system

Abstract

We provide the system. [Solution] A means of automatically collecting digital data entered by users, The means for analyzing the collected digital data and extracting information based on text and images, A means including a generation engine that automatically generates a document based on the aforementioned analysis results, A means for electronically distributing the automatically generated document, 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 as a 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 activities of guardians such as PTAs and sports clubs, a lot of information sharing and document creation are required. However, these tasks are often done manually, which is a great burden on the guardians. Specifically, the problems are that a great deal of time and effort are spent on recruiting event participants, preparing activity reports, and creating regulations and notice documents that are essential annually.

Means for Solving the Problems

[0005] To address this challenge, the present invention provides a system that automatically collects digital data, analyzes it to extract necessary information, and automatically generates documents using a generation engine based on the analysis results. Furthermore, the generated documents are electronically distributable and include interfaces for review and manual adjustment, thereby enabling rapid and efficient information sharing and document creation.

[0006] "Digital data" refers to electronically encoded information that can be represented in multiple formats, such as text, images, and audio.

[0007] "Means of automatic collection" refers to methods or functions for continuously or periodically acquiring digital data without user intervention.

[0008] "Means of analysis" refers to methods or mechanisms for processing collected digital data and extracting meaningful information or features.

[0009] A "generative engine" is a component of a system that automatically constructs documents based on analysis results using specific algorithms and rules.

[0010] "Means of electronic distribution" refers to methods and systems for sending generated documents to other electronic devices via a network.

[0011] An "interface" is a screen or means through which a user interacts with a system, receiving information or giving instructions. [Brief explanation of the drawing]

[0012] [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]It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0013] 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.

[0014] [[ID=4५]]First, the language used in the following description will be explained.

[0015] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] 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.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F manages communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] The system of this invention consists of a user, a terminal, and a server. The system starts operating when the user sends digital data, such as text messages or images, via a messaging platform such as LINE.

[0034] User roles

[0035] Users join LINE groups using their smartphones or computers to indicate their intention to participate in events, report on their activities, share photos, and so on. This information becomes the basic input data for the system.

[0036] Terminal role

[0037] The terminal receives digital data sent by the user. The terminal temporarily stores this data and prepares it for transmission to the server. The terminal also displays generated documents sent from the server and notifies the user.

[0038] Server Role

[0039] The server is the core of this system and performs multiple processes. First, the server automatically collects digital data sent from terminals. Next, it analyzes the collected digital data, extracting text content and performing image analysis. This identifies event participation status, activity details, or other necessary information.

[0040] Subsequently, the server uses a generation engine based on the analysis results to automatically generate the necessary documents. This generation process ensures consistent document quality by using pre-configured formats and rules. The generated documents can be reviewed by the system administrator before distribution, and manual adjustments are possible if necessary.

[0041] The server then electronically distributes the generated documents, delivering them to relevant members in designated LINE groups or other platforms. This ensures that information is shared quickly and efficiently.

[0042] Specific example

[0043] For example, if a user posts match results and photos to LINE after a sports club game, the server collects and analyzes that information and automatically generates a match results report. The report includes the match score, a list of participants, and photos of notable plays. The generated report is electronically distributed to all involved parties and can be viewed on their devices.

[0044] In this way, the system of the present invention can streamline information sharing and document creation, and simplify overall operation, thereby reducing the burden on the user.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The server periodically checks for new messages and posts through the LINE group API and automatically collects digital data. This includes event participation confirmation messages and photo data.

[0048] Step 2:

[0049] The terminal receives digital data sent by the user and temporarily stores it locally. It then converts the data into a format that can be sent to the server.

[0050] Step 3:

[0051] The server receives digital data transmitted from the terminal and analyzes its content using natural language processing (NLP) and image analysis techniques. In particular, it extracts meaning from text messages and identifies scene content and related information from images.

[0052] Step 4:

[0053] The server passes the analysis results to the generation engine, which automatically generates the document according to pre-configured templates and rules. In this process, the necessary information is placed in the appropriate format in each section of the document.

[0054] Step 5:

[0055] The server presents the generated documents to the system administrator via a management interface for review. The administrator can review the documents and make adjustments as needed.

[0056] Step 6:

[0057] The server sends the finalized document electronically to the LINE group or a designated platform. Distribution is done in real time to all relevant users.

[0058] Step 7:

[0059] The terminal displays received documents and notifies the user. The user can then review the documents in detail on the terminal and share the information with other relevant parties as needed.

[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 information society, it is crucial to efficiently share information about various events and activities in which users participate and to quickly create necessary documents. However, traditional methods often involve manual processes for information collection, analysis, document generation, and distribution, which are time-consuming and laborious. Ensuring the consistency and accuracy of information also poses challenges. There is a need for a system that can solve these problems and improve the efficiency of information sharing.

[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] In this invention, the server includes means for automatically collecting information input via a communication device operated by a user, means for analyzing the collected information and extracting information based on characters and images, and means including a generation device for automatically generating documents based on the analysis results. This enables a series of processes from information collection to document generation and distribution to be carried out quickly and automatically, significantly improving the efficiency of information sharing.

[0065] A "communication device" is a device that has the function of receiving information input by a user and communicating with other system components via a network.

[0066] "Information" refers to digital data, including text data and image data entered by the user.

[0067] "Means of automatic collection" refers to means that have the function of autonomously collecting input information without requiring user intervention.

[0068] "Analysis" refers to the process of processing collected information to extract specific content or features.

[0069] "Means for extracting information based on text and images" refers to means for extracting necessary information from text data and visual data.

[0070] A "generator" is a device that has the function of constructing a document based on the analysis results.

[0071] An "information network" refers to communication infrastructure for transmitting digital data, and includes the internet and local networks.

[0072] An "output device" is a device that has a display or screen on which the user can ultimately view the document.

[0073] An "interface" is a means for a user to interact with a system, and in particular, it provides an environment for reviewing and editing documents.

[0074] A "participant list" is information that shows a list of users who participated in an event or activity.

[0075] The system based on this invention consists of a user, a terminal, and a server. This system starts operating upon information input from a communication device operated by the user.

[0076] Users transmit digital data using a communication platform via devices such as smartphones and computers. This data includes event participation information and images, and is used as basic input data for the system.

[0077] The terminal temporarily stores the received input information and transfers it to the server via the network. The terminal also plays a role in displaying the generated documents sent from the server.

[0078] The server functions as a central control component, automatically collecting digital data sent from communication devices. The server analyzes the collected data and extracts specific information based on text and images. This analysis utilizes natural language processing tools and image recognition algorithms. As a specific example, the Google® Cloud Vision API can be used for image analysis.

[0079] The server then sends the analysis results to a generating AI model, which generates a document according to a pre-configured format. The generated document is reviewed through an interface that allows for inspection and manual modification, and then distributed to the designated recipient via the information network.

[0080] As a concrete example, in a sports event, if a user posts match results and related photos to a dedicated group chat, the server automatically collects this information and generates a report that includes a summary of the match results. This report is generated in a format that includes a list of participants and photos of important events, and is distributed to all relevant parties. An example of a specific prompt message would be, "Please create a report using the following match information: match date, team names, score, and photos of notable plays."

[0081] This allows users to simplify the information sharing process and efficiently handle everything from document creation to distribution.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] Users access messaging platforms such as LINE using communication devices and send digital data. This data includes text messages and images. For example, score information for sporting events and photos of participants are sent. This information serves as foundational data for subsequent processing.

[0085] Step 2:

[0086] The terminal receives digital data sent from the user. The data received as input is temporarily stored in the terminal's local storage. Specifically, the terminal takes in the received data via the network communication module and stores it in a buffer. This process prepares the data for immediate transfer to the server.

[0087] Step 3:

[0088] The terminal sends the stored digital data to the server. This involves specific actions that use security protocols to securely transfer the input data to the server. As output, the data arrives at the server and is ready for processing on the server side.

[0089] Step 4:

[0090] The server receives and automatically collects digital data transmitted from the terminal. Upon receiving the input data, the server analyzes its contents. Specifically, it uses natural language processing tools to analyze text information and extract important content and event information. For image data, it uses image recognition algorithms to identify visual information. The output is the analyzed information, now ready for use by the generation engine.

[0091] Step 5:

[0092] The server automatically generates documents using an AI model based on the analysis results. Analyzed text and image information are provided as input. Based on prompts, the document is generated according to a pre-configured format. Specifically, important information is extracted and assembled according to a system-defined template. As a result, a highly polished document is produced as output.

[0093] Step 6:

[0094] The server uses the network to deliver the generated documents to users. The generated documents are sent via the information network to a designated LINE group or other platform. The specific operation includes a transmission process using a distribution protocol. As output, the documents are delivered to and viewable on devices accessible to the user.

[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 factory and other work environments, it is necessary to quickly and accurately communicate progress reports from each section and equipment maintenance results to managers. However, these reporting tasks are often done manually, which is time-consuming and labor-intensive, making efficient information sharing difficult.

[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] In this invention, the server includes means for automatically collecting digital data entered by a user, means for analyzing the collected digital data and extracting information based on characters and images, and means including a generation processing unit that automatically generates a document based on the analysis results. This enables the automatic compilation of work reports and equipment maintenance status within the factory, prompt notification to managers, and efficient information sharing.

[0100] A "user" is an individual or group that uses a system to input digital data.

[0101] "Digital data" refers to electronically recorded information, and is a general term for data that includes text and images.

[0102] "Automatic collection methods" refer to systems that capture digital data sent by users without human intervention.

[0103] "Means for analyzing and extracting information based on text and images" refers to processing technologies for understanding digital data and extracting important information.

[0104] "Means including a generation processing unit" refers to a mechanism that has the function of automatically creating a document based on the analyzed information.

[0105] "Means of electronic distribution" refers to the technology of delivering generated documents to recipients via digital communication.

[0106] The "means of immediately notifying administrators" refer to a function that facilitates the rapid exchange of information regarding generated documents.

[0107] A "display unit" refers to a device or software that allows users to visually confirm the content of a generated document.

[0108] "Information processing equipment" is a general term for electronic devices used to manipulate and manage digital data.

[0109] To realize this application, the server runs a program that automatically collects work reports and equipment maintenance progress information from within the factory. The collected digital data is analyzed on the server using a Python program. This analysis uses OpenCV to analyze image data and NLTK to analyze text data.

[0110] After analysis, the document is automatically created in the generation processing unit and documented using the Docx library. This document is distributed electronically and immediately notified to information processing devices used by administrators and relevant personnel using the LINE Notify API. The notified content can be visually confirmed on each user's device.

[0111] As a concrete example, if a part in the factory needs maintenance, a worker sends a photo of the part to the server via LINE. This information is automatically analyzed by the server, and a report is generated indicating whether the part needs to be replaced or maintained. This report is immediately notified to the manager, allowing for prompt and appropriate action to be taken.

[0112] An example of a prompt message for the generating AI model would be an instruction such as, "Please compile a report on the equipment maintenance status. Please highlight any critical failure points." This format can reduce the burden of manual reporting and significantly improve the efficiency of information sharing.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] Users send information about factory work status and equipment maintenance as LINE messages. Input is either text messages or image data on LINE. This is the first time that user-observed information is incorporated into the system in digital format.

[0116] Step 2:

[0117] The terminal forwards the received LINE message to the server. The input is the LINE message from the user, and the output is the transmission of digital data to the server. In this step, the data is subject to processing by the server.

[0118] Step 3:

[0119] The server parses the received messages. Here, Python is used, with NLTK for text analysis and OpenCV for image analysis. The input is LINE digital data transferred by the user, and the output is extracted text content and image information. The server generates analysis results based on this information.

[0120] Step 4:

[0121] The server automatically generates documents based on the analysis results. The Python Docx library is used for the generation process. The input is text and image information from the analysis results, and the output is a documented report. At this stage, prompt sentences are provided to the generation AI model to optimize the document content.

[0122] Step 5:

[0123] The server uses the LINE Notify API to notify administrators and relevant personnel of the generated report. The input is the generated report, and the output is a notification via LINE. The information generated in this step is distributed to users, prompting a quick response.

