system

Abstract

We provide the system. [Solution] A means of communication for receiving messages from users, An analysis means for analyzing the user's request from the aforementioned message, A design means for designing an application based on the aforementioned requirements, A generation means for automatically generating an application based on the specifications designed by the design means, A system including a display means for providing a preview of the aforementioned application to a user.

Description

Technical Field

[0005] ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, many users are searching for efficient management methods in their daily lives and business management, but there is a problem that it is difficult to find a method that perfectly meets each need. In particular, there is a lack of an environment where general users without specialized programming knowledge can easily create and manage their own dedicated applications. For this reason, users are facing the problem that although they need applications specialized for specific uses, their development is difficult.

Means for Solving the Problems

[0005] The present invention solves the aforementioned problems by providing a system that automatically generates applications based on user input. Specifically, it includes means for receiving messages from users and designing and automatically generating applications based on the analysis results. This system also includes means for easily incorporating user-requested functions and interfaces into the design and providing previews to obtain feedback. Furthermore, it enables the application to be redesigned based on user feedback, ultimately completing an application tailored to the user. In this way, even without specialized knowledge, users can easily create and use management tools that meet their needs.

[0006] "Communication means" refers to a device or software that has the function of receiving messages from a user and sending them to a server.

[0007] "Analysis means" refers to a device or software that processes messages received from a user and extracts the user's requests and needs from them.

[0008] "Design means" refers to the process of determining the specifications of an application based on the analyzed user requirements, and is the device or system that performs the design based on those specifications.

[0009] "Generation means" refers to a device or software that automatically creates and constructs application code based on specifications determined by the design means.

[0010] "Display means" refers to a device or software that has the function of providing a user with an easily understandable preview of the generated application, allowing the user to visually confirm it.

[0011] "Acquisition means" refers to a device or software that has the function of receiving feedback from a user after they have viewed a preview of an application and transmitting that feedback to the system.

[0012] A "redesign tool" is a device or software that handles the process of reviewing the application design based on the feedback received, making necessary modifications, and then regenerating it. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention relates to a system that automatically generates applications tailored to the user's needs. This system consists of a terminal used by the user, an analysis and generation device located on a cloud server, and a function to control the user interface.

[0035] The user uses their usual messaging application to input a message from their device requesting the application they need. The device sends this message to the server and initiates the task. At this point, the communication is encrypted, and the user's information is securely protected.

[0036] On the server, received messages are processed by an analysis tool. The analysis tool uses natural language processing to analyze the user's message and clearly identify the requested functions and elements. Based on these analysis results, the design tool operates to design an application that embodies the user's requirements.

[0037] The designed information is generated as actual application code by a generation mechanism. The necessary program logic and database structure are automatically constructed according to the specified requirements. This code generation is designed to efficiently and flexibly meet user needs.

[0038] The generated application is provided to the user as a preview through a display mechanism. Through this preview, the user can verify the application's basic structure and functionality. For example, in the case of a task management application, the user can check whether adding tasks and displaying lists works correctly.

[0039] Users can provide feedback on the preview via their devices. This feedback is sent to a server by a data acquisition mechanism and analyzed. Based on this, a redesign mechanism revises the process as needed and creates a new design. Through this cycle, users can obtain their ideal application.

[0040] This invention employs a multi-stage intelligent generation process to realize a user-centric process and provides applications optimized to solve specific problems. Furthermore, by flexibly responding to user input, it ensures a high degree of customization to meet individual user needs.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users use LINE's chat interface to enter their needs and requests in message format. For example, by writing a request such as "I want to create a project management app," they can send a request focused on a specific function to the system.

[0044] Step 2:

[0045] The device encrypts the user's input messages and sends them to the cloud server. Appropriate encryption protocols are used throughout this process to maintain data integrity and privacy.

[0046] Step 3:

[0047] The server passes the received message to the parsing mechanism. The parsing mechanism uses a natural language processing algorithm to analyze the user's request and extract the necessary functions and requirements. Here, keywords such as project management and task deadline management are identified.

[0048] Step 4:

[0049] Based on the analysis results, the server begins designing the application using design tools. This involves creating mockups of the user interface and performing hypothetical modeling to design the database structure. Necessary features, such as task addition and deadline setting, are incorporated into the design.

[0050] Step 5:

[0051] After the design is complete, the generation process on the server automatically generates the application code. The source code is constructed to include backend logic, frontend components, database schema, and other elements.

[0052] Step 6:

[0053] A preview of the generated application is sent to the device. The device displays this preview to the user, allowing the user to visually confirm how the system actually works.

[0054] Step 7:

[0055] Users evaluate the application based on the provided preview and send any necessary changes or additional feedback to the server via their device. This allows for optimization based on user preferences.

[0056] Step 8:

[0057] The server analyzes the feedback and redesigns based on the newly extracted requirements. The redesign mechanism then regenerates the application with the new specifications, creating an improved version.

[0058] Step 9:

[0059] The final version of the redesigned application is transferred to the terminal, allowing users to use it in their actual work and daily lives. Through this iterative process, the system provides a customized solution that fully meets the user's needs.

[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] There is a growing demand for software that can flexibly respond to diverse user needs and be efficiently, securely, and safely customizable. However, many current software generation systems fail to respond quickly to user requests and lack sufficient customization options for individual requirements. Furthermore, they lack adequate mechanisms for effectively utilizing user feedback during previews.

[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 a communication device that receives requests from users, an analysis device that analyzes the requests and extracts the user's objectives, a design device that designs software based on the objectives, a display device that presents an overview of the software to the user, and a verification device that verifies the operation of the software and optimizes the design content according to the user's requests. This makes it possible to efficiently generate customizable software that can respond immediately to the needs of diverse users, and to optimize the design through user feedback.

[0065] A "communication device" is a device that has the function of receiving requests from users and transmitting them to a server.

[0066] An "analysis device" is a device that analyzes received requests and extracts the user's objectives.

[0067] A "design device" is a device used to design software based on the extracted objectives.

[0068] A "generation device" is a device that automatically generates software using data created by a design device.

[0069] A "display device" is a device that has the function of presenting an overview of the generated software to the user.

[0070] A "verification device" is a device that verifies the operation of software and optimizes its design to meet user requirements.

[0071] A "redesign device" is a device used to redesign and regenerate software based on user feedback.

[0072] "Encryption" is a method of securely protecting data during transmission so that it cannot be read by a third party.

[0073] This invention relates to a system that allows a user to automatically generate software according to their own requirements. This system mainly includes a terminal for inputting user requests, a server that analyzes the requests and generates software, and various devices for verifying and optimizing the generated software.

[0074] Users use their usual messaging applications to input requests for the software they need into their devices. For example, they can use specific prompts such as, "I want an app to keep track of my household finances." The device receives this input and sends it to the server in an encrypted form via a communication device. Security protocols such as SSL / TLS are commonly used for this encryption.

[0075] The server analyzes received requests using natural language processing technology with an analysis device. A generative AI model is used to analyze the context and content of the request, clearly extracting the user's objective. Next, a design device operates based on these analysis results, designing the necessary software structure and functionality. Specifically, this involves database structure design and interface layout design.

[0076] The generation device automatically generates software based on the design. This process comprehensively and automatically generates program logic and data management structures, providing software that adheres faithfully to the designed specifications. The generated software is presented to the user as a preview via a display device, allowing for verification of its operation and functionality. After reviewing the preview and verifying the software's usability, the user can provide feedback through the terminal.

[0077] User feedback is resent to the server, where a verification device analyzes its contents. This allows a redesign device to redesign and modify the software as needed, then generate a new version. Through this cycle, users can obtain software that is more ideal and better suited to their needs.

[0078] This system makes it possible to quickly respond to complex and individualized user needs and improve the user experience.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The user uses a messaging application to input their request into the device. The input is a prompt message such as, "I want an app to keep track of household expenses." This input is captured by the device as text data, including the user's request and desired application features.

[0082] Step 2:

[0083] The terminal sends the received prompt message to the server. During this process, the prompt message is encrypted using a communication device and securely transmitted to the server. The input is encrypted text data, and the output is the message securely sent to the server.

[0084] Step 3:

[0085] The server decrypts the received encrypted message and performs natural language processing using an analysis device. Here, a generative AI model is used to extract the user's objective (e.g., a request for a financial management function) from the prompt text. The input is the decrypted prompt text, and the output is the analyzed user objective data.

[0086] Step 4:

[0087] The server designs software using a design device based on the analysis results. This process involves designing the necessary database structure and user interface. The input is user-targeted data, and the output is software structure data as design information.

[0088] Step 5:

[0089] The server automatically generates software based on data designed using a generation device. Program code is generated, and a functional application is formed. The input is software structure data, and the output is the generated application program.

[0090] Step 6:

[0091] The server provides the generated application to the user as a preview via a display device. The user tries out the provided application and checks its usability and functionality. The input is the application program, and the output is the preview environment that the user actually interacts with.

[0092] Step 7:

[0093] After reviewing the preview, users send feedback to the server via their device. This feedback includes specific comments on usability and additional requests. The input is text data representing the user's opinion, and the output is the feedback message sent to the server.

[0094] Step 8:

[0095] The server analyzes the received feedback and modifies the software as needed using a redesign device. Here, the software is redesigned and generated based on the feedback. The input is the analyzed feedback data, and the output is the modified application program.

[0096] (Application Example 1)

[0097] 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."

[0098] There is a lack of means to quickly and efficiently build computer programs with the functions desired by users. This results in the problem of difficulty and cost in customizing programs to meet individual needs.

[0099] 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.

[0100] In this invention, the server includes a transmission means for receiving instructions from a user, an analysis means for understanding the user's requests from the instructions, and a construction means for constructing a computer program based on the requests. This enables rapid response to individual user needs and automatic generation of customized programs.

[0101] A "transmission means" is a device equipped with communication functions for receiving instructions from a user.

[0102] An "analysis tool" is a device that has a processing function to understand the user's request from the received instructions.

[0103] "Construction means" refers to a device that has design and construction functions for creating computer programs based on user requirements.

[0104] A "creation means" is a device that has the function of automatically generating a computer program based on the established specifications.

[0105] "Provisioning means" refers to a device that has the function of providing a trial version of a generated computer program to a user.

[0106] A "collection device" is a device with communication capabilities for collecting opinions and feedback from users.

[0107] A "reconstruction tool" is a device that has the function of modifying the design of a computer program based on collected feedback and then regenerating it.

[0108] "Encryption" is the process of transforming data to enhance security during the transmission and reception of information.

[0109] To implement this invention, a terminal for the user to give instructions, a server to receive and process the instructions, and means to provide the generated computer program are required. First, the user uses the terminal to input instructions requesting a specific function or service. These instructions might be, for example, a request for an application that has the function to update new products in a virtual store.

[0110] The terminal securely transmits user instructions to the server. The server uses natural language processing techniques to analyze the received instructions. This analysis utilizes generative AI models such as Google® BERT and OpenAI® GPT-3®, with the aim of clearly understanding what the user wants. After the analysis is complete, the server designs a program in response to the request through a construction mechanism and generates the actual code through a creation mechanism.

[0111] The generated computer program is provided to the user as a trial version through a distribution channel. This trial version allows the user to verify whether the generated program's functionality meets their requirements. For example, if the prompt "Create an application that updates new book information daily and issues an alert if it is not updated" is entered, the server will create an application based on this and provide it to the user.

[0112] This system can also obtain feedback from users through collection mechanisms and modify the program through reconstruction mechanisms. For example, if a user requests "stronger notifications when product updates are delayed," the server can reconstruct the application based on that feedback and provide it again.

[0113] In this way, this invention makes it possible to quickly and efficiently generate customizable applications that meet the individual needs of users.

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

[0115] Step 1:

[0116] The user uses their device to input application requests in natural language. For example, they might specifically type, "I want an app with a new product update function," into a messaging app. The device encrypts the user's input and securely transmits it to the server.

[0117] Step 2:

[0118] The server decrypts the received encrypted message and receives the input text. Next, it uses a generative AI model (e.g., OpenAI GPT-3) to analyze the text, breaking down and understanding the user's request into specific elements. This analysis extracts keywords such as "new product" and "update function."

