js environment.

[0114] Next, the server automatically submits applications to fundraising platforms in each country. Here, the application process is efficiently executed by utilizing the APIs of each platform. Once the application is complete, the system sends a notification to the user.

[0115] Sales progress information for products and services is updated regularly, and the server generates informational materials based on this information. These materials are sent via social media and email newsletters, disseminating information to the market through virtual communication channels. This information dissemination activity is managed using Amazon S3 and Amazon DynamoDB.

[0116] As a concrete example, if a user utilizes a system to sell a new eco-bag design to the international market, they first enter the eco-bag's details into a terminal, which is then automatically translated into multiple languages ​​online and posted on sales websites in each country. This makes it easy to gain support and purchases from consumers around the world.

[0117] An example of a prompt message is: "Register an international sales project for a new eco-bag design and generate a multilingual translation page. Then, automatically submit applications to crowdfunding platforms in each country and create promotional materials for social media."

[0118] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0119] Step 1:

[0120] The user enters project information using a terminal. This information includes the product name, description, target amount, images, and videos, which are then sent from the terminal to the server. At this stage, the user's input data is ready to be transferred to the server.

[0121] Step 2:

[0122] The server analyzes project information received from the terminal. The analysis extracts text information and uses image recognition technology to recognize text information contained in images and videos. The input is raw user data, and the output is translatable text data.

[0123] Step 3:

[0124] The server uses natural language processing technology to translate the analyzed text information into multiple languages. This process utilizes the Google Translate API and Azure Cognitive Services, generating text data in each language as output.

[0125] Step 4:

[0126] The server generates e-commerce recruitment pages optimized for each country's culture based on the translation results. This process utilizes a template engine, automatically incorporating designs and layouts suitable for multinational markets. The input is translated text data, and the output is recruitment pages for each country.

[0127] Step 5:

[0128] The server automatically submits applications to various fundraising platforms in different countries based on the generated e-commerce fundraising pages. Information is entered via API, and the application status is returned. The input is the content of the fundraising page, and the output is the application completion status.

[0129] Step 6:

[0130] The server collects progress information and generates informational materials based on it. These materials are sent to the communication medium specified by the user, such as social media or a newsletter. The input is progress information, and the output is informational materials.

[0131] Step 7:

[0132] Users receive informational materials generated by the server and disseminate them to the market using social media and email. Users then review this information and create prompt messages tailored to local culture and trends.

[0133] 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.

[0134] This invention is a system that translates project information into multiple languages ​​to generate funding pages for each country, and further incorporates an emotion engine to provide optimal information tailored to the user's emotions. This system is realized when the user inputs project information using a terminal, and the server processes that information.

[0135] First, the user inputs project details from their device. This information includes the project title, detailed description, target amount, images, and videos. The device organizes this information and sends it to the server. The server analyzes the received information and translates the project information into the languages ​​of the target countries. This translation uses natural language processing and image recognition technologies to ensure that the text and media are appropriately expressed according to the culture and business practices of each country.

[0136] Next, the server uses an emotion engine to analyze user input and interactions, and evaluates the user's emotional state. This emotion recognition is reflected in how project information is presented and the page design, customizing it according to the user's emotional response. For example, when a specific emotional state is recognized, the priority of information and emphasis points are adjusted. This adjustment makes it possible for users to experience the project in a more engaging way.

[0137] Furthermore, the server also has the capability to automatically execute applications on crowdfunding platforms. This is achieved by utilizing the APIs or web pages of each country's platform and automatically filling in the necessary information. If legal requirements or additional information are requested, it will be translated and appropriate instructions will be provided to the user.

[0138] During project execution, the server periodically utilizes an emotion engine to analyze project progress and prepare and generate promotional materials. These materials are distributed at appropriate times via social media, email, etc., and feedback from users and supporters is accumulated on the server. This feedback is then used to improve content for future promotional activities.

[0139] For example, if the emotion engine detects that a particular project is causing anxiety among supporters, the server can adjust the page content to emphasize reassuring information and highlight positive aspects. This makes it possible to create an environment where potential supporters can participate in the project with peace of mind.

[0140] In this way, this system provides a comprehensive solution for smoothly advancing projects across language and cultural barriers, and strongly supports users aiming for success in the global market.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The user enters project information (e.g., title, description, target amount, images, videos) via their device and sends that information to the server.

[0144] Step 2:

[0145] The server analyzes the project information it receives. It identifies multiple target languages ​​and uses natural language processing techniques to translate the text information into those languages.

[0146] Step 3:

[0147] The server analyzes the image and video content included in the project using image recognition technology, extracts text information, translates it, and incorporates it as multilingual content.

[0148] Step 4:

[0149] The server uses an emotion engine to evaluate the user's emotional state. Emotion recognition is performed based on the user's input information and past interactions.

[0150] Step 5:

[0151] Based on the results of the emotion engine, the server adjusts the content and layout of the crowdfunding page to provide the most appropriate expression for each country's culture and emotions.

[0152] Step 6:

[0153] The server accesses the crowdfunding platform and automatically submits project applications via API or web page. It enters the necessary information and handles any legal requirements appropriately.

[0154] Step 7:

[0155] During the project, the server periodically collects progress information, performs another analysis using the sentiment engine, and generates optimized promotional materials.

[0156] Step 8:

[0157] The server distributes the publicity materials to various communication channels such as social media and email, as configured, and collects user feedback. This feedback is then used to improve future materials.

[0158] Step 9:

[0159] The system checks the information received from the user's terminal and updates or corrects project information. The server then receives this updated information and performs reprocessing.

[0160] (Example 2)

[0161] 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".

[0162] In the international expansion of a project, effective information dissemination that transcends language and cultural differences is required. Furthermore, rapid and automated responses to digital fundraising platforms in each country, as well as sentiment analysis to optimize appeals to supporters, are necessary. Addressing these challenges and achieving efficient and effective fundraising is highly desirable.

[0163] 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.

[0164] This invention includes a server that receives project information, converts it into multiple languages ​​using natural language processing technology to generate information pages, automatically submits an application to a digital fundraising platform in a target country using the translated information, and evaluates the user's emotional state to dynamically optimize the way project information is presented. This enables efficient and effective dissemination of project information across language and cultural barriers, and facilitates attractive appeals to potential supporters.

[0165] "Project information" refers to a collection of all data related to a project, including its title, details, target amount, images, videos, and more.

[0166] "Natural language processing technology" refers to technologies that use computers to understand, generate, and manipulate human language.

[0167] An "information page" is a web page or electronic document created to display the content and progress of a project.

[0168] A "digital fundraising platform" is a platform used to raise funds online.

[0169] "Emotional state" refers to information about the emotions a user expresses, and represents their psychological response to the project.

[0170] "Dynamic optimization" means automatically adjusting the content and design to suit the situation at any given time.

[0171] "Electronic communication media" refers to electronic means used to transmit information, such as email and social media.

[0172] Users input project information using their own devices. This information includes the project title, details, target amount, images, videos, etc. The user's device formats the entered information and sends it to the server. The HTTP / HTTPS protocol is used for this information transmission.

[0173] The server uses natural language processing (NLP) technology to analyze received project information and translate it into multiple languages, utilizing a natural language processing system. Specifically, it uses open-source NLP libraries and commercial services to convert text. Furthermore, the server applies image recognition technology to images and videos, adjusting these media to suit the culture of each country.

[0174] The translated information is generated as an information page and becomes data for the server to automatically submit applications to digital fundraising platforms. The server uses the APIs and automation tools of each platform to input the necessary information and manage the application process.

[0175] Furthermore, the server analyzes user interactions and input information using an emotion engine to evaluate the user's emotional state. Based on this evaluation, it dynamically optimizes the content and design of information pages to improve the user experience.

[0176] While the project is underway, the server monitors progress and automatically generates reports. This generation utilizes a template system and AI models. The generated reports are distributed to users and supporters via electronic communication media to gather additional feedback.

[0177] As a concrete example, a user might send a prompt to the server saying, "Please input project information, translate it, and create funding pages for each country. Also, analyze user sentiment and optimize the information." The system then processes and generates the content accordingly. However, for specific sentiment analysis and translation, a generative AI model is used to improve accuracy.

[0178] The program integrates advanced data processing technologies at each step to support daily operations, enabling the smooth operation of the entire system.

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The user uses a terminal to enter project information. The information entered includes the project title, details, target amount, and image / video files in text format. The terminal formats the input data and converts it into JSON format, which can be sent to the server. The output is JSON data sent to the server.

[0182] Step 2:

[0183] The server receives project information from the terminal. The input is project data in JSON format, which the server parses and translates into multiple languages ​​using natural language processing techniques. Multiple translation algorithms and libraries may be utilized during this process. The output is text data translated into various languages.

[0184] Step 3:

[0185] The server analyzes image and video media data and uses image recognition technology to process the content to suit each culture. The input is image and video files, and the output is appropriately adjusted media data.

[0186] Step 4:

[0187] The server generates an information page based on the translated and adjusted data. This information page is a webpage with content customized for the target country. The output is HTML data properly formatted as a webpage.

[0188] Step 5:

[0189] The server uses the generated information page to prepare and execute applications to digital fundraising platforms. The input consists of the information page and translation data, and the server automatically sends the application data through each platform's API. The output is a success or failure status code.

[0190] Step 6:

[0191] The server collects user interaction data and uses an emotion engine to evaluate the user's emotional state. Inputs include user behavior history and clickstream data, and the server analyzes the emotional state and generates an emotion report as output.

[0192] Step 7:

[0193] The server dynamically optimizes how project information is presented based on collected emotional states and feedback. The input is an emotional report, and the output is a customized information page.

[0194] Step 8:

[0195] The server monitors project progress and generates reports. The input is project progress data, and the reports are generated by an AI model based on a template. The output is a distributable PDF or HTML document.

[0196] Step 9:

[0197] The server distributes the generated reports to users and supporters via electronic communication media. The input is the report data, and the output is the notifications sent via email, social media, etc.

[0198] (Application Example 2)

[0199] 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".

[0200] Traditional crowdfunding systems and e-commerce sites face challenges such as communication barriers due to language and cultural differences, and a lack of optimal information provision tailored to user emotions. Furthermore, the absence of real-time means to address user anxieties and doubts can create significant psychological barriers for supporters and buyers. Conventional systems struggle to improve user experience and accurately reflect market needs. This invention solves these problems, enabling the creation of effective funding pages and product pages with a global market context.

[0201] 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.

[0202] This invention includes a server that provides means for receiving project information, translating it into multiple languages, and generating a crowdfunding page; means for automatically submitting applications to crowdfunding platforms in other countries; means for generating promotional materials based on progress information and transmitting them to multiple communication media; and means for analyzing the user's emotional state and adjusting the presentation of information according to that emotion. This enables the provision of optimal information to users across language and cultural barriers, and by customizing information according to their emotions, the user experience is improved, and the success rate of projects in the global market increases.

[0203] "Project information" refers to data that includes detailed descriptions, images, videos, and target amounts for projects and products that users register as targets for funding or online sales.

[0204] "Multiple languages" refers to the diversity of languages ​​in different countries and regions, and is primarily a medium for transmitting information through translation.

[0205] A "funding page" is an online information page published to solicit support for a project, and it includes details about the project, the target amount, and the progress status.

[0206] "Means for automatically executing applications" refers to methods or devices for automating necessary procedures and information input within crowdfunding platforms and related systems.

[0207] "Public relations materials" refer to informational content such as text, images, and videos created to promote a project or inform the public about its progress.

[0208] "Communication media" refers to channels and platforms for the exchange of information, including the internet, email, and social media.

[0209] "User emotional state" refers to the psychological reactions and feelings that users exhibit when they encounter information about a project, and can be inferred through text analysis and other methods.

[0210] "Means for adjusting the presentation of information" refers to methods or devices for changing the display format or order of information based on the user's emotional state.

[0211] This invention describes a system in which a user inputs project information using their own device, and a server then uses this information to perform automated multilingual translation and provide emotionally responsive information. The information input by the user includes the project name, details, target amount, images, and videos. This information is transmitted from the device to the server.