[0124] 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.

[0125] This invention relates to a system consisting of a user, a terminal, and a server, which, in particular, uses an emotion engine to perform emotion analysis on data input by the user. The results of this analysis are reflected in various processes in document generation and distribution.

[0126] User roles

[0127] Users send text messages and images using platforms such as LINE via their smartphones or computers. Emotional messages are also entered into the system during this process.

[0128] Terminal role

[0129] The device receives and temporarily stores the digital data sent by the user. The text data is then sent directly to the server for analysis by the emotion engine.

[0130] Server Role

[0131] 1. Data Collection and Analysis

[0132] The server receives digital data sent from the terminal and uses an emotion engine to perform sentiment analysis on the text data. This analysis identifies the emotions contained in the user's message, such as joy, sadness, or surprise.

[0133] 2. Document generation

[0134] The server automatically generates documents using a generation engine based on the collected and analyzed results. It can flexibly adjust the content and expression of the documents, taking into account the results of sentiment analysis. For example, if a user expresses dissatisfaction, it can use more polite language.

[0135] 3. Review and adjustment

[0136] The generated documents are presented to the administrator through an interface. The administrator can review the documents and make manual adjustments, taking into account the results of the sentiment analysis.

[0137] 4. Distribution

[0138] The finalized document will be distributed electronically from the server. All relevant parties will be notified via LINE or other designated platforms.

[0139] Specific example

[0140] Consider a scenario where a user submits event feedback via LINE. When the sentiment engine detects elements of dissatisfaction in the user's comment, the server analyzes the feedback and generates a document containing suggestions and acknowledgments. This document includes a response to the issues the user raised, along with an expression of gratitude. After review by the administrator, the document is distributed to all relevant parties, and the content is followed up on.

[0141] Thus, this invention enables advanced document generation through emotion analysis, improving the user experience. Furthermore, by immediately reflecting emotional feedback, it is expected to facilitate rapid problem solving and smoother communication among stakeholders.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] Users post text messages and images to groups using messaging platforms such as LINE. These messages may contain the user's emotions.

[0145] Step 2:

[0146] The terminal receives digital data sent by the user and prepares it for transmission to the server. It then transmits the digital data to the server via a secure channel.

[0147] Step 3:

[0148] The server automatically collects digital data transmitted from terminals and analyzes the text and image data. Natural language processing techniques are used to extract content and sentiment from the text data.

[0149] Step 4:

[0150] The server identifies the user's emotions from the text data extracted using an emotion engine. Depending on the user's message, emotions such as joy, sadness, and anger may be identified.

[0151] Step 5:

[0152] Based on the analyzed emotion data, the server activates a generation engine and automatically generates a document. During this process, it is possible to adjust the tone and content of the document according to the detected emotions.

[0153] Step 6:

[0154] The generated document is presented to the administrator via an interface by the server. The administrator can review the document and make manual adjustments as needed. Sentiment analysis results assist in the review process.

[0155] Step 7:

[0156] The server will deliver the final verified document. All relevant parties will be notified via electronic means, such as a LINE group or other platform.

[0157] Step 8:

[0158] The device displays the received document and notifies the user of its contents. The user can view this document and provide responses or feedback as needed.

[0159] This series of steps ensures that digital data, including user emotions, is effectively processed and shared through the system.

[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 recent years, with the proliferation of diverse communication platforms, messages sent by users are imbued with a wealth of emotions. If these emotional elements cannot be properly analyzed and reflected in responses, improving the user experience and quickly resolving problems becomes difficult. Furthermore, manually processing large volumes of messages is inefficient, and there is a need to provide appropriate feedback in a timely manner.

[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] In this invention, the server includes means for automatically collecting data entered by the user, means for analyzing the collected data using an emotion analysis engine and extracting emotion information, and means including a generation engine for automatically generating text based on the analysis results. This makes it possible to instantly analyze the user's emotions and generate and deliver an appropriate response.

[0165] A "user" is an individual or group that inputs data and uses the system.

[0166] "Data" refers to information such as messages and images entered by the user.

[0167] An "emotion analysis engine" is specialized software or hardware used to extract and analyze emotional information from input data.

[0168] A "generative engine" is a program or system that automatically generates text based on the results of sentiment analysis.

[0169] An "administrator" is a person or system whose role is to review the generated document and manually adjust its content as needed.

[0170] "Interface" refers to the means or screens that users or administrators use to interact with a system.

[0171] "Distribution" refers to electronically sending generated and edited documents to relevant parties.

[0172] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate text.

[0173] A "prompt" refers to the text that serves as instructions or guidelines input into a generative AI model.

[0174] This invention is a system comprising a user, a terminal, and a server. The user uses a smart device to send messages containing emotional elements via a digital platform. Examples include text messages and images sent through communication applications.

[0175] The device receives data sent by the user and stores it temporarily. The stored data is sent to a server and used for sentiment analysis. The device may use encryption technology to securely transmit the data.

[0176] The server receives data sent from the terminal and analyzes the text data using an emotion analysis engine. The analysis process utilizes natural language processing techniques to extract emotional information from the message's context and vocabulary. This analysis identifies emotions such as joy, sadness, and dissatisfaction contained in the user's message.

[0177] Based on the analysis results, the server uses a generation engine to automatically generate appropriate text. In this process, it uses a generation AI model to customize the document according to specific emotions. For example, if an emotion of dissatisfaction is detected, it will create a text that includes suggestions for improvement or expressions of gratitude, taking that emotion into account.

[0178] The generated text can be reviewed and manually edited by the administrator. After administrator approval, the final version of the text is finalized and distributed electronically from the server through the designated platform.

[0179] As a concrete example, consider a scenario where a user submits feedback about an event, and that feedback includes complaints. The server analyzes this feedback and generates a message expressing gratitude and proposing solutions to the user's points of dissatisfaction. This message is then quickly sent back to the user, contributing to increased satisfaction.

[0180] An example of a prompt message is: "User-sent message: Enter the user's message here. Analyze the user's sentiment and generate a polite response based on it." This is how you can instruct the generation AI model.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] Users send messages to the platform via digital devices. Input consists of digital data in text and image formats. The device receives this data and temporarily stores it.

[0184] Step 2:

[0185] The terminal transmits stored digital data to the server. The input is the user's message data. As output, the data is sent to the server and prepared for sentiment analysis. Encryption technology is used for data transmission to ensure security.

[0186] Step 3:

[0187] The server receives data sent from the terminal and uses an emotion analysis engine. The input is text message data. This engine uses natural language processing techniques to extract emotional information from the data. The output is numerical information representing the user's emotions.

[0188] Step 4:

[0189] The server automatically generates text using a generation engine based on the results of sentiment analysis. The input is quantified sentiment information. Using a generation AI model, it creates the most appropriate document according to the sentiment. The output at this step is text specifically tailored for user interaction.

[0190] Step 5:

[0191] The server presents the generated text to the administrator's interface. The administrator reviews the text and makes manual adjustments as needed. The input is pre-generated text. Once adjustments are complete, the final version is finalized as output.

[0192] Step 6:

[0193] The server distributes the final version of the document to relevant parties via a digital platform. The input is the document reviewed and edited by the administrator. The output is the message sent to the designated users and parties. The distribution process is completed, and the system operation ends.

[0194] (Application Example 2)

[0195] 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".

[0196] Modern virtual stores lack the ability to provide services that reflect user emotions in real time, and a uniform approach is insufficient to adequately enhance customer satisfaction. Therefore, personalized suggestions and feedback based on actual user emotions are needed, but this has been difficult to achieve with conventional systems.

[0197] 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.

[0198] In this invention, the server includes means for automatically collecting digital data entered by the user, means for analyzing the collected digital data using an emotion engine and extracting emotion-based information, and means including a generation engine that automatically generates documents based on the analysis results and adjusts the content to match the user's emotions. This enables personalized suggestions that take the user's emotions into consideration and smooth customer service.

[0199] "User-input digital data" refers to data such as text and images that users input using input devices such as smartphones and computers and send to the system.

[0200] An "emotion engine" is an analytical device or software that analyzes emotional components contained in digital data received from a user to identify emotions such as joy, sadness, and dissatisfaction.

[0201] A "generative engine" is a generation device or software that generates documents based on the results obtained from sentiment analysis and has the function of adjusting the content and expression to match the user's emotions.

[0202] "Electronic communication means" refers to means for transmitting or receiving information by electromagnetic means, enabling the transmission and reception of digital data via the internet, mobile networks, etc.

[0203] A "human interface" is an interface device or software used by humans to interact with a system and information, and it includes features that allow administrators to review and adjust emotionally-based suggestions and feedback.

[0204] "Means for displaying on electronic devices" refers to a method or device for presenting automatically generated documents on a user's computer, smartphone, or other display device.

[0205] "Data input means" refers to a means of receiving emotional feedback from a user, and is an input device or software that uses a keyboard, touchscreen, voice input, etc.

[0206] This invention is implemented by a system consisting of a user, a terminal, and a server. The system is built around an emotion engine and a generation engine.

[0207] System Overview

[0208] Users input digital data through devices such as smartphones and computers. This digital data includes information such as text messages and images. The data entered by the user is sent to a server using a platform such as LINE. The server receives the input and uses an emotion engine to perform sentiment analysis on this data. As a result of this analysis, a variety of emotions such as joy, sadness, surprise, and dissatisfaction are identified.

[0209] Based on the analyzed sentiment data, the server utilizes a generation engine to automatically generate documents tailored to the user's emotions. These documents may include, for example, polite wording that addresses user dissatisfaction, or purchase suggestions that respond to positive emotions.

[0210] The generated documents are refined in a personalized manner, taking into account the user's emotions. During this process, the documents are reviewed and adjusted by an administrator's human interface before the final document is delivered to the user's device via electronic communication.

[0211] Specific example

[0212] For example, if a user submits feedback about a new product and the server detects an emotion of "joy" in response, it will generate a document containing related product campaign information and a thank-you message, and quickly send it to the user.

[0213] Example of a prompt

[0214] "Analyze the sentiment of user messages and generate appropriate follow-up messages based on the results. For example, if a user expresses dissatisfaction, include an apology and a solution."

[0215] In this system, the server's primary role is to analyze user data and generate and distribute documents based on that analysis. A common API (e.g., the Python library Natural Language Toolkit) is used as the sentiment analysis engine. A widely known generative AI model (e.g., OpenAI®'s GPT series) is applied as the generation engine to appropriately adjust the documents.

[0216] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0217] Step 1:

[0218] The terminal transfers digital data (text and images) entered by the user to a server via a communication platform such as LINE. The input data includes user feedback and inquiries. The output here is the raw data sent to the server.

[0219] Step 2:

[0220] The server temporarily stores the digital data received from the terminal in storage and sends it to the emotion engine. The input is the received digital data, and the output is the data ready for emotion analysis.

[0221] Step 3:

[0222] The server uses an emotion engine to analyze the input data and identify the user's emotions. Based on the input digital data, the emotion engine uses natural language processing techniques to analyze the emotional components of the data. In this step, the user's emotional state (e.g., joy, dissatisfaction) is labeled.

[0223] Step 4:

[0224] The server automatically generates documents using a generative AI model based on the sentiment labels obtained in the previous step. The input is the sentiment labels and user requests, and the output is a sentiment-sensitive, customized document. Specifically, the model uses prompt sentences to form appropriate responses.

[0225] Step 5:

[0226] The server presents the generated document to the administrator's human interface for review and adjustment. The input is the document generated in the previous step, and the output is the final, adjusted document. The administrator then reviews the content and tone of the document and makes manual corrections as needed.

[0227] Step 6:

[0228] The server delivers the final version of the document to the user's terminal using electronic communication methods. The input is the finalized document, and the output is the message displayed on the user's screen. Specifically, it is shared with the user as an email or LINE message.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] [Second Embodiment]

[0233] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0234] 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.

[0235] 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).

[0236] 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.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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".

[0245] The system of this invention consists of a user, a terminal, and a server. The system starts operating when the user sends digital data, such as text messages or images, via a messaging platform such as LINE.