[0119] Step 3:

[0120] Based on the analyzed requests, the server begins program design using a generation mechanism. Specifically, the necessary functions (e.g., database updates, notification functions) are designed, and the logical structure of the computer program is defined.

[0121] Step 4:

[0122] The server generates program code using a generation mechanism based on the designed logical structure. The input is design information, and the output is executable program code. This code generation is automated and performed quickly.

[0123] Step 5:

[0124] The generated program is sent to the terminal via a delivery method and provided to the user as a trial version. The user can run the program and verify that it functions as required.

[0125] Step 6:

[0126] Users use the trial version and provide feedback via their device. This feedback, such as "the notification function doesn't work as expected," is sent to the server.

[0127] Step 7:

[0128] The server receives user feedback using collection methods and modifies the program using reconstruction methods. Based on the feedback, the program is redesigned and generated again to create an improved program.

[0129] Step 8:

[0130] The reconstructed program is again sent to the terminal via the delivery method and provided to the user as a trial version. By repeating this cycle, the final program that perfectly matches the user's requirements is generated.

[0131] 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.

[0132] This invention relates to a system that recognizes a user's emotions and automatically generates a customized application based on those emotions. The system includes an emotion engine that analyzes the user's input and emotions, and processing means for optimizing the design and functionality of the generated application.

[0133] Users use a messaging application to input and send requests for applications they need. These requests include not only the message content itself, but also the emotions the user may have. The device securely sends this message to a cloud server. The server analyzes the received message and extracts functional requests from the user's input.

[0134] In this analysis process, the emotion engine plays a particularly important role. The emotion engine installed on the server uses natural language processing technology to read emotions from the user's words. For example, if a user inputs "I'm too busy to manage things properly," the engine recognizes emotions such as "dissatisfaction" and "stress" from that input and determines which functions to prioritize providing in the application.

[0135] Based on user requests and emotions, the emotion engine automatically designs and optimizes the application. This enables design considerations tailored to the user's emotional state and a user-friendly layout of features. For example, users experiencing high stress levels will be given emphasis on simple, intuitive designs and reminder functions.

[0136] The generation mechanism works closely with the emotion engine to provide the user with a preview application optimized for them on their device. Users can review this preview and evaluate how the application functions and whether it meets their emotionally demanding needs. This feedback is also incorporated into the redesign, enabling further optimization based on user emotions.

[0137] This invention enables users to utilize more personalized applications that are tailored to their emotions at any given moment, without being bound by templates. This combination of emotion recognition technology and automatic generation means contributes to improving the user experience and provides effective solutions quickly.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] Users use messaging applications to input their problems and requests for necessary applications, and send messages through their devices. These inputs may include expressions of the user's emotions.

[0141] Step 2:

[0142] The device receives messages from the user and sends them to the cloud server. During this process, the device encrypts the messages to ensure the user's data remains secure.

[0143] Step 3:

[0144] The server processes received messages using analysis tools. During the analysis process, it utilizes language processing techniques to identify specific functions desired by the user from the message, while simultaneously analyzing the user's emotional state using an emotion engine.

[0145] Step 4:

[0146] The emotion engine analyzes the emotions derived from user messages and correlates them with the results to determine application design priorities. This information is used to select features that recommend stress reduction and designs that enhance joy.

[0147] Step 5:

[0148] The server uses design tools based on the analysis results to create the initial application design. Here, the placement of functions and interfaces is considered based on user emotions, and a design adapted to those emotions is created.

[0149] Step 6:

[0150] According to the designed specifications, the server-based generation system automatically generates specific application code. This generation process places particular emphasis on emotion-based customization, resulting in programs tailored to the user's needs.

[0151] Step 7:

[0152] A preview of the generated application is sent to the device. The device displays the preview, allowing the user to check the actual application's functionality and provide an evaluation, including emotional satisfaction.

[0153] Step 8:

[0154] Users submit feedback on the preview via their devices. This feedback includes comments on how well the application addresses their emotional needs.

[0155] Step 9:

[0156] The server incorporates feedback and uses redesign tools to modify the application. During this process, it leverages the emotion engine's learning capabilities and uses the collected emotion data to inform future designs.

[0157] Step 10:

[0158] Ultimately, the redesigned application is delivered to the device, allowing users to actually use it and meet their daily needs. Emotion-driven customization provides a more intuitive and user-friendly experience.

[0159] (Example 2)

[0160] 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".

[0161] In modern technology, it is difficult to quickly and automatically generate applications that take into account the individual needs and emotions of users. In particular, systems capable of making adjustments in response to user emotions are limited, and there is a demand for providing personalized experiences that do not rely on templates.

[0162] 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.

[0163] In this invention, the server includes receiving means for acquiring information from the user, extracting means for analyzing the user's requests and emotions from the information, and planning means for designing a program based on the requests and emotions. This enables the rapid and accurate generation of personalized applications for the user, and allows for optimization based on emotions.

[0164] "Receiving means" refers to a device or function that acquires information from a user and initiates a process for using that information within the system.

[0165] "Extraction means" refers to a device or function that analyzes and identifies the user's requests and emotions from the received information.

[0166] "Planning means" refers to a device or function that designs a program based on the requirements and emotions obtained by the extraction means.

[0167] "Forming means" refers to a device or function that automatically creates a program based on planned specifications.

[0168] "Display means" refers to a device or function that visually presents a prototype of the generated program to the user.

[0169] "Collection means" refers to a device or function used to receive user feedback and utilize it for system improvement.

[0170] "Revision means" refers to a device or function that modifies and regenerates a program based on collected feedback.

[0171] This invention is a system that automatically generates customized applications based on user requests and emotions. The system operates around three main entities: the terminal, the server, and the user.

[0172] The terminal provides an interface for receiving information from the user. The user inputs text about the application they need and their circumstances, and sends it from the terminal. This information includes specific feature requests and underlying emotions. This information is encrypted using the SSL / TLS protocol and securely transmitted to the server.

[0173] The server plays a central role in analyzing the received information. The server implements an emotion engine utilizing natural language processing technology to extract both requests and emotions from the user's input text. This analysis uses emotion analysis libraries and natural language processing libraries (e.g., NLTK, TextBlob). Based on these analysis results, the server designs the optimal application for the user. Furthermore, it leverages generative AI models to dynamically generate the application's program code according to the design.

[0174] For example, if a user submits a request stating "I'm too busy to manage things properly," the server extracts emotions such as "dissatisfaction" and "stress" from this request. It then generates an application that reflects these emotions, emphasizing a simple, intuitive design and reminder features.

[0175] Users can view a preview of the application presented from the server through their device and evaluate whether its UI and functionality meet their emotional needs. Furthermore, user feedback is incorporated back into the system and used to further optimize the application. This feedback loop is a crucial means of improving the user experience.

[0176] An example of a prompt message would be something like, "I need an app that can help me manage tasks efficiently when I'm busy. Everything is going wrong and I'm feeling stressed."

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] Users use their devices to input and submit information about their application requirements and personal circumstances. This input includes specific feature requests and emotional statements. This data is encrypted using the SSL / TLS protocol when transmitted from the device, ensuring data privacy and security.

[0180] Step 2:

[0181] The terminal sends the information entered by the user to the server. The server stores the received information for analysis. The input data is received as a string and converted on the server side into a format prepared for the next sentiment analysis step.

[0182] Step 3:

[0183] The server inputs the received text data into the sentiment engine. In this step, a natural language processing engine is used to analyze the requests and emotions from the text. Specifically, sentiment analysis libraries (e.g., NLTK, TextBlob) are used to extract keywords and sentiment scores from the input text. As a result of this process, the user's basic requests and emotions (e.g., stress, dissatisfaction) are output.

[0184] Step 4:

[0185] The server designs the application based on the analyzed requests and emotions. Here, it selects the UI components and functional modules to be used based on the obtained emotion scores. It utilizes a generative AI model to create design guidelines for dynamically structuring the program, and then solidifies the design specifications based on these guidelines.

[0186] Step 5:

[0187] The server generates the application based on the planned design specifications. It automatically generates the specific application programming code using front-end frameworks (e.g., React.js) and back-end technologies. A prototype is created to serve as an indicator to confirm that this generated program meets user needs.

[0188] Step 6:

[0189] The terminal receives a prototype of the application generated by the server and displays a preview to the user. The user uses this preview to evaluate the application's behavior and confirm that its functionality and user experience meet their emotional requirements. This feedback is used in the next improvement cycle.

[0190] Step 7:

[0191] Users submit feedback via their devices, including evaluations and suggestions for improvement based on their experience using the preview. This feedback is sent to the server and considered in the next design cycle. The server re-evaluates the design based on the collected feedback, regenerates the program as needed, and provides a better user experience.

[0192] (Application Example 2)

[0193] 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".

[0194] Traditional content delivery systems struggled to recommend content based on user emotions, failing to provide content best suited to the user's current psychological state. As a result, providing users with personalized experiences was limited.

[0195] 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.

[0196] In this invention, the server includes a receiving device that receives information via a communication network, an analysis device that analyzes the user's emotions from the information, and a selection device that selects content based on the emotions. This makes it possible to recommend content that matches the user's emotions.

[0197] A "communication network" is an infrastructure that connects multiple devices in order to send and receive information.

[0198] "Information" refers to messages and data obtained from users that are subject to processing by the system.

[0199] A "receiving device" refers to equipment or functions used to acquire information via a communication network.

[0200] "Emotions" represent the user's psychological state and are the subject of analysis based on the information.

[0201] An "analysis device" is a device or software used to understand a user's emotions from the information it receives.

[0202] A "selection device" refers to a device or function that determines what to offer based on analyzed emotions.

[0203] "Content" refers to the collective term for information, services, or materials provided to the user.

[0204] A "display device" is a device that has the functionality of hardware and software for visually providing selected content to the user.

[0205] A system for implementing this invention includes a receiving device, an analyzing device, a selection device, and a display device.

[0206] The server receives information from the user's terminal via a communication network. This information includes emotions based on the user's input. The receiving device can encrypt the data for secure handling.

[0207] The received information is processed by an analysis device installed on the server. The analysis device uses natural language processing technology to analyze the user's emotions from their linguistic information. Typical implementations utilize the Python programming language and the Hugging Face Transformers library. This allows the user's psychological state to be classified as "joy," "sadness," "stress," etc.

[0208] Next, based on the analyzed emotions, the selection device determines content appropriate for the user. Using the analysis results, the selection device utilizes APIs from music and video streaming services to obtain the most suitable content for the user. Specific services used in this process include Spotify and Apple Music.

[0209] The decided information is presented to the user's device via a display device. The display device provides the information in a format suitable for devices such as smartphones and tablets.

[0210] As a concrete example, if a user sends emotional information such as "I'm feeling down today," the system will interpret that emotion as "sadness" and recommend a playlist of relaxing music to the user. The prompt input to the generation AI model would be, "I'm feeling a little down today, and I'd like to listen to some relaxing music. Please recommend some songs." Based on this prompt, the system generates a playlist.

[0211] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0212] Step 1:

[0213] The user inputs a message containing emotional information from their device. The input is text data such as "I'm feeling down today." The device encrypts this message and sends it to the server via the communication network. The output is the encrypted message data.

[0214] Step 2:

[0215] The server receives encrypted message data using a receiving device. Next, it decrypts the message to obtain the original text data. The input is the encrypted message data, and the output is the decrypted text data.

[0216] Step 3:

[0217] The server analyzes the user's emotions from the decoded text data using an analysis device. Natural language processing techniques are used to extract emotions such as "sadness" from the input text data. This process utilizes the Hugging Face Transformers library. The input is decoded text data, and the output is data indicating the user's emotions.

[0218] Step 4:

[0219] The server selects the most suitable content for the user based on emotional data analyzed using a selection device. For example, it might use the API of a music streaming service such as Spotify to retrieve a "relaxing music playlist." The input is emotional data, and the output is music content data.

[0220] Step 5:

[0221] The server transmits the selected music content data to the user's terminal via a display device. The terminal displays the received content data with an appropriate user interface and plays the music. The input is the music content data, and the output is the music playlist presented to the user.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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).