[0212] Upon receiving the input project information, the server uses natural language processing technology to translate it into multiple languages. Specifically, it processes not only text information but also media content using image recognition technology, including translation and cultural adaptation. The translated information is then incorporated into the funding page.

[0213] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state and adjusts how information is presented based on that data. For example, if the server detects that the user is feeling anxious, the page content is customized to emphasize elements that provide a sense of security. This customization feature removes psychological barriers for the user, providing a more user-friendly project experience.

[0214] The server also automates applications to crowdfunding platforms. It supports platform APIs and web interfaces in various countries, streamlining the process by automatically entering necessary information. Progress information is regularly updated and generated as promotional materials. These materials are delivered to backers and buyers through multiple communication channels. These materials may include content created by generative AI models.

[0215] For example, if a user says, "I'm not sure if I really need this product," the AI ​​model will use that prompt to generate a response that alleviates their anxiety. An example of a prompt might be, "Create a program that adjusts product information based on the user's emotions. If the user expresses anxiety, highlight the warranty information."

[0216] The main hardware used includes servers and user terminals, while the software includes EmotionEngine for sentiment analysis and APIs for processing text and images.

[0217] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0218] Step 1:

[0219] The user uses a terminal to enter project information.

[0220] The input includes the project name, details, target amount, images, and videos.

[0221] The terminal processes the input information, standardizes the data format, and sends it to the server.

[0222] Step 2:

[0223] The server analyzes the received project information and uses natural language processing technology to translate it into multiple languages.

[0224] This translation process takes text data as input and uses a multilingual translation API to obtain the output.

[0225] The output will provide a set of project information for each language.

[0226] Step 3:

[0227] The server automatically generates the funding page using the translated information.

[0228] We utilize image recognition technology to adapt images and video content to different cultures.

[0229] The generated pages are saved to a database and made available for distribution to various countries.

[0230] Step 4:

[0231] The server uses an emotion engine to analyze the user's emotional state based on their input.

[0232] The input includes text data and interaction logs.

[0233] An emotion analysis algorithm is applied to obtain the user's emotional state as output.

[0234] Step 5:

[0235] The server adjusts the information displayed on the funding page based on the user's emotional state.

[0236] If a specific emotion (e.g., anxiety) is detected, the content will be emphasized in accordance with that emotion.

[0237] Customize page design and information emphasis to generate optimized output.

[0238] Step 6:

[0239] The server automatically submits applications to crowdfunding platforms.

[0240] Enter the required information into the API of the target platform and complete the application.

[0241] The output will be confirmation of application completion or response data.

[0242] Step 7:

[0243] Based on project progress information, the server generates promotional materials.

[0244] We use AI models to analyze progress data and create optimal documents.

[0245] Send the created promotional materials to communication channels such as social media and email, and obtain feedback on their output.

[0246] Step 8:

[0247] The server stores feedback information received from users and supporters and uses it for future public relations activities.

[0248] The input includes comments and reviews.

[0249] We conduct emotional analysis to identify areas for improvement and factors for success, and then formulate an improvement plan as the output.

[0250] 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.

[0251] 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.

[0252] 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.

[0253] [Second Embodiment]

[0254] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0255] 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.

[0256] 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).

[0257] 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.

[0258] 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.

[0259] 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).

[0260] 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.

[0261] 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.

[0262] 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.

[0263] 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.

[0264] 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.

[0265] 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".

[0266] This invention relates to a system in which users input project information via a terminal, which is then processed by a server in multiple languages ​​for each country, and a crowdfunding campaign page is generated. This system has multiple functions and supports the international expansion of projects.

[0267] First, the user enters necessary information such as the project title, description, target amount, images, and videos using their own device. This input information is sent from the user's device to the server. Based on the received information, the server executes a program to perform multilingual translation. Natural language processing (NLP) technology is used for translation, and image recognition technology can also be used to translate text information contained within images and videos.

[0268] After the translation is complete, the server incorporates the translation results into templates tailored to each language, generating appropriate funding pages for each. For example, it might translate a Japanese project description into English and French, and then apply a page design that is appropriate for the culture and customs of each language.

[0269] Next, the server executes the application process on behalf of the user. It accesses the APIs or web pages of crowdfunding platforms in each country and automatically fills in the required application fields. If legal documents or platform-specific information are required, the server may translate them and present them to the user, requesting any necessary action.

[0270] In addition, project progress information is continuously collected, and drafts for social media posts and newsletters are generated as promotional materials. These promotional materials are created in multiple languages ​​by the server and delivered according to user-defined timings. The server analyzes the feedback received after delivery and incorporates the results into future content generation to ensure more effective information dissemination.

[0271] For example, when a Japanese startup company attempts to crowdfund a new product overseas, this system allows them to quickly and easily create pages for supporters in English-speaking and French-speaking regions, enabling effective promotion. In this way, the present invention removes language and cultural barriers, supporting easy entry into the global market.

[0272] The following describes the processing flow.

[0273] Step 1:

[0274] The user inputs project information (title, description, target amount, image, video, etc.) through the terminal and sends it to the server.

[0275] Step 2:

[0276] The server analyzes the received project information and identifies the languages corresponding to each country. Using natural language processing (NLP), it prepares to translate the text into the target languages.

[0277] Step 3:

[0278] The server extracts the text information in the images and videos using image recognition technology and also translates them. It understands the content and generates translations suitable for the cultural background.

[0279] Step 4:

[0280] AThe server incorporates the translated content in each language into templates and generates funding solicitation pages applicable to each country. The design and layout are also adjusted to be suitable for each region.

[0281] Step 5:

[0282] The server starts the application process in each country via the API of the crowdfunding platform or the web page. It automatically fills in the required forms and submits the information considering legal requirements.

[0283] Step 6:

[0284] The server regularly checks the progress of the project and generates materials for publicity activities (such as SNS posts, newsletters, etc.) in each language.

[0285] Step 7:

[0286] The server distributes promotional materials to each communication medium at the timing when they are set. After distribution, feedback and engagement data are collected and reflected in subsequent promotional activities.

[0287] Step 8:

[0288] The user monitors the results of the server through the terminal and modifies or adds project information as needed. The server receives this update and performs reprocessing.

[0289] (Example 1)

[0290] Next, 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".

[0291] In the modern global market environment, it is required to widely announce projects in multiple languages and realize efficient applications to crowdfunding platforms in various regions. However, with the previous methods, due to language barriers and cultural differences, it has been difficult to multilingualize project information and conduct appropriate marketing in various regions. To solve this problem, it is also required to establish an effective promotional method based on the progress information of the project.

[0292] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0293] In this invention, the server includes means for receiving project information from a user, translating the information into multiple different languages using natural language processing technology to generate publicity materials, automatically constructing a recruitment page using templates corresponding to each language based on the translated information, and automatically performing an application process to the fundraising platforms in various regions. Thereby, the international expansion of the project is smoothly carried out, and promotional and marketing activities can be effectively implemented.

[0294] "Receiving project information from the user" refers to the server retrieving detailed project data entered by the user via their device.

[0295] "Natural language processing technology" refers to the technology that allows computers to understand, analyze, and generate natural human language, and is used for translation and text analysis.

[0296] "Translating into multiple different languages" refers to accurately and culturally appropriate rephrasing from the original language into two or more other languages.

[0297] "Generating publicly available materials" refers to creating informational content based on collected information and data, to be provided to relevant markets and target customers.

[0298] "Automatically building fundraising pages using templates" refers to generating web pages for fundraising and donations without manual intervention, by using pre-defined templates with standardized structures and designs.

[0299] "Automating the application process to regional fundraising platforms" means that the server automatically submits the necessary information and handles the application process for crowdfunding and other fundraising systems that differ from region to region.

[0300] "Collecting progress data" refers to gathering and managing information about the progress of a project during its execution.

[0301] "Generating and sending promotional materials via multiple communication channels" refers to creating content for advertising and information dissemination and distributing it through various communication channels such as email and social media.

[0302] "Analyzing the feedback received after transmission and reflecting the analysis results in the creation of future materials" means analyzing the feedback received on the distributed information and using that insight to improve the effectiveness of future information content.

[0303] The present invention is a system that enables a user to efficiently and effectively conduct international expansion of a project. It starts when the user inputs project information via a terminal and transmits it to the server. The project information includes a title, description, target amount, image, video, etc.

[0304] Based on the received information, the server performs multilingual translation using natural language processing technology. A generative AI model is used for the translation work, and translation is carried out from Japanese to multiple languages such as English and French. Also, image recognition technology is utilized to detect text within visual content and convert it into the required language. Thereby, accurate and culturally appropriate project materials are created.

[0305] Subsequently, the server automatically constructs a recruitment page using templates corresponding to each language for the translated information. In this process, by applying designs and layouts according to the cultures and customs of each country, a more user-friendly page is provided.

[0306] The server further automatically applies for the project to crowdfunding platforms in each region. When specific legal documents and information are required, the user can be asked to respond by providing the translated materials. Thereby, the user can reduce manual work and quickly complete project applications in various countries.

[0307] When the project is started, the server automatically collects progress information and generates publicity materials. Here too, the technology of the generative AI model is utilized to create SNS posts and newsletters in multiple languages. The materials are distributed to multiple communication media at the timing set by the user. The feedback obtained after distribution is analyzed and reflected in subsequent publicity activities.

[0308] For example, when a Japanese startup seeks to raise international funds for a new product, this system can be used to quickly create campaign pages for English-speaking and French-speaking supporters and effectively promote the product. An example of a prompt would be: "Translate the project description written in Japanese into English and French, and create crowdfunding pages that reflect the cultural and design differences of each language."

[0309] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0310] Step 1:

[0311] The user uses a terminal to enter information about the project. This data includes title, description, target amount, images, and videos. The user's input actions send this data from the terminal to the server. As output, the terminal provides the server with a set of the input data.

[0312] Step 2:

[0313] The server analyzes project information received from the user. First, it extracts text data and translates it into multiple different languages ​​using natural language processing (NLP) techniques. Generative AI models are utilized in this process. The input is the received project information, and the output is the translated text data.

[0314] Step 3:

[0315] The server uses image recognition technology to identify text within images and videos. It analyzes image and video data as input, extracts text information, and then translates this extracted text into various languages, adding it to previously translated text. The output is an updated multilingual text set.

[0316] Step 4:

[0317] The server automatically generates crowdfunding campaign pages by selecting a template corresponding to each language based on the translated information. Here, template selection and construction are automated, and a design appropriate to cultural conventions is applied. The input is translated data, and the output is a completed multilingual web page.

[0318] Step 5:

[0319] The server submits applications to various crowdfunding platforms on behalf of the user. It automatically enters the necessary information using APIs and web interfaces, and proceeds with the application process. Inputs include data from the fundraising page and platform requirements, and output is application completion status information.

[0320] Step 6:

[0321] As the project progresses, the server continuously collects progress data and generates promotional materials. These materials are then organized into drafts for social media posts and newsletters. The input is collected progress data, and the output is multilingual promotional materials.

[0322] Step 7:

[0323] The server distributes public relations materials to multiple communication channels at scheduled times. It analyzes the feedback received after distribution and uses it to improve future content creation. The input is the public relations materials, and the output is the feedback received and its analysis results.

[0324] (Application Example 1)

[0325] 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 glasses 214 will be referred to as the "terminal."

[0326] In recent years, the e-commerce market has become increasingly globalized, requiring sales strategies that are tailored to the cultures and languages ​​of each country. In particular, in international markets, it is necessary to effectively appeal to multinational consumers with product ideas and to quickly generate sales and funding. However, achieving this using traditional methods requires considerable effort and cost, and continuously conducting optimal public relations activities in line with market trends presents significant challenges.

[0327] 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.

[0328] This invention includes a server that provides means for receiving project information, converting it into multiple languages, and generating an e-commerce solicitation page; means for automatically submitting applications to fundraising platforms in target countries; means for generating information dissemination materials based on progress information and transmitting them to multiple communication media; means for acquiring product ideas entered by users, transmitting this information to the cloud for translation; and means for automatically generating product pages optimized for the culture of each country based on the translation results, making them available for sale. This makes it possible to sell products and raise funds quickly and efficiently in the international market.

[0329] "Project information" refers to detailed information about products or services offered by users, such as the title, description, target amount, images, and videos.