[0246] User roles

[0247] Users join LINE groups using their smartphones or computers to indicate their intention to participate in events, report on their activities, share photos, and so on. This information becomes the basic input data for the system.

[0248] Terminal role

[0249] The terminal receives digital data sent by the user. The terminal temporarily stores this data and prepares it for transmission to the server. The terminal also displays generated documents sent from the server and notifies the user.

[0250] Server Role

[0251] The server is the core of this system and performs multiple processes. First, the server automatically collects digital data sent from terminals. Next, it analyzes the collected digital data, extracting text content and performing image analysis. This identifies event participation status, activity details, or other necessary information.

[0252] Subsequently, the server uses a generation engine based on the analysis results to automatically generate the necessary documents. This generation process ensures consistent document quality by using pre-configured formats and rules. The generated documents can be reviewed by the system administrator before distribution, and manual adjustments are possible if necessary.

[0253] The server then electronically distributes the generated documents, delivering them to relevant members in designated LINE groups or other platforms. This ensures that information is shared quickly and efficiently.

[0254] Specific example

[0255] For example, if a user posts match results and photos to LINE after a sports club game, the server collects and analyzes that information and automatically generates a match results report. The report includes the match score, a list of participants, and photos of notable plays. The generated report is electronically distributed to all involved parties and can be viewed on their devices.

[0256] In this way, the system of the present invention can streamline information sharing and document creation, and simplify overall operation, thereby reducing the burden on the user.

[0257] The following describes the processing flow.

[0258] Step 1:

[0259] The server periodically checks for new messages and posts through the LINE group API and automatically collects digital data. This includes event participation confirmation messages and photo data.

[0260] Step 2:

[0261] The terminal receives digital data sent by the user and temporarily stores it locally. It then converts the data into a format that can be sent to the server.

[0262] Step 3:

[0263] The server receives digital data transmitted from the terminal and analyzes its content using natural language processing (NLP) and image analysis techniques. In particular, it extracts meaning from text messages and identifies scene content and related information from images.

[0264] Step 4:

[0265] The server passes the analysis results to the generation engine, which automatically generates the document according to pre-configured templates and rules. In this process, the necessary information is placed in the appropriate format in each section of the document.

[0266] Step 5:

[0267] The server presents the generated documents to the system administrator via a management interface for review. The administrator can review the documents and make adjustments as needed.

[0268] Step 6:

[0269] The server sends the finalized document electronically to the LINE group or a designated platform. Distribution is done in real time to all relevant users.

[0270] Step 7:

[0271] The terminal displays received documents and notifies the user. The user can then review the documents in detail on the terminal and share the information with other relevant parties as needed.

[0272] (Example 1)

[0273] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0274] In today's information society, it is crucial to efficiently share information about various events and activities in which users participate and to quickly create necessary documents. However, traditional methods often involve manual processes for information collection, analysis, document generation, and distribution, which are time-consuming and laborious. Ensuring the consistency and accuracy of information also poses challenges. There is a need for a system that can solve these problems and improve the efficiency of information sharing.

[0275] 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.

[0276] In this invention, the server includes means for automatically collecting information input via a communication device operated by a user, means for analyzing the collected information and extracting information based on characters and images, and means including a generation device for automatically generating documents based on the analysis results. This enables a series of processes from information collection to document generation and distribution to be carried out quickly and automatically, significantly improving the efficiency of information sharing.

[0277] A "communication device" is a device that receives information input by a user and has the function of communicating with other system components through a network.

[0278] "Information" refers to digital data including character data and image data input by a user.

[0279] The "means for automatically collecting" is a means having the function of autonomously collecting the input information without requiring a user operation.

[0280] "Analysis" refers to the process of processing the collected information to extract specific contents and features.

[0281] The "means for extracting information based on characters and images" is a means for extracting necessary information from text data and visual data.

[0282] A "generation device" is a device having the function of constructing a document based on the analysis result.

[0283] An "information network" refers to a communication infrastructure for transmitting digital data and includes the Internet and local networks.

[0284] An "output device" is a device having a display or screen through which a user can finally view a document.

[0285] An "interface" is a means for a user to interact with a system, and particularly provides an environment for reviewing and modifying a document.

[0286] A "participant list" refers to information indicating a list of users who participated in an event or activity.

[0287] The system based on this invention consists of a user, a terminal, and a server. This system starts operating upon information input from a communication device operated by the user.

[0288] Users transmit digital data using a communication platform via devices such as smartphones and computers. This data includes event participation information and images, and is used as basic input data for the system.

[0289] The terminal temporarily stores the received input information and transfers it to the server via the network. The terminal also plays a role in displaying the generated documents sent from the server.

[0290] The server functions as a central control component, automatically collecting digital data sent from communication devices. The server analyzes the collected data and extracts specific information based on text and images. This analysis utilizes natural language processing tools and image recognition algorithms. A specific example is the use of the Google Cloud Vision API for image analysis.

[0291] The server then sends the analysis results to a generating AI model, which generates a document according to a pre-configured format. The generated document is reviewed through an interface that allows for inspection and manual modification, and then distributed to the designated recipient via the information network.

[0292] As a concrete example, in a sports event, if a user posts match results and related photos to a dedicated group chat, the server automatically collects this information and generates a report that includes a summary of the match results. This report is generated in a format that includes a list of participants and photos of important events, and is distributed to all relevant parties. An example of a specific prompt message would be, "Please create a report using the following match information: match date, team names, score, and photos of notable plays."

[0293] This allows users to simplify the information sharing process and efficiently handle everything from document creation to distribution.

[0294] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0295] Step 1:

[0296] Users access messaging platforms such as LINE using communication devices and send digital data. This data includes text messages and images. For example, score information for sporting events and photos of participants are sent. This information serves as foundational data for subsequent processing.

[0297] Step 2:

[0298] The terminal receives digital data sent from the user. The data received as input is temporarily stored in the terminal's local storage. Specifically, the terminal takes in the received data via the network communication module and stores it in a buffer. This process prepares the data for immediate transfer to the server.

[0299] Step 3:

[0300] The terminal sends the stored digital data to the server. This involves specific actions that use security protocols to securely transfer the input data to the server. As output, the data arrives at the server and is ready for processing on the server side.

[0301] Step 4:

[0302] The server receives and automatically collects the digital data transmitted from the terminal. The server that has received the input data analyzes its content. Specifically, it uses natural language processing tools to analyze the text information and extracts important content and event information. For image data, it uses an image recognition algorithm to identify visual information. As an output, the preparation for the analyzed information to be used by the generation engine is completed.

[0303] Step 5:

[0304] Based on the analysis results, the server automatically generates a document using the generated AI model. The analyzed text and image information are provided as inputs. Based on the prompt, a document is generated according to a pre-set format. Specifically, important information is extracted and assembled along the template set in the system. As a result, a highly completed document is generated as an output.

[0305] Step 6:

[0306] The server uses the network to distribute the generated document to the user. The generated document is sent to a specified LINE group or other platforms via the information network. The specific operation includes a sending process using a distribution protocol. As an output, the document is distributed to the terminal accessible by the user and can be viewed.

[0307] (Application Example 1)

[0308] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0309] In a working environment such as a factory, it is necessary to quickly and accurately convey the progress reports of each section and the maintenance results of equipment to the administrator. However, these reporting tasks are often carried out manually, which takes time and effort, so there is a problem that efficient information sharing is difficult.

[0310] 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.

[0311] In this invention, the server includes means for automatically collecting digital data entered by a user, means for analyzing the collected digital data and extracting information based on characters and images, and means including a generation processing unit that automatically generates a document based on the analysis results. This enables the automatic compilation of work reports and equipment maintenance status within the factory, prompt notification to managers, and efficient information sharing.

[0312] A "user" is an individual or group that uses a system to input digital data.

[0313] "Digital data" refers to electronically recorded information, and is a general term for data that includes text and images.

[0314] "Automatic collection methods" refer to systems that capture digital data sent by users without human intervention.

[0315] "Means for analyzing and extracting information based on text and images" refers to processing technologies for understanding digital data and extracting important information.

[0316] "Means including a generation processing unit" refers to a mechanism that has the function of automatically creating a document based on the analyzed information.

[0317] "Means of electronic distribution" refers to the technology of delivering generated documents to recipients via digital communication.

[0318] The "means of immediately notifying administrators" refer to a function that facilitates the rapid exchange of information regarding generated documents.

[0319] A "display unit" refers to a device or software that allows users to visually confirm the content of a generated document.

[0320] "Information processing equipment" is a general term for electronic devices used to manipulate and manage digital data.

[0321] To realize this application, the server runs a program that automatically collects work reports and equipment maintenance progress information from within the factory. The collected digital data is analyzed on the server using a Python program. This analysis uses OpenCV to analyze image data and NLTK to analyze text data.

[0322] After analysis, the document is automatically created in the generation processing unit and documented using the Docx library. This document is distributed electronically and immediately notified to information processing devices used by administrators and relevant personnel using the LINE Notify API. The notified content can be visually confirmed on each user's device.

[0323] As a concrete example, if a part in the factory needs maintenance, a worker sends a photo of the part to the server via LINE. This information is automatically analyzed by the server, and a report is generated indicating whether the part needs to be replaced or maintained. This report is immediately notified to the manager, allowing for prompt and appropriate action to be taken.

[0324] An example of a prompt message for the generating AI model would be an instruction such as, "Please compile a report on the equipment maintenance status. Please highlight any critical failure points." This format can reduce the burden of manual reporting and significantly improve the efficiency of information sharing.

[0325] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0326] Step 1:

[0327] Users send information about factory work status and equipment maintenance as LINE messages. Input is either text messages or image data on LINE. This is the first time that user-observed information is incorporated into the system in digital format.

[0328] Step 2:

[0329] The terminal forwards the received LINE message to the server. The input is the LINE message from the user, and the output is the transmission of digital data to the server. In this step, the data is subject to processing by the server.

[0330] Step 3:

[0331] The server parses the received messages. Here, Python is used, with NLTK for text analysis and OpenCV for image analysis. The input is LINE digital data transferred by the user, and the output is extracted text content and image information. The server generates analysis results based on this information.

[0332] Step 4:

[0333] The server automatically generates documents based on the analysis results. The Python Docx library is used for the generation process. The input is text and image information from the analysis results, and the output is a documented report. At this stage, prompt sentences are provided to the generation AI model to optimize the document content.

[0334] Step 5:

[0335] The server uses the LINE Notify API to notify administrators and relevant personnel of the generated report. The input is the generated report, and the output is a notification via LINE. The information generated in this step is distributed to users, prompting a quick response.

[0336] 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.

[0337] This invention relates to a system consisting of a user, a terminal, and a server, which, in particular, uses an emotion engine to perform emotion analysis on data input by the user. The results of this analysis are reflected in various processes in document generation and distribution.

[0338] User roles

[0339] Users send text messages and images using platforms such as LINE via their smartphones or computers. Emotional messages are also entered into the system during this process.

[0340] Terminal role

[0341] The device receives and temporarily stores the digital data sent by the user. The text data is then sent directly to the server for analysis by the emotion engine.

[0342] Server Role

[0343] 1. Data Collection and Analysis

[0344] The server receives digital data sent from the terminal and uses an emotion engine to perform sentiment analysis on the text data. This analysis identifies the emotions contained in the user's message, such as joy, sadness, or surprise.

[0345] 2. Document generation

[0346] The server automatically generates documents using a generation engine based on the collected and analyzed results. It can flexibly adjust the content and expression of the documents, taking into account the results of sentiment analysis. For example, if a user expresses dissatisfaction, it can use more polite language.

[0347] 3. Review and adjustment

[0348] The generated documents are presented to the administrator through an interface. The administrator can review the documents and make manual adjustments, taking into account the results of the sentiment analysis.

[0349] 4. Distribution

[0350] The finalized document will be distributed electronically from the server. All relevant parties will be notified via LINE or other designated platforms.