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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".

[0238] This invention relates to a system that automatically generates applications tailored to the user's needs. This system consists of a terminal used by the user, an analysis and generation device located on a cloud server, and a function to control the user interface.

[0239] The user uses their usual messaging application to input a message from their device requesting the application they need. The device sends this message to the server and initiates the task. At this point, the communication is encrypted, and the user's information is securely protected.

[0240] On the server, received messages are processed by an analysis tool. The analysis tool uses natural language processing to analyze the user's message and clearly identify the requested functions and elements. Based on these analysis results, the design tool operates to design an application that embodies the user's requirements.

[0241] The designed information is generated as actual application code by a generation mechanism. The necessary program logic and database structure are automatically constructed according to the specified requirements. This code generation is designed to efficiently and flexibly meet user needs.

[0242] The generated application is provided to the user as a preview through a display mechanism. Through this preview, the user can verify the application's basic structure and functionality. For example, in the case of a task management application, the user can check whether adding tasks and displaying lists works correctly.

[0243] Users can provide feedback on the preview via their devices. This feedback is sent to a server by a data acquisition mechanism and analyzed. Based on this, a redesign mechanism revises the process as needed and creates a new design. Through this cycle, users can obtain their ideal application.

[0244] This invention employs a multi-stage intelligent generation process to realize a user-centric process and provides applications optimized to solve specific problems. Furthermore, by flexibly responding to user input, it ensures a high degree of customization to meet individual user needs.

[0245] The following describes the processing flow.

[0246] Step 1:

[0247] Users use LINE's chat interface to enter their needs and requests in message format. For example, by writing a request such as "I want to create a project management app," they can send a request focused on a specific function to the system.

[0248] Step 2:

[0249] The device encrypts the user's input messages and sends them to the cloud server. Appropriate encryption protocols are used throughout this process to maintain data integrity and privacy.

[0250] Step 3:

[0251] The server passes the received message to the parsing mechanism. The parsing mechanism uses a natural language processing algorithm to analyze the user's request and extract the necessary functions and requirements. Here, keywords such as project management and task deadline management are identified.

[0252] Step 4:

[0253] Based on the analysis results, the server begins designing the application using design tools. This involves creating mockups of the user interface and performing hypothetical modeling to design the database structure. Necessary features, such as task addition and deadline setting, are incorporated into the design.

[0254] Step 5:

[0255] After the design is complete, the generation process on the server automatically generates the application code. The source code is constructed to include backend logic, frontend components, database schema, and other elements.

[0256] Step 6:

[0257] A preview of the generated application is sent to the device. The device displays this preview to the user, allowing the user to visually confirm how the system actually works.

[0258] Step 7:

[0259] Users evaluate the application based on the provided preview and send any necessary changes or additional feedback to the server via their device. This allows for optimization based on user preferences.

[0260] Step 8:

[0261] The server analyzes the feedback and redesigns based on the newly extracted requirements. The redesign mechanism then regenerates the application with the new specifications, creating an improved version.

[0262] Step 9:

[0263] The final version of the redesigned application is transferred to the terminal, allowing users to use it in their actual work and daily lives. Through this iterative process, the system provides a customized solution that fully meets the user's needs.

[0264] (Example 1)

[0265] 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."

[0266] There is a growing demand for software that can flexibly respond to diverse user needs and be efficiently, securely, and safely customizable. However, many current software generation systems fail to respond quickly to user requests and lack sufficient customization options for individual requirements. Furthermore, they lack adequate mechanisms for effectively utilizing user feedback during previews.

[0267] 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.

[0268] In this invention, the server includes a communication device that receives requests from users, an analysis device that analyzes the requests and extracts the user's objectives, a design device that designs software based on the objectives, a display device that presents an overview of the software to the user, and a verification device that verifies the operation of the software and optimizes the design content according to the user's requests. This makes it possible to efficiently generate customizable software that can respond immediately to the needs of diverse users, and to optimize the design through user feedback.

[0269] A "communication device" is a device that has the function of receiving requests from users and transmitting them to a server.

[0270] An "analysis device" is a device that analyzes received requests and extracts the user's objectives.

[0271] A "design device" is a device used to design software based on the extracted objectives.

[0272] A "generation device" is a device that automatically generates software using data created by a design device.

[0273] A "display device" is a device that has the function of presenting an overview of the generated software to the user.

[0274] A "verification device" is a device that verifies the operation of software and optimizes its design to meet user requirements.

[0275] A "redesign device" is a device used to redesign and regenerate software based on user feedback.

[0276] "Encryption" is a method of securely protecting data during transmission so that it cannot be read by a third party.

[0277] This invention relates to a system that allows a user to automatically generate software according to their own requirements. This system mainly includes a terminal for inputting user requests, a server that analyzes the requests and generates software, and various devices for verifying and optimizing the generated software.

[0278] Users use their usual messaging applications to input requests for the software they need into their devices. For example, they can use specific prompts such as, "I want an app to keep track of my household finances." The device receives this input and sends it to the server in an encrypted form via a communication device. Security protocols such as SSL / TLS are commonly used for this encryption.

[0279] The server analyzes received requests using natural language processing technology with an analysis device. A generative AI model is used to analyze the context and content of the request, clearly extracting the user's objective. Next, a design device operates based on these analysis results, designing the necessary software structure and functionality. Specifically, this involves database structure design and interface layout design.

[0280] The generation device automatically generates software based on the design. This process comprehensively and automatically generates program logic and data management structures, providing software that adheres faithfully to the designed specifications. The generated software is presented to the user as a preview via a display device, allowing for verification of its operation and functionality. After reviewing the preview and verifying the software's usability, the user can provide feedback through the terminal.

[0281] Feedback from the user is resent to the server, and the verification device analyzes the content. As a result, the redesign device redesigns the software as needed, makes corrections, and then performs new generation. Through this cycle, the user can obtain more ideal and need-matching software.

[0282] This system enables quick response to complex and individualized user needs and improvement of the user experience.

[0283] The flow of the specific process in Example 1 will be described using FIG. 11.

[0284] Step 1:

[0285] The user inputs their request into the terminal using the messaging application. What is input is a prompt sentence such as "I want an app for keeping a household account book." This input is taken into the terminal as text data including the user's desires and hopes for the functions of the application.

[0286] Step 2:

[0287] The terminal sends the received prompt sentence to the server. At this time, the prompt sentence is encrypted using the communication device and sent to the server securely. The input is encrypted text data, and the output is a message securely sent to the server.

[0288] Step 3:

[0289] The server decrypts the received encrypted message and performs natural language processing with the analysis device. Here, the generation AI model is used to extract the user's purpose (e.g., the desire for a revenue and expenditure management function) from the prompt sentence. The input is the decrypted prompt sentence, and the output is the analyzed user purpose data.

[0290] Step 4:

[0291] The server designs software using a design device based on the analysis results. This process involves designing the necessary database structure and user interface. The input is user-targeted data, and the output is software structure data as design information.

[0292] Step 5:

[0293] The server automatically generates software based on data designed using a generation device. Program code is generated, and a functional application is formed. The input is software structure data, and the output is the generated application program.

[0294] Step 6:

[0295] The server provides the generated application to the user as a preview via a display device. The user tries out the provided application and checks its usability and functionality. The input is the application program, and the output is the preview environment that the user actually interacts with.

[0296] Step 7:

[0297] After reviewing the preview, users send feedback to the server via their device. This feedback includes specific comments on usability and additional requests. The input is text data representing the user's opinion, and the output is the feedback message sent to the server.

[0298] Step 8:

[0299] The server analyzes the received feedback and modifies the software as needed using a redesign device. Here, the software is redesigned and generated based on the feedback. The input is the analyzed feedback data, and the output is the modified application program.

[0300] (Application Example 1)

[0301] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0302] There is a lack of means for quickly and efficiently constructing a computer program having functions desired by a user. For this reason, there is a problem that it is difficult to customize a program according to individual needs and it takes time and cost.

[0303] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0304] In this invention, the server includes a transmission means for receiving an instruction from a user, an analysis means for understanding the user's request from the instruction, and a construction means for constructing a computer program based on the request. Thereby, it is possible to quickly respond to individual user needs and automatically generate a customized program.

[0305] The "transmission means" is a device having a communication function for receiving an instruction from a user.

[0306] The "analysis means" is a device having a processing function for understanding the user's request from the received instruction.

[0307] The "construction means" is a device having a design and construction function for creating a computer program based on the user's request.

[0308] The "creation means" is a device having a function of automatically generating a computer program based on the constructed specifications.

[0309] The "provision means" is a device having a function of providing a trial version of the generated computer program to the user.

[0310] A "collection device" is a device with communication capabilities for collecting opinions and feedback from users.

[0311] A "reconstruction tool" is a device that has the function of modifying the design of a computer program based on collected feedback and then regenerating it.

[0312] "Encryption" is the process of transforming data to enhance security during the transmission and reception of information.

[0313] To implement this invention, a terminal for the user to give instructions, a server to receive and process the instructions, and means to provide the generated computer program are required. First, the user uses the terminal to input instructions requesting a specific function or service. These instructions might be, for example, a request for an application that has the function to update new products in a virtual store.

[0314] The terminal securely transmits user instructions to the server. The server uses natural language processing techniques to analyze the received instructions. This analysis utilizes generative AI models such as Google BERT and OpenAI GPT-3, with the aim of clearly understanding what the user wants. After the analysis is complete, the server designs a program in response to the request through a construction tool and generates the actual code through a creation tool.

[0315] The generated computer program is provided to the user as a trial version through a distribution channel. This trial version allows the user to verify whether the generated program's functionality meets their requirements. For example, if the prompt "Create an application that updates new book information daily and issues an alert if it is not updated" is entered, the server will create an application based on this and provide it to the user.

[0316] This system can also obtain feedback from users through collection mechanisms and modify the program through reconstruction mechanisms. For example, if a user requests "stronger notifications when product updates are delayed," the server can reconstruct the application based on that feedback and provide it again.

[0317] In this way, this invention makes it possible to quickly and efficiently generate customizable applications that meet the individual needs of users.

[0318] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0319] Step 1:

[0320] The user uses their device to input application requests in natural language. For example, they might specifically type, "I want an app with a new product update function," into a messaging app. The device encrypts the user's input and securely transmits it to the server.

[0321] Step 2:

[0322] The server decrypts the received encrypted message and receives the input text. Next, it uses a generative AI model (e.g., OpenAI GPT-3) to analyze the text, breaking down and understanding the user's request into specific elements. This analysis extracts keywords such as "new product" and "update function."

[0323] Step 3:

[0324] Based on the analyzed requests, the server begins program design using a generation mechanism. Specifically, the necessary functions (e.g., database updates, notification functions) are designed, and the logical structure of the computer program is defined.

[0325] Step 4:

[0326] The server generates program code using a generation mechanism based on the designed logical structure. The input is design information, and the output is executable program code. This code generation is automated and performed quickly.

[0327] Step 5:

[0328] The generated program is sent to the terminal via a delivery method and provided to the user as a trial version. The user can run the program and verify that it functions as required.

[0329] Step 6:

[0330] Users use the trial version and provide feedback via their device. This feedback, such as "the notification function doesn't work as expected," is sent to the server.

[0331] Step 7:

[0332] The server receives user feedback using collection methods and modifies the program using reconstruction methods. Based on the feedback, the program is redesigned and generated again to create an improved program.

[0333] Step 8:

[0334] The reconstructed program is again sent to the terminal via the delivery method and provided to the user as a trial version. By repeating this cycle, the final program that perfectly matches the user's requirements is generated.

[0335] 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.

[0336] This invention relates to a system that recognizes a user's emotions and automatically generates a customized application based on those emotions. The system includes an emotion engine that analyzes the user's input and emotions, and processing means for optimizing the design and functionality of the generated application.

[0337] Users use a messaging application to input and send requests for applications they need. These requests include not only the message content itself, but also the emotions the user may have. The device securely sends this message to a cloud server. The server analyzes the received message and extracts functional requests from the user's input.