[0330] An "e-commerce recruitment page" refers to an online page generated using translated multilingual information, intended for the sale of goods or fundraising.

[0331] A "fundraising platform" refers to an online service that showcases multiple projects or products and solicits support or purchases from consumers.

[0332] "Progress information" refers to data that shows the status of a project or product sales, including deadlines and target achievement rates.

[0333] "Information dissemination materials" refer to documents and digital content used to introduce products or projects to the market or consumers.

[0334] "Communication medium" refers to a means used to transmit information, including email, social media, and newsletters.

[0335] A "product idea" refers to a concept or plan for a new product or service devised by a user.

[0336] "Translation" refers to the process of converting information written in one language into another language.

[0337] "Cloud" refers to a service that provides resources on the internet for storing and processing data.

[0338] A "culture-optimized page" refers to a webpage whose design and content have been adjusted to take into account the culture and customs of the target country or region.

[0339] The system for realizing this invention consists of multiple computer programs. These programs operate by combining a user-owned terminal, server infrastructure, and cloud computing services.

[0340] First, users enter project information using a device such as a smartphone or tablet. This project information includes the title, description, target amount, images, and videos of the product or service. The entered information is then transmitted to the server via the network.

[0341] The server uses natural language processing technology to perform multilingual translation based on the received project information. The translation process utilizes Google Translate API and Azure Cognitive Services. Furthermore, it can translate text information within images and videos using image recognition technology.

[0342] After multilingual translation is complete, the server generates e-commerce recruitment pages with designs tailored to the culture and customs of each country. This process uses a template engine, and page generation is performed in a Node.js environment.

[0343] Next, the server automatically submits applications to fundraising platforms in each country. Here, the application process is efficiently executed by utilizing the APIs of each platform. Once the application is complete, the system sends a notification to the user.

[0344] Sales progress information for products and services is updated regularly, and the server generates informational materials based on this information. These materials are sent via social media and email newsletters, disseminating information to the market through virtual communication channels. This information dissemination activity is managed using Amazon S3 and Amazon DynamoDB.

[0345] As a concrete example, if a user utilizes a system to sell a new eco-bag design to the international market, they first enter the eco-bag's details into a terminal, which is then automatically translated into multiple languages ​​online and posted on sales websites in each country. This makes it easy to gain support and purchases from consumers around the world.

[0346] An example of a prompt message is: "Register an international sales project for a new eco-bag design and generate a multilingual translation page. Then, automatically submit applications to crowdfunding platforms in each country and create promotional materials for social media."

[0347] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0348] Step 1:

[0349] The user enters project information using a terminal. This information includes the product name, description, target amount, images, and videos, which are then sent from the terminal to the server. At this stage, the user's input data is ready to be transferred to the server.

[0350] Step 2:

[0351] The server analyzes project information received from the terminal. The analysis extracts text information and uses image recognition technology to recognize text information contained in images and videos. The input is raw user data, and the output is translatable text data.

[0352] Step 3:

[0353] The server uses natural language processing technology to translate the analyzed text information into multiple languages. This process utilizes the Google Translate API and Azure Cognitive Services, generating text data in each language as output.

[0354] Step 4:

[0355] The server generates e-commerce recruitment pages optimized for each country's culture based on the translation results. This process utilizes a template engine, automatically incorporating designs and layouts suitable for multinational markets. The input is translated text data, and the output is recruitment pages for each country.

[0356] Step 5:

[0357] The server automatically submits applications to various fundraising platforms in different countries based on the generated e-commerce fundraising pages. Information is entered via API, and the application status is returned. The input is the content of the fundraising page, and the output is the application completion status.

[0358] Step 6:

[0359] The server collects progress information and generates informational materials based on it. These materials are sent to the communication medium specified by the user, such as social media or a newsletter. The input is progress information, and the output is informational materials.

[0360] Step 7:

[0361] Users receive informational materials generated by the server and disseminate them to the market using social media and email. Users then review this information and create prompt messages tailored to local culture and trends.

[0362] 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.

[0363] This invention is a system that translates project information into multiple languages ​​to generate funding pages for each country, and further incorporates an emotion engine to provide optimal information tailored to the user's emotions. This system is realized when the user inputs project information using a terminal, and the server processes that information.

[0364] First, the user inputs project details from their device. This information includes the project title, detailed description, target amount, images, and videos. The device organizes this information and sends it to the server. The server analyzes the received information and translates the project information into the languages ​​of the target countries. This translation uses natural language processing and image recognition technologies to ensure that the text and media are appropriately expressed according to the culture and business practices of each country.

[0365] Next, the server uses an emotion engine to analyze user input and interactions, and evaluates the user's emotional state. This emotion recognition is reflected in how project information is presented and the page design, customizing it according to the user's emotional response. For example, when a specific emotional state is recognized, the priority of information and emphasis points are adjusted. This adjustment makes it possible for users to experience the project in a more engaging way.

[0366] Furthermore, the server also has the capability to automatically execute applications on crowdfunding platforms. This is achieved by utilizing the APIs or web pages of each country's platform and automatically filling in the necessary information. If legal requirements or additional information are requested, it will be translated and appropriate instructions will be provided to the user.

[0367] During project execution, the server periodically utilizes an emotion engine to analyze project progress and prepare and generate promotional materials. These materials are distributed at appropriate times via social media, email, etc., and feedback from users and supporters is accumulated on the server. This feedback is then used to improve content for future promotional activities.

[0368] For example, if the emotion engine detects that a particular project is causing anxiety among supporters, the server can adjust the page content to emphasize reassuring information and highlight positive aspects. This makes it possible to create an environment where potential supporters can participate in the project with peace of mind.

[0369] In this way, this system provides a comprehensive solution for smoothly advancing projects across language and cultural barriers, and strongly supports users aiming for success in the global market.

[0370] The following describes the processing flow.

[0371] Step 1:

[0372] The user enters project information (e.g., title, description, target amount, images, videos) via their device and sends that information to the server.

[0373] Step 2:

[0374] The server analyzes the project information it receives. It identifies multiple target languages ​​and uses natural language processing techniques to translate the text information into those languages.

[0375] Step 3:

[0376] The server analyzes the image and video content included in the project using image recognition technology, extracts text information, translates it, and incorporates it as multilingual content.

[0377] Step 4:

[0378] The server uses an emotion engine to evaluate the user's emotional state. Emotion recognition is performed based on the user's input information and past interactions.

[0379] Step 5:

[0380] Based on the results of the emotion engine, the server adjusts the content and layout of the crowdfunding page to provide the most appropriate expression for each country's culture and emotions.

[0381] Step 6:

[0382] The server accesses the crowdfunding platform and automatically submits project applications via API or web page. It enters the necessary information and handles any legal requirements appropriately.

[0383] Step 7:

[0384] During the project, the server periodically collects progress information, performs another analysis using the sentiment engine, and generates optimized promotional materials.

[0385] Step 8:

[0386] The server distributes the publicity materials to various communication channels such as social media and email, as configured, and collects user feedback. This feedback is then used to improve future materials.

[0387] Step 9:

[0388] The system checks the information received from the user's terminal and updates or corrects project information. The server then receives this updated information and performs reprocessing.

[0389] (Example 2)

[0390] 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".

[0391] In the international expansion of a project, effective information dissemination that transcends language and cultural differences is required. Furthermore, rapid and automated responses to digital fundraising platforms in each country, as well as sentiment analysis to optimize appeals to supporters, are necessary. Addressing these challenges and achieving efficient and effective fundraising is highly desirable.

[0392] 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.

[0393] This invention includes a server that receives project information, converts it into multiple languages ​​using natural language processing technology to generate information pages, automatically submits an application to a digital fundraising platform in a target country using the translated information, and evaluates the user's emotional state to dynamically optimize the way project information is presented. This enables efficient and effective dissemination of project information across language and cultural barriers, and facilitates attractive appeals to potential supporters.

[0394] "Project information" refers to a collection of all data related to a project, including its title, details, target amount, images, videos, and more.

[0395] "Natural language processing technology" refers to technologies that use computers to understand, generate, and manipulate human language.

[0396] An "information page" is a web page or electronic document created to display the content and progress of a project.

[0397] A "digital fundraising platform" is a platform used to raise funds online.

[0398] "Emotional state" refers to information about the emotions a user expresses, and represents their psychological response to the project.

[0399] "Dynamic optimization" means automatically adjusting the content and design to suit the situation at any given time.

[0400] "Electronic communication media" refers to electronic means used to transmit information, such as email and social media.

[0401] Users input project information using their own devices. This information includes the project title, details, target amount, images, videos, etc. The user's device formats the entered information and sends it to the server. The HTTP / HTTPS protocol is used for this information transmission.

[0402] The server uses natural language processing (NLP) technology to analyze received project information and translate it into multiple languages, utilizing a natural language processing system. Specifically, it uses open-source NLP libraries and commercial services to convert text. Furthermore, the server applies image recognition technology to images and videos, adjusting these media to suit the culture of each country.

[0403] The translated information is generated as an information page and becomes data for the server to automatically submit applications to digital fundraising platforms. The server uses the APIs and automation tools of each platform to input the necessary information and manage the application process.

[0404] Furthermore, the server analyzes user interactions and input information using an emotion engine to evaluate the user's emotional state. Based on this evaluation, it dynamically optimizes the content and design of information pages to improve the user experience.

[0405] While the project is underway, the server monitors progress and automatically generates reports. This generation utilizes a template system and AI models. The generated reports are distributed to users and supporters via electronic communication media to gather additional feedback.

[0406] As a concrete example, a user might send a prompt to the server saying, "Please input project information, translate it, and create funding pages for each country. Also, analyze user sentiment and optimize the information." The system then processes and generates the content accordingly. However, for specific sentiment analysis and translation, a generative AI model is used to improve accuracy.

[0407] The program integrates advanced data processing technologies at each step to support daily operations, enabling the smooth operation of the entire system.

[0408] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0409] Step 1:

[0410] The user uses a terminal to enter project information. The information entered includes the project title, details, target amount, and image / video files in text format. The terminal formats the input data and converts it into JSON format, which can be sent to the server. The output is JSON data sent to the server.

[0411] Step 2:

[0412] The server receives project information from the terminal. The input is project data in JSON format, which the server parses and translates into multiple languages ​​using natural language processing techniques. Multiple translation algorithms and libraries may be utilized during this process. The output is text data translated into various languages.

[0413] Step 3:

[0414] The server analyzes image and video media data and uses image recognition technology to process the content to suit each culture. The input is image and video files, and the output is appropriately adjusted media data.

[0415] Step 4:

[0416] The server generates an information page based on the translated and adjusted data. This information page is a webpage with content customized for the target country. The output is HTML data properly formatted as a webpage.

[0417] Step 5:

[0418] The server uses the generated information page to prepare and execute applications to digital fundraising platforms. The input consists of the information page and translation data, and the server automatically sends the application data through each platform's API. The output is a success or failure status code.

[0419] Step 6:

[0420] The server collects user interaction data and uses an emotion engine to evaluate the user's emotional state. Inputs include user behavior history and clickstream data, and the server analyzes the emotional state and generates an emotion report as output.

[0421] Step 7:

[0422] The server dynamically optimizes how project information is presented based on collected emotional states and feedback. The input is an emotional report, and the output is a customized information page.

[0423] Step 8:

[0424] The server monitors project progress and generates reports. The input is project progress data, and the reports are generated by an AI model based on a template. The output is a distributable PDF or HTML document.

[0425] Step 9:

[0426] The server distributes the generated reports to users and supporters via electronic communication media. The input is the report data, and the output is the notifications sent via email, social media, etc.

[0427] (Application Example 2)

[0428] 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 will be referred to as the "terminal."

[0429] Traditional crowdfunding systems and e-commerce sites face challenges such as communication barriers due to language and cultural differences, and a lack of optimal information provision tailored to user emotions. Furthermore, the absence of real-time means to address user anxieties and doubts can create significant psychological barriers for supporters and buyers. Conventional systems struggle to improve user experience and accurately reflect market needs. This invention solves these problems, enabling the creation of effective funding pages and product pages with a global market context.

[0430] 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.