[0351] Specific example

[0352] Consider a scenario where a user submits event feedback via LINE. When the sentiment engine detects elements of dissatisfaction in the user's comment, the server analyzes the feedback and generates a document containing suggestions and acknowledgments. This document includes a response to the issues the user raised, along with an expression of gratitude. After review by the administrator, the document is distributed to all relevant parties, and the content is followed up on.

[0353] Thus, this invention enables advanced document generation through emotion analysis, improving the user experience. Furthermore, by immediately reflecting emotional feedback, it is expected to facilitate rapid problem solving and smoother communication among stakeholders.

[0354] The following describes the processing flow.

[0355] Step 1:

[0356] Users post text messages and images to groups using messaging platforms such as LINE. These messages may contain the user's emotions.

[0357] Step 2:

[0358] The terminal receives digital data sent by the user and prepares it for transmission to the server. It then transmits the digital data to the server via a secure channel.

[0359] Step 3:

[0360] The server automatically collects digital data transmitted from terminals and analyzes the text and image data. Natural language processing techniques are used to extract content and sentiment from the text data.

[0361] Step 4:

[0362] The server identifies the user's emotions from the text data extracted using an emotion engine. Depending on the user's message, emotions such as joy, sadness, and anger may be identified.

[0363] Step 5:

[0364] Based on the analyzed emotion data, the server activates a generation engine and automatically generates a document. During this process, it is possible to adjust the tone and content of the document according to the detected emotions.

[0365] Step 6:

[0366] The generated document is presented to the administrator via an interface by the server. The administrator can review the document and make manual adjustments as needed. Sentiment analysis results assist in the review process.

[0367] Step 7:

[0368] The server will deliver the final verified document. All relevant parties will be notified via electronic means, such as a LINE group or other platform.

[0369] Step 8:

[0370] The device displays the received document and notifies the user of its contents. The user can view this document and provide responses or feedback as needed.

[0371] This series of steps ensures that digital data, including user emotions, is effectively processed and shared through the system.

[0372] (Example 2)

[0373] 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".

[0374] In recent years, with the proliferation of diverse communication platforms, messages sent by users are imbued with a wealth of emotions. If these emotional elements cannot be properly analyzed and reflected in responses, improving the user experience and quickly resolving problems becomes difficult. Furthermore, manually processing large volumes of messages is inefficient, and there is a need to provide appropriate feedback in a timely manner.

[0375] 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.

[0376] In this invention, the server includes means for automatically collecting data entered by the user, means for analyzing the collected data using an emotion analysis engine and extracting emotion information, and means including a generation engine for automatically generating text based on the analysis results. This makes it possible to instantly analyze the user's emotions and generate and deliver an appropriate response.

[0377] A "user" is an individual or group that inputs data and uses the system.

[0378] "Data" refers to information such as messages and images entered by the user.

[0379] An "emotion analysis engine" is specialized software or hardware used to extract and analyze emotional information from input data.

[0380] A "generative engine" is a program or system that automatically generates text based on the results of sentiment analysis.

[0381] An "administrator" is a person or system whose role is to review the generated document and manually adjust its content as needed.

[0382] "Interface" refers to the means or screens that users or administrators use to interact with a system.

[0383] "Distribution" refers to electronically sending generated and edited documents to relevant parties.

[0384] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate text.

[0385] A "prompt" refers to the text that serves as instructions or guidelines input into a generative AI model.

[0386] This invention is a system comprising a user, a terminal, and a server. The user uses a smart device to send messages containing emotional elements via a digital platform. Examples include text messages and images sent through communication applications.

[0387] The device receives data sent by the user and stores it temporarily. The stored data is sent to a server and used for sentiment analysis. The device may use encryption technology to securely transmit the data.

[0388] The server receives data sent from the terminal and analyzes the text data using an emotion analysis engine. The analysis process utilizes natural language processing techniques to extract emotional information from the message's context and vocabulary. This analysis identifies emotions such as joy, sadness, and dissatisfaction contained in the user's message.

[0389] Based on the analysis results, the server uses a generation engine to automatically generate appropriate text. In this process, it uses a generation AI model to customize the document according to specific emotions. For example, if an emotion of dissatisfaction is detected, it will create a text that includes suggestions for improvement or expressions of gratitude, taking that emotion into account.

[0390] The generated text can be reviewed and manually edited by the administrator. After administrator approval, the final version of the text is finalized and distributed electronically from the server through the designated platform.

[0391] As a concrete example, consider a scenario where a user submits feedback about an event, and that feedback includes complaints. The server analyzes this feedback and generates a message expressing gratitude and proposing solutions to the user's points of dissatisfaction. This message is then quickly sent back to the user, contributing to increased satisfaction.

[0392] An example of a prompt message is: "User-sent message: Enter the user's message here. Analyze the user's sentiment and generate a polite response based on it." This is how you can instruct the generation AI model.

[0393] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0394] Step 1:

[0395] Users send messages to the platform via digital devices. Input consists of digital data in text and image formats. The device receives this data and temporarily stores it.

[0396] Step 2:

[0397] The terminal transmits stored digital data to the server. The input is the user's message data. As output, the data is sent to the server and prepared for sentiment analysis. Encryption technology is used for data transmission to ensure security.

[0398] Step 3:

[0399] The server receives data sent from the terminal and uses an emotion analysis engine. The input is text message data. This engine uses natural language processing techniques to extract emotional information from the data. The output is numerical information representing the user's emotions.

[0400] Step 4:

[0401] The server automatically generates text using a generation engine based on the results of sentiment analysis. The input is quantified sentiment information. Using a generation AI model, it creates the most appropriate document according to the sentiment. The output at this step is text specifically tailored for user interaction.

[0402] Step 5:

[0403] The server presents the generated text to the administrator's interface. The administrator reviews the text and makes manual adjustments as needed. The input is pre-generated text. Once adjustments are complete, the final version is finalized as output.

[0404] Step 6:

[0405] The server distributes the final version of the document to relevant parties via a digital platform. The input is the document reviewed and edited by the administrator. The output is the message sent to the designated users and parties. The distribution process is completed, and the system operation ends.

[0406] (Application Example 2)

[0407] 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."

[0408] Modern virtual stores lack the ability to provide services that reflect user emotions in real time, and a uniform approach is insufficient to adequately enhance customer satisfaction. Therefore, personalized suggestions and feedback based on actual user emotions are needed, but this has been difficult to achieve with conventional systems.

[0409] 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.

[0410] In this invention, the server includes means for automatically collecting digital data entered by the user, means for analyzing the collected digital data using an emotion engine and extracting emotion-based information, and means including a generation engine that automatically generates documents based on the analysis results and adjusts the content to match the user's emotions. This enables personalized suggestions that take the user's emotions into consideration and smooth customer service.

[0411] "User-input digital data" refers to data such as text and images that users input using input devices such as smartphones and computers and send to the system.

[0412] An "emotion engine" is an analytical device or software that analyzes emotional components contained in digital data received from a user to identify emotions such as joy, sadness, and dissatisfaction.

[0413] A "generative engine" is a generation device or software that generates documents based on the results obtained from sentiment analysis and has the function of adjusting the content and expression to match the user's emotions.

[0414] "Electronic communication means" refers to means for transmitting or receiving information by electromagnetic means, enabling the transmission and reception of digital data via the internet, mobile networks, etc.

[0415] A "human interface" is an interface device or software used by humans to interact with a system and information, and it includes features that allow administrators to review and adjust emotionally-based suggestions and feedback.

[0416] "Means for displaying on electronic devices" refers to a method or device for presenting automatically generated documents on a user's computer, smartphone, or other display device.

[0417] "Data input means" refers to a means of receiving emotional feedback from a user, and is an input device or software that uses a keyboard, touchscreen, voice input, etc.

[0418] This invention is implemented by a system consisting of a user, a terminal, and a server. The system is built around an emotion engine and a generation engine.

[0419] System Overview

[0420] Users input digital data through devices such as smartphones and computers. This digital data includes information such as text messages and images. The data entered by the user is sent to a server using a platform such as LINE. The server receives the input and uses an emotion engine to perform sentiment analysis on this data. As a result of this analysis, a variety of emotions such as joy, sadness, surprise, and dissatisfaction are identified.

[0421] Based on the analyzed sentiment data, the server utilizes a generation engine to automatically generate documents tailored to the user's emotions. These documents may include, for example, polite wording that addresses user dissatisfaction, or purchase suggestions that respond to positive emotions.

[0422] The generated documents are refined in a personalized manner, taking into account the user's emotions. During this process, the documents are reviewed and adjusted by an administrator's human interface before the final document is delivered to the user's device via electronic communication.

[0423] Specific example

[0424] For example, if a user submits feedback about a new product and the server detects an emotion of "joy" in response, it will generate a document containing related product campaign information and a thank-you message, and quickly send it to the user.

[0425] Example of a prompt

[0426] "Analyze the sentiment of user messages and generate appropriate follow-up messages based on the results. For example, if a user expresses dissatisfaction, include an apology and a solution."

[0427] In this system, the server's primary role is to analyze user data and generate and distribute documents based on that analysis. A common API (e.g., the Python library Natural Language Toolkit) is used as the sentiment analysis engine. A widely known generative AI model (e.g., OpenAI's GPT series) is applied as the generation engine to appropriately adjust the documents.

[0428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0429] Step 1:

[0430] The terminal transfers digital data (text and images) entered by the user to a server via a communication platform such as LINE. The input data includes user feedback and inquiries. The output here is the raw data sent to the server.

[0431] Step 2:

[0432] The server temporarily stores the digital data received from the terminal in storage and sends it to the emotion engine. The input is the received digital data, and the output is the data ready for emotion analysis.

[0433] Step 3:

[0434] The server uses an emotion engine to analyze the input data and identify the user's emotions. Based on the input digital data, the emotion engine uses natural language processing techniques to analyze the emotional components of the data. In this step, the user's emotional state (e.g., joy, dissatisfaction) is labeled.

[0435] Step 4:

[0436] The server automatically generates documents using a generative AI model based on the sentiment labels obtained in the previous step. The input is the sentiment labels and user requests, and the output is a sentiment-sensitive, customized document. Specifically, the model uses prompt sentences to form appropriate responses.

[0437] Step 5:

[0438] The server presents the generated document to the administrator's human interface for review and adjustment. The input is the document generated in the previous step, and the output is the final, adjusted document. The administrator then reviews the content and tone of the document and makes manual corrections as needed.

[0439] Step 6:

[0440] The server delivers the final version of the document to the user's terminal using electronic communication methods. The input is the finalized document, and the output is the message displayed on the user's screen. Specifically, it is shared with the user as an email or LINE message.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] [Third Embodiment]

[0445] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0446] 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.

[0447] 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).

[0448] 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.

[0449] 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.

[0450] 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).

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] 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".

[0457] The system of this invention consists of a user, a terminal, and a server. The system starts operating when the user sends digital data, such as text messages or images, via a messaging platform such as LINE.

[0458] User roles

[0459] Users join LINE groups using their smartphones or computers to indicate their intention to participate in events, report on their activities, share photos, and so on. This information becomes the basic input data for the system.

[0460] Terminal role

[0461] The terminal receives digital data sent by the user. The terminal temporarily stores this data and prepares it for transmission to the server. The terminal also displays generated documents sent from the server and notifies the user.

[0462] Server Role

[0463] The server is the core of this system and performs multiple processes. First, the server automatically collects digital data sent from terminals. Next, it analyzes the collected digital data, extracting text content and performing image analysis. This identifies event participation status, activity details, or other necessary information.

[0464] Subsequently, the server uses a generation engine based on the analysis results to automatically generate the necessary documents. This generation process ensures consistent document quality by using pre-configured formats and rules. The generated documents can be reviewed by the system administrator before distribution, and manual adjustments are possible if necessary.

[0465] The server then electronically distributes the generated documents, delivering them to relevant members in designated LINE groups or other platforms. This ensures that information is shared quickly and efficiently.

[0466] Specific example

[0467] For example, if a user posts match results and photos to LINE after a sports club game, the server collects and analyzes that information and automatically generates a match results report. The report includes the match score, a list of participants, and photos of notable plays. The generated report is electronically distributed to all involved parties and can be viewed on their devices.