[0338] In this analysis process, the emotion engine plays a particularly important role. The emotion engine installed on the server uses natural language processing technology to read emotions from the user's words. For example, if a user inputs "I'm too busy to manage things properly," the engine recognizes emotions such as "dissatisfaction" and "stress" from that input and determines which functions to prioritize providing in the application.

[0339] Based on user requests and emotions, the emotion engine automatically designs and optimizes the application. This enables design considerations tailored to the user's emotional state and a user-friendly layout of features. For example, users experiencing high stress levels will be given emphasis on simple, intuitive designs and reminder functions.

[0340] The generation mechanism works closely with the emotion engine to provide the user with a preview application optimized for them on their device. Users can review this preview and evaluate how the application functions and whether it meets their emotionally demanding needs. This feedback is also incorporated into the redesign, enabling further optimization based on user emotions.

[0341] This invention enables users to utilize more personalized applications that are tailored to their emotions at any given moment, without being bound by templates. This combination of emotion recognition technology and automatic generation means contributes to improving the user experience and provides effective solutions quickly.

[0342] The following describes the processing flow.

[0343] Step 1:

[0344] Users use messaging applications to input their problems and requests for necessary applications, and send messages through their devices. These inputs may include expressions of the user's emotions.

[0345] Step 2:

[0346] The device receives messages from the user and sends them to the cloud server. During this process, the device encrypts the messages to ensure the user's data remains secure.

[0347] Step 3:

[0348] The server processes received messages using analysis tools. During the analysis process, it utilizes language processing techniques to identify specific functions desired by the user from the message, while simultaneously analyzing the user's emotional state using an emotion engine.

[0349] Step 4:

[0350] The emotion engine analyzes the emotions derived from user messages and correlates them with the results to determine application design priorities. This information is used to select features that recommend stress reduction and designs that enhance joy.

[0351] Step 5:

[0352] The server uses design tools based on the analysis results to create the initial application design. Here, the placement of functions and interfaces is considered based on user emotions, and a design adapted to those emotions is created.

[0353] Step 6:

[0354] According to the designed specifications, the server-based generation system automatically generates specific application code. This generation process places particular emphasis on emotion-based customization, resulting in programs tailored to the user's needs.

[0355] Step 7:

[0356] A preview of the generated application is sent to the device. The device displays the preview, allowing the user to check the actual application's functionality and provide an evaluation, including emotional satisfaction.

[0357] Step 8:

[0358] Users submit feedback on the preview via their devices. This feedback includes comments on how well the application addresses their emotional needs.

[0359] Step 9:

[0360] The server incorporates feedback and uses redesign tools to modify the application. During this process, it leverages the emotion engine's learning capabilities and uses the collected emotion data to inform future designs.

[0361] Step 10:

[0362] Ultimately, the redesigned application is delivered to the device, allowing users to actually use it and meet their daily needs. Emotion-driven customization provides a more intuitive and user-friendly experience.

[0363] (Example 2)

[0364] 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".

[0365] In modern technology, it is difficult to quickly and automatically generate applications that take into account the individual needs and emotions of users. In particular, systems capable of making adjustments in response to user emotions are limited, and there is a demand for providing personalized experiences that do not rely on templates.

[0366] 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.

[0367] In this invention, the server includes receiving means for acquiring information from the user, extracting means for analyzing the user's requests and emotions from the information, and planning means for designing a program based on the requests and emotions. This enables the rapid and accurate generation of personalized applications for the user, and allows for optimization based on emotions.

[0368] "Receiving means" refers to a device or function that acquires information from a user and initiates a process for using that information within the system.

[0369] "Extraction means" refers to a device or function that analyzes and identifies the user's requests and emotions from the received information.

[0370] "Planning means" refers to a device or function that designs a program based on the requirements and emotions obtained by the extraction means.

[0371] "Forming means" refers to a device or function that automatically creates a program based on planned specifications.

[0372] "Display means" refers to a device or function that visually presents a prototype of the generated program to the user.

[0373] "Collection means" refers to a device or function used to receive user feedback and utilize it for system improvement.

[0374] "Revision means" refers to a device or function that modifies and regenerates a program based on collected feedback.

[0375] This invention is a system that automatically generates customized applications based on user requests and emotions. The system operates around three main entities: the terminal, the server, and the user.

[0376] The terminal provides an interface for receiving information from the user. The user inputs text about the application they need and their circumstances, and sends it from the terminal. This information includes specific feature requests and underlying emotions. This information is encrypted using the SSL / TLS protocol and securely transmitted to the server.

[0377] The server plays a central role in analyzing the received information. The server implements an emotion engine utilizing natural language processing technology to extract both requests and emotions from the user's input text. This analysis uses emotion analysis libraries and natural language processing libraries (e.g., NLTK, TextBlob). Based on these analysis results, the server designs the optimal application for the user. Furthermore, it leverages generative AI models to dynamically generate the application's program code according to the design.

[0378] For example, if a user submits a request stating "I'm too busy to manage things properly," the server extracts emotions such as "dissatisfaction" and "stress" from this request. It then generates an application that reflects these emotions, emphasizing a simple, intuitive design and reminder features.

[0379] Users can view a preview of the application presented from the server through their device and evaluate whether its UI and functionality meet their emotional needs. Furthermore, user feedback is incorporated back into the system and used to further optimize the application. This feedback loop is a crucial means of improving the user experience.

[0380] An example of a prompt message would be something like, "I need an app that can help me manage tasks efficiently when I'm busy. Everything is going wrong and I'm feeling stressed."

[0381] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0382] Step 1:

[0383] Users use their devices to input and submit information about their application requirements and personal circumstances. This input includes specific feature requests and emotional statements. This data is encrypted using the SSL / TLS protocol when transmitted from the device, ensuring data privacy and security.

[0384] Step 2:

[0385] The terminal sends the information entered by the user to the server. The server stores the received information for analysis. The input data is received as a string and converted on the server side into a format prepared for the next sentiment analysis step.

[0386] Step 3:

[0387] The server inputs the received text data into the sentiment engine. In this step, a natural language processing engine is used to analyze the requests and emotions from the text. Specifically, sentiment analysis libraries (e.g., NLTK, TextBlob) are used to extract keywords and sentiment scores from the input text. As a result of this process, the user's basic requests and emotions (e.g., stress, dissatisfaction) are output.

[0388] Step 4:

[0389] The server designs the application based on the analyzed requests and emotions. Here, it selects the UI components and functional modules to be used based on the obtained emotion scores. It utilizes a generative AI model to create design guidelines for dynamically structuring the program, and then solidifies the design specifications based on these guidelines.

[0390] Step 5:

[0391] The server generates the application based on the planned design specifications. It automatically generates the specific application programming code using front-end frameworks (e.g., React.js) and back-end technologies. A prototype is created to serve as an indicator to confirm that this generated program meets user needs.

[0392] Step 6:

[0393] The terminal receives a prototype of the application generated by the server and displays a preview to the user. The user uses this preview to evaluate the application's behavior and confirm that its functionality and user experience meet their emotional requirements. This feedback is used in the next improvement cycle.

[0394] Step 7:

[0395] Users submit feedback via their devices, including evaluations and suggestions for improvement based on their experience using the preview. This feedback is sent to the server and considered in the next design cycle. The server re-evaluates the design based on the collected feedback, regenerates the program as needed, and provides a better user experience.

[0396] (Application Example 2)

[0397] 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."

[0398] Traditional content delivery systems struggled to recommend content based on user emotions, failing to provide content best suited to the user's current psychological state. As a result, providing users with personalized experiences was limited.

[0399] 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.

[0400] In this invention, the server includes a receiving device that receives information via a communication network, an analysis device that analyzes the user's emotions from the information, and a selection device that selects content based on the emotions. This makes it possible to recommend content that matches the user's emotions.

[0401] A "communication network" is an infrastructure that connects multiple devices in order to send and receive information.

[0402] "Information" refers to messages and data obtained from users that are subject to processing by the system.

[0403] A "receiving device" refers to equipment or functions used to acquire information via a communication network.

[0404] "Emotions" represent the user's psychological state and are the subject of analysis based on the information.

[0405] An "analysis device" is a device or software used to understand a user's emotions from the information it receives.

[0406] A "selection device" refers to a device or function that determines what to offer based on analyzed emotions.

[0407] "Content" refers to the collective term for information, services, or materials provided to the user.

[0408] A "display device" is a device that has the functionality of hardware and software for visually providing selected content to the user.

[0409] A system for implementing this invention includes a receiving device, an analyzing device, a selection device, and a display device.

[0410] The server receives information from the user's terminal via a communication network. This information includes emotions based on the user's input. The receiving device can encrypt the data for secure handling.

[0411] The received information is processed by an analysis device installed on the server. The analysis device uses natural language processing technology to analyze the user's emotions from their linguistic information. Typical implementations utilize the Python programming language and the Hugging Face Transformers library. This allows the user's psychological state to be classified as "joy," "sadness," "stress," etc.

[0412] Next, based on the analyzed emotions, the selection device determines content appropriate for the user. Using the analysis results, the selection device utilizes APIs from music and video streaming services to obtain the most suitable content for the user. Specific services used in this process include Spotify and Apple Music.

[0413] The decided information is presented to the user's device via a display device. The display device provides the information in a format suitable for devices such as smartphones and tablets.

[0414] As a concrete example, if a user sends emotional information such as "I'm feeling down today," the system will interpret that emotion as "sadness" and recommend a playlist of relaxing music to the user. The prompt input to the generation AI model would be, "I'm feeling a little down today, and I'd like to listen to some relaxing music. Please recommend some songs." Based on this prompt, the system generates a playlist.

[0415] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0416] Step 1:

[0417] The user inputs a message containing emotional information from their device. The input is text data such as "I'm feeling down today." The device encrypts this message and sends it to the server via the communication network. The output is the encrypted message data.

[0418] Step 2:

[0419] The server receives encrypted message data using a receiving device. Next, it decrypts the message to obtain the original text data. The input is the encrypted message data, and the output is the decrypted text data.

[0420] Step 3:

[0421] The server analyzes the user's emotions from the decoded text data using an analysis device. Natural language processing techniques are used to extract emotions such as "sadness" from the input text data. This process utilizes the Hugging Face Transformers library. The input is decoded text data, and the output is data indicating the user's emotions.

[0422] Step 4:

[0423] The server selects the most suitable content for the user based on emotional data analyzed using a selection device. For example, it might use the API of a music streaming service such as Spotify to retrieve a "relaxing music playlist." The input is emotional data, and the output is music content data.

[0424] Step 5:

[0425] The server transmits the selected music content data to the user's terminal via a display device. The terminal displays the received content data with an appropriate user interface and plays the music. The input is the music content data, and the output is the music playlist presented to the user.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] [Third Embodiment]

[0430] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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".

[0442] This invention relates to a system that automatically generates applications tailored to the user's needs. This system consists of a terminal used by the user, an analysis and generation device located on a cloud server, and a function to control the user interface.

[0443] The user uses their usual messaging application to input a message from their device requesting the application they need. The device sends this message to the server and initiates the task. At this point, the communication is encrypted, and the user's information is securely protected.

[0444] On the server, received messages are processed by an analysis tool. The analysis tool uses natural language processing to analyze the user's message and clearly identify the requested functions and elements. Based on these analysis results, the design tool operates to design an application that embodies the user's requirements.

[0445] The designed information is generated as actual application code by a generation mechanism. The necessary program logic and database structure are automatically constructed according to the specified requirements. This code generation is designed to efficiently and flexibly meet user needs.

[0446] The generated application is provided to the user as a preview through a display mechanism. Through this preview, the user can verify the application's basic structure and functionality. For example, in the case of a task management application, the user can check whether adding tasks and displaying lists works correctly.

[0447] Users can provide feedback on the preview via their devices. This feedback is sent to a server by a data acquisition mechanism and analyzed. Based on this, a redesign mechanism revises the process as needed and creates a new design. Through this cycle, users can obtain their ideal application.