[0431] This invention includes a server that provides means for receiving project information, translating it into multiple languages, and generating a crowdfunding page; means for automatically submitting applications to crowdfunding platforms in other countries; means for generating promotional materials based on progress information and transmitting them to multiple communication media; and means for analyzing the user's emotional state and adjusting the presentation of information according to that emotion. This enables the provision of optimal information to users across language and cultural barriers, and by customizing information according to their emotions, the user experience is improved, and the success rate of projects in the global market increases.

[0432] "Project information" refers to data that includes detailed descriptions, images, videos, and target amounts for projects and products that users register as targets for funding or online sales.

[0433] "Multiple languages" refers to the diversity of languages ​​in different countries and regions, and is primarily a medium for transmitting information through translation.

[0434] A "funding page" is an online information page published to solicit support for a project, and it includes details about the project, the target amount, and the progress status.

[0435] "Means for automatically executing applications" refers to methods or devices for automating necessary procedures and information input within crowdfunding platforms and related systems.

[0436] "Public relations materials" refer to informational content such as text, images, and videos created to promote a project or inform the public about its progress.

[0437] "Communication media" refers to channels and platforms for the exchange of information, including the internet, email, and social media.

[0438] "User emotional state" refers to the psychological reactions and feelings that users exhibit when they encounter information about a project, and can be inferred through text analysis and other methods.

[0439] "Means for adjusting the presentation of information" refers to methods or devices for changing the display format or order of information based on the user's emotional state.

[0440] This invention describes a system in which a user inputs project information using their own device, and a server then uses this information to perform automated multilingual translation and provide emotionally responsive information. The information input by the user includes the project name, details, target amount, images, and videos. This information is transmitted from the device to the server.

[0441] Upon receiving the input project information, the server uses natural language processing technology to translate it into multiple languages. Specifically, it processes not only text information but also media content using image recognition technology, including translation and cultural adaptation. The translated information is then incorporated into the funding page.

[0442] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state and adjusts how information is presented based on that data. For example, if the server detects that the user is feeling anxious, the page content is customized to emphasize elements that provide a sense of security. This customization feature removes psychological barriers for the user, providing a more user-friendly project experience.

[0443] The server also automates applications to crowdfunding platforms. It supports platform APIs and web interfaces in various countries, streamlining the process by automatically entering necessary information. Progress information is regularly updated and generated as promotional materials. These materials are delivered to backers and buyers through multiple communication channels. These materials may include content created by generative AI models.

[0444] For example, if a user says, "I'm not sure if I really need this product," the AI ​​model will use that prompt to generate a response that alleviates their anxiety. An example of a prompt might be, "Create a program that adjusts product information based on the user's emotions. If the user expresses anxiety, highlight the warranty information."

[0445] The main hardware used includes servers and user terminals, while the software includes EmotionEngine for sentiment analysis and APIs for processing text and images.

[0446] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0447] Step 1:

[0448] The user uses a terminal to enter project information.

[0449] The input includes the project name, details, target amount, images, and videos.

[0450] The terminal processes the input information, standardizes the data format, and sends it to the server.

[0451] Step 2:

[0452] The server analyzes the received project information and uses natural language processing technology to translate it into multiple languages.

[0453] This translation process takes text data as input and uses a multilingual translation API to obtain the output.

[0454] The output will provide a set of project information for each language.

[0455] Step 3:

[0456] The server automatically generates the funding page using the translated information.

[0457] We utilize image recognition technology to adapt images and video content to different cultures.

[0458] The generated pages are saved to a database and made available for distribution to various countries.

[0459] Step 4:

[0460] The server uses an emotion engine to analyze the user's emotional state based on their input.

[0461] The input includes text data and interaction logs.

[0462] An emotion analysis algorithm is applied to obtain the user's emotional state as output.

[0463] Step 5:

[0464] The server adjusts the information displayed on the funding page based on the user's emotional state.

[0465] If a specific emotion (e.g., anxiety) is detected, the content will be emphasized in accordance with that emotion.

[0466] Customize page design and information emphasis to generate optimized output.

[0467] Step 6:

[0468] The server automatically submits applications to crowdfunding platforms.

[0469] Enter the required information into the API of the target platform and complete the application.

[0470] The output will be confirmation of application completion or response data.

[0471] Step 7:

[0472] Based on project progress information, the server generates promotional materials.

[0473] We use AI models to analyze progress data and create optimal documents.

[0474] Send the created promotional materials to communication channels such as social media and email, and obtain feedback on their output.

[0475] Step 8:

[0476] The server stores feedback information received from users and supporters and uses it for future public relations activities.

[0477] The input includes comments and reviews.

[0478] We conduct emotional analysis to identify areas for improvement and factors for success, and then formulate an improvement plan as the output.

[0479] 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.

[0480] 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.

[0481] 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.

[0482] [Third Embodiment]

[0483] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0484] 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.

[0485] 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).

[0486] 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.

[0487] 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.

[0488] 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).

[0489] 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.

[0490] 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.

[0491] 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.

[0492] 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.

[0493] 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.

[0494] 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".

[0495] This invention relates to a system in which users input project information via a terminal, which is then processed by a server in multiple languages ​​for each country, and a crowdfunding campaign page is generated. This system has multiple functions and supports the international expansion of projects.

[0496] First, the user enters necessary information such as the project title, description, target amount, images, and videos using their own device. This input information is sent from the user's device to the server. Based on the received information, the server executes a program to perform multilingual translation. Natural language processing (NLP) technology is used for translation, and image recognition technology can also be used to translate text information contained within images and videos.

[0497] After the translation is complete, the server incorporates the translation results into templates tailored to each language, generating appropriate funding pages for each. For example, it might translate a Japanese project description into English and French, and then apply a page design that is appropriate for the culture and customs of each language.

[0498] Next, the server executes the application process on behalf of the user. It accesses the APIs or web pages of crowdfunding platforms in each country and automatically fills in the required application fields. If legal documents or platform-specific information are required, the server may translate them and present them to the user, requesting any necessary action.

[0499] In addition, project progress information is continuously collected, and drafts for social media posts and newsletters are generated as promotional materials. These promotional materials are created in multiple languages ​​by the server and delivered according to user-defined timings. The server analyzes the feedback received after delivery and incorporates the results into future content generation to ensure more effective information dissemination.

[0500] For example, when a Japanese startup company attempts to crowdfund a new product overseas, this system allows them to quickly and easily create pages for supporters in English-speaking and French-speaking regions, enabling effective promotion. In this way, the present invention removes language and cultural barriers, supporting easy entry into the global market.

[0501] The following describes the processing flow.

[0502] Step 1:

[0503] The user enters project information (title, description, target amount, images, videos, etc.) via their device and sends it to the server.

[0504] Step 2:

[0505] The server analyzes the received project information and identifies the languages ​​corresponding to each country. Natural language processing (NLP) is used to prepare the text for translation into the target language.

[0506] Step 3:

[0507] The server extracts text information from images and videos using image recognition technology and translates it as well. It understands the content and generates translations appropriate to the cultural context.

[0508] Step 4:

[0509] The server incorporates translated content in each language into templates and generates fundraising pages adapted for each country. The design and layout are also adjusted to suit each region.

[0510] Step 5:

[0511] The server initiates the application process in each country via the crowdfunding platform's API or webpage. It automatically fills in the necessary forms and submits the information, taking legal requirements into consideration.

[0512] Step 6:

[0513] The server periodically checks the project's progress and generates promotional materials (SNS posts, newsletters, etc.) in various languages.

[0514] Step 7:

[0515] The server distributes public relations materials to various communication channels at the scheduled time. After distribution, feedback and engagement data are collected and used to improve future public relations activities.

[0516] Step 8:

[0517] Users monitor server results via their terminals and modify or add project information as needed. The server receives these updates and reprocesses the data.

[0518] (Example 1)

[0519] 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."

[0520] In today's global market environment, it is essential to widely publicize projects in multiple languages ​​and efficiently submit applications to crowdfunding platforms in each region. However, traditional methods have faced difficulties in multilingualizing project information and conducting appropriate marketing in each region due to language barriers and cultural differences. To address this challenge, there is a need to establish effective public relations methods based on project progress information.

[0521] 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.

[0522] This invention includes a server that receives project information from a user, translates the information into multiple different languages ​​using natural language processing technology to generate publicly available documents, automatically constructs recruitment pages using templates corresponding to each language based on the translated information, and automatically performs the application process to regional fundraising platforms. This enables smooth international expansion of the project and allows for effective public relations and marketing activities.

[0523] "Receiving project information from the user" refers to the server retrieving detailed project data entered by the user via their device.

[0524] "Natural language processing technology" refers to the technology that allows computers to understand, analyze, and generate natural human language, and is used for translation and text analysis.

[0525] "Translating into multiple different languages" refers to accurately and culturally appropriate rephrasing from the original language into two or more other languages.

[0526] "Generating publicly available materials" refers to creating informational content based on collected information and data, to be provided to relevant markets and target customers.

[0527] "Automatically building fundraising pages using templates" refers to generating web pages for fundraising and donations without manual intervention, by using pre-defined templates with standardized structures and designs.

[0528] "Automating the application process to regional fundraising platforms" means that the server automatically submits the necessary information and handles the application process for crowdfunding and other fundraising systems that differ from region to region.

[0529] "Collecting progress data" refers to gathering and managing information about the progress of a project during its execution.

[0530] "Generating and sending promotional materials via multiple communication channels" refers to creating content for advertising and information dissemination and distributing it through various communication channels such as email and social media.

[0531] "Analyzing the feedback received after transmission and reflecting the analysis results in the creation of future materials" means analyzing the feedback received on the distributed information and using that insight to improve the effectiveness of future information content.

[0532] This invention is a system that enables users to efficiently and effectively expand their projects internationally. It begins with the user inputting project information via a terminal and sending it to a server. Project information includes title, description, target amount, images, videos, and more.

[0533] The server uses natural language processing technology to perform multilingual translation based on the received information. A generative AI model is used for translation, translating from Japanese to English, French, and other languages. Furthermore, image recognition technology is utilized to detect text within visual content and convert it to the required language. This ensures the creation of accurate and culturally appropriate project documents.

[0534] Next, the server automatically constructs the recruitment page using templates corresponding to each language based on the translated information. In this process, a design and layout that is appropriate for the culture and customs of each country is applied, resulting in a more user-friendly page.

[0535] The server also automatically submits applications to local crowdfunding platforms. If specific legal documents or information are required, it can provide users with translated materials and request their cooperation. This reduces manual work for users and allows them to complete project applications quickly in each country.

[0536] Once a project begins, the server automatically collects progress information and generates promotional materials. Here too, AI modeling technology is utilized to create social media posts and newsletters in multiple languages. These materials are distributed to multiple communication channels at user-defined timings. Feedback received after distribution is analyzed and incorporated into future promotional activities.

[0537] For example, when a Japanese startup seeks to raise international funds for a new product, this system can be used to quickly create campaign pages for English-speaking and French-speaking supporters and effectively promote the product. An example of a prompt would be: "Translate the project description written in Japanese into English and French, and create crowdfunding pages that reflect the cultural and design differences of each language."

[0538] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0539] Step 1:

[0540] The user uses a terminal to enter information about the project. This data includes title, description, target amount, images, and videos. The user's input actions send this data from the terminal to the server. As output, the terminal provides the server with a set of the input data.

[0541] Step 2:

[0542] The server analyzes project information received from the user. First, it extracts text data and translates it into multiple different languages ​​using natural language processing (NLP) techniques. Generative AI models are utilized in this process. The input is the received project information, and the output is the translated text data.

[0543] Step 3:

[0544] The server uses image recognition technology to identify text within images and videos. It analyzes image and video data as input, extracts text information, and then translates this extracted text into various languages, adding it to previously translated text. The output is an updated multilingual text set.

[0545] Step 4:

[0546] The server automatically generates crowdfunding campaign pages by selecting a template corresponding to each language based on the translated information. Here, template selection and construction are automated, and a design appropriate to cultural conventions is applied. The input is translated data, and the output is a completed multilingual web page.