[0468] In this way, the system of the present invention can streamline information sharing and document creation, and simplify overall operation, thereby reducing the burden on the user.

[0469] The following describes the processing flow.

[0470] Step 1:

[0471] The server periodically checks for new messages and posts through the LINE group API and automatically collects digital data. This includes event participation confirmation messages and photo data.

[0472] Step 2:

[0473] The terminal receives digital data sent by the user and temporarily stores it locally. It then converts the data into a format that can be sent to the server.

[0474] Step 3:

[0475] The server receives digital data transmitted from the terminal and analyzes its content using natural language processing (NLP) and image analysis techniques. In particular, it extracts meaning from text messages and identifies scene content and related information from images.

[0476] Step 4:

[0477] The server passes the analysis results to the generation engine, which automatically generates the document according to pre-configured templates and rules. In this process, the necessary information is placed in the appropriate format in each section of the document.

[0478] Step 5:

[0479] The server presents the generated documents to the system administrator via a management interface for review. The administrator can review the documents and make adjustments as needed.

[0480] Step 6:

[0481] The server sends the finalized document electronically to the LINE group or a designated platform. Distribution is done in real time to all relevant users.

[0482] Step 7:

[0483] The terminal displays received documents and notifies the user. The user can then review the documents in detail on the terminal and share the information with other relevant parties as needed.

[0484] (Example 1)

[0485] 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."

[0486] In today's information society, it is crucial to efficiently share information about various events and activities in which users participate and to quickly create necessary documents. However, traditional methods often involve manual processes for information collection, analysis, document generation, and distribution, which are time-consuming and laborious. Ensuring the consistency and accuracy of information also poses challenges. There is a need for a system that can solve these problems and improve the efficiency of information sharing.

[0487] 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.

[0488] In this invention, the server includes means for automatically collecting information input via a communication device operated by a user, means for analyzing the collected information and extracting information based on characters and images, and means including a generation device for automatically generating documents based on the analysis results. This enables a series of processes from information collection to document generation and distribution to be carried out quickly and automatically, significantly improving the efficiency of information sharing.

[0489] A "communication device" is a device that has the function of receiving information input by a user and communicating with other system components via a network.

[0490] "Information" refers to digital data, including text data and image data entered by the user.

[0491] "Means of automatic collection" refers to means that have the function of autonomously collecting input information without requiring user intervention.

[0492] "Analysis" refers to the process of processing collected information to extract specific content or features.

[0493] "Means for extracting information based on text and images" refers to means for extracting necessary information from text data and visual data.

[0494] A "generator" is a device that has the function of constructing a document based on the analysis results.

[0495] An "information network" refers to communication infrastructure for transmitting digital data, and includes the internet and local networks.

[0496] An "output device" is a device that has a display or screen on which the user can ultimately view the document.

[0497] An "interface" is a means for a user to interact with a system, and in particular, it provides an environment for reviewing and editing documents.

[0498] A "participant list" is information that shows a list of users who participated in an event or activity.

[0499] The system based on this invention consists of a user, a terminal, and a server. This system starts operating upon information input from a communication device operated by the user.

[0500] Users transmit digital data using a communication platform via devices such as smartphones and computers. This data includes event participation information and images, and is used as basic input data for the system.

[0501] The terminal temporarily stores the received input information and transfers it to the server via the network. The terminal also plays a role in displaying the generated documents sent from the server.

[0502] The server functions as a central control component, automatically collecting digital data sent from communication devices. The server analyzes the collected data and extracts specific information based on text and images. This analysis utilizes natural language processing tools and image recognition algorithms. A specific example is the use of the Google Cloud Vision API for image analysis.

[0503] The server then sends the analysis results to a generating AI model, which generates a document according to a pre-configured format. The generated document is reviewed through an interface that allows for inspection and manual modification, and then distributed to the designated recipient via the information network.

[0504] As a concrete example, in a sports event, if a user posts match results and related photos to a dedicated group chat, the server automatically collects this information and generates a report that includes a summary of the match results. This report is generated in a format that includes a list of participants and photos of important events, and is distributed to all relevant parties. An example of a specific prompt message would be, "Please create a report using the following match information: match date, team names, score, and photos of notable plays."

[0505] This allows users to simplify the information sharing process and efficiently handle everything from document creation to distribution.

[0506] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0507] Step 1:

[0508] Users access messaging platforms such as LINE using communication devices and send digital data. This data includes text messages and images. For example, score information for sporting events and photos of participants are sent. This information serves as foundational data for subsequent processing.

[0509] Step 2:

[0510] The terminal receives digital data sent from the user. The data received as input is temporarily stored in the terminal's local storage. Specifically, the terminal takes in the received data via the network communication module and stores it in a buffer. This process prepares the data for immediate transfer to the server.

[0511] Step 3:

[0512] The terminal sends the stored digital data to the server. This involves specific actions that use security protocols to securely transfer the input data to the server. As output, the data arrives at the server and is ready for processing on the server side.

[0513] Step 4:

[0514] The server receives and automatically collects digital data transmitted from the terminal. Upon receiving the input data, the server analyzes its contents. Specifically, it uses natural language processing tools to analyze text information and extract important content and event information. For image data, it uses image recognition algorithms to identify visual information. The output is the analyzed information, now ready for use by the generation engine.

[0515] Step 5:

[0516] The server automatically generates documents using an AI model based on the analysis results. Analyzed text and image information are provided as input. Based on prompts, the document is generated according to a pre-configured format. Specifically, important information is extracted and assembled according to a system-defined template. As a result, a highly polished document is produced as output.

[0517] Step 6:

[0518] The server uses the network to deliver the generated documents to users. The generated documents are sent via the information network to a designated LINE group or other platform. The specific operation includes a transmission process using a distribution protocol. As output, the documents are delivered to and viewable on devices accessible to the user.

[0519] (Application Example 1)

[0520] 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."

[0521] In factory and other work environments, it is necessary to quickly and accurately communicate progress reports from each section and equipment maintenance results to managers. However, these reporting tasks are often done manually, which is time-consuming and labor-intensive, making efficient information sharing difficult.

[0522] 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.

[0523] In this invention, the server includes means for automatically collecting digital data entered by a user, means for analyzing the collected digital data and extracting information based on characters and images, and means including a generation processing unit that automatically generates a document based on the analysis results. This enables the automatic compilation of work reports and equipment maintenance status within the factory, prompt notification to managers, and efficient information sharing.

[0524] A "user" is an individual or group that uses a system to input digital data.

[0525] "Digital data" refers to electronically recorded information, and is a general term for data that includes text and images.

[0526] "Automatic collection methods" refer to systems that capture digital data sent by users without human intervention.

[0527] "Means for analyzing and extracting information based on text and images" refers to processing technologies for understanding digital data and extracting important information.

[0528] "Means including a generation processing unit" refers to a mechanism that has the function of automatically creating a document based on the analyzed information.

[0529] "Means of electronic distribution" refers to the technology of delivering generated documents to recipients via digital communication.

[0530] The "means of immediately notifying administrators" refer to a function that facilitates the rapid exchange of information regarding generated documents.

[0531] A "display unit" refers to a device or software that allows users to visually confirm the content of a generated document.

[0532] "Information processing equipment" is a general term for electronic devices used to manipulate and manage digital data.

[0533] To realize this application, the server runs a program that automatically collects work reports and equipment maintenance progress information from within the factory. The collected digital data is analyzed on the server using a Python program. This analysis uses OpenCV to analyze image data and NLTK to analyze text data.

[0534] After analysis, the document is automatically created in the generation processing unit and documented using the Docx library. This document is distributed electronically and immediately notified to information processing devices used by administrators and relevant personnel using the LINE Notify API. The notified content can be visually confirmed on each user's device.

[0535] As a concrete example, if a part in the factory needs maintenance, a worker sends a photo of the part to the server via LINE. This information is automatically analyzed by the server, and a report is generated indicating whether the part needs to be replaced or maintained. This report is immediately notified to the manager, allowing for prompt and appropriate action to be taken.

[0536] An example of a prompt message for the generating AI model would be an instruction such as, "Please compile a report on the equipment maintenance status. Please highlight any critical failure points." This format can reduce the burden of manual reporting and significantly improve the efficiency of information sharing.

[0537] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0538] Step 1:

[0539] Users send information about factory work status and equipment maintenance as LINE messages. Input is either text messages or image data on LINE. This is the first time that user-observed information is incorporated into the system in digital format.

[0540] Step 2:

[0541] The terminal forwards the received LINE message to the server. The input is the LINE message from the user, and the output is the transmission of digital data to the server. In this step, the data is subject to processing by the server.

[0542] Step 3:

[0543] The server parses the received messages. Here, Python is used, with NLTK for text analysis and OpenCV for image analysis. The input is LINE digital data transferred by the user, and the output is extracted text content and image information. The server generates analysis results based on this information.

[0544] Step 4:

[0545] The server automatically generates documents based on the analysis results. The Python Docx library is used for the generation process. The input is text and image information from the analysis results, and the output is a documented report. At this stage, prompt sentences are provided to the generation AI model to optimize the document content.

[0546] Step 5:

[0547] The server uses the LINE Notify API to notify administrators and relevant personnel of the generated report. The input is the generated report, and the output is a notification via LINE. The information generated in this step is distributed to users, prompting a quick response.

[0548] 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.

[0549] This invention relates to a system consisting of a user, a terminal, and a server, which, in particular, uses an emotion engine to perform emotion analysis on data input by the user. The results of this analysis are reflected in various processes in document generation and distribution.

[0550] User roles

[0551] Users send text messages and images using platforms such as LINE via their smartphones or computers. Emotional messages are also entered into the system during this process.

[0552] Terminal role

[0553] The device receives and temporarily stores the digital data sent by the user. The text data is then sent directly to the server for analysis by the emotion engine.

[0554] Server Role

[0555] 1. Data Collection and Analysis

[0556] The server receives digital data sent from the terminal and uses an emotion engine to perform sentiment analysis on the text data. This analysis identifies the emotions contained in the user's message, such as joy, sadness, or surprise.

[0557] 2. Document generation

[0558] The server automatically generates documents using a generation engine based on the collected and analyzed results. It can flexibly adjust the content and expression of the documents, taking into account the results of sentiment analysis. For example, if a user expresses dissatisfaction, it can use more polite language.

[0559] 3. Review and adjustment

[0560] The generated documents are presented to the administrator through an interface. The administrator can review the documents and make manual adjustments, taking into account the results of the sentiment analysis.

[0561] 4. Distribution

[0562] The finalized document will be distributed electronically from the server. All relevant parties will be notified via LINE or other designated platforms.

[0563] Specific example

[0564] Consider a scenario where a user submits event feedback via LINE. When the sentiment engine detects elements of dissatisfaction in the user's comment, the server analyzes the feedback and generates a document containing suggestions and acknowledgments. This document includes a response to the issues the user raised, along with an expression of gratitude. After review by the administrator, the document is distributed to all relevant parties, and the content is followed up on.

[0565] Thus, this invention enables advanced document generation through emotion analysis, improving the user experience. Furthermore, by immediately reflecting emotional feedback, it is expected to facilitate rapid problem solving and smoother communication among stakeholders.

[0566] The following describes the processing flow.

[0567] Step 1:

[0568] Users post text messages and images to groups using messaging platforms such as LINE. These messages may contain the user's emotions.

[0569] Step 2:

[0570] The terminal receives digital data sent by the user and prepares it for transmission to the server. It then transmits the digital data to the server via a secure channel.

[0571] Step 3:

[0572] The server automatically collects digital data transmitted from terminals and analyzes the text and image data. Natural language processing techniques are used to extract content and sentiment from the text data.

[0573] Step 4:

[0574] The server identifies the user's emotions from the text data extracted using an emotion engine. Depending on the user's message, emotions such as joy, sadness, and anger may be identified.

[0575] Step 5:

[0576] Based on the analyzed emotion data, the server activates a generation engine and automatically generates a document. During this process, it is possible to adjust the tone and content of the document according to the detected emotions.