[0448] This invention employs a multi-stage intelligent generation process to realize a user-centric process and provides applications optimized to solve specific problems. Furthermore, by flexibly responding to user input, it ensures a high degree of customization to meet individual user needs.

[0449] The following describes the processing flow.

[0450] Step 1:

[0451] Users use LINE's chat interface to enter their needs and requests in message format. For example, by writing a request such as "I want to create a project management app," they can send a request focused on a specific function to the system.

[0452] Step 2:

[0453] The device encrypts the user's input messages and sends them to the cloud server. Appropriate encryption protocols are used throughout this process to maintain data integrity and privacy.

[0454] Step 3:

[0455] The server passes the received message to the parsing mechanism. The parsing mechanism uses a natural language processing algorithm to analyze the user's request and extract the necessary functions and requirements. Here, keywords such as project management and task deadline management are identified.

[0456] Step 4:

[0457] Based on the analysis results, the server begins designing the application using design tools. This involves creating mockups of the user interface and performing hypothetical modeling to design the database structure. Necessary features, such as task addition and deadline setting, are incorporated into the design.

[0458] Step 5:

[0459] After the design is complete, the generation process on the server automatically generates the application code. The source code is constructed to include backend logic, frontend components, database schema, and other elements.

[0460] Step 6:

[0461] A preview of the generated application is sent to the device. The device displays this preview to the user, allowing the user to visually confirm how the system actually works.

[0462] Step 7:

[0463] Users evaluate the application based on the provided preview and send any necessary changes or additional feedback to the server via their device. This allows for optimization based on user preferences.

[0464] Step 8:

[0465] The server analyzes the feedback and redesigns based on the newly extracted requirements. The redesign mechanism then regenerates the application with the new specifications, creating an improved version.

[0466] Step 9:

[0467] The final version of the redesigned application is transferred to the terminal, allowing users to use it in their actual work and daily lives. Through this iterative process, the system provides a customized solution that fully meets the user's needs.

[0468] (Example 1)

[0469] 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."

[0470] There is a growing demand for software that can flexibly respond to diverse user needs and be efficiently, securely, and safely customizable. However, many current software generation systems fail to respond quickly to user requests and lack sufficient customization options for individual requirements. Furthermore, they lack adequate mechanisms for effectively utilizing user feedback during previews.

[0471] 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.

[0472] In this invention, the server includes a communication device that receives requests from users, an analysis device that analyzes the requests and extracts the user's objectives, a design device that designs software based on the objectives, a display device that presents an overview of the software to the user, and a verification device that verifies the operation of the software and optimizes the design content according to the user's requests. This makes it possible to efficiently generate customizable software that can respond immediately to the needs of diverse users, and to optimize the design through user feedback.

[0473] A "communication device" is a device that has the function of receiving requests from users and transmitting them to a server.

[0474] An "analysis device" is a device that analyzes received requests and extracts the user's objectives.

[0475] A "design device" is a device used to design software based on the extracted objectives.

[0476] A "generation device" is a device that automatically generates software using data created by a design device.

[0477] A "display device" is a device that has the function of presenting an overview of the generated software to the user.

[0478] A "verification device" is a device that verifies the operation of software and optimizes its design to meet user requirements.

[0479] A "redesign device" is a device used to redesign and regenerate software based on user feedback.

[0480] "Encryption" is a method of securely protecting data during transmission so that it cannot be read by a third party.

[0481] This invention relates to a system that allows a user to automatically generate software according to their own requirements. This system mainly includes a terminal for inputting user requests, a server that analyzes the requests and generates software, and various devices for verifying and optimizing the generated software.

[0482] Users use their usual messaging applications to input requests for the software they need into their devices. For example, they can use specific prompts such as, "I want an app to keep track of my household finances." The device receives this input and sends it to the server in an encrypted form via a communication device. Security protocols such as SSL / TLS are commonly used for this encryption.

[0483] The server analyzes received requests using natural language processing technology with an analysis device. A generative AI model is used to analyze the context and content of the request, clearly extracting the user's objective. Next, a design device operates based on these analysis results, designing the necessary software structure and functionality. Specifically, this involves database structure design and interface layout design.

[0484] The generation device automatically generates software based on the design. This process comprehensively and automatically generates program logic and data management structures, providing software that adheres faithfully to the designed specifications. The generated software is presented to the user as a preview via a display device, allowing for verification of its operation and functionality. After reviewing the preview and verifying the software's usability, the user can provide feedback through the terminal.

[0485] User feedback is resent to the server, where a verification device analyzes its contents. This allows a redesign device to redesign and modify the software as needed, then generate a new version. Through this cycle, users can obtain software that is more ideal and better suited to their needs.

[0486] This system makes it possible to quickly respond to complex and individualized user needs and improve the user experience.

[0487] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0488] Step 1:

[0489] The user uses a messaging application to input their request into the device. The input is a prompt message such as, "I want an app to keep track of household expenses." This input is captured by the device as text data, including the user's request and desired application features.

[0490] Step 2:

[0491] The terminal sends the received prompt message to the server. During this process, the prompt message is encrypted using a communication device and securely transmitted to the server. The input is encrypted text data, and the output is the message securely sent to the server.

[0492] Step 3:

[0493] The server decrypts the received encrypted message and performs natural language processing using an analysis device. Here, a generative AI model is used to extract the user's objective (e.g., a request for a financial management function) from the prompt text. The input is the decrypted prompt text, and the output is the analyzed user objective data.

[0494] Step 4:

[0495] The server designs software using a design device based on the analysis results. This process involves designing the necessary database structure and user interface. The input is user-targeted data, and the output is software structure data as design information.

[0496] Step 5:

[0497] The server automatically generates software based on data designed using a generation device. Program code is generated, and a functional application is formed. The input is software structure data, and the output is the generated application program.

[0498] Step 6:

[0499] The server provides the generated application to the user as a preview via a display device. The user tries out the provided application and checks its usability and functionality. The input is the application program, and the output is the preview environment that the user actually interacts with.

[0500] Step 7:

[0501] After reviewing the preview, users send feedback to the server via their device. This feedback includes specific comments on usability and additional requests. The input is text data representing the user's opinion, and the output is the feedback message sent to the server.

[0502] Step 8:

[0503] The server analyzes the received feedback and modifies the software as needed using a redesign device. Here, the software is redesigned and generated based on the feedback. The input is the analyzed feedback data, and the output is the modified application program.

[0504] (Application Example 1)

[0505] 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."

[0506] There is a lack of means to quickly and efficiently build computer programs with the functions desired by users. This results in the problem of difficulty and cost in customizing programs to meet individual needs.

[0507] 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.

[0508] In this invention, the server includes a transmission means for receiving instructions from a user, an analysis means for understanding the user's requests from the instructions, and a construction means for constructing a computer program based on the requests. This enables rapid response to individual user needs and automatic generation of customized programs.

[0509] A "transmission means" is a device equipped with communication functions for receiving instructions from a user.

[0510] An "analysis tool" is a device that has a processing function to understand the user's request from the received instructions.

[0511] "Construction means" refers to a device that has design and construction functions for creating computer programs based on user requirements.

[0512] A "creation means" is a device that has the function of automatically generating a computer program based on the established specifications.

[0513] "Provisioning means" refers to a device that has the function of providing a trial version of a generated computer program to a user.

[0514] A "collection device" is a device with communication capabilities for collecting opinions and feedback from users.

[0515] A "reconstruction tool" is a device that has the function of modifying the design of a computer program based on collected feedback and then regenerating it.

[0516] "Encryption" is the process of transforming data to enhance security during the transmission and reception of information.

[0517] To implement this invention, a terminal for the user to give instructions, a server to receive and process the instructions, and means to provide the generated computer program are required. First, the user uses the terminal to input instructions requesting a specific function or service. These instructions might be, for example, a request for an application that has the function to update new products in a virtual store.

[0518] The terminal securely transmits user instructions to the server. The server uses natural language processing techniques to analyze the received instructions. This analysis utilizes generative AI models such as Google BERT and OpenAI GPT-3, with the aim of clearly understanding what the user wants. After the analysis is complete, the server designs a program in response to the request through a construction tool and generates the actual code through a creation tool.

[0519] The generated computer program is provided to the user as a trial version through a distribution channel. This trial version allows the user to verify whether the generated program's functionality meets their requirements. For example, if the prompt "Create an application that updates new book information daily and issues an alert if it is not updated" is entered, the server will create an application based on this and provide it to the user.

[0520] This system can also obtain feedback from users through collection mechanisms and modify the program through reconstruction mechanisms. For example, if a user requests "stronger notifications when product updates are delayed," the server can reconstruct the application based on that feedback and provide it again.

[0521] In this way, this invention makes it possible to quickly and efficiently generate customizable applications that meet the individual needs of users.

[0522] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0523] Step 1:

[0524] The user uses their device to input application requests in natural language. For example, they might specifically type, "I want an app with a new product update function," into a messaging app. The device encrypts the user's input and securely transmits it to the server.

[0525] Step 2:

[0526] The server decrypts the received encrypted message and receives the input text. Next, it uses a generative AI model (e.g., OpenAI GPT-3) to analyze the text, breaking down and understanding the user's request into specific elements. This analysis extracts keywords such as "new product" and "update function."

[0527] Step 3:

[0528] Based on the analyzed requests, the server begins program design using a generation mechanism. Specifically, the necessary functions (e.g., database updates, notification functions) are designed, and the logical structure of the computer program is defined.

[0529] Step 4:

[0530] The server generates program code using a generation mechanism based on the designed logical structure. The input is design information, and the output is executable program code. This code generation is automated and performed quickly.

[0531] Step 5:

[0532] The generated program is sent to the terminal via a delivery method and provided to the user as a trial version. The user can run the program and verify that it functions as required.

[0533] Step 6:

[0534] Users use the trial version and provide feedback via their device. This feedback, such as "the notification function doesn't work as expected," is sent to the server.

[0535] Step 7:

[0536] The server receives user feedback using collection methods and modifies the program using reconstruction methods. Based on the feedback, the program is redesigned and generated again to create an improved program.

[0537] Step 8:

[0538] The reconstructed program is again sent to the terminal via the delivery method and provided to the user as a trial version. By repeating this cycle, the final program that perfectly matches the user's requirements is generated.

[0539] 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.

[0540] This invention relates to a system that recognizes a user's emotions and automatically generates a customized application based on those emotions. The system includes an emotion engine that analyzes the user's input and emotions, and processing means for optimizing the design and functionality of the generated application.

[0541] Users use a messaging application to input and send requests for applications they need. These requests include not only the message content itself, but also the emotions the user may have. The device securely sends this message to a cloud server. The server analyzes the received message and extracts functional requests from the user's input.

[0542] In this analysis process, the emotion engine plays a particularly important role. The emotion engine installed on the server uses natural language processing technology to read emotions from the user's words. For example, if a user inputs "I'm too busy to manage things properly," the engine recognizes emotions such as "dissatisfaction" and "stress" from that input and determines which functions to prioritize providing in the application.

[0543] Based on user requests and emotions, the emotion engine automatically designs and optimizes the application. This enables design considerations tailored to the user's emotional state and a user-friendly layout of features. For example, users experiencing high stress levels will be given emphasis on simple, intuitive designs and reminder functions.

[0544] The generation mechanism works closely with the emotion engine to provide the user with a preview application optimized for them on their device. Users can review this preview and evaluate how the application functions and whether it meets their emotionally demanding needs. This feedback is also incorporated into the redesign, enabling further optimization based on user emotions.

[0545] This invention enables users to utilize more personalized applications that are tailored to their emotions at any given moment, without being bound by templates. This combination of emotion recognition technology and automatic generation means contributes to improving the user experience and provides effective solutions quickly.

[0546] The following describes the processing flow.

[0547] Step 1:

[0548] Users use messaging applications to input their problems and requests for necessary applications, and send messages through their devices. These inputs may include expressions of the user's emotions.

[0549] Step 2:

[0550] The device receives messages from the user and sends them to the cloud server. During this process, the device encrypts the messages to ensure the user's data remains secure.

[0551] Step 3:

[0552] The server processes received messages using analysis tools. During the analysis process, it utilizes language processing techniques to identify specific functions desired by the user from the message, while simultaneously analyzing the user's emotional state using an emotion engine.