[0547] Step 5:

[0548] The server submits applications to various crowdfunding platforms on behalf of the user. It automatically enters the necessary information using APIs and web interfaces, and proceeds with the application process. Inputs include data from the fundraising page and platform requirements, and output is application completion status information.

[0549] Step 6:

[0550] As the project progresses, the server continuously collects progress data and generates promotional materials. These materials are then organized into drafts for social media posts and newsletters. The input is collected progress data, and the output is multilingual promotional materials.

[0551] Step 7:

[0552] The server distributes public relations materials to multiple communication channels at scheduled times. It analyzes the feedback received after distribution and uses it to improve future content creation. The input is the public relations materials, and the output is the feedback received and its analysis results.

[0553] (Application Example 1)

[0554] 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."

[0555] In recent years, the e-commerce market has become increasingly globalized, requiring sales strategies that are tailored to the cultures and languages ​​of each country. In particular, in international markets, it is necessary to effectively appeal to multinational consumers with product ideas and to quickly generate sales and funding. However, achieving this using traditional methods requires considerable effort and cost, and continuously conducting optimal public relations activities in line with market trends presents significant challenges.

[0556] 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.

[0557] This invention includes a server that provides means for receiving project information, converting it into multiple languages, and generating an e-commerce solicitation page; means for automatically submitting applications to fundraising platforms in target countries; means for generating information dissemination materials based on progress information and transmitting them to multiple communication media; means for acquiring product ideas entered by users, transmitting this information to the cloud for translation; and means for automatically generating product pages optimized for the culture of each country based on the translation results, making them available for sale. This makes it possible to sell products and raise funds quickly and efficiently in the international market.

[0558] "Project information" refers to detailed information about products or services offered by users, such as the title, description, target amount, images, and videos.

[0559] An "e-commerce recruitment page" refers to an online page generated using translated multilingual information, intended for the sale of goods or fundraising.

[0560] A "fundraising platform" refers to an online service that showcases multiple projects or products and solicits support or purchases from consumers.

[0561] "Progress information" refers to data that shows the status of a project or product sales, including deadlines and target achievement rates.

[0562] "Information dissemination materials" refer to documents and digital content used to introduce products or projects to the market or consumers.

[0563] "Communication medium" refers to a means used to transmit information, including email, social media, and newsletters.

[0564] A "product idea" refers to a concept or plan for a new product or service devised by a user.

[0565] "Translation" refers to the process of converting information written in one language into another language.

[0566] "Cloud" refers to a service that provides resources on the internet for storing and processing data.

[0567] A "culture-optimized page" refers to a webpage whose design and content have been adjusted to take into account the culture and customs of the target country or region.

[0568] The system for realizing this invention consists of multiple computer programs. These programs operate by combining a user-owned terminal, server infrastructure, and cloud computing services.

[0569] First, users enter project information using a device such as a smartphone or tablet. This project information includes the title, description, target amount, images, and videos of the product or service. The entered information is then transmitted to the server via the network.

[0570] The server uses natural language processing technology to perform multilingual translation based on the received project information. The translation process utilizes Google Translate API and Azure Cognitive Services. Furthermore, it can translate text information within images and videos using image recognition technology.

[0571] After multilingual translation is complete, the server generates e-commerce recruitment pages with designs tailored to the culture and customs of each country. This process uses a template engine, and page generation is performed in a Node.js environment.

[0572] Next, the server automatically submits applications to fundraising platforms in each country. Here, the application process is efficiently executed by utilizing the APIs of each platform. Once the application is complete, the system sends a notification to the user.

[0573] Sales progress information for products and services is updated regularly, and the server generates informational materials based on this information. These materials are sent via social media and email newsletters, disseminating information to the market through virtual communication channels. This information dissemination activity is managed using Amazon S3 and Amazon DynamoDB.

[0574] As a concrete example, if a user utilizes a system to sell a new eco-bag design to the international market, they first enter the eco-bag's details into a terminal, which is then automatically translated into multiple languages ​​online and posted on sales websites in each country. This makes it easy to gain support and purchases from consumers around the world.

[0575] An example of a prompt message is: "Register an international sales project for a new eco-bag design and generate a multilingual translation page. Then, automatically submit applications to crowdfunding platforms in each country and create promotional materials for social media."

[0576] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0577] Step 1:

[0578] The user enters project information using a terminal. This information includes the product name, description, target amount, images, and videos, which are then sent from the terminal to the server. At this stage, the user's input data is ready to be transferred to the server.

[0579] Step 2:

[0580] The server analyzes project information received from the terminal. The analysis extracts text information and uses image recognition technology to recognize text information contained in images and videos. The input is raw user data, and the output is translatable text data.

[0581] Step 3:

[0582] The server uses natural language processing technology to translate the analyzed text information into multiple languages. This process utilizes the Google Translate API and Azure Cognitive Services, generating text data in each language as output.

[0583] Step 4:

[0584] The server generates e-commerce recruitment pages optimized for each country's culture based on the translation results. This process utilizes a template engine, automatically incorporating designs and layouts suitable for multinational markets. The input is translated text data, and the output is recruitment pages for each country.

[0585] Step 5:

[0586] The server automatically submits applications to various fundraising platforms in different countries based on the generated e-commerce fundraising pages. Information is entered via API, and the application status is returned. The input is the content of the fundraising page, and the output is the application completion status.

[0587] Step 6:

[0588] The server collects progress information and generates informational materials based on it. These materials are sent to the communication medium specified by the user, such as social media or a newsletter. The input is progress information, and the output is informational materials.

[0589] Step 7:

[0590] Users receive informational materials generated by the server and disseminate them to the market using social media and email. Users then review this information and create prompt messages tailored to local culture and trends.

[0591] 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.

[0592] This invention is a system that translates project information into multiple languages ​​to generate funding pages for each country, and further incorporates an emotion engine to provide optimal information tailored to the user's emotions. This system is realized when the user inputs project information using a terminal, and the server processes that information.

[0593] First, the user inputs project details from their device. This information includes the project title, detailed description, target amount, images, and videos. The device organizes this information and sends it to the server. The server analyzes the received information and translates the project information into the languages ​​of the target countries. This translation uses natural language processing and image recognition technologies to ensure that the text and media are appropriately expressed according to the culture and business practices of each country.

[0594] Next, the server uses an emotion engine to analyze user input and interactions, and evaluates the user's emotional state. This emotion recognition is reflected in how project information is presented and the page design, customizing it according to the user's emotional response. For example, when a specific emotional state is recognized, the priority of information and emphasis points are adjusted. This adjustment makes it possible for users to experience the project in a more engaging way.

[0595] Furthermore, the server also has the capability to automatically execute applications on crowdfunding platforms. This is achieved by utilizing the APIs or web pages of each country's platform and automatically filling in the necessary information. If legal requirements or additional information are requested, it will be translated and appropriate instructions will be provided to the user.

[0596] During project execution, the server periodically utilizes an emotion engine to analyze project progress and prepare and generate promotional materials. These materials are distributed at appropriate times via social media, email, etc., and feedback from users and supporters is accumulated on the server. This feedback is then used to improve content for future promotional activities.

[0597] For example, if the emotion engine detects that a particular project is causing anxiety among supporters, the server can adjust the page content to emphasize reassuring information and highlight positive aspects. This makes it possible to create an environment where potential supporters can participate in the project with peace of mind.

[0598] In this way, this system provides a comprehensive solution for smoothly advancing projects across language and cultural barriers, and strongly supports users aiming for success in the global market.

[0599] The following describes the processing flow.

[0600] Step 1:

[0601] The user enters project information (e.g., title, description, target amount, images, videos) via their device and sends that information to the server.

[0602] Step 2:

[0603] The server analyzes the project information it receives. It identifies multiple target languages ​​and uses natural language processing techniques to translate the text information into those languages.

[0604] Step 3:

[0605] The server analyzes the image and video content included in the project using image recognition technology, extracts text information, translates it, and incorporates it as multilingual content.

[0606] Step 4:

[0607] The server uses an emotion engine to evaluate the user's emotional state. Emotion recognition is performed based on the user's input information and past interactions.

[0608] Step 5:

[0609] Based on the results of the emotion engine, the server adjusts the content and layout of the crowdfunding page to provide the most appropriate expression for each country's culture and emotions.

[0610] Step 6:

[0611] The server accesses the crowdfunding platform and automatically submits project applications via API or web page. It enters the necessary information and handles any legal requirements appropriately.

[0612] Step 7:

[0613] During the project, the server periodically collects progress information, performs another analysis using the sentiment engine, and generates optimized promotional materials.

[0614] Step 8:

[0615] The server distributes the publicity materials to various communication channels such as social media and email, as configured, and collects user feedback. This feedback is then used to improve future materials.

[0616] Step 9:

[0617] The system checks the information received from the user's terminal and updates or corrects project information. The server then receives this updated information and performs reprocessing.

[0618] (Example 2)

[0619] 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."

[0620] In the international expansion of a project, effective information dissemination that transcends language and cultural differences is required. Furthermore, rapid and automated responses to digital fundraising platforms in each country, as well as sentiment analysis to optimize appeals to supporters, are necessary. Addressing these challenges and achieving efficient and effective fundraising is highly desirable.

[0621] 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.

[0622] This invention includes a server that receives project information, converts it into multiple languages ​​using natural language processing technology to generate information pages, automatically submits an application to a digital fundraising platform in a target country using the translated information, and evaluates the user's emotional state to dynamically optimize the way project information is presented. This enables efficient and effective dissemination of project information across language and cultural barriers, and facilitates attractive appeals to potential supporters.

[0623] "Project information" refers to a collection of all data related to a project, including its title, details, target amount, images, videos, and more.

[0624] "Natural language processing technology" refers to technologies that use computers to understand, generate, and manipulate human language.

[0625] An "information page" is a web page or electronic document created to display the content and progress of a project.

[0626] A "digital fundraising platform" is a platform used to raise funds online.

[0627] "Emotional state" refers to information about the emotions a user expresses, and represents their psychological response to the project.

[0628] "Dynamic optimization" means automatically adjusting the content and design to suit the situation at any given time.

[0629] "Electronic communication media" refers to electronic means used to transmit information, such as email and social media.

[0630] Users input project information using their own devices. This information includes the project title, details, target amount, images, videos, etc. The user's device formats the entered information and sends it to the server. The HTTP / HTTPS protocol is used for this information transmission.

[0631] The server uses natural language processing (NLP) technology to analyze received project information and translate it into multiple languages, utilizing a natural language processing system. Specifically, it uses open-source NLP libraries and commercial services to convert text. Furthermore, the server applies image recognition technology to images and videos, adjusting these media to suit the culture of each country.

[0632] The translated information is generated as an information page and becomes data for the server to automatically submit applications to digital fundraising platforms. The server uses the APIs and automation tools of each platform to input the necessary information and manage the application process.

[0633] Furthermore, the server analyzes user interactions and input information using an emotion engine to evaluate the user's emotional state. Based on this evaluation, it dynamically optimizes the content and design of information pages to improve the user experience.

[0634] While the project is underway, the server monitors progress and automatically generates reports. This generation utilizes a template system and AI models. The generated reports are distributed to users and supporters via electronic communication media to gather additional feedback.

[0635] As a concrete example, a user might send a prompt to the server saying, "Please input project information, translate it, and create funding pages for each country. Also, analyze user sentiment and optimize the information." The system then processes and generates the content accordingly. However, for specific sentiment analysis and translation, a generative AI model is used to improve accuracy.

[0636] The program integrates advanced data processing technologies at each step to support daily operations, enabling the smooth operation of the entire system.

[0637] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0638] Step 1:

[0639] The user uses a terminal to enter project information. The information entered includes the project title, details, target amount, and image / video files in text format. The terminal formats the input data and converts it into JSON format, which can be sent to the server. The output is JSON data sent to the server.

[0640] Step 2:

[0641] The server receives project information from the terminal. The input is project data in JSON format, which the server parses and translates into multiple languages ​​using natural language processing techniques. Multiple translation algorithms and libraries may be utilized during this process. The output is text data translated into various languages.

[0642] Step 3:

[0643] The server analyzes image and video media data and uses image recognition technology to process the content to suit each culture. The input is image and video files, and the output is appropriately adjusted media data.