[0577] Step 6:

[0578] The generated document is presented to the administrator via an interface by the server. The administrator can review the document and make manual adjustments as needed. Sentiment analysis results assist in the review process.

[0579] Step 7:

[0580] The server will deliver the final verified document. All relevant parties will be notified via electronic means, such as a LINE group or other platform.

[0581] Step 8:

[0582] The device displays the received document and notifies the user of its contents. The user can view this document and provide responses or feedback as needed.

[0583] This series of steps ensures that digital data, including user emotions, is effectively processed and shared through the system.

[0584] (Example 2)

[0585] 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."

[0586] In recent years, with the proliferation of diverse communication platforms, messages sent by users are imbued with a wealth of emotions. If these emotional elements cannot be properly analyzed and reflected in responses, improving the user experience and quickly resolving problems becomes difficult. Furthermore, manually processing large volumes of messages is inefficient, and there is a need to provide appropriate feedback in a timely manner.

[0587] 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.

[0588] In this invention, the server includes means for automatically collecting data entered by the user, means for analyzing the collected data using an emotion analysis engine and extracting emotion information, and means including a generation engine for automatically generating text based on the analysis results. This makes it possible to instantly analyze the user's emotions and generate and deliver an appropriate response.

[0589] A "user" is an individual or group that inputs data and uses the system.

[0590] "Data" refers to information such as messages and images entered by the user.

[0591] An "emotion analysis engine" is specialized software or hardware used to extract and analyze emotional information from input data.

[0592] A "generative engine" is a program or system that automatically generates text based on the results of sentiment analysis.

[0593] An "administrator" is a person or system whose role is to review the generated document and manually adjust its content as needed.

[0594] "Interface" refers to the means or screens that users or administrators use to interact with a system.

[0595] "Distribution" refers to electronically sending generated and edited documents to relevant parties.

[0596] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate text.

[0597] A "prompt" refers to the text that serves as instructions or guidelines input into a generative AI model.

[0598] This invention is a system comprising a user, a terminal, and a server. The user uses a smart device to send messages containing emotional elements via a digital platform. Examples include text messages and images sent through communication applications.

[0599] The device receives data sent by the user and stores it temporarily. The stored data is sent to a server and used for sentiment analysis. The device may use encryption technology to securely transmit the data.

[0600] The server receives data sent from the terminal and analyzes the text data using an emotion analysis engine. The analysis process utilizes natural language processing techniques to extract emotional information from the message's context and vocabulary. This analysis identifies emotions such as joy, sadness, and dissatisfaction contained in the user's message.

[0601] Based on the analysis results, the server uses a generation engine to automatically generate appropriate text. In this process, it uses a generation AI model to customize the document according to specific emotions. For example, if an emotion of dissatisfaction is detected, it will create a text that includes suggestions for improvement or expressions of gratitude, taking that emotion into account.

[0602] The generated text can be reviewed and manually edited by the administrator. After administrator approval, the final version of the text is finalized and distributed electronically from the server through the designated platform.

[0603] As a concrete example, consider a scenario where a user submits feedback about an event, and that feedback includes complaints. The server analyzes this feedback and generates a message expressing gratitude and proposing solutions to the user's points of dissatisfaction. This message is then quickly sent back to the user, contributing to increased satisfaction.

[0604] An example of a prompt message is: "User-sent message: Enter the user's message here. Analyze the user's sentiment and generate a polite response based on it." This is how you can instruct the generation AI model.

[0605] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0606] Step 1:

[0607] Users send messages to the platform via digital devices. Input consists of digital data in text and image formats. The device receives this data and temporarily stores it.

[0608] Step 2:

[0609] The terminal transmits stored digital data to the server. The input is the user's message data. As output, the data is sent to the server and prepared for sentiment analysis. Encryption technology is used for data transmission to ensure security.

[0610] Step 3:

[0611] The server receives data sent from the terminal and uses an emotion analysis engine. The input is text message data. This engine uses natural language processing techniques to extract emotional information from the data. The output is numerical information representing the user's emotions.

[0612] Step 4:

[0613] The server automatically generates text using a generation engine based on the results of sentiment analysis. The input is quantified sentiment information. Using a generation AI model, it creates the most appropriate document according to the sentiment. The output at this step is text specifically tailored for user interaction.

[0614] Step 5:

[0615] The server presents the generated text to the administrator's interface. The administrator reviews the text and makes manual adjustments as needed. The input is pre-generated text. Once adjustments are complete, the final version is finalized as output.

[0616] Step 6:

[0617] The server distributes the final version of the document to relevant parties via a digital platform. The input is the document reviewed and edited by the administrator. The output is the message sent to the designated users and parties. The distribution process is completed, and the system operation ends.

[0618] (Application Example 2)

[0619] 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."

[0620] Modern virtual stores lack the ability to provide services that reflect user emotions in real time, and a uniform approach is insufficient to adequately enhance customer satisfaction. Therefore, personalized suggestions and feedback based on actual user emotions are needed, but this has been difficult to achieve with conventional systems.

[0621] 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.

[0622] In this invention, the server includes means for automatically collecting digital data entered by the user, means for analyzing the collected digital data using an emotion engine and extracting emotion-based information, and means including a generation engine that automatically generates documents based on the analysis results and adjusts the content to match the user's emotions. This enables personalized suggestions that take the user's emotions into consideration and smooth customer service.

[0623] "User-input digital data" refers to data such as text and images that users input using input devices such as smartphones and computers and send to the system.

[0624] An "emotion engine" is an analytical device or software that analyzes emotional components contained in digital data received from a user to identify emotions such as joy, sadness, and dissatisfaction.

[0625] A "generative engine" is a generation device or software that generates documents based on the results obtained from sentiment analysis and has the function of adjusting the content and expression to match the user's emotions.

[0626] "Electronic communication means" refers to means for transmitting or receiving information by electromagnetic means, enabling the transmission and reception of digital data via the internet, mobile networks, etc.

[0627] A "human interface" is an interface device or software used by humans to interact with a system and information, and it includes features that allow administrators to review and adjust emotionally-based suggestions and feedback.

[0628] "Means for displaying on electronic devices" refers to a method or device for presenting automatically generated documents on a user's computer, smartphone, or other display device.

[0629] "Data input means" refers to a means of receiving emotional feedback from a user, and is an input device or software that uses a keyboard, touchscreen, voice input, etc.

[0630] This invention is implemented by a system consisting of a user, a terminal, and a server. The system is built around an emotion engine and a generation engine.

[0631] System Overview

[0632] Users input digital data through devices such as smartphones and computers. This digital data includes information such as text messages and images. The data entered by the user is sent to a server using a platform such as LINE. The server receives the input and uses an emotion engine to perform sentiment analysis on this data. As a result of this analysis, a variety of emotions such as joy, sadness, surprise, and dissatisfaction are identified.

[0633] Based on the analyzed sentiment data, the server utilizes a generation engine to automatically generate documents tailored to the user's emotions. These documents may include, for example, polite wording that addresses user dissatisfaction, or purchase suggestions that respond to positive emotions.

[0634] The generated documents are refined in a personalized manner, taking into account the user's emotions. During this process, the documents are reviewed and adjusted by an administrator's human interface before the final document is delivered to the user's device via electronic communication.

[0635] Specific example

[0636] For example, if a user submits feedback about a new product and the server detects an emotion of "joy" in response, it will generate a document containing related product campaign information and a thank-you message, and quickly send it to the user.

[0637] Example of a prompt

[0638] "Analyze the sentiment of user messages and generate appropriate follow-up messages based on the results. For example, if a user expresses dissatisfaction, include an apology and a solution."

[0639] In this system, the server's primary role is to analyze user data and generate and distribute documents based on that analysis. A common API (e.g., the Python library Natural Language Toolkit) is used as the sentiment analysis engine. A widely known generative AI model (e.g., OpenAI's GPT series) is applied as the generation engine to appropriately adjust the documents.

[0640] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0641] Step 1:

[0642] The terminal transfers digital data (text and images) entered by the user to a server via a communication platform such as LINE. The input data includes user feedback and inquiries. The output here is the raw data sent to the server.

[0643] Step 2:

[0644] The server temporarily stores the digital data received from the terminal in storage and sends it to the emotion engine. The input is the received digital data, and the output is the data ready for emotion analysis.

[0645] Step 3:

[0646] The server uses an emotion engine to analyze the input data and identify the user's emotions. Based on the input digital data, the emotion engine uses natural language processing techniques to analyze the emotional components of the data. In this step, the user's emotional state (e.g., joy, dissatisfaction) is labeled.

[0647] Step 4:

[0648] The server automatically generates documents using a generative AI model based on the sentiment labels obtained in the previous step. The input is the sentiment labels and user requests, and the output is a sentiment-sensitive, customized document. Specifically, the model uses prompt sentences to form appropriate responses.

[0649] Step 5:

[0650] The server presents the generated document to the administrator's human interface for review and adjustment. The input is the document generated in the previous step, and the output is the final, adjusted document. The administrator then reviews the content and tone of the document and makes manual corrections as needed.

[0651] Step 6:

[0652] The server delivers the final version of the document to the user's terminal using electronic communication methods. The input is the finalized document, and the output is the message displayed on the user's screen. Specifically, it is shared with the user as an email or LINE message.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] [Fourth Embodiment]

[0657] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0658] 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.

[0659] 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).

[0660] 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.

[0661] 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.

[0662] 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).

[0663] 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.

[0664] 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.

[0665] 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.

[0666] 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.

[0667] 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.

[0668] 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.

[0669] 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".

[0670] The system of this invention consists of a user, a terminal, and a server. The system starts operating when the user sends digital data, such as text messages or images, via a messaging platform such as LINE.

[0671] User roles

[0672] Users join LINE groups using their smartphones or computers to indicate their intention to participate in events, report on their activities, share photos, and so on. This information becomes the basic input data for the system.

[0673] Terminal role

[0674] The terminal receives digital data sent by the user. The terminal temporarily stores this data and prepares it for transmission to the server. The terminal also displays generated documents sent from the server and notifies the user.

[0675] Server Role

[0676] The server is the core of this system and performs multiple processes. First, the server automatically collects digital data sent from terminals. Next, it analyzes the collected digital data, extracting text content and performing image analysis. This identifies event participation status, activity details, or other necessary information.

[0677] Subsequently, the server uses a generation engine based on the analysis results to automatically generate the necessary documents. This generation process ensures consistent document quality by using pre-configured formats and rules. The generated documents can be reviewed by the system administrator before distribution, and manual adjustments are possible if necessary.

[0678] The server then electronically distributes the generated documents, delivering them to relevant members in designated LINE groups or other platforms. This ensures that information is shared quickly and efficiently.

[0679] Specific example

[0680] For example, if a user posts match results and photos to LINE after a sports club game, the server collects and analyzes that information and automatically generates a match results report. The report includes the match score, a list of participants, and photos of notable plays. The generated report is electronically distributed to all involved parties and can be viewed on their devices.

[0681] In this way, the system of the present invention can streamline information sharing and document creation, and simplify overall operation, thereby reducing the burden on the user.

[0682] The following describes the processing flow.

[0683] Step 1:

[0684] The server periodically checks for new messages and posts through the LINE group API and automatically collects digital data. This includes event participation confirmation messages and photo data.

[0685] Step 2:

[0686] The terminal receives digital data sent by the user and temporarily stores it locally. It then converts the data into a format that can be sent to the server.

[0687] Step 3:

[0688] The server receives digital data transmitted from the terminal and analyzes its content using natural language processing (NLP) and image analysis techniques. In particular, it extracts meaning from text messages and identifies scene content and related information from images.

[0689] Step 4:

[0690] The server passes the analysis results to the generation engine, which automatically generates the document according to pre-configured templates and rules. In this process, the necessary information is placed in the appropriate format in each section of the document.

[0691] Step 5:

[0692] The server presents the generated documents to the system administrator via a management interface for review. The administrator can review the documents and make adjustments as needed.