[0553] Step 4:

[0554] The emotion engine analyzes the emotions derived from user messages and correlates them with the results to determine application design priorities. This information is used to select features that recommend stress reduction and designs that enhance joy.

[0555] Step 5:

[0556] The server uses design tools based on the analysis results to create the initial application design. Here, the placement of functions and interfaces is considered based on user emotions, and a design adapted to those emotions is created.

[0557] Step 6:

[0558] According to the designed specifications, the server-based generation system automatically generates specific application code. This generation process places particular emphasis on emotion-based customization, resulting in programs tailored to the user's needs.

[0559] Step 7:

[0560] A preview of the generated application is sent to the device. The device displays the preview, allowing the user to check the actual application's functionality and provide an evaluation, including emotional satisfaction.

[0561] Step 8:

[0562] Users submit feedback on the preview via their devices. This feedback includes comments on how well the application addresses their emotional needs.

[0563] Step 9:

[0564] The server incorporates feedback and uses redesign tools to modify the application. During this process, it leverages the emotion engine's learning capabilities and uses the collected emotion data to inform future designs.

[0565] Step 10:

[0566] Ultimately, the redesigned application is delivered to the device, allowing users to actually use it and meet their daily needs. Emotion-driven customization provides a more intuitive and user-friendly experience.

[0567] (Example 2)

[0568] 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."

[0569] In modern technology, it is difficult to quickly and automatically generate applications that take into account the individual needs and emotions of users. In particular, systems capable of making adjustments in response to user emotions are limited, and there is a demand for providing personalized experiences that do not rely on templates.

[0570] 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.

[0571] In this invention, the server includes receiving means for acquiring information from the user, extracting means for analyzing the user's requests and emotions from the information, and planning means for designing a program based on the requests and emotions. This enables the rapid and accurate generation of personalized applications for the user, and allows for optimization based on emotions.

[0572] "Receiving means" refers to a device or function that acquires information from a user and initiates a process for using that information within the system.

[0573] "Extraction means" refers to a device or function that analyzes and identifies the user's requests and emotions from the received information.

[0574] "Planning means" refers to a device or function that designs a program based on the requirements and emotions obtained by the extraction means.

[0575] "Forming means" refers to a device or function that automatically creates a program based on planned specifications.

[0576] "Display means" refers to a device or function that visually presents a prototype of the generated program to the user.

[0577] "Collection means" refers to a device or function used to receive user feedback and utilize it for system improvement.

[0578] "Revision means" refers to a device or function that modifies and regenerates a program based on collected feedback.

[0579] This invention is a system that automatically generates customized applications based on user requests and emotions. The system operates around three main entities: the terminal, the server, and the user.

[0580] The terminal provides an interface for receiving information from the user. The user inputs text about the application they need and their circumstances, and sends it from the terminal. This information includes specific feature requests and underlying emotions. This information is encrypted using the SSL / TLS protocol and securely transmitted to the server.

[0581] The server plays a central role in analyzing the received information. The server implements an emotion engine utilizing natural language processing technology to extract both requests and emotions from the user's input text. This analysis uses emotion analysis libraries and natural language processing libraries (e.g., NLTK, TextBlob). Based on these analysis results, the server designs the optimal application for the user. Furthermore, it leverages generative AI models to dynamically generate the application's program code according to the design.

[0582] For example, if a user submits a request stating "I'm too busy to manage things properly," the server extracts emotions such as "dissatisfaction" and "stress" from this request. It then generates an application that reflects these emotions, emphasizing a simple, intuitive design and reminder features.

[0583] Users can view a preview of the application presented from the server through their device and evaluate whether its UI and functionality meet their emotional needs. Furthermore, user feedback is incorporated back into the system and used to further optimize the application. This feedback loop is a crucial means of improving the user experience.

[0584] An example of a prompt message would be something like, "I need an app that can help me manage tasks efficiently when I'm busy. Everything is going wrong and I'm feeling stressed."

[0585] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0586] Step 1:

[0587] Users use their devices to input and submit information about their application requirements and personal circumstances. This input includes specific feature requests and emotional statements. This data is encrypted using the SSL / TLS protocol when transmitted from the device, ensuring data privacy and security.

[0588] Step 2:

[0589] The terminal sends the information entered by the user to the server. The server stores the received information for analysis. The input data is received as a string and converted on the server side into a format prepared for the next sentiment analysis step.

[0590] Step 3:

[0591] The server inputs the received text data into the sentiment engine. In this step, a natural language processing engine is used to analyze the requests and emotions from the text. Specifically, sentiment analysis libraries (e.g., NLTK, TextBlob) are used to extract keywords and sentiment scores from the input text. As a result of this process, the user's basic requests and emotions (e.g., stress, dissatisfaction) are output.

[0592] Step 4:

[0593] The server designs the application based on the analyzed requests and emotions. Here, it selects the UI components and functional modules to be used based on the obtained emotion scores. It utilizes a generative AI model to create design guidelines for dynamically structuring the program, and then solidifies the design specifications based on these guidelines.

[0594] Step 5:

[0595] The server generates the application based on the planned design specifications. It automatically generates the specific application programming code using front-end frameworks (e.g., React.js) and back-end technologies. A prototype is created to serve as an indicator to confirm that this generated program meets user needs.

[0596] Step 6:

[0597] The terminal receives a prototype of the application generated by the server and displays a preview to the user. The user uses this preview to evaluate the application's behavior and confirm that its functionality and user experience meet their emotional requirements. This feedback is used in the next improvement cycle.

[0598] Step 7:

[0599] Users submit feedback via their devices, including evaluations and suggestions for improvement based on their experience using the preview. This feedback is sent to the server and considered in the next design cycle. The server re-evaluates the design based on the collected feedback, regenerates the program as needed, and provides a better user experience.

[0600] (Application Example 2)

[0601] 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."

[0602] Traditional content delivery systems struggled to recommend content based on user emotions, failing to provide content best suited to the user's current psychological state. As a result, providing users with personalized experiences was limited.

[0603] 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.

[0604] In this invention, the server includes a receiving device that receives information via a communication network, an analysis device that analyzes the user's emotions from the information, and a selection device that selects content based on the emotions. This makes it possible to recommend content that matches the user's emotions.

[0605] A "communication network" is an infrastructure that connects multiple devices in order to send and receive information.

[0606] "Information" refers to messages and data obtained from users that are subject to processing by the system.

[0607] A "receiving device" refers to equipment or functions used to acquire information via a communication network.

[0608] "Emotions" represent the user's psychological state and are the subject of analysis based on the information.

[0609] An "analysis device" is a device or software used to understand a user's emotions from the information it receives.

[0610] A "selection device" refers to a device or function that determines what to offer based on analyzed emotions.

[0611] "Content" refers to the collective term for information, services, or materials provided to the user.

[0612] A "display device" is a device that has the functionality of hardware and software for visually providing selected content to the user.

[0613] A system for implementing this invention includes a receiving device, an analyzing device, a selection device, and a display device.

[0614] The server receives information from the user's terminal via a communication network. This information includes emotions based on the user's input. The receiving device can encrypt the data for secure handling.

[0615] The received information is processed by an analysis device installed on the server. The analysis device uses natural language processing technology to analyze the user's emotions from their linguistic information. Typical implementations utilize the Python programming language and the Hugging Face Transformers library. This allows the user's psychological state to be classified as "joy," "sadness," "stress," etc.

[0616] Next, based on the analyzed emotions, the selection device determines content appropriate for the user. Using the analysis results, the selection device utilizes APIs from music and video streaming services to obtain the most suitable content for the user. Specific services used in this process include Spotify and Apple Music.

[0617] The decided information is presented to the user's device via a display device. The display device provides the information in a format suitable for devices such as smartphones and tablets.

[0618] As a concrete example, if a user sends emotional information such as "I'm feeling down today," the system will interpret that emotion as "sadness" and recommend a playlist of relaxing music to the user. The prompt input to the generation AI model would be, "I'm feeling a little down today, and I'd like to listen to some relaxing music. Please recommend some songs." Based on this prompt, the system generates a playlist.

[0619] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0620] Step 1:

[0621] The user inputs a message containing emotional information from their device. The input is text data such as "I'm feeling down today." The device encrypts this message and sends it to the server via the communication network. The output is the encrypted message data.

[0622] Step 2:

[0623] The server receives encrypted message data using a receiving device. Next, it decrypts the message to obtain the original text data. The input is the encrypted message data, and the output is the decrypted text data.

[0624] Step 3:

[0625] The server analyzes the user's emotions from the decoded text data using an analysis device. Natural language processing techniques are used to extract emotions such as "sadness" from the input text data. This process utilizes the Hugging Face Transformers library. The input is decoded text data, and the output is data indicating the user's emotions.

[0626] Step 4:

[0627] The server selects the most suitable content for the user based on emotional data analyzed using a selection device. For example, it might use the API of a music streaming service such as Spotify to retrieve a "relaxing music playlist." The input is emotional data, and the output is music content data.

[0628] Step 5:

[0629] The server transmits the selected music content data to the user's terminal via a display device. The terminal displays the received content data with an appropriate user interface and plays the music. The input is the music content data, and the output is the music playlist presented to the user.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] [Fourth Embodiment]

[0634] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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).

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] 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".

[0647] This invention relates to a system that automatically generates applications tailored to the user's needs. This system consists of a terminal used by the user, an analysis and generation device located on a cloud server, and a function to control the user interface.

[0648] The user uses their usual messaging application to input a message from their device requesting the application they need. The device sends this message to the server and initiates the task. At this point, the communication is encrypted, and the user's information is securely protected.

[0649] On the server, received messages are processed by an analysis tool. The analysis tool uses natural language processing to analyze the user's message and clearly identify the requested functions and elements. Based on these analysis results, the design tool operates to design an application that embodies the user's requirements.

[0650] The designed information is generated as actual application code by a generation mechanism. The necessary program logic and database structure are automatically constructed according to the specified requirements. This code generation is designed to efficiently and flexibly meet user needs.

[0651] The generated application is provided to the user as a preview through a display mechanism. Through this preview, the user can verify the application's basic structure and functionality. For example, in the case of a task management application, the user can check whether adding tasks and displaying lists works correctly.

[0652] Users can provide feedback on the preview via their devices. This feedback is sent to a server by a data acquisition mechanism and analyzed. Based on this, a redesign mechanism revises the process as needed and creates a new design. Through this cycle, users can obtain their ideal application.

[0653] This invention employs a multi-stage intelligent generation process to realize a user-centric process and provides applications optimized to solve specific problems. Furthermore, by flexibly responding to user input, it ensures a high degree of customization to meet individual user needs.

[0654] The following describes the processing flow.

[0655] Step 1:

[0656] Users use LINE's chat interface to enter their needs and requests in message format. For example, by writing a request such as "I want to create a project management app," they can send a request focused on a specific function to the system.

[0657] Step 2:

[0658] The device encrypts the user's input messages and sends them to the cloud server. Appropriate encryption protocols are used throughout this process to maintain data integrity and privacy.

[0659] Step 3:

[0660] The server passes the received message to the parsing mechanism. The parsing mechanism uses a natural language processing algorithm to analyze the user's request and extract the necessary functions and requirements. Here, keywords such as project management and task deadline management are identified.

[0661] Step 4:

[0662] Based on the analysis results, the server begins designing the application using design tools. This involves creating mockups of the user interface and performing hypothetical modeling to design the database structure. Necessary features, such as task addition and deadline setting, are incorporated into the design.

[0663] Step 5:

[0664] After the design is complete, the generation process on the server automatically generates the application code. The source code is constructed to include backend logic, frontend components, database schema, and other elements.

[0665] Step 6:

[0666] A preview of the generated application is sent to the device. The device displays this preview to the user, allowing the user to visually confirm how the system actually works.

[0667] Step 7:

[0668] Users evaluate the application based on the provided preview and send any necessary changes or additional feedback to the server via their device. This allows for optimization based on user preferences.