[0644] Step 4:

[0645] The server generates an information page based on the translated and adjusted data. This information page is a webpage with content customized for the target country. The output is HTML data properly formatted as a webpage.

[0646] Step 5:

[0647] The server uses the generated information page to prepare and execute applications to digital fundraising platforms. The input consists of the information page and translation data, and the server automatically sends the application data through each platform's API. The output is a success or failure status code.

[0648] Step 6:

[0649] The server collects user interaction data and uses an emotion engine to evaluate the user's emotional state. Inputs include user behavior history and clickstream data, and the server analyzes the emotional state and generates an emotion report as output.

[0650] Step 7:

[0651] The server dynamically optimizes how project information is presented based on collected emotional states and feedback. The input is an emotional report, and the output is a customized information page.

[0652] Step 8:

[0653] The server monitors project progress and generates reports. The input is project progress data, and the reports are generated by an AI model based on a template. The output is a distributable PDF or HTML document.

[0654] Step 9:

[0655] The server distributes the generated reports to users and supporters via electronic communication media. The input is the report data, and the output is the notifications sent via email, social media, etc.

[0656] (Application Example 2)

[0657] 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."

[0658] Traditional crowdfunding systems and e-commerce sites face challenges such as communication barriers due to language and cultural differences, and a lack of optimal information provision tailored to user emotions. Furthermore, the absence of real-time means to address user anxieties and doubts can create significant psychological barriers for supporters and buyers. Conventional systems struggle to improve user experience and accurately reflect market needs. This invention solves these problems, enabling the creation of effective funding pages and product pages with a global market context.

[0659] 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.

[0660] This invention includes a server that provides means for receiving project information, translating it into multiple languages, and generating a crowdfunding page; means for automatically submitting applications to crowdfunding platforms in other countries; means for generating promotional materials based on progress information and transmitting them to multiple communication media; and means for analyzing the user's emotional state and adjusting the presentation of information according to that emotion. This enables the provision of optimal information to users across language and cultural barriers, and by customizing information according to their emotions, the user experience is improved, and the success rate of projects in the global market increases.

[0661] "Project information" refers to data that includes detailed descriptions, images, videos, and target amounts for projects and products that users register as targets for funding or online sales.

[0662] "Multiple languages" refers to the diversity of languages ​​in different countries and regions, and is primarily a medium for transmitting information through translation.

[0663] A "funding page" is an online information page published to solicit support for a project, and it includes details about the project, the target amount, and the progress status.

[0664] "Means for automatically executing applications" refers to methods or devices for automating necessary procedures and information input within crowdfunding platforms and related systems.

[0665] "Public relations materials" refer to informational content such as text, images, and videos created to promote a project or inform the public about its progress.

[0666] "Communication media" refers to channels and platforms for the exchange of information, including the internet, email, and social media.

[0667] "User emotional state" refers to the psychological reactions and feelings that users exhibit when they encounter information about a project, and can be inferred through text analysis and other methods.

[0668] "Means for adjusting the presentation of information" refers to methods or devices for changing the display format or order of information based on the user's emotional state.

[0669] This invention describes a system in which a user inputs project information using their own device, and a server then uses this information to perform automated multilingual translation and provide emotionally responsive information. The information input by the user includes the project name, details, target amount, images, and videos. This information is transmitted from the device to the server.

[0670] Upon receiving the input project information, the server uses natural language processing technology to translate it into multiple languages. Specifically, it processes not only text information but also media content using image recognition technology, including translation and cultural adaptation. The translated information is then incorporated into the funding page.

[0671] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state and adjusts how information is presented based on that data. For example, if the server detects that the user is feeling anxious, the page content is customized to emphasize elements that provide a sense of security. This customization feature removes psychological barriers for the user, providing a more user-friendly project experience.

[0672] The server also automates applications to crowdfunding platforms. It supports platform APIs and web interfaces in various countries, streamlining the process by automatically entering necessary information. Progress information is regularly updated and generated as promotional materials. These materials are delivered to backers and buyers through multiple communication channels. These materials may include content created by generative AI models.

[0673] For example, if a user says, "I'm not sure if I really need this product," the AI ​​model will use that prompt to generate a response that alleviates their anxiety. An example of a prompt might be, "Create a program that adjusts product information based on the user's emotions. If the user expresses anxiety, highlight the warranty information."

[0674] The main hardware used includes servers and user terminals, while the software includes EmotionEngine for sentiment analysis and APIs for processing text and images.

[0675] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0676] Step 1:

[0677] The user uses a terminal to enter project information.

[0678] The input includes the project name, details, target amount, images, and videos.

[0679] The terminal processes the input information, standardizes the data format, and sends it to the server.

[0680] Step 2:

[0681] The server analyzes the received project information and uses natural language processing technology to translate it into multiple languages.

[0682] This translation process takes text data as input and uses a multilingual translation API to obtain the output.

[0683] The output will provide a set of project information for each language.

[0684] Step 3:

[0685] The server automatically generates the funding page using the translated information.

[0686] We utilize image recognition technology to adapt images and video content to different cultures.

[0687] The generated pages are saved to a database and made available for distribution to various countries.

[0688] Step 4:

[0689] The server uses an emotion engine to analyze the user's emotional state based on their input.

[0690] The input includes text data and interaction logs.

[0691] An emotion analysis algorithm is applied to obtain the user's emotional state as output.

[0692] Step 5:

[0693] The server adjusts the information displayed on the funding page based on the user's emotional state.

[0694] If a specific emotion (e.g., anxiety) is detected, the content will be emphasized in accordance with that emotion.

[0695] Customize page design and information emphasis to generate optimized output.

[0696] Step 6:

[0697] The server automatically submits applications to crowdfunding platforms.

[0698] Enter the required information into the API of the target platform and complete the application.

[0699] The output will be confirmation of application completion or response data.

[0700] Step 7:

[0701] Based on project progress information, the server generates promotional materials.

[0702] We use AI models to analyze progress data and create optimal documents.

[0703] Send the created promotional materials to communication channels such as social media and email, and obtain feedback on their output.

[0704] Step 8:

[0705] The server stores feedback information received from users and supporters and uses it for future public relations activities.

[0706] The input includes comments and reviews.

[0707] We conduct emotional analysis to identify areas for improvement and factors for success, and then formulate an improvement plan as the output.

[0708] 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.

[0709] 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.

[0710] 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.

[0711] [Fourth Embodiment]

[0712] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0713] 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.

[0714] 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).

[0715] 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.

[0716] 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.

[0717] 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).

[0718] 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.

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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".

[0725] This invention relates to a system in which users input project information via a terminal, which is then processed by a server in multiple languages ​​for each country, and a crowdfunding campaign page is generated. This system has multiple functions and supports the international expansion of projects.

[0726] First, the user enters necessary information such as the project title, description, target amount, images, and videos using their own device. This input information is sent from the user's device to the server. Based on the received information, the server executes a program to perform multilingual translation. Natural language processing (NLP) technology is used for translation, and image recognition technology can also be used to translate text information contained within images and videos.

[0727] After the translation is complete, the server incorporates the translation results into templates tailored to each language, generating appropriate funding pages for each. For example, it might translate a Japanese project description into English and French, and then apply a page design that is appropriate for the culture and customs of each language.

[0728] Next, the server executes the application process on behalf of the user. It accesses the APIs or web pages of crowdfunding platforms in each country and automatically fills in the required application fields. If legal documents or platform-specific information are required, the server may translate them and present them to the user, requesting any necessary action.

[0729] In addition, project progress information is continuously collected, and drafts for social media posts and newsletters are generated as promotional materials. These promotional materials are created in multiple languages ​​by the server and delivered according to user-defined timings. The server analyzes the feedback received after delivery and incorporates the results into future content generation to ensure more effective information dissemination.

[0730] For example, when a Japanese startup company attempts to crowdfund a new product overseas, this system allows them to quickly and easily create pages for supporters in English-speaking and French-speaking regions, enabling effective promotion. In this way, the present invention removes language and cultural barriers, supporting easy entry into the global market.

[0731] The following describes the processing flow.

[0732] Step 1:

[0733] The user enters project information (title, description, target amount, images, videos, etc.) via their device and sends it to the server.

[0734] Step 2:

[0735] The server analyzes the received project information and identifies the languages ​​corresponding to each country. Natural language processing (NLP) is used to prepare the text for translation into the target language.

[0736] Step 3:

[0737] The server extracts text information from images and videos using image recognition technology and translates it as well. It understands the content and generates translations appropriate to the cultural context.

[0738] Step 4:

[0739] The server incorporates translated content in each language into templates and generates fundraising pages adapted for each country. The design and layout are also adjusted to suit each region.

[0740] Step 5:

[0741] The server initiates the application process in each country via the crowdfunding platform's API or webpage. It automatically fills in the necessary forms and submits the information, taking legal requirements into consideration.

[0742] Step 6:

[0743] The server periodically checks the project's progress and generates promotional materials (SNS posts, newsletters, etc.) in various languages.

[0744] Step 7:

[0745] The server distributes public relations materials to various communication channels at the scheduled time. After distribution, feedback and engagement data are collected and used to improve future public relations activities.

[0746] Step 8:

[0747] Users monitor server results via their terminals and modify or add project information as needed. The server receives these updates and reprocesses the data.

[0748] (Example 1)

[0749] 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".

[0750] In today's global market environment, it is essential to widely publicize projects in multiple languages ​​and efficiently submit applications to crowdfunding platforms in each region. However, traditional methods have faced difficulties in multilingualizing project information and conducting appropriate marketing in each region due to language barriers and cultural differences. To address this challenge, there is a need to establish effective public relations methods based on project progress information.

[0751] 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.

[0752] This invention includes a server that receives project information from a user, translates the information into multiple different languages ​​using natural language processing technology to generate publicly available documents, automatically constructs recruitment pages using templates corresponding to each language based on the translated information, and automatically performs the application process to regional fundraising platforms. This enables smooth international expansion of the project and allows for effective public relations and marketing activities.

[0753] "Receiving project information from the user" refers to the server retrieving detailed project data entered by the user via their device.

[0754] "Natural language processing technology" refers to the technology that allows computers to understand, analyze, and generate natural human language, and is used for translation and text analysis.

[0755] "Translating into multiple different languages" refers to accurately and culturally appropriate rephrasing from the original language into two or more other languages.

[0756] "Generating publicly available materials" refers to creating informational content based on collected information and data, to be provided to relevant markets and target customers.

[0757] "Automatically building fundraising pages using templates" refers to generating web pages for fundraising and donations without manual intervention, by using pre-defined templates with standardized structures and designs.

[0758] "Automating the application process to regional fundraising platforms" means that the server automatically submits the necessary information and handles the application process for crowdfunding and other fundraising systems that differ from region to region.

[0759] "Collecting progress data" refers to gathering and managing information about the progress of a project during its execution.

[0760] "Generating and sending promotional materials via multiple communication channels" refers to creating content for advertising and information dissemination and distributing it through various communication channels such as email and social media.

[0761] "Analyzing the feedback received after transmission and reflecting the analysis results in the creation of future materials" means analyzing the feedback received on the distributed information and using that insight to improve the effectiveness of future information content.

[0762] This invention is a system that enables users to efficiently and effectively expand their projects internationally. It begins with the user inputting project information via a terminal and sending it to a server. Project information includes title, description, target amount, images, videos, and more.

[0763] The server uses natural language processing technology to perform multilingual translation based on the received information. A generative AI model is used for translation, translating from Japanese to English, French, and other languages. Furthermore, image recognition technology is utilized to detect text within visual content and convert it to the required language. This ensures the creation of accurate and culturally appropriate project documents.

[0764] Next, the server automatically constructs the recruitment page using templates corresponding to each language based on the translated information. In this process, a design and layout that is appropriate for the culture and customs of each country is applied, resulting in a more user-friendly page.

[0765] The server also automatically submits applications to local crowdfunding platforms. If specific legal documents or information are required, it can provide users with translated materials and request their cooperation. This reduces manual work for users and allows them to complete project applications quickly in each country.

[0766] Once a project begins, the server automatically collects progress information and generates promotional materials. Here too, AI modeling technology is utilized to create social media posts and newsletters in multiple languages. These materials are distributed to multiple communication channels at user-defined timings. Feedback received after distribution is analyzed and incorporated into future promotional activities.