[0693] Step 6:

[0694] The server sends the finalized document electronically to the LINE group or a designated platform. Distribution is done in real time to all relevant users.

[0695] Step 7:

[0696] The terminal displays received documents and notifies the user. The user can then review the documents in detail on the terminal and share the information with other relevant parties as needed.

[0697] (Example 1)

[0698] 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".

[0699] In today's information society, it is crucial to efficiently share information about various events and activities in which users participate and to quickly create necessary documents. However, traditional methods often involve manual processes for information collection, analysis, document generation, and distribution, which are time-consuming and laborious. Ensuring the consistency and accuracy of information also poses challenges. There is a need for a system that can solve these problems and improve the efficiency of information sharing.

[0700] 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.

[0701] In this invention, the server includes means for automatically collecting information input via a communication device operated by a user, means for analyzing the collected information and extracting information based on characters and images, and means including a generation device for automatically generating documents based on the analysis results. This enables a series of processes from information collection to document generation and distribution to be carried out quickly and automatically, significantly improving the efficiency of information sharing.

[0702] A "communication device" is a device that has the function of receiving information input by a user and communicating with other system components via a network.

[0703] "Information" refers to digital data, including text data and image data entered by the user.

[0704] "Means of automatic collection" refers to means that have the function of autonomously collecting input information without requiring user intervention.

[0705] "Analysis" refers to the process of processing collected information to extract specific content or features.

[0706] "Means for extracting information based on text and images" refers to means for extracting necessary information from text data and visual data.

[0707] A "generator" is a device that has the function of constructing a document based on the analysis results.

[0708] An "information network" refers to communication infrastructure for transmitting digital data, and includes the internet and local networks.

[0709] An "output device" is a device that has a display or screen on which the user can ultimately view the document.

[0710] An "interface" is a means for a user to interact with a system, and in particular, it provides an environment for reviewing and editing documents.

[0711] A "participant list" is information that shows a list of users who participated in an event or activity.

[0712] The system based on this invention consists of a user, a terminal, and a server. This system starts operating upon information input from a communication device operated by the user.

[0713] Users transmit digital data using a communication platform via devices such as smartphones and computers. This data includes event participation information and images, and is used as basic input data for the system.

[0714] The terminal temporarily stores the received input information and transfers it to the server via the network. The terminal also plays a role in displaying the generated documents sent from the server.

[0715] The server functions as a central control component, automatically collecting digital data sent from communication devices. The server analyzes the collected data and extracts specific information based on text and images. This analysis utilizes natural language processing tools and image recognition algorithms. A specific example is the use of the Google Cloud Vision API for image analysis.

[0716] The server then sends the analysis results to a generating AI model, which generates a document according to a pre-configured format. The generated document is reviewed through an interface that allows for inspection and manual modification, and then distributed to the designated recipient via the information network.

[0717] As a concrete example, in a sports event, if a user posts match results and related photos to a dedicated group chat, the server automatically collects this information and generates a report that includes a summary of the match results. This report is generated in a format that includes a list of participants and photos of important events, and is distributed to all relevant parties. An example of a specific prompt message would be, "Please create a report using the following match information: match date, team names, score, and photos of notable plays."

[0718] This allows users to simplify the information sharing process and efficiently handle everything from document creation to distribution.

[0719] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0720] Step 1:

[0721] Users access messaging platforms such as LINE using communication devices and send digital data. This data includes text messages and images. For example, score information for sporting events and photos of participants are sent. This information serves as foundational data for subsequent processing.

[0722] Step 2:

[0723] The terminal receives digital data sent from the user. The data received as input is temporarily stored in the terminal's local storage. Specifically, the terminal takes in the received data via the network communication module and stores it in a buffer. This process prepares the data for immediate transfer to the server.

[0724] Step 3:

[0725] The terminal sends the stored digital data to the server. This involves specific actions that use security protocols to securely transfer the input data to the server. As output, the data arrives at the server and is ready for processing on the server side.

[0726] Step 4:

[0727] The server receives and automatically collects digital data transmitted from the terminal. Upon receiving the input data, the server analyzes its contents. Specifically, it uses natural language processing tools to analyze text information and extract important content and event information. For image data, it uses image recognition algorithms to identify visual information. The output is the analyzed information, now ready for use by the generation engine.

[0728] Step 5:

[0729] The server automatically generates documents using an AI model based on the analysis results. Analyzed text and image information are provided as input. Based on prompts, the document is generated according to a pre-configured format. Specifically, important information is extracted and assembled according to a system-defined template. As a result, a highly polished document is produced as output.

[0730] Step 6:

[0731] The server uses the network to deliver the generated documents to users. The generated documents are sent via the information network to a designated LINE group or other platform. The specific operation includes a transmission process using a distribution protocol. As output, the documents are delivered to and viewable on devices accessible to the user.

[0732] (Application Example 1)

[0733] 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".

[0734] In factory and other work environments, it is necessary to quickly and accurately communicate progress reports from each section and equipment maintenance results to managers. However, these reporting tasks are often done manually, which is time-consuming and labor-intensive, making efficient information sharing difficult.

[0735] 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.

[0736] In this invention, the server includes means for automatically collecting digital data entered by a user, means for analyzing the collected digital data and extracting information based on characters and images, and means including a generation processing unit that automatically generates a document based on the analysis results. This enables the automatic compilation of work reports and equipment maintenance status within the factory, prompt notification to managers, and efficient information sharing.

[0737] A "user" is an individual or group that uses a system to input digital data.

[0738] "Digital data" refers to electronically recorded information, and is a general term for data that includes text and images.

[0739] "Automatic collection methods" refer to systems that capture digital data sent by users without human intervention.

[0740] "Means for analyzing and extracting information based on text and images" refers to processing technologies for understanding digital data and extracting important information.

[0741] "Means including a generation processing unit" refers to a mechanism that has the function of automatically creating a document based on the analyzed information.

[0742] "Means of electronic distribution" refers to the technology of delivering generated documents to recipients via digital communication.

[0743] The "means of immediately notifying administrators" refer to a function that facilitates the rapid exchange of information regarding generated documents.

[0744] A "display unit" refers to a device or software that allows users to visually confirm the content of a generated document.

[0745] "Information processing equipment" is a general term for electronic devices used to manipulate and manage digital data.

[0746] To realize this application, the server runs a program that automatically collects work reports and equipment maintenance progress information from within the factory. The collected digital data is analyzed on the server using a Python program. This analysis uses OpenCV to analyze image data and NLTK to analyze text data.

[0747] After analysis, the document is automatically created in the generation processing unit and documented using the Docx library. This document is distributed electronically and immediately notified to information processing devices used by administrators and relevant personnel using the LINE Notify API. The notified content can be visually confirmed on each user's device.

[0748] As a concrete example, if a part in the factory needs maintenance, a worker sends a photo of the part to the server via LINE. This information is automatically analyzed by the server, and a report is generated indicating whether the part needs to be replaced or maintained. This report is immediately notified to the manager, allowing for prompt and appropriate action to be taken.

[0749] An example of a prompt message for the generating AI model would be an instruction such as, "Please compile a report on the equipment maintenance status. Please highlight any critical failure points." This format can reduce the burden of manual reporting and significantly improve the efficiency of information sharing.

[0750] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0751] Step 1:

[0752] Users send information about factory work status and equipment maintenance as LINE messages. Input is either text messages or image data on LINE. This is the first time that user-observed information is incorporated into the system in digital format.

[0753] Step 2:

[0754] The terminal forwards the received LINE message to the server. The input is the LINE message from the user, and the output is the transmission of digital data to the server. In this step, the data is subject to processing by the server.

[0755] Step 3:

[0756] The server parses the received messages. Here, Python is used, with NLTK for text analysis and OpenCV for image analysis. The input is LINE digital data transferred by the user, and the output is extracted text content and image information. The server generates analysis results based on this information.

[0757] Step 4:

[0758] The server automatically generates documents based on the analysis results. The Python Docx library is used for the generation process. The input is text and image information from the analysis results, and the output is a documented report. At this stage, prompt sentences are provided to the generation AI model to optimize the document content.

[0759] Step 5:

[0760] The server uses the LINE Notify API to notify administrators and relevant personnel of the generated report. The input is the generated report, and the output is a notification via LINE. The information generated in this step is distributed to users, prompting a quick response.

[0761] 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.

[0762] This invention relates to a system consisting of a user, a terminal, and a server, which, in particular, uses an emotion engine to perform emotion analysis on data input by the user. The results of this analysis are reflected in various processes in document generation and distribution.

[0763] User roles

[0764] Users send text messages and images using platforms such as LINE via their smartphones or computers. Emotional messages are also entered into the system during this process.

[0765] Terminal role

[0766] The device receives and temporarily stores the digital data sent by the user. The text data is then sent directly to the server for analysis by the emotion engine.

[0767] Server Role

[0768] 1. Data Collection and Analysis

[0769] The server receives digital data sent from the terminal and uses an emotion engine to perform sentiment analysis on the text data. This analysis identifies the emotions contained in the user's message, such as joy, sadness, or surprise.

[0770] 2. Document generation

[0771] The server automatically generates documents using a generation engine based on the collected and analyzed results. It can flexibly adjust the content and expression of the documents, taking into account the results of sentiment analysis. For example, if a user expresses dissatisfaction, it can use more polite language.

[0772] 3. Review and adjustment

[0773] The generated documents are presented to the administrator through an interface. The administrator can review the documents and make manual adjustments, taking into account the results of the sentiment analysis.

[0774] 4. Distribution

[0775] The finalized document will be distributed electronically from the server. All relevant parties will be notified via LINE or other designated platforms.

[0776] Specific example

[0777] Consider a scenario where a user submits event feedback via LINE. When the sentiment engine detects elements of dissatisfaction in the user's comment, the server analyzes the feedback and generates a document containing suggestions and acknowledgments. This document includes a response to the issues the user raised, along with an expression of gratitude. After review by the administrator, the document is distributed to all relevant parties, and the content is followed up on.

[0778] Thus, this invention enables advanced document generation through emotion analysis, improving the user experience. Furthermore, by immediately reflecting emotional feedback, it is expected to facilitate rapid problem solving and smoother communication among stakeholders.

[0779] The following describes the processing flow.

[0780] Step 1:

[0781] Users post text messages and images to groups using messaging platforms such as LINE. These messages may contain the user's emotions.

[0782] Step 2:

[0783] The terminal receives digital data sent by the user and prepares it for transmission to the server. It then transmits the digital data to the server via a secure channel.

[0784] Step 3:

[0785] The server automatically collects digital data transmitted from terminals and analyzes the text and image data. Natural language processing techniques are used to extract content and sentiment from the text data.

[0786] Step 4:

[0787] The server identifies the user's emotions from the text data extracted using an emotion engine. Depending on the user's message, emotions such as joy, sadness, and anger may be identified.

[0788] Step 5:

[0789] Based on the analyzed emotion data, the server activates a generation engine and automatically generates a document. During this process, it is possible to adjust the tone and content of the document according to the detected emotions.

[0790] Step 6:

[0791] The generated document is presented to the administrator via an interface by the server. The administrator can review the document and make manual adjustments as needed. Sentiment analysis results assist in the review process.

[0792] Step 7:

[0793] The server will deliver the final verified document. All relevant parties will be notified via electronic means, such as a LINE group or other platform.

[0794] Step 8:

[0795] The device displays the received document and notifies the user of its contents. The user can view this document and provide responses or feedback as needed.

[0796] This series of steps ensures that digital data, including user emotions, is effectively processed and shared through the system.

[0797] (Example 2)

[0798] 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".

[0799] In recent years, with the proliferation of diverse communication platforms, messages sent by users are imbued with a wealth of emotions. If these emotional elements cannot be properly analyzed and reflected in responses, improving the user experience and quickly resolving problems becomes difficult. Furthermore, manually processing large volumes of messages is inefficient, and there is a need to provide appropriate feedback in a timely manner.

[0800] 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.