[0669] Step 8:

[0670] The server analyzes the feedback and redesigns based on the newly extracted requirements. The redesign mechanism then regenerates the application with the new specifications, creating an improved version.

[0671] Step 9:

[0672] The final version of the redesigned application is transferred to the terminal, allowing users to use it in their actual work and daily lives. Through this iterative process, the system provides a customized solution that fully meets the user's needs.

[0673] (Example 1)

[0674] 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".

[0675] There is a growing demand for software that can flexibly respond to diverse user needs and be efficiently, securely, and safely customizable. However, many current software generation systems fail to respond quickly to user requests and lack sufficient customization options for individual requirements. Furthermore, they lack adequate mechanisms for effectively utilizing user feedback during previews.

[0676] 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.

[0677] In this invention, the server includes a communication device that receives requests from users, an analysis device that analyzes the requests and extracts the user's objectives, a design device that designs software based on the objectives, a display device that presents an overview of the software to the user, and a verification device that verifies the operation of the software and optimizes the design content according to the user's requests. This makes it possible to efficiently generate customizable software that can respond immediately to the needs of diverse users, and to optimize the design through user feedback.

[0678] A "communication device" is a device that has the function of receiving requests from users and transmitting them to a server.

[0679] An "analysis device" is a device that analyzes received requests and extracts the user's objectives.

[0680] A "design device" is a device used to design software based on the extracted objectives.

[0681] A "generation device" is a device that automatically generates software using data created by a design device.

[0682] A "display device" is a device that has the function of presenting an overview of the generated software to the user.

[0683] A "verification device" is a device that verifies the operation of software and optimizes its design to meet user requirements.

[0684] A "redesign device" is a device used to redesign and regenerate software based on user feedback.

[0685] "Encryption" is a method of securely protecting data during transmission so that it cannot be read by a third party.

[0686] This invention relates to a system that allows a user to automatically generate software according to their own requirements. This system mainly includes a terminal for inputting user requests, a server that analyzes the requests and generates software, and various devices for verifying and optimizing the generated software.

[0687] Users use their usual messaging applications to input requests for the software they need into their devices. For example, they can use specific prompts such as, "I want an app to keep track of my household finances." The device receives this input and sends it to the server in an encrypted form via a communication device. Security protocols such as SSL / TLS are commonly used for this encryption.

[0688] The server analyzes received requests using natural language processing technology with an analysis device. A generative AI model is used to analyze the context and content of the request, clearly extracting the user's objective. Next, a design device operates based on these analysis results, designing the necessary software structure and functionality. Specifically, this involves database structure design and interface layout design.

[0689] The generation device automatically generates software based on the design. This process comprehensively and automatically generates program logic and data management structures, providing software that adheres faithfully to the designed specifications. The generated software is presented to the user as a preview via a display device, allowing for verification of its operation and functionality. After reviewing the preview and verifying the software's usability, the user can provide feedback through the terminal.

[0690] User feedback is resent to the server, where a verification device analyzes its contents. This allows a redesign device to redesign and modify the software as needed, then generate a new version. Through this cycle, users can obtain software that is more ideal and better suited to their needs.

[0691] This system makes it possible to quickly respond to complex and individualized user needs and improve the user experience.

[0692] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0693] Step 1:

[0694] The user uses a messaging application to input their request into the device. The input is a prompt message such as, "I want an app to keep track of household expenses." This input is captured by the device as text data, including the user's request and desired application features.

[0695] Step 2:

[0696] The terminal sends the received prompt message to the server. During this process, the prompt message is encrypted using a communication device and securely transmitted to the server. The input is encrypted text data, and the output is the message securely sent to the server.

[0697] Step 3:

[0698] The server decrypts the received encrypted message and performs natural language processing using an analysis device. Here, a generative AI model is used to extract the user's objective (e.g., a request for a financial management function) from the prompt text. The input is the decrypted prompt text, and the output is the analyzed user objective data.

[0699] Step 4:

[0700] The server designs software using a design device based on the analysis results. This process involves designing the necessary database structure and user interface. The input is user-targeted data, and the output is software structure data as design information.

[0701] Step 5:

[0702] The server automatically generates software based on data designed using a generation device. Program code is generated, and a functional application is formed. The input is software structure data, and the output is the generated application program.

[0703] Step 6:

[0704] The server provides the generated application to the user as a preview via a display device. The user tries out the provided application and checks its usability and functionality. The input is the application program, and the output is the preview environment that the user actually interacts with.

[0705] Step 7:

[0706] After reviewing the preview, users send feedback to the server via their device. This feedback includes specific comments on usability and additional requests. The input is text data representing the user's opinion, and the output is the feedback message sent to the server.

[0707] Step 8:

[0708] The server analyzes the received feedback and modifies the software as needed using a redesign device. Here, the software is redesigned and generated based on the feedback. The input is the analyzed feedback data, and the output is the modified application program.

[0709] (Application Example 1)

[0710] 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".

[0711] There is a lack of means to quickly and efficiently build computer programs with the functions desired by users. This results in the problem of difficulty and cost in customizing programs to meet individual needs.

[0712] 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.

[0713] In this invention, the server includes a transmission means for receiving instructions from a user, an analysis means for understanding the user's requests from the instructions, and a construction means for constructing a computer program based on the requests. This enables rapid response to individual user needs and automatic generation of customized programs.

[0714] A "transmission means" is a device equipped with communication functions for receiving instructions from a user.

[0715] An "analysis tool" is a device that has a processing function to understand the user's request from the received instructions.

[0716] "Construction means" refers to a device that has design and construction functions for creating computer programs based on user requirements.

[0717] A "creation means" is a device that has the function of automatically generating a computer program based on the established specifications.

[0718] "Provisioning means" refers to a device that has the function of providing a trial version of a generated computer program to a user.

[0719] A "collection device" is a device with communication capabilities for collecting opinions and feedback from users.

[0720] A "reconstruction tool" is a device that has the function of modifying the design of a computer program based on collected feedback and then regenerating it.

[0721] "Encryption" is the process of transforming data to enhance security during the transmission and reception of information.

[0722] To implement this invention, a terminal for the user to give instructions, a server to receive and process the instructions, and means to provide the generated computer program are required. First, the user uses the terminal to input instructions requesting a specific function or service. These instructions might be, for example, a request for an application that has the function to update new products in a virtual store.

[0723] The terminal securely transmits user instructions to the server. The server uses natural language processing techniques to analyze the received instructions. This analysis utilizes generative AI models such as Google BERT and OpenAI GPT-3, with the aim of clearly understanding what the user wants. After the analysis is complete, the server designs a program in response to the request through a construction tool and generates the actual code through a creation tool.

[0724] The generated computer program is provided to the user as a trial version through a distribution channel. This trial version allows the user to verify whether the generated program's functionality meets their requirements. For example, if the prompt "Create an application that updates new book information daily and issues an alert if it is not updated" is entered, the server will create an application based on this and provide it to the user.

[0725] This system can also obtain feedback from users through collection mechanisms and modify the program through reconstruction mechanisms. For example, if a user requests "stronger notifications when product updates are delayed," the server can reconstruct the application based on that feedback and provide it again.

[0726] In this way, this invention makes it possible to quickly and efficiently generate customizable applications that meet the individual needs of users.

[0727] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0728] Step 1:

[0729] The user uses their device to input application requests in natural language. For example, they might specifically type, "I want an app with a new product update function," into a messaging app. The device encrypts the user's input and securely transmits it to the server.

[0730] Step 2:

[0731] The server decrypts the received encrypted message and receives the input text. Next, it uses a generative AI model (e.g., OpenAI GPT-3) to analyze the text, breaking down and understanding the user's request into specific elements. This analysis extracts keywords such as "new product" and "update function."

[0732] Step 3:

[0733] Based on the analyzed requests, the server begins program design using a generation mechanism. Specifically, the necessary functions (e.g., database updates, notification functions) are designed, and the logical structure of the computer program is defined.

[0734] Step 4:

[0735] The server generates program code using a generation mechanism based on the designed logical structure. The input is design information, and the output is executable program code. This code generation is automated and performed quickly.

[0736] Step 5:

[0737] The generated program is sent to the terminal via a delivery method and provided to the user as a trial version. The user can run the program and verify that it functions as required.

[0738] Step 6:

[0739] Users use the trial version and provide feedback via their device. This feedback, such as "the notification function doesn't work as expected," is sent to the server.

[0740] Step 7:

[0741] The server receives user feedback using collection methods and modifies the program using reconstruction methods. Based on the feedback, the program is redesigned and generated again to create an improved program.

[0742] Step 8:

[0743] The reconstructed program is again sent to the terminal via the delivery method and provided to the user as a trial version. By repeating this cycle, the final program that perfectly matches the user's requirements is generated.

[0744] 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.

[0745] This invention relates to a system that recognizes a user's emotions and automatically generates a customized application based on those emotions. The system includes an emotion engine that analyzes the user's input and emotions, and processing means for optimizing the design and functionality of the generated application.

[0746] Users use a messaging application to input and send requests for applications they need. These requests include not only the message content itself, but also the emotions the user may have. The device securely sends this message to a cloud server. The server analyzes the received message and extracts functional requests from the user's input.

[0747] In this analysis process, the emotion engine plays a particularly important role. The emotion engine installed on the server uses natural language processing technology to read emotions from the user's words. For example, if a user inputs "I'm too busy to manage things properly," the engine recognizes emotions such as "dissatisfaction" and "stress" from that input and determines which functions to prioritize providing in the application.

[0748] Based on user requests and emotions, the emotion engine automatically designs and optimizes the application. This enables design considerations tailored to the user's emotional state and a user-friendly layout of features. For example, users experiencing high stress levels will be given emphasis on simple, intuitive designs and reminder functions.

[0749] The generation mechanism works closely with the emotion engine to provide the user with a preview application optimized for them on their device. Users can review this preview and evaluate how the application functions and whether it meets their emotionally demanding needs. This feedback is also incorporated into the redesign, enabling further optimization based on user emotions.

[0750] This invention enables users to utilize more personalized applications that are tailored to their emotions at any given moment, without being bound by templates. This combination of emotion recognition technology and automatic generation means contributes to improving the user experience and provides effective solutions quickly.

[0751] The following describes the processing flow.

[0752] Step 1:

[0753] Users use messaging applications to input their problems and requests for necessary applications, and send messages through their devices. These inputs may include expressions of the user's emotions.

[0754] Step 2:

[0755] The device receives messages from the user and sends them to the cloud server. During this process, the device encrypts the messages to ensure the user's data remains secure.

[0756] Step 3:

[0757] The server processes received messages using analysis tools. During the analysis process, it utilizes language processing techniques to identify specific functions desired by the user from the message, while simultaneously analyzing the user's emotional state using an emotion engine.

[0758] Step 4:

[0759] The emotion engine analyzes the emotions derived from user messages and correlates them with the results to determine application design priorities. This information is used to select features that recommend stress reduction and designs that enhance joy.

[0760] Step 5:

[0761] The server uses design tools based on the analysis results to create the initial application design. Here, the placement of functions and interfaces is considered based on user emotions, and a design adapted to those emotions is created.

[0762] Step 6:

[0763] According to the designed specifications, the server-based generation system automatically generates specific application code. This generation process places particular emphasis on emotion-based customization, resulting in programs tailored to the user's needs.

[0764] Step 7:

[0765] A preview of the generated application is sent to the device. The device displays the preview, allowing the user to check the actual application's functionality and provide an evaluation, including emotional satisfaction.

[0766] Step 8:

[0767] Users submit feedback on the preview via their devices. This feedback includes comments on how well the application addresses their emotional needs.

[0768] Step 9:

[0769] The server incorporates feedback and uses redesign tools to modify the application. During this process, it leverages the emotion engine's learning capabilities and uses the collected emotion data to inform future designs.

[0770] Step 10:

[0771] Ultimately, the redesigned application is delivered to the device, allowing users to actually use it and meet their daily needs. Emotion-driven customization provides a more intuitive and user-friendly experience.

[0772] (Example 2)

[0773] 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".