[0767] For example, when a Japanese startup seeks to raise international funds for a new product, this system can be used to quickly create campaign pages for English-speaking and French-speaking supporters and effectively promote the product. An example of a prompt would be: "Translate the project description written in Japanese into English and French, and create crowdfunding pages that reflect the cultural and design differences of each language."

[0768] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0769] Step 1:

[0770] The user uses a terminal to enter information about the project. This data includes title, description, target amount, images, and videos. The user's input actions send this data from the terminal to the server. As output, the terminal provides the server with a set of the input data.

[0771] Step 2:

[0772] The server analyzes project information received from the user. First, it extracts text data and translates it into multiple different languages ​​using natural language processing (NLP) techniques. Generative AI models are utilized in this process. The input is the received project information, and the output is the translated text data.

[0773] Step 3:

[0774] The server uses image recognition technology to identify text within images and videos. It analyzes image and video data as input, extracts text information, and then translates this extracted text into various languages, adding it to previously translated text. The output is an updated multilingual text set.

[0775] Step 4:

[0776] The server automatically generates crowdfunding campaign pages by selecting a template corresponding to each language based on the translated information. Here, template selection and construction are automated, and a design appropriate to cultural conventions is applied. The input is translated data, and the output is a completed multilingual web page.

[0777] Step 5:

[0778] The server submits applications to various crowdfunding platforms on behalf of the user. It automatically enters the necessary information using APIs and web interfaces, and proceeds with the application process. Inputs include data from the fundraising page and platform requirements, and output is application completion status information.

[0779] Step 6:

[0780] As the project progresses, the server continuously collects progress data and generates promotional materials. These materials are then organized into drafts for social media posts and newsletters. The input is collected progress data, and the output is multilingual promotional materials.

[0781] Step 7:

[0782] The server distributes public relations materials to multiple communication channels at scheduled times. It analyzes the feedback received after distribution and uses it to improve future content creation. The input is the public relations materials, and the output is the feedback received and its analysis results.

[0783] (Application Example 1)

[0784] 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".

[0785] In recent years, the e-commerce market has become increasingly globalized, requiring sales strategies that are tailored to the cultures and languages ​​of each country. In particular, in international markets, it is necessary to effectively appeal to multinational consumers with product ideas and to quickly generate sales and funding. However, achieving this using traditional methods requires considerable effort and cost, and continuously conducting optimal public relations activities in line with market trends presents significant challenges.

[0786] 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.

[0787] This invention includes a server that provides means for receiving project information, converting it into multiple languages, and generating an e-commerce solicitation page; means for automatically submitting applications to fundraising platforms in target countries; means for generating information dissemination materials based on progress information and transmitting them to multiple communication media; means for acquiring product ideas entered by users, transmitting this information to the cloud for translation; and means for automatically generating product pages optimized for the culture of each country based on the translation results, making them available for sale. This makes it possible to sell products and raise funds quickly and efficiently in the international market.

[0788] "Project information" refers to detailed information about products or services offered by users, such as the title, description, target amount, images, and videos.

[0789] An "e-commerce recruitment page" refers to an online page generated using translated multilingual information, intended for the sale of goods or fundraising.

[0790] A "fundraising platform" refers to an online service that showcases multiple projects or products and solicits support or purchases from consumers.

[0791] "Progress information" refers to data that shows the status of a project or product sales, including deadlines and target achievement rates.

[0792] "Information dissemination materials" refer to documents and digital content used to introduce products or projects to the market or consumers.

[0793] "Communication medium" refers to a means used to transmit information, including email, social media, and newsletters.

[0794] A "product idea" refers to a concept or plan for a new product or service devised by a user.

[0795] "Translation" refers to the process of converting information written in one language into another language.

[0796] "Cloud" refers to a service that provides resources on the internet for storing and processing data.

[0797] A "culture-optimized page" refers to a webpage whose design and content have been adjusted to take into account the culture and customs of the target country or region.

[0798] The system for realizing this invention consists of multiple computer programs. These programs operate by combining a user-owned terminal, server infrastructure, and cloud computing services.

[0799] First, users enter project information using a device such as a smartphone or tablet. This project information includes the title, description, target amount, images, and videos of the product or service. The entered information is then transmitted to the server via the network.

[0800] The server uses natural language processing technology to perform multilingual translation based on the received project information. The translation process utilizes Google Translate API and Azure Cognitive Services. Furthermore, it can translate text information within images and videos using image recognition technology.

[0801] After multilingual translation is complete, the server generates e-commerce recruitment pages with designs tailored to the culture and customs of each country. This process uses a template engine, and page generation is performed in a Node.js environment.

[0802] Next, the server automatically submits applications to fundraising platforms in each country. Here, the application process is efficiently executed by utilizing the APIs of each platform. Once the application is complete, the system sends a notification to the user.

[0803] Sales progress information for products and services is updated regularly, and the server generates informational materials based on this information. These materials are sent via social media and email newsletters, disseminating information to the market through virtual communication channels. This information dissemination activity is managed using Amazon S3 and Amazon DynamoDB.

[0804] As a concrete example, if a user utilizes a system to sell a new eco-bag design to the international market, they first enter the eco-bag's details into a terminal, which is then automatically translated into multiple languages ​​online and posted on sales websites in each country. This makes it easy to gain support and purchases from consumers around the world.

[0805] An example of a prompt message is: "Register an international sales project for a new eco-bag design and generate a multilingual translation page. Then, automatically submit applications to crowdfunding platforms in each country and create promotional materials for social media."

[0806] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0807] Step 1:

[0808] The user enters project information using a terminal. This information includes the product name, description, target amount, images, and videos, which are then sent from the terminal to the server. At this stage, the user's input data is ready to be transferred to the server.

[0809] Step 2:

[0810] The server analyzes project information received from the terminal. The analysis extracts text information and uses image recognition technology to recognize text information contained in images and videos. The input is raw user data, and the output is translatable text data.

[0811] Step 3:

[0812] The server uses natural language processing technology to translate the analyzed text information into multiple languages. This process utilizes the Google Translate API and Azure Cognitive Services, generating text data in each language as output.

[0813] Step 4:

[0814] The server generates e-commerce recruitment pages optimized for each country's culture based on the translation results. This process utilizes a template engine, automatically incorporating designs and layouts suitable for multinational markets. The input is translated text data, and the output is recruitment pages for each country.

[0815] Step 5:

[0816] The server automatically submits applications to various fundraising platforms in different countries based on the generated e-commerce fundraising pages. Information is entered via API, and the application status is returned. The input is the content of the fundraising page, and the output is the application completion status.

[0817] Step 6:

[0818] The server collects progress information and generates informational materials based on it. These materials are sent to the communication medium specified by the user, such as social media or a newsletter. The input is progress information, and the output is informational materials.

[0819] Step 7:

[0820] Users receive informational materials generated by the server and disseminate them to the market using social media and email. Users then review this information and create prompt messages tailored to local culture and trends.

[0821] 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.

[0822] This invention is a system that translates project information into multiple languages ​​to generate funding pages for each country, and further incorporates an emotion engine to provide optimal information tailored to the user's emotions. This system is realized when the user inputs project information using a terminal, and the server processes that information.

[0823] First, the user inputs project details from their device. This information includes the project title, detailed description, target amount, images, and videos. The device organizes this information and sends it to the server. The server analyzes the received information and translates the project information into the languages ​​of the target countries. This translation uses natural language processing and image recognition technologies to ensure that the text and media are appropriately expressed according to the culture and business practices of each country.

[0824] Next, the server uses an emotion engine to analyze user input and interactions, and evaluates the user's emotional state. This emotion recognition is reflected in how project information is presented and the page design, customizing it according to the user's emotional response. For example, when a specific emotional state is recognized, the priority of information and emphasis points are adjusted. This adjustment makes it possible for users to experience the project in a more engaging way.

[0825] Furthermore, the server also has the capability to automatically execute applications on crowdfunding platforms. This is achieved by utilizing the APIs or web pages of each country's platform and automatically filling in the necessary information. If legal requirements or additional information are requested, it will be translated and appropriate instructions will be provided to the user.

[0826] During project execution, the server periodically utilizes an emotion engine to analyze project progress and prepare and generate promotional materials. These materials are distributed at appropriate times via social media, email, etc., and feedback from users and supporters is accumulated on the server. This feedback is then used to improve content for future promotional activities.

[0827] For example, if the emotion engine detects that a particular project is causing anxiety among supporters, the server can adjust the page content to emphasize reassuring information and highlight positive aspects. This makes it possible to create an environment where potential supporters can participate in the project with peace of mind.

[0828] In this way, this system provides a comprehensive solution for smoothly advancing projects across language and cultural barriers, and strongly supports users aiming for success in the global market.

[0829] The following describes the processing flow.

[0830] Step 1:

[0831] The user enters project information (e.g., title, description, target amount, images, videos) via their device and sends that information to the server.

[0832] Step 2:

[0833] The server analyzes the project information it receives. It identifies multiple target languages ​​and uses natural language processing techniques to translate the text information into those languages.

[0834] Step 3:

[0835] The server analyzes the image and video content included in the project using image recognition technology, extracts text information, translates it, and incorporates it as multilingual content.

[0836] Step 4:

[0837] The server uses an emotion engine to evaluate the user's emotional state. Emotion recognition is performed based on the user's input information and past interactions.

[0838] Step 5:

[0839] Based on the results of the emotion engine, the server adjusts the content and layout of the crowdfunding page to provide the most appropriate expression for each country's culture and emotions.

[0840] Step 6:

[0841] The server accesses the crowdfunding platform and automatically submits project applications via API or web page. It enters the necessary information and handles any legal requirements appropriately.

[0842] Step 7:

[0843] During the project, the server periodically collects progress information, performs another analysis using the sentiment engine, and generates optimized promotional materials.

[0844] Step 8:

[0845] The server distributes the publicity materials to various communication channels such as social media and email, as configured, and collects user feedback. This feedback is then used to improve future materials.

[0846] Step 9:

[0847] The system checks the information received from the user's terminal and updates or corrects project information. The server then receives this updated information and performs reprocessing.

[0848] (Example 2)

[0849] 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".

[0850] In the international expansion of a project, effective information dissemination that transcends language and cultural differences is required. Furthermore, rapid and automated responses to digital fundraising platforms in each country, as well as sentiment analysis to optimize appeals to supporters, are necessary. Addressing these challenges and achieving efficient and effective fundraising is highly desirable.

[0851] 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.

[0852] This invention includes a server that receives project information, converts it into multiple languages ​​using natural language processing technology to generate information pages, automatically submits an application to a digital fundraising platform in a target country using the translated information, and evaluates the user's emotional state to dynamically optimize the way project information is presented. This enables efficient and effective dissemination of project information across language and cultural barriers, and facilitates attractive appeals to potential supporters.

[0853] "Project information" refers to a collection of all data related to a project, including its title, details, target amount, images, videos, and more.

[0854] "Natural language processing technology" refers to technologies that use computers to understand, generate, and manipulate human language.

[0855] An "information page" is a web page or electronic document created to display the content and progress of a project.

[0856] A "digital fundraising platform" is a platform used to raise funds online.

[0857] "Emotional state" refers to information about the emotions a user expresses, and represents their psychological response to the project.

[0858] "Dynamic optimization" means automatically adjusting the content and design to suit the situation at any given time.

[0859] "Electronic communication media" refers to electronic means used to transmit information, such as email and social media.

[0860] Users input project information using their own devices. This information includes the project title, details, target amount, images, videos, etc. The user's device formats the entered information and sends it to the server. The HTTP / HTTPS protocol is used for this information transmission.

[0861] The server uses natural language processing (NLP) technology to analyze received project information and translate it into multiple languages, utilizing a natural language processing system. Specifically, it uses open-source NLP libraries and commercial services to convert text. Furthermore, the server applies image recognition technology to images and videos, adjusting these media to suit the culture of each country.

[0862] The translated information is generated as an information page and becomes data for the server to automatically submit applications to digital fundraising platforms. The server uses the APIs and automation tools of each platform to input the necessary information and manage the application process.