[0801] In this invention, the server includes means for automatically collecting data entered by the user, means for analyzing the collected data using an emotion analysis engine and extracting emotion information, and means including a generation engine for automatically generating text based on the analysis results. This makes it possible to instantly analyze the user's emotions and generate and deliver an appropriate response.

[0802] A "user" is an individual or group that inputs data and uses the system.

[0803] "Data" refers to information such as messages and images entered by the user.

[0804] An "emotion analysis engine" is specialized software or hardware used to extract and analyze emotional information from input data.

[0805] A "generative engine" is a program or system that automatically generates text based on the results of sentiment analysis.

[0806] An "administrator" is a person or system whose role is to review the generated document and manually adjust its content as needed.

[0807] "Interface" refers to the means or screens that users or administrators use to interact with a system.

[0808] "Distribution" refers to electronically sending generated and edited documents to relevant parties.

[0809] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate text.

[0810] A "prompt" refers to the text that serves as instructions or guidelines input into a generative AI model.

[0811] This invention is a system comprising a user, a terminal, and a server. The user uses a smart device to send messages containing emotional elements via a digital platform. Examples include text messages and images sent through communication applications.

[0812] The device receives data sent by the user and stores it temporarily. The stored data is sent to a server and used for sentiment analysis. The device may use encryption technology to securely transmit the data.

[0813] The server receives data sent from the terminal and analyzes the text data using an emotion analysis engine. The analysis process utilizes natural language processing techniques to extract emotional information from the message's context and vocabulary. This analysis identifies emotions such as joy, sadness, and dissatisfaction contained in the user's message.

[0814] Based on the analysis results, the server uses a generation engine to automatically generate appropriate text. In this process, it uses a generation AI model to customize the document according to specific emotions. For example, if an emotion of dissatisfaction is detected, it will create a text that includes suggestions for improvement or expressions of gratitude, taking that emotion into account.

[0815] The generated text can be reviewed and manually edited by the administrator. After administrator approval, the final version of the text is finalized and distributed electronically from the server through the designated platform.

[0816] As a concrete example, consider a scenario where a user submits feedback about an event, and that feedback includes complaints. The server analyzes this feedback and generates a message expressing gratitude and proposing solutions to the user's points of dissatisfaction. This message is then quickly sent back to the user, contributing to increased satisfaction.

[0817] An example of a prompt message is: "User-sent message: Enter the user's message here. Analyze the user's sentiment and generate a polite response based on it." This is how you can instruct the generation AI model.

[0818] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0819] Step 1:

[0820] Users send messages to the platform via digital devices. Input consists of digital data in text and image formats. The device receives this data and temporarily stores it.

[0821] Step 2:

[0822] The terminal transmits stored digital data to the server. The input is the user's message data. As output, the data is sent to the server and prepared for sentiment analysis. Encryption technology is used for data transmission to ensure security.

[0823] Step 3:

[0824] The server receives data sent from the terminal and uses an emotion analysis engine. The input is text message data. This engine uses natural language processing techniques to extract emotional information from the data. The output is numerical information representing the user's emotions.

[0825] Step 4:

[0826] The server automatically generates text using a generation engine based on the results of sentiment analysis. The input is quantified sentiment information. Using a generation AI model, it creates the most appropriate document according to the sentiment. The output at this step is text specifically tailored for user interaction.

[0827] Step 5:

[0828] The server presents the generated text to the administrator's interface. The administrator reviews the text and makes manual adjustments as needed. The input is pre-generated text. Once adjustments are complete, the final version is finalized as output.

[0829] Step 6:

[0830] The server distributes the final version of the document to relevant parties via a digital platform. The input is the document reviewed and edited by the administrator. The output is the message sent to the designated users and parties. The distribution process is completed, and the system operation ends.

[0831] (Application Example 2)

[0832] 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".

[0833] Modern virtual stores lack the ability to provide services that reflect user emotions in real time, and a uniform approach is insufficient to adequately enhance customer satisfaction. Therefore, personalized suggestions and feedback based on actual user emotions are needed, but this has been difficult to achieve with conventional systems.

[0834] 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.

[0835] In this invention, the server includes means for automatically collecting digital data entered by the user, means for analyzing the collected digital data using an emotion engine and extracting emotion-based information, and means including a generation engine that automatically generates documents based on the analysis results and adjusts the content to match the user's emotions. This enables personalized suggestions that take the user's emotions into consideration and smooth customer service.

[0836] "User-input digital data" refers to data such as text and images that users input using input devices such as smartphones and computers and send to the system.

[0837] An "emotion engine" is an analytical device or software that analyzes emotional components contained in digital data received from a user to identify emotions such as joy, sadness, and dissatisfaction.

[0838] A "generative engine" is a generation device or software that generates documents based on the results obtained from sentiment analysis and has the function of adjusting the content and expression to match the user's emotions.

[0839] "Electronic communication means" refers to means for transmitting or receiving information by electromagnetic means, enabling the transmission and reception of digital data via the internet, mobile networks, etc.

[0840] A "human interface" is an interface device or software used by humans to interact with a system and information, and it includes features that allow administrators to review and adjust emotionally-based suggestions and feedback.

[0841] "Means for displaying on electronic devices" refers to a method or device for presenting automatically generated documents on a user's computer, smartphone, or other display device.

[0842] "Data input means" refers to a means of receiving emotional feedback from a user, and is an input device or software that uses a keyboard, touchscreen, voice input, etc.

[0843] This invention is implemented by a system consisting of a user, a terminal, and a server. The system is built around an emotion engine and a generation engine.

[0844] System Overview

[0845] Users input digital data through devices such as smartphones and computers. This digital data includes information such as text messages and images. The data entered by the user is sent to a server using a platform such as LINE. The server receives the input and uses an emotion engine to perform sentiment analysis on this data. As a result of this analysis, a variety of emotions such as joy, sadness, surprise, and dissatisfaction are identified.

[0846] Based on the analyzed sentiment data, the server utilizes a generation engine to automatically generate documents tailored to the user's emotions. These documents may include, for example, polite wording that addresses user dissatisfaction, or purchase suggestions that respond to positive emotions.

[0847] The generated documents are refined in a personalized manner, taking into account the user's emotions. During this process, the documents are reviewed and adjusted by an administrator's human interface before the final document is delivered to the user's device via electronic communication.

[0848] Specific example

[0849] For example, if a user submits feedback about a new product and the server detects an emotion of "joy" in response, it will generate a document containing related product campaign information and a thank-you message, and quickly send it to the user.

[0850] Example of a prompt

[0851] "Analyze the sentiment of user messages and generate appropriate follow-up messages based on the results. For example, if a user expresses dissatisfaction, include an apology and a solution."

[0852] In this system, the server's primary role is to analyze user data and generate and distribute documents based on that analysis. A common API (e.g., the Python library Natural Language Toolkit) is used as the sentiment analysis engine. A widely known generative AI model (e.g., OpenAI's GPT series) is applied as the generation engine to appropriately adjust the documents.

[0853] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0854] Step 1:

[0855] The terminal transfers digital data (text and images) entered by the user to a server via a communication platform such as LINE. The input data includes user feedback and inquiries. The output here is the raw data sent to the server.

[0856] Step 2:

[0857] The server temporarily stores the digital data received from the terminal in storage and sends it to the emotion engine. The input is the received digital data, and the output is the data ready for emotion analysis.

[0858] Step 3:

[0859] The server uses an emotion engine to analyze the input data and identify the user's emotions. Based on the input digital data, the emotion engine uses natural language processing techniques to analyze the emotional components of the data. In this step, the user's emotional state (e.g., joy, dissatisfaction) is labeled.

[0860] Step 4:

[0861] The server automatically generates documents using a generative AI model based on the sentiment labels obtained in the previous step. The input is the sentiment labels and user requests, and the output is a sentiment-sensitive, customized document. Specifically, the model uses prompt sentences to form appropriate responses.

[0862] Step 5:

[0863] The server presents the generated document to the administrator's human interface for review and adjustment. The input is the document generated in the previous step, and the output is the final, adjusted document. The administrator then reviews the content and tone of the document and makes manual corrections as needed.

[0864] Step 6:

[0865] The server delivers the final version of the document to the user's terminal using electronic communication methods. The input is the finalized document, and the output is the message displayed on the user's screen. Specifically, it is shared with the user as an email or LINE message.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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."

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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 to be incorporated by reference.

[0887] The following is further disclosed regarding the embodiments described above.

[0888] (Claim 1)

[0889] A means of automatically collecting digital data entered by users,

[0890] The means for analyzing the collected digital data and extracting information based on text and images,

[0891] A means including a generation engine that automatically generates a document based on the aforementioned analysis results,

[0892] A means for electronically distributing the automatically generated document,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, further comprising an interface that enables review and manual adjustment of the automatically generated document.

[0896] (Claim 3)

[0897] The system according to claim 1, further comprising means for displaying the distributed document on a terminal accessible to the user.

[0898] "Example 1"

[0899] (Claim 1)

[0900] A means for automatically collecting information entered via a communication device operated by a user,

[0901] The means for analyzing the collected information and extracting information based on text and images,

[0902] Means including a generation device that automatically generates a document based on the analysis results,

[0903] Means for distributing the automatically generated document via an information network,

[0904] Means for displaying a document on an output device accessible to the user,

[0905] A system that includes this.

[0906] (Claim 2)

[0907] The system according to claim 1, further comprising an interface that enables inspection and manual modification of the automatically generated document.

[0908] (Claim 3)

[0909] The system according to claim 1, further comprising means for creating a specific participant list when the input information includes the status of event participation.

[0910] "Application Example 1"

[0911] (Claim 1)

[0912] A means of automatically collecting digital data entered by users,

[0913] The means for analyzing the collected digital data and extracting information based on text and images,

[0914] Means including a generation processing unit that automatically generates a document based on the analysis results,

[0915] A means for electronically distributing the automatically generated document,

[0916] A means of immediately notifying the administrator of the generated document,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, further comprising a display unit that enables review and manual adjustment of the automatically generated document.

[0920] (Claim 3)

[0921] The system according to claim 1, further comprising means for displaying the distributed document on an information processing device accessible to the user.

[0922] "Example 2 of combining an emotion engine"

[0923] (Claim 1)

[0924] A means of automatically collecting data entered by the user,

[0925] The collected data is analyzed by an emotion analysis engine, and means are used to extract emotional information.

[0926] A means including a generation engine that automatically generates text based on the aforementioned analysis results,

[0927] Means for providing an interface for an administrator to review and manually adjust the automatically generated text,

[0928] A means for electronically distributing the aforementioned adjusted text,

[0929] A system that includes this.

[0930] (Claim 2)

[0931] The system according to claim 1, further comprising means for displaying the distributed text on a device accessible to the user.

[0932] (Claim 3)

[0933] The system according to claim 1, comprising means for inputting a prompt sentence for generating the aforementioned text using a generative AI model.

[0934] "Application example 2 when combining with an emotional engine"

[0935] (Claim 1)

[0936] A means of automatically collecting digital data entered by users,

[0937] A means for analyzing the collected digital data using an emotion engine and extracting information based on emotions,

[0938] A means including a generation engine that automatically generates documents based on the aforementioned analysis results and adjusts the content to suit the user's emotions,

[0939] A means for distributing the automatically generated document using electronic communication means and making commercial proposals to improve the user experience,

[0940] A system that includes this.

[0941] (Claim 2)

[0942] The system according to claim 1, comprising a human interface for reviewing and manually adjusting the automatically generated documents and for confirming suggestions based on the user's sentiment.

[0943] (Claim 3)

[0944] The system according to claim 1, further comprising means for displaying the delivered document on an electronic device accessible to the user, and for receiving emotional feedback. [Explanation of Symbols]

[0945] 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 automatically collecting digital data entered by users, The means for analyzing the collected digital data and extracting information based on text and images, A means including a generation engine that automatically generates a document based on the aforementioned analysis results, A means for electronically distributing the automatically generated document, A system that includes this.

2. The system according to claim 1, further comprising an interface that enables review and manual adjustment of the automatically generated document.

3. The system according to claim 1, further comprising means for displaying the distributed document on a terminal accessible to the user.

Images