[0774] In modern technology, it is difficult to quickly and automatically generate applications that take into account the individual needs and emotions of users. In particular, systems capable of making adjustments in response to user emotions are limited, and there is a demand for providing personalized experiences that do not rely on templates.

[0775] 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.

[0776] In this invention, the server includes receiving means for acquiring information from the user, extracting means for analyzing the user's requests and emotions from the information, and planning means for designing a program based on the requests and emotions. This enables the rapid and accurate generation of personalized applications for the user, and allows for optimization based on emotions.

[0777] "Receiving means" refers to a device or function that acquires information from a user and initiates a process for using that information within the system.

[0778] "Extraction means" refers to a device or function that analyzes and identifies the user's requests and emotions from the received information.

[0779] "Planning means" refers to a device or function that designs a program based on the requirements and emotions obtained by the extraction means.

[0780] "Forming means" refers to a device or function that automatically creates a program based on planned specifications.

[0781] "Display means" refers to a device or function that visually presents a prototype of the generated program to the user.

[0782] "Collection means" refers to a device or function used to receive user feedback and utilize it for system improvement.

[0783] "Revision means" refers to a device or function that modifies and regenerates a program based on collected feedback.

[0784] This invention is a system that automatically generates customized applications based on user requests and emotions. The system operates around three main entities: the terminal, the server, and the user.

[0785] The terminal provides an interface for receiving information from the user. The user inputs text about the application they need and their circumstances, and sends it from the terminal. This information includes specific feature requests and underlying emotions. This information is encrypted using the SSL / TLS protocol and securely transmitted to the server.

[0786] The server plays a central role in analyzing the received information. The server implements an emotion engine utilizing natural language processing technology to extract both requests and emotions from the user's input text. This analysis uses emotion analysis libraries and natural language processing libraries (e.g., NLTK, TextBlob). Based on these analysis results, the server designs the optimal application for the user. Furthermore, it leverages generative AI models to dynamically generate the application's program code according to the design.

[0787] For example, if a user submits a request stating "I'm too busy to manage things properly," the server extracts emotions such as "dissatisfaction" and "stress" from this request. It then generates an application that reflects these emotions, emphasizing a simple, intuitive design and reminder features.

[0788] Users can view a preview of the application presented from the server through their device and evaluate whether its UI and functionality meet their emotional needs. Furthermore, user feedback is incorporated back into the system and used to further optimize the application. This feedback loop is a crucial means of improving the user experience.

[0789] An example of a prompt message would be something like, "I need an app that can help me manage tasks efficiently when I'm busy. Everything is going wrong and I'm feeling stressed."

[0790] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0791] Step 1:

[0792] Users use their devices to input and submit information about their application requirements and personal circumstances. This input includes specific feature requests and emotional statements. This data is encrypted using the SSL / TLS protocol when transmitted from the device, ensuring data privacy and security.

[0793] Step 2:

[0794] The terminal sends the information entered by the user to the server. The server stores the received information for analysis. The input data is received as a string and converted on the server side into a format prepared for the next sentiment analysis step.

[0795] Step 3:

[0796] The server inputs the received text data into the sentiment engine. In this step, a natural language processing engine is used to analyze the requests and emotions from the text. Specifically, sentiment analysis libraries (e.g., NLTK, TextBlob) are used to extract keywords and sentiment scores from the input text. As a result of this process, the user's basic requests and emotions (e.g., stress, dissatisfaction) are output.

[0797] Step 4:

[0798] The server designs the application based on the analyzed requests and emotions. Here, it selects the UI components and functional modules to be used based on the obtained emotion scores. It utilizes a generative AI model to create design guidelines for dynamically structuring the program, and then solidifies the design specifications based on these guidelines.

[0799] Step 5:

[0800] The server generates the application based on the planned design specifications. It automatically generates the specific application programming code using front-end frameworks (e.g., React.js) and back-end technologies. A prototype is created to serve as an indicator to confirm that this generated program meets user needs.

[0801] Step 6:

[0802] The terminal receives a prototype of the application generated by the server and displays a preview to the user. The user uses this preview to evaluate the application's behavior and confirm that its functionality and user experience meet their emotional requirements. This feedback is used in the next improvement cycle.

[0803] Step 7:

[0804] Users submit feedback via their devices, including evaluations and suggestions for improvement based on their experience using the preview. This feedback is sent to the server and considered in the next design cycle. The server re-evaluates the design based on the collected feedback, regenerates the program as needed, and provides a better user experience.

[0805] (Application Example 2)

[0806] 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".

[0807] Traditional content delivery systems struggled to recommend content based on user emotions, failing to provide content best suited to the user's current psychological state. As a result, providing users with personalized experiences was limited.

[0808] 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.

[0809] In this invention, the server includes a receiving device that receives information via a communication network, an analysis device that analyzes the user's emotions from the information, and a selection device that selects content based on the emotions. This makes it possible to recommend content that matches the user's emotions.

[0810] A "communication network" is an infrastructure that connects multiple devices in order to send and receive information.

[0811] "Information" refers to messages and data obtained from users that are subject to processing by the system.

[0812] A "receiving device" refers to equipment or functions used to acquire information via a communication network.

[0813] "Emotions" represent the user's psychological state and are the subject of analysis based on the information.

[0814] An "analysis device" is a device or software used to understand a user's emotions from the information it receives.

[0815] A "selection device" refers to a device or function that determines what to offer based on analyzed emotions.

[0816] "Content" refers to the collective term for information, services, or materials provided to the user.

[0817] A "display device" is a device that has the functionality of hardware and software for visually providing selected content to the user.

[0818] A system for implementing this invention includes a receiving device, an analyzing device, a selection device, and a display device.

[0819] The server receives information from the user's terminal via a communication network. This information includes emotions based on the user's input. The receiving device can encrypt the data for secure handling.

[0820] The received information is processed by an analysis device installed on the server. The analysis device uses natural language processing technology to analyze the user's emotions from their linguistic information. Typical implementations utilize the Python programming language and the Hugging Face Transformers library. This allows the user's psychological state to be classified as "joy," "sadness," "stress," etc.

[0821] Next, based on the analyzed emotions, the selection device determines content appropriate for the user. Using the analysis results, the selection device utilizes APIs from music and video streaming services to obtain the most suitable content for the user. Specific services used in this process include Spotify and Apple Music.

[0822] The decided information is presented to the user's device via a display device. The display device provides the information in a format suitable for devices such as smartphones and tablets.

[0823] As a concrete example, if a user sends emotional information such as "I'm feeling down today," the system will interpret that emotion as "sadness" and recommend a playlist of relaxing music to the user. The prompt input to the generation AI model would be, "I'm feeling a little down today, and I'd like to listen to some relaxing music. Please recommend some songs." Based on this prompt, the system generates a playlist.

[0824] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0825] Step 1:

[0826] The user inputs a message containing emotional information from their device. The input is text data such as "I'm feeling down today." The device encrypts this message and sends it to the server via the communication network. The output is the encrypted message data.

[0827] Step 2:

[0828] The server receives encrypted message data using a receiving device. Next, it decrypts the message to obtain the original text data. The input is the encrypted message data, and the output is the decrypted text data.

[0829] Step 3:

[0830] The server analyzes the user's emotions from the decoded text data using an analysis device. Natural language processing techniques are used to extract emotions such as "sadness" from the input text data. This process utilizes the Hugging Face Transformers library. The input is decoded text data, and the output is data indicating the user's emotions.

[0831] Step 4:

[0832] The server selects the most suitable content for the user based on emotional data analyzed using a selection device. For example, it might use the API of a music streaming service such as Spotify to retrieve a "relaxing music playlist." The input is emotional data, and the output is music content data.

[0833] Step 5:

[0834] The server transmits the selected music content data to the user's terminal via a display device. The terminal displays the received content data with an appropriate user interface and plays the music. The input is the music content data, and the output is the music playlist presented to the user.

[0835] 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.

[0836] 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.

[0837] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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."

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] The following is further disclosed regarding the embodiments described above.

[0857] (Claim 1)

[0858] A means of communication for receiving messages from users,

[0859] An analysis means for analyzing the user's request from the aforementioned message,

[0860] A design means for designing an application based on the aforementioned requirements,

[0861] A generation means for automatically generating an application based on the specifications designed by the design means,

[0862] A system including a display means for providing a preview of the aforementioned application to a user.

[0863] (Claim 2)

[0864] A means for obtaining user feedback on the preview of the aforementioned application,

[0865] The system according to claim 1, further comprising a redesign means for modifying and regenerating the application design based on the aforementioned feedback.

[0866] (Claim 3)

[0867] The system according to claim 1, wherein the communication means has the function of encrypting and transmitting and receiving messages.

[0868] "Example 1"

[0869] (Claim 1)

[0870] A communication device that receives requests from users,

[0871] An analysis device that analyzes the aforementioned requirements and extracts the user's objective,

[0872] A design device for designing software based on the aforementioned objective,

[0873] A generation device that automatically generates software based on data designed by the aforementioned design device,

[0874] A display device that presents an overview of the aforementioned software to the user,

[0875] A system including a verification device that verifies the operation of the aforementioned software and optimizes the design content according to user requirements.

[0876] (Claim 2)

[0877] We obtain user feedback on the overview of the aforementioned software,

[0878] The system according to claim 1, further comprising a redesign device for modifying and regenerating the software design based on the aforementioned opinion.

[0879] (Claim 3)

[0880] The system according to claim 1, wherein the communication device has the function of encrypting and transmitting and receiving requests.

[0881] "Application Example 1"

[0882] (Claim 1)

[0883] A means of receiving instructions from the user,

[0884] An analytical means for understanding the user's requirements from the aforementioned instructions,

[0885] A construction means for constructing a computer program based on the aforementioned requirements,

[0886] A creation means for automatically creating a computer program based on the specifications constructed by the aforementioned construction means,

[0887] A system including means for providing a trial version of the aforementioned computer program to a user.

[0888] (Claim 2)

[0889] A means for collecting user feedback on the trial version of the aforementioned computer program,

[0890] The system according to claim 1, comprising a reconstruction means for modifying and regenerating the construction of a computer program based on the aforementioned opinion.

[0891] (Claim 3)

[0892] The system according to claim 1, wherein the transmitting means has the function of encrypting and transmitting and receiving instructions.

[0893] "Example 2 of combining an emotion engine"

[0894] (Claim 1)

[0895] A means of receiving information from the user,

[0896] An extraction means for analyzing user requests and emotions from the aforementioned information,

[0897] A planning means for designing a program based on the aforementioned requirements and emotions,

[0898] A forming means that automatically creates a program based on the specifications determined by the planning means,

[0899] A system including a display means for presenting a prototype of the aforementioned program to a user.

[0900] (Claim 2)

[0901] A means for collecting user feedback on a prototype of the aforementioned program,

[0902] The system according to claim 1, further comprising a revision means for modifying and regenerating the program design based on the aforementioned opinion.

[0903] (Claim 3)

[0904] The system according to claim 1, wherein the receiving means has the function of encrypting and transmitting and receiving information.

[0905] "Application example 2 when combining with an emotional engine"

[0906] (Claim 1)

[0907] A receiving device that receives information via a communication network,

[0908] An analytical device that analyzes the user's emotions from the aforementioned information,

[0909] A selection device that selects content based on the aforementioned emotions,

[0910] A system including a display device that displays the selected content on the user's device.

[0911] (Claim 2)

[0912] The system according to claim 1, comprising a generating device that generates recommended content in response to the user's emotions.

[0913] (Claim 3)

[0914] The system according to claim 1, wherein the receiving device has the function of transmitting and receiving information using a protocol for protecting information. [Explanation of symbols]

[0915] 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 communication for receiving messages from users, An analysis means for analyzing the user's request from the aforementioned message, A design means for designing an application based on the aforementioned requirements, A generation means for automatically generating an application based on the specifications designed by the design means, A system including a display means for providing a preview of the aforementioned application to a user.

2. A means for obtaining user feedback on the preview of the aforementioned application, The system according to claim 1, further comprising a redesign means for modifying and regenerating the application design based on the aforementioned feedback.

3. The system according to claim 1, wherein the communication means has the function of encrypting and transmitting and receiving messages.

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