[0863] Furthermore, the server analyzes user interactions and input information using an emotion engine to evaluate the user's emotional state. Based on this evaluation, it dynamically optimizes the content and design of information pages to improve the user experience.

[0864] While the project is underway, the server monitors progress and automatically generates reports. This generation utilizes a template system and AI models. The generated reports are distributed to users and supporters via electronic communication media to gather additional feedback.

[0865] As a concrete example, a user might send a prompt to the server saying, "Please input project information, translate it, and create funding pages for each country. Also, analyze user sentiment and optimize the information." The system then processes and generates the content accordingly. However, for specific sentiment analysis and translation, a generative AI model is used to improve accuracy.

[0866] The program integrates advanced data processing technologies at each step to support daily operations, enabling the smooth operation of the entire system.

[0867] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0868] Step 1:

[0869] The user uses a terminal to enter project information. The information entered includes the project title, details, target amount, and image / video files in text format. The terminal formats the input data and converts it into JSON format, which can be sent to the server. The output is JSON data sent to the server.

[0870] Step 2:

[0871] The server receives project information from the terminal. The input is project data in JSON format, which the server parses and translates into multiple languages ​​using natural language processing techniques. Multiple translation algorithms and libraries may be utilized during this process. The output is text data translated into various languages.

[0872] Step 3:

[0873] The server analyzes image and video media data and uses image recognition technology to process the content to suit each culture. The input is image and video files, and the output is appropriately adjusted media data.

[0874] Step 4:

[0875] The server generates an information page based on the translated and adjusted data. This information page is a webpage with content customized for the target country. The output is HTML data properly formatted as a webpage.

[0876] Step 5:

[0877] The server uses the generated information page to prepare and execute applications to digital fundraising platforms. The input consists of the information page and translation data, and the server automatically sends the application data through each platform's API. The output is a success or failure status code.

[0878] Step 6:

[0879] The server collects user interaction data and uses an emotion engine to evaluate the user's emotional state. Inputs include user behavior history and clickstream data, and the server analyzes the emotional state and generates an emotion report as output.

[0880] Step 7:

[0881] The server dynamically optimizes how project information is presented based on collected emotional states and feedback. The input is an emotional report, and the output is a customized information page.

[0882] Step 8:

[0883] The server monitors project progress and generates reports. The input is project progress data, and the reports are generated by an AI model based on a template. The output is a distributable PDF or HTML document.

[0884] Step 9:

[0885] The server distributes the generated reports to users and supporters via electronic communication media. The input is the report data, and the output is the notifications sent via email, social media, etc.

[0886] (Application Example 2)

[0887] 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".

[0888] Traditional crowdfunding systems and e-commerce sites face challenges such as communication barriers due to language and cultural differences, and a lack of optimal information provision tailored to user emotions. Furthermore, the absence of real-time means to address user anxieties and doubts can create significant psychological barriers for supporters and buyers. Conventional systems struggle to improve user experience and accurately reflect market needs. This invention solves these problems, enabling the creation of effective funding pages and product pages with a global market context.

[0889] 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.

[0890] This invention includes a server that provides means for receiving project information, translating it into multiple languages, and generating a crowdfunding page; means for automatically submitting applications to crowdfunding platforms in other countries; means for generating promotional materials based on progress information and transmitting them to multiple communication media; and means for analyzing the user's emotional state and adjusting the presentation of information according to that emotion. This enables the provision of optimal information to users across language and cultural barriers, and by customizing information according to their emotions, the user experience is improved, and the success rate of projects in the global market increases.

[0891] "Project information" refers to data that includes detailed descriptions, images, videos, and target amounts for projects and products that users register as targets for funding or online sales.

[0892] "Multiple languages" refers to the diversity of languages ​​in different countries and regions, and is primarily a medium for transmitting information through translation.

[0893] A "funding page" is an online information page published to solicit support for a project, and it includes details about the project, the target amount, and the progress status.

[0894] "Means for automatically executing applications" refers to methods or devices for automating necessary procedures and information input within crowdfunding platforms and related systems.

[0895] "Public relations materials" refer to informational content such as text, images, and videos created to promote a project or inform the public about its progress.

[0896] "Communication media" refers to channels and platforms for the exchange of information, including the internet, email, and social media.

[0897] "User emotional state" refers to the psychological reactions and feelings that users exhibit when they encounter information about a project, and can be inferred through text analysis and other methods.

[0898] "Means for adjusting the presentation of information" refers to methods or devices for changing the display format or order of information based on the user's emotional state.

[0899] This invention describes a system in which a user inputs project information using their own device, and a server then uses this information to perform automated multilingual translation and provide emotionally responsive information. The information input by the user includes the project name, details, target amount, images, and videos. This information is transmitted from the device to the server.

[0900] Upon receiving the input project information, the server uses natural language processing technology to translate it into multiple languages. Specifically, it processes not only text information but also media content using image recognition technology, including translation and cultural adaptation. The translated information is then incorporated into the funding page.

[0901] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state and adjusts how information is presented based on that data. For example, if the server detects that the user is feeling anxious, the page content is customized to emphasize elements that provide a sense of security. This customization feature removes psychological barriers for the user, providing a more user-friendly project experience.

[0902] The server also automates applications to crowdfunding platforms. It supports platform APIs and web interfaces in various countries, streamlining the process by automatically entering necessary information. Progress information is regularly updated and generated as promotional materials. These materials are delivered to backers and buyers through multiple communication channels. These materials may include content created by generative AI models.

[0903] For example, if a user says, "I'm not sure if I really need this product," the AI ​​model will use that prompt to generate a response that alleviates their anxiety. An example of a prompt might be, "Create a program that adjusts product information based on the user's emotions. If the user expresses anxiety, highlight the warranty information."

[0904] The main hardware used includes servers and user terminals, while the software includes EmotionEngine for sentiment analysis and APIs for processing text and images.

[0905] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0906] Step 1:

[0907] The user uses a terminal to enter project information.

[0908] The input includes the project name, details, target amount, images, and videos.

[0909] The terminal processes the input information, standardizes the data format, and sends it to the server.

[0910] Step 2:

[0911] The server analyzes the received project information and uses natural language processing technology to translate it into multiple languages.

[0912] This translation process takes text data as input and uses a multilingual translation API to obtain the output.

[0913] The output will provide a set of project information for each language.

[0914] Step 3:

[0915] The server automatically generates the funding page using the translated information.

[0916] We utilize image recognition technology to adapt images and video content to different cultures.

[0917] The generated pages are saved to a database and made available for distribution to various countries.

[0918] Step 4:

[0919] The server uses an emotion engine to analyze the user's emotional state based on their input.

[0920] The input includes text data and interaction logs.

[0921] An emotion analysis algorithm is applied to obtain the user's emotional state as output.

[0922] Step 5:

[0923] The server adjusts the information displayed on the funding page based on the user's emotional state.

[0924] If a specific emotion (e.g., anxiety) is detected, the content will be emphasized in accordance with that emotion.

[0925] Customize page design and information emphasis to generate optimized output.

[0926] Step 6:

[0927] The server automatically submits applications to crowdfunding platforms.

[0928] Enter the required information into the API of the target platform and complete the application.

[0929] The output will be confirmation of application completion or response data.

[0930] Step 7:

[0931] Based on project progress information, the server generates promotional materials.

[0932] We use AI models to analyze progress data and create optimal documents.

[0933] Send the created promotional materials to communication channels such as social media and email, and obtain feedback on their output.

[0934] Step 8:

[0935] The server stores feedback information received from users and supporters and uses it for future public relations activities.

[0936] The input includes comments and reviews.

[0937] We conduct emotional analysis to identify areas for improvement and factors for success, and then formulate an improvement plan as the output.

[0938] 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.

[0939] 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.

[0940] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0941] 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.

[0942] 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. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, 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.

[0943] 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.

[0944] 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.

[0945] 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.

[0946] 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."

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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.

[0952] 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.

[0953] 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.

[0954] 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.

[0955] 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.

[0956] 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.

[0957] 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.

[0958] 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.

[0959] The following is further disclosed regarding the embodiments described above.

[0960] (Claim 1)

[0961] A means of receiving project information, converting it into multiple languages, and generating a funding page,

[0962] A means to automatically submit applications to the crowdfunding platform in the target country,

[0963] A means of generating public relations materials based on progress information and sending them to multiple communication media,

[0964] A system that includes this.

[0965] (Claim 2)

[0966] The system according to claim 1, which analyzes image and video content included in project information, translates them, and incorporates them.

[0967] (Claim 3)

[0968] The system according to claim 1, which analyzes social media and optimizes public relations materials according to market trends.

[0969] "Example 1"

[0970] (Claim 1)

[0971] A means of receiving project information from users, translating that information into multiple different languages ​​using natural language processing technology, and generating publicly available documents,

[0972] A method for automatically building recruitment pages using templates corresponding to each language based on translated information,

[0973] A means to automate the application process to funding platforms in each region,

[0974] A means for collecting progress data, generating public relations materials, and transmitting them via multiple communication channels,

[0975] A means to analyze the opinions received after submission and reflect the analysis results in the generation of the next document,

[0976] A system that includes this.

[0977] (Claim 2)

[0978] The system according to claim 1, which analyzes image and video data included in project information, translates and incorporates the information contained therein, and reflects it on the page.

[0979] (Claim 3)

[0980] The system according to claim 1, which adjusts the timing of transmission based on user settings and selects a communication means to maximize effectiveness.

[0981] "Application Example 1"

[0982] (Claim 1)

[0983] A means for receiving project information, converting it into multiple languages, and generating an e-commerce recruitment page,

[0984] A means of automatically submitting applications to the partner country's fundraising platform,

[0985] A means of generating information dissemination materials based on progress information and transmitting them to multiple communication media,

[0986] A method for obtaining product ideas entered by users, sending this information to the cloud for translation,

[0987] A method to automatically generate product pages optimized for each country's culture based on translation results, and make them available for sale.

[0988] A system that includes this.

[0989] (Claim 2)

[0990] The system according to claim 1, which analyzes image and video content included in project information, translates them, and incorporates them.

[0991] (Claim 3)

[0992] The system according to claim 1, which analyzes virtual communication media and optimizes information dissemination materials according to market trends.

[0993] "Example 2 of combining an emotion engine"

[0994] (Claim 1)

[0995] A means for receiving project information, converting it into multiple languages ​​using natural language processing technology, and generating an information page,

[0996] A means of automatically submitting applications to the target country's digital financing platform using translated information,

[0997] A means to evaluate the user's emotional state and dynamically optimize how project information is presented,

[0998] A means of automatically generating report materials based on progress information and distributing them via electronic communication media,

[0999] A system that includes this.

[1000] (Claim 2)

[1001] The system according to claim 1, which analyzes image information and video information contained in project information, and translates and incorporates them using natural language processing and image recognition technology.

[1002] (Claim 3)

[1003] The system according to claim 1, which analyzes electronic information exchange media and dynamically optimizes reporting materials according to market trends.

[1004] "Application example 2 when combining with an emotional engine"

[1005] (Claim 1)

[1006] A means of receiving project information, converting it into multiple languages, and generating a funding page,

[1007] A means to automatically submit applications to the crowdfunding platform in the target country,

[1008] A means of generating public relations materials based on progress information and sending them to multiple communication media,

[1009] A means of analyzing the user's emotional state and adjusting the presentation of information according to that emotion,

[1010] A system that includes this.

[1011] (Claim 2)

[1012] The system according to claim 1, which analyzes image and video content included in project information, translates and incorporates them, and customizes the information based on the user's emotional state.

[1013] (Claim 3)

[1014] The system according to claim 1, which analyzes social media, optimizes public relations materials according to market trends, and further adjusts public relations activities based on the emotional state of users. [Explanation of Symbols]

[1015] 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 means of receiving project information, converting it into multiple languages, and generating a funding page, A means to automatically submit applications to the crowdfunding platform in the target country, A means of generating public relations materials based on progress information and sending them to multiple communication media, A system that includes this.

2. The system according to claim 1, which analyzes image and video content included in project information, translates them, and incorporates them.

3. The system according to claim 1, which analyzes social media and optimizes public relations materials according to market trends.

